National Longitudinal Mortality Study Research Articles

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.

Marital status and suicide in the National Longitudinal Mortality Study

OBJECTIVESThe purpose of the study was to examine the effect of marital status on the risk of suicide, using a large nationally representative sample. A related objective was to investigate...

Relation between income inequality and mortality: empirical demonstration

Objective To assess the extent to which observed associations between income inequality and mortality at population level are statistical artifacts. Design Indirect "what if" simulation using observed risks of mortality at individual level as a function of income to construct hypothetical state-level mortality specific for age and sex as if the statistical artifact argument were 100% correct. Method Data from the 1990 census for the 50 US states plus Washington, DC, were used for population distributions by age, sex, state, and income range; data disaggregated by age, sex, and state from the Centers for Disease Control and Prevention were used for mortality; and regressions from the national longitudinal mortality study were used for the individual-level relation between income and risk of mortality. Results Hypothetical mortality, although correlated with inequality (as implied by the logic of the statistical artifact argument), showed a weaker association with the level of income inequality in each state than the observed mortality. Conclusions The observed associations in the United States at the state level between income inequality and mortality cannot be entirely or substantially explained as statistical artifacts of an underlying individual-level relation between income and mortality. There remains an important association between income inequality and mortality at state level above anything that could be accounted for by any statistical artifact. This result reinforces the need to consider a broad range of factors, including the social milieu, as fundamental determinants of health.

A further analysis of race differences in the National Longitudinal Mortality Study.

The purpose of this study was to investigate associations between race and specific causes of mortality among adults 25 years and older in the National Longitudinal Mortality Study. Mortality hazard ratios between races during 9 years of follow-up were estimated with Cox proportional hazards models, with control for multiple indicators of socioeconomic status (SES) and SES-relevant variables. Black persons younger than 65 years were at higher risk than others for all-cause and cardiovascular mortality; the strongest effects were observed among persons aged 25 through 44 years. Race, independent of SES, is related to mortality in American society, but these effects vary by age and disease categories.

Suicide mortality in the United States: differentials by industrial and occupational groups.

The objective of this study was to investigate variations in the risk of suicide by industrial and occupational groups. Cox proportional hazards regression models were fitted to the data from the National Longitudinal Mortality Study (1979-1989). In estimating the effects of industry and occupation, controls were made for the potentially confounding effects of age, sex, marital status, education, income, and region of residence. It was found that persons employed in mining experienced the highest risk of suicide (RR=4.29, CI=1.59, 12.13) compared to workers in finance, insurance, and real estate. Elevated risks were also observed among business and repair services (RR=4.20, CI=1.72, 10.25), professional and related services (RR=2.92, CI=1.25,6.82), and wholesale and retail trade (RR=2.71, CI=1.17,6.25). When comparisons were made by occupational status, it was found that laborers experienced the highest risk of suicide (RR=2.12, CI=1.09,4. 12) when compared to farmers, farm managers, and farm workers. There are differentials in the risk of suicide among industrial groups, and the industry with the highest risk is mining. The disparities in suicide remained even after the effects of socioeconomic and other variables were controlled. Further research needs to determine if the high suicide risk observed in some industrial groups may be linked to possible depressive symptomatology in the workplace.

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$1000 increase in income is much greater at incomes below US$22,500 than at incomes above US$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.

The impact of specific occupation on mortality in the U.S. National Longitudinal Mortality Study

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. High-risk 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.

The Effects of Occupation and Industry on the Risk of Homicide Victimization in the United States

This study examined individual and structural covariates of homicides among males aged 15-64 years, focusing on whether occupation and industry are risk factors for victimization. Cox's proportional hazards regression models were fitted to data from the National Longitudinal Mortality Study to estimate the effects of selected micro-level and macro-level covariates on homicide. Multivariate analysis indicated considerable racial or ethnic and socioeconomic disparities in homicide. Compared to non-Hispanic whites, Hispanics and African Americans were at higher risk of death. Those in the lowest occupational strata had a particularly high homicide risk. Others at elevated risk of homicide were persons in low-income strata and inner-city residents. Results showed that the mining industry had a significant effect on homicide. Bivariate analysis revealed that equipment operatives, operatives in general, farm laborers, farmers and farm foremen had elevated risks of homicide. However, multivariate analysis indicated no occupational differentials in the risk of homicide.

U.S. Life Tables for 1990 by Sex, Race, and Education

This article presents life tables by education for all races, whites, and blacks using data from the National Longitudinal Mortality Study scaled to official 1990 mortality rates. Life expectancies are directly correlated with educational level. At birth the difference of life expectancies between the lowest and highest educational levels is least for females (4.0 years for white females) and greatest for males (8.9 years for black males). Furthermore, life tables for the total population of each sex/racial category calculated as educationally weighted averages show that the Vital Statistics of the United States, Life Tables, 1990, are statistically significant underestimates. Corrections are greater for men than for women, and for blacks than for whites. They range from an increase at birth for white women of about 0.8 years to about 1.4 years for black males.

Evaluation of social status as a contributing factor to the stroke belt region of the United States.

The southeastern United States has stroke mortality rates above the national average. The causes for this excess mortality are unknown; however, lower socioeconomic status (SES) is a risk factor for stroke, and the lower SES in the Southeast is a potential cause. In this report we assess the proportion of the excess stroke mortality attributable to SES. The more than 400,000 participants in the National Longitudinal Mortality Study were categorized into three regions: the coastal plain region of North Carolina, South Carolina, and Georgia ("stroke buckle"); the remainder of these states plus five other southern states ("stroke belt"); and the remainder of the United States. The stroke mortality rates were calculated with and without adjustment for SES, and the proportion of the excess mortality attributable to SES was estimated. In persons between the ages of 35 and 54 years, stroke mortality in the stroke buckle is estimated to be more than twice that of the rest of the nation and 1.7 times greater for ages 55 to 74 years. For persons in the stroke belt, the stroke mortality was 1.3 times greater than that in the rest of the nation for the ages of 35 to 54 and 55 to 74 years. Less than 16% of this excess stroke morality was attributable to SES. SES does not appear to be a major contributor to the excess mortality in the southeastern United States. Of additional concern is the stroke buckle region, which was shown to have stroke mortality rates substantially greater than those in the traditionally recognized stroke belt.

The effects of race, socioeconomic status, and household structure on injury mortality in children and young adults.

Injuries are the leading killer of young persons in the United States, yet significant gaps in our understanding of this cause of death remain. By examining the independent influences of race, education, income, household structure, and residential location on injury mortality in young persons, this study addresses these gaps. Using data from the National Longitudinal Mortality Study, survival analysis is used to examine the injury mortality risk faced by 0 to 17 year olds over a nine-year follow-up period. Separate models are estimated for homicide, suicide, unintentional injury deaths, and all injury deaths. Household head's education has an independent effect on youth homicide and unintentional injury mortality risk. By contrast, family income and household structure do not have independent effects on any of the injury outcomes. Finally, much of the excess homicide risk faced by young African-Americans is explained by underlying racial differentials in socioeconomic status, household structure, and residential location. By finding an independent effect of household head's education on youth mortality risk from homicide and unintentional injuries, this study adds to the large body of evidence linking socioeconomic differentials to inequality in life chances.

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 women 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.

ESTIMATING FATALITIES INDUCED BY THE ECONOMIC COSTS OF REGULATIONS

Regulatory costs are paid by individuals, which leaves them with less disposable income. Since individuals on average use additional income to make their lives safer and healthier, the regulatory costs lead to higher mortality risks and fatalities. Based on data from the National Longitudinal Mortality Study relating income to the risk of dying, approximately each $5 million of regulatory cost induces a fatality if costs are borne equally among the public. If costs are borne proportional to income, approximately $11.5 million in regulatory costs induces a fatality. Cost-induced fatalities disproportionally burden the poor and minorities, particularly blacks.

The NHS: who is attacking, who is defending?

7. Schensul, J. J. and Guest, B. H. (1994). Ethics, ethnicity, and health care reform. In, "It Just Ain't Fair'raThe Ethics of Health Care for African Americans, ed. by A. Dula and S. Goering, Praeger Publishers, Westport, CT. 8. Ferguson, W. (1994). The physician's responsibility to medically underserved poor people. In, 'It Just Ain't Fair'--The Ethics of Health Care for African Americans, ed. by A. Dula and S. Goering, Praeger Publishers, Westport, CT. 9. Radical Health Statistics Group (1977). In Defence of the NHS, Radical Health Statistics Group, London. 10. Hahn, B. and Flood, A. B. (1995). No insurance, public insurance, and private insurance: do these options contribute to differences in general health? Journal of Health Care for the Poor and Underserved 6, 41-59. 11. Sorlie, P. D., Backlund, E. and Keller, J. B. (1995). USA mortality by economic, demographic, and social characteristics: the national longitudinal mortality study. American Journal of Public Health 85, 949-956. 12. Veatch, R. M. (1995). Abandoning informed consent. Hastings Center Report 25, 5-12.

Trends and differentials in adolescent and young adult mortality in the United States, 1950 through 1993.

Using data from the National Vital Statistics System and the National Longitudinal Mortality Study, this study examined mortality trends and differentials from 1950 through 1993 among US adolescents and young adults according to sex, race/ethnicity, education, family income, marital status, and cause of dealth. No appreciable reduction in youth mortality has occurred, especially among men. Declines in youth mortality from accidents have been nearly ofset by increases in death rates from homicide, suicide, and firearm injuries. American Indians, Blacks, males, and those with least education and income were at increased risk of both overall and injury-specific youth mortality.

US childhood mortality, 1950 through 1993: Trends and socioeconomic diffferentials.

This study examined trends and differentials in US childhood mortality from 1950 through 1993 according to sex, race/ethnicity, education, family income, and cause of death. Log-linear, multiple regression, and Cox proportional hazards regression models were applied to the data from the National Vital Statistics System, the National Longitudinal Mortality Study, and the Area Resource File. Substantial declines in US childhood mortality have occurred in the past 4 decades, primarily due to decreases in mortality from unintentional injuries, cancer, pneumonia and influenza, and congenital anomalies. The overall declining trend, however, has been dampened by a twofold to threefold increase in the suicide and homicide rates among children since 1968. Male, Black, American Indian, Hawaiian, and Puerto Rican children and those in the lower socioeconomic strata were at an increased risk of death. Increasing trends in mortality from violence, firearm injuries, and human immunodeficiency virus/acquired immunodeficiency syndrome pose a major obstacle to continued declines in US childhood mortality. Reducing socioeconomic disparities and improving access to and use of health care may bring about further declines in overall and injury-related childhood mortality.

When is enough, enough?: Sortie PD, Bachlund E, Keller JB. US mortality by economic demographic, and social characteristics: the national longitudinal mortality study. Am J Public Health. 1995;85:949ȁ956.

When is enough, enough?: Sortie PD, Bachlund E, Keller JB. US mortality by economic demographic, and social characteristics: the national longitudinal mortality study. Am J Public Health. 1995;85:949ȁ956.

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 welle-stablished 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.

Role of social class in excess black stroke mortality.

It has been suggested that a substantial proportion of the excess stroke mortality among black Americans may be attributable to relatively lower socioeconomic status (SES) in this group. In this report we provide the first quantitative estimates of the proportion of excess black stroke mortality attributable to SES for a large population-based cohort. We used data from the National Longitudinal Mortality Study for persons 45 years and older (73,400 white men, 87,528 white women, 6522 black men, and 8816 black women). Sex-specific proportional hazards model were used to estimate excess black stroke mortality with and without adjustment for education and income (measures of SES). The contribution of SES to the excess black stroke risk was estimated from the difference in regression coefficients for race in these models. In men, low SES was associated with increased stroke mortality (P < or = .0001) and accounted for 14% to 46% of the excess black stroke risk (P < .05). However, we could find no association between SES and stroke mortality in women, and SES did not account for a significant proportion of the excess stroke mortality in black women. Although SES proved to account for a statistically significant proportion of excess male black stroke mortality, overall SES explained less than one quarter of the observed excess between ages 45 and 65. In women, SES did not significantly reduce the estimated excess black stroke mortality. Although SES may be playing a role in excess black stroke mortality, a substantial proportion of the excess appears attributable to other sources, including cerebrovascular risk factors that are unrelated to SES, unmeasured lifestyle influences, social resources, and genetic factors.

US mortality by economic, demographic, and social characteristics: the National Longitudinal Mortality Study.

A large US sample was used to estimate the effects of race, employment status, income, education, occupation, marital status, and household size on mortality. Approximately 530,000 persons 25 years of age or more were identified from selected Current Population Surveys between 1979 and 1985. These individuals were followed for mortality through use of the National Death Index for the years 1979 through 1989. Higher mortality was found in Blacks than in Whites less than 65 years of age; in persons not in the labor force, with lower incomes, with less education, and in service and other lower level occupations; and in persons not married and living alone. With occasional exceptions, in specific sex and age groups, these relationships were reduced but remained strong and statistically significant when each variable was adjusted for all of the other characteristics. The relationships were generally weaker in individuals 65 years of age or more. Employment status, income, education, occupation, race, and marital status have substantial net associations with mortality. This study identified segments of the population in need of public health attention and demonstrated the importance of including these variables in morbidity and mortality studies.