Article

Health insurance coverage and mortality revisited.

Department of Family and Preventive Medicine, Division of Heath Care Sciences, UCSD School of Medicine, La Jolla, CA 92093-0622, USA.
Health Services Research (Impact Factor: 2.49). 05/2009; 44(4):1211-31. DOI: 10.1111/j.1475-6773.2009.00973.x
Source: PubMed

ABSTRACT To improve understanding of the relationship between lack of insurance and risk of subsequent mortality.
Adults who reported being uninsured or privately insured in the National Health Interview Survey from 1986 to 2000 were followed prospectively for mortality from initial interview through 2002. Baseline information was obtained on 672,526 respondents, age 18-64 at the time of the interview. Follow-up information on vital status was obtained for 643,001 (96 percent) of these respondents, with approximately 5.4 million person-years of follow-up.
Relationships between insurance status and subsequent mortality are examined using Cox proportional hazard survival analysis.
Adjusted for demographic, health status, and health behavior characteristics, the risk of subsequent mortality is no different for uninsured respondents than for those covered by employer-sponsored group insurance at baseline (hazard ratio 1.03, 95 percent confidence interval [CI], 0.95-1.12). Omitting health status as a control variable increases the estimated hazard ratio to 1.10 (95 percent CI, 1.03-1.19). Also omitting smoking status and body mass index increases the hazard ratio to 1.20 (95 percent CI, 1.15-1.24). The estimated association between lack of insurance and mortality is not larger among disadvantaged subgroups; when the analysis is restricted to amenable causes of death; when the follow-up period is shortened (to increase the likelihood of comparing the continuously insured and continuously uninsured); and does not change after people turn 65 and gain Medicare coverage.
The Institute of Medicine's estimate that lack of insurance leads to 18,000 excess deaths each year is almost certainly incorrect. It is not possible to draw firm causal inferences from the results of observational analyses, but there is little evidence to suggest that extending insurance coverage to all adults would have a large effect on the number of deaths in the United States.

0 Bookmarks
 · 
99 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Although numerous studies have considered the effects of having health insurance on access to health care, physical health, and mortality risk, the association between insurance coverage and mental health has been surprisingly understudied. Building on previous work, we use data collected from a two-year follow-up of low-income women living in Boston, Chicago and San Antonio to estimate a series of latent fixed effects regression models assessing the association between insurance status and symptoms of psychological distress. We find that having any insurance and private insurance is unrelated to depression, anxiety, and somatization. Having public insurance is unrelated to depression and somatization, but there is some evidence that having public insurance is associated with greater anxiety. Although not a direct test of the Affordable Care Act, our results suggest that the expansion of coverage may have a limited impact on symptoms of psychological distress among low-income urban women with children.
    Mental health and society 01/2015; 5(1):1-15. DOI:10.1177/2156869314549674
  • Source
  • [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, robust fault detection problem for uncertain multiple packets transmission networked systems (NSs) is investigated, and a novel Markovian jump system model is proposed to describe the data transmission pattern. Based on the obtained model, by employing mode-dependent fault detection filter as residual generator, the addressed fault detection problem is converted into H∞ filtering problem. Then, with the help of stochastic Lyapunov function approach, the sufficient condition for the desired fault detection filter is constructed in terms of certain linear matrix inequalities, which depend on not only the transmission matrix but also on the Markov chains. The effectiveness of the proposed method is demonstrated by simulation example..
    Control and Decision Conference (CCDC), 2012 24th Chinese; 01/2012

Preview

Download
1 Download
Available from