Annals of Epidemiology
Volume 19, Issue 7 , Pages 504-511 , July 2009

The Male–Female Health–Survival Paradox: A Survey and Register Study of the Impact of Sex-Specific Selection and Information Bias

  • Anna Oksuzyan, MD, MPH

      Affiliations

    • Max Planck Institute for Demographic Research, Rostock, Germany
    • Danish Aging Research Center, Institute of Public Health, University of Southern Denmark, Odense
    • Corresponding Author InformationAddress correspondence to: Anna Oksuzyan, Address: Max Planck Institute for Demographic Research, Konrad-Zuse Str.1, 18057 Rostock, Germany. Tel.: +49 381 2082 178; fax: +49 381 2082 478.
  • ,
  • Inge Petersen, MSc

      Affiliations

    • Danish Aging Research Center, Institute of Public Health, University of Southern Denmark, Odense
  • ,
  • Henrik Stovring, PhD

      Affiliations

    • Research Unit of General Practice, University of Southern Denmark, Odense
  • ,
  • Paul Bingley, MA, PhD

      Affiliations

    • The Danish National Center for Social Research, Copenhagen, Denmark
  • ,
  • James W. Vaupel, MPP, PhD

      Affiliations

    • Max Planck Institute for Demographic Research, Rostock, Germany
  • ,
  • Kaare Christensen, MD, PhD

      Affiliations

    • Danish Aging Research Center, Institute of Public Health, University of Southern Denmark, Odense
    • The Danish Twin Registry, University of Southern Denmark, Odense

Received 19 August 2008 ,Accepted 2 March 2009.

References 

  1. Olsen KM, Dahl S-A. Health differences between European countries. Soc Sci Med. 2007;64:1665–1678
  2. Case A, Paxson C. Sex differences in morbidity and mortality. Demography. 2005;42:189–214
  3. Barford A, Dorling D, Smith GD, Shaw M. Life expectancy: women now on top everywhere. BMJ. 2006;332:808
  4. Waldron I, Johnston S. Why do women live longer than men?. J Human Stress. 1976;2:19–30
  5. Austad S. Why women live longer than men: sex differences in longevity. Gend Med. 2006;3:79–92
  6. Christensen K, Kristiansen M, Hagen-Larsen H, Skytthe A, Bathum L, Jeune B, et al. X-linked genetic factors regulate hematopoietic stem-cell kinetics in females. Blood. 2000;95:2449–2451
  7. Owens IPF. Ecology and evolution: sex differences in mortality rate. Science. 2002;297:2008–2009
  8. Nathanson CA. Illness and the feminine role: a theoretical review. Soc Sci Med. 1975;9:57–62
  9. Galdas PM, Cheater F, Marshall P. Men and health help-seeking behavior: literature review. J Adv Nurs. 2005;49:616–623
  10. Verbrugge LM, Wingard DL. Sex differentials in health and mortality. Women Health. 1987;12:103–145
  11. Kroenke K, Spitzer RL. Gender differences in the reporting of physical and somatoform symptoms. Psychosom Med. 1998;60:150–155
  12. Wingard DL, Cohn BA, Kaplan GA, Cirillo PM, Cohen RD. Sex differentials in morbidity and mortality risk examined by age and cause in the same cohort. Am J Epidemiol. 1989;130:601–610
  13. Gaist D, Bathum L, Skytthe A, Jensen TK, McGue M, Vaupel JW, et al. Strength and anthropometric measures in identical and fraternal twins: no evidence of masculinization of females with male co-twins. Epidemiology. 2000;11:340–343
  14. Christensen K, Holm NV, McGue M, Corder L, Vaupel JW. A Danish population-based twin study on general health in the elderly. J Aging Health. 1999;11:49–64
  15. Nybo H, Gaist D, Jeune B, Bathum L, McGue M, Vaupel JW, et al. The Danish 1905 Cohort: a genetic-epidemiological nationwide survey. J Aging Health. 2001;13:32–46
  16. Christensen K, Frederiksen H, Vaupel JW, McGue M. Age trajectories of genetic variance in physical functioning: a longitudinal study of Danish twins aged 70 years and older. Behav Genet. 2003;33:125–136
  17. Støvring H. Selection bias due to immigration in pharmacoepidemiologic studies. Pharmacoepidemiol Drug Safety. 2007;16:681–686
  18. Osler M, Schroll M. Differences between participants and non-participants in a population study on nutrition and health in the elderly. Eur J Clin Nutr. 1992;46:289–295
  19. von Strauss E, Fratiglioni L, Jorm AF, Viitanen M, Winblad B. Attitudes and participation of the elderly in population surveys: data from a longitudinal study on aging and dementia in Stockholm. J Clin Epidemiol. 1998;51:181–187
  20. Boshuizen HC, Viet AL, Picavet HSJ, Botterweck A, van Loon AJM. Non-response in a survey of cardiovascular risk factors in the Dutch population: determinants and resulting biases. Public Health. 2006;120:297–308
  21. Zunzunegui MV, Beland F, Gutierrez-Cuadra P. Loss to follow-up in a longitudinal study on aging in Spain. J Clin Epidemiol. 2001;54:501–510
  22. Launer LJ, Wind AW, Deeg DJH. Nonresponse pattern and bias in a community-based cross-sectional study of cognitive functioning among the elderly. Am J Epidemiol. 1994;139:803–812
  23. Korkeila K, Suominen S, Ahvenainen J, Ojanlatva A, Rautava P, Helenius H, et al. Non-response and related factors in a nationwide health survey. Eur J Epidemiol. 2001;17:991–999
  24. van den Akker M, Buntinx F, Metsemakers JF, Knottnerus JA. Morbidity in responders and non-responders in a register-based population survey. Fam Pract. 1998;15:261–263
  25. Kjoller M, Thoning H. Characteristics of non-response in the Danish Health Interview Surveys, 1987-1994. Eur J Public Health. 2005;15:528–535
  26. Lamers LM. Medical consumption of respondents and non-respondents to a mailed health survey. Eur J Public Health. 1997;7:267–271
  27. Jacomb P, Jorm A, Korten A, Christensen H, Henderson AS. Predictors of refusal to participate: a longitudinal health survey of the elderly in Australia. BMC Public Health. 2002;2:4
  28. Drivsholm T, Eplov LF, Davidsen M, Jorgensen T, Ibsen H, Hollnagel H, et al. Representativeness in population-based studies: a detailed description of non-response in a Danish cohort study. Scand J Public Health. 2006;34:623–631
  29. Reijneveld SA, Stronks K. The impact of response bias on estimates of health care utilization in a metropolitan area: the use of administrative data. Int J Epidemiol. 1999;28:1134–1140
  30. Barat I, Andreasen F, Damsgaard EM. The consumption of drugs by 75-year-old individuals living in their own homes. Eur J Clin Pharmacol. 2000;56:501–509
  31. Roe CM, McNamara AM, Motheral BR. Gender- and age-related prescription drug use patterns. Ann Pharmacother. 2002;36:3–39
  32. Osler M, Prescott E, Gottschau A, Bjerg A, Hein HO, Sjol A, et al. Trends in smoking prevalence in Danish adults, 1964-1994. The influence of gender, age, and education. Scand J Soc Med. 1998;26:293–298
  33. Caskie GIL, Willis SL. Congruence of self-reported medications with pharmacy prescription records in low-income older adults. Gerontologist. 2004;44:176–185
  34. Van den Brandt PA, Petri H, Dorant E, Goldbohm RA, Van de Crommert S. Comparison of questionnaire information and pharmacy data on drug use. Pharm Weekbl Sci. 1991;13:91–96
  35. West SL, Savitz DA, Koch G, Strom BL, Guess HA, Hartzema A. Recall accuracy for prescription medications: self-report compared with database information. Am J Epidemiol. 1995;142:1103–1112
  36. Sjahid SI, van der Linden PD, Stricker BHC. Agreement between the pharmacy medication history and patient interview for cardiovascular drugs: The Rotterdam Elderly Study. Br J Clin Pharmacol. 1998;45:591–595

PII: S1047-2797(09)00088-X

doi: 10.1016/j.annepidem.2009.03.014

Annals of Epidemiology
Volume 19, Issue 7 , Pages 504-511 , July 2009