Background Mental health issues, particularly depression, have seen a significant increase worldwide in recent years, raising global concern. Depression is projected by the World Health Organization to become the leading cause of mental illness by 2030. This condition severely impacts the quality of life and psychosocial functioning of those affected, underscoring the need for effective interventions and awareness. The 2022 Kenya Demographic and Health Survey is the first Demographic and Health Surveys in Africa to incorporate the mental health diagnosis module. Therefore, this study assesses socio-economic, demographic characteristics and health conditions associated with depression in Kenya. Methods This secondary analysis uses data from the 2022 Kenya Demographic and Health Survey, in which participants were selected from households within designated demographic surveillance areas across Kenya. A two-stage cluster sampling method was applied to achieve national representativeness. The study examined associations between socio-demographic characteristics that included age, gender, education level, marital status, household wealth index, and urban/rural residence, as well as chronic diseases such as heart and lung diseases, hypertension and diabetes, and self-reported depression using logistic regression analysis. Both crude and adjusted odds ratios (ORs) for self-reported depression were assessed, with statistical significance set at a p-value of <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="12889_2025_24304_Article_IEq1.gif" Format="GIF" Height="13" Rendition="HTML" Resolution="72" Type="Linedraw" Width="48" /> </InlineMediaObject> <EquationSource Format="TEX">\(<0.05\)</EquationSource> </InlineEquation>. Additionally, spatial analyses of self-reported depression prevalence were conducted to identify regional patterns. Results A total of 31354 men and women were assessed. The prevalence of self-reported depression was 2.6%. Being a middle-income earner was associated with increased likelihood of depression (aOR:1.12, 95% CI: 1.03-1.22). Being hypertensive, diabetic, and having heart and lung diseases increased the likelihood of having depression by at least two-fold, (aOR:3.71, 95% CI: 3.49-3.95, aOR:1.14, 95% CI: 0.96-1.35, aOR:3.10, 95% CI: 2.68-3.57 and aOR:3.21, 95% CI: 2.84-3.62, respectively). Conclusion The proportion of participants who self-reported depression was low. Besides, there was a considerable variation in self-reported depression across different counties in Kenya. Furthermore, there was variability in depression among different socio-demographic groups. Therefore, there is a need to target mental health interventions to persons with chronic conditions and those in middle economic class as they are greatly affected with depression.

Factors associated with self-reported diagnosis of depression in Kenya: insights from 2022 Demographic and Health Survey

期刊论文
出版模式：

开放获取
发表日期：

2025年8月29日

查看全文

Evans Omondi,
Wingston Felix Ng’ambi,
Bylhah Mugotitsa,
Chance Ng’ambi,
Miriam Sitienei,
Steve Cygu,
Collins Odhiambo,
Samuel Iddi,
Damazo T. Kadengye,
Agnes Kiragga

摘要

Background

Mental health issues, particularly depression, have seen a significant increase worldwide in recent years, raising global concern. Depression is projected by the World Health Organization to become the leading cause of mental illness by 2030. This condition severely impacts the quality of life and psychosocial functioning of those affected, underscoring the need for effective interventions and awareness. The 2022 Kenya Demographic and Health Survey is the first Demographic and Health Surveys in Africa to incorporate the mental health diagnosis module. Therefore, this study assesses socio-economic, demographic characteristics and health conditions associated with depression in Kenya.

Methods

This secondary analysis uses data from the 2022 Kenya Demographic and Health Survey, in which participants were selected from households within designated demographic surveillance areas across Kenya. A two-stage cluster sampling method was applied to achieve national representativeness. The study examined associations between socio-demographic characteristics that included age, gender, education level, marital status, household wealth index, and urban/rural residence, as well as chronic diseases such as heart and lung diseases, hypertension and diabetes, and self-reported depression using logistic regression analysis. Both crude and adjusted odds ratios (ORs) for self-reported depression were assessed, with statistical significance set at a p-value of \(<0.05\) . Additionally, spatial analyses of self-reported depression prevalence were conducted to identify regional patterns.

Results

A total of 31354 men and women were assessed. The prevalence of self-reported depression was 2.6%. Being a middle-income earner was associated with increased likelihood of depression (aOR:1.12, 95% CI: 1.03-1.22). Being hypertensive, diabetic, and having heart and lung diseases increased the likelihood of having depression by at least two-fold, (aOR:3.71, 95% CI: 3.49-3.95, aOR:1.14, 95% CI: 0.96-1.35, aOR:3.10, 95% CI: 2.68-3.57 and aOR:3.21, 95% CI: 2.84-3.62, respectively).

Conclusion

The proportion of participants who self-reported depression was low. Besides, there was a considerable variation in self-reported depression across different counties in Kenya. Furthermore, there was variability in depression among different socio-demographic groups. Therefore, there is a need to target mental health interventions to persons with chronic conditions and those in middle economic class as they are greatly affected with depression.