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Race, Socioeconomic Status, and the Use of Bariatric Surgery in Michigan

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Abstract

Studies examining the characteristics of patients undergoing bariatric surgery in the USA have concluded that the procedure is not being used equitably. We used population-based data from Michigan to explore disparities in the use of bariatric surgery by gender, race, and socioeconomic status. We constructed a summary measure of socioeconomic status (SES) for Michigan postal ZIP codes using data from the 2000 census and divided the population into quintiles according to SES. We then used data from the state drivers’ license list and 2004–2005 state inpatient and ambulatory surgery databases to examine population-based rates of morbid obesity and bariatric surgery in adults according to gender, race, and socioeconomic status. There is an inverse linear relationship between SES and morbid obesity. In the lowest SES quintile, 13% of females and 7% of males have a body mass index >40 compared to 4% of females and males in the highest SES quintile. Overall rates of bariatric surgery were highest for black females (29.4/10,000), followed by white (21.3/10,000), and other racial minority (8.6/10,000) females. Rates of bariatric surgery were low (<6/10,000) for males of all racial groups. An inverse linear relationship was observed between SES and rates of bariatric surgery among whites. However, for racial minorities, rates of surgery are lower in the lowest SES quintiles with the highest rates of bariatric surgery in the medium or highest SES quintiles. In contrast with prior studies, we do not find evidence of wide disparities in the use of bariatric surgery.

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References

  1. Sturm R. Increases in morbid obesity in the USA: 2000–2005. J R Inst Public Health. 2007;121:492–6.

    CAS  Google Scholar 

  2. Santry H, Gillen D, Lauderdale D. Trends in bariatric surgical procedures. J Am Med Assoc. 2005;294(15):1909–17.

    Article  CAS  Google Scholar 

  3. Sjostrom L, Narbro K, Sjostrom C. Effects of bariatric surgery on mortality in Swedish obese subjects. N Engl J Med. 2007;357(8):741–52.

    Article  PubMed  Google Scholar 

  4. Dymek MP, Le Grange D, Neven K, et al. Quality of life after gastric bypass surgery: a cross-sectional study. Obes Res. 2002;10(11):1135–42.

    Article  PubMed  Google Scholar 

  5. Hafner RJ, Watts JM, Rogers J. Quality of life after gastric bypass for morbid obesity. Int J Obes. 1991;15(8):555–60.

    PubMed  CAS  Google Scholar 

  6. Adams T, Gress R, Smith S, et al. Long-term mortality after gastric bypass surgery. N Engl J Med. 2007;357(8):753–61.

    Article  PubMed  CAS  Google Scholar 

  7. Mokdad A, Bowman B, Ford E, et al. The continuing epidemic of obesity and diabetes in the United States. J Am Med Assoc. 2001;286(10):1195–200.

    Article  CAS  Google Scholar 

  8. Flegal K, Carroll M, Ogden C, et al. Prevalence and trends in obesity among US adults, 1999–2000. J Am Med Assoc. 2007;288(14):1723–7.

    Article  Google Scholar 

  9. Livingston E, Ko C. Socioeconomic characteristics of the population eligible for obesity surgery. Surgery. 2004;2004(135):3.

    Google Scholar 

  10. Levi J, Vinter S, Richardson L, et al. F as in Fat: how obesity policies are failing in America. Washington, DC: Trust for America’s Health; 2009.

    Google Scholar 

  11. Diez Roux AV, Merkin SS, Arnett D, et al. Neighborhood of residence and incidence of coronary heart disease. N Engl J Med. 2001;345(2):99–106.

    Article  PubMed  CAS  Google Scholar 

  12. Black D, Taylor A, Coster D. Accuracy of self-reported body weight: stepped Approach Model component assessment. Health Educ Res. 1998;13:301–7.

    Article  PubMed  CAS  Google Scholar 

  13. Engstrom J, Paterson S, Doherty A, et al. Accuracy of self-reported height and weight in women: an integrative review of the literature. J Midwifery Womens Health. 2003;48:338–45.

    Article  PubMed  Google Scholar 

  14. Ezzati M, Martin H, Skjold S, et al. Trends in national and state-level obesity in the USA after correction for self-report bias: analysis of health surveys. J R Soc Med. 2006;99:250–7.

    Article  PubMed  Google Scholar 

  15. Jeffery R. Bias in reported body weight as a function of education, occupation, health, and weight concern. Addict Behav. 1996;21:217–22.

    Article  PubMed  CAS  Google Scholar 

  16. Villanueva E. The validity of self-reported weight in US adults: a population-based cross-sectional study. BMC Public Health. 2001;1:11.

    Article  PubMed  CAS  Google Scholar 

  17. Zhang J, Feldblum P, Fortney J. The validity of self-reported height and weight in perimenopausal women. Am J Public Health. 1993;83:1052–3.

    Article  PubMed  CAS  Google Scholar 

  18. Cawley J, Burkhauser R. Beyond BMI: the value of more accurate measures of fatness and obesity in social science research. Cambridge, MA: National Bureau of Economic Research; 2006.

    Google Scholar 

  19. Elixhauser A, Steiner C, Harris DR, et al. Comorbidity measures for use with administrative data. Med Care. 1998;36(1):8–27.

    Article  PubMed  CAS  Google Scholar 

  20. Deyo R, Cherkin D, Ciol M. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol. 1992;45:613–9.

    Article  PubMed  CAS  Google Scholar 

  21. Royston P. Multiple imputation of missing values. Stata J. 2004;4(3):227–41.

    Google Scholar 

  22. Royston P. Multiple imputation of missing values: update. Stata J. 2005;5(2):188–201.

    Google Scholar 

  23. Royston P. Multiple imputation of missing values: update of ice. Stata J. 2005;5(4):527–36.

    Google Scholar 

  24. Bach P, Cramer L, Warren J, et al. Racial differences in the treatment of early-stage lung cancer. N Engl J Med. 1999;341(16):1198–205.

    Article  PubMed  CAS  Google Scholar 

  25. Skinner J, Weinstein J, Sporer S, et al. Racial, ethnic, and geographic disparities in rates of knee arthroplasty among Medicare patients. N Engl J Med. 2003;349:1350–9.

    Article  PubMed  CAS  Google Scholar 

  26. Smedley B, Stith A, Nelson A, editors. Unequal treatment: confronting racial and ethnic disparities in health care. Washington DC: National Academies Press; 2002.

  27. Martin M, Beekley A, Kjorstad R, Sebesta J. PL-217. Socioeconomic disparities in eligibility and access to bariatric surgery: A national population-based analysis. In: 26th Annual Meeting of the American Society for Metabolic & Bariatric Surgery (ASMBS). Dallas, TX; 2009.

  28. Sobal J, Stunkard A. Socioeconomic status and obesity: a review of the literature. Psychol Bull. 1989;105:260–75.

    Article  PubMed  CAS  Google Scholar 

  29. Wang Y, Beydoun M. The obesity epidemic in the United States—gender, age, socioeconomic, racial/ethnic, and geographic characteristics: a systematic review and meta-analysis. Epidemiol Rev. 2007;29:6–28.

    Article  PubMed  CAS  Google Scholar 

  30. Zagorsky J. Health and wealth: the late-20th century obesity epidemic in the U.S. Econ Hum Biol. 2005;3:296–313.

    Article  PubMed  Google Scholar 

  31. Zhang Q. Socioeconomic inequality of obesity in the United States: do gender, age, and ethnicity matter? Soc Sci Med. 2004;58:1171–80.

    Article  PubMed  Google Scholar 

  32. Zhang Q, Wang Y. Trends in the association between obesity and socioeconomic status in U.S. adults: 1971 to 2000. Obes Res. 2004;12:1622–32.

    Article  PubMed  Google Scholar 

  33. Cooper G, Yuan Z, Landefeld C, et al. Surgery for colorectal cancer: race-related differences in rates and survival among Medicare beneficiaries. Am J Public Health. 1996;86(4):582–6.

    Article  PubMed  CAS  Google Scholar 

  34. Dominitz J, Maynard C, Billingsley K, et al. Race, treatment, and survival of veterans with cancer of the distal esophagus and gastric cardia. Med Care. 2002;40(1 Supplement):I-14–26.

    Google Scholar 

  35. Miller K, Gleaves D, Hirsch T, et al. Comparisons of body image dimensions by race/ethnicity and gender in a university population. Int J Eat Disord. 2000;27(3):310–6.

    Article  PubMed  CAS  Google Scholar 

  36. Allison D, Hoy M, Fournier A, et al. Can ethnic differences in men's preferences for women's body shapes contribute to ethnic differences in female adiposity? Obes Res. 1994;1(6):425–32.

    Google Scholar 

  37. Krieger N. Overcoming the absence of socioeconomic data in medical records: validation and application of a census-based methodology. Am J Public Health. 1992;82:703–10.

    Article  PubMed  CAS  Google Scholar 

  38. Subramanian S, Chen J, Rehkopf D, et al. Comparing individual- and area-based socioeconomic disparities: a multilevel analysis of Massachusetts births, 1989–1991. Am J Epidemiol. 2006;164(9):823–34.

    Article  PubMed  CAS  Google Scholar 

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Correspondence to Nancy J. O. Birkmeyer.

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Birkmeyer, N.J.O., Gu, N. Race, Socioeconomic Status, and the Use of Bariatric Surgery in Michigan. OBES SURG 22, 259–265 (2012). https://doi.org/10.1007/s11695-010-0210-3

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