Social determinants of mental health of women living in slum: a systematic review

Abdi, Fatemeh; Rahnemaei, Fatemeh Alsadat; Shojaei, Parisa; Mahmoodi, Zohreh

doi:10.5468/ogs.20264

Cited by 13 publications

(9 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Inequalities in the distribution of doctor diagnosed and screened depression are stark. The findings echo those of earlier research in Brazil and internationally, which shows female sex, increased age, comorbidities, and smoking are associated with increased odds of depression (Wittayanukorn et al, 2014;Stopa et al, 2015;Souza Lopes et al, 2016;Abdi et al, 2021). Although research has not determined a definitive cause for higher rates of depression in women, previous analysis has suggested that higher Gross National Income (GNI) and shifting gender roles can influence the ratio of depression between males and females (Rai et al, 2013).…”

Section: Discussionsupporting

confidence: 86%

Inequalities in the prevalence of major depressive disorder in Brazilian slum populations: a cross-sectional analysis

Pitcairn

Chan

Oyebode

et al. 2021

Epidemiol Psychiatr Sci

View full text Add to dashboard Cite

Aims The mental health of slum residents is under-researched globally, and depression is a significant source of worldwide morbidity. Brazil's large slum-dwelling population is often considered part of a general urban-poor demographic. This study aims to identify the prevalence and distribution of depression in Brazil and compare mental health inequalities between slum and non-slum populations. Methods Data were obtained from Brazil's 2019 National Health Survey. Slum residence was defined based on the UN-Habitat definition for slums and estimated from survey responses. Doctor-diagnosed depression, Patient Health Questionnaire (PHQ-9)-screened depression and presence of undiagnosed depression (PHQ-9-screened depression in the absence of a doctor's diagnosis) were analysed as primary outcomes, alongside depressive symptom severity as a secondary outcome. Prevalence estimates for all outcomes were calculated. Multivariable logistic regression models were used to investigate the association of socioeconomic characteristics, including slum residence, with primary outcomes. Depressive symptom severity was analysed using generalised ordinal logistic regression. Results Nationally, the prevalence of doctor diagnosed, PHQ-9 screened and undiagnosed depression were 9.9% (95% confidence interval (CI): 9.5–10.3), 10.8% (95% CI: 10.4–11.2) and 6.9% (95% CI: 6.6–7.2), respectively. Slum residents exhibited lower levels of doctor-diagnosed depression than non-slum urban residents (8.6%; 95% CI: 7.9–9.3 v. 10.7%; 95% CI: 10.2–11.2), while reporting similar levels of PHQ-9-screened depression (11.3%; 95% CI: 10.4–12.1 v. 11.3%; 95% CI: 10.8–11.8). In adjusted regression models, slum residence was associated with a lower likelihood of doctor diagnosed (adjusted odds ratio (adjusted OR): 0.87; 95% CI: 0.77–0.97) and PHQ-9-screened depression (adjusted OR: 0.87; 95% CI: 0.78–0.97). Slum residents showed a greater likelihood of reporting less severe depressive symptoms. There were significant ethnic/racial disparities in the likelihood of reporting doctor-diagnosed depression. Black individuals were less likely to report doctor-diagnosed depression (adjusted OR: 0.66; 95% CI: 0.57–0.75) than white individuals. A similar pattern was observed in Mixed Black (adjusted OR: 0.72; 95% CI: 0.66–0.79) and other (adjusted OR: 0.63; 95% CI: 0.45–0.88) ethnic/racial groups. Slum residents self-reporting a diagnosis of one or more chronic non-communicable diseases had greater odds of exhibiting all three primary depression outcomes. Conclusions Substantial inequalities characterise the distribution of depression in Brazil including in slum settings. People living in slums may have lower diagnosed rates of depression than non-slum urban residents. Understanding the mechanisms behind the discrepancy in depression diagnosis between slum and non-slum populations is important to inform health policy in Brazil, including in addressing potential gaps in access to mental healthcare.

show abstract

Section: Discussionsupporting

confidence: 86%

Inequalities in the prevalence of major depressive disorder in Brazilian slum populations: a cross-sectional analysis

Pitcairn

Chan

Oyebode

et al. 2021

Epidemiol Psychiatr Sci

View full text Add to dashboard Cite

show abstract

“…Migration costs consist of two main aspects: the rural means of production that need to be given up, and the urban cost of living that need to be borne, which appear even heavier in the context of the lack of social security for employees. Firstly, rural land is not only a means of production but also a means of livelihood [ 15 ]. Therefore, it is easy to produce a tunnel effect, and the tunnel effect at this time can alleviate part of the sense of deprivation.…”

Section: Correlation Analysis Of Income Satisfaction and Mental Healt...mentioning

confidence: 99%

Correlation Analysis between Residents’ Income Satisfaction and Mental Health Based on Big Data

Wang

Teo

et al. 2022

Occupational Therapy International

View full text Add to dashboard Cite

This paper presents an in-depth study and analysis of the correlation between satisfaction with rural residents’ income and mental health well-being in the context of industrial structure upgrading. Most of the studies on residents’ subjective well-being from the perspective of relative income or income inequality have started from the happiness of rural residents and the satisfaction of rural residents’ life, and few scholars have focused on the psychological health of rural residents. Subjective well-being is significantly related to external and internal goals in desire. Life satisfaction is significantly and positively correlated with external and internal goals, as well as the six dimensions of desire, except for social identity; positive emotions are significantly and positively correlated with internal goals; negative emotions are only negatively correlated with self-acceptance, and there is a significant positive correlation between income level and desire. In vertical income, there is also a process of judging whether the expected income is achieved. If the expected income growth level is achieved, the income satisfaction will increase. Desire mediates the effect of income level on subjective well-being. Income level influences subjective well-being through internal goals; income level influences life satisfaction and positive emotions through external goals. The relationship between income inequality and mental health is influenced by the characteristics of the population, with women and middle-aged people being the most negatively affected. This relationship is also influenced by income level, with the effect of income inequality on mental health showing a negative effect in the lower and middle-income groups but a positive effect in the higher income groups. Income inequality affects residents’ mental health through the mediating effects of a sense of social justice, life stress, and trust in government. Inequality in household wealth can exacerbate the negative effects of income inequality on mental health.

show abstract

“…This 'othering' of certain communities during COVID-19 has been reported by another study from north India [32] as well as one study from South Africa [50]. This issue is of utmost concern since such communities were already vulnerable to mental health conditions, and the pandemic has brought with it a host of additional stressors [57][58][59].…”

Section: Plos Onementioning

confidence: 78%

Corona was scary, lockdown was worse: A mixed-methods study of community perceptions on COVID-19 from urban informal settlements of Mumbai

et al. 2022

View full text Add to dashboard Cite

The COVID-19 pandemic has magnified the multiple vulnerabilities of people living in urban informal settlements globally. To bring community voices from such settlements to the center of COVID-19 response strategies, we undertook a study in the urban informal settlements of Dharavi, Mumbai, from September 2020-April 2021. In this study, we have examined the awareness, attitudes, reported practices, and some broader experiences of the community in Dharavi with respect to COVID-19. We have used a mixed-methods approach, that included a cross-sectional survey of 468 people, and in-depth interviews and focus group discussions with 49 people living in this area. Data was collected via a mix of phone and face-to-face interviews. We have presented here the descriptive statistics from the survey and the key themes that emerged from our qualitative data. People reported high levels of knowledge about COVID-19, with television (90%), family and friends (56%), and social media (47%) being the main sources of information. The knowledge people had, however, was not free of misconceptions and fear; people were scared of being forcefully quarantined and dying alone during the early days of COVID-19. These fears had negative repercussions in the form of patient-related stigma and hesitancy in seeking healthcare. A year into the pandemic, however, people reported a shift in attitudes from ‘extreme fear to low fear’ (67% reported perceiving low/no COVID risk in October 2020), contributing to a general laxity in following COVID-appropriate behaviors. Currently, the community is immensely concerned about the revival of livelihoods, that have been adversely impacted due to the lockdown in 2020 as well as the continued ‘othering’ of Dharavi for being a COVID hotspot. These findings suggest that urban informal settlements like Dharavi need community-level messaging that counters misinformation and denial of the outbreak; local reinforcement of COVID-appropriate behaviours; and long-term social protection measures.

show abstract

Social determinants of mental health of women living in slum: a systematic review

Cited by 13 publications

References 34 publications

Inequalities in the prevalence of major depressive disorder in Brazilian slum populations: a cross-sectional analysis

Inequalities in the prevalence of major depressive disorder in Brazilian slum populations: a cross-sectional analysis

Correlation Analysis between Residents’ Income Satisfaction and Mental Health Based on Big Data

Corona was scary, lockdown was worse: A mixed-methods study of community perceptions on COVID-19 from urban informal settlements of Mumbai

Contact Info

Product

Resources

About