research articles on farmers

• Reference Manager
• Simple TEXT file

People also looked at

Mini review article, farmers’ perception of climate change: a review of the literature for latin america.

• 1 Tecnologico de Monterrey, School of Social Science and Government, Mexico and Economics Department, Centro de Investigación y Docencia Económicas, Mexico City, Mexico
• 2 Economics Department, Centro de Investigación y Docencia Económicas, Mexico City, Mexico

Global climate is changing rapidly, and it is not clear if agricultural producers in developing countries will be able to adapt fast enough in order to mitigate its negative effects. In order to be willing to take adaptation measures, farmers need to perceive that the climate is changing or could change, and they need to attribute enough weight to this perception to take action. During the last two decades, the literature that examines farmers’ perception of climate change has gained ground, but it is still scant. This is particularly true for Latin America, which is highly vulnerable to climate change. Based on a review of original research articles published between 2000 and 2020, this article presents the status of knowledge about the topic in the region to identify research gaps and inform future research. The review found that the available research has been based mostly on qualitative analyses of case studies for a few countries. More research that identifies causal relationships is necessary. Data from surveys that are representative at the national or subnational levels, as well as longitudinal data, will be very helpful to better understand farmer’s perceptions. Finally, the use of field experiments and choice experiments can complement the use of observational data.

Introduction

Throughout human history, farmers have adapted to changing environmental, social and economic conditions ( Kurukulasuriya and Rosenthal, 2013 ). Nonetheless, it is not clear if agricultural producers will be able to keep up with the unprecedented speed at which climate is expected to change in the coming years ( Jones et al., 2012 ). The negative effects of these changes will be higher for agricultural producers that practice rainfed agriculture, as well as for those with limited access to credit and insurance, and those that are disconnected from regional or national markets ( Skoufias et al., 2011 ; Quiroga et al., 2015 ; IFAD, 2016 ; Castells-Quintana et al., 2018 ). In order to ameliorate these negative effects, public policies and interventions to promote and facilitate adaptation will be needed ( Howden et al., 2007 ; Kumar et al., 2020 ). Nonetheless, in order to be willing to implement adaptation measures, farmers need to be aware of climate change ( Silvestri et al., 2012 ; Simelton et al., 2013 ; Meldrum et al., 2018 ). In that sense, the perception that farmers have about climate change not only informs their planting decisions, but also determines the adoption of adaptation measures ( Meldrum et al., 2018 ; De Matos Carlos et al., 2020 ). Therefore, understanding farmers’ perceptions about climate change can be seen as a condition for the design and successful implementation of adaptation policies in agriculture ( Hansen et al., 2004 ; Silvestri et al., 2012 ; De Matos Carlos et al., 2020 ).

The number of studies that focus on understanding farmers’ climate change perception has been increasing, but it is still scant. This is particularly true for Latin America ( Dang et al., 2019 ; Karki et al., 2020 ), a region highly vulnerable to climate change ( López-Feldman and Hernández Cort ). This phenomenon is expected to have serious negative impacts on the income, consumption and health of agricultural producers in the region ( Reyer et al., 2017 ; IPCC et al., 2018 ), leading to increases in poverty and inequality ( Skoufias et al., 2011 ; Harvey et al., 2018 ; López-Feldman and Mora Rivera, 2018 ). Given this scenario, the lack of research on the determinants of climate change perception is worrisome. The objective of this work is to present an overview of the studies on this topic available for Latin America while identifying research gaps and potential paths for future research.

Climate Change Perception

Climate change perception is a complex process that encompasses a range of psychological constructs such as knowledge, beliefs, attitudes and concerns about if and how the climate is changing ( Whitmarsh and Capstick, 2018 ). Perception is influenced and shaped, among other things, by the individuals’ characteristics, their experience, the information that they receive, and the cultural and geographic context in which they live ( van der Linden, 2015 ; Whitmarsh and Capstick, 2018 ). Therefore, measuring climate change perception and trying to find its determinants is not an easy task.

The variability that local weather can have from one day to the other, from one season to the next, and between years, is one of the many challenges that a person faces when trying to distinguish between normal short-run variations and climate change manifestations ( Hansen et al., 2012 ). In fact, local short-term variations tend to be more salient than long-term trends and hence can have a key impact on the formation of climate change perceptions ( Lehner and Stocker, 2015 ). Although the perception of those that directly depend on the weather for at least part of their income, such as farmers, tend to be more accurate than that of their counterparts, they might still have problems using their own experience with weather variables to correctly interpret changes as being big enough as to feel worried and compelled to do something about it ( Weber, 2010 ; Whitmarsh and Capstick, 2018 ).

Life experiences influence perception, individuals who have been directly affected by extreme climatic events tend to report that the probability of such event happening again is relatively high ( Patt and Schröter, 2008 ; De Matos Carlos et al., 2020 ). Furthermore, the perception that a person has about climate change can be influenced or modified by the information that she receives ( Weber, 2010 ). Finally, it should be noted that perception is in part a subjective phenomenon, therefore, different people in the same locality might construct different perceptions of climate change even though they experience the same weather patterns ( Simelton et al., 2013 ).

The Link Between Perception and Adaptation to Climate Change

In order to protect the livelihoods of the population that directly depends on agriculture, adaptation of the agricultural sector to the adverse effects of climate change is crucial ( Asfaw et al., 2016 ). In a world with perfect information, complete markets, and adequate incentives, the decision to adopt or implement a particular adaptation measure would simply be a matter of evaluating the net benefits of said measure. That is certainly not the setting in which small and subsistence farmers in developing countries operate ( Castells-Quintana et al., 2018 ). Therefore, the adoption of adaptation measures is not an automatic or smooth process, quite the contrary. The evidence has shown that factors like inadequate access to insurance or credit, limited information about adaptation alternatives, and incomplete property rights, constitute barriers that small and subsistence farmers face in relation to technology adoption ( Asfaw et al., 2016 ). Furthermore, the decision to adopt a new technology or production method frequently entails cognitive processes, like mental accounting ( Thaler, 1999 ), loss aversion ( Kahneman and Tversky, 1979 ), and hyperbolic discounting ( Laibson, 1997 ), which can lead to suboptimal levels of adoption ( Zilberman et al., 2012 ). This is particularly relevant for adaptation to climate change, as even farmers with access to weather information and climate forecasts face considerable levels of uncertainty ( Silvestri et al., 2012 ). Under these conditions, the perception that farmers have about climate change is a key component to understanding their adaptation decisions ( Clarke, et al., 2012 ).

Adaptation requires not only that individuals perceive that something is changing or could change, but also that they attribute enough weight to this perception to be willing to take action and try to do something about it ( Eakin et al., 2014 ). In this sense, perceiving that the climate is changing can be seen as a pre-condition for the adoption of agricultural adaptation measures ( Simelton et al., 2013 ; Makuvaro et al., 2018 ). Furthermore, the successful implementation of public policies aimed towards the promotion of adaptation requires, among many other things, the cooperation and participation of the intended beneficiaries. If their perception about the consequences or immediacy of climate change is different from that of the policy makers, then it is likely that the implementation of the policy will fail ( Patt and Schrö ).

Climate Change Perception of Farmers in Latin America

Hansen et al. (2004) were the first to analyze the climate perceptions of farmers in a Latin American country (Argentina). The literature on this topic has slowly grown since then, although it is still scarce compared to that from Africa and South-East Asia ( Altea, 2020 ; Karki et al., 2020 ). Here we briefly summarize some of the main findings of the studies about Latin America published, in either English or Spanish, during the period 2000–2020. The articles’ selection process was based on some of the steps used in systematic reviews, in particular we followed Karki et al. (2020) and Dang et al. (2019) . For our search, we used the following combinations of keywords or closely related words: climate change (climate, climate variability, global warming, temperature, rainfall), extreme weather events (droughts, hurricanes, tropical storms), perception (understanding), Latin America (Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominican Republic, Ecuador, El Salvador, Guatemala, Haiti, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Uruguay, Venezuela, North America, Central America, South America), family farms (farms, small producers, farmers, subsistence farms, household, communities, villages), indigenous (indigeneity) . In our search, in addition to Science Direct and Web of Science , we also used Google Scholar. It has been shown that Google Scholar has a very good coverage in areas where Web of Science does not ( Martín-Martín, et al., 2018 ), therefore, by using these three databases we have a comprehensive coverage of the literature. The title and abstract of 112 published papers that resulted from the search were analyzed to check if at least one of the objectives of the paper was to empirically analyze the climate change perceptions of farmers in a Latin American country; if that was the case, the paper was included in the revision. We focused on research published in peer-reviewed journals, the only exception was ( Hansen et al., 2004 ) which was published as a technical report and was the first study to analyze the topic in a Latin American country. At the end of this procedure, 21 scientific articles met the pre-established criteria.

As Table 1 shows, the existing studies come from a limited number of countries in the region; Mexico being the country with the highest number of studies available with five. Case based analysis was conducted for most, allowing for a more in depth understanding of local actors and weather ( Funatsu et al., 2019 ), while excluding generalizations at greater scales. Only two studies ( Eakin et al., 2014 ; Leroy 2019 ), covered more than one Latin American country. The studies are based on small samples; the average sample size of the papers included in Table 1 is 240, with a range of 23–1,267 observations. Most of the studies are qualitative, only three use an econometric approach as part of the analysis. Latin America’s diversity in terms of ecosystems, climate, and agricultural production systems is reflected in the studies. The papers in Table 1 analyze farmers in settings that go from semiarid environments to high mountain ecosystems, intertropical alpine ecosystems ( páramos ), and tropical forests, and, although the majority of them are of subsistence farmers, there are also studies that look at small commercial farmers, such as winegrowers. Coffee is the crop that farmers were planting in most of the studies, followed by maize, banana, cacao, potatoes, sugar cane, beans, tomatoes, and cocoa.

TABLE 1 . Basic information for studies regarding climate change perception in Latin America.

The papers reviewed look at the perception that farmers have about changes in, among other climate and weather-related variables, temperature, precipitation, and droughts. Results show that most of the farmers have in fact perceived changes in these variables. A common approach used in many of the studies is to compare farmers perceptions with the actual measured variations in the respective variables. In this way, in addition to testing if farmers perceive changes in climate-related variables, it is also possible to test if farmers perceptions coincide with actual changes. The reported results are mixed, in some cases there is a clear correspondence between changes reported by farmers and actual changes ( Pinilla et al., 2012 ; Roco et al., 2015 ; Fourment et al., 2020 ), while in other contexts, farmers’ perceptions are less aligned with observed changes ( Valdivia et al., 2010 ; Gurgiser et at., 2016; Funatsu et al., 2019 ). However, even in those cases where farmers disagree in the direction in which weather variables are changing (e.g., more or less precipitation), they tend to agree in reporting that there is more variability and in mentioning that a less reliable and more unpredictable weather complicates their farming related decisions ( Eakin et al., 2014 ; Meli et al., 2015 ; López-García and Manzano, 2016 ). Nonetheless, in some cases even when farmers perceive climate variability, they do not attribute it to climate change as they see it as a future and long-term issue ( Fourment et al., 2020 ).

Even though the focus of this review was not farmers’ adoption of adaptation practices, the articles that do look at adoption show that, in general, farmers try to adapt to the changing environmental circumstances that they are facing ( Eakin et al., 2014 ; Jacobi et al., 2015 ; Gurgiser et al., 2016 ; Meldrum et al., 2018 ; De Matos Carlos et al., 2020 ). Particularly relevant for the focus of this review is the result reported by De Matos Carlos et al. (2020) showing that there is a positive correlation between the adoption of adaptation practices and perceiving a change in climate.

The literature for Africa and Asia has shown that factors such as age, gender, education, and culture, play an important role in the processes that determine farmers’ perception of climate change ( Karki et al., 2020 ). This seems to be the case in Latin America as well. Results for Chile show that younger and more educated household heads tend to have a perception of climate change that is more aligned with the observed changes in weather variables than the perception of their older and less educated counterparts ( Roco et al., 2015 ). Nonetheless, there is also evidence showing that, in other contexts, farmers might have similar perceptions of climate change irrespective of their age; that is the case for Southern Mexico ( Meli et al., 2015 ). Meanwhile, results for Brazil ( Funatsu et al., 2019 ), Peru ( Altea, 2020 ), and Mexico (Sánchez-Cortés and Lazos, 2011; Orduño et al., 2019 ) show that women are less involved than men in agricultural activities and in general in decision making. Furthermore, they tend to be less perceptive of climate change, and, at least according to the evidence for Brazil and Peru, when they perceive it, they do not think of it as an anthropogenic phenomenon. Similarly, some indigenous farmers in Bolivia see climate change as a punishment of God to inappropriate human behavior ( Boillat and Berkes, 2013 ). Results from an analysis of indigenous farmers in Mexico, show another relevant cultural aspect behind climate change perception; the Zoques in Chiapas use biological indicators (e.g., ants, birds and some plants), in addition to their observation of weather variables, to explain perceived changes in climate variability (Sánchez-Cortés and Lazos, 2011).

In addition to the aforementioned characteristics, agroclimatic conditions can also play a relevant role as a determinant of climate change perception ( Karki et al., 2020 ). In Chile, for example, farmers living in dryland areas, where rainfall is always marginal, seem to be more aware of climate change than those located in places where irrigation infrastructure is widely available ( Roco et al., 2015 ). Something similar, although less conclusive, is reported for Ecuador ( VanderMolen, 2011 ). Altea (2020) presents evidence suggesting that in Peru perception of climate change varies with the altitude in which the agricultural land is located. Meanwhile, in the case of Brazil, although droughts affect farmers located in the tropical rainforest as well as those living in shrubland areas (characterized by low and irregular levels of precipitation), rainforest farmers seem to be less aware of the effects of climate change ( De Matos Carlos et al., 2020 ). Farmers’ location can be related to perception for another reason: access to meteorological information. This seems to be the case of Chilean farmers, those located close to the regional capital are more aware of the actual changes in weather ( Roco et al., 2015 ). Finally, perception could be affected by recent experience with climate events. Barrucand et al. (2017) report that the perception of changes in precipitation could be biased upwards when farmers have been recently affected by a weather phenomenon; La Niña occurred a few months before farmers participating in their case study were interviewed.

Discussion, Research Gaps and Opportunities for Future Research

The “finite pool of worry” hypothesis proposes that climate change concern is a finite resource, that is, it diminishes as other worries rise in prominence ( Weber, 2006 ; Weber, 2015 ). Other than the work from Hansen et al. (2004) , this is something that has not been carefully studied for Latin American farmers. Understanding how the presence of more immediate threats (e.g., violence) might hinder concern, and therefore action, about the implications of climate change is crucial in a region with high levels of poverty, inequality and social unrest. In particular, it has been shown that exposure to violence can induce higher levels of risk aversion, which in turn hampers productive investments ( Moya, 2018 ). Given the relatively high levels of violence experienced by rural populations in many Latin American countries, understanding the effects that exposure to violence can have on climate change perceptions, as well as on adaptation decisions, is crucial for the successful adaptation of farmers in the region.

The studies available for Latin America are mostly qualitative in nature and based on case studies and small samples. While these studies provide abundant information in terms of the local context, it is desirable to complement them with quantitative studies, in particular with econometric studies. Econometric studies have the potential to identify the main factors behind climate change perceptions as well as the relationship between perception and adaptation. Furthermore, given the adequate data and the correct identification strategy, econometric tools can help establish causal relationships. Moreover, data from surveys that are representative at the national or sub-national levels are necessary to obtain results that can be generalized and used to scale-up adaptation policies and programs. Ideally, these data should be longitudinal in order to better understand how information and the occurrence of extreme climatic events affect perception and adaptation over time. The national statistical offices of all Latin American countries should regularly collect information on perception of climate change and adoption of adaptation mechanisms.

The use of field experiments and choice experiments is an alternative approach which can complement the use of observational data. These tools are used widely in behavioral, environmental and experimental economics, among other disciplines. The use of hypothetical scenarios, a characteristic of these two methods, allows for the construction of mental simulations of the negative effects of climate change. By being based on hypothetical scenarios, these methods have an important advantage over observational studies: they can be used to analyze policies before they are actually implemented. These methods could also be useful to test how successful different policies might be in terms of promoting adoption of adaptation measures. Furthermore, they can help us analyze the effect that different approaches to communicate climate change information has on perception. The issue of the perception of climate change in a context where concern is in fact a finite resource could also be analyzed using these methods. Applying field and choice experiments to study perception and adaptation to climate change in Latin America is a very promising agenda from a purely academic perspective, but, more importantly, it could be very relevant in terms of providing valuable information that could aid in the design and successful implementation of public policies.

The complexity behind the analysis of farmers’ climate change perception implies that the collaboration between researchers from different disciplines, such as economics, geography, meteorology, psychology, and sociology, among others, is almost a necessity. If such collaboration is successfully achieved, the results could generate recommendations for the design of adaptation policies that are better tailored to local conditions, less costly, more efficient, and conducive to rural development.

Author Contributions

All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.

The Postdoctoral Fellowships Program of CONACYT and the Centro de Investigación y Docencia Económicas provided support for IF during the development of the present investigation.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Altea, L. (2020). Perceptions of Climate Change and its Impacts: a Comparison between Farmers and Institutions in the Amazonas Region of Peru. Clim. Development 12 (2), 134–146. doi:10.1080/17565529.2019.1605285

CrossRef Full Text | Google Scholar

Asfaw, S., McCarthy, N., Lipper, L., Arslan, A., and Cattaneo, A. (2016). What Determines Farmers' Adaptive Capacity? Empirical Evidence from Malawi. Food Sec. 8 (3), 643–664. doi:10.1007/s12571-016-0571-0

Barrucand, M. G., Giraldo Vieira, C., and Canziani, P. O. (2017). Climate Change and its Impacts: Perception and Adaptation in Rural Areas of Manizales, Colombia. Clim. Development 9 (5), 415–427. doi:10.1080/17565529.2016.1167661

Boillat, S., and Berkes, F. (2013). Perception and Interpretation of Climate Change Among Quechua Farmers of Bolivia: Indigenous Knowledge as a Resource for Adaptive Capacity. Ecol. Soc. 18 (4), 21. doi:10.5751/es-05894-180421

Castells-Quintana, D., Lopez-Uribe, M. D. P., and McDermott, T. K. J. (2018). Adaptation to Climate Change: A Review through a Development Economics Lens. World Development 104, 183–196. doi:10.1016/j.worlddev.2017.11.016

Clarke, C., Shackleton, S., and Powell, M. (2012). Climate Change Perceptions, Drought Responses and Views on Carbon Farming Amongst Commercial Livestock and Game Farmers in the Semiarid Great Fish River Valley, Eastern Cape Province, South Africa. Afr. J. Range Forage Sci. 29 (1), 13–23. doi:10.2989/10220119.2012.687041

Dang, H. L., Li, E., Nuberg, I., and Bruwer, J. (2019). Factors Influencing the Adaptation of Farmers in Response to Climate Change: a Review. Clim. Development 11 (9), 765–774. doi:10.1080/17565529.2018.1562866

De Matos Carlos, S., da Cunha, D. A., Pires, M. V., and Do Couto-Santos, F. R. (2020). Understanding farmers' perceptions and adaptation to climate change: the case of Rio das Contas basin, Brazil. GeoJournal 85, 805–821. doi:10.1007/s10708-019-09993-1

Eakin, H., Tucker, C. M., Castellanos, E., Diaz-Porras, R., Barrera, J. F., and Morales, H. (2014). Adaptation in a Multi-Stressor Environment: Perceptions and Responses to Climatic and Economic Risks by Coffee Growers in Mesoamerica. Environ. Dev. Sustain. 16, 123–139. doi:10.1007/s10668-013-9466-9

Fourment, M., Ferrer, M., Barbeau, G., and Quénol, H. (2020). Local Perceptions, Vulnerability and Adaptive Responses to Climate Change and Variability in a Winegrowing Region in Uruguay. Environ. Manage. 66 (4), 590–599. doi:10.1007/s00267-020-01330-4

PubMed Abstract | CrossRef Full Text | Google Scholar

Funatsu, B. M., Dubreuil, V., Racapé, A., Debortoli, N. S., Nasuti, S., and Le Tourneau, F.-M. (2019). Perceptions of Climate and Climate Change by Amazonian Communities. Glob. Environ. Change 57, 101923. doi:10.1016/j.gloenvcha.2019.05.007

Gurgiser, W., Juen, I., Singer, K., Neuburger, M., Schauwecker, S., Hofer, M., et al. (2016). Comparing peasants' perceptions of precipitation change with precipitation records in the tropical Callejón de Huaylas, Peru. Earth Syst. Dynam. 7 (2), 499–515. doi:10.5194/esd-7-499-2016

Hansen, J., Marx, S., and Weber, E. (2004). The Role of Climate Perceptions, Expectations, and Forecasts in Farmer Decision Making: The Argentine Pampas and South Florida . NY, U.S.A: Palisades . Technical report 04-01. doi:10.2172/833414

CrossRef Full Text

Hansen, J., Sato, M., and Ruedy, R. (2012). Perception of Climate Change. Proc. Natl. Acad. Sci. 109 (37), E2415–E2423. doi:10.1073/pnas.1205276109

Harvey, C. A., Saborio-Rodríguez, M., Martinez-Rodríguez, M. R., Viguera, B., Chain-Guadarrama, A., Vignola, R., et al. (2018). Climate Change Impacts and Adaptation Among Smallholder Farmers in Central America. Agric. Food Secur 7 (1), 57. doi:10.1186/s40066-018-0209-x

Howden, S. M., Soussana, J.-F., Tubiello, F. N., Chhetri, N., Dunlop, M., and Meinke, H. (2007). Adapting Agriculture to Climate Change. Proc. Natl. Acad. Sci. 104 (50), 19691–19696. doi:10.1073/pnas.0701890104

International Fund for Agricultural Development (IFAD) (2016). Rural Development Report 2016: Fostering Inclusive Rural Transformation . Rome: International Fund for Agricultural Development .

Jacobi, J., Schneider, M., Bottazzi, P., Pillco, M., Calizaya, P., and Rist, S. (2015). Agroecosystem Resilience and Farmers' Perceptions of Climate Change Impacts on cocoa Farms in Alto Beni, Bolivia. Renew. Agric. Food Syst. 30 (2), 170–183. doi:10.1017/s174217051300029x

Jones, H. P., Hole, D. G., and Zavaleta, E. S. (2012). Harnessing Nature to Help People Adapt to Climate Change. Nat. Clim Change 2 (7), 504–509. doi:10.1038/nclimate1463

Kahneman, D., and Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica 47 (2), 263–291. doi:10.2307/1914185

Karki, S., Burton, P., and Mackey, B. (2020). The Experiences and Perceptions of Farmers about the Impacts of Climate Change and Variability on Crop Production: a Review. Clim. Development 12 (1), 80–95. doi:10.1080/17565529.2019.1603096

Kumar, S., Mishra, A. K., Pramanik, S., Mamidanna, S., and Whitbread, A. (2020). Climate Risk, Vulnerability and Resilience: Supporting Livelihood of Smallholders in Semiarid India. Land Use Policy 97, 104729. doi:10.1016/j.landusepol.2020.104729

Kurukulasuriya, P., and Rosenthal, S. (2013). Climate Change and Agriculture: A Review of Impacts and Adaptations . Washington, DC: World Bank . Environment department papers no. 91 (Climate change series.

Laibson, D. (1997). Golden Eggs and Hyperbolic Discounting. Q. J. Econ. 112 (2), 443–478. doi:10.1162/003355397555253

Lehner, F., and Stocker, T. F. (2015). From Local Perception to Global Perspective. Nat. Clim Change 5, 731–734. doi:10.1038/nclimate2660

Leroy, D. (2019). Farmers' Perceptions of and Adaptations to Water Scarcity in Colombian and Venezuelan Páramos in the Context of Climate Change. Mountain Res. Development 39 (2), R21–R34. doi:10.1659/MRD-JOURNAL-D-18-00062.1

López-Feldman, A., and Mora Rivera, J. J. (2018). “The Effects of Climate Change on Poverty and Income Distribution: A Case Study for Rural Mexico,” in Economic Tools and Methods for the Analysis of Global Change Impacts on Agriculture and Food Security . Editor S. Quiroga (Cham: Springer ).

Google Scholar

López Feldman, A. J., and Hernández Cortés, D. (2016). Cambio climático y agricultura: una revisión de la literatura con énfasis en América Latina. El Trimestre 83 (332), 459–496. doi:10.20430/ete.v83i332.231

López-García, T. G., and Manzano, M. G. (2016). Vulnerabilidad climática y situación socioambiental: percepciones en una región semiárida del noreste de México. Myb 22 (2), 105–117. doi:10.21829/myb.2016.2221328

Makuvaro, V., Walker, S., Masere, T. P., and Dimes, J. (2018). Smallholder Farmer Perceived Effects of Climate Change on Agricultural Productivity and Adaptation Strategies. J. Arid Environments 152, 75–82. doi:10.1016/j.jaridenv.2018.01.016

Martín-Martín, A., Orduna-Malea, E., Thelwall, M., and Delgado López-Cózar, E. (2018). Google Scholar, Web of Science, and Scopus: A Systematic Comparison of Citations in 252 Subject Categories. J. informetrics 12 (4), 1160–1177. doi:10.1016/j.joi.2018.09.002

Meldrum, G., Mijatović, D., Rojas, W., Flores, J., Pinto, M., Mamani, G., et al. (2018). Climate Change and Crop Diversity: Farmers' Perceptions and Adaptation on the Bolivian Altiplano. Environ. Dev. Sustain. 20, 703–730. doi:10.1007/s10668-016-9906-4

Meli, P., Landa, R., López-Medellín, X., and Carabias, J. (2015). Social Perceptions of Rainforest and Climatic Change from Rural Communities in Southern Mexico. Ecosystems 18, 1343–1355. doi:10.1007/s10021-015-9903-8

Moya, A. (2018). Violence, Psychological Trauma, and Risk Attitudes: Evidence from Victims of Violence in Colombia. J. Development Econ. 131, 15–27. doi:10.1016/j.jdeveco.2017.11.001

Orduño, M., Kallas, Z., and Ornelas, H., S. (2019). Analysis of Farmers’ Stated Risk Using Lotteries and Their Perceptions of Climate Change in the Northwest of Mexico. Agronomy 9 (1), 4. doi:10.3390/agronomy9010004

Patt, A., and Schröter, D. (2008). Perceptions of Climate Risk in Mozambique: Implications for the success of Adaptation Strategies. Glob. Environ. Change 18 (3), 458–467. doi:10.1016/j.gloenvcha.2008.04.002

Pinilla, M. C. H., Rueda, A., and Pinzón, C. (2012). Percepciones sobre los fenómenos de variabilidad y cambio climáticos entre campesinos del centro de Santander, Colombia. Ambiente y Desarrollo 16 (31), 25–37.

Quiroga, S., Suárez, C., and Solís, J. D. (2015). Exploring Coffee Farmers' Awareness about Climate Change and Water Needs: Smallholders' Perceptions of Adaptive Capacity. Environ. Sci. Pol. 45, 53–66. doi:10.1016/j.envsci.2014.09.007

Reyer, C. P. O., Adams, S., Albrecht, T., Baarsch, F., Boit, A., Canales Trujillo, N., et al. (2017). Climate Change Impacts in Latin America and the Caribbean and Their Implications for Development. Reg. Environ. Change 17, 1601–1621. doi:10.1007/s10113-015-0854-6

Roco, L., Engler, A., Bravo-Ureta, B. E., and Jara-Rojas, R. (2015). Farmers' Perception of Climate Change in Mediterranean Chile. Reg. Environ. Change 15 (5), 867–879. doi:10.1007/s10113-014-0669-x

Sánchez-Cortés, M. S., and Lazos, C. E (2011). Indigenous Perception of Changes in Climate Variability and its Relationship with Agriculture in a Zoque Community of Chiapas, Mexico. Climatic Change 107 (3-4), 363–389. doi:10.1007/s10584-010-9972-9

Silvestri, S., Bryan, E., Ringler, C., Herrero, M., and Okoba, B. (2012). Climate Change Perception and Adaptation of Agro-Pastoral Communities in Kenya. Reg. Environ. Change 12 (4), 791–802. doi:10.1007/s10113-012-0293-6

Simelton, E., Quinn, C. H., Batisani, N., Dougill, A. J., Dyer, J. C., Fraser, E. D. G., et al. (2013). Is Rainfall Really Changing? Farmers' Perceptions, Meteorological Data, and Policy Implications. Clim. Development 5, 123–138. doi:10.1080/17565529.2012.751893

Skoufias, E., Rabassa, M., and Olivieri, S. (2011). The Poverty Impacts of Climate Change: A Review of the Evidence . in Policy Research Working Paper . Washington, DC: World Bank . no. WPS 5622. doi:10.1596/1813-9450-5622

Thaler, R. H. (1999). Mental Accounting Matters. J. Behav. Decis. Making 12 (3), 183–206. doi:10.1002/(sici)1099-0771(199909)12:3<183::aid-bdm318>3.0.co;2-f

IPCC (2018). “Summary for Policymakers,” in Global Warming of 1.5°C. An IPCC Special Report on the Impacts of Global Warming of 1.5°C above Pre-industrial Levels and Related Global Greenhouse Gas Emission Pathways, in the Context of Strengthening the Global Response to the Threat of Climate Change, Sustainable Development, and Efforts to Eradicate Poverty in Press . Editors V. Masson-Delmotte, P. Zhai, H-O. Pörtner, D. Roberts, J. Skea, P. R. Shuklaet al.

Valdivia, C., Seth, A., Gilles, J. L., García, M., Jiménez, E., Cusicanqui, J., et al. (2010). Adapting to Climate Change in Andean Ecosystems: Landscapes, Capitals, and Perceptions Shaping Rural Livelihood Strategies and Linking Knowledge Systems. Ann. Assoc. Am. Geogr. 100 (4), 818–834. doi:10.1080/00045608.2010.500198

Van der Linden, S. (2015). The Social-Psychological Determinants of Climate Change Risk Perceptions: Towards a Comprehensive Model. J. Environ. Psychol. 41, 112–124. doi:10.1016/j.jenvp.2014.11.012

VanderMolen, K. (2011). Percepciones de cambio climático y estrategias de adaptación en las comunidades agrícolas de Cotacachi (Debate Agrario-Rural). Ecuador Debate 82, 145–157.

Weber, E. U. (2015). Climate Change Demands Behavioral Change: What Are the Challenges? Soc. Res. 82 (3), 561–580. Availableat: https://www.jstor.org/stable/44282122 .

Weber, E. U. (2006). Experience-based and Description-Based Perceptions of Long-Term Risk: Why Global Warming Does Not Scare Us (Yet). Climatic Change 77 (1), 103–120. doi:10.1007/s10584-006-9060-3

Weber, E. U. (2010). What Shapes Perceptions of Climate Change? Wires Clim. Change 1 (3), 332–342. doi:10.1002/wcc.41

Whitmarsh, L., and Capstick, S. (2018). “Perceptions of Climate Change,” in Psychology and Climate Change: Human Perceptions, Impacts, and Responses . Editors S. Clayton, and C. Manning ( Academic Press ), 13–33. doi:10.1016/B978-0-12-813130-5.00002-3

Zilberman, D., Zhao, J., and Heiman, A. (2012). Adoption versus Adaptation, with Emphasis on Climate Change. Annu. Rev. Resour. Econ. 4 (1), 27–53. doi:10.1146/annurev-resource-083110-115954

Keywords: perception, climate change, adaptation, Latin America, farmer, agriculture

Citation: Fierros-González I and López-Feldman A (2021) Farmers’ Perception of Climate Change: A Review of the Literature for Latin America. Front. Environ. Sci. 9:672399. doi: 10.3389/fenvs.2021.672399

Received: 26 February 2021; Accepted: 26 May 2021; Published: 07 June 2021.

Reviewed by:

Copyright © 2021 Fierros-González and López-Feldman. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Alejandro López-Feldman, [email protected]

This article is part of the Research Topic

Climate Change and Society

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here .

Loading metrics

Open Access

Peer-reviewed

Research Article

Research trends in farmers’ mental health: A scoping review of mental health outcomes and interventions among farming populations worldwide

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, Ontario, Canada

Contributed equally to this work with: Ashley Albright, Jan Sargeant, Charlotte B. Winder, Andria Jones-Bitton

Roles Data curation, Formal analysis, Methodology, Writing – original draft

Roles Methodology, Writing – original draft, Writing – review & editing

Affiliations Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, Ontario, Canada, Centre for Public Health and Zoonoses, University of Guelph, Guelph, Ontario, Canada

Roles Data curation, Formal analysis, Methodology, Validation, Writing – review & editing

Roles Writing – original draft, Writing – review & editing

¶ ‡ These authors also contributed equally to this work.

Affiliations Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, Ontario, Canada, School of Public Health, University of Alberta, Edmonton, Alberta, Canada

Roles Conceptualization, Methodology, Supervision, Writing – original draft, Writing – review & editing

• Briana N. M. Hagen, 
• Ashley Albright, 
• Jan Sargeant, 
• Charlotte B. Winder, 
• Sherilee L. Harper, 
• Terri L. O’Sullivan, 
• Andria Jones-Bitton

• Published: December 5, 2019
• https://doi.org/10.1371/journal.pone.0225661
• Reader Comments

Mental health issues among farmers are identified population health concerns. While one systematic review focused on suicide in farming populations in the United States, there have been no scoping studies examining mental health in farming communities worldwide. The objectives of this scoping review were to: provide a descriptive analysis of the literature pertaining to mental health outcomes in farming populations; describe the international scope of the research; and highlight published mental health services and interventions that have been evaluated.

Following Arksey and O’Malley’s scoping review framework, five major health and science platforms were used to identify studies examining mental health outcomes in farming populations, worldwide. Studies that met a priori inclusion criteria that were published prior to December 31, 2017 were included in this review. Data synthesis and descriptive statistics were conducted using STATA 15® software; proportions were calculated by country.

The initial literature search yielded 9,906 records. After title and abstract screening, 676 articles were reviewed in-full. Of these, 341 met a priori inclusion criteria. Studies included were conducted between 1979 and 2017; the majority (265; 77.7%) were published between 2002–2017. The most frequently measured outcomes were stress (41.9%), suicide (33.1%), and depression (32.6%). Over 70% of studies that examined stress described using quantitative research methods, most predominantly, cross-sectional designs (42.7%). Approximately 64% of studies that measured suicide reported using a quantitative approach; the largest proportion of included suicide studies (33.6%) described using cohort designs. Approximately 84% of studies that measured depression described using quantitative approaches; sixty percent of these studies reported using a cross-sectional study design. Twenty included studies described a mental health service or intervention (5.9%).

Conclusions

This scoping review provides a critical overview of the literature examining mental health outcomes in farming populations worldwide. Given the importance of farming and agriculture, this review can be used to ensure future research complements existing work, avoids unnecessary overlap, and begins to tackle the less-studied mental health outcomes amongst farmers. These results can guide researchers to identified gaps in research and services, leading to a more informed approach to future work, and ultimately, a more comprehensive understanding of mental health among farmers worldwide.

Citation: Hagen BNM, Albright A, Sargeant J, Winder CB, Harper SL, O’Sullivan TL, et al. (2019) Research trends in farmers’ mental health: A scoping review of mental health outcomes and interventions among farming populations worldwide. PLoS ONE 14(12): e0225661. https://doi.org/10.1371/journal.pone.0225661

Editor: Stefano Triberti, University of Milan, ITALY

Received: June 10, 2019; Accepted: November 8, 2019; Published: December 5, 2019

Copyright: © 2019 Hagen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the article and its Supporting Information files.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Farmer mental health can have impacts on individual health [ 1 – 3 ], family life [ 4 ], [ 5 ], farm productivity [ 6 ], and animal health and welfare [ 7 ]. Considering that approximately one-third of individuals that contribute to the global economy through their employment do so through the agricultural industry [ 8 ], poor mental health could therefore have considerable negative impact on economic productivity, animal health, and human health worldwide. Hence, ensuring the mental health of farmers and farmworkers may be essential for global health.

It is estimated that 1 in 4 people worldwide experience issues with their mental health annually [ 9 ]. If farmers experience problems with their mental health at the same rates as the general population, this would mean that approximately 25% of farmers worldwide are struggling with their mental health every year. Globally, there are more than 570 million farms, of which approximately 550 million are family-run [ 8 ]. With a conservative estimate of 2-member families, this would mean that every year, roughly 225 million farmers worldwide may struggle with their mental health. This number is likely an underestimate when considering the evidence that farmers experience mental illness at a higher rate than the general population [ 10 ], coupled with the fact that farmworkers and other farm helpers are not included within that conservative estimate.

One recent systematic review conducted by Klingleschmidt and colleagues (2017) reported that male farmers in the United States of America (US) experience an increased risk of suicide (pooled effect size = 1.48; 95% CI: 1.30–1.68) compared to the general population [ 11 ]. Additionally, it is well established through psychological autopsy studies conducted in the US and Europe that over 90% of people who died by suicide had experienced issues with their mental health [ 12 ]. It is essential that mental illness and associated risk factors be assessed in farming populations. Highlighting which mental health outcomes and associated risk factors have previously been studied and, more specifically, how they are studied among farming populations, can inform future research and mental health intervention planning. To date, there is no comprehensive review of mental health outcomes among farming populations worldwide or any that explore mental health interventions for farming populations.

Across the globe, farmers, community groups, mental health experts, and governmental agencies have called for making farmer mental health a research and policy priority [ 8 ]. While there are a multitude of individual studies examining mental health outcomes in farming populations across the world, there are no methodological guidelines for measuring individual mental health outcomes in these populations. Such guidelines could help researchers compare findings across countries and build on previous work more efficiently.

In order to determine the breadth of the existing research and identify current gaps in knowledge, we conducted a scoping review of the literature. Scoping reviews map the existing literature, especially in areas that are rapidly evolving [ 13 ], such as farmer mental health. The objectives of the scoping review were to: (a) provide a descriptive analysis of the literature pertaining to mental health outcomes in farming populations; (b) describe the international scope of the research; and (c) highlight the mental health services and interventions that have been evaluated in the literature to help identify successes and limitations for implementing services in farming populations.

Following the guidelines set out by Arksey and O’Malley (2005) and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for scoping reviews (PRISMA-ScR) guidelines [ 14 ], this scoping review was designed with an analytical framework that maps the available literature, describing the study types and outcomes assessed.

Protocol and registration

Prior to conducting the search, we developed our review question, eligibility criteria, screening questions, and data extraction tool ( S1 Appendix ). There was no formal registration of a study protocol with the international systematic review database (PROSPERO).

Eligibility criteria

• The study population explicitly included farmers or agricultural workers (from any farming commodity)
• The full text of the research article was accessible in English
• The article was a primary study, a review, or governmental report
• If a primary study, studies that used primary data collection (i.e. the authors collected the data themselves in order to answer their research question) or secondary data analysis (i.e. the authors did not collect the data themselves but used an existing dataset or census data)
• The outcome(s) investigated were mental health outcome(s). This could include negative (e.g. depression, anxiety) or positive (e.g. resilience) mental health outcomes.

Information sources and electronic search

Databases searched were: Agricola (via ProQuest, 1970 to current), CABI (via CAB Direct, 1973 to current), PubMed (via NCBI, 1950 to current), Science Citation Index Expanded (via Web of Science, 1900 to current), Social Sciences Citation Index (via Web of Science, 1900 to current), Arts & Humanities Citation Index (via Web of Science, 1975 to current), Conference Proceedings Citation Index-Science (via Web of Science, 1990 to current), Conference Proceedings Citation Index–Social Science & Humanities (via Web of Science, 1990 to current), Emerging Sources Citation Index (via Web of Science, 2015 to current), Medline (via Ovid, 1950 to current), and PsycINFO. These platforms were chosen based on the breadth of their journal libraries in the databases and use in mental health scoping reviews in other populations [ 15 – 19 ].

The search strategy was developed in consultation with a library scientist at the University of Guelph to include the following concepts: mental health outcomes or mental wellness, and farming populations. The full search string is available in Table 1 . We chose to use the terms “clinical depression” and “depressive symptom” to capture studies measuring depression, as the term “depression” was considered too broad. To verify these terms were adequately sensitive, key studies were pre-selected by the primary author to ensure they were captured in the search. Additionally, studies examining positive mental health outcomes typically have the term “resilience” nested within the concept of “mental wellbeing”. When resilience was tested as an additional search term, no additional relevant records were identified; therefore, this term was removed for parsimony. One author (AA) executed the initial search strategy and a second author (BH) replicated the search. There were no timeline restrictions. The initial search was conducted in July 2017 and a second search was conducted using the same methodology in April 2018 to capture studies published in press or online before December 31, 2017.

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

https://doi.org/10.1371/journal.pone.0225661.t001

An a priori decision was made to examine reference lists for all review articles after full-text screening to identify any potentially relevant articles not found in the electronic search. These records were then screened at the title and abstract phase for inclusion.

Study selection

• Does the study examine a mental health outcome as a primary outcome of interest?
• Does the study examine a farming population?
• Is the study available in English?

For each question, answers could have been “yes”, “no”, or “unclear”. Citations were excluded if the reviewers answered “no” to any of the screening questions. Any discrepancies in selection were discussed to achieve consensus. If consensus could not be reached, a third reviewer was used. Articles with ambiguous abstracts or abstracts that were not available online were deemed as eligible in this title and abstract phase and were evaluated using the full text.

After title and abstract screening, eligible full-text articles were imported into DistillerSR™. Full texts of all articles were retrieved through online databases or through the Rapid Access to Collections by Electronic Requesting (RACER). RACER includes all databases from all libraries that are members of the Ontario Council of University Libraries. Articles were excluded if they were inaccessible online or through RACER, or were academic theses or books.

Data charting process

Four authors (BH, AA, JS, AJB) developed a comprehensive data extraction form, which was pre-tested by two authors (BH, AA) on ten articles to ensure consistency in form completion. The data extraction was completed in DistillerSR TM by the same two authors for each article that met the inclusion criteria; any conflicts were discussed to achieve consensus ( S1 Appendix ).

Data of interest in this review included: the country of study; year of publication; the mental health outcome(s) measured; farming population studied (farm level and individual level); the methodological approach to the data (qualitative, quantitative, mixed methods, or review); whether the study used primary or secondary data or was a review article; and the specific study design.

Study demographics.

Farming populations of interest included: animal farmers (swine, beef, dairy, small ruminants (meat or dairy), poultry, aquaculture, or other); plant farmers (crops and/or horticulture); migrant farm workers; permanent farm workers; farm families; not specified; or other. These items were collected as a list, where more than one data item could be selected. Where the study examined a farming population that was not an option on the data extraction form, there was an open-text box where the commodity was entered manually ( S1 Appendix ). We defined migrant and permanent farmworkers as farmworkers who left their country of origin to find agricultural employment (seasonally and permanently, respectively). Further, individual level populations of interest were identified through the “other” text-box variable, and included female farmers, male farmers, older farmers, farm managers, and farm owners.

Study characteristics.

Observational studies were categorized as descriptive, hypothesis testing, or both. Descriptive studies were reported as studies that estimated the prevalence of a mental health outcome, evaluated attitudes towards mental health outcomes, or both. Hypothesis testing studies were reported as studies that evaluated an intervention, investigated risk factors, or evaluated a diagnostic criterion. Qualitative study designs were reported as phenomenology, grounded theory, ethnographic, case study, biography, or other.

Mental health services and interventions.

Interventions reported could include behaviour modification, health measures, efficacy, or other. Additional data extracted for these studies included funding information, whether the service was informational or interventional, who developed the service, who delivered the service, how the service was delivered, how the service was/is funded, and whether the service has been formally evaluated in the literature. Given the limited number of intervention studies found, in addition to the formal data extraction approach taken with the mental health outcomes, we reported a more in-depth description of the mental health services and interventions. This in-depth review was conducted by the primary author.

Synthesis of results

Data synthesis and descriptive statistics (proportions) were conducted using STATA 15® data software; proportions were calculated by mental health outcome.

Studies included

The initial search conducted in July 2017 yielded a total of 9906 articles: 430 identified in Agricola, 2374 in CAB Direct, 2797 in Pubmed, 1516 in Web of Science, 494 in PsycINFO, and 2295 in Medline. Title and abstract screening resulted in 676 articles eligible for full review; of these, 341 articles were included in the data extraction ( Fig 1 ).

https://doi.org/10.1371/journal.pone.0225661.g001

Overview of the data–study context

Studies were published between 1979–2017 ( Fig 2 ). A large proportion of the literature was published since the year 2000 (80.9%), and 48.1% had been published between 2010 and 2017.

Twenty-seven countries were represented in the literature ( Fig 3 ). As shown in Table 2 , the largest proportion of studies were conducted in the United States (34.6%), followed by Australia (18.8%), India (12.6%), and the United Kingdom (7.3%).

https://doi.org/10.1371/journal.pone.0225661.g002

https://doi.org/10.1371/journal.pone.0225661.g003

https://doi.org/10.1371/journal.pone.0225661.t002

Outcomes of interest

Overall, 75.1% of the studies collected primary data to examine mental health outcome(s), while 18.5% used secondary data sources, such as data collected through census surveys or vital statistics ( S1 Table ); review articles and governmental reports accounted for 6.5% of the included studies. The majority of all studies used quantitative research methods (72.1%); qualitative research methods and mixed methods represented 14.4% and 7.0% of studies, respectively.

Mental health outcomes

Stress was the most prevalent outcome of interest, accounting for 41.9% (n = 143) of all studies ( Table 2 ). The second most common outcome was suicide (33.1% of all studies; 111/341), followed closely by depression (32.6% of all studies). Anxiety was an outcome of interest in 15.0% of studies worldwide (51/341). Resilience was studied in 5.9% (20/341) of all studies.

Stress (n = 143).

Studies that examined stress as a mental health outcome of interest were represented across the full range of publication years (1979–2017). As shown in Table 2 , four countries contributed over 75% of the literature around stress among farmers: US (41.9%), Australia (18.9%), United Kingdom (UK) (8.4)%, and Canada (7.7%). As shown in Table 3 , over 70% of this research was quantitative in nature, with 42.7% of studies using a cross-sectional study design, followed by cohort studies, which accounted for 21.0% of the included studies. Approximately 15% of studies examining stress were qualitative and 7.7% were mixed methods studies; twenty-five of these studies reported using a phenomenological approach and two studies used an ethnographic approach.

Studies may have reported on more than one mental health outcome.

https://doi.org/10.1371/journal.pone.0225661.t003

Suicide (n = 113).

Suicide was reported as an outcome of interest in 33.1% (113/431) of included studies. As reported in Table 2 , 16 individual countries contributed studies; over a third (37.2%) of suicide studies were conducted in India, followed by approximately 17% in Australia, 9.7% in the US, and 8% in the UK.

As reported in Table 3 , nearly 64% of studies examining suicide were quantitative in nature; approximately 21% of these studies used cohort designs, 15% used cross-sectional designs, and 5.3% were case control studies. Almost 80% of studies did not specify a farming population of interest (78.8%) instead just referring to “farmers” generally. Of the studies that did identify a farming population, crop farmers were the most represented in studies that examined suicide (20.4%), followed by permanent farmworkers (15.0%).

Depression (n = 111).

Depression was reported as a mental health outcome of interest in 32.6% of included studies. Over half of the literature examining depression among farming populations was conducted in the US (53.2%). The next largest contributors were Australia, UK, and Norway, accounting for 9.9%, 7.2%, and 5.4% of the included studies, respectively.

As depicted in Table 3 , 93/111 (83.7%) of the studies that examined depression as an outcome of interest were quantitative. The majority of depression studies reported using a cross-sectional approach (60.4%). Migrant and permanent farmworker populations were the most represented farming groups and were included in 36.6% of all included studies.

Anxiety (n = 51).

Fifteen percent of included studies examined anxiety as a mental health outcome of interest (51/341). The US contributed the largest proportion of studies examining anxiety (39.2%), followed by Australia (13.7%), UK (11.8%) and Norway (9.8%) ( Table 2 ).

Quantitative research methods were reported in 84.3% of anxiety studies. These quantitative studies consisted largely of cross-sectional study designs (62.8%), while cohort study designs were reported in 13.7% of included studies. Quasi-experimental designs were reported in three studies examining anxiety (5.9%), and one randomized control trial was included (2.0%). Migrant and permanent farmworkers were the most prevalent study population of interest (37.2%), followed by farm families and female farmers (9.8% each). A large proportion of studies that examined anxiety did not report a farming population of interest (68.6%).

Resilience (n = 20).

Resilience was a mental health outcome of interest in 5.9% of the included studies (20/341) ( Table 2 ). These studies were conducted in the US (45.0%), Australia (40.0%), Canada (10.0%), and one study that was international in scope (5.0%).

Sixty percent of studies that explored resilience used a quantitative approach including one cohort study (5.0%), one scale development/validity testing study (5.0%), and ten cross-sectional studies (50.0%). Forty percent of resilience studies reported farm families as their population of interest (n = 8), while 60% of studies had no reported farm type ( Table 3 ). Resilience was the only positive mental health outcome observed in the search.

Mortality (n = 7).

Mortality studies that examined farmer mental health appeared in the literature in 2002 ( Table 3 ). Since 2002, seven studies reported on mortality from mental health struggle, which was 2.1% of the mental health literature in farming populations. As depicted in Table 2 , two of studies that reported mortality were conducted in Australia (28.6%), while India, US, New Zealand, and Norway each contributed one study.

Three mortality studies reported using quantitative methods, more specifically, a cohort study design (42.9%). Two studies reported using a phenomenological approach to qualitative data (28.6%) and two studies were literature reviews (28.6%). Four mortality studies did not report if they had a particular farming population of interest (57.1%). Among the studies that did report a population of interest, crop farmers and permanent farm workers were indicated in three studies (42.9%)

Burnout (n = 2).

Two studies reported examining burnout as a mental health outcome of interest among a farming population; one study was conducted in Canada and one in Finland. Both of these studies used a cross-sectional approach to estimate the prevalence of burnout among farming populations. The Canadian study did not specify a farming population of interest, while the Finnish study examined dairy farmers.

Non-specified mental health outcome (n = 25).

In 7.3% of studies, a specific mental health outcome was not identified, but rather, the broad construct of mental health or psychological wellness was examined. Eighty percent of these studies had a quantitative study type: 52.0% used a cross-sectional study design and 8.0% used a cohort study design to measure mental health. Qualitatively, 28.0% of studies used a phenomenological approach to exploring mental health among farmers.

Risk factors associated with mental health outcomes.

As outlined in Table 4 , examined risk factors related to farmer mental health included: demographic information (19.9%) and socioeconomic status (7.6%); help-seeking (6.2%); pesticide use (5.0%); substance use (5.0%); and climate change (2.3%). Physical health was represented in approximately 15.2% of all studies.

https://doi.org/10.1371/journal.pone.0225661.t004

Mental health interventions

Twenty studies described a mental health service or resource (5.9% of all studies). These were conducted between 1998 and 2016.

Australia (n = 12).

In Australia, twelve studies described or assessed mental health services (60.0%) [ 20 ]–[ 26 ]. Four of these studies focused on assessing the efficacy of increasing mental health literacy among farmers and those who work with farmers [ 21 ]–[ 23 ], [ 27 ]. One mixed-methods study, conducted by Brumby et al (2009), provided an overview of their approach to farmer physical and mental health through “The Sustainable Farm Families (SFF)” project. This comprehensive approach to health and wellness highlighted the need for focusing on the farm family as a unit and engaging families as active learners [ 22 ]. Using a workshop format, this intervention consisted of a two-day workshop, followed by a one-day workshop in years two and three of the three-year intervention. These workshops combined physical and mental health education, and both pre- and post-training data were collected by questionnaire to assess knowledge and understanding of the core topics covered. Results showed a statistically significant change in knowledge around participant’s basic understanding of rural health facts, disease processes (including risk factors), and lifestyle questions that was maintained over the 3-year project for both men (85% retention; p<0.05) and women (86% retention; p<0.05) [ 22 ].

A qualitative study conducted by Brumby and Smith (2009) showed the impact of the “Sustainable Farm Families Train the Trainer” model as a successful approach to mental health and wellness in farming populations [ 21 ]. Through this program, participants, who were service providers in the community, increased their knowledge around how mental health impacts farmers and their farm. It showed the value of engagement with farmers through a “farmer centred model of care” versus the traditional health model [ 21 ]. Women were more likely to access supports than men, and women experienced stress, in the context of their farm, differently than men [ 21 ]. Additionally, results showed that farmers maintained a “masculine” or “stoic” view of accessing mental health services, emphasizing the need for a farmer-based approach, grounded in the agricultural culture, to mental health services in agriculture [ 21 ].

A longitudinal cohort, the Australian Rural Mental Health Study, recruited participants from 2007–2009, to examine mental health outcomes and variables surrounding help-seeking for mental health issues, among farmers and non-farmers, across four time points (122). Results showed that farmers were significantly less likely than non-farmers to access services, regardless of the service accessibility within the community [ 28 ]. The authors discussed the importance of tailoring services to farmers to improve trust and improve service use.

A short report published in 2009 by Robinson and colleagues discussed the need for innovation through an initiative of the Centre for Rural and Remote Mental Health (Australia) aimed at enhancing existing models to better serve rural communities, including farmers [ 29 ]. Participating psychiatrists were surveyed to assess their level of comfort in serving farming populations by partnering with existing agencies that farmers accessed regularly (unrelated to mental health). Particularly, the authors discussed the role of partnering with farm financial advisors as a way to increase access to mental health services [ 29 ]. No data were presented in this short report.

Another short report, published in 2009, assessed the efficacy of a mental health support line for farmers in New South Wales who experienced severe draught [ 30 ]. This assessment used a mixed-methods approach, analyzing data collected by the Centre for Rural and Remote Mental health on a monthly basis, along with conducting qualitative interviews with phone line staff (n = 5). Regression analysis suggested that the number of calls was not significantly associated with the percentage of the state declared in drought. However, no data were presented and no overview of the approach to the qualitative data was discussed [ 30 ].

A qualitative study, published in 2009, explored mental health service providers’ perceptions, through oral histories, of how climate change has impacted the interdependency of political, environmental, economic, and mental health concerns in rural and remote communities that serve farmers [ 25 ].

The value of Mental Health First Aid (MHFA) training for Advisory and Extension agents working with farmers was evaluated in a pilot project conducted by Hossain et al in 2010 [ 27 ]. This study assessed the impact of MHFA training one-year post delivery. Using a mixed-methods approach, participants (n = 15) were surveyed and two focus groups were also conducted. Results showed “moderate” to “good” gains in understanding of mental health issues, “pathways to address” mental health issues, and a gain in confidence with respect to recognizing mental struggle and providing support to farmers to help them access appropriate services [ 27 ]. Participants rated MHFA as “moderately” to “quite” beneficial. The qualitative data were analyzed for themes; the specific approach to the qualitative analysis was not discussed [ 27 ].

In 2011, another Australian study provided an overview of using a community development approach to developing services, including mental health literacy training, in hopes of increasing service use by farming populations in New South Wales [ 23 ]. This region-based approach to service development allowed working groups (including industry groups, governmental agencies, and regional health and mental health service agencies) to adapt existing resources to meet the needs of their farming communities. Over the four-year project, over 3000 participants received mental health literacy training. The authors discussed the positive impact of this approach to development and delivery of mental health related services to rural areas [ 23 ]; however, no formal evaluation of the program was presented.

Farm-Link was another initiative in Australia (New South Wales) developed as a suicide prevention project [ 24 ], [ 31 ]; two studies were published. Funded from 2006–2011 through partnership between the Australian government and the University of Newcastle, this initiative aimed to promote prevention and early intervention for mental health issues, improve the care system, particularly in aiding in the coordination of multiple component parts that exist in rural areas to deliver mental health services [ 31 ]. Specifically, Farm-Link aimed to improve access to mental health services through improving linkages between existing agencies; both mental health agencies and other “trusted” agencies in the farming community (e.g. agricultural agencies and farm financial service agencies). Further, Farm-Link mapped these networks to report back to the agencies in order to facilitate relationship building and sharing of workload, and to bolster farmer engagement with available services without overlap [ 24 ], [ 31 ]. An independent evaluation was conducted on this project, using a mixed-methods approach [ 31 ]. The evaluation indicated that there was a large need for mental health resources across agencies, and that most agencies did not have the capacity to deal with these needs. Overall, all agencies increased the number of other agencies that they shared information with, but improvements to programs or mental health outcomes among program users were not tested statistically [ 31 ].

A research protocol for a clinical trial was published in 2016 by Kennedy et al [ 20 ]. This protocol was for a digital intervention aimed at reducing stigma around personal experiences with suicide among males who have lived-experience of suicide (e.g., bereaved, previous attempts, or ideation) living in Australian farming communities. This study proposed using a mixed-methods design, multi-level evaluation of a web-based intervention where participants would have access to educational materials, resource information, shared stories from peers, and a personal section for goal setting [ 20 ]. Quantitatively, perceived stigma was to be assessed using an adaptation of a validated scale, the Stigma of Suicide Scale (SOSS). Qualitatively, authors proposed to explore personal insights around stigma. This trial was registered with the Australian and New Zealand Clinical Trials Registry (ACTRN: ACTRN12416000289415). SOSS scores were to be assessed at the beginning of the trial and again, upon completion [ 20 ].

United States (n = 4).

The Farm Partners program in New York state was the first mental health intervention to be discussed in the literature, published in 1998 [ 32 ]. This program aimed to increase awareness and use of community resources by farm families in order to address the high levels of occupational stress. Results showed that over four years, this program helped to refer farmers to services for financial advice, health services, support groups, mental health professionals, social services, legal services, and more [ 32 ]. Within our search, we did not find a formal evaluation of this program’s effectiveness.

Another study explored the “Sowing the Seeds of Hope” behavioural health program, which had representation in Iowa, Kansas, Minnesota, Nebraska, North Dakota, South Dakota, and Wisconsin [ 33 ]. It highlighted the impact of creating services that were delivered by providers who have knowledge of agriculture to ensure that services are culturally acceptable, affordable, and accessible within the region they are meant to serve [ 33 ]. There was no published formal evaluation of this program returned in our search.

One experimental study sought to determine the effectiveness of music therapy aimed at decreasing depression, anxiety, and social isolation among Mexican farmworkers in the southern US [ 34 ]. The authors reported that music therapy had a “medium” but non-significant effect on decreasing depression scores (7).

In 2011, a cross-sectional study conducted through the National AgriAbility Project, highlighting the mental health services and resources that were available to farmers throughout this network, which included 21 United States Department of Agriculture-funded State and Regional Projects [ 35 ]. The most commonly provided mental health resources were speakers at workshops, with brochures, papers, or articles to share information about mental/behavioural health issues [ 35 ]. Within our search, we did not find a formal evaluation of the effectiveness of this program published.

Canada (n = 1).

In Canada, one qualitative study published in the year 2000 described the development and evaluation of a mental health service for Saskatchewan farmers intended to help farmers cope with stress [ 36 ]. Beginning with a qualitative needs-assessment, this study highlighted gaps in education (around stress management, anger management, self-esteem, and communication), support group formation and maintenance, clinical services, general information, and advocacy. Based on the results of this assessment, the author developed a program to address these needs within the health region, partnering with existing organizations to help deliver services [ 36 ]. This program included workshops on topics such as stress, anger and grief in the rural context, coping, and stress resiliency. The author emphasized the importance of trust and credibility as major factors to consider when developing mental health resources in farming communities. Once trust was established with farmers, she was able to deliver these services more effectively, and attendance improved [ 36 ]. A partial “evaluability assessment” was conducted in 1995; however, the author indicated that this evaluation was incomplete, leaving assessment of the program’s effectiveness reliant on anecdotal evidence.

United Kingdom (n = 1).

In the UK, an overview of an ongoing in-person support service delivered in farming communities by two nurses with farming backgrounds was published in 2000 [ 37 ]. This service aimed to address farming accidents, mental health, and occupational-related diseases. This review did not include any data and a follow-up report with findings was not identified.

India (n = 1).

In India, a mental health intervention was implemented in the Maharashtra region, which had experienced an increase in suicides [ 38 ]. This intervention recruited “social health activists” and trained them to use a tailored screening tool for depression among farmers. This tool was developed by psychiatrists in the region. The goal of the intervention was to detect depression among farmers and refer them for services, such as counselling and long-term treatment, more effectively [ 38 ]. No results or evaluation of this program was presented in this short report.

Africa (n = 1).

The study conducted in the Democratic Republic of Congo was unique in that the intervention the authors were evaluating was farming itself [ 39 ]. Specifically, this randomized control trial measured the impact of an intervention, Pigs for Peace, on individuals who were from regions greatly impacted by conflict. Approximately 50% of their participants identified as farmers. The study showed a statistically significant positive effect of having livestock as a moderator for good mental health, lowering overall impacts of depression and post-traumatic stress disorder [ 39 ].

This study systematically maps the literature examining mental health outcomes among farming populations, worldwide. The results of this review highlight gaps in research on farmer mental health. For example, the majority of research examining mental health outcomes focused on stress, suicide, and depression. These mental health outcomes were reported concerns in the specific regions in which they were studied, and thus may warrant further investigation globally. Further, mental health outcomes that have been less studied, including anxiety, burnout, and positive mental health outcomes, such as resilience, may warrant further investigation to determine the trends across nations.

Until recently, there have been very few studies of national scope that have examined mental health outcomes in North America beyond suicide, and these results have yet to be published in the academic literature (currently limited to conference publications) [ 40 ]. While small-scale studies contribute to localized knowledge, successful programming for farmer mental health has been supported with broader epidemiological data [ 22 ], [ 41 ]. A systematic mapping of existing research can help researchers avoid unnecessary overlap and can help identify knowledge gaps to inform the distribution of funds to where resources may be most effectual.

Beyond migrant farmworkers, other farming populations were not always explicitly identified within the literature. Overall, 36.1% of the cited literature did not specify which types of farming populations the authors were studying. While there is likely to be overlap between farming subpopulations regarding some aspects of mental health, there may be important differences to explore. For example, in a North American context, farmers are greatly impacted by changes in trade agreements, supply management, and governmental regulations that are vastly different and dependent on the specific farming commodity [ 42 ], [ 43 ]. Knowing which farming population is being examined lends more specificity to the work and can help researchers to elucidate these relationships more clearly.

Existing systematic reviews of farmer mental health are limited to one review of suicide [ 11 ]. Based on the findings of this review, it is warranted that researchers also systematically examine other outcomes; for example, depression among farming populations was measured in 109 (33.3%) of all studies included here. A limitation of this scoping review is that we did not aim to determine the number of studies that quantify the prevalence or incidence of depression; however, providing an adequate number of studies quantifying the prevalence of depression exists, conducting a systematic review and meta-analysis could provide valuable insights into establishing the global risk of experiencing depression among farmers. It could also allow for an exploration of heterogeneity among studies, which would help determine the degree of bias within and between studies. Additionally, this could provide a comprehensive analysis of the methodological rigour with which the studies were conducted. While there are many studies of depression throughout the literature, the way in which depression was investigated varied in study design, sample size, and measurement tools used. Assessing which tools (i.e. validated scales, physician diagnosis, self-report) have been used in farming populations can help inform future work and the development of standardized methodological guidelines could help make studies across the globe more comparable. For example, the Core Outcome Measurements in Effectiveness Trials (COMET) initiative has created a database of clinical studies that contribute to the development “core outcome sets (COS)” [ 44 ]. These COS inform the most appropriate measurement tools for clinical outcomes across many areas of health and wellness, to ensure data are comparable across trials. This could also serve to improve the epidemiological rigour of studying mental health outcomes in farming populations.

There were several studies that investigated “mental health” without operationalizing their definition of what this term meant within the study context. This trend has largely diminished over time, with more recent studies providing clear operational definitions that can be more easily interpreted.

With the exception of stress, depression, and suicide, other mental health outcomes were infrequently studied. Burnout, a more recent construct to be measured among farmers, was investigated in two studies [ 40 ], [ 45 ]. Given the association between burnout and employee retention generally [ 46 ], farmers experiencing burnout may have increased burdens beyond those of other occupations, given the nature of farming as an occupation, lifestyle, [ 45 ] and identity [ 47 ].

The vast majority of research focused on negative mental health outcomes (i.e. mental health pathology), to the near exclusion of positive mental health outcomes. Only one outcome identified in the present review focused on a positive outcome: resilience. While it is important to examine negative mental health outcomes, it could be argued that it is detrimental to do so to the exclusion of positive mental health outcomes like resilience, quality of life, and life satisfaction, which are outcomes commonly studied in the field of positive psychology. Positive psychology is “the scientific study of optimal human functioning [that] aims to discover and promote the factors that allow individuals and communities to thrive” [ 48 ]. Expansion of positive psychology research amongst farmers could help improve understanding on what helps enhance farmers’ well-being, and what helps some farmers thrive, even in the face of the significant stresses they face. In 2005, a literature review conducted by Fraser and colleagues concluded that more research is needed to explore resilience among farmers worldwide [ 10 ]. Give that resilience is positively associated with mental health [ 49 ], focusing research and resources on assessing how resilience can be taught and increased among farmers should be a priority for future work.

Mental health services

To date, few studies have published formal evaluations of their mental health interventions/services, with all published evaluations coming from Australia. Globally, farming populations can benefit from building on this Australian knowledge, adapting services to fit other farming contexts. Formal evaluation of the impact of these services would also help to bolster existing literature and provide statistical evidence that can be used to prioritize farmer mental health research and services and lobby for permanent funding.

Throughout the studies that aimed to assess interventions, there were common findings indicating that farmers require services that are specifically tailored to their population needs and that are delivered by service providers that have a foundational understanding of the specific pressures associated with farming, and how this may impact the mental health of farmers. For example, studies conducted in Canada [ 50 ], Australia [ 21 ], and the US [ 33 ] reported that farmers are more willing to seek help for their mental health if they know the care provider has a knowledge base of agriculture. This may impact the trust between the farmer and mental health provider, which a systematic review of barriers to help-seeking for mental health issues in young people reported as essential for help-seeking both short- and long-term [ 51 ].

Gender differences were highlighted in an Australian study examining help-seeking among farmers [ 21 ]. Women were more willing to seek help for mental health concerns than men, and this gender association was further impacted by whether or not the mental health service provider had a knowledge base of farming and agriculture.

Hence, future mental health interventions that are developed for farming populations may benefit from considering both farm-specific needs and potential gender differences when designing new mental health prevention and intervention strategies. Furthermore, existing mental health services may benefit from educating service providers around farming practices, lifestyle, and realities in the communities that they serve, increasing their credibility within the farming community, and potentially increasing the likelihood that farmers will seek help for their mental health.

Study limitations

While this review aimed to comprehensively map the existing peer-reviewed literature, it is possible that studies were not captured within the search. We aimed to reduce this risk by using comprehensive databases and checking reference lists of literature reviews that were identified in the study prior to full-text screening. As reference lists of reviews were examined prior to full-text screening, we are unable to identify the number of additional studies that were included as a result of reference checking. Further, this review excluded studies that did not explicitly state that they were examining a farming population. This may have led to the exclusion of studies labelling their population as “rural”, but included farmers. Lastly, studies that were unavailable in English, or that were part of a textbook or thesis were excluded, which may have excluded some geographical regions from the review.

This scoping review provides a critical overview of the literature examining mental health outcomes in farming populations, globally. While some geographic regions had a substantial body of literature, knowledge gaps remain including the prevalence of mental health outcomes, how they are impacted by risk and protective factors, and which intervention strategies are most impactful in farming communities. The results of this scoping review can help guide researchers to identified gaps in research and services, leading to a more informed and focused approach to future work, and ultimately a more comprehensive understanding of mental health and wellness among farmers worldwide.

Supporting information

S1 appendix. data extraction form..

https://doi.org/10.1371/journal.pone.0225661.s001

S1 Table. Reference list of included studies.

https://doi.org/10.1371/journal.pone.0225661.s002

S1 Checklist. PRISMA-ScR checklist.

https://doi.org/10.1371/journal.pone.0225661.s003

• View Article
• PubMed/NCBI
• Google Scholar

Articles on Farmers

Displaying 1 - 20 of 171 articles.

We’re helping farmers access future climate projections as easily as checking the weather

Stephen Snow , CSIRO ; Aysha Fleming , CSIRO , and Yuwan Malakar , CSIRO

Ignoring Welsh farmers’ protests is a dangerous move for politicians

Lawrence McKay , University of Southampton and Davide Vampa , The University of Edinburgh

EU increases tariffs on Russian grain to hamper its war effort – but it’s European consumers who could feel the pinch

Kirill Shakhnov , University of Surrey

Cocoa beans are in short supply: what this means for farmers, businesses and chocolate lovers

Michael E Odijie , UCL

From the end of CAP quotas to the present day, 20 years of failed European agricultural policies

Xavier Hollandts , Kedge Business School

European farmers are angry: addressing root causes would overcome polarisation

Tomaso Ferrando , University of Antwerp

Stop killing brown snakes – they could be a farmer’s best friend

Rick Shine , Macquarie University

Wheat Pool 2.0: The time might be ripe for a revival of Prairie  co-ops

Marc-Andre Pigeon , University of Saskatchewan and Natalie Kallio , University of Saskatchewan

Climate change and nature loss are our biggest environmental problems - so why isn’t the market tackling them together?

Patrick O'Connor , University of Adelaide and Anthelia Bond , University of Adelaide

3 ways AI can help farmers tackle the challenges of modern agriculture

Joe Hollis , Iowa State University

How digital twins will enable the next generation of precision agriculture

Istvan David , McMaster University

Giraffes could go extinct – the 5 biggest threats they face

Derek E. Lee , Penn State

In defence of Bill C-282 : Canada’s supply management supports farmers while safeguarding consumers

Bruce Muirhead , University of Waterloo and Jodey Nurse , McGill University

Traditional farming knowledge should be stored for future use: the technology to do this is available

Mourine Sarah Achieng , University of South Africa

Why Australia urgently needs a climate plan and a Net Zero National Cabinet Committee to implement it

Tony Wood , Grattan Institute

America’s farmers are getting older, and young people aren’t rushing to join them

David R. Buys , Mississippi State University ; John J. Green , Mississippi State University , and Mary Nelson Robertson , Mississippi State University

Suicide rates increased after extreme drought in the Murray-Darling Basin – we have to do better as climate change intensifies

Sarah Ann Wheeler , University of Adelaide ; Alec Zuo , University of Adelaide , and Ying Xu , University of Adelaide

Cocoa prices are surging: west African countries should seize the moment to negotiate a better deal for farmers

Mixed-use solar and agricultural land is the silver bullet Alberta’s Conservatives have wished for

Joshua M. Pearce , Western University

Farmers face a soaring risk of flash droughts in every major food-growing region in coming decades, new research shows

Jeff Basara , University of Oklahoma and Jordan Christian , University of Oklahoma

Related Topics

• Agriculture
• Climate change
• Food security
• Peacebuilding

Top contributors

Research associate, UCL

Professorial Fellow, University of Canberra

Professor in Water Economics, University of Adelaide

Sociologist/Criminologist/Victimologist and Media Communication Expert, University of Ibadan

Lecturer in Integrated Crop Management, University of Neuchâtel

Researcher, Centre for Peace and Security Studies, Modibbo Adama University of Technology

Senior Lecturer in Criminology, Co-Director of the Centre for Rural Criminology, University of New England

Principal Lecturer, Harper Adams University

Assistant Professor, Department of Entomology; African-American Studies, University of Illinois at Urbana-Champaign

Researcher and Project Manager in Agriculture, Food Security and Climate Change, University of Cape Town

Chair in Agricultural Marketing, Trade and Policy, The Ohio State University

Assistant Professor, Cornell University

Senior Lecturer in Criminology, Co-director of the Centre for Rural Criminology, University of New England

Clinical Professor of Medicine, University of California, San Francisco

Emeritus Professor of Law and Criminal Justice, University of South Australia

• X (Twitter)
• Unfollow topic Follow topic

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Int J Environ Res Public Health

Key Risk Factors Affecting Farmers’ Mental Health: A Systematic Review

Recently, concern has increased globally over farmers’ mental health issues. We present a systematic review of the outcomes, locations, study designs, and methods of current studies on farmers’ mental health. In particular, this review aims to fill an important gap in understanding of the potential key risk factors affecting farmers’ mental health around the world. 167 articles on farmer mental health were included in a final systematic review using a standardized electronic literature search strategy and PRISMA guidelines. The four most-cited influences on farmers’ mental health in the reviewed literature respectively were pesticide exposure, financial difficulties, climate variabilities/drought, and poor physical health/past injuries. The majority of studies were from developed countries, most specifically from the United States, Australia, and the United Kingdom. Comparative studies on the mental health of farmers and other occupational workers showed mixed results, with a larger portion identifying that psychological health disturbances were more common in farmers and farm-workers. Knowledge of farmer psychological disorder risk factors and its impacts are essential for reducing the burden of mental illness. Further research will be required on climate change impacts, developing country farmers’ mental health, and information on how to reduce help-seeking barriers amongst farmers.

1. Introduction

Researchers have identified a number of occupational health risks through studies of farming communities, and some have specified farming as an especially stressful occupation [ 1 , 2 , 3 , 4 ]. Farming is associated with a range of physical and mental health risks because of the hard work under challenging conditions [ 2 ]. Studies on mental health in farming communities around the world have identified several common risk factors, namely: commodity prices, debt, climate change, drought, overwork, government regulations, isolation, role conflict, time pressure, and poor housing [ 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 ].

It has been shown that chronic stressors have a major influence on well-being and health. Particularly, stress is associated with an increased prevalence of mental disorders, such as depression and anxiety [ 7 ]. Stress has dominated the literature as one of the most broadly researched psychosocial constructs, mainly in the work-related stress area. Work-related stress is defined as a conflict when the demands of work are high, and the worker cannot manage, control, or cope with that stress [ 27 ]. For farmers in particular, the advent of future climate change means that their job will become even more stressful [ 28 ]. Williams [ 29 ] reported that chronic stress among farming communities might lead to physical problems (e.g., headaches, sleep problems), mental problems (e.g., anxiety, anger, depression), and cognitive issues (e.g., memory loss, inability to make decisions). Farmers have also been more likely to report that life was not worth living than non-farmers [ 2 ]. Mental problems among farmers can affect their lives in different ways, and the impact of stress factors are varied among them. These include less interest in pleasure, less concentration, loss of appetite, weight change, tiredness, irritability, problems sleeping, fatigue, loss of control, and anxiety [ 5 , 28 , 30 , 31 , 32 , 33 , 34 ]. Also, loss of self-esteem, withdrawal from social activity, relationship breakdown, forgetfulness, loss of temper, relaxation problems, feeling blue, and substance abuse have been reported [ 9 , 13 , 35 , 36 ]. A danger of burnout and exhaustion is possible with all these symptoms. Burnout is a gradually developing disorder that may consist of physical and mental exhaustion, a cynical attitude towards work, and a reduction in self-esteem [ 37 ]. Most importantly, mental disorders have been identified as one of the key risk factors for suicide attempts among farmers [ 34 ]. High suicide rates among farmers, farm manager and agricultural labourer have been reported in several studies [ 38 , 39 , 40 , 41 ], which is considered one of the most serious concerns affecting some farming communities. As the issue of farmers’ mental health raises many concerns, we conducted a search of the literature to answer the following main research questions: what are the key risk factors affecting farmers’ mental health and how does this differ around the world?

To explore the research question, this paper systematically reviews published studies on farmers’ mental health, and details the risk factors that have been considered and how farmer mental health has been measured. What is clear is that interpretations of mental health outcomes vary across identified studies, and most of the times outcomes are not clearly defined. We distinguish between mental health and mental disorder here. According to the WHO (2007; p. 1), mental health is: “a state of well-being in which the individual realizes his or her own abilities, can cope with the normal stresses of life, can work productively and fruitfully, and is able to make a contribution to his or her community” [ 42 ]. Mental disorders are normally defined by some combination of abnormal thoughts, emotion, behaviour, and relationships with others [ 43 ]. Mental disorders include depression, anxiety, stress, schizophrenia, bipolar disorder, and emotional/psychological distress [ 44 ]. The most common mental disorders are said to be anxiety and depressive disorders, which are a reaction to the stresses of life. A person with an anxiety disorder feels distressed a lot of the time, for no apparent reason, and a person with a depressive disorder can experience a long-term depressed mood and loss of interest in activities that used to be enjoyable [ 45 ]. The burden of mental disorders continues to grow with substantial impacts on health and major social, human rights, and economic consequences around the world [ 44 ].

Given the growing farming pressures in many countries (e.g., declining productivity, declining terms of trade, worsening weather impacts, and deteriorating soil and water quality), evidence-based understanding of risk factors on farmer mental health will become increasingly more important to improve the efficiency of prevention efforts. Hence, we sought to understand what the potential key risks affecting farmers’ mental health are, as well as if these risks vary across space and time.

2. Materials and Methods

This systematic review followed the standard Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [ 46 ], namely: (1) identification of literature; (2) screening questions; (3) eligibility using inclusion criteria; and (4) assessment of the quality of the studies and detection of any possible bias, which are discussed in the following sections.

2.1. Identification

To identify relevant literature, we searched the literature published until April 2019 in electronic databases PsycINFO, PubMed, Scopus and Google Scholar using the following keywords: “Mental health” OR “mental disorder” OR “depression” OR “distress” OR “anxiety” OR “stressors” in the combination of “farmer” “farmworker” “agricultural worker”. Note: suicide and suicide ideation was not included in this review.

2.2. Screening Questions

The electronic database search generated 1224 English language articles (excluding duplicates), and after screening the title and abstract, 436 studies were included in the review. Then the body of these selected articles were screened with the following questions:

• Are farmers included as a general study population? (y/n)
• Are any kind of “mental disorders” part of the study? (y/n)

Based on the results of the screening questions, 329 studies were first included in the review. Studies were excluded because of limited relevance to farmers’ mental health issues (e.g., those focused on rural communities as a whole or those related to farmer/rural suicidal behaviours only).

2.3. Eligibility Assessment

The following inclusion criteria were then applied:

• Does the study clearly mention which risk factors/stressors affect farmers’ mental health (y/n)?
• Does the study detail the direction on farmers’ mental health (+/−/0)?

Among the identified articles, 162 failed to meet the eligibility criteria, hence 167 articles were included in the review. Of the 167 articles, 146 of these were quantitative studies. Figure 1 provides the roadmap followed for the studies selection.

Schematic for identifying studies.

2.4. Assessment of the Quality of the Studies and Detection of Possible Bias

Each study that used quantitative methods was rated using the OHAT risk of bias rating tool [ 47 ]. The OHAT risk of bias tool consists of a set of questions to address the main bias domains (see Appendix A for the bias questions). Each question within the tool receives one of four assessment levels (definitely low risk of bias, probably low risk of bias, probably high risk of bias, and definitely high risk of bias). Based on the answers to the assessment questions, each study was classified into one of the three tiers proposed by the OHAT to synthesise risk of bias evaluations across studies.

NVivo, a qualitative data analysis software, was used to classify the total 167 selected studies on farmer mental health. We provide an overview of the findings of this review for: (i) study geographical focus, (ii) mental health scales or measures, (iii) mental health of farmers versus non-farmers, (iv) key farm risk factors, (v) socio-demographic characteristics of farmers with poorer mental health, and (vi) farmer help seeking behaviour.

3. Systematic Review Results

3.1. geographic focus.

Research into farmer mental health has been conducted in several countries, but mostly in developed countries. As Table 1 and Figure 2 show, the United States, Australia and the United Kingdom have conducted the greatest amount of research in this space (27%, 17%, and 8% respectively). Of the papers that focused on farmers’ mental health, the majority used quantitative methods (146 studies) versus qualitative methods (18), versus a combination of both qualitative and quantitative (3).

Number of farmers’ mental health studies published by country.

Geographical locations of the selected studies.

Note: Percent totals may not exactly sum to 100% due to rounding.

Figure 3 shows an increasing focus on farmer mental health research over the past couple of decades, with an increase from the mid-2000s onwards. This increase was driven by a surge in research by researchers on Australian farmers’ mental health 2005 onwards (with was near the middle of the Millennium Drought in Australia). The highest number of publications was in 2018.

Number of farmers’ mental health studies from 1979 to April 2019.

3.2. Measures and Methods of Farmer Mental Health and Assessment of Quality

Method and measurement assessment of farmer mental illness has varied greatly (see Table 2 ). Our systematic review indicates that literature used a variety of methods and scales for measuring farmer mental health. The most common method for measuring mental health was the Centre for Epidemiologic Studies-Depression Scale. However, other reasonably common methods such as Kessler 10, Hospital Anxiety and Depression, Clinical Tests, Mini-Mental State Examination, and SF-36.

Details of the mental health measures used in the selected studies.

Note: Percent totals may not exactly sum to 100% due to rounding. * These studies often used self-reporting methods to allow participants to tell their stories, and discuss their issues. The results of the discussions were defined as revealing farmers’ mental health issues.

Several measures have also been constructed to measure agricultural-related stress, including the Farm/Ranch Stress Scale, the Edinburgh Farming Stress Inventory, Welke’s Farm Ranch Stress Inventory, and Migrant Farmworker Stress Inventory.

The assessment of bias by using the tiering approach across the studies showed that, out of the 146 quantitative studies, 99 (68%) of them were categorised in “Tier1” or “plausible bias unlikely to seriously alter the results”; 37 (25%) of studies were categorised in “Tier2” or “plausible bias that raises some doubt about the results”; and only 10 studies (7%) of studies were categorised in “Tier3” or “plausible bias that seriously weakens confidence in the results.”

3.3. Mental Disorders among Farmers Versus Non-Farmers

The systematic review found that 28 articles (17% of the total) compared farmers’ mental health with other occupational groups. Out of those articles, 20 studies (71%) suggested farmers have worse mental health issues than the general population, e.g., [ 86 , 87 , 88 ]. Also, the National Institute for Occupational Safety and Health [ 89 ] examined 130 different occupations and found farm workers and farm owners had the highest rate of deaths due to stress-related conditions and mental disorders. Higher mental disorder levels and poorer vitality have been reported for animal farmers [ 90 , 91 ] and dairy farmers [ 90 , 92 ], compared to non-farmers. Others also find a higher prevalence of mental disorders in farm workers as compared to employed non-farmworkers and other occupations such as teaching, office work, and building construction [ 62 , 86 , 90 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 ]. Wheeler et al. [ 26 ] identified that some Australian irrigators experienced high levels of psychological distress nationally; higher than dryland farmers or the Australian population. Gevaert et al. [ 85 ] found farmers, self-employed, and own account workers have worse mental health compared to medium-to-large employers and liberal professions. Ulrich et al. [ 102 ] identified that stress was significantly higher in farmworkers compared with non-farmworkers only in one farming period.

However, not all studies confirm that farmers have worse mental health than the general population [ 103 ]. Our review showed that 18% of the studies found farmers have a lower prevalence of mental illness than non-farmers, and 11% reported that there was no difference. For example, Otsuka and Kato [ 55 ] compared a traditional society occupation group (e.g., farmers and skilled manual workers) with an industry occupation group (e.g., managers and technicians) and revealed that the industrialized occupation group had higher levels of depression. Similarly, Liu et al. [ 83 ] found that general workers suffered from higher levels of mental stress and worse physical health compared to farmers. But, Thomas et al. [ 104 ] and Feng et al. [ 105 ] reported farmers have a lower prevalence of mental illness than the general population, although were more likely to report thinking that life was not worth living. Tomasson and Gudmundsson [ 106 ] stated that farmers were less likely to consume alcohol and that farmers’ mental health problems were 5% lower than non-farmers. Finally, Brew et al. [ 58 ] and Stain et al. [ 107 ] argued that there was no difference between mental health outcomes and wellbeing of farmers compared to non-farm workers in general, although Brew et al. [ 58 ] added that those farmers who lived more remotely had poorer mental health than non-farm workers living remotely.

3.4. Farm Risk Factors

Our systematic review identified several types of farmers’ risk factors. Table 3 depicts the main cited key risk factors of farmers that have been cited in the literature, namely: pesticide exposure, financial problems, climate variability/drought, physical health, isolation, role conflict, and time pressure respectively. We discuss each in more detail below.

Key farmer mental health risk factors.

3.4.1. Pesticide Exposure

An association between pesticide exposure and farmer mental disorders has been reported in 43 reviewed studies in both developed and developing countries. As Table 3 illustrates, pesticide exposure is more cited in the developing country literature, for example studies in Brazil, India, Nepal, Philippines, Iran, Tanzania, China, Egypt, Pakistan, and Costa Rica have focused on pesticide exposure and farmer mental distress. Among the developed country literature, United States studies have also studied links between pesticide exposure and farmer mental health. Some pesticides are neurotoxic, which are said to directly affect neural systems known to cause mental illness [ 108 , 109 , 110 , 111 , 112 , 113 ] and depression [ 56 , 60 , 64 , 65 , 70 , 72 , 74 , 114 , 115 , 116 , 117 , 118 , 119 , 120 , 121 , 122 , 123 ]. Some studies have examined pesticide exposure in general, while others considered specific compounds such as organophosphates. Organophosphates can enter an individual’s body by the skin or through inhalation, [ 124 ] and this is associated with a range of physical symptoms (e.g dementia, Parkinson, phobia, diarrhoea, vomiting, dizziness, chest-pain, memory loss, concentration difficulties, body weakness, irritation, etc.), [ 60 , 119 , 123 , 124 , 125 ]. Wesseling et al. [ 60 ] found a relationship between acute occupational poisoning with organophosphates and psychological distress. Koh et al. [ 81 ] revealed that the association with depression was stronger amongst farmers with past pesticide poisoning episodes than amongst those with no such reported experiences. A study by Serrano-Medina et al. [ 126 ] on 140 agricultural workers with organophosphorus pesticide exposure in Mexico showed that 25% of them had major depression with suicidal attitudes, 24% had anxiety, 24% had combined depression–anxiety, and 22% of them had major depression and no psychiatric diagnosis disorder. Focus group discussions with cotton-growing farmers in India showed that during hot summer and windy seasons, some farmers reported serious health problems such as cancer, mental illness, and diabetes [ 127 ].

3.4.2. Financial Pressures

Financial challenges were reported in 39 articles as negatively impacting farmers’ mental health, particularly where farming was the primary income source [ 8 , 15 , 19 , 20 , 31 , 37 , 79 , 105 , 128 , 129 , 130 , 131 ]. Various types of financial stress were reported by farmers in both developed and developing countries, including market prices for crops and livestock, irregular/insufficient cash flow, increased input costs, taxes, health care costs and high debt [ 28 ]. A few studies have examined the links between the 1980s farm financial crisis and mental health among U.S. farmers. During the crisis, farmers were faced with decreasing world demand, higher input costs, and low commodity prices [ 15 , 49 , 132 , 133 ]. Bultena et al. [ 133 ] found these factors caused farmer psychological distress, depression, lower life satisfaction, alcoholism, and even suicide. Farmers experiencing significant financial losses usually seek to make significant farm changes (e.g., through reducing the number of paid farm employees, working longer hours), diversify/change production or decide to exit [ 134 ].

Given that many other family members are impacted by farm financial problems, this has been found positively associated with farmers’ family unit stress perceptions [ 135 ]. Other mental health associations with financial stress include children numbers, broadacre production, and rental land [ 132 ]. Lawrence et al. [ 136 ] indicated that farmers are more successful in finding some alternative agronomic options for adapting to drought, but adapting to financial burdens was more difficult. There has been a positive and consistent relationship found between higher farm profit, greater well-being, and less distress amongst farmers and farm-workers [ 69 ].

3.4.3. Climate Variability

Climate variability was revealed as another large risk factor for farmers in our review (25 articles of included studies focused on climate issues, mostly in developed countries). It is predicted that severe and widespread droughts will increase in the future [ 137 ]. Droughts have been categorized as slow-moving disasters which can have significant health effects, usually mediated through environmental, economic, and social pathways [ 76 , 138 ]. For example, 75% of farmers in a study by Walker et al. [ 5 ] reported unfavorable climate conditions and the unpredictability of the weather as their key stress in North America. Kearney et al. [ 28 ] found 60% of farmers who worked more than 40 h per week identified bad weather as ‘very stressful’ in Eastern North Carolina. In-depth interviews with 16 citrus growers in Australia, revealed that 11 of them cited drought and insufficient water allocations as potential stressors [ 9 ]. The uncertainty of weather was also reported by 70% of farmers in New York State [ 16 ]. The observed patterns of climate change have worsened farmers’ worries about the future climate and contributed to their chronic forms of mental distress [ 139 ].

Droughts have been categorized as slow-moving disasters which can have significant health effects, usually mediated through environmental, economic, and social pathways [ 76 ]. The agricultural sector is hit the hardest by drought, with farmers experiencing declined production, crop loss, and livestock failure [ 140 ]. Farmers reported a strong association between prolonged drought and stress, and higher levels of psychological morbidity [ 131 , 141 , 142 , 143 , 144 ]. Some studies reported that the major stress in a time of drought is financial hardship. For example, Edwards et al. [ 143 ] identified that drought has significant negative economic impacts, especially for farmers who reported that the drought had reduced their output substantially.

Table 3 indicates that Australia stands out in terms of the pressure of climate variability on farmer mental health in our review. Climate stressors were mentioned in 40% of Australian studies, the highest risk factor out of all possible factors. For example, Edwards et al. [ 145 ] found that the more severe the drought, the higher the adverse effects on farmer mental health. With the ongoing threat of water scarcity, falling water allocations, water reform, and drought in Australia, Wheeler et al. [ 26 ] found that some irrigators in particular industries have higher mental health problems than dryland farmers in the Murray-Darling Basin. Austin et al. [ 146 ] found that higher drought-related stress was associated with young farmers (<35 years) who live and work on a farm, and having greater financial hardship. A study by Hanigan et al. [ 147 ] showed significant associations between distress and drought duration in young rural women regardless of whether they were in farming occupations or not. However, they found that the level of drought-related distress did not differ between farmers and non-farmers in their sample.

In addition, summer heat waves are likely to have immediate effects on the prevalence and severity of farmers’ mental health. Farmers and farm workers often have no choice but to keep working, even in extreme hot weather [ 148 ]. There are also the emotional effects of landscape changes. Loss of gardens (and ‘greenness’) has been reported as a source of distress by farming families [ 68 ].

Despite several studies finding climate variability and/or drought as key risk factors on farmers, studies with a specific focus on climate variability and farmer mental health outcomes are relatively thin. Our review found that only a small amount of research (and much of it was from Australia) have focused on the effects of climate change/drought. We could find only three studies in non-developed countries (India, Ghana, and Iran) concentrating on the mental health effects of climate on farmers. Similar to our findings, a recent study by Berry et al. [ 149 ] argued that the mental health effects of climate change has received little attention in research and policy and needs greater systems thinking.

3.4.4. Poor Physical Health/Past Injury

Greater mental illness amongst farmers who have poor physical health, past injury or work disability has also been found [ 50 , 52 , 66 , 150 ]. Farming is one of the highest risk groups for occupational injury and illness [ 151 ]. Often agricultural workers live at their worksite, so it is not surprising that an injury at work can impact their life satisfaction [ 54 ]. Distress was also related to increased physical illness on spouses and possible injury of children, which was particularly felt by farm women [ 152 ]. It has been found that farm residents with self-reported physical illness (e.g., neck, shoulder, and back pain [ 73 ]; obesity; metabolic syndrome; abdominal adiposity; and cardiovascular disease [ 153 , 154 ]) tend to have higher self-reported psychiatric impairment. Hawes et al. [ 155 ] found that higher body mass index (BMI) and poor sleep quality were also associated with higher depression scores. Carvalho et al. [ 156 ] found an association between work end time on the relationship between sleep onset time and farmer psychological well-being. Mazzoni et al. [ 157 ] and Stieglitz et al. [ 158 ] stated that those farmers who diagnosed with depression had a significantly higher total disability score. DeArmond and colleagues [ 159 ] found high levels of somatic symptom disorder (SSD) among farmers. SSD occurs when a person feels extreme anxiety about physical symptoms such as pain or fatigue and is significantly related to depression. Physical toxicity by agro-chemicals and damage to farmer health have been reported in a study by Kannuri and Jadhav [ 127 ]. Crandall et al. [ 160 ] argued that mental illness and the side effect of its medication can cause cognitive changes, which can put farmers at more risk of injury. Rostamabadi et al. [ 161 ] reported that musculoskeletal disorders, cuts, and fractures accounted for the most frequent injuries amongst farmer affecting their mental health. Other researchers discussed that depression and dissatisfaction with life were more strongly associated with agricultural worker injury than among other workers, and that farmers may work longer with physical health problems before receiving a disability pension than other occupations [ 54 , 100 , 162 ]. Also, as previously reported, increased symptoms of depression and suicidal thoughts were found for farm workers with a previous organophosphate poisoning [ 60 ].

3.4.5. Other Risk Factors

Several other risk factors and symptoms predictive of psychological distress in farmers have been identified by researchers, such as government policies [ 5 , 17 , 18 , 22 , 67 , 77 ], isolation [ 9 , 17 , 18 , 37 , 163 ], heavy workload [ 7 , 37 ], role conflict [ 7 , 16 ], time pressure [ 7 , 67 , 79 ], poor housing conditions [ 11 , 22 , 32 , 66 ], foot and mouth disease among livestock [ 57 , 61 , 80 , 164 ], coal and gas development [ 165 , 166 ], beef crisis [ 167 , 168 ], lower levels of mindfulness and farmers’ work ability [ 78 ]. Overall these risk factors were stated in almost 42% of the identified studies on farmers’ mental health. Other agricultural stressors which have been identified to be common in developing countries include poor agricultural extension services/contact, poor road infrastructure, unfavourable market prices, poor access to market information, and poor access to credit facilities [ 36 ].

3.5. Socio-Demographic and Farm Characteristics Associated with Mental Health

We concentrate here on three of the most identified socio-demograhic and farm characteristics cited in our systematic review that have been investigated with farmer mental health, namely: gender issues (particularly for female farmers), age, and farming system type.

The literature has mainly focussed on male farmers’ mental health, even though farm women usually engage in several farm roles, which include farm labour/management, household duties and childcare [ 169 ]. Overall, our review suggested that female farmers experience more psychological distress than male farmers [ 14 , 16 , 21 , 30 , 50 , 59 , 62 , 77 , 80 , 170 , 171 ]. However, a few studies found otherwise [ 13 , 172 ]. Role conflict between farm and home roles, and the absence of husband support are all potential risk factors [ 48 ]. Berkowitz and Perkins [ 173 ] found that farm women who are in conflict with their husbands about farm roles, or are unhappy with their marriages, are more likely to report stress related health symptoms. Female farmers whose husbands worked more hours on the farm reported higher depressive symptoms [ 96 ]. Farm women’s depressive symptoms have also been found to be positively associated with perceived racial or ethnic discrimination and family conflict [ 174 , 175 ]. Alston et al. [ 176 ] found a significant increase in women’s work hours reflected their emotional distress; also that farm women are more likely to talk about their partner’s health and ignore their own. Pattnaik et al. [ 177 ] also described the feminization of agriculture as the feminization of agrarian distress.

Similar to male farmers, pesticide exposure, economic hardship and worrying about finances has often been identified as significant risk factors for female farmers’ mental health [ 14 , 16 , 30 , 67 , 129 , 174 , 178 ]. This may be a result of women undertaking additional on-farm work because of a reduction in farm paid labour [ 2 ]. Carruth and Logan [ 152 ] found that women were more likely to report depressive symptoms if they reported driving a tractor, using pesticides, and if they had a recent farm-related injury. Beseler et al. [ 51 ] found an increase in the risk of depression among women with a history of pesticide poisoning. Lu [ 178 ] examined pesticide exposure based on the duration of pesticide use amongst Philippines farmers, and reported the mean duration of pesticide exposure of 14.2 years for males and 15.4 years for females, resulting in mental and physical abnormalities in 5.4% of males and 13.3% of females. In addition, a lack of family support and listening to loud machines were also predictors of poor female mental health [ 14 ]. Alpass and collegues [ 67 ] found that farm women experienced higher levels of stress in trying to understand new farming technologies.

Age of farmers and the association with mental health issues has been discussed in-depth in the literature. Overall, younger farmers experienced higher levels of stress-related symptoms [ 62 , 85 , 88 , 179 ]. This was most likely associated with higher debt levels. However, Çakmur [ 66 ] found that the frequency of depressive symptoms was higher among farmers who were 35 years or older. It has also been found that there are more mental impairments observed with aging farmers [ 96 , 97 , 100 , 129 , 180 ]. Polain et al. [ 181 ] found that older farmers felt an irresistible sense of loss during prolonged drought compared with younger farmers. Scarth et al. [ 162 ] found a farmer’s depressive symptoms were not significantly related to their age. In addition, lower education levels [ 13 , 61 , 66 , 77 , 82 , 91 , 161 , 165 , 179 ], being married and having marital stress [ 16 , 82 , 141 ], and not living in a joint family [ 82 ], were associated with poorer farmer mental health.

The association with farm type (system used—such as organic farming and industry type) was also a considerable focus in the literature [ 182 ]. A study on comparing the self-reported psychological health of workers on organic and conventional horticultural farms by Cross et al. [ 183 ] showed no significant difference. However, using scores from the Short Depression Happiness Scale, organic farmers were significantly happier than conventional farmers. Similar self-reported questionnaire survey by Khan et al. [ 184 ] on 200 conventional and 157 organic farmers in Indiana, USA, found conventional farmers demonstrated a significantly higher frequency of neurological symptoms and depression problems. Similar results were found in Australian irrigation [ 182 ]. However, Brigance et al. [ 185 ] indicated that some of the risk factors that affect the mental health of organic farmers—e.g., economic insecurity, long hours of work, social isolation, and unpredictable weather conditions—are the same as the mental risk factors for conventional farmers. A recent qualitative study by Soto Mas et al. [ 186 ] on health issues in organic farming argue that although exposure to hazardous pesticides is lower amongst organic farmers, organic farming mostly relies on a few people performing a lot of tasks for cultivation, harvesting, and distribution. This issue can increase psychological and physical risk factors for organic farmers.

3.6. Barriers to Help-Seeking Behaviour

The final area that our systematic review covered was identifying barriers to farmers’ help-seeking behaviour. Not many of the identified studies (only 9 studies, 5% of total) reported help seeking barriers among farmers. Farmer stress and exhaustion of an individual farmer is often hidden, which may delay help-seeking behaviour [ 37 ]. Help-seeking is an active search for a relief or cure to fulfil a need and is a complex decision-making process especially for persons suffering from mental disorders [ 187 ]. Usually lack of knowledge or the belief that a person should deal with his or her mental problems alone were common reasons that decrease the possibility of individuals’ help-seeking [ 9 , 58 , 179 ]. Lack of access to mental health services in rural areas was another major burden to the delivery of appropriate mental health services [ 20 , 33 , 155 ]. Polain et al. [ 181 ] found that usually, older farmers try to access mental health support; however, practical and cultural barriers often prevented them from succeeding. Singh et al. [ 148 ] identified that existing policies were impractical and conflicts between various policies and other safety programmes were common barriers to implementation. Other barriers included farmer self-reliance, social image/stigma, negative perceptions of health professionals’ efficacy and high treatment fees [ 9 , 20 ]. Staniford et al. [ 9 ] and Brew et al. [ 58 ] found that farmers were half as likely to visit general practitioners or mental health professionals in the last 12 months as compared to non-farmers. Farmers often stated that it was better to manage themselves rather than access help for physical or mental health needs. Also, it has been argued that while the traditional masculine hegemony of male farmers can be a benefit to them during good times, in times of heightened stress (like drought), it can lead them to fail to address their mental health needs [ 188 ].

4. Discussion

This study systematically reviewed relevant research (n = 167) in order to identify the key risk factors on farming communities around the world and summarize the state of knowledge about farmer mental health. Studies reviewed were undertaken in 34 different countries, using several different assessment tools. Of the identified papers, the majority used quantitative approaches and most of them were undertaken within the past 10 years, showing increasing interest in farmers’ mental health issues, both in developed and developing countries.

Elevated levels of mental disorder within farming populations were identified by many studies e.g., [ 6 , 33 , 130 , 131 , 152 ]. However, it is also important to note that there is mixed evidence regarding the prevalence of whether mental health was worse in farmers as compared to non-farmers, but a larger portion of studies identified that psychological health disturbances were more common in farmers and farm-workers.

The most reported risk factors for farmers respectively were daily pesticides exposure [ 110 , 189 ], financial problems [ 37 , 129 ], unpredictable climate [ 139 , 143 ], and past injuries [ 52 , 66 ]. Furthermore, machinery breakdown [ 67 ], hearing loud machines [ 14 ], time pressure [ 79 ], and governmental regulations [ 6 ] were other identified risk factors. These conditions potentially make farmers more vulnerable to mental health problems. Outcomes included loss of self-esteem, withdrawal from social/community activity, relationship breakdown, hopelessness, nervousness, inability to function in occupational roles, feelings of suffocation, fatigue, insomnia, loss of control violence, and substance abuse.

The US represents the country with the highest number of farmer mental health studies, followed by Australia. American researchers were mostly focused on the associations between financial problems and farmer mental health, which has been driven by the fact that the US experienced several agricultural crises in the past few decades. Australian researchers were also concerned with financial influences impact on farmer mental health [e.g., 182]; however, Australian studies undertook the largest amount of research on climate and weather stresses for farmers, probably due to the Millennium Drought conditions in Australia in the 2000s which triggered much mental health research [ 188 , 190 , 191 ].

Most of the studies included in the systematic review used cross-sectional design (92%). The cross-sectional design prevented researchers from making strong inferences about causality and the directionality of effects reported in the studies, as the data observe the study population at only one point in time. Although several key risk factors assessed in the selected studies were significantly associated with farmer mental health status, it is unclear whether farmer stress dimensions were the primary drivers of psychological illness outcomes or not. Longitudinal research might overcome these limitations, by illustrating over the longer time, how mental distress, depression, and anxiety are connected with environmental, social and economic pressures. Also, there is a need to study the association between natural capital factors (e.g., type of farming—regenerative, organic, impact of the environment) and mental distress over the long-term, given emerging research in this space [ 182 ].

Similarly, greater consistency in assessment tools used to examine mental disorder prevalence rates among farmers may be beneficial for future research. The assessment tools used in the reviewed studies varied widely. While each of these tools may be reliable and valid indicators of clinically relevant mental disorders, they may not be directly comparable. As shown in this systematic review, farm environments (weather, environment, etc.) can significantly impact farmer health both mentally and physically. One area that will need further research in the future, is the link between climate variability, rainfall deficiency and severe drought across the world. There is a clear need for more longitudinal research in this space.

While there is extensive evidence that farming is a complex and demanding occupation with various risk factors, we suggest that access to primary care and specialist ongoing services for rural and remote communities needs greater priority. There is an argument that the impact of mental health issues for those living in rural areas is greater because many of the stresses are not paid sufficient attention, since mental health professionals are not as common in rural areas and because considerable barriers stop farmers help-seeking for mental health problems [ 9 ]. Formal help-seeking for mental health problems requires that individuals first be able to recognise that a mental health problem exists, and secondly to believe that seeking some help may be beneficial for solving their problem [ 192 ]. Limited studies to date have investigated help-seeking behaviour among farmers. Future research needs to investigate how to break down the help-seeking barriers amongst farming communities to decrease the risk of their mental disorders, as well as understanding how different types of policies can influence farmer mental health.

While this study has provided useful information to understand the issues surrounding farmer mental health, it is not without limitations. Although using systematic review principles can help researchers structure and focus literature reviews, there might be literature inadvertently missed, particularly grey literature. The issue of identifying causality of risk factors with mental health also needs careful consideration. In addition, there are many other unexamined factors which may affect farmers’ mental health but they are broader in concept and not just related to farmers. One plausible example could be solar radiation exposure for all outdoor workers, resulting in several severe adverse health effects with possible psychological consequences but also a supposed beneficial effect on some psychiatric disorders, such as depression [ 193 ]. Indeed, there might be some therapeutic potential of outdoor activities or being more outdoor vs. indoor, which might be encouraged to improve individuals’ (not specifically farmers) mental health and vitamin D status [ 194 , 195 ], but these aspects were not the specific focus of this study and they are left for future research.

5. Conclusions

The findings of this systematic review support the view that farmers’ mental health issues are a result of a complex interplay between social, environmental, and economic factors. The four most-cited risk influences on farmers’ mental health included pesticide exposure, financial difficulties, climate variabilities/drought, and poor physical health/past injuries. Studies in developed countries dominated the literature, with comparative studies suggesting that farmers generally experienced worse psychological health disturbances. Thus, future social, environmental, financial, and health policy needs to consider how best to address various mental health risk factors in the most effective way, as well as understanding how future adverse impacts from climate change can be addressed. Knowledge of risk factors affecting farmers’ mental issues is essential for reducing the burden of mental illness, hence this research is an important step in synthesising some of these important factors and outlining possible suggestions for prevention, as well as areas for future research.

Acknowledgments

The authors acknowledge the help of three anonymous reviewers whose comments improved this manuscript.

Appendix A. Risk of Bias Assessment Questions

Selection Bias

1. Was administered dose or exposure level adequately randomized?

2. Was allocation to study groups adequately concealed?

3. Did selection of study participants result in appropriate comparison groups?

Confounding Bias

4. Did the study design or analysis account for important confounding and modifying variables?

Performance Bias

5. Were experimental conditions identical across study groups?

6. Were the research personnel and human subjects blinded to the study group during the study?

Attrition/Exclusion Bias

7. Were outcome data complete without attrition or exclusion from analysis?

Detection Bias

8. Can we be confident in the exposure characterization?

9. Can we be confident in the outcome assessment?

Selective Reporting Bias

10. Were all measured outcomes reported?

Other Sources of Bias

11. Were there no other potential threats to internal validity (e.g., statistical methods were appropriate and researchers adhered to the study protocol)?

Author Contributions

All authors discussed the research questions. S.D.Y. searched and screened the literature (under S.A.W. and A.Z.’s supervision) and conducted the literature review, assessment of the quality of the studies, and preliminary analysis. S.D.Y. and S.A.W. drafted the paper, and S.A.W., S.D.Y., and A.Z. participated in revisions.

This work was supported by the Australian Research Council (FT140100773), and a University of Adelaide International Postgraduate Scholarship.

Conflicts of Interest

The authors declare no conflict of interest.

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Published: 30 April 2014

Agriculture: Engage farmers in research

• Tom MacMillan 1 &
• Tim G. Benton 2  

Nature volume  509 ,  pages 25–27 ( 2014 ) Cite this article

2546 Accesses

72 Citations

235 Altmetric

Metrics details

• Agriculture

A new wave of small-scale agricultural innovation will boost yields and protect the planet, contend Tom MacMillan and Tim G. Benton.

Climate change threatens a creaking food system in which harvests are already lagging behind rising demand 1 , 2 . A sustainable supply of food hinges on agricultural innovation, but current investments neglect a key area for improving yields.

Since the 1970s, agricultural research and development (R&D) has invested mainly in a few research institutes equipped with cutting-edge instruments. For example, the Biotechnology and Biological Sciences Research Council, responsible for much of the public research spending in food security in the United Kingdom, invested 27% of its 2010–11 budget in just three institutes. Multinational seed and agrochemical companies invest billions of dollars to develop products in hopes that they will be used by millions of farmers.

This one-size-fits-all approach has had qualified success. In a 2011 analysis 3 , average global crop yields increased by 56% between 1965 and 1985, and by 20% from 1985 to 2005, underpinned by increasing inputs of non-renewable resources.

But advances are slowing. According to a 2013 study 4 , yields have plateaued in some of the world's most important food-producing regions, including east Asia (for rice) and northwest Europe (for wheat). In some countries, yields have declined.

The next wave of innovation must be at smaller scales. What one farmer can do to boost yield or efficiency is not necessarily the same as for a farmer hundreds of kilometres away with different soil, microclimate, topology and methods. How well crops and livestock grow depends on the interaction of genes, management and environment. As weather patterns fluctuate, gains in production will depend ever more on innovating in context. Big knowledge flowing from institute to farm must be complemented by local knowledge.

Enhancing farmers' own R&D could reap big rewards for minimal extra cost. Farmers everywhere are practical experimentalists who understand the idiosyncrasies of their land 5 . Modern agronomy evolved out of practices such as rotating crops to rebuild soil nutrients, fertilizing fields with manure, and adding lime to soil to alter pH. Even technologies not invented by farmers — new kit, seeds or chemicals — are adapted by them to fit their circumstances.

Such essential contributions are rarely recognized in official assessments of agricultural R&D. These count farmers as users, rather than makers, of knowledge. When the US Department of Agriculture tots up the US$20 billion that the global private sector invests annually in agricultural R&D, it does not include that done by farmers 6 . Makers of farm machinery, pesticides, seeds and other 'inputs' invest around 3–11% of their revenue in R&D. Globally, if farmers' innovations were valued at just 0.5% of farming production — worth $4 trillion — that would match formal R&D investment from the private sector.

Some of the best returns can come from helping farmers to assess their own ideas. Until now, such initiatives have been at arm's length from formal science, and almost exclusively in the developing world. Our involvement in a farmer-focused innovation programme in the United Kingdom has convinced us that such participatory R&D could also boost agricultural innovation in rich countries.

Grass-roots research

Farmer-centred approaches are not new. In villages in Kenya, rice fields in Indonesia and other places out of reach from industrialized agriculture, group learning programmes recognize and support farmers as innovators.

The best known of these is the farmer field school approach, in which groups of farmers meet regularly to learn alongside their neighbours. The UN Food and Agricultural Organization set up the first such school in Indonesia in 1989, aiming to reduce rice farmers' reliance on pesticides by enabling them to observe, identify and actively manage pests' natural enemies.

Since then, at least 10 million smallholder farmers have taken part in field schools across Asia, Africa and Latin America. This year, a meta-analysis 7 of 71 projects found that farmers' experiences of these schools vary enormously, with targeted initiatives being more successful than large-scale national programmes. In targeted initiatives, participants gained knowledge, changed practices and consequently netted higher yields and incomes.

Inspired by the approach, a UK programme adapts participatory learning to suit farmers in the industrialized world, who, in many cases, are not short of capital, training or access to knowledge. Piloted in 2012, the Duchy Originals Future Farming Programme is funded by the Prince of Wales's Charitable Foundation, in turn funded by sales of products through the supermarket chain Waitrose. The work is led by two charities, the Soil Association in Bristol (at which T.M. works, and T.B. serves on the programme steering group) and the Organic Research Centre in Newbury. The aim is to help farmers to sharpen their skills as innovators so that they can be more productive with fewer non-renewable inputs — good for the environment and their bottom line.

Groups of 5–15 farmers tackle a problem put forward by a participant and test solutions over up to a year in as many as four workshops on one of their own farms. A facilitator helps to keep meetings on track, and a relevant researcher — crop or animal scientist, agronomist or ecologist — is on hand to advise on experimental design and point out existing studies to avoid redundant work.

So far, 450 UK farmers have piloted 'field labs' for about 20 topics, with results documented publicly online. Their farms range from under a hectare to more than a thousand. Field labs have tested ways to control black grass (a persistent weed that resists herbicides), assessed the economics of keeping hens alive to lay eggs for a second season, and evaluated ways to reduce use of drugs that control liver fluke in sheep.

These field labs do not always provide clear answers because of their small samples and short timescales. Field labs raise scientific standards nonetheless: early evaluation suggests that most farmers who have taken part in field labs are eager to engage with formal research. And some have yielded useful lessons. In one, vegetable growers tested composts that do not include peat (which releases greenhouse gases when mined). In contrast to prevailing views, the farmers deemed these peat-free composts commercially viable. And the agronomists learned how labour savings from easily handled materials can outweigh business benefits of higher germination rates.

Grass-roots R&D projects are cropping up elsewhere in the developed world. A participatory breeding programme sponsored by the European Union (EU) has recruited farmers to develop crops that can be grown more sustainably. Organic and small-scale farmers in Italy and France (and in some developing countries) are testing and selecting varieties of barley, beans, broccoli, maize (corn), tomato and wheat.

Animal scientists in Denmark adapted the farmer field school approach to develop 'stable schools'. Four groups of around five farms each worked together to assess changes to herds' housing, hygiene and milking practices and reduced use of antibiotics 8 . A study funded by the European Commission is evaluating 17 'learning and innovation networks' for sustainable agriculture.

Apps, software and websites that recognize farmers as innovators, not just managers, are also on the rise. In the United States, FarmHack.net is an open-source community in which mainly small-scale farmers share know-how, tools and designs. Recent posts include advice on affordable aerial imaging and guides for repurposing old equipment.

More lessons are coming from the developing world. CABI, an intergovernmental agency, is training community 'plant doctors' who help farmers to identify pests and diseases and to enter the information in open-access databases that could be used to control pests or track epidemics.

Research funders are waking up to the advantages of asking farmers what they need to know. In the United Kingdom, the main farming bodies convened a consultation called Feeding the Future that identified topics such as precision agriculture and animal-disease management as practical priorities 9 . But we believe that field labs could boost farmers' productivity by supporting low-cost innovations that fly below the radars of large research institutions. When farmers produce knowledge, they are more likely to adopt new practices, and their insights are more likely to be relevant to local conditions.

Testing ground

Field labs attract innovative farmers — early adopters who can spread best practices. The challenge now is to evaluate and popularize the approach. In Europe, at least, the moment may have arrived. Linked to the latest round of reforms to the Common Agricultural Policy and the Horizon 2020 research programme, the EU launched the European Innovation Partnership for agricultural productivity and sustainability. It aims to promote bottom-up approaches by linking farmers, researchers, businesses and other stakeholders into groups charged with finding solutions to shared problems. With billions of euros earmarked for food and farming research over the next six years, the impact of this initiative is potentially enormous.

The European Commission has set out principles for this approach. Whether it flies or fails depends how EU member states rise to the challenge. For this initiative to succeed, governments must opt to spend a proportion of their rural development funds on supporting grass-roots training and learning by actual farmers — beyond the established partnerships with farmers' suppliers, customers and political representatives. Governments should back brokerage services that help farmers to team up with relevant researchers on their own terms, and enable them to navigate the maze of bureaucracy that will probably stand between them and this invaluable seed investment.

The time has come to decentralize, diversify, and enrich agricultural R&D. Farmers — not scientists, outreach workers or salespeople — are the essential players in any agricultural innovation system. Helping them will put food on the world's tables.

Challinor, A. J. et al. Nature Clim. Change 4 , 287–291 (2014).

Article   ADS   Google Scholar  

Ray, D. K., Mueller, N. D., West, P. C. &amp; Foley, J. A. PLoS ONE 8 , e66428 (2013).

Article   ADS   CAS   Google Scholar  

Foley, J. A. et al. Nature 478 , 337–342 (2011).

Grassini, P., Eskride, K. M. &amp; Cassman, K. G. Nature Commun. 4 , 2918 (2013).

Standing Committee on Agricultural Research. Agricultural Knowledge and Innovation Systems in Transition (European Commission, 2012).

Fuglie, K. O. et al. Research Investments and Market Structure in the Food Processing, Agricultural Input, and Biofuel Industries Worldwide (US Department of Agriculture, 2011).

Waddington, H. &amp; White, H. Farmer Field Schools: From Agricultural Extension to Adult Education 17 (International Initiative for Impact Evaluation, 2014).

Book   Google Scholar  

Vaarst, M. et al. J. Dairy Sci. 90 , 2543–2554 (2007).

Article   CAS   Google Scholar  

Pollock, C. Feeding the Future (Joint Commissioning Group, 2013).

Download references

Author information

Authors and affiliations.

Tom MacMillan is director of innovation at the Soil Association, Bristol, UK.,

Tom MacMillan

Tim G. Benton leads the United Kingdom's Global Food Security programme and is professor of population ecology at the University of Leeds, UK.,

Tim G. Benton

You can also search for this author in PubMed   Google Scholar

Corresponding authors

Correspondence to Tom MacMillan or Tim G. Benton .

Related links

Related links in nature research.

Agriculture: Steps to sustainable livestock 2014-Mar-05

Solutions for a cultivated planet 2011-Oct-12

Nature special: Can science feed the world?

Related external links

Soil Association: Field labs

Support of Learning and Innovation Networks for Sustainable Agriculture

Rights and permissions

Reprints and permissions

About this article

Cite this article.

MacMillan, T., Benton, T. Agriculture: Engage farmers in research. Nature 509 , 25–27 (2014). https://doi.org/10.1038/509025a

Download citation

Published : 30 April 2014

Issue Date : 01 May 2014

DOI : https://doi.org/10.1038/509025a

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

This article is cited by

A typology to guide design and assessment of participatory farming research projects.

• Douglas Jackson-Smith

Socio-Ecological Practice Research (2023)

Pesticide-free agriculture as a new paradigm for research

• Florence Jacquet
• Marie-Hélène Jeuffroy
• Christian Huyghe

Agronomy for Sustainable Development (2022)

Factors influencing intention to apply spatial approaches to on-farm experimentation: insights from the Australian winegrape sector

• Xinxin Song
• Katherine J. Evans
• Saideepa Kumar

On-Farm Experimentation to transform global agriculture

• Myrtille Lacoste
• Andrew Hall

Nature Food (2021)

Estimating food production in an urban landscape

• Darren R. Grafius
• Jill L. Edmondson
• Philip H. Warren

Scientific Reports (2020)

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing: Anthropocene newsletter — what matters in anthropocene research, free to your inbox weekly.

Determinants for rainwater harvesting adoption: a case study of smallholder farmers in Murang’a County, Kenya

• Original Article
• Published: 17 May 2024
• Volume 10 , article number  126 , ( 2024 )

Cite this article

• Itemo Francis Irungu   ORCID: orcid.org/0000-0001-9379-7220 1 ,
• Rebecca Yegon 1 &
• Faith Milkah Muniale 2  

27 Accesses

Explore all metrics

Rainwater harvesting has been practiced among smallholder farmers for centuries in many parts of the world. Recently, it has gained more attention due to the reported increasing water demand and the need for sustainable water management. Drawing on data from a cross sectional survey of 384 household heads (HH), the research study explored the determinants for rainwater harvesting among smallholder farmers in Murang’a County, Kenya. Multistage random sampling technique was employed during the survey using KOBO collect software for data collection. The findings revealed that socio-economic, socio-demographic and institutional factors significantly influenced the adoption of rooftop RWH, mulching, terraces, infiltration pits, retention ditches, water bunds, water pans, dams, furrows, negarims and deep ploughing among HH in Murang’a County. The multivariate probit model results showed that household head’s access to credit facilities, land ownership, age, level of income, education level, gender, family size, source of income, membership to farmers’ groups and access to training services positively influenced rainwater harvesting (RWH) adoption. Similarly, HH membership to farmers group(s) had merits including: social ties, source of information and source of credit which were also key determinants to RWH adoption in the area. The findings of the present study recommends the relevant stakeholders to carry out training to HH on RWHTs, creation of awareness among youths on merits for RWH adoption, encourage HH to join farmers’ groups and encourage partnership with credit facilities in RWHTs adoption among HH in the region. Results of the present study provide valuable insights into the determinants for rainwater harvesting among smallholder farmers in Murang’a County which can be used to inform policy and practice for widespread adoption.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Similar content being viewed by others

Responses of rural livelihood with limited access to water resources: a case from water-scarce region of West Bengal, India

Planning for Effective and Sustainable Water Access and Provision in QwaQwa Through the UN Sustainable Development Goals

Sustainability of drinking water and sanitation delivery systems in rural communities of the Lepelle Nkumpi Local Municipality, South Africa

Data availability.

All the relevant data for this study was included in the paper and is available upon reasonable request.

Adhikari SP, Timsina KP, Lamichhane J (2018) Adoption and impact of rain water harvesting technology on rural livelihoods: the case of Makwanpur district, Nepal. Rural Exten Innov Syst J 14(1):34–40

Google Scholar  

ADP (2019) Murang’a County Government Annual Development Plan 2018/2019.

Akroush S, Dehehibi B, Dessalegn B, Al-Hadidi O, Abo-Roman M (2016) Factors affecting the adoption of water harvesting technologies: a case study of Jordanian Arid area. Sustain Agri Res 6(1):80. https://doi.org/10.5539/sar.v6n1p80

Article   Google Scholar  

Alam MN (2015) Effect of farmers socio-economic toward adoption level of agricultural technology in Sigi Regency Indonesia. J Appl Sci 15(5):826–830

Andati P, Majiwa E, Ngigi M, Mbeche R, Ateka J (2022) Sustainable technology and entrepreneurship. Sustain Technol Entrep 1(2):1–11. https://doi.org/10.1016/j.stae.2022.100017

Baiyegunhi LJS (2015) Determinants of rainwater harvesting technology (RWHT) adoption for home gardening in Msinga, KwaZulu-Natal. South Africa Water SA 41(1):33–40. https://doi.org/10.4314/wsa.v41i1.6

Bartlett JE, Kotrlik JW, Higgins CC (2001) Organizational research: determining appropriate sample size in survey research. Inf Technol, Learn Perform J (Spring). 19(1):43–50

Belachew A, Mekuria W, Nachimuthu K (2020) Factors influencing adoption of soil and water conservation practices in the northwest Ethiopian highlands. Int Soil Water Conserv Res 8(1):80–89. https://doi.org/10.1016/j.iswcr.2020.01.005

Bitok EK, Nyariki DM, Amwata DA (2023) The nature and extent of adoption of climate-smart agriculture technologies in Murang ’ a County, Kenya : a case of Kiharu Constituency. J Emerg Technol Innov Res 10(9):1–12

Black J, Maimbo M, Alex O, Kipruto C, Meshack N (2012) Rainwater harvesting inventory of Kenya: an overview of techniques, sustainability factors, and stakeholders. Nairobi: ICRAF.

Bryan E, Ringler C, Okoba B, Roncoli C, Silvestri S, Herrero M (2013) Adapting agriculture to climate change in Kenya: Household strategies and determinants. J Environ Manage 114:26–35. https://doi.org/10.1016/j.jenvman.2012.10.036

CIDP (2018) Murang’a County Integrated Development Plan (Issue May 2018).

García-Ávila F, Guanoquiza-Suárez M, Guzmán-Galarza J, Cabello-Torres R, Valdiviezo-Gonzales L (2023) Rainwater harvesting and storage systems for domestic supply: an overview of research for water scarcity management in rural areas. Results Eng. https://doi.org/10.1016/j.rineng.2023.101153

Gichangi E, Gatheru M (2018) Farmers’ awareness and perception of climate change and the various adaptation measures they employ in the semi-arid eastern Kenya Climate Change. Clim Change 4(14):112–122

GOK (2006) Murang’a District Short rains assessment 2006 (Issue January). https://reliefweb.int/report/kenya/kenya-muranga-district-short-rain-assessment-2006-12-jan-2006

Jan I (2020) Socio-economic determinants of farmers’ adoption of rainwater harvesting systems in semi-arid regions of Pakistan. J Agric Sci Technol 22(2):377–387

Kalungu J, Filho W, Harris D (2013) Joint Proceedings of the 27th Soil Science Society of East Africa and the 6th African Soil Science Society Conference. Exploring Gender Dynamics on Percetion of Climate Change on Farming with Focus Groups in Machakos and Makueni Counties, Kenya., October, 901.

Kifle T, Ayal DY, Mulugeta M (2022) Factors influencing farmers adoption of climate smart agriculture to respond climate variability in Siyadebrina Wayu District Central Highland of Ethiopia. Clim Serv 26(April):1–10. https://doi.org/10.1016/j.cliser.2022.100290

Kimani M, Gitau A, Ndunge D (2015) Review of rainwater harvesting technologies in Makueni County. Res Inventy Int J Eng Sci 5(2):39–49

KNBS (2019) 2019 Kenya Population and Housing Census volume I : Population by County and Sub-County: Vol. I.

Kpadonou RA, Owiyo T, Barbier B, Denton F, Rutabingwa F, Kiema A (2017) Advancing climate-smart-agriculture in developing drylands: joint analysis of the adoption of multiple on-farm soil and water conservation technologies in West African Sahel. Land Use Policy 61:196–207. https://doi.org/10.1016/j.landusepol.2016.10.050

Lutta AI, Wasonga OV, Nyangito MM, Robinson LW (2020) Adoption of water harvesting technologies among agro—pastoralists in semi—arid rangelands of South Eastern Kenya. Environ Syst Res 9(36):1–12. https://doi.org/10.1186/s40068-020-00202-4

Maindi NC, Osuga IM, Gicheha MG (2020) Advancing climate smart agriculture: adoption potential of multiple on-farm dairy production strategies among farmers in Murang’a County, Kenya. Livest Res Rural Dev 32(4):1–9

Mairura FS, Musafiri CM, Kiboi MN, Macharia JM, Ng’etich OK, Shisanya CA, Okeyo JM, Mugendi DN, Okwuosa EA, Ngetich FK (2021) Determinants of farmers’ perceptions of climate variability, mitigation, and adaptation strategies in the central highlands of Kenya. Weather Clim Extremes 34:100374. https://doi.org/10.1016/j.wace.2021.100374

Mangisoni JH (2019) Determinants of adoption of rainwater-harvesting technologies in a rain shadow area of southern Malawi. Afr J Agric Resourc Econ 14(2):106–119

Mango N, Makate C, Tamene L, Mponela P, Ndengu G (2018) Adoption of small-scale irrigation farming as a climate-smart agriculture practice and its influence on household income in the Chinyanja Triangle. Southern Africa Land 7(2):1–19. https://doi.org/10.3390/land7020049

Mekuria ZK, Amede AK, Mekonnen EE (2020) Adoption of rainwater harvesting and its impact on smallholder farmer livelihoods in Kutaber district, South Wollo Zone Ethiopia. Cogent Food Agric 6(1):1–19. https://doi.org/10.1080/23311932.2020.1834910

Motho M, Kolawole OD, Motsholapheko MR, Mogomotsi PK (2022) Influence of household demographic and socio-economic factors on water demand in Ngamiland District Botswana. Water Sci 36(1):48–59. https://doi.org/10.1080/23570008.2022.2048581

Mpatane O, Kayombo B, Patrick C, Malope P, Tapela M, Planning L, Resources N (2016) An assessment of socio-economic potential for Rain Water Harvesting ( RWH) in semi-arid Bobirwa Sub-district of Eastern Botswana. Afr J Rural Dev 1(1):99–106

Muchai SWK, Ngetich FK, Baaru M, Mucheru-Muna MW (2020) Adoption and utilisation of Zai pits for improved farm productivity in drier upper eastern Kenya. J Agric Rural Dev Tropics Subtropics 121(1):13–22. https://doi.org/10.17170/kobra-202002281030

Murgor FA, Owino JO, Cheserek GJ, Saina CK, Author C, Cheserek GJ (2013) Factors influencing farmers ’ decisions to adapt rain water harvesting techniques in Keiyo District, Kenya. J Emerg Trends Econ Manag Sci 4(2):133–139

Musa CM, Kiboi M, Macharia J, Ng OK, Kosgei DK, Mulianga B, Okoti M, Ngetich FK (2022) Adoption of climate-smart agricultural practices among smallholder farmers in Western Kenya: do socioeconomic, institutional, and biophysical factors matter? Heliyon 8:1–8. https://doi.org/10.1016/j.heliyon.2021.e08677

Mwaura J, Koske J, Kiprotich B (2018) Economic value of water harvesting for climate-smart adaptation in semi-arid Ijara Garissa, Kenya. Environ Syst Res. https://doi.org/10.1186/s40068-017-0088-3

Nabwire TJ.(2020) Assesing the adoption of rainwater harvesting technologies (RWHT) as a coping mechanism to climate variability in Kilifi County, Kenya.

Ngango J, Hong S (2021) Adoption of small-scale irrigation technologies and its impact on land productivity: evidence from Rwanda. J Integr Agric 20(8):2302–2312. https://doi.org/10.1016/S2095-3119(20)63417-7

Ngure MW, Wandiga SO, Olago DO, Oriaso SO (2021) Climate change stressors a ff ecting household food security among Kimandi—Wanyaga smallholder farmers in Murang’a County. Kenya Open Agric 6(1):587–608

Nicholas ES, Ukoha PO (2023) Evaluation of the effect of different conventional roof types and industrial activity on harvested rainwater in Southern Nigeria. Discover Water. https://doi.org/10.1007/s43832-023-00036-y

Odhiambo KO, Iro Ong’Or BT, Kanda EK (2021) Optimization of rainwater harvesting system design for smallholder irrigation farmers in Kenya: a review. Aqua Water Infrastruct Ecosyst Soc 70(4):483–492. https://doi.org/10.2166/aqua.2021.087

Odhiambo KO, Ong’or BTI, Kanda EK (2022) Assessment of rainwater harvesting potential of Rachuonyo North Sub-Catchment in Kenya using the Australian water balance model. J Water Supply Res Technol Aqua. https://doi.org/10.2166/aqua.2022.153

Okello D, Owuor G, Larochelle C, Gathungu E, Mshenga P (2021) Determinants of utilization of agricultural technologies among smallholder dairy farmers in Kenya. J Agric Food Res 6:1–10. https://doi.org/10.1016/j.jafr.2021.100213

Okello Dorothy, Mayega RW, Muhumuza C, Amuge PO, Kakamagi E, Amollo M, Amuku I, Kayiwa R, Bazeyo W (2018) Gender and innovation for climate-smart agriculture Gender and innovation for climate-smart agriculture. CCAFS Working Paper. https://ccafs.cgiar.org/donors .

Ondieki WM, Tonui WK, Kodiwo O, Atamba AA (2019) Assessment of coping and adaptation strategies employed by dairy cattle farmers to counter the effects of rainfall variability in Keumbu division, Kisii County, Kenya. Int J Geogr Geol Environ 1(2):23–27

Reza M, Noer M, Asmawi Y (2018) Benefits of social ties in farmer’s groups at agricultural extension planning in the District of Lima Puluh Kota Indonesia. Int J Agric Exten 6(01):17–24. https://doi.org/10.33687/ijae.006.01.2416

Röhrig F, Schümmelfeder M, Schaller M, Barth E, Blies D (2017) Climate Smart Agriculture ( CSA): Conservation Agriculture (CA). Clim Dev 12(14):1–4

Sombroek WG, Braun HM, Van der Pouw BJ (1982) Exploratory soil map and agro-climatic zone map of Kenya, 1980. Scale 1: 1,000,000. Kenya Soil Survey.

Teklewold H, Mekonnen A, Kohlin G, Falco DI, S. (2017) Does adoption of multiple climate-smart practices improve farmers’ climate resilience? Empirical evidence from the Nile Basin of Ethiopia. Clim Change Econ. https://doi.org/10.1142/S2010007817500014

Tesfaye SS (2017) Determinants of Adoption of Sustainable Land Management (SLM) Practices among Smallholder Farmers’ in Jeldu District, West Shewa Zone, Oromia Region, Ethiopia. Journal of Resources Development and Management. 30(1): 2422–8397. https://globaljournals.org/GJSFR_Volume17/5-Determinants-of-Adoption.pdf

The World Bank Annual Report 2016 (2016) In The World Bank Annual Report 2016. https://doi.org/10.1596/978-1-4648-0852-4

Theis S, Lefore N, Meinzen-Dick R, Bryan E (2018) What happens after technology adoption? Gendered aspects of small-scale irrigation technologies in Ethiopia, Ghana, and Tanzania. Agric Hum Values 35(3):671–684. https://doi.org/10.1007/s10460-018-9862-8

Timothy S, Lokina R, James Mgale Y, Dimoso P (2022) What matters in adoption of small-scale rain water harvesting technologies at household level? Evidence from Charco-dam users in Nzega Tanzania. Cogent Food Agric 8(1):1–17. https://doi.org/10.1080/23311932.2022.2112429

Article   CAS   Google Scholar  

Waaswa A, Nkurumwa AO, Kibe AM, Waaswa A (2021) Climate-smart agriculture and potato production in Kenya: review of the determinants of practice determinants of practice. Clim Dev. https://doi.org/10.1080/17565529.2021.1885336

Wamunyu ME, Bett EK, Macharia I (2017) Impact of group microcredit lending on maize productivity among the small holder farmers in Murang’a County Kenya. J Agric 1(1):15–31

WorldBank (2023) World Bank Country and Lending Groups. https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups

Download references

Acknowledgements

The authors thank Kiharu Sub-County Agricultural Officers under Murang’a County government, Kenya for their warm support. The co-author thanks University of Embu for the scholarship award to pursue his postgraduate studies. We also thank the enumerators who assisted in data collection exercise and household heads from Murarandia, Mugoiri and Weithaga administrative wards in Kiharu Sub-County for their participation in the survey.

Author information

Authors and affiliations.

Department of Water and Agricultural Resource Management, University of Embu, P.O. Box 6-60100, Embu, Kenya

Itemo Francis Irungu & Rebecca Yegon

Programmes Manager, Tropical Biology Association, P.O. Box 112-20107, Njoro, Kenya

Faith Milkah Muniale

You can also search for this author in PubMed   Google Scholar

Contributions

The main idea of this research paper was generated by the corresponding author Francis Irungu Itemo. Later the author conceptualized the study, carried out data collection, data analysis, interpreted data and wrote the first version of the manuscript and more comments were added by the second and third authors respectively. Dr. Rebecca Yegon was the second author who took part in study conceptualization, ideas generation, data interpretation and commented on the second version of the manuscript. Dr. Muniale Faith Milkah took part in idea generation, study conceptualization, data interpretation and contributed in making comments to the final version of the manuscript.

Corresponding author

Correspondence to Itemo Francis Irungu .

Ethics declarations

Conflict of interest.

All authors declared no personal or any financial competing interests for the research work reported in this study.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Irungu, I.F., Yegon, R. & Muniale, F.M. Determinants for rainwater harvesting adoption: a case study of smallholder farmers in Murang’a County, Kenya. Sustain. Water Resour. Manag. 10 , 126 (2024). https://doi.org/10.1007/s40899-024-01104-4

Download citation

Received : 05 May 2023

Accepted : 06 May 2024

Published : 17 May 2024

DOI : https://doi.org/10.1007/s40899-024-01104-4

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Agricultural water harvesting
• Multivariate probit model
• Rainwater harvesting technologies
• Smallholder farming
• Socio-demographic determinants
• Socio-economic determinants
• Find a journal
• Publish with us
• Track your research

• Skip to main content
• Keyboard shortcuts for audio player

Researchers aim to figure out how to harvest food and electricity off the same land

Frank Morris

Solar farms generate resistance from neighbors worried about changing the agricultural landscape. So a team in Iowa is working on a way to grow food and harvest solar power on the same acreage.

Copyright © 2024 NPR. All rights reserved. Visit our website terms of use and permissions pages at www.npr.org for further information.

NPR transcripts are created on a rush deadline by an NPR contractor. This text may not be in its final form and may be updated or revised in the future. Accuracy and availability may vary. The authoritative record of NPR’s programming is the audio record.

Impact story

Food forests; a sustainable option for agriculture

Within a couple of years, hundreds of food forests have been planted in the Netherlands. They produce food and at the same time contribute to many different ecosystem services. To what extent do food forests contribute to major agricultural issues, such as climate change, the nitrogen problem, biodiversity restauration, as well as water retention and buffering? And is there a revenue model for the farmer? WUR contributes by working on these fundamental questions about the value of food forests.

Agroforestry vs food forestry

The government is convinced of the advantages: the ambition is to have realized 25,000 hectares of agroforestry of which a 1,000 hectares of food forests in the Netherlands by 2030. Farmers mostly grow annual crops. Agroforestry combines annual crops or, for example, keeping cattle with perennials. This is done by, for example, planting rows of trees between fields of grain. The trees have positive effects on the annual crops because they provide shade, wind protection and root deeper. That helps limiting evaporation during droughts and drainage in events of heavy rainfall besides also storing CO 2 . Food forestry takes it a step further. These multi-layered perennial systems mimic a forest ecosystem, growing many different species that produce edible fruits, nuts, leaves, roots, herbs and seeds. Manure and pesticides are not needed, and it has a potential to restore soil while providing some food security through diversity of harvestable products all year round.

Food forests are a new phenomenon in the Netherlands: the most well-known food forest in Groesbeek was only planted in 2009. Meanwhile, hundreds of small initiatives, initiated by enthusiasts, have started. Slowly on also lager scale commercial food forest of 5 hectares and more are starting off. The Dutch association of food forests includes all current locations on a map (Dutch).

Challenging alternative for farmers

The government’s aim is ambitious but promising, because it is linked to the objective of planting more forests in the Netherlands. As space is scarce in the Netherlands, land with a current agricultural use is also part of the search area. To meet the ambitions by planting trees on arable land, farmers will have to be seduced to integrate trees in their agricultural system. In a food forest, the most complex agroforestry system, the earning model is possibly most challenging. Return on investments will take (a lot) more time compared to annual crop agricultural systems. Although a food forest will in time produce in abundance, it will approximately take up to 10 years before a food forest starts producing serious volumes. However, at the same time there is no need for crop protection products and (chemical) fertilizer and no seasonal preparing the soil with heavy machinery for ploughing and sowing. As part of the research concerning food forests students developed a calculation tool (Dutch) in which farmers and banks can enter factors such as investments, costs, picking performance and yields per plant. Other possible forms of yield, such as the contribution to biodiversity and education are also part of the tool. That is how a bridge is created between the knowledge and the actual application.

What's more, harvesting in food forests is done by hand and often with volunteers. The food forests in Almere and Schijndel were developed with a research ambition in mind. The planting scheme was designed as such that future small machine harvesting is possible. Developing these machines is one of the fields of research right now. Since many of the food forests are still in the build-up phase, it is also necessary to consider foraging damage and other problems that come with this early stage. WUR students have developed several proposals for this, some already applied in practice, in an Academic Consultancy Training assignment Food for thought .Another challenge is the danger of introducing invasive species. In WUR research (Dutch) it is recommended to use a negatives list. In conclusion, there are still plenty of challenges and questions, but also huge potential.

Food forests have a potentially important role to play in making the overall agricultural system more robust. It deserves a place alongside other forms of sustainable agriculture. This project teaches us to what level food forests can contribute to food production, biodiversity, climate mitigation (carbon sequestration) and climate adaptation (adapting to the effects of climate change). WUR is an important partner for fundamental and applied research on food forests. Together with research partners, WUR contributes to the development of successful food forests that provide their own pest control, build fertility, produce food, and are climate robust.

Part of this article has previously appeared in TO2 magazine. Information has been added according to new developments within the research.

Biodiversity: Native trees on Canterbury farms could bring birdsong back - research

Share this article

Dr Sara Kross, a University of Canterbury senior lecturer, is leading research into how native hedgerows and shelterbelts on farms could help boost biodiversity.

Canterbury researchers are exploring how planting native shelterbelts and hedgerows on farms could deliver biodiversity benefits and make good business sense.

While stands of weather-worn macrocarpa and pine are still a common sight in rural Canterbury, a growing number of farmers are planting native trees on their land.

Conservation biologist Dr Sara Kross is leading a series of projects aimed at better understanding this trend.

Kross is a senior lecturer in the School of Biological Sciences at Te Whare Wānanga o Waitaha University of Canterbury .

Her team is investigating how the conservation and rewilding potential of increased native planting can coexist alongside the commercial imperatives of farming.

Non-crop planting features such as shelterbelts, hedgerows, and bush blocks are of particular interest to the researchers.

“These features provide shelter for crops and livestock, as well as preventing erosion and runoff,” Kross said.

“But they’re also important for biodiversity and because those habitats exist at the field margin there’s a lot more interaction with the farmland and the way it’s managed.”

Kross sees huge potential for farmers to assist in the establishment of green corridors of native plantings across Canterbury.

These pathways of habitats can provide food, water, nesting, breeding, and migration sites for native species including birds, lizards, and invertebrates.

While this could significantly improve biodiversity on the plains, Kross acknowledged this goal could be at odds with the commercial side of farming.

“Most farmers are really passionate stewards of their land and want to leave it in better condition,” she said.

“At the same time, their farms are businesses and that creates a hierarchy of needs.”

She hoped the new research would show that improving biodiversity and meeting economic goals needn’t be mutually exclusive.

Encouragingly, similar research from around the world has shown an overall positive impact for farmers who develop native habitats on farm margins.

“There aren’t just ethical or aesthetic reasons to plant natives,” Kross said.

“It has the potential to deliver real production and financial benefits in the long run.”

While it’s not currently known how much Canterbury land is planted in non-crop features, an early part of the research will involve University of Canterbury PhD student Mary Buford Turnage using remote sensing technology to map existing plantings.

“We’re hoping to use methods that will allow us to differentiate between the native hedgerows and the exotic shelterbelts,” Kross said.

“That will also help us to see where the gaps are and to map connectivity.”

Several plant nurseries now specialise in advising farmers in the choice of natives to suit their requirements.

Dairy farmers might select low-growing natives like flaxes, coprosmas or pōhuehue (muehlenbeckia) for hedgerows in the centre of pasture, so that pivot irrigators can move across them.

Fast-growing natives can be used for shelterbelts at the edges of fields, to provide weather protection for stock and to enable slower-growing natives to become established.

Though their research is still in the early stages, Kross’ team has already discovered some farmers who want to bring native birdsong back to the plains.

“We went door-knocking in the Methven area in January and found two great locations that one farmer was managing,” she said.

“He’d put in native hedgerows around 10 years ago, and that level of maturity makes it an excellent field site for us.”

Latest from The Country

'An ordeal by fire': Wattie's blaze destroyed one third of factory

OPINION: A 'bigger and better' business rose from the ashes.

Court appearances for Gisborne forestry companies

'Stainless steel cows': Is precision fermentation a threat to Kiwi farmers?

EPA says hydrogen cyanamide 'safe to use' but growers face new rules

Cracking open the truth

Chocolate that harnesses the full potential of the cocoa fruit

Researchers at ETH Zurich have teamed up with the food industry to produce a whole-​fruit variety of chocolate. This helps increase the value creation of cocoa farming -- and is healthier.

For many people, chocolate is a sweet delight: its main components are cocoa mass and cocoa butter, which are extracted from the cocoa fruit. What is less known, however, is that the cocoa fruit contains additional valuable ingredients that have been underutilised until now. Researchers at ETH Zurich have joined forces with the chocolate industry to investigate the potential for making maximum use of the cocoa fruit, which would increase the profitability of cocoa cultivation while making chocolate a healthier indulgence. As part of an Innosuisse project, a research team led by emeritus ETH professor Erich Windhab worked together with start-​up Koa, which is dedicated to sustainable cocoa fruit cultivation, and Swiss chocolate manufacturer Felchlin to develop a recipe for cocoa-​fruit chocolate.

Finding the perfect recipe

Kim Mishra, main author of the external pageNature Foodcall_madestudy, says that the cocoa fruit is similar to the honeydew melon: "These fruits have similar structures. Both have a hard outer shell that reveals the flesh of the fruit when cut open, as well as the cocoa beans or melon seeds and pulp in the interior." Conventional chocolate only makes use of the beans, but the researchers were able to use the flesh and parts of the fruit shell -- or the endocarp, to use the field-​specific term -- for their cocoa-​fruit chocolate recipe. They process it into powder and mix it with part of the pulp to form cocoa gel. This gel substance is extremely sweet and can replace the added powdered sugar that is normally part of the chocolate experience.

However, it was not easy for the scientists to find the perfect recipe for cocoa-​fruit chocolate. They systematically tested the texture of various compositions in the lab. Too much fruit juice extracted from the pulp made for a clumpy chocolate, but too little resulted in an insufficiently sweet product. The research team therefore endeavoured to find the perfect balance between sweetness and texture. The issue with clumping does not arise when using powdered sugar. The experiments showed that chocolate may contain up to 20 percent of gel, which equivalates to the sweetness of chocolate with 5 to 10 percent powdered sugar. In comparison, conventional dark chocolate can easily contain between 30 and 40 percent powdered sugar.

To test the sensory experience of the new recipes, trained panellists from the Bern University of Applied Sciences taste-​tested pieces of chocolate weighing 5 grams each, with some containing various amounts of powdered sugar and others containing the new variety sweetened with cocoa gel. "This allowed us to empirically determine the sweetness of our recipe as expressed in the equivalent amount of powdered sugar," says Mishra.

Healthy, sustainable and good for farmers

By using cocoa gel as a sweetener, cocoa-​fruit chocolate boasts a higher fibre content than your average European dark chocolate (15 grams versus 12 grams per 100 grams). It also contains only 23 grams of saturated fat as opposed to the usual 33 grams. This means that ETH researchers were able to increase the fibre content by around 20 percent while reducing the saturated fat percentage by around 30 percent. "Fibre is valuable from a physiological perspective because it naturally regulates intestinal activity and prevents blood sugar levels from rising too rapidly when consuming chocolate. Saturated fat can also pose a health risk when too much is consumed. There's a relationship between increased consumption of saturated fats and increased risk of cardiovascular diseases," explains Mishra.

Small-​scale farmers can diversify their product offerings and increase their income if other components of the cocoa fruit can be marketed for chocolate production instead of just the beans. And if most of the fruit can be used to produce cocoa-​fruit chocolate, only the shell remains, which is traditionally used as fuel or composting material. "This means that farmers can not only sell the beans, but also dry out the juice from the pulp and the endocarp, grind it into powder and sell that as well," explains Mishra. "This would allow them to generate income from three value-​creation streams. And more value creation for the cocoa fruit makes it more sustainable."

This doesn't mean that cocoa-​fruit chocolate will be hitting grocery store shelves anytime soon, however. "Although we've shown that our chocolate is attractive and has a comparable sensory experience to normal chocolate, the entire value creation chain will need to be adapted, starting with the cocoa farmers, who will require drying facilities," says Mishra. "Cocoa-​fruit chocolate can only be produced and sold on a large scale by chocolate producers once enough powder is produced by food processing companies." The first step has been taken: ETH has filed a patent for its cocoa-​fruit chocolate recipe. The development of cocoa-​fruit chocolate is a promising example of how technology, nutrition, eco-​compatibility and income diversification for small farmers can all work in tandem to improve the entire value-​creation chain of the cocoa plant.

• Food and Agriculture
• Agriculture and Food
• Insects (including Butterflies)
• Marine Biology
• Evolutionary Biology
• Palomino horse
• Sugar Glider
• Seedless Fruit

Story Source:

Materials provided by ETH Zurich . Original written by Deborah Kyburz. Note: Content may be edited for style and length.

Journal Reference :

• Kim Mishra, Ashley Green, Johannes Burkard, Irina Gubler, Roberta Borradori, Lucas Kohler, Johannes Meuli, Ursina Krähenmann, Jotam Bergfreund, Armin Siegrist, Maria Schnyder, Alexander Mathys, Peter Fischer, Erich J. Windhab. Valorization of cocoa pod side streams improves nutritional and sustainability aspects of chocolate . Nature Food , 2024; DOI: 10.1038/s43016-024-00967-2

Cite This Page :

Explore More

• Symbiotic Bacteria Communicate With Plants
• Birdsong and Human Voice: Same Genetic Blueprint
• Molecular Dysregulations in PTSD and Depression
• Look, Then Listen to 1 Person in a Crowd: AI
• Predicting Individual Cancer Risk
• Sexual Parasitism Helped Anglerfish Enter ...
• Treating Cataracts and Other Eye Conditions
• Early Arrival of Palaeolithic People On Cyprus
• Networks Regulating Gene Function in Human Brain
• Birth of Universe's Earliest Galaxies

Trending Topics

Strange & offbeat.