Norman J. Johnson

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.

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

Validity of demographic characteristics on the death certificate.

1000 increase in income is much greater at incomes below US

Quality of race, Hispanic ethnicity, and immigrant status in population-based cancer registry data: implications for health disparity studies

22,500 than at incomes above US

The relation of residential segregation to all-cause mortality : A study in black and white

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.

Effects of individual-level socioeconomic factors on racial disparities in cancer treatment and survival: findings from the National Longitudinal Mortality Study, 1979-2003.

In a sample of the United States population from the Census Bureaus current Population Surveys, we compared demographic characteristics with those recorded on the death certificate for the 43,000 decedents in the samples followed from 1979 to 1985. Overall percentage agreements were: Sex 99.5, Race 99.4, Place of birth 99.4, Hispanic origin 98.7, and Veteran status 95.2. Relatively fewer American Indians and Asian/Pacific Islanders had death certificates that agreed with the baseline race (73.6% and 82.4%, respectively). The direction of disagreement suggests that current estimates of mortality rates for American Indians and Asian/Pacific Islanders are underestimated.

Validity of education information on the death certificate.

Population-based cancer registry data from the Surveillance, Epidemiology, and End Results (SEER) Program at the National Cancer Institute are based on medical records and administrative information. Although SEER data have been used extensively in health disparities research, the quality of information concerning race, Hispanic ethnicity, and immigrant status has not been systematically evaluated. The quality of this information was determined by comparing SEER data with self-reported data among 13,538 cancer patients diagnosed between 1973–2001 in the SEER—National Longitudinal Mortality Study linked database. The overall agreement was excellent on race (κ = 0.90, 95% CI = 0.88–0.91), moderate to substantial on Hispanic ethnicity (κ = 0.61, 95% CI = 0.58–0.64), and low on immigrant status (κ = 0.21. 95% CI = 0.10, 0.23). The effect of these disagreements was that SEER data tended to under-classify patient numbers when compared to self-identifications, except for the non-Hispanic group which was slightly over-classified. These disagreements translated into varying racial-, ethnic-, and immigrant status-specific cancer statistics, depending on whether self-reported or SEER data were used. In particular, the 5-year Kaplan–Meier survival and the median survival time from all causes for American Indians/Alaska Natives were substantially higher when based on self-classification (59% and 140 months, respectively) than when based on SEER classification (44% and 53 months, respectively), although the number of patients is small. These results can serve as a useful guide to researchers contemplating the use of population-based registry data to ascertain disparities in cancer burden. In particular, the study results caution against evaluating health disparities by using birthplace as a measure of immigrant status and race information for American Indians/Alaska Natives.

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

OBJECTIVES This study investigated the influence of an aggregate measure of the social environment on racial differences in all-cause mortality. METHODS Data from the National Longitudinal Mortality Study were analyzed. RESULTS After adjustment for family income, age-adjusted mortality risk increased with increasing minority residential segregation among Blacks aged 25 to 44 years and non-Blacks aged 45 to 64 years. In most age/race/gender groups, the highest and lowest mortality risks occurred in the highest and lowest categories of residential segregation, respectively. CONCLUSIONS These results suggest that minority residential segregation may influence mortality risk and underscore the traditional emphasis on the social underpinnings of disease and death.

New variable selection methods for zero-inflated count data with applications to the substance abuse field

This is the first study to use the linked National Longitudinal Mortality Study and Surveillance, Epidemiology, and End Results (SEER) data to determine the effects of individual‐level socioeconomic factors (health insurance, education, income, and poverty status) on racial disparities in receiving treatment and in survival.