IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v11y2014i1p830-848d31977.html
   My bibliography  Save this article

Area-Level Socioeconomic Characteristics, Prevalence and Trajectories of Cardiometabolic Risk

Author

Listed:
  • Anh D. Ngo

    (Clinical and Population Perinatal Research, Kolling Institute of Medical Research, University of Sydney at Royal North Shore Hospital, St Leonards, New South Wales, NSW 2065, Australia
    The paper was written while the first author was based at the Social Epidemiology and Evaluation Research Group, School of Population Health and Sansom Institute for Health Research, University of South Australia, Adelaide, SA 5001.)

  • Catherine Paquet

    (Social Epidemiology and Evaluation Research Group, School of Population Health and Sansom Institute for Health Research, University of South Australia, Adelaide, SA 5001, Australia
    Research Centre of the Douglas Mental Health University Institute, Verdun, QC H4H 1R2, Canada)

  • Natasha J. Howard

    (Social Epidemiology and Evaluation Research Group, School of Population Health and Sansom Institute for Health Research, University of South Australia, Adelaide, SA 5001, Australia)

  • Neil T. Coffee

    (Social Epidemiology and Evaluation Research Group, School of Population Health and Sansom Institute for Health Research, University of South Australia, Adelaide, SA 5001, Australia)

  • Anne W. Taylor

    (Population Research and Outcome Studies, Discipline of Medicine, The University of Adelaide, Adelaide, SA 5005, Australia)

  • Robert J. Adams

    (The Health Observatory, Discipline of Medicine, The University of Adelaide, Adelaide, SA 5005, Australia)

  • Mark Daniel

    (Social Epidemiology and Evaluation Research Group, School of Population Health and Sansom Institute for Health Research, University of South Australia, Adelaide, SA 5001, Australia
    Department of Medicine, The University of Melbourne, St Vincent's Hospital, Melbourne, VIC 3065, Australia)

Abstract

This study examines the relationships between area-level socioeconomic position (SEP) and the prevalence and trajectories of metabolic syndrome (MetS) and the count of its constituents ( i.e. , disturbed glucose and insulin metabolism, abdominal obesity, dyslipidemia, and hypertension). A cohort of 4,056 men and women aged 18+ living in Adelaide, Australia was established in 2000–2003. MetS was ascertained at baseline, four and eight years via clinical examinations. Baseline area-level median household income, percentage of residents with a high school education, and unemployment rate were derived from the 2001 population Census. Three-level random-intercepts logistic and Poisson regression models were performed to estimate the standardized odds ratio (SOR), prevalence risk ratio (SRR), ratio of SORs/SRRs, and (95% confidence interval (CI)). Interaction between area- and individual-level SEP variables was also tested. The odds of having MetS and the count of its constituents increased over time. This increase did not vary according to baseline area-level SEP (ratios of SORs/SRRs ≈ 1; p ≥ 0.42). However, at baseline, after adjustment for individual SEP and health behaviours, median household income (inversely) and unemployment rate (positively) were significantly associated with MetS prevalence (SOR (95%CI) = 0.76 (0.63–0.90), and 1.48 (1.26–1.74), respectively), and the count of its constituents (SRR (95%CI) = 0.96 (0.93–0.99), and 1.06 (1.04–1.09), respectively). The inverse association with area-level education was statistically significant only in participants with less than post high school education (SOR (95%CI) = 0.58 (0.45–0.73), and SRR (95%CI) = 0.91 (0.88–0.94)). Area-level SEP does not predict an elevated trajectory to developing MetS or an elevated count of its constituents. However, at baseline, area-level SEP was inversely associated with prevalence of MetS and the count of its constituents, with the association of area-level education being modified by individual-level education. Population-level interventions for communities defined by area-level socioeconomic disadvantage are needed to reduce cardiometabolic risks.

Suggested Citation

  • Anh D. Ngo & Catherine Paquet & Natasha J. Howard & Neil T. Coffee & Anne W. Taylor & Robert J. Adams & Mark Daniel, 2014. "Area-Level Socioeconomic Characteristics, Prevalence and Trajectories of Cardiometabolic Risk," IJERPH, MDPI, vol. 11(1), pages 1-19, January.
  • Handle: RePEc:gam:jijerp:v:11:y:2014:i:1:p:830-848:d:31977
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/11/1/830/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/11/1/830/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xinghua Yang & Qiushan Tao & Feng Sun & Siyan Zhan, 2012. "The impact of socioeconomic status on the incidence of metabolic syndrome in a Taiwanese health screening population," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 57(3), pages 551-559, June.
    2. Langenberg, C. & Kuh, D. & Wadsworth, M.E.J. & Brunner, E. & Hardy, R., 2006. "Social circumstances and education: Life course origins of social inequalities in metabolic risk in a prospective national birth cohort," American Journal of Public Health, American Public Health Association, vol. 96(12), pages 2216-2221.
    3. Cozier, Y.C. & Palmer, J.R. & Horton, N.J. & Fredman, L. & Wise, L.A. & Rosenberg, L., 2007. "Relation between neighborhood median housing value and hypertension risk among black women in the United States," American Journal of Public Health, American Public Health Association, vol. 97(4), pages 718-724.
    4. Lucove, J.C. & Kaufman, J.S. & James, S.A., 2007. "Association between adult and childhood socioeconomic status and prevalence of the metabolic syndrome in African Americans: The pitt county study," American Journal of Public Health, American Public Health Association, vol. 97(2), pages 234-236.
    5. McGrath, Jennifer J. & Matthews, Karen A. & Brady, Sonya S., 2006. "Individual versus neighborhood socioeconomic status and race as predictors of adolescent ambulatory blood pressure and heart rate," Social Science & Medicine, Elsevier, vol. 63(6), pages 1442-1453, September.
    6. Diez-Roux, Ana V. & Link, Bruce G. & Northridge, Mary E., 2000. "A multilevel analysis of income inequality and cardiovascular disease risk factors," Social Science & Medicine, Elsevier, vol. 50(5), pages 673-687, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Suzanne J. Carroll & Michael J. Dale & Anne W. Taylor & Mark Daniel, 2020. "Contributions of Multiple Built Environment Features to 10-Year Change in Body Mass Index and Waist Circumference in a South Australian Middle-Aged Cohort," IJERPH, MDPI, vol. 17(3), pages 1-18, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Harrington, Daniel W. & Elliott, Susan J., 2009. "Weighing the importance of neighbourhood: A multilevel exploration of the determinants of overweight and obesity," Social Science & Medicine, Elsevier, vol. 68(4), pages 593-600, February.
    2. Jonathan K Burns & Andrew Tomita & Amy S Kapadia, 2014. "Income inequality and schizophrenia: Increased schizophrenia incidence in countries with high levels of income inequality," International Journal of Social Psychiatry, , vol. 60(2), pages 185-196, March.
    3. Chaix, Basile & Jouven, Xavier & Thomas, Frédérique & Leal, Cinira & Billaudeau, Nathalie & Bean, Kathy & Kestens, Yan & Jëgo, Bertrand & Pannier, Bruno & Danchin, Nicolas, 2011. "Why socially deprived populations have a faster resting heart rate: Impact of behaviour, life course anthropometry, and biology – the RECORD Cohort Study," Social Science & Medicine, Elsevier, vol. 73(10), pages 1543-1550.
    4. Thurston, Rebecca C. & Matthews, Karen A., 2009. "Racial and socioeconomic disparities in arterial stiffness and intima media thickness among adolescents," Social Science & Medicine, Elsevier, vol. 68(5), pages 807-813, March.
    5. C Mary Schooling & Tai Hing Lam & G Neil Thomas & Benjamin J Cowling & Michelle Heys & Edward D Janus & Gabriel M Leung & for the Hong Kong Cardiovascular Risk Factor Prevalence Study Steering Committ, 2007. "Growth Environment and Sex Differences in Lipids, Body Shape and Diabetes Risk," PLOS ONE, Public Library of Science, vol. 2(10), pages 1-9, October.
    6. Godoy, Ricardo A. & Reyes-García, Victoria & McDade, Thomas & Huanca, Tomás & Leonard, William R. & Tanner, Susan & Vadez, Vincent, 2006. "Does village inequality in modern income harm the psyche? Anger, fear, sadness, and alcohol consumption in a pre-industrial society," Social Science & Medicine, Elsevier, vol. 63(2), pages 359-372, July.
    7. Fatiha Bennia & Nicolas Gravel, 2016. "Is the Distribution of Cardiovascular Risks Really Improving ? A Robust Analysis for France," Working Papers halshs-01321838, HAL.
    8. Arline Geronimus & John Bound & Annie Ro, 2014. "Residential Mobility Across Local Areas in the United States and the Geographic Distribution of the Healthy Population," Demography, Springer;Population Association of America (PAA), vol. 51(3), pages 777-809, June.
    9. Chen-Mao Liao & Chih-Ming Lin, 2018. "Life Course Effects of Socioeconomic and Lifestyle Factors on Metabolic Syndrome and 10-Year Risk of Cardiovascular Disease: A Longitudinal Study in Taiwan Adults," IJERPH, MDPI, vol. 15(10), pages 1-15, October.
    10. Chen, Chun-Chih & Chen, Chin-Shyan & Liu, Tsai-Ching & Lin, Ying-Tzu, 2012. "Stock or stroke? Stock market movement and stroke incidence in Taiwan," Social Science & Medicine, Elsevier, vol. 75(11), pages 1974-1980.
    11. Manuela Abbate & Jordi Pericas & Aina M. Yañez & Angel A. López-González & Joan De Pedro-Gómez & Antoni Aguilo & José M. Morales-Asencio & Miquel Bennasar-Veny, 2021. "Socioeconomic Inequalities in Metabolic Syndrome by Age and Gender in a Spanish Working Population," IJERPH, MDPI, vol. 18(19), pages 1-16, September.
    12. Masako Horino & Sze Yan Liu & Eun-Young Lee & Ichiro Kawachi & Roman Pabayo, 2020. "State-level income inequality and the odds for meeting fruit and vegetable recommendations among US adults," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-15, September.
    13. Böckerman, Petri & Johansson, Edvard & Helakorpi, Satu & Uutela, Antti, 2007. "Economic Inequality and Health: Looking Beyond Aggregate Indicators," Discussion Papers 1104, The Research Institute of the Finnish Economy.
    14. Clément, Matthieu & Levasseur, Pierre & Seetahul, Suneha & Piaser, Lucie, 2021. "Does inequality have a silver lining? Municipal income inequality and obesity in Mexico," Social Science & Medicine, Elsevier, vol. 272(C).
    15. Barnett, Ross & Pearce, Jamie & Moon, Graham, 2009. "Community inequality and smoking cessation in New Zealand, 1981-2006," Social Science & Medicine, Elsevier, vol. 68(5), pages 876-884, March.
    16. Weatherspoon, Dave D. & Oehmke, James F. & Coleman, Marcus A. & Weatherspoon, Lorraine J., 2014. "Understanding Consumer Preferences for Nutritious Foods: Retailing Strategies in a Food Desert," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 17(A), pages 1-22, March.
    17. Xuejie Ding & Francesco C. Billari & Stuart Gietel-Basten, 2017. "Health of midlife and older adults in China: the role of regional economic development, inequality, and institutional setting," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 62(8), pages 857-867, November.
    18. Hastert, Theresa A. & Ruterbusch, Julie J. & Beresford, Shirley A.A. & Sheppard, Lianne & White, Emily, 2016. "Contribution of health behaviors to the association between area-level socioeconomic status and cancer mortality," Social Science & Medicine, Elsevier, vol. 148(C), pages 52-58.
    19. Zheng, Hui, 2009. "Rising U.S. income inequality, gender and individual self-rated health, 1972-2004," Social Science & Medicine, Elsevier, vol. 69(9), pages 1333-1342, November.
    20. Gustafsson, Per E. & Hammarström, Anne, 2012. "Socioeconomic disadvantage in adolescent women and metabolic syndrome in mid-adulthood: An examination of pathways of embodiment in the Northern Swedish Cohort," Social Science & Medicine, Elsevier, vol. 74(10), pages 1630-1638.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:11:y:2014:i:1:p:830-848:d:31977. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.