Modifiable Healthy Lifestyle Behaviors: 10-Year Health Outcomes From a Health Promotion Program


      Previous studies have examined the impact of healthy lifestyle choices on health-related outcomes; however, given their fragmented, often cross-sectional nature, assessing the relative impact of daily modifiable behaviors on overall long-term outcomes, particularly for a diverse working adult population, remains challenging.


      Relationships between ten self-reported healthy lifestyle behaviors and health outcomes during the subsequent 9 years in a cohort of 10,248 participants enrolled during 2003 in a voluntary workplace wellness program were assessed. Cox proportional-hazards models computed hazard ratios (HRs) for lifestyle characteristics associated with time to one of seven self-reported chronic diseases or death. Data were collected between 2003 and 2012 and analyzed between 2014 and 2016.


      Behaviors that most significantly affected future outcomes were low-fat diet, aerobic exercise, nonsmoking, and adequate sleep. A dose–response effect was seen between dietary fat intake and hypertension, obesity, diabetes, heart disease, and hypercholesterolemia. After dietary fat intake, aerobic exercise was the next most significant behavior associated with development of outcomes. Compared with sedentary participants, those who exercised 4 days per week were less likely to develop new-onset diabetes (HR=0.31, 95% CI=0.20, 0.48); heart disease (HR=0.46, 95% CI=0.27, 0.80); and hypercholesterolemia (HR=0.61, 95% CI=0.50, 0.74). Low-fat diet and adequate sleep were more significant than commonly promoted healthy behaviors, such as eating a daily breakfast.


      Modifiable lifestyle behaviors targeted in health promotion programs should be prioritized in an evidence-based manner. Top priorities for workplace health promotion should include low-fat diet, aerobic exercise, nonsmoking, and adequate sleep.
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        • Goetzel R.Z.
        • Pei X.
        • Tabrizi M.J.
        • et al.
        Ten modifiable health risk factors are linked to more than one-fifth of employer-employee health care spending.
        Health Aff (Millwood). 2012; 31 (2474-1284.
        • Edington D.W.
        • Yen L.T.
        • Witting P.
        The financial impact of changes in personal health practices.
        J Occup Environ Med. 1997; 39: 1037-1046
        • Anderson D.R.
        • Whitmer R.W.
        • Goetzel R.Z.
        • et al.
        The relationship between modifiable health risks and group-level health care expenditures. Health Enhancement Research Organization (HERO) Research Committee.
        Am J Health Promot. 2000; 15: 45-52
        • Yusuf S.
        • Hawken S.
        • Ounpuu S.
        • et al.
        Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study.
        Lancet. 2004; 364: 937-952
        • Kannel W.B.
        • Larson M.
        Long-term epidemiologic prediction of coronary disease. The Framingham experience.
        Cardiology. 1993; 82: 137-152
        • Djoussé L.
        • Driver J.A.
        • Gaziano J.M.
        Relation between modifiable lifestyle factors and lifetime risk of heart failure.
        JAMA. 2009; 302: 394-400
        • Djoussé L.
        • Biggs M.L.
        • Mukamal K.J.
        • Siscovick D.
        Alcohol consumption and type 2 diabetes among older adults: the Cardiovascular Health Study.
        Obesity (Silver Spring). 2007; 15: 1758-1765
        • Moore L.L.
        • Singer M.R.
        • Bradlee M.L.
        • et al.
        Intake of fruits, vegetables, and dairy products in early childhood and subsequent blood pressure change.
        Epidemiology. 2005; 16: 4-11
        • Appel L.J.
        • Moore T.J.
        • Obarzanek E.
        • et al.
        A clinical trial of the effects of dietary patterns on blood pressure.
        N Engl J Med. 1997; 336: 1117-1124
        • Byun W.
        • Sieverdes J.C.
        • Sui X.
        • et al.
        Effect of positive health factors and all-cause mortality in men.
        Med Sci Sports Exerc. 2010; 42: 1632-1638
        • King D.E.
        • Mainous 3rd, A.G.
        • Geesey M.E.
        Turning back the clock: adopting a healthy lifestyle in middle age.
        Am J Med. 2007; 120: 598-603
        • Edington D.W.
        • Yen L.
        • Braunstein A.
        The reliability and validity of health risk assessments.
        in: Hyner G. Peterson K. Travis J. Dewet J. Forester J. Framer E. SPM Handbook of Health Assessment Tools. The Society of Prospective Medicine and Institute for Health and Productivity Management, Pittsburgh, PA1999: 135-142
        • Ford E.S.
        • Bergmann M.M.
        • Kroger J.M.
        • Schienkiewitz A.
        • Weikert C.
        • Boeing H.
        Healthy living is the best revenge: findings from the European Prospective Investigation Into Cancer and Nutrition-Potsdam study.
        Arch Intern Med. 2009; 169: 1355-1362
        • Will J.C.
        • Galuska D.A.
        • Ford E.S.
        • et al.
        Cigarette smoking and diabetes mellitus: evidence of a positive association from a large prospective cohort study.
        Int J Epidemiol. 2001; 30: 540-546
        • Laugsand L.E.
        • Strand L.B.
        • Platou C.
        • Vatten L.J.
        • Janszky I.
        Insomnia and the risk of incident heart failure: a population study.
        Eur Heart J. 2014; 35: 1382-1393
        • Ornish D.
        • Scherwitz L.W.
        • Billings J.H.
        • et al.
        Intensive lifestyle changes for reversal of coronary heart disease.
        JAMA. 1998; 280: 2001-2007
        • Goetzel R.Z.
        • Carls G.S.
        • Wang S.
        • et al.
        The relationship between modifiable health risk factors and medical expenditures, absenteeism, short-term disability, and presenteeism among employees at Novartis.
        J Occup Environ Med. 2009; 51: 487-499
        • Pronk N.P.
        • Goodman M.J.
        • O’Connor P.J.
        • Martinson B.C.
        Relationship between modifiable health risks and short-term health care charges.
        JAMA. 1999; 282: 2235-2239
        • Chiuve S.E.
        • McCullough M.L.
        • Sacks F.M.
        • Rimm E.B.
        Healthy lifestyle factors in the primary prevention of coronary heart disease among men: benefits among users and nonusers of lipid-lowering and antihypertensive medications.
        Circulation. 2006; 114: 160-167
        • Pelletier K.R.
        A review and analysis of the clinical and cost-effectiveness studies of comprehensive health promotion and disease management programs at the worksite: update VI 2000-2004.
        J Occup Environ Med. 2005; 47: 1051-1058
        • Nyce S.
        • Grossmeier J.
        • Anderson D.R.
        • Terry P.E.
        • Kelley B.
        Association between changes in health risk status and changes in future health care costs: a multiemployer study.
        J Occup Environ Med. 2012; 54: 1364-1373
        • Pronk N.P.
        • Anderson L.H.
        • Crain A.L.
        • et al.
        Meeting recommendations for multiple healthy lifestyle factors. Prevalence, clustering, and predictors among adolescent, adult, and senior health plan members.
        Am J Prev Med. 2004; 27: 25-33
        • Byrne D.W.
        • Goetzel R.Z.
        • McGown P.W.
        • et al.
        Seven-year trends in employee health habits from a comprehensive workplace health promotion program at Vanderbilt University.
        J Occup Environ Med. 2011; 53: 1372-1381
        • Rolando L.
        • Byrne D.W.
        • McGown P.W.
        • Goetzel R.Z.
        • Elasy T.A.
        • Yarbrough M.I.
        Health risk factor modification predicts incidence of diabetes in an employee population: results of an 8-year longitudinal cohort study.
        J Occup Environ Med. 2013; 55: 410-415
        • Birdee G.S.
        • Byrne D.W.
        • McGown P.W.
        • et al.
        Relationship between physical inactivity and health characteristics among participants in an employee-wellness program.
        J Occup Environ Med. 2013; 55: 514-519
      1. The Health Project. C. Everett Koop National Health Awards. 2008 Winning Programs. Go for the Gold Wellness Program—Vanderbilt University. Accessed August 17, 2014.

        • Wellsource, Inc
        Health assessment software systems.
        Clackamas, OR, Personal Wellness Profile, Concise Assessment Plus2014
      2. Wellsource, Inc. Personal Wellness Profile(TM), Advantage Health Risk Assessment. Clackamas, OR. Accessed September 1, 2016.

        • Soler R.E.
        • Leeks K.D.
        • Razi S.
        • et al.
        Task Force on Community Preventive Services. A systematic review of selected interventions for worksite health promotion. The assessment of health risks with feedback.
        Am J Prev Med. 2010; 38: S237-S262
        • Goetzel R.Z.
        • Pronk N.P.
        Worksite health promotion—how much do we really know about what works?.
        Am J Prev Med. 2010; 38: S223-S225
        • Goetzel R.Z.
        • Anderson D.R.
        • Whitmer R.W.
        • et al.
        The relationship between modifiable health risks and health care expenditures. An analysis of the multi-employer HERO health risk and cost database.
        J Occup Environ Med. 1998; 40: 843-854
      3. Mattke S, Schnyer C, Van Busum KR. A review of the U.S. workplace wellness market. U.S. Department of Labor, U.S. DHHS. Published 2012. Accessed August 29, 2014.

        • Harrell Jr, F.E.
        Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis.
        2nd ed. Springer, Cham2015 (section 4.4, page 72)
        • Smith L.R.
        • Harrell Jr, F.E.
        • Muhlbaier L.H.
        Problems and potentials in modeling survival.
        in: Grady M.L. Schwartz H.A. Medical Effectiveness Research Data Methods (Summary Report), AHCPR Pub. No. 92-0056, 151–59. U.S. DHHS, Agency for Health Care Policy and Research, Rockville, MD1992
        • Cox D.R.
        Regression models and life tables.
        J R Stat Soc B. 1972; 34: 187-202
      4. R Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. Published 2014. Accessed August 17, 2014.

        • Dhurandhar E.J.
        • Dawson J.
        • Alcorn A.
        • et al.
        The effectiveness of breakfast recommendations on weight loss: a randomized controlled trial.
        Am J Clin Nutr. 2014; 100: 507-513
        • Task Force on Community Preventive Services
        Recommendations for worksite-based interventions to improve workers’ health.
        Am J Prev Med. 2010; 38: S232-S236
        • Chakravarthy M.V.
        • Joyner M.J.
        • Booth F.W.
        An obligation for primary care physicians to prescribe physical activity to sedentary patients to reduce the risk of chronic health conditions.
        Mayo Clin Proc. 2002; 77: 165-173
        • Paffenbarger Jr, R.S.
        • Hyde R.T.
        • Wing A.L.
        • Lee I.M.
        • Jung D.L.
        • Kampert J.B.
        The association of changes in physical-activity level and other lifestyle characteristics with mortality among men.
        N Engl J Med. 1993; 328: 538-545
        • CDC, Merck Institute of Aging & Health
        The state of aging and health in America 2004.
        Merck Institute of Aging & Health, Washington, DC2004 (Accessed August 25, 2014)
        • Eyre H.
        • Kahn R.
        • Robertson R.M.
        • et al.
        Preventing cancer, cardiovascular disease, and diabetes: a common agenda for the American Cancer Society, the American Diabetes Association, and the American Heart Association.
        Circulation. 2004; 109: 3244-3255
        • Reis J.P.
        • Loria C.M.
        • Sorlie P.D.
        • Park Y.
        • Hollenbeck A.
        • Schatzkin A.
        Lifestyle factors and risk for new-onset diabetes: a population-based cohort study.
        Ann Intern Med. 2011; 155: 292-299
        • Britton A.
        • Shipley M.
        • Singh-Manoux A.
        • Marmot M.G.
        Successful aging: the contribution of early-life and midlife risk factors.
        J Am Geriatr Soc. 2008; 56: 1098-1105
        • Arena R.
        • Guazzi M.
        • Briggs P.D.
        • et al.
        Promoting health and wellness in the workplace: a unique opportunity to establish primary and extended secondary cardiovascular risk reduction programs.
        Mayo Clin Proc. 2013; 88: 605-617
        • Stamler J.
        • Wentworth D.
        • Neaton J.D.
        Is relationship between serum cholesterol and risk of premature death from coronary heart disease continuous and graded? Findings in 356,222 primary screenees of the Multiple Risk Factor Intervention Trial (MRFIT).
        JAMA. 1986; 256: 2823-2828
        • Yates L.B.
        • Djoussé L.
        • Kurth T.
        • Buring J.E.
        • Gaziano J.M.
        Exceptional longevity in men: modifiable factors associated with survival and function to age 90 years.
        Arch Intern Med. 2008; 168: 284-290
        • Stampfer M.J.
        • Hu F.B.
        • Manson J.E.
        • Rimm E.B.
        • Willett W.C.
        Primary prevention of coronary heart disease in women through diet and lifestyle.
        N Engl J Med. 2000; 343: 16-22
        • Liu S.
        • Manson J.E.
        • Stampfer M.J.
        • et al.
        A prospective study of whole-grain intake and risk of type 2 diabetes mellitus in U.S. women.
        Am J Public Health. 2000; 90: 1409-1415
        • Brunner Huber L.R.
        Validity of self-reported height and weight in women of reproductive age.
        Matern Child Health J. 2007; 11: 137-144
        • Kurth T.
        • Moore S.C.
        • Gaziano J.M.
        • et al.
        Healthy lifestyle and the risk of stroke in women.
        Arch Intern Med. 2006; 166: 1403-1409
        • Hu F.B.
        • Manson J.E.
        • Stampfer M.J.
        • et al.
        Diet, lifestyle, and the risk of type 2 diabetes mellitus in women.
        N Engl J Med. 2001; 345: 790-799
        • Behrens G.
        • Fischer B.
        • Kohler S.
        • Park Y.
        • Hollenbeck A.R.
        • Leitzmann M.F.
        Healthy lifestyle behaviors and decreased risk of mortality in a large prospective study of U.S. women and men.
        Eur J Epidemiol. 2013; 28: 361-372
        • Knoops K.T.
        • de Groot L.C.
        • Kromhout D.
        • et al.
        Mediterranean diet, lifestyle factors, and 10-year mortality in elderly European men and women: the HALE project.
        JAMA. 2004; 292: 1433-1439
        • Newman A.B.
        • Spiekerman C.F.
        • Enright P.
        • et al.
        Daytime sleepiness predicts mortality and cardiovascular disease in older adults. The Cardiovascular Health Study Research Group.
        J Am Geriatr Soc. 2000; 48: 115-123
        • Mozaffarian D.
        • Kamineni A.
        • Carnethon M.
        • Djousse´ L.
        • Mukamal K.J.
        • Siscovick D.
        Lifestyle risk factors and new-onset diabetes mellitus in older adults: the cardiovascular health study.
        Arch Intern Med. 2009; 169: 798-807
        • Sahyoun N.R.
        • Jacques P.F.
        • Zhang X.L.
        • Juan W.
        • McKeown N.M.
        Whole-grain intake is inversely associated with the metabolic syndrome and mortality in older adults.
        Am J Clin Nutr. 2006; 83: 124-131
        • Lewis C.
        • Jacobs D.
        • McCreath H.
        • et al.
        Weight gain continues in the 1990s: 10-year trends in weight and overweight from the CARDIA study.
        Am J Epidemiol. 2000; 151: 1172-1181
        • Kochar J.
        • Djousse´ L.
        • Gaziano J.M.
        Breakfast cereals and risk of type-2 diabetes in the Physicians’ Health Study I.
        Obesity (Silver Spring). 2007; 15: 3039-3044
        • Djousse´ L.
        • Kochar J.
        • Gaziano J.M.
        Dietary factors and risk of heart failure: a systematic review.
        Curr Cardiovasc Risk Rep. 2007; 1: 330-334
        • Merrill R.M.
        • Anderson A.
        • Thygerson S.M.
        Effectiveness of a worksite wellness program on health behaviors and personal health.
        J Occup Environ Med. 2011; 53: 1008-1012
        • Fryer R.
        Financial incentives and student achievement: evidence from randomized trials.
        Q J Econ. 2011; 126: 1755-1798
        • Kane R.L.
        • Johnson P.E.
        • Town R.J.
        • Butler M.
        A structured review of the effect of economic incentives on consumers’ preventive behavior.
        Am J Prev Med. 2004; 27: 327-352
        • Reeves M.J.
        • Rafferty A.P.
        Healthy lifestyle characteristics among adults in the United States, 2000.
        Arch Intern Med. 2005; 165: 854-857
        • Troost J.P.
        • Rafferty A.P.
        • Luo Z.
        • Reeves M.J.
        Temporal and regional trends in the prevalence of healthy lifestyle characteristics: United States, 1994-2007.
        Am J Public Health. 2012; 102: 1392-1398
        • Muraki I,
        • Imamura F.
        • Manson J.E.
        • et al.
        Fruit consumption and risk of type 2 diabetes: results from three prospective longitudinal cohort studies.
        BMJ. 2013; 28: f5001
        • Ozminkowski R.J.
        • Goetzel R.Z.
        Getting closer to the truth: overcoming research challenges when estimating the financial impact of worksite health promotion programs.
        Am J Health Promot. 2001; 15: 289-295
        • Neville B.H.
        • Merrill R.M.
        • Kumpfer K.L.
        Longitudinal outcomes of a comprehensive, incentivized worksite wellness program.
        Eval Health Prof. 2011; 34: 103-123
        • Marshall A.L.
        • Smith B.J.
        • Bauman A.E.
        • Kaur S.
        Reliability and validity of a brief physical activity assessment for use by family doctors.
        Br J Sports Med. 2005; 39: 294-297
        • Molenaar E.A.
        • Van Ameijden E.J.
        • Grobbee D.E.
        • Numans M.E.
        Comparison of routine care self-reported and biometrical data on hypertension and diabetes: results of the Utrecht Health Project.
        Eur J Public Health. 2007; 17: 199-205
        • Goldman N.
        • Lin I.F.
        • Weinstein M.
        • Lin Y.H.
        Evaluating the quality of self-reports of hypertension and diabetes.
        J Clin Epidemiol. 2003; 56: 148-154
        • Newell S.A.
        • Girgis A.
        • Sanson-Fisher R.W.
        • Savolainen N.J.
        The accuracy of self-reported health behaviors and risk factors relating to cancer and cardiovascular disease in the general population: a critical review.
        Am J Prev Med. 1999; 17: 211-229
        • Johansson J.
        • Hellenius M.L.
        • Elofsson S.
        • Krakau I.
        Self-report as a selection instrument in screening for cardiovascular disease risk.
        Am J Prev Med. 1999; 16: 322-324
        • Oliveira A.
        • Ramos E.
        • Lopes C.
        • Barros H.
        Self-reporting weight and height: misclassification effect on the risk estimates for acute myocardial infarction.
        Eur J Public Health. 2009; 19: 548-553
        • Okura Y.
        • Urban L.H.
        • Mahoney D.W.
        • Jacobsen S.J.
        • Rodeheffer R.J.
        Agreement between self-report questionnaires and medical record data was substantial for diabetes, hypertension, myocardial infarction and stroke but not for heart failure.
        J Clin Epidemiol. 2004; 57: 1096-1103
        • Chapman L.S.
        Proof Positive: An Analysis of the Cost Effectiveness of Worksite Wellness.
        Chapman Institute, Seattle, WA2008
      5. U.S. Department of Labor. Women’s Bureau. Women in the Labor Force in 2010. Accessed August 21, 2014.

      6. U.S. Department of Labor. Bureau of Labor Statistics. Accessed August 21, 2014.

        • Schroeder S.A.
        We can do better—improving the health of the American people.
        N Engl J Med. 2007; 357: 1221-1228
        • Mokdad A.H.
        • Marks J.S.
        • Stroup J.S.
        • Gerberding J.L.
        Actual causes of death in the United States, 2000.
        JAMA. 2004; 291 ([Errata, JAMA. 2005;293:293–4,298.] 1238-1245
        • Stringhini S.
        • Sabia S.
        • Shipley M.
        • et al.
        Association of socioeconomic position with health behaviors and mortality.
        JAMA. 2010; 303: 1159-1166