Advertisement

Elucidating the Multidimensionality of Socioeconomic Status in Relation to Metabolic Syndrome in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL)

  • Tasneem KhambatyEmail author
  • Neil Schneiderman
  • Maria M. Llabre
  • Tali Elfassy
  • Ashley E. Moncrieft
  • Martha Daviglus
  • Gregory A. Talavera
  • Carmen R. Isasi
  • Linda C. Gallo
  • Samantha A. Reina
  • Denise Vidot
  • Gerardo Heiss
Full length manuscript

Abstract

Background

Socioeconomic (SES) factors underlying disparities in the prevalence of metabolic syndrome (MetSyn) and consequently, type 2 diabetes among Hispanics/Latino populations are of considerable clinical and public health interest. However, incomplete and/or imprecise measurement of the multidimensional SES construct has impeded a full understanding of how SES contributes to disparities in metabolic disease. Consequently, a latent-variable model of the SES-MetSyn association was investigated and compared with the more typical proxy-variable model.

Methods

A community-based cross-sectional probability sample (2008–2011) of 14,029 Hispanic/Latino individuals of Puerto Rican, Cuban, Dominican, Central American, South American, and Mexican ancestry living in the USA was used. SES proxy’s education, income, and employment were examined as effect indicators of a latent variable, and as individual predictors. MetSyn was defined using 2009 harmonized guidelines, and MetSyn components were also examined individually.

Results

In multivariate regression analyses, the SES latent variable was associated with 9% decreased odds of MetSyn (95% confidence interval: 0.85, 0.96, P < .001) and was associated with all MetSyn components, except diastolic blood pressure. Additionally, greater income, education, and employment status were associated with 4%, 3%, and 24% decreased odds of having MetSyn, respectively (Ps < .001). The income-MetSyn association was only significant for women and those with current health insurance.

Conclusions

Hispanic/Latinos exhibit an inverse association between SES and MetSyn of varying magnitudes across SES variables. Public health research is needed to further probe these relationships, particularly among Hispanic/Latina women, to ultimately improve healthcare access to prevent diabetes in this underserved population.

Keywords

Health disparities Hispanics/Latinos Latent models Metabolic syndrome Socioeconomic status Women’s health 

Notes

Acknowledgments

The authors thank the more than 250 staff members of the HCHS/SOL for their dedication and expertise. The study website is http://www.cscc.unc.edu/hchs/.

Funding

The HCHS/SOL was carried out as a collaborative study supported by contracts from the National Heart, Lung, and Blood Institute (NHLBI) to the University of North Carolina (N01-HC25233), University of Miami (N01-HC65234), Albert Einstein College of Medicine (N01-HC65235), Northwestern University (N01-HC65236), and San Diego State University (N01-HC65237). The following institutes/centers contributed to the baseline HCHS/SOL funding period through a transfer of funds to the NHLBI: National Institute on Minority Health and Health Disparities, National Institute on Deafness and Other Communication Disorders, National Institute of Dental and Craniofacial Research, National Institute of Diabetes and Digestive and Kidney Diseases, National Institute of Neurological Disorders and Stroke, and National Institute of Health Office of Dietary Supplements. T.E., T.K., A.M., S.R., and D.V. were supported by T32 HL07426. These funding sources were not involved in the study design, data collection, analysis and interpretation of data, in the writing of this manuscript, or in the decision to submit it for publication.

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.

Informed Consent

The study protocol was approved by the Institutional Review Board (IRB) at each field center, namely the University of Miami IRB, the University of North Carolina IRB, Albert Einstein College of Medicine IRB, San Diego State University IRB, and Northwestern University IRB. Written informed consent was obtained from all participants.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Supplementary material

12529_2020_9847_MOESM1_ESM.docx (32 kb)
ESM 1 (DOCX 14 kb)

References

  1. 1.
    Go AS, Mozaffarian D, Roger VL, Benjamin EJ, Berry JD, Borden WB, et al. Heart disease and stroke statistics--2013 update: a report from the American Heart Association. Circulation. 2013;127(1):e6–e245.PubMedGoogle Scholar
  2. 2.
    Ford ES, Li C, Sattar N. Metabolic syndrome and incident diabetes current state of the evidence. Diabetes Care. 2008;31(9):1898–904.CrossRefGoogle Scholar
  3. 3.
    Ballantyne CM, et al. Metabolic syndrome risk for cardiovascular disease and diabetes in the ARIC study. Int J Obes. 2008;32(Suppl 2):S21.CrossRefGoogle Scholar
  4. 4.
    Alberti K, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the metabolic syndrome a joint interim statement of the international diabetes federation task force on epidemiology and prevention; National Heart, Lung, and Blood Institute; American Heart Association; world heart federation; international atherosclerosis society; and International Association for the Study of obesity. Circulation. 2009;120(16):1640–5.CrossRefGoogle Scholar
  5. 5.
    Heiss G, Snyder ML, Teng Y, Schneiderman N, Llabre MM, Cowie C, et al. Prevalence of metabolic syndrome among Hispanics/Latinos of diverse background: the Hispanic community health study/study of Latinos. Diabetes Care. 2014;37(8):2391–9.CrossRefGoogle Scholar
  6. 6.
    Ennis S, Rios-Vargas M, Albert N. The Hispanic Population 2010: 2010 Census Briefs. Washington, DC: US Census Bureau; 2011. 2014.Google Scholar
  7. 7.
    Piccolo RS, Subramanian SV, Pearce N, Florez JC, McKinlay J. Relative contributions of socioeconomic, local environmental, psychosocial, lifestyle/behavioral, biophysiological, and ancestral factors to racial/ethnic disparities in type 2 diabetes. Diabetes Care. 2016;39(7):1208–17.CrossRefGoogle Scholar
  8. 8.
    Bradley RH, Corwyn RF. Socioeconomic status and child development. Annu Rev Psychol. 2002;53(1):371–99.CrossRefGoogle Scholar
  9. 9.
    Adler NE, Stewart J. Health disparities across the lifespan: meaning, methods, and mechanisms. Ann N Y Acad Sci. 2010;1186(1):5–23.CrossRefGoogle Scholar
  10. 10.
    Lucove JC, Kaufman JS, James SA. Association between adult and childhood socioeconomic status and prevalence of the metabolic syndrome in African Americans: the Pitt County study. Am J Public Health. 2007;97(2):234–6.CrossRefGoogle Scholar
  11. 11.
    Chichlowska KL, Rose KM, Diez-Roux AV, Golden SH, McNeill A, Heiss G. Individual and neighborhood socioeconomic status characteristics and prevalence of metabolic syndrome. The atherosclerosis risk in communities (ARIC) study. Psychosom Med. 2008;70(9):986–92.CrossRefGoogle Scholar
  12. 12.
    Kang H-T, Kim HY, Kim JK, Linton JA, Lee YJ. Employment is associated with a lower prevalence of metabolic syndrome in postmenopausal women based on the 2007-2009 Korean National Health Examination and nutrition survey. Menopause. 2014;21(3):221–6.CrossRefGoogle Scholar
  13. 13.
    Yang X, Tao Q, Sun F, Zhan S. The impact of socioeconomic status on the incidence of metabolic syndrome in a Taiwanese health screening population. Int J Public Health. 2012;57(3):551–9.CrossRefGoogle Scholar
  14. 14.
    Gupta, R., et al., Association of educational, occupational and socioeconomic status with cardiovascular risk factors in Asian Indians: a cross-sectional study. 2012.Google Scholar
  15. 15.
    Gallo LC, Fortmann AL, Roesch SC, Barrett-Connor E, Elder JP, de los Monteros K, et al. Socioeconomic status, psychosocial resources and risk, and cardiometabolic risk in Mexican-American women. Health Psychol. 2012;31(3):334–42.CrossRefGoogle Scholar
  16. 16.
    Loucks EB, Rehkopf DH, Thurston RC, Kawachi I. Socioeconomic disparities in metabolic syndrome differ by gender: evidence from NHANES III. Ann Epidemiol. 2007;17(1):19–26.CrossRefGoogle Scholar
  17. 17.
    Gallo LC, Penedo FJ, Carnethon M, Isasi CR, Sotres-Alvarez D, Malcarne VL, et al. The Hispanic community health study/study of Latinos sociocultural ancillary study: sample, design, and procedures. Ethn Dis. 2014;24(1):77–83.PubMedPubMedCentralGoogle Scholar
  18. 18.
    Kavanagh A, Bentley RJ, Turrell G, Shaw J, Dunstan D, Subramanian SV. Socioeconomic position, gender, health behaviours and biomarkers of cardiovascular disease and diabetes. Soc Sci Med. 2010;71(6):1150–60.CrossRefGoogle Scholar
  19. 19.
    Dallongeville J, Cottel D, Ferrières J, Arveiler D, Bingham A, Ruidavets JB, et al. Household income is associated with the risk of metabolic syndrome in a sex-specific manner. Diabetes Care. 2005;28(2):409–15.CrossRefGoogle Scholar
  20. 20.
    Ruiz JM, et al. The Hispanic health paradox: from epidemiological phenomenon to contribution opportunities for psychological science. Group Process Intergroup Relat. 2016;19(4):462–76.CrossRefGoogle Scholar
  21. 21.
    González HM, et al. Diabetes awareness and knowledge among Latinos: does a usual source of healthcare matter? J Gen Intern Med. 2009;24(3):528.CrossRefGoogle Scholar
  22. 22.
    Heisler M, Faul JD, Hayward RA, Langa KM, Blaum C, Weir D. Mechanisms for racial and ethnic disparities in glycemic control in middle-aged and older Americans in the health and retirement study. Arch Intern Med. 2007;167(17):1853–60.CrossRefGoogle Scholar
  23. 23.
    Sorlie PD, Avilés-Santa LM, Wassertheil-Smoller S, Kaplan RC, Daviglus ML, Giachello AL, et al. Design and implementation of the Hispanic community health study/study of Latinos. Ann Epidemiol. 2010;20(8):629–41.CrossRefGoogle Scholar
  24. 24.
    LaVange LM, et al. Sample design and cohort selection in the Hispanic community health study/study of Latinos. Ann Epidemiol. 2010;20(8):642–9.CrossRefGoogle Scholar
  25. 25.
    Kagura J, Adair LS, Pisa PT, Griffiths PL, Pettifor JM, Norris SA. Association of socioeconomic status change between infancy and adolescence, and blood pressure, in south African young adults: birth to twenty cohort. BMJ Open. 2016;6(3):e008805.CrossRefGoogle Scholar
  26. 26.
    Blumenthal JA, Babyak MA, Hinderliter A, Watkins LL, Craighead L, Lin PH, et al. Effects of the dash diet alone and in combination with exercise and weight loss on blood pressure and cardiovascular biomarkers in men and women with high blood pressure: the encore study. Arch Intern Med. 2010;170(2):126–35.CrossRefGoogle Scholar
  27. 27.
    Arguelles W, Llabre MM, Sacco RL, Penedo FJ, Carnethon M, Gallo LC, et al. Characterization of metabolic syndrome among diverse Hispanics/Latinos living in the United States: latent class analysis from the Hispanic community health study/study of Latinos (HCHS/SOL). Int J Cardiol. 2015;184:373–9.CrossRefGoogle Scholar
  28. 28.
    Llabre MM, Arguelles W, Schneiderman N, Gallo LC, Daviglus ML, Chambers EC, et al. Do all components of the metabolic syndrome cluster together in U.S. Hispanics/Latinos? Results from the Hispanic community health study/study of Latinos. Ann Epidemiol. 2015;25(7):480–5.CrossRefGoogle Scholar
  29. 29.
    Schneiderman N, Llabre M, Cowie CC, Barnhart J, Carnethon M, Gallo LC, et al. Prevalence of diabetes among hispanics/latinos from diverse backgrounds: the hispanic community health study/study of latinos (HCHS/SOL). Diabetes Care. 2014;37(8):2233–9.CrossRefGoogle Scholar
  30. 30.
    McCurley JL, et al. Psychosocial factors in the relationship between socioeconomic status and Cardiometabolic risk: the HCHS/SOL sociocultural ancillary study. Ann Behav Med. 2017;51(4):477–88.CrossRefGoogle Scholar
  31. 31.
    Salsberry PJ, Corwin E, Reagan PB. A complex web of risks for metabolic syndrome: race/ethnicity, economics, and gender. Am J Prev Med. 2007;33(2):114–20.CrossRefGoogle Scholar
  32. 32.
    Elovainio M, et al. Socioeconomic differences in cardiometabolic factors: social causation or health-related selection? Evidence from the Whitehall II Cohort Study, 1991–2004. Am J Epidemiol. 2011:kwr149.Google Scholar
  33. 33.
    Galanti G-A. The Hispanic family and male-female relationships: an overview. J Transcult Nurs. 2003;14(3):180–5.CrossRefGoogle Scholar
  34. 34.
    Thurston RC, Kubzansky LD, Kawachi I, Berkman LF. Is the association between socioeconomic position and coronary heart disease stronger in women than in men? Am J Epidemiol. 2005;162(1):57–65.CrossRefGoogle Scholar
  35. 35.
    Rosero-Bixby L, Dow WH. Surprising SES gradients in mortality, health, and biomarkers in a Latin American population of adults. J Gerontol Ser B Psychol Sci Soc Sci. 2009;64(1):105–17.CrossRefGoogle Scholar
  36. 36.
    Kutner M, et al. The Health Literacy of America's Adults: Results from the 2003 National Assessment of Adult Literacy. NCES 2006–483. National Center for Education Statistics, 2006.Google Scholar
  37. 37.
    Schumacher JR, Hall AG, Davis TC, Arnold CL, Bennett RD, Wolf MS, et al. Potentially preventable use of emergency services: the role of low health literacy. Med Care. 2013;51(8):654–8.CrossRefGoogle Scholar
  38. 38.
    DeVoe JE, et al. Receipt of preventive care among adults: insurance status and usual source of care. Am J Public Health. 2003;93(5):786–91.CrossRefGoogle Scholar
  39. 39.
    DeVoe JE, et al. Is health insurance enough? A usual source of care may be more important to ensure a child receives preventive health counseling. Matern Child Health J. 2012;16(2):306–15.CrossRefGoogle Scholar
  40. 40.
    US Department of Health Human Services. HHS action plan to reduce racial and ethnic health disparities: A nation free of disparities in health and health care. 2011; Available from: http://minorityhealth.hhs.gov/npa/files/plans/hhs/hhs_plan_complete.pdf.
  41. 41.
    McClurkin MA, et al. Health insurance status as a barrier to ideal cardiovascular health for US adults: data from the National Health and nutrition examination survey (NHANES). PLoS One. 2015;10(11):e0141534.CrossRefGoogle Scholar
  42. 42.
    Stringhini, S., et al., Contribution of modifiable risk factors to social inequalities in type 2 diabetes: prospective Whitehall II cohort study. 2012.Google Scholar
  43. 43.
    Pampel FC, Krueger PM, Denney JT. Socioeconomic disparities in health behaviors. Annu Rev Sociol. 2010;36:349–70.CrossRefGoogle Scholar

Copyright information

© International Society of Behavioral Medicine 2020

Authors and Affiliations

  • Tasneem Khambaty
    • 1
    Email author
  • Neil Schneiderman
    • 2
  • Maria M. Llabre
    • 2
  • Tali Elfassy
    • 2
  • Ashley E. Moncrieft
    • 2
  • Martha Daviglus
    • 3
  • Gregory A. Talavera
    • 4
  • Carmen R. Isasi
    • 5
  • Linda C. Gallo
    • 6
  • Samantha A. Reina
    • 2
  • Denise Vidot
    • 2
  • Gerardo Heiss
    • 7
  1. 1.Department of PsychologyUniversity of Maryland Baltimore CountyBaltimoreUSA
  2. 2.Department of Psychology and Behavioral Medicine Research CenterUniversity of MiamiCoral GablesUSA
  3. 3.Department of MedicineUniversity of IllinoisChicagoUSA
  4. 4.Graduate School of Public HealthSan Diego State UniversitySan DiegoUSA
  5. 5.Department of Epidemiology & Population HealthAlbert Einstein College of MedicineBronxUSA
  6. 6.Department of PsychologySan Diego State UniversitySan DiegoUSA
  7. 7.Department of EpidemiologyUniversity of North Carolina at Chapel HillChapel HillUSA

Personalised recommendations