New dimensions of economic well-being among people with mental illness: evidence from Healthcare for Communities.
OBJECTIVE
To analyze the relationship between mental health and savings and compare it to the relationship between common chronic physical conditions and savings.


METHODS
Healthcare for Communities, a national survey conducted in 1997/1998 with approximately 10,000 respondents.


METHODS
We used logistic regression to analyze any savings versus no savings and used ordinary least squares regression to study level of savings conditional on having any savings.


RESULTS
Individuals screening positive for any mental health disorder are less than two-thirds as likely as individuals with no mental health problems to have any savings. The percent age of savers declines with age among those with a probable mental health condition, compared to a rise with age among other individuals, including those who are chronically physically ill.


CONCLUSIONS
The main finding is less the sizeable gap in the percentage of savers among individuals who have and do not have a mental disorder th an the strong interaction with age. Older individuals with mental health conditions are at particular risk for having no savings and are at more risk than individuals in poor physical health . Low levels of saving among older individuals with mental health problems become particularly problematic when these individuals transition into Medicare. With limited household wealth, these individuals are the group least likely to be able to afford supplemental insurance that covers medications and least likely to be able to afford the out-of-pocket costs for newer psychotropic medications.
Gresenz
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Sturm
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D000328:Adult; D000367:Age Factors; D002908:Chronic Disease / Q000191:economics* / Q000453:epidemiology; D017047:Cost Sharing; D003625:Data Collection; D004651:Employment / Q000191:economics; D005191:Family Characteristics; D005382:Financing, Personal / Q000706:statistics & numerical data*; D006304:Health Status; D006801:Humans; D007182:Income / Q000706:statistics & numerical data*; D017054:Insurance, Medigap / Q000191:economics; D016015:Logistic Models; D006278:Medicare; D001523:Mental Disorders / Q000191:economics* / Q000453:epidemiology; D008875:Middle Aged; D011336:Probability; D018570:Risk Assessment; D014481:United States / Q000453:epidemiology