Education, income inequality, and mortality: a multiple regression analysis

Müller, Andreas

doi:10.1136/bmj.324.7328.23

Cited by 219 publications

(142 citation statements)

References 15 publications

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“…Ahluwalia & Bolen (2008) represent lifetime e↵ects of socioeconomic limitations, and may influence future occupational opportunities and earning potential. Higher educational degrees are typical prerequisites for highly compensated work, which allows a↵ordability of health insurance coverage and access to high-quality care (Muller, 2002). Similar to the finding of the previous literature, our results show that non-Hispanic whites are more likely than any other race/group to have insurance coverage (Ahluwalia & Bolen, 2008;Cohen & Martinez, 2013).…”

Section: Discussionsupporting

confidence: 81%

“…The racial disparities in health insurance are strongly associated with socioeconomic factors: African Americans and Hispanics face greater economic and educational barriers than other groups and have less access to high-paying jobs that facilitate access to health care and health care coverage. Compared with non-Hispanic whites, non-Hispanic blacks and Hispanics tend to have higher rates of unemployment and under-representation in good-paying jobs that include health insurance as part of the benefit package (Muller, 2002). Furthermore, individuals from racially or ethnically diverse backgrounds make up a great majority of the uninsured population (Cohen & Martinez, 2013).…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Analyzing Disparities Trends for Health Care Insurance Coverage Among Non-Elderly Adults in the US: Evidence from the Behavioral Risk Factor Surveillance System, 1993-2009

et al. 2014

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A c c e s s t o h e a l t h c a r e i n t h e U n i t e d S t a t e s r e m a i n s g r e a t l y d i s p r o p o r t i o n a t e a c r o s s s o c i o e c o n o m i c g r o u p s . I t i s n o t k n o w n , h o w e v e r , w h e t h e r t h e d i s p a r i t i e s b e t w e e n t h e s o c i o e c o n o m i c c a t e g o r i e s a r e i n c r e a s i n g o r d e c r e a s i n g . T h i s a n a l y s i s u s e d a w e l le s t a b l i s h e d n o n-p a r a m e t r i c t e c h n i q u e , e m p l o y i n g t i m e -v a r y i n g c o e f f i c i e n t m o d e l s a p p l i e d t o d a t a f r o m t h e 1 9 9 3 t o 2 0 0 9 U S B e h a v i o r a l R i s k F a c t o r S u r v e i l l a n c e S y s t e m ( B R F S S ) . T h e a n a l y s i s w a s a b l e t o s h o w t h e c h a n g e s i n t h e o d d s r a t i o s o f h a v i n g n o h e a l t h i n s u r a n c e p l a n f o r v a r i a b l e s o f i n t e r e s t o v e r t i m e , t h e r e f o r e h i g h l ig h t i n g t h e c h a n g e s i n t h e d i s p a r i t i e s b e t w e e n t h e c a t e g o r i e s o f a v a r i a b l e o v e r t i m e . W h i l e o t h e r s t u d i e s h a v e a t t e m p t e d t o s h o w t h e c h a n g e s i n h e a l t h i n s u r a n c e c o v e r a g e b y s o c i o e c o n o m i c g r o u p s i n d i f f e r e n t t i m e p e r i o d s , t h e r e i s n o s t u d y t o d a t e t h a t h a s s h o w n t h e s e c h a n g e s a s a s m o o t h f u n c t i o n w i t h t i m e , t h e r e f o r e p r o v i d i n g a c l e a r e r p i c t u r e o f t h e c h a n g e s i n t h e s e d i s p a r i t i e s . T h e r e s u l t s o f t h i s a n a l y s i s s h o w , f o r i n s t a n c e , t h a t w h e n c o m p a r e d w i t h i n d i v i d u a l s w i t h a c o l l e g e e d u c a t i o n o r g r e a t e r , t h o s e w i t h l e s s t h a n a h i g h s c h o o l e d u c a t i o n s h o w e d a s t e a d y i n c r e a s e i n t h e o d d s r a t i o s f o r h a v i n g n o h e a l t hi n s u r a n c e . T h e s a m e t r e n d s e e m s a p p l i c a b l e a l t h o u g h i n a l e s s-c l e a r w a y t o H i s p a n i c s a n d N o n -H i s p a n i c b l a c k r a c e -e t h n i c i t i e s , c o m p a r e d w i t h n o n -H i s p a n i c w h i t e s ( t h e r e f e r e n c e r a c e c a t e g o r y ) . A s m e a s u r e s o f t h e A f f o r d a b l e C a r e A c t a r e b e i n g g r a d u a l l y i m p l e m e n t e d , s t u d i e s a r e n e e d e d t o p r o v i d e b a s e l i n e i n f o r m a t i o n a b o u t h e a l t h c a r e a c c e s s d i s p a r i t y , i n o r d e r t o g a u g e a n y c h a n g e s i n h e a l t h c a r e a c c e s s o v e r t i m e ; B R F S S c a n b e a u s e f u l d a t a s o u r c e i n a c c o m p l i s h i n g t h i s t a s k . K e y w o r d s : U S A , b i g d a t a , d i s p a r i t i e s , h e a l t h p l a n , h e a l t h s u r v e i l l a n c e d a t a , P -s p l i n e s , t e m p o r a l t r e n d s , v a r y i n g c o e f f i c i e n t m o d e l J E L C o d e s : I 1 4Addr...

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Section: Discussionsupporting

confidence: 81%

Section: Discussionmentioning

confidence: 99%

Analyzing Disparities Trends for Health Care Insurance Coverage Among Non-Elderly Adults in the US: Evidence from the Behavioral Risk Factor Surveillance System, 1993-2009

et al. 2014

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“…Previous research has suggested that education may be such a determinant, because it has been linked to mortality risks both between and within countries, including in natural experiments (1)(2)(3)(4).…”

Section: Epidemiology | Natural Experimentsmentioning

confidence: 99%

Causal effect of education on mortality in a quasi-experiment on 1.2 million Swedes

Lager

Torssander

2012

Proc. Natl. Acad. Sci. U.S.A.

127

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In 1949-1962, Sweden implemented a 1-y increase in compulsory schooling as a quasi-experiment. Each year, children in a number of municipalities were exposed to the reform and others were kept as controls, allowing us to test the hypothesis that education is causally related to mortality. We studied all children born between 1943 and 1955, in 900 Swedish municipalities, with control for birth-cohort and area differences. Primary outcome measures are all-cause and cause-specific mortality until the end of 2007. The analyses include 1,247,867 individuals, of whom 92,351 died. We found lower all-cause mortality risk in the experimental group after age 40 [hazard ratio (HR) = 0.96, 95% confidence interval (CI) 0.93-0.99] but not before (HR = 1.03, 95% CI 0.98-1.07) or during the whole follow-up (HR = 0.98, 95% CI 0.95-1.01). After age 40, the experimental group had lower mortality from overall cancer, lung cancer, and accidents. In addition, exposed women had lower mortality from ischemic heart disease, and exposed men lower mortality from overall external causes. In analyses stratified for final educational level, we found lower mortality in the experimental group within the strata that settled for compulsory schooling only (HR = 0.94, 95% CI 0.89-0.99) and compulsory schooling plus vocational training (HR = 0.92, 95% CI 0.88-0.97).

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“…Previous studies have importantly shown that the compositional effect of income on health may generate a spurious association between inequality and health (Jen et al 2008). Previous study has also identified a negative association between inequality and education as a potential cause of the association between inequality and health (Muller 2002).…”

Section: Covariatesmentioning

confidence: 99%

Long-term exposure to income inequality: implications for physical functioning at older ages

2013

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The 'inequality hypothesis' proposes that higher levels of societal income inequality have a direct negative causal effect on health. Support for this hypothesis has been mixed; particularly among older people. However, most previous studies have not accounted for people's exposure to inequality over the long-term. We aimed to address this problem by examining the implications of long-term inequality exposure for older people's physical health. Data on individual health and covariates were drawn from three large, comparable surveys of older people, covering 16 countries: the English Longitudinal Study of Ageing, the Survey of Health and Retirement in Europe and the U.S. Health and Retirement Study. Historical inequality information was derived from the Standardised World Income Inequality Database. We used multilevel regression methods to model the association between longterm average inequality and three measures of physical functioning: grip strength, lung function and self-reported activity limitation. Exposure to higher average long-term levels of inequality was significantly negatively related to objectively measured grip strength and lung function, but unrelated to self-reported limitations (although increasing inequality over time was positively related to self-reported limitations). The grip strength and lung function associations were partially explained by between-country differences in height, and in the latter case this factor may fully account for the apparent effect of inequality. We discuss implications of these results for the inequality hypothesis.

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Education, income inequality, and mortality: a multiple regression analysis

Cited by 219 publications

References 15 publications

Analyzing Disparities Trends for Health Care Insurance Coverage Among Non-Elderly Adults in the US: Evidence from the Behavioral Risk Factor Surveillance System, 1993-2009

Analyzing Disparities Trends for Health Care Insurance Coverage Among Non-Elderly Adults in the US: Evidence from the Behavioral Risk Factor Surveillance System, 1993-2009

Causal effect of education on mortality in a quasi-experiment on 1.2 million Swedes

Long-term exposure to income inequality: implications for physical functioning at older ages

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