Impact of socioeconomic, behavioral and clinical risk factors on mortality

Rask, Kimberly J.; O'Malley, Emily; Druss, Benjamin G.

doi:10.1093/pubmed/fdp015

Cited by 32 publications

(25 citation statements)

References 26 publications

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“…Consistent with prior studies conducted in the NHANES III cohort (Suresh et al, 2011; Rask et al, 2009; Sabanayagam and Shankar, 2012), we found strong and statistically significant associations between low socioeconomic status and increased mortality in the overall study population. Indeed, individuals in the lowest income group were 1.8 times as likely to die within the follow-up period compared to those in the highest income group and individuals with at most a high school education were approximately 1.3 times as likely to die within the follow-up period compared to those who had attained more than a high school education.…”

Section: Discussionsupporting

confidence: 91%

Does cytomegalovirus infection contribute to socioeconomic disparities in all-cause mortality?

Feinstein

Douglas

Stebbins

et al. 2016

Mechanisms of Ageing and Development

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The social patterning of cytomegalovirus (CMV) and its implication in aging suggest that the virus may partially contribute to socioeconomic disparities in mortality. We used Cox regression and inverse odds ratio weighting to quantify the proportion of the association between socioeconomic status (SES) and all-cause mortality that was attributable to mediation by CMV seropositivity. Data were from the National Health and Nutrition Examination Survey (NHANES) III (1988–1994), with mortality follow-up through December 2011. SES was assessed as household income (income-to-poverty ratio ≤1.30; >1.30 to ≤1.85; >1.85 to ≤3.50; >3.50) and education (high school). We found strong associations between low SES and increased mortality: hazard ratio (HR) 1.80; 95% confidence interval (CI): 1.57, 2.06 comparing the lowest versus highest income groups and HR 1.29; 95% CI: 1.13, 1.48 comparing high school education. 65% of individuals were CMV seropositive, accounting for 6–15% of the SES-mortality associations. Age modified the associations between SES, CMV, and mortality, with CMV more strongly associated with mortality in older individuals. Our findings suggest that cytomegalovirus may partially contribute to persistent socioeconomic disparities in mortality, particularly among older individuals.

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Section: Discussionsupporting

confidence: 91%

Does cytomegalovirus infection contribute to socioeconomic disparities in all-cause mortality?

Feinstein

Douglas

Stebbins

et al. 2016

Mechanisms of Ageing and Development

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“…However, research on factors other than demographics suggests that socioeconomic conditions may have a profound effect on risk of mortality, both in the general population and after SCI. [3][4][5] This research has typically focused on education and income to the exclusion of gainful employment as a risk factor for mortality.…”

Section: Introductionmentioning

confidence: 99%

“…9 These studies demonstrated the importance of income and education but did not address gainful employment. Studies in the general population have rarely addressed employment, [3][4][5] as employment is fundamental to adult life and employment rates are typically high. However, given the low employment rates and the relationship of poor employment outcomes with policy factors (particularly work disincentives in the USA), employment may be a critical, yet overlooked, risk factor for mortality.…”

Section: Introductionmentioning

confidence: 99%

Gainful employment and risk of mortality after spinal cord injury: effects beyond that of demographic, injury and socioeconomic factors

2012

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Objective: To evaluate the association of three levels of gainful employment with the risk of mortality after traumatic spinal cord injury (SCI) while controlling for known predictors of mortality status (including education and income). Study design: Prospective cohort study Setting: A total of 20 federally funded SCI Model Systems of care in the United States. Methods: Participants included 7955 adults with traumatic SCI. Preliminary assessments were conducted between 1995 and 2006. Mortality status was determined by the Social Security Death Index (1308 deaths). A two-stage logistic regression model was used to estimate the chance of dying in any given year. Life expectancy was calculated under different economic assumptions. Results: Compared with those who were working 30 þ h per week, the odds of mortality was 1.37 for those who worked 1-29 h and 1.67 for those who were unemployed. The addition of gainful employment only modestly reduced the effects of household income and education, both of which remained significant. For instance, the odds of mortality for household income (referent $75 000 þ) decreased from 1.50 to 1.38 for $25 000-$75 000 and from 2.10 to 1.82 for o$25 000. Life expectancy varied widely depending on socioeconomic characteristics more than doubling under certain assumptions. Conclusion: Substantial variation in mortality is attributable to employment, above and beyond the effects of previously established demographic, injury and socioeconomic predictors. Although some excess mortality may be the inevitable consequence of SCI, risk is substantially increased with poor socioeconomic characteristics.

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“…The effects of premature deaths are highly important and they should be analyzed in 3 aspects: macrosocial, mezosocial and in the perspective of a particular individual. [110]. It should be stressed that depression appeared to be a predictive mortality factor, especially in elderly people.…”

Section: Discussionmentioning

confidence: 98%

Determinants of premature mortality in a city population: An eight-year observational study concerning subjects aged 18–64

Maniecka-Bryła¹,

Dziankowska-Zaborszczyk²,

Bryła³

et al. 2013

International Journal of Occupational Medicine and Environmental Health

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Background: Premature deaths constitute 31.1% of all deaths in Łódź. Analysis of the causes of premature deaths may be helpful in the evaluation of health risk factors. Moreover, findings of this study may enhance prophylactic measures. Material and Methods: In 2001, 1857 randomly selected citizens, aged 18-64, were included in the Countrywide Integrated Noncommunicable Diseases Intervention (CINDI) Programme. In 2009, a follow-up study was conducted and information on the subjects of the study was collected concerning their health status and if they continued to live in Łódź. The Cox proportional hazards model was used for evaluation of hazard coefficients. We adjusted our calculations for age and sex. The analysis revealed statistically significant associations between the number of premature deaths of the citizens of Łódź and the following variables: a negative self-evaluation of health -HR = 3.096 (95% CI: 1.729-5.543), poor financial situation -HR = 2.811 (95% CI: 1.183-6.672), occurring in the year preceding the study: coronary pain -HR = 2.754 (95% CI: 1.167-6.494), depression -HR = 2.001 (95% CI: 1.222-3.277) and insomnia -HR = 1.660 (95% CI: 1.029-2.678). Our research study also found a negative influence of smoking on the health status -HR = 2.782 (95% CI: 1.581-4.891). Moreover, we conducted survival analyses according to sex and age with Kaplan-Meier curves. Conclusions: The risk factors leading to premature deaths were found to be highly significant but possible to reduce by modifying lifestyle-related health behaviours. The confirmed determinants of premature mortality indicate a need to spread and intensify prophylactic activities in Poland, which is a post-communist country, in particular, in the field of cardiovascular diseases. Attempts to find reasons of deaths in the first decade of the 21st century may lead to a detailed and long-term research which would focus on determining a wide spectrum of factors contributing to the mortality of Łódź citizens. This in turn, may lead to implementation of a multidimensional prophylaxis which would contribute to improving the state of health of the inhabitants of Łódź as well as other cities and industrial populations, where the population of Łódź may act as a representative. THE AIM OF THE STUDYThe study aimed at listing factors which determine premature mortality of the citizens of Łódź, basing on the results of empirical data the sources of which are multidirectional epidemiological studies. Researchers attempt to identify factors influencing the phenomenon of premature deaths.

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Impact of socioeconomic, behavioral and clinical risk factors on mortality

Cited by 32 publications

References 26 publications

Does cytomegalovirus infection contribute to socioeconomic disparities in all-cause mortality?

Does cytomegalovirus infection contribute to socioeconomic disparities in all-cause mortality?

Gainful employment and risk of mortality after spinal cord injury: effects beyond that of demographic, injury and socioeconomic factors

Determinants of premature mortality in a city population: An eight-year observational study concerning subjects aged 18–64

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