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  • Original Article
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Clinical Studies and Practice

Interactive effects of obesity and physical fitness on risk of ischemic heart disease

Abstract

Background/Objectives:

Obesity and low physical fitness are known risk factors for ischemic heart disease (IHD), but their interactive effects are unclear. Elucidation of interactions between these common, modifiable risk factors may help inform more effective preventive strategies. We examined interactive effects of obesity, aerobic fitness and muscular strength in late adolescence on risk of IHD in adulthood in a large national cohort.

Subjects/Methods:

We conducted a national cohort study of all 1 547 407 military conscripts in Sweden during 1969–1997 (97–98% of all 18-year-old males each year). Aerobic fitness, muscular strength and body mass index (BMI) measurements were examined in relation to IHD identified from outpatient and inpatient diagnoses through 2012 (maximum age 62 years).

Results:

There were 38 142 men diagnosed with IHD in 39.7 million person years of follow-up. High BMI or low aerobic fitness (but not muscular strength) was associated with higher risk of IHD, adjusting for family history and socioeconomic factors. The combination of high BMI (overweight/obese vs normal) and low aerobic fitness (lowest vs highest tertile) was associated with highest IHD risk (incidence rate ratio, 3.11; 95% confidence interval (CI), 2.91–3.31; P<0.001). These exposures had no additive and a negative multiplicative interaction (that is, their combined effect was less than the product of their separate effects). Low aerobic fitness was a strong risk factor even among those with normal BMI.

Conclusions:

In this large cohort study, low aerobic fitness or high BMI at age 18 was associated with higher risk of IHD in adulthood, with a negative multiplicative interaction. Low aerobic fitness appeared to account for a similar number of IHD cases among those with normal vs high BMI (that is, no additive interaction). These findings suggest that interventions to prevent IHD should begin early in life and include not only weight control but aerobic fitness, even among persons of normal weight.

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References

  1. Lloyd-Jones D, Adams RJ, Brown TM, Carnethon M, Dai S, De Simone G et al. Executive summary: heart disease and stroke statistics—2010 update: a report from the American Heart Association. Circulation 2010; 121: 948–954.

    Article  Google Scholar 

  2. Go AS, Mozaffarian D, Roger VL, Benjamin EJ, Berry JD, Blaha MJ et al. Executive summary: heart disease and stroke statistics—2014 update: a report from the American Heart Association. Circulation 2014; 129: 399–410.

    Article  Google Scholar 

  3. Andersen LG, Angquist L, Eriksson JG, Forsen T, Gamborg M, Osmond C et al. Birth weight, childhood body mass index and risk of coronary heart disease in adults: combined historical cohort studies. PLoS One 2010; 5: e14126.

    Article  CAS  Google Scholar 

  4. Baker JL, Olsen LW, Sorensen TI . Childhood body-mass index and the risk of coronary heart disease in adulthood. N Engl J Med 2007; 357: 2329–2337.

    Article  CAS  Google Scholar 

  5. Owen CG, Whincup PH, Orfei L, Chou QA, Rudnicka AR, Wathern AK et al. Is body mass index before middle age related to coronary heart disease risk in later life? Evidence from observational studies. Int J Obes 2009; 33: 866–877.

    Article  CAS  Google Scholar 

  6. Falkstedt D, Hemmingsson T, Rasmussen F, Lundberg I . Body mass index in late adolescence and its association with coronary heart disease and stroke in middle age among Swedish men. Int J Obes 2007; 31: 777–783.

    Article  CAS  Google Scholar 

  7. Osler M, Lund R, Kriegbaum M, Andersen AM . The influence of birth weight and body mass in early adulthood on early coronary heart disease risk among Danish men born in 1953. Eur J Epidemiol 2009; 24: 57–61.

    Article  Google Scholar 

  8. Yang L, Kuper H, Weiderpass E . Anthropometric characteristics as predictors of coronary heart disease in women. J Intern Med 2008; 264: 39–49.

    Article  CAS  Google Scholar 

  9. Bergh C, Udumyan R, Fall K, Almroth H, Montgomery S . Stress resilience and physical fitness in adolescence and risk of coronary heart disease in middle age. Heart 2015; 101: 623–629.

    Article  Google Scholar 

  10. Hogstrom G, Nordstrom A, Nordstrom P . High aerobic fitness in late adolescence is associated with a reduced risk of myocardial infarction later in life: a nationwide cohort study in men. Eur Heart J 2014; 35: 3133–3140.

    Article  Google Scholar 

  11. Andersen K, Rasmussen F, Held C, Neovius M, Tynelius P, Sundstrom J . Exercise capacity and muscle strength and risk of vascular disease and arrhythmia in 1.1 million young Swedish men: cohort study. BMJ 2015; 351: h4543.

    Article  Google Scholar 

  12. Kodama S, Saito K, Tanaka S, Maki M, Yachi Y, Asumi M et al. Cardiorespiratory fitness as a quantitative predictor of all-cause mortality and cardiovascular events in healthy men and women: a meta-analysis. JAMA 2009; 301: 2024–2035.

    Article  CAS  Google Scholar 

  13. Li TY, Rana JS, Manson JE, Willett WC, Stampfer MJ, Colditz GA et al. Obesity as compared with physical activity in predicting risk of coronary heart disease in women. Circulation 2006; 113: 499–506.

    Article  Google Scholar 

  14. Weinstein AR, Sesso HD, Lee IM, Rexrode KM, Cook NR, Manson JE et al. The joint effects of physical activity and body mass index on coronary heart disease risk in women. Arch Intern Med 2008; 168: 884–890.

    Article  Google Scholar 

  15. Hu G, Tuomilehto J, Silventoinen K, Barengo NC, Peltonen M, Jousilahti P . The effects of physical activity and body mass index on cardiovascular, cancer and all-cause mortality among 47 212 middle-aged Finnish men and women. Int J Obes 2005; 29: 894–902.

    Article  CAS  Google Scholar 

  16. Crump C, Sundquist J, Winkleby MA, Sundquist K . Interactive effects of physical fitness and body mass index on the risk of hypertension. JAMA Intern Med 2016; 176: 210–216.

    Article  Google Scholar 

  17. Crump C, Sundquist J, Winkleby MA, Sieh W, Sundquist K . Physical fitness among Swedish military conscripts and long-term risk for type 2 diabetes mellitus: a cohort study. Ann Intern Med 2016; 164: 577–584.

    Article  Google Scholar 

  18. Crump C, Sundquist J, Winkleby MA, Sundquist K . Interactive effects of physical fitness and body mass index on risk of stroke: a national cohort study. Int J Stroke 2016; 11: 683–694.

    Article  Google Scholar 

  19. Nordesjo L, Schele R . Validity of an ergometer cycle test and measures of isometric muscle strength when predicting some aspects of military performance. Swed J Def Med 1974; 10: 11–23.

    Google Scholar 

  20. Patton JF, Vogel JA, Mello RP . Evaluation of a maximal predictive cycle ergometer test of aerobic power. Eur J Appl Physiol Occup Physiol 1982; 49: 131–140.

    Article  CAS  Google Scholar 

  21. Andersen LB . A maximal cycle exercise protocol to predict maximal oxygen uptake. Scand J Med Sci Sports 1995; 5: 143–146.

    Article  CAS  Google Scholar 

  22. Hook O, Tornvall G . Apparatus and method for determination of isometric muscle strength in man. Scand J Rehabil Med 1969; 1: 139–142.

    CAS  PubMed  Google Scholar 

  23. Ogden CL, Flegal KM . Changes in terminology for childhood overweight and obesity. Natl Health Stat Report 2010; 25: 1–5.

    Google Scholar 

  24. Ludvigsson JF, Andersson E, Ekbom A, Feychting M, Kim JL, Reuterwall C et al. External review and validation of the Swedish national inpatient register. BMC Public Health 2011; 11: 450.

    Article  Google Scholar 

  25. Diez Roux AV, Merkin SS, Arnett D, Chambless L, Massing M, Nieto FJ et al. Neighborhood of residence and incidence of coronary heart disease. N Engl J Med 2001; 345: 99–106.

    Article  CAS  Google Scholar 

  26. Winkleby M, Sundquist K, Cubbin C . Inequities in CHD incidence and case fatality by neighborhood deprivation. Am J Prev Med 2007; 32: 97–106.

    Article  Google Scholar 

  27. Stoddard PJ, Laraia BA, Warton EM, Moffet HH, Adler NE, Schillinger D et al. Neighborhood deprivation and change in BMI among adults with type 2 diabetes: the Diabetes Study of Northern California (DISTANCE). Diabetes Care 2013; 36: 1200–1208.

    Article  Google Scholar 

  28. Crump C, Sundquist K, Sundquist J, Winkleby MA . Neighborhood deprivation and psychiatric medication prescription: a Swedish national multilevel study. Ann Epidemiol 2011; 21: 231–237.

    Article  Google Scholar 

  29. Rubin DB . Multiple Imputation for Nonresponse in Surveys. Wiley: New York, 1987.

    Book  Google Scholar 

  30. Zou G . A modified poisson regression approach to prospective studies with binary data. Am J Epidemiol 2004; 159: 702–706.

    Article  Google Scholar 

  31. Li R, Chambless L . Test for additive interaction in proportional hazards models. Ann Epidemiol 2007; 17: 227–236.

    Article  Google Scholar 

  32. Orsini N, Bellocco R, Bottai M, Wolk A, Greenland S . A tool for deterministic and probabilistic sensitivity analysis of epidemiologic studies. Stata J 2008; 8: 29–48.

    Article  Google Scholar 

  33. Furberg H, Lichtenstein P, Pedersen NL, Bulik C, Sullivan PF . Cigarettes and oral snuff use in Sweden: prevalence and transitions. Addiction 2006; 101: 1509–1515.

    Article  Google Scholar 

  34. Njolstad I, Arnesen E, Lund-Larsen PG . Smoking, serum lipids, blood pressure, and sex differences in myocardial infarction. A 12-year follow-up of the Finnmark Study. Circulation 1996; 93: 450–456.

    Article  CAS  Google Scholar 

  35. Prescott E, Hippe M, Schnohr P, Hein HO, Vestbo J . Smoking and risk of myocardial infarction in women and men: longitudinal population study. BMJ 1998; 316: 1043–1047.

    Article  CAS  Google Scholar 

  36. StataCorp. Stata Statistical Software: Release 14. StataCorp LP: College Station, TX, 2014.

  37. Ng M, Fleming T, Robinson M, Thomson B, Graetz N, Margono C et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 2014; 384: 766–781.

    Article  Google Scholar 

  38. Hallal PC, Andersen LB, Bull FC, Guthold R, Haskell W, Ekelund U et al. Global physical activity levels: surveillance progress, pitfalls, and prospects. Lancet 2012; 380: 247–257.

    Article  Google Scholar 

  39. Global Burden of Disease and Risk Factors Collaborators Global Burden of Disease and Risk Factors Collaborators Forouzanfar MH, Global Burden of Disease and Risk Factors Collaborators Alexander L, Global Burden of Disease and Risk Factors Collaborators Anderson HR, Global Burden of Disease and Risk Factors Collaborators Bachman VF, Global Burden of Disease and Risk Factors Collaborators Biryukov S et al. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 2015; 386: 2287–2323.

    Article  Google Scholar 

  40. Knol MJ, Egger M, Scott P, Geerlings MI, Vandenbroucke JP . When one depends on the other: reporting of interaction in case-control and cohort studies. Epidemiology 2009; 20: 161–166.

    Article  Google Scholar 

  41. Greenland S . Interactions in epidemiology: relevance, identification, and estimation. Epidemiology 2009; 20: 14–17.

    Article  Google Scholar 

  42. Owen CG, Kapetanakis VV, Rudnicka AR, Wathern AK, Lennon L, Papacosta O et al. Body mass index in early and middle adult life: prospective associations with myocardial infarction, stroke and diabetes over a 30-year period: the British Regional Heart Study. BMJ Open 2015; 5: e008105.

    Article  Google Scholar 

  43. Jurca R, Lamonte MJ, Barlow CE, Kampert JB, Church TS, Blair SN . Association of muscular strength with incidence of metabolic syndrome in men. Med Sci Sports Exerc 2005; 37: 1849–1855.

    Article  Google Scholar 

  44. Wijndaele K, Duvigneaud N, Matton L, Duquet W, Thomis M, Beunen G et al. Muscular strength, aerobic fitness, and metabolic syndrome risk in Flemish adults. Med Sci Sports Exerc 2007; 39: 233–240.

    Article  Google Scholar 

  45. Van Gaal LF, Mertens IL, De Block CE . Mechanisms linking obesity with cardiovascular disease. Nature 2006; 444: 875–880.

    Article  CAS  Google Scholar 

  46. Sandvik L, Erikssen J, Thaulow E, Erikssen G, Mundal R, Rodahl K . Physical fitness as a predictor of mortality among healthy, middle-aged Norwegian men. N Engl J Med 1993; 328: 533–537.

    Article  CAS  Google Scholar 

  47. Diaz VA, Player MS, Mainous AG 3rd, Carek PJ, Geesey ME . Competing impact of excess weight versus cardiorespiratory fitness on cardiovascular risk. Am J Cardiol 2006; 98: 1468–1471.

    Article  Google Scholar 

  48. Allison MA, Jensky NE, Marshall SJ, Bertoni AG, Cushman M . Sedentary behavior and adiposity-associated inflammation: the Multi-Ethnic Study of Atherosclerosis. Am J Prev Med 2012; 42: 8–13.

    Article  Google Scholar 

  49. Rana JS, Arsenault BJ, Despres JP, Cote M, Talmud PJ, Ninio E et al. Inflammatory biomarkers, physical activity, waist circumference, and risk of future coronary heart disease in healthy men and women. Eur Heart J 2011; 32: 336–344.

    Article  CAS  Google Scholar 

  50. Swift DL, Lavie CJ, Johannsen NM, Arena R, Earnest CP, O'Keefe JH et al. Physical activity, cardiorespiratory fitness, and exercise training in primary and secondary coronary prevention. Circ J 2013; 77: 281–292.

    Article  Google Scholar 

  51. Sui X, LaMonte MJ, Blair SN . Cardiorespiratory fitness as a predictor of nonfatal cardiovascular events in asymptomatic women and men. Am J Epidemiol 2007; 165: 1413–1423.

    Article  Google Scholar 

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Acknowledgements

This work was supported by the National Heart, Lung, and Blood Institute at the National Institutes of Health (R01 HL116381 to K.S.); the Swedish Research Council; and ALF project grant, Region Skåne/Lund University, Sweden. The funding agencies had no role in the design and conduct of the study; in the collection, analysis, and interpretation of the data; or in the preparation, review, or approval of the manuscript.

Author contributions

JS had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis; study concept and design: CC, JS, MAW and KS; acquisition of data: JS and KS; analysis and interpretation of data: CC, JS, MAW and KS; drafting of the manuscript: CC; critical revision of the manuscript for important intellectual content: CC, JS, MAW and KS; statistical analysis: CC and JS; obtained funding: JS and KS.

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Correspondence to C Crump.

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Crump, C., Sundquist, J., Winkleby, M. et al. Interactive effects of obesity and physical fitness on risk of ischemic heart disease. Int J Obes 41, 255–261 (2017). https://doi.org/10.1038/ijo.2016.209

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