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Why socially deprived populations have a faster resting heart rate: Impact of behaviour, life course anthropometry, and biology – the RECORD Cohort Study

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  • Chaix, Basile
  • Jouven, Xavier
  • Thomas, Frédérique
  • Leal, Cinira
  • Billaudeau, Nathalie
  • Bean, Kathy
  • Kestens, Yan
  • Jëgo, Bertrand
  • Pannier, Bruno
  • Danchin, Nicolas

Abstract

Although studies have shown that resting heart rate (RHR) is predictive of cardiovascular morbidity/mortality, few studies focused on the epidemiology and social aetiology of RHR. Using the RECORD Cohort Study (7158 participants, 2007–2008, Paris region, France), we investigated individual/neighbourhood socioeconomic variables associated with resting heart rate, and assessed which of a number of psychological factors (depression and stress), behaviour (sport-related energy expenditure, medication use, and alcohol, coffee, and tobacco consumption), life course anthropometric factors (body mass index, waist circumference, and leg length as a marker of childhood environmental exposures), and biologic factors (alkaline phosphatase and gamma-glutamyltransferase) contributed to the socioeconomic disadvantage–RHR relationship. Combining individual/neighbourhood socioeconomic factors in a socioeconomic score, RHR increased with socioeconomic disadvantage: +0.9 [95% credible interval (CrI): +0.2, +1.6], +1.8 (95% CrI: +1.0, +2.5), and +3.6 (95% CrI: +2.9, +4.4) bpm for the 3 categories reflecting increasing disadvantage, compared with the lowest disadvantage category. Twenty-one percent of the socioeconomic disadvantage–RHR relationship was explained by sport practise variables, 9% by waist circumference, 7% by gamma-glutamyltransferase, 5% by alkaline phosphatase, and 3% by leg length. Future research should further clarify the mechanisms through which socioeconomic disadvantage influences resting heart rate, as a pathway to social disparities in cardiovascular morbidity/mortality.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:socmed:v:73:y:2011:i:10:p:1543-1550
    DOI: 10.1016/j.socscimed.2011.09.009
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    References listed on IDEAS

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    1. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    2. 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.
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    Cited by:

    1. Isaac Debache & Audrey Bergouignan & Basile Chaix & Emiel M Sneekes & Frédérique Thomas & Cédric Sueur, 2019. "Associations of Sensor-Derived Physical Behavior with Metabolic Health: A Compositional Analysis in the Record Multisensor Study," IJERPH, MDPI, vol. 16(5), pages 1-15, March.
    2. Noëlla Karusisi & Frédérique Thomas & Julie Méline & Ruben Brondeel & Basile Chaix, 2014. "Environmental Conditions around Itineraries to Destinations as Correlates of Walking for Transportation among Adults: The RECORD Cohort Study," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-8, May.
    3. Teresa N. Brockie & Morgan Heinzelmann & Jessica Gill, 2013. "A Framework to Examine the Role of Epigenetics in Health Disparities among Native Americans," Nursing Research and Practice, Hindawi, vol. 2013, pages 1-9, December.
    4. Catherine Paquet & Basile Chaix & Natasha J. Howard & Neil T. Coffee & Robert J. Adams & Anne W. Taylor & Frédérique Thomas & Mark Daniel, 2016. "Geographic Clustering of Cardiometabolic Risk Factors in Metropolitan Centres in France and Australia," IJERPH, MDPI, vol. 13(5), pages 1-17, May.

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