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

International Journal of Behavioral Medicine - Tập 27 - Trang 188-199 - 2020
Tasneem Khambaty1, Neil Schneiderman2, Maria M. Llabre2, Tali Elfassy2, Ashley E. Moncrieft2, Martha Daviglus3, Gregory A. Talavera4, Carmen R. Isasi5, Linda C. Gallo6, Samantha A. Reina2, Denise Vidot2, Gerardo Heiss7
1Department of Psychology, University of Maryland Baltimore County, Baltimore, USA
2Department of Psychology and Behavioral Medicine Research Center, University of Miami, Coral Gables, USA
3Department of Medicine, University of Illinois, Chicago, USA
4Graduate School of Public Health, San Diego State University, San Diego, USA
5Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, USA
6Department of Psychology, San Diego State University, San Diego, USA
7Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, USA

Tóm tắt

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. 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. 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. 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.

Tài liệu tham khảo

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. Ford ES, Li C, Sattar N. Metabolic syndrome and incident diabetes current state of the evidence. Diabetes Care. 2008;31(9):1898–904. Ballantyne CM, et al. Metabolic syndrome risk for cardiovascular disease and diabetes in the ARIC study. Int J Obes. 2008;32(Suppl 2):S21. 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. 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. Ennis S, Rios-Vargas M, Albert N. The Hispanic Population 2010: 2010 Census Briefs. Washington, DC: US Census Bureau; 2011. 2014. 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. Bradley RH, Corwyn RF. Socioeconomic status and child development. Annu Rev Psychol. 2002;53(1):371–99. Adler NE, Stewart J. Health disparities across the lifespan: meaning, methods, and mechanisms. Ann N Y Acad Sci. 2010;1186(1):5–23. 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. 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. 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. 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. Gupta, R., et al., Association of educational, occupational and socioeconomic status with cardiovascular risk factors in Asian Indians: a cross-sectional study. 2012. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. Galanti G-A. The Hispanic family and male-female relationships: an overview. J Transcult Nurs. 2003;14(3):180–5. 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. 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. 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. 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. 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. 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. 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. 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. Stringhini, S., et al., Contribution of modifiable risk factors to social inequalities in type 2 diabetes: prospective Whitehall II cohort study. 2012. Pampel FC, Krueger PM, Denney JT. Socioeconomic disparities in health behaviors. Annu Rev Sociol. 2010;36:349–70.