Eric Backlund

Marital Status and Mortality ☆: The National Longitudinal Mortality Study

PURPOSE To examine the effect of marital status (married, widowed, divorced/separated, and never-married) on mortality in a cohort of 281,460 men and women, ages 45 years and older, of black and white races, who were part of the National Longitudinal Mortality Study (NLMS). METHODS Major findings are based on assessments of estimated relative risk (RR) from Cox proportional hazards models. Duration of bereavement for the widowed is also estimated using the Cox model. RESULTS For persons aged 45-64, each of the non-married groups generally showed statistically significant increased risk compared to their married counterparts (RR for white males, 1.24-1.39; white females, 1.46-1.49; black males, 1.27-1.57; and black females, 1. 10-1.36). Older age groups tended to have smaller RRs than their younger counterparts. Elevated risk for non-married females was comparable to that of non-married males. For cardiovascular disease mortality, widowed and never-married white males ages 45-64 showed statistically significant increased RRs of 1.25 and 1.32, respectively, whereas each non-married group of white females showed statistically significant increased RRs from 1.50 to 1.60. RRs for causes other than cardiovascular diseases or cancers were high (for white males ages 45-64: widowed, 1.85; divorced/separated, 2.15; and never-married, 1.48). The importance of labor force status in determining the elevated risk of non-married males compared to non-married females by race is shown. CONCLUSIONS Each of the non-married categories show elevated RR of death compared to married persons, and these effects continue to be strong after adjustment for other socioeconomic factors.

Mortality effects of community socioeconomic status

We linked data from the National Longitudinal Mortality Study to census tract information on 239,187 persons to assess 11‐year mortality risk among black and white men and women associated with median census tract income, adjusted for individual family income from the Current Population Survey. We stratified Cox proportional hazards models by ages 25–64 years and 65 years and older. We used a robust covariance matrix to obtain standard errors for the model coefficients that account for correlation among individuals in the same census tract. Both income indicators were independently related to all‐cause mortality. Among persons age 25–64 years, the rate ratios (RR) for individual family income and the median census tract income, respectively, for low income relative to high income were RR = 2.10 vs 1.49 for black men, RR = 2.03 vs 1.26 for white men; and RR = 1.92 vs 1.30 for black women and RR = 1.61 vs 1.16 for white women. Among persons age 65 years or greater, only individual family income was associated with mortality, and only for white men. Although family income has a stronger association with mortality than census tract, our results indicate that, more broadly, area socioeconomic status makes a unique and substantial contribution to mortality and should be explored in health policy and disease prevention research.

The Shape of the Relationship between Income and Mortality in the United States Evidence from the National Longitudinal Mortality Study

A follow-up study based on a large national sample was used to examine differences in the well-established inverse gradient between income and mortality at different income levels. The study showed the income-mortality gradient to be much smaller at high income levels than at low to moderate income levels in the working age (25 to 64 years) and elderly (over 65 years) populations for men and women both before and after adjustment for other socioeconomic variables. In addition, a much larger gradient existed for working age women at extreme poverty levels than for those women at low to moderate income levels. The income-mortality gradient was much smaller in the elderly than in the working age population. The study also examined the ability of several different mathematic functions of income to delineate the relationship between income and mortality. The study suggested that the health benefits associated with increased income diminish as income increases.

A comparison of the relationships of education and income with mortality: the national longitudinal mortality study

A sample of over 400,000 men and women, ages 25-64, from the National Longitudinal Mortality Study (NLMS), a cohort study representative of the noninstitutionalized US population, was followed for mortality between the years of 1979 and 1989 in order to compare and contrast the functional forms of the relationships of education and income with mortality. Results from the study suggest that functional forms for both variables are nonlinear. Education is described significantly better by a trichotomy (represented by less than a high school diploma, a high school diploma or greater but no college diploma, or a college diploma or greater) than by a simple linear function for both men (p < 0.0001 for lack of fit) and women (p = 0.006 for lack of fit). For describing the association between income and mortality, a two-sloped function, where the decrease in mortality associated with a US

The Hispanic Mortality Advantage and Ethnic Misclassification on US Death Certificates

1000 increase in income is much greater at incomes below US

THE IMPACT OF SPECIFIC OCCUPATION ON MORTALITY IN THE U.S. NATIONAL LONGITUDINAL MORTALITY STUDY

22,500 than at incomes above US

Occupational hierarchy, economic sector, and mortality from cardiovascular disease among men and women findings from the National Longitudinal Mortality Study

22,500, fits significantly better than a linear function for both men (p < 0.0001 for lack of fit) and women (p = 0.0005 for lack of fit). The different shapes for the two functional forms imply that differences in mortality may primarily be a function of income at the low end of the socioeconomic continuum, but primarily a function of education at the high end.

Mortality by Hispanic Status in the United States

OBJECTIVES We tested the data artifact hypothesis regarding the Hispanic mortality advantage by investigating whether and to what degree this advantage is explained by Hispanic origin misclassification on US death certificates. METHODS We used the National Longitudinal Mortality Study, which links Current Population Survey records to death certificates for 1979 through 1998, to estimate the sensitivity, specificity, and net ascertainment of Hispanic ethnicity on death certificates compared with survey classifications. Using national vital statistics mortality data, we estimated Hispanic age-specific and age-adjusted death rates, which were uncorrected and corrected for death certificate misclassification, and produced death rate ratios comparing the Hispanic with the non-Hispanic White population. RESULTS Hispanic origin reporting on death certificates in the United States is reasonably good. The net ascertainment of Hispanic origin is just 5% higher on survey records than on death certificates. Corrected age-adjusted death rates for Hispanics are lower than those for the non-Hispanic White population by close to 20%. CONCLUSIONS The Hispanic mortality paradox is not explained by an incongruence between ethnic classification in vital registration and population data systems.

The validity of race and Hispanic origin reporting on death certificates in the United States.

We compare mortality differences for specific and general categories of occupations using a national cohort of approximately 380,000 persons aged 25-64 from the U.S. National Longitudinal Mortality Study. Based on comparisons of relative risk obtained from Cox proportional-hazards model analyses, higher risk is observed in moving across the occupational spectrum from the technical, highly skilled occupations to less-skilled and generally more labor-intensive occupations. Mortality differences obtained for social status groups of specific occupations are almost completely accounted for by adjustments for income and education. Important differences are shown to exist for selected specific occupations beyond those accounted for by social status, income, and education. Highrisk specific occupations include taxi drivers, cooks, longshoremen, and transportation operatives. Low-risk specific occupations include lawyers, natural scientists, teachers, farmers, and a variety of engineers.

Mortality in the Uninsured Compared With That in Persons With Public and Private Health Insurance

PURPOSE Although socioeconomic position has been identified as a determinant of cardiovascular disease among employed men and women in the U.S., the role of economic sector in shaping this relationship has yet to be examined. We sought to estimate the combined effects of economic sector-one of the three major sectors of the economy: finance, government and production-and socioeconomic position on cardiovascular mortality among employed men and women. METHODS Approximately 375,000 men and women 25 years of age or more were identified from selected Current Population Surveys between 1979 and 1985. These persons were followed for cardiovascular mortality through use of the National Death Index for the years 1979 through 1989. RESULTS In men, the lowest cardiovascular mortality was found for professionals in the finance sector (76/100,000 person/years). The highest cardiovascular mortality was found among male non-professional workers in the production sector (192/100,000 person years). A different pattern was observed among women. Professional women in the finance sector had the highest rates of cardiovascular mortality (133/100,000 person years). For both men and women, the professional/non-professional gap in cardiovascular mortality was lower in the government sector than in the production and finance sectors. These associations were strong even after adjustment for age, race and income. CONCLUSIONS Characteristics of government, finance and production work differentially influence the risk of cardiovascular disease mortality. Men, women, professionals and non-professionals experience this risk differently.