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Population-level trends in the distribution of body mass index in Canada, 2000–2014

  • Quantitative Research
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Abstract

Objective

Research studying population-level body mass index (BMI) trends document increases in mean or prevalence of overweight/obese but less consideration has been given to describing the changing distribution of BMI. The objective of this research was to perform a detailed analysis of changes in the BMI distribution in Canada.

Methods

Using data from the CCHS (2000–2014), we analyzed distributional parameters of BMI for 492,886 adults aged 25–64 years. We further stratified these analyses for women and men, education level, and region of residence.

Results

Mean BMI has increased for most subgroups of the Canadian population. Mean BMI values were higher for men, while standard deviation (SD) of the BMI distribution was systematically higher in women. Increases in mean BMI were accompanied with increases in SD of BMI across cycles. Across survey cycles, the 95th percentile increased more than 10 times more rapidly compared to the 5th percentile, showing a very unequal change between extreme values in the BMI distribution over time. There was a relationship between SD with BMI, but these relations were generally not different between educational categories and regions. This suggests that the growing inter-individual inequalities (i.e., dispersion) in BMI were not solely attributable to socioeconomic and demographic factors.

Conclusions

This study supports the hypothesis that the simultaneous increases in mean BMI and SD of the BMI distribution are occurring, and suggests the need to move beyond the mean-centric paradigm when studying a complex public health phenomenon such as population change in BMI.

Résumé

Objectif

Les recherches populationnelles portant sur l’évolution de l’indice de masse corporelle (IMC) rapportent une augmentation de la moyenne et de la prévalence de l’embonpoint/obésité, mais accordent moins d’intérêt aux changements distributionnels. L’objectif de cette recherche était de réaliser une analyse détaillée des changements distributionnels de l’IMC au Canada.

Méthodologie

À partir des données de l’ESCC (2000–2014), nous avons analysé les paramètres distributionnels de l’IMC de 492,886 adultes âgés de 25 à 64 ans. Les analyses ont été stratifiées entre les femmes et les hommes, le niveau d’instruction et la région de résidence.

Résultats

L’IMC moyen a augmenté pour la majorité des sous-groupes de la population canadienne. Les valeurs de l’IMC moyen étaient plus élevées pour les hommes, alors que celles de l’écart-type (É-T) de la distribution de l’IMC étaient systématiquement plus élevées chez les femmes. L’augmentation de l’IMC moyen était accompagnée d’une augmentation de l’É-T de l’IMC à travers les cycles. À travers les cycles de l’enquête, le 95ème percentile augmentait plus de dix fois plus rapidement que le 5ème percentile, révélant un changement très inégal entre les valeurs extrêmes de la distribution de l’IMC dans le temps. Il y avait une relation entre l’É-T et l’IMC, mais de façon générale, ces relations n’étaient pas différentes entre les catégories du niveau d’instruction et de la région de résidence. Ceci suggère que la croissance des inégalités interindividuelles de l’IMC n’est pas uniquement attribuable à des facteurs socioéconomiques et démographiques.

Conclusions

Cette étude supporte l’hypothèse que la croissance de l’IMC moyen et de l’É-T de la distribution de l’IMC se produisent de façon simultanée et suggère le besoin d’aller au-delà du paradigme de recherche centré sur la moyenne pour l’étude de phénomènes de santé publique complexes comme celui de l’évolution de l’IMC à l’échelle des populations.

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References

  • Baum 2nd, C. L., & Ruhm, C. J. (2009). Age, socioeconomic status and obesity growth. Journal of Health Economics, 28(3), 635–648.

    Article  PubMed  Google Scholar 

  • Dutton, D. J., & McLaren, L. (2016). How important are determinants of obesity measured at the individual level for explaining geographic variation in body mass index distributions? Observational evidence from Canada using Quantile Regression and Blinder-Oaxaca Decomposition. Journal of Epidemiology and Community Health, 70(4), 367–373.

    Article  PubMed  Google Scholar 

  • Finucane, M. M., Stevens, G. A., Cowan, M. J., Danaei, G., Lin, J. K., Paciorek, C. J., et al. (2011). National, regional, and global trends in body-mass index since 1980: systematic analysis of health examination surveys and epidemiological studies with 960 country-years and 91 million participants. The Lancet, 377(9765), 557–567.

    Article  Google Scholar 

  • Flegal, K. M., Carroll, M. D., Kit, B. K., & Ogden, C. L. (2012). Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999–2010. JAMA: The Journal of the American Medical Association, 307(5), 491–497.

    Article  PubMed  Google Scholar 

  • Frohlich, K. L., & Potvin, L. (2008). Transcending the known in public health practice. American Journal of Public Health, 98(2).

    Article  PubMed  PubMed Central  Google Scholar 

  • Gakidou, E. E., Murray, C. J., & Frenk, J. (2000). Defining and measuring health inequality: an approach based on the distribution of health expectancy. Bulletin of the World Health Organization, 78(1), 42–54.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Glymour, M. M., & Spiegelman, D. (2017). Evaluating public health interventions: 5. Causal inference in public health research—do sex, race, and biological factors cause health outcomes? American Journal of Public Health, 107(1), 81–85.

    Article  PubMed  PubMed Central  Google Scholar 

  • Gotay, C. C., Katzmarzyk, P. T., Janssen, I., Dawson, M. Y., Aminoltejari, K., & Bartley, N. L. (2013). Updating the Canadian obesity maps: an epidemic in progress. Canadian Journal of Public Health, 104(1), e64–e68.

    PubMed Central  Google Scholar 

  • Green, M., Subramanian, S., & Razak, F. (2016). Population-level trends in the distribution of body mass index in England, 1992–2013. Journal of Epidemiology and Community Health, 70(8), 832–835. https://doi.org/10.1136/jech-2015-206468.

    Article  CAS  PubMed  Google Scholar 

  • Hawkes, C. (2006). Uneven dietary development: linking the policies and processes of globalization with the nutrition transition, obesity and diet-related chronic diseases. Globalization and Health, 2(1), 4.

    Article  PubMed  PubMed Central  Google Scholar 

  • Howe, L. D., Tilling, K., Galobardes, B., Smith, G. D., Ness, A. R., & Lawlor, D. A. (2011). Socioeconomic disparities in trajectories of adiposity across childhood. International Journal of Pediatric Obesity, 6(2–2), e144–e153.

    Article  PubMed  Google Scholar 

  • Jenkins, A. and Campbell L. V. (2014). Future management of human obesity: understanding the meaning of genetic susceptibility.

  • Jenkins, A. B., & Campbell, L. V. (2015). Variation in genetic susceptibility drives increasing dispersion of population BMI. The American Journal of Clinical Nutrition, 101(6), 1308–1308.

    Article  CAS  PubMed  Google Scholar 

  • Kelly, B. B., & Fuster, V. (2010). Promoting cardiovascular health in the developing world: A Critical Challenge to Achieve Global Health. Washington, DC: National Academies Press.

    Google Scholar 

  • Kivimäki, M., Stenholm, S., & Kawachi, I. (2015). The widening BMI distribution in the United States. The American Journal of Clinical Nutrition, 101(6), 1307–1308.

    Article  CAS  PubMed  Google Scholar 

  • Krishna, A., Razak, F., Lebel, A., Smith, G. D., & Subramanian, S. (2015). Trends in group inequalities and interindividual inequalities in BMI in the United States, 1993–2012. The American Journal of Clinical Nutrition, 101(3), 598–605.

    Article  CAS  PubMed  Google Scholar 

  • Krueger, P. M., Coleman-Minahan, K., & Rooks, R. N. (2014). Race/ethnicity, nativity and trends in BMI among US adults. Obesity, 22(7), 1739–1746.

    Article  PubMed  Google Scholar 

  • Lebel, A., Kestens, Y., Clary, C., Bisset, S., & Subramanian, S. (2014). Geographic variability in the association between socioeconomic status and BMI in the USA and Canada. PLoS One, 9(6), e99158.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Ludwig, J., Sanbonmatsu, L., Gennetian, L., Adam, E., Duncan, G. J., Katz, L. F., et al. (2011). Neighborhoods, obesity, and diabetes—a randomized social experiment. New England Journal of Medicine, 365(16), 1509–1519.

    Article  CAS  PubMed  Google Scholar 

  • Malik, V. S., Willett, W. C., & Hu, F. B. (2013). Global obesity: trends, risk factors and policy implications. Nat Rev Endocrinol, 9(1), 13–27.

    Article  PubMed  Google Scholar 

  • McLaren, L. (2007). Socioeconomic status and obesity. Epidemiologic Reviews, 29(1), 29–48.

    Article  PubMed  Google Scholar 

  • Merlo, J. (2011). Contextual influences on the individual life course: building a research framework for social epidemiology. Psychosocial Intervention, 20(1), 109–118.

    Article  Google Scholar 

  • Murray, C. J., Gakidou, E. E., & Frenk, J. (1999). Health inequalities and social group differences: what should we measure? Bulletin of the World Health Organization, 77(7), 537.

    CAS  PubMed  PubMed Central  Google Scholar 

  • NCD-RisC. (2017) Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128·9 million children, adolescents, and adults. The Lancet.

  • Neuman, M., Kawachi, I., Gortmaker, S., & Subramanian, S. V. (2013). Urban-rural differences in BMI in low- and middle-income countries: the role of socioeconomic status. The American Journal of Clinical Nutrition, 97(2), 428–436.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Ogden, C. L., Yanovski, S. Z., Carroll, M. D., & Flegal, K. M. (2007). The epidemiology of obesity. Gastroenterology, 132(6), 2087–2102.

    Article  PubMed  Google Scholar 

  • Popkin, B. M., Adair, L.S., and Ng, S.W. (2012). Global nutrition transition and the pandemic of obesity in developing countries. Nutr Rev,70, 3–21.

    Article  PubMed  Google Scholar 

  • Razak, F., Smith, G. D., Krishna, A., Lebel, A., & Subramanian, S. (2015). Reply to M Kivimäki et al. and AB Jenkins and LV Campbell. The American Journal of Clinical Nutrition, 101(6), 1308–1309.

    Article  CAS  PubMed  Google Scholar 

  • Razak, F., Smith, G. D., & Subramanian, S. (2016). The idea of uniform change: is it time to revisit a central tenet of Rose’s “Strategy of Preventive Medicine”? The American Journal of Clinical Nutrition, 104(6), 1497–1507.

    Article  CAS  PubMed  Google Scholar 

  • Shields, M., Gorber, S. C., Janssen, I., & Tremblay, M. S. (2011). Bias in self-reported estimates of obesity in Canadian health surveys: an update on correction equations for adults. Health Reports, 22(3), 35–45.

    PubMed  Google Scholar 

  • Silventoinen, K., Tatsuse, T., Martikainen, P., Rahkonen, O., Lahelma, E., Sekine, M., et al. (2013). Occupational class differences in body mass index and weight gain in Japan and Finland. Journal of Epidemiology, 23(6), 443–450.

    Article  PubMed  PubMed Central  Google Scholar 

  • Sorkin, J. D., Muller, D. C., & Andres, R. (1999). Longitudinal change in height of men and women: implications for interpretation of the body mass index: the Baltimore Longitudinal Study of Aging. American Journal of Epidemiology, 150(9), 969–977.

    Article  CAS  PubMed  Google Scholar 

  • Statistics Canada (2011). Canadian Community Health Survey (CCHS) annual component: user guide 2010 and 2009–2010 microdata files (p. 100). Ottawa: Statistics Canada.

    Google Scholar 

  • Statistics Canada. Canadian Community Health Survey. 2012 2016-12-08; Available from: http://www.statcan.gc.ca/cgi-bin/imdb/p2SV.pl?Function=getSurvey&SDDS=3226&lang=en&db=imdb&adm=8&dis=2.

  • Tchernof, A., & Després, J.-P. (2013). Pathophysiology of human visceral obesity: an update. Physiological Reviews, 93(1), 359–404.

    Article  CAS  PubMed  Google Scholar 

  • Twells, L. K., Gregory, D. M., Reddigan, J., & Midodzi, W. K. (2014). Current and predicted prevalence of obesity in Canada: a trend analysis. Canadian Medical Association Open Access Journal, 2(1), E18–E26.

    Google Scholar 

  • Vaezghasemi, M., Razak, F., Ng, N., & Subramanian, S. (2016). Inter-individual inequality in BMI: an analysis of Indonesian Family Life Surveys (1993–2007). SSM-Population Health, 2, 876–888.

    Article  PubMed  PubMed Central  Google Scholar 

  • Wilk, M. B., & Gnanadesikan, R. (1968). Probability plotting methods for the analysis of data. Biometrika, 55(1), 1–17.

    CAS  PubMed  Google Scholar 

  • World Health Organization (2014) Obesity and inequities: guidance for addressing inequities in overweight and obesity. Regional office for Europe. Copenhagen: World Health Organization. ISBN, 978(92), pp. 890.

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Funding

This research was partly funded by the Fonds de recherche du Québec-Santé (FRQS), the Centre de recherche en aménagement et développement (CRAD) of Laval University, and the Evaluation Platform on Obesity Prevention of the Quebec Heart and Lung Institute.

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Correspondence to Alexandre Lebel.

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The authors declare that they have no conflict of interest.

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Lebel, A., Subramanian, S.V., Hamel, D. et al. Population-level trends in the distribution of body mass index in Canada, 2000–2014. Can J Public Health 109, 539–548 (2018). https://doi.org/10.17269/s41997-018-0060-7

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  • DOI: https://doi.org/10.17269/s41997-018-0060-7

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