A cross-sectional study on the key risk factors affecting farmers’ mental health

INTRODUCTION

Agriculture has long been a cornerstone of global economies, sustaining nations and providing livelihoods for millions. However, the idealized perception of a farmer’s life, deeply connected to the land, is increasingly overshadowed by growing challenges such as market fluctuations, legal changes, climate impacts, and technological advancements, all of which exert significant pressure on farmers’ mental health.¹ The alarming rates of stress, anxiety, depression, and suicide among farmers have drawn global attention, highlighting the broader implications for rural communities, food security, and agricultural sustainability.² Understanding farmers’ mental well-being is not just a moral imperative but essential for safeguarding the future of food production.³ Farmers, who predominantly reside in rural areas, face unique challenges related to healthcare access, economic struggles, and occupational hazards. Increased suicide rates within this group often signal societal pressures, including debt and limited medical support.³ Depression, linked to demanding work conditions, is prevalent among farmers who work long hours with minimal social support.² Moreover, barriers to healthcare access in rural areas, including high costs and logistical challenges, further exacerbate mental health neglect.⁴ In countries like India, where a significant portion of the population lives in rural areas with inadequate healthcare infrastructure, the prevalence of mental health disorders among farmers is likely higher than reported.² This study employs a cross-sectional approach to explore the mental health of farmers, providing insights into the factors influencing their well-being and identifying areas for intervention.⁴

Objectives

Primary objective was to assess the prevalence of depression among farmers and to determine the risk factors affecting the farmer’s mental health status.

Secondary objective was to determine the cause of depression and anxiety among farmers and to educate on the management of stress.

METHODS

Study type and site

This was a non-experimental descriptive cross-sectional study based on a survey conducted among farmers with the aim of determining the factors affecting the mental health of farmers living in villages near Bangalore.

Study population

The study population included farmers living in rural areas of Bangalore.

Inclusion criteria

Farmers without congenital birth defect. Age between 21-60 years. Currently engaged in farming activities. Able to provide informed consent.

Exclusion criteria

Retired or inactive farmers. Individuals unable to complete the survey due to cognitive impairments. Unable to provide informed consent due to some other reasons.

Sample size

A sample size of 153 farmers was targeted to ensure sufficient statistical power to detect significant associations between risk factors and mental health outcomes.

Sampling method

A stratified random sampling technique was employed to ensure representation from different farming sectors (e.g., livestock, crops) and geographical regions.

Data collection methods

Questionnaire

A structured questionnaire was developed, incorporating validated instruments to measure mental health outcomes (e.g., depression, anxiety, and stress scale- DASS-21) and potential risk factors (e.g., socioeconomic status, work-related stress, social support).

Interviews

Semi-structured interviews were conducted with a subset of participants to gain deeper insights into their experiences and coping mechanisms.

Ethical considerations

Participants were provided with detailed information about the study and were required to give written consent. Data were anonymized and stored securely to protect participants’ privacy.

Study duration

The study took place from January to October 2023.

Expected outcomes

Identification of the primary risk factors affecting farmers’ mental health. Recommendations for targeted interventions to support farmers’ mental health. Contribution to the broader understanding of mental health issues in agricultural communities.

Statistical analysis

Data were entered into Microsoft Excel spread sheets and cross checked for its accuracy. The statistical analysis was performed using IBM SPSS statistics software for windows, version 22 (Armonk, NY, USA).

Data analysis

Descriptive statistics

To summarize the characteristics of the study population and prevalence of mental health issues.

Inferential statistics

The chi-square tests and phi coefficients have been used to indicate associations between several risk factors and depression status among farmers and p value of <0.05 was considered as statistically significant.

RESULTS

Socio-demographic characteristics

A total of 153 farmers were surveyed. Of these, 120 (78.4%) were males and 33 (21.6%) females. The mean age of the farmers was approximately 46.41 years and categorized into different groups: 47 (30.7%) aged 21-35 years, 64 (41.8%) aged 36-50 years, and 42 (27.5%) aged 51-60 years. Regarding education, 61 (39.9%) had 1-5^th grade education, another 61 (39.9%) had 6-10^th grade education, and 31 (20.3%) had completed a degree course. In terms of work experience, 35 (22.9%) had 1-15 years, 61 (39.9%) had 16-30 years, 45 (29.4%) had 31-45 years, and 12 (7.8%) had 46-60 years of experience. Financially, 13 (8.5%) were struggling, 96 (62.7%) had average income, and 44 (28.8%) were well-off. Concerning substance use, 33 (21.6%) were alcoholics, 47 (30.7%) were smokers and 73 (47.7%) had no habits. All the socio-demographic characteristics are detailed in the Table 1.

Associations between several risk factors and depression status among farmers

The chi-square tests and phi coefficients indicate significant associations between several risk factors and depression status among farmers. Age group, gender, work experience, financial status, and substance use all show significant chi-square values (p<0.05), suggesting these factors are associated with depression. Specifically, the phi coefficients for these variables range from 0.214 to 0.320, indicating weak to moderate relationships. Education level, however, showed no significant association with depression (p>0.05), with a very weak phi coefficient (0.082). These results suggest that demographic, financial, and behavioral factors significantly influence depression rates among farmers (Table 2).

DISCUSSION

A study conducted on 153 farmers reveals significant associations between various socio-demographic factors and depression. Chi-square tests and phi coefficients ranging from 0.214 to 0.320 indicate that older age, male gender, longer work experience, financial instability, and substance use (alcohol and smoking) were significantly correlated with higher rates of depression. These findings align with other studies.^5,6 Notably, our study identified middle-aged farmers as the most depressed group, contrasting with other research indicating that younger farmers experience higher stress levels due to debt.^7,8 Çakmur found higher depressive symptoms in farmers aged 35 and older, and aging has been linked to increased mental impairments.^9-12 Polain et al noted that older farmers feel a profound sense of loss during prolonged droughts, unlike younger farmers, while Scarth et al.^13,14 reported no significant age-related differences in depressive symptoms among farmers. Financial burden emerged as a critical factor in our study, corroborated by 39 articles highlighting the negative impact of financial challenges on farmers’ mental health, particularly when farming is the primary income source.^15-18 Farmers face financial stress from market prices, cash flow issues, increased costs, taxes, healthcare expenses, and high debt.¹⁹ Historical analyses of the 1980s farm financial crisis in the US reveal that declining demand, rising costs, and low commodity prices caused significant psychological distress among farmers, leading to depression, lower life satisfaction, alcoholism, and even suicide.^20,21 In response to financial losses, farmers often make substantial changes to their operations, such as reducing staff, working longer hours, diversifying production, or exiting farming altogether.²² These findings underscore the need for tailored mental health strategies addressing farmers’ unique challenges, including financial support, stress management resources, and substance use interventions to enhance their well-being and mental health outcomes.

Conversely, the study found that education level did not significantly impact depression rates among farmers, evidenced by a very weak phi coefficient (0.082). This suggests that educational attainment, whether basic or advanced, does not play a substantial role in mitigating depression within this demographic. Given that farming relies heavily on practical experience rather than formal education, this result is not entirely surprising. However, it is important to note that other studies have indicated that lower education levels are generally associated with poorer mental health outcomes among farmers.^23-25 These mixed findings underscore the complexity of mental health in the agricultural sector and highlight the need for tailored mental health strategies that address the specific challenges faced by farmers. Such strategies should include financial support, stress management resources, and substance use interventions to enhance their well-being and mental health outcomes.

This study has some limitations. Many farmers faced challenges due to language barriers in communicating their issues effectively. Additionally, a significant number of them were reluctant to openly discuss their problems or reveal the medications they were using, despite consuming various treatments.

CONCLUSION

The findings of this study indicate that demographic, financial, and behavioral factors significantly influence depression rates among farmers. Age, gender, work experience, financial status, and substance use are all associated with depression, highlighting the need for targeted mental health interventions and support systems tailored to these specific risk factors. Understanding these associations can help in developing comprehensive mental health strategies and policies aimed at improving the well-being of farmers, a group that plays a vital role in society but often faces unique and challenging conditions.

ACKNOWLEDGEMENTS

We would like to thank director Dr. K. Ramesh of Karnataka College of Pharmacy for his support throughout the study. Our gratitude extends to Dr. Athira Krishnan, Assistant Professor in the Department of Pharmacy Practice, Dr. Balakeshwa Ramaiah, Professor and Head of the Department of Pharmacy Practice at Karnataka College of Pharmacy. Additionally, we are thankful to Dr. Waseem Hussain Bhat for his efforts in preparing the manuscript.

Funding: No funding sources

Conflict of interest: None declared

Ethical approval: The study was approved by the Institutional Ethics Committee

REFERENCES

1. 1. Kurmis PA, Apps AS. Occupationally-acquired noise-induced hearing loss: a senseless workplace hazard. Int J Occup Med Environ Health. 2007;20(2):127-36.
2. 2. Rangkooy HA, Rashnuodi P, Monjezi Ali Salehy M, Bavandpour A. Evaluation of noise-induced hearing loss on the workers of one of the Ahvaz Steel Companies. Jundishapur J Health Sci. 2018;10(1):1-6.
3. 3. Zaw AK, Myat AM, Thandar M, Htun YM, Aung TH, Tun KM, et al. Assessment of noise exposure and hearing loss among workers in textile mill (thamine), Myanmar: a cross-sectional study. Safe Health Work. 2020;11(2):199-206.
4. 4. Whittaker JD, Robinson T, Acharya A, Singh D, Smith M. Noise-induced hearing loss in small-scale metal industry in Nepal. J Laryngol Otol. 2014;128(10):871-80.
5. 5. Kallioniemi MK, Simola A, Kaseva J, Kymäläinen HR. Stress and burnout among Finnish dairy farmers. J Agromed. 2016;21(3):259-68.
6. 6. Pulgar CA, Trejo G, Suerken C, Ip EH, Arcury TA, Quandt SA. Economic hardship and depression among women in Latino farmworker families. J Immigr Minority Health. 2016;18:497-504.
7. 7. Walker JL, Walker LJS. Self-reported stress symptoms in farmers. J Clin Psychol. 1988;44:10-6.
8. 8. Gevaert J, De Moortel D, Wilkens M, Vanroelen C. What’s up with the self-employed? A cross-national perspective on the self-employed’s work-related mental well-being. SSM-Popul Health. 2018;4:317-26.
9. 9. Çakmur H. Health risks faced by Turkish agricultural workers. Sci World J. 2014;2014:1-8.
10. 10. Demos K, Sazakli E, Jelastopulu E, Charokopos N, Ellul J, Leotsinidis M. Does farming have an effect on health status? A comparison study in West Greece. Int J Environ Res Public Health. 2013;10(3):776-92.
11. 11. Rayens MK, Reed DB. Predictors of depressive symptoms in older rural couples: the impact of work, stress and health. J Rural Health. 2014;30:59-68.
12. 12. Torske MO, Hilt B, Bjørngaard JH, Glasscock D, Krokstad S. Disability pension and symptoms of anxiety and depression: a prospective comparison of farmers and other occupational groups. The HUNT Study, Norway. BMJ Open. 2015;5(11):e009114.
13. 13. Polain JD, Berry HL, Hoskin JO. Rapid change, climate adversity and the next ‘big dry’: older farmers’ mental health. Aust J Rural Health. 2011;19:239-43.
14. 14. Scarth RD, Zwerling C, Lewis MQ, Burmeister LF. Depression and risk factors among Iowa farmers. J Agromed. 1997;3:207-16.
15. 15. Bryant L, Garnham B. Economies, ethics and emotions: Farmer distress within the moral economy of agribusiness. J Rural Stud. 2014;34:304-12.
16. 16. Pulgar CA, Trejo G, Suerken C, Ip EH, Arcury TA, Quandt SA. Economic hardship and depression among women in Latino farmworker families. J Immigr Minor Health. 2016;18:497-504.
17. 17. Truchot D, Andela M. Burnout and hopelessness among farmers: the farmers stressors inventory. Soc Psychiatr Psychiat. Epidemiol. 2018;5:1-9.
18. 18. Kureshi JS, Somsundaram K. Assessment of occupational stress among farmers in Aurangabad district, Maharashtra. Int J Community Med Public Health. 2018;5:1434-40. Belyea MJ, Lobao LM. Psychosocial consequences of agricultural transformation: the farm crisis and depression. Rural Sociol. 1990;55:58-75.
19. 19. Kearney GD, Rafferty AP, Hendricks LR, Allen DL, Tutor-Marcom R. A cross-sectional study of stressors among farmers in eastern North Carolina. N C Med J. 2014;75(6):384-92.
20. 20. Williams RT. The on-going farm crisis: extension leadership in rural communities. J Ext. 1996;34:1-3. Daghagh Yazd S, Wheeler SA, Zuo A. Key risk factors affecting farmers’ mental health: a systematic review. Int J Environ Res Public Health. 2019;16(23):4849.
21. 21. Ortega ST, Johnson DR, Beeson PG, Craft BJ. The farm crisis and mental health: a longitudinal study of the 1980s. Rural Sociol. 1994;59:598-619.
22. 22. Bryant L, Garnham B. Beyond discourses of drought: the micro-politics of the wine industry and farmer distress. J Rural Stud. 2013;32:1-9.
23. 23. Logstein B. Farm-related concerns and mental health status among Norwegian farmers. J Agromed. 2016;21:316-26.
24. 24. Olff M, Koeter MW, Van Haaften EH, Kersten PH, Gersons BP. Impact of a foot and mouth disease crisis on post-traumatic stress symptoms in farmers. Br J Psychiatr. 2005;186(2):165-6.
25. 25. Çakmur H. Health Risks Faced by Turkish Agricultural Workers. Sci World J. 2014;2014:1-2348.