Evidence map›Paper›PMID 39534737›Full record

ArticleFrontiers in public health2024

Gendered socio-economic and mental health effects of the COVID-19 pandemic among adults living in selected informal settlements in Kenya: an intersectional analysis.

Daniel M Mwanga, Henry Owoko Odero, Damazo T Kadengye, Sally Atieno Odunga, Eva Muluve, Bylhah Mugotitsa, Ruth Nanjekho Wafubwa, Karen Austrian, Sylvia Kiwuwa-Muyingo

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Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Daniel M MwangaAfrican Population and Health Research Center, Nairobi, Kenya.
Henry Owoko OderoAfrican Population and Health Research Center, Nairobi, Kenya.
Damazo T KadengyeAfrican Population and Health Research Center, Nairobi, Kenya.
Sally Atieno OdungaAfrican Population and Health Research Center, Nairobi, Kenya.
Eva MuluvePopulation Council, Nairobi, Kenya.
Bylhah MugotitsaAfrican Population and Health Research Center, Nairobi, Kenya.
Ruth Nanjekho WafubwaPopulation Council, Nairobi, Kenya.
Karen AustrianPopulation Council, Nairobi, Kenya.
Sylvia Kiwuwa-MuyingoAfrican Population and Health Research Center, Nairobi, Kenya.

Funding

Gates Foundation INV-005210
6 · The paper itself

Abstract

Background: COVID-19 pandemic had devastating socio-economic and health effects, including mental health. This study examines the intersectionality between gender and mental health outcomes among Kenyan adults in informal settlements of Nairobi, Kisumu, and Kilifi Counties during the COVID-19 crisis. This is necessary to inform mental health response in case of another pandemic. Methods: We analyzed data collected in a longitudinal survey between July 2020 (fourth round) and February 2021 (fifth round). The data covered COVID-19-related effects on job loss, food insecurity, access to health services, and mental health. Participants were randomly sampled from existing cohorts at the Population Council. The outcomes of interest were depressive and anxiety disorders, combined into a binary composite outcome variable. Descriptive statistics included means for continuous variables and frequencies and proportions for categorical variables. Chi-square tests were used to examine the differences between groups. The relationship between the gendered COVID-19 socio-economic effects and participants' mental health was examined using modified Poisson regression. Results: A total of 4,050 participants were interviewed, 66% female and median age 38 [interquartile range (IQR): 29-46]. Complete income loss was strongly associated with negative mental health outcomes in multiple intersections with varied magnitudes. The association was larger among older females (≥50 years) (PR = 1.33, 95% CI = 1.17-1.51, Conclusion: We observed significant gender differences in the prevalence of depressive symptoms and anxiety disorders during the COVID-19 pandemic, underscoring the importance of socio-economic factors and health services access in shaping mental health outcomes. Interventions targeting pandemic-related mental health issues should be gender-sensitive and address economic vulnerabilities such as job losses and food insecurity. Policies to mitigate these effects, especially for at-risk groups are crucial for reducing mental health burden in future crises.

Indexed as

COVID-19Mental HealthSocioeconomic FactorsAdolescentAdultAnxiety DisordersDepressionFemaleFood InsecurityHealth Services AccessibilityHumansKenyaLongitudinal StudiesMaleMiddle AgedPandemicsaccess to health servicesCOVID-19food insecuritygender intersectionalityincome lossmental health

Identifiers

PMID39534737
PMCPMC11554471

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.