title: US mortality by economic, demographic, and social characteristics: the National Longitudinal Mortality Study.
abstract: OBJECTIVE
  A large US sample was used to estimate the effects of race, employment status, income, education, occupation, marital status, and household size on mortality.
  
  
  METHODS
  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.
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Epidemiology and Biometry Program, National Heart, Lung, and Blood Institute, Bethesda, MD 20892, USA.
authors.forename: P D
authors.initials: PD
authors.lastname: Sorlie
authors.forename: E
authors.initials: E
authors.lastname: Backlund
authors.forename: J B
authors.initials: JB
authors.lastname: Keller
mesh_terms: D000328:Adult; D017677:Age Distribution; D000368:Aged; D003710:Demography; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D009026:Mortality / Q000639:trends*; D009790:Occupations / Q000706:statistics & numerical data; D016016:Proportional Hazards Models; D012306:Risk; D017678:Sex Distribution; D012923:Social Class; D012959:Socioeconomic Factors; D014481:United States / Q000453:epidemiology