Annotated Bibliography, NLMS

Annotated Bibliography, NLMS

Updated July 30, 2002

Annotated Bibliography

National Longitudinal Mortality Study

1. Rogot E, Feinleib M, Ockay KA, Schwartz S H, Bilgrad R, Patterson JE: On the Feasibility of Linking Census Samples to the National Death Index for Epidemiologic Studies: A Progress Report. Am J Public Health 1983;73:1265-1269.

2. Rogot E, Schwartz SH, O'Conor KV, Olsen CL: The Use of Probabilistic Methods in Matching Census Samples to the National Death Index. 1983 Proceedings of the Section on Survey Research Methods, American Statistical Association, 319-324. Also published in Statistics of Income and Related Administrative Record Research: 1983. Department of the Treasury, Internal Revenue Service, Statistics of Income Division, 75-80.

3.Makuc D, McMillen M, Feinleib M, McMillen D, Schwartz W, Rogot E: An overview of the U.S. National Longitudinal Mortality Study. 1984 Proceedings of the Section on Social Statistics, American Statistical Association.

4. Johnson N, Rogot E, Glover C, Sorlie P, McMillen M.: General Mortality Among Selected Census Bureau Sample Cohorts for 1979-1981. 1985 Proceedings of the Section on Survey Research Methods, American Statistical Association.

5. Rogot E, Sorlie P, Johnson NJ, Glover CS, Makuc D: Mortality by Cause of Death Among Selected Census Bureau Sample Cohorts for 1979-1981. 1985 Proceedings of the Section on Survey Research Methods, American Statistical Association.

6. Rogot E, Sorlie P, Johnson NJ: Probabilistic methods in matching Census samples to the National Death Index. J Chron Dis 1986;39:719-734.

A. Defines the NLMS screening algorithm and presents the findings of an application of the algorithm in a pilot study. Results indicate that the NLMS match strategy is sound and has universal application potential.

7.Rogot E, Sorlie PD, Johnson NJ, Glover CS, Treasure DW: A Mortality Study of One Million Persons by Demographic, Social and Economic Factors: 1979-1981 Follow-up. First Data Book. NIH Publication No 88-2896. National Institutes of Health, PHS, DHHS. 1988.

A. Twelve tables give observed and expected sex-race-age frequencies for demographic and socio-economic variables. Frequencies are presented for race, geographical division, SMSA status, nativity, Hispanic status, income, education, household size, marital status, employment status, major occupation, and major industry.

Annotated Bibliography, NLMS

Updated July 30, 2002

B. Some of the findings highlighted in the ASelected Study Findings@ include:

1. Black men have higher SMR=s for all cause mortality than white men for ages 0-74 but not for ages 75 and older.

2. For all cause deaths for white men, the Pacific states have the lowest SMR(87) and the Middle Atlantic states have the highest SMR(107).

3. For black males, ages 0-64, all cause SMR arre lowest for those living in an SMSA but not in the central city.

4. Foreign-born men have lower all-cause mortality ratios then men born in the United States.

5. There is an inverse relationship for level of education and all cause mortality for both men and women. Very strong relationships indicated for cardiovascular disease, heart disease and ischemic heart disease.

6. For white men ages 25-64, the SMR is 3 times higher for persons with income $50,000 or mor than for persons with income less than $5,000.

7. Both males and females living alone have higher SMR=s than persons of the same sex living in multiple member households.

8. The SMR=s for white males who are laborers are nearly twice as high as for the corresponding age groups of professional or technical workers.

8. Sorlie PD, Rogot E: Mortality by employment status in the National Longitudinal Mortality Study. Am J Epidemiol 1990;132:983-992.

9. Sorlie PD, Rogot E, Johnson NJ: Validity of demographic characteristics on the death certificate. Epidemiology 1992;3:181-184.

A. Highest agreement of education on NLMS and education on death certificate occurred for persons who had completed four years of a high school education.

B. For NLMS education levels less than four years of high school, education on the death certificate tends to be recorded at a higher level.

10.Rogot E, Sorlie PD, Backlund E: Air conditioning and mortality in hot weather. Am J Epidemiol 1992;136:106-116.

A. Significant benefits were observed for females, for persons not in the labor force, and for persons living in fewer than 6 rooms for those having central air conditioning compared to those who don=t.

B. For persons who had central air conditioning, the death rate was 42% lower than for persons who did not have air-conditioning.

C. There was no statistical difference in mortality rates between those with no air-conditioning and those with room air-conditioning only.

Annotated Bibliography, NLMS

Updated July 30, 2002

11.Rogot E, Sorlie PD, Johnson NJ: Life expectancy by employment status, income and education in the National Longitudinal Mortality Study. Public Health Reports 1992;107:457-461.

A. Life expectancy varies directly with income and education.

B. Life expectancy for white males of age 25 differed by 6 years between the persons with the lowest levels of education and those with the highest level.

C. Life expectancy for white males age 25 differed by about 10 years between men with the highest levels of income and those with the lowest.

12.Sorlie P, Rogot E, Anderson RT, Johnson NJ, Backlund E: Black-white mortality differences by family income. Lancet 1992;340:346-350.

A. For each black-white, male-female sex/race combination mortality rates are lower for higher income groups than for lower groups.

B. At each level of income, blacks have a higher mortality rate than whites

C. Lower death rates are observed for higher income for the three cause of death groupings of cardiovascular, all cancers and other diseases that cancers or cardiovascular.

D. After adjustment for income, blacks have higher death rates than whites for each of the three disease groupings.

13.Rogot E, Sorlie PD, Johnson NJ, Schmitt C: A Mortality Study of 1.3 Million Persons by Demographic, Social and Economic Factors: 1979-1985 Follow-up. Second Data Book. NIH Publication No 92-3297. National Institutes of Health, PHS, DHHS. 1992.

14.Sorlie PD, Backlund E, Johnson NJ: Mortality by Hispanic Status in the United States. JAMA 1993;270:2464-2468.

15.Sorlie PD, Johnson NJ, Backlund E, Bradham DD: Mortality in the uninsured compared to those with public and private health insurance. Arch Int Medicine 1994;154:2409-2416.

A. After adjustments of age and income, persons with medicare and medicaid coverage only and persons with no health insurance had higher mortality risk than persons with employer-provided insurance.

B. Moratlity rates were higher for those with lower incomes after adjustment for insurance status.

C. Persons with income less than $10,000/year had mortality risk about 2 times as high as persons with incomes greater than $25,000/year.

16.Sorlie PD, Backlund E, Keller JB: U.S. Mortality by economic, demographic, and social characteristics: The National Longitudinal Mortality Study. Am J of Public Health 1995;85:949-956.

Annotated Bibliography, NLMS

Updated July 30, 2002

17. Howard G, Anderson R, Sorlie P, Andrews V, Backlund E, Burke GL: Ethnic differences in stroke mortality between non-Hispanic whites, Hispanic whites and blacks: The National Longitudinal Mortality Study. Stroke 1994;25:2120-2125.

18. Backlund E, Sorlie PD, Johnson NJ: The shape of the relationship between income and mortality in the United States: Evidence from the National Longitudinal Mortality Study. Ann Epidemiol 1996;6:12-20.

A. Income-mortality gradient shown to be much smaller at the high income levels than at the low to moderate income levels.

B. The income-mortality gradient was much smaller in the elderly than in the working population.

C. The study suggests that health benefits associated with increased income diminish as income increases.

19.Smith MH, Anderson R, Bradham DD, Longino Jr CF: Rural-urban differences in mortality among Americans 55 and older: Analysis of the National Longitudinal Mortality Study. J Rural Health 1995;11:274-285.

20.Preston SH, Elo IT: Are educational differentials in adult mortality increasing in the United States? Journal of Aging and Health 1995;7:476-496.

21.Elo IT, Preston SH: Educational differentials in mortality: United States, 1979-1985. Soc Sci Med 1996;42:47-57.

22.Sorlie PD, Johnson NJ: Validity of education information on the death certificate. Epidemiology 1996;7:437-439.

A. Results showed that there was a tendency to report the education as higher on the death certificate than as given in the NLMS.

B. Of those who were reported as high school graduate on the death certificate, 38% were reported as less than high school graduate in the NLMS.

C. The bias of over stating education is more pronounced for older aged person than for younger aged persons.

23.Anderson RT, Sorlie P, Backlund E, Johnson N, Kaplan G: Mortality effects of community socioeconomic status. Epidemiology 1997;8:42-47.

24.Howard G, Anderson R, Johnson NJ, Sorlie P, Russell G, Howard VJ: An evaluation of social status as a contributing factor to the stoke belt region of the United States. Stroke 1997;28:936-940.

Annotated Bibliography, NLMS

Updated July 30, 2002

25. Gregorio DI, Walsh SJ, Paturzo D: The effects of occupation-based social position on mortality in a large American cohort. Am J Public Health 1997;87:1472-1475.

26. Kunst, Anton: Cross-national Comparisons of Socio-Economic Differences in Mortality. Erasmus University, Rotterdam, 1997, 264 pp.

27. Kposowa AJ, Breault KD, Singh GK: White male suicide in the United States: A multivariate individual-level analysis. Social Forces 1995;74:315-323.

28.Singh GK, Yu SM: Trends and differentials in adolescent and young adult mortality in the United States, 1950 through 1993. Am J Public Health 1996;86:560-564.

29. Hoyert DL, Singh GK, Rosenberg HM: Sources of data on socio-economic differential mortality in the United States. J Official Stat 1995;11:233-260.

30.Singh GK, Yu SM: US childhood mortality, 1950 through 1993, trends and socioeconomic differentials. Am J Public Health 1996;86:505-512.

31. Kposowa AJ, Singh GK, Breault KD: The effects of marital status and social isolation on adult male homicides in the United States; Evidence from the National Longitudinal Mortality Study. J Quantitative Criminology 1994;10:277-289.

32. Backlund E, Sorlie PD, Johnson NJ: A Comparison of the Relationships of Education and Income with Mortality: The National Longitudinal Mortality Study. Soc Sci and Med. 1999;49:1373-1384.

A. The functional forms for both education and income are nonlinear.

B. For both males and females, education is better fit by trichotomy, splitting education into less-than-high school, high school, and greater-than-high school, than by a linear function.

C. Interpreting the functional forms suggests that mortality differences may be a function of income at the low end of the socio-economic continuum, but primarily a function of education at the high end.

33. Johnson NJ, Sorlie PD, Backlund E: The impact of specific occupation on mortality in the U.S. National Longitudinal Mortality Study. Demography 1999;36:355-367.

A. Higher risk is observed in moving across the occupational spectrum from less skilled labor intensive jobs to the highly skilled-highly trained jobs.

B. Mortality differences obtained for social status groups of specific occupations are almost completely accounted for by adjustments for income and education.

Annotated Bibliography, NLMS

Updated July 30, 2002

C. Important differences in risk are shown for specific occupations beyond those accounted for by social status, income and education.

34. Ng-Mak DS, Dohrenwend BP, Abraido-Lanza AF, Turner JB: A further analysis of race differences in the National Longitudinal Mortality Study. Am J Pub Health 1999;89:1748-1751.

35. Singh GK. Socioeconomic and behavioral differences in health, morbidity, and mortality in Kansas: empirical data, models, and analyses. In Tarlov AR, St. Peter RF, eds, The Society and Population Health Reader, Volume II: A State and Community Perspective. New York, NY: The New Press; 2000:15-56.

1. Johnson NJ, Backlund E, Sorlie PD, Loveless CA: Marital status and mortality: The National Longitudinal Mortality Study. Ann Epidemiol 2000;10:224-238.

A. For both middle-aged males and females, non-married groups showed significantly increased mortality risk compared to corresponding married groups.

B. Older age groups did not show as strong relationsships between married and non-married groups as their younger counterparts.

C. For cardiovascular disease, statistically significant risks near 1.3 were shown for widowed and never-married white males ages 45-64 and for white females of the same age group statistically significant risks of around 1.55 were observed.

D. For all cancers and other causes, not cardiovascular, high risks were shown for all non-married groups compared to the married groups.

1. Rosenberg HM, Maurer JD, Sorlie PD, Johnson NJ, MacDorman MF, Hoyert DL, Spitler JF, Scott C. Quality of death rates by race and Hispanic origin: A summary of current research, 1999. National Center for Health Statistics. Vital Health Stat 2(128). 1999.

1. Wolfson M, Kaplan G, Lynch J, Ross N, Backlund E. Relation between income inequality and mortality: empirical demonstration. Br Med J 1999;319:953-955.

1. Abraído-Lanza AF, Dohrenwend BP, Ng-Mak DS, Turner JB. The Latino mortality paradox: A test of the Asalmon bias@ and healthy migrant hyotheses. Am J Public Health 1999;89:1543-1548.

1. Mackenbach JP, Kunst AE, Groenhof F, Borgan J, Costa G, Faggiano F, Jozan P, Leinsalu M, Martikainen P, Rychtarikova J, Valkonen T. Socioeconomic inequalities in mortality among women and among men: An international study. Am J Public Health 1999;89:1800-1806.

Annotated Bibliography, NLMS

Updated July 30, 2002

1. Jackson SA, Anderson RT, Johnson NJ, Sorlie PD. The relation of residential segregation to all-cause mortality: A study in black and white. Am J Public Health 2000;90:615-617.

A. Age adjusted mortality risk increases with increasing minority residential segregation in middle-aged blacks.

B. For most age/race/gender groups, the highest and lowest mortality risks occurred in the highest and lowest categories of residential segregation.

1. Kunst AE, Groenhof F, Andersen O, Borgan J, Costa G, Desplanques G, Filakti H, Giraldes MR, Faggiano F, Harding S, Junker C, Martikainen P, Minder C, Nolan B, Pagnanelli F, Regidor E, Vagero D, Valkonen T, Mackenbach JP. Occupational class and ischemic heart disease mortality in the United States and 11 European countries. Am J Public Health 1999;89:47-55.

1. Liao Y, McGee DL, Cooper RS. Mortality among US adult Asians and Pacific Islanders: Findings from the National Health Interview Surveys and the National Longitudinal Mortality Study. Ethn Dis 1999;9:423-433.

1. Kposowa AJ. Suicide mortality in the United States: Differentials by industrial and occupational groups. Am J Ind Med 1999;36:645-652.

1. Howard G, Russell GB, Anderson R, Evans GW, Morgan T, Howard VJ, Burke GL. Role of social class in excess black stroke mortality. Stroke 1995;26:1759-1763.

1. Kposowa AJ. Marital status and suicide in the National Longitudinal Mortality Study. J Epidemiol Community Health. 2000; 54(4):254-261.

1. Howard G, Anderson RT, Russell G, Howard VJ, Burke GL: Race, socioeconomic status, and cause-specific mortality. Ann Epidemiol 2000;10:214-223.

1. Singh GK, Siahpush M. All-cause and cause-specific mortality of immigrants and native born in the United States. Am J Public Health. 2001;91(3):392-399.

49. Singh GK, Hoyert DL: Social epidemiology of chronic liver disease and cirrhosis mortality in the United States, 1935-1997: Trends and differentials by ethnicity, socioeconomic status, and alcohol consumption. Human Biol 2000;72:801-820.

50. Kposowa AJ. Unemployment and suicide: a cohort analysis of social factors predicting suicide in the US National Longitudinal Mortality Study. Psychol Med. 2001; 31(1):127-138.

51.Kaufman JS, Kaufman S. Assessment of structured socioeconomic effects on health. Epidemiology. 2001;12(2):157-167.

Annotated Bibliography, NLMS

Updated July 30, 2002

52.Muntaner C, Sorlie P, O=Campo P, Johnson N, Backlund E. Occupational hierarchy, economic sector, and mortality from cardiovascular disease among men and women: findings from the National Longitudinal Mortality Study. Ann Epidemiol. 2001;11(3):194-201.

53. Richardus JH, Kunst AE: Black-white differences in infectious disease mortality in the United States. Am J Public Health 2001;91:1251-1253.

54. Hussey JM: The effects of race, socioeconomic status, and household structure on injury mortality in children and young adults. Maternal and Child Health J 1997;1:217-227.

55.Singh GK, Siahpush M. 2002. Ethnic-Immigrant Differentials in Health Behaviors, Morbidity, and Cause-Specific Mortality in the United States: An Analysis of Two National Databases. Human Biology. 74(1): 83-109.