Literature DB >> 12119429

Income and Mental Health: Unraveling Community and Individual Level Relationships.

Carole Roan Gresenz1, Roland Sturm, Lingqi Tang.   

Abstract

BACKGROUND: The association between individual socioeconomic status (SES) and mental disorder is well-documented, but studies to date have provided limited and sometimes conflicting evidence on the relationship between aspects of socioeconomic environment, including the role of income inequality, and mental disorder. AIMS OF THE STUDY: This paper explores the relationships between mental disorder and individual SES and socioeconomic environment, with particular attention to both the level and dispersion of community income and to their interactions with individual income.
METHODS: Cross sectional study using nationally representative, individual level data from the Healthcare for Communities survey merged with supplemental information. Dependent variable is individual mental health status, measured by the 5 item Mental Health Inventory (MHI-5; average 80.6) and an indicator of probable anxiety or mood disorder based on clinical screening instruments (positive for 14.3 percent of respondents in the sample).
RESULTS: MHI-5 decreases (indicating worse mental health), and the probability of an anxiety or depressive disorder increases continuously from the highest to the lowest quintiles of family income. Compared to those in the highest income quintile, MHI-5 is more than 10 points lower and the probability of disorder is much greater among individuals in the lowest income quintile. Within-quintile own income level is also strongly associated with mental health among lower income individuals. We find no evidence that higher levels of income inequality are associated with poor mental health outcomes, measured either by the probability of disorder or MHI-5. Regarding income level, MHI-5 is 3.4 to 3.5 points higher among low income individuals in medium or high income states compared to those in low income states. DISCUSSION: The qualitative conclusions are stable across various specifications reported (two different measures of mental health, two geographic levels, and among all individuals and low income individuals alone), and in specifications with alternative parameterizations of the community variables (continuously measured, included as quintiles instead of tertiles, and using other indicators of inequality). Individual income is highly correlated with mental health status; level of state income has some association; community or state income inequality has no detectable relationship with mental health. This analysis provides no support for the hypothesis that income inequality is a stronger determinant of health than individual or family income, a hypothesis that in recent years has received much attention in the popular press and policy debates. Limitations of our analysis include the cross-sectional nature of the analysis, the sample sizes used in derivation of the site variables (though sensitivity analyses showed robust results) and the age of the state data.
CONCLUSIONS: The association between individual income and mental health is strong. No support for the income inequality hypothesis is found.IMPLICATIONS FOR HEALTH POLICY FORMULATION: Our findings point to a need for better understanding of the relationship between individual income and mental health outcomes. Our research does not support the notion that policies aimed at diminishing income inequality are an important lever in improving mental health outcomes for individuals. IMPLICATIONS FOR FURTHER RESEARCH: This research does not address whether and how different sources of income-at the individual or community level-may affect mental health, and whether the associations observed cross-sectionally also bear out longitudinally. In addition, more research into the relationship between other community characteristics, such as service availability, and mental health outcomes is needed.

Entities:  

Year:  2001        PMID: 12119429

Source DB:  PubMed          Journal:  J Ment Health Policy Econ        ISSN: 1099-176X


  18 in total

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Journal:  Depress Anxiety       Date:  2011-06-16       Impact factor: 6.505

4.  Income inequality and physical and mental health: testing associations consistent with proposed causal pathways.

Authors:  Frederick J Zimmerman; Janice F Bell
Journal:  J Epidemiol Community Health       Date:  2006-06       Impact factor: 3.710

5.  Outcomes in men denied access to a California public assistance program for prostate cancer.

Authors:  Jennifer T Anger; Sally L Maliski; Tracey L Krupski; Lorna Kwan; John L Gore; Arlene Fink; Sarah E Connor; James R Orecklin; Mark S Litwin
Journal:  Public Health Rep       Date:  2007 Mar-Apr       Impact factor: 2.792

6.  Factors Associated with Depression Among Male Casual Laborers in Urban Vietnam.

Authors:  Nguyen Van Huy; Michael P Dunne; Joseph Debattista
Journal:  Community Ment Health J       Date:  2015-02-05

7.  Positive screens for psychiatric disorders in primary care: a long-term follow-up of patients who were not in treatment.

Authors:  Myrna M Weissman; Yuval Neria; Marc J Gameroff; Daniel J Pilowsky; Priya Wickramaratne; Rafael Lantigua; Steven Shea; Mark Olfson
Journal:  Psychiatr Serv       Date:  2010-02       Impact factor: 3.084

8.  Correlates of self-reported depressive symptoms: a study of older persons of Punjab, Pakistan.

Authors:  Fauzia Maqsood; Jason D Flatt; Steven M Albert; Sidra Maqsood; Mohammad Nizamuddin
Journal:  J Cross Cult Gerontol       Date:  2013-03

9.  Area characteristics and admission rates of people with schizophrenia and affective disorders in a German rural catchment area.

Authors:  C Losert; M Schmauß; T Becker; R Kilian
Journal:  Epidemiol Psychiatr Sci       Date:  2012-04-11       Impact factor: 6.892

10.  Assessing the perceived changes in neighborhood physical and social environments and how they are associated with Chinese internal migrants' mental health.

Authors:  Min Yang; Julian Hagenauer; Martin Dijst; Marco Helbich
Journal:  BMC Public Health       Date:  2021-06-28       Impact factor: 3.295

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