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Original Investigation |

Healthy Lifestyle Characteristics Among Adults in the United States, 2000 FREE

Mathew J. Reeves, PhD; Ann P. Rafferty, PhD
[+] Author Affiliations

Author Affiliations: Department of Epidemiology, College of Human Medicine, Michigan State University, East Lansing (Dr Reeves); and Bureau of Epidemiology, Michigan Department of Community Health, Lansing (Dr Rafferty).


Arch Intern Med. 2005;165(8):854-857. doi:10.1001/archinte.165.8.854.
Text Size: A A A
Published online

Background  Many public health recommendations and clinical guidelines emphasize the importance of healthy lifestyles. Recent epidemiologic studies demonstrate that following a healthy lifestyle has substantial health benefits. The objectives of this study were to report on the prevalence of healthy lifestyle characteristics (HLCs) and to generate a single indicator of a healthy lifestyle.

Methods  National data for the year 2000 were obtained from the Behavioral Risk Factor Surveillance System, which consists of annual, statewide, random digit–dialed household telephone surveys. We defined the following 4 HLCs: nonsmoking, healthy weight (body mass index [calculated as weight in kilograms divided by the square of height in meters] of 18.5-25.0), consuming 5 or more fruits and vegetables per day, and regular physical activity (≥30 minutes for ≥5 times per week). The 4 HLCs were summed to create a healthy lifestyle index (range, 0-4), and the pattern of following all 4 HLCs was defined as a single healthy lifestyle indicator. We report prevalences of each HLC and the indicator by major demographic subgroups.

Results  By using data from more than 153 000 adults, the prevalence (95% confidence interval) of the individual HLCs was as follows: nonsmoking, 76.0% (75.6%-76.4%); healthy weight, 40.1% (39.7%-40.5%); 5 fruits and vegetables per day, 23.3% (22.9%-23.7%); and regular physical activity, 22.2% (21.8%-22.6%). The overall prevalence of the healthy lifestyle indicator (ie, having all 4 HLCs) was only 3.0% (95% confidence interval, 2.8%-3.2%), with little variation among subgroups (range, 0.8%-5.7%).

Conclusion  These data illustrate that a healthy lifestyle—defined as a combination of 4 HLCs—was undertaken by very few adults in the United States, and that no subgroup followed this combination to a level remotely consistent with clinical or public health recommendations.

In the United States and worldwide, chronic diseases account for the greatest overall population disease burden in terms of mortality, morbidity, and decreased quality of life.1 Most people with major chronic diseases share multiple common lifestyle characteristics or behaviors, particularly smoking, poor diet, physical inactivity, and obesity.2 Tobacco, poor diet, and physical inactivity have been identified as leading contributors to overall mortality in the United States.3 The public health importance of these lifestyle characteristics can also be gauged by their inclusion in major public health reports on smoking,4,5 physical activity,6 and diet,7 and in clinical guidelines concerning blood pressure,8 cholesterol,9 and obesity,10 which all emphasize lifestyle modification as a key element of prevention and control.

Recently, epidemiologic studies have provided clear evidence of the benefits of avoiding major cardiovascular risk factors1114 and following a healthy lifestyle.15,16 For example, the Nurses’ Health Study found that the risk of coronary heart disease15 and type 2 diabetes mellitus16 was reduced 5- and 10-fold, respectively, among those who engaged in 5 modifiable healthy behaviors. However, only 3% of the nurses actually engaged in this lifestyle.

We chose to estimate the prevalence of 4 healthy lifestyle characteristics (HLCs) (ie, nonsmoking, healthy weight, fruit and vegetable consumption, and leisure time physical activity [LTPA]) using a nationally representative sample of US adults, and to generate a single indicator of a healthy lifestyle defined by undertaking all 4 HLCs.

The Behavioral Risk Factor Surveillance System (BRFSS) is composed of annual, statewide, random digit–dialed household telephone surveys of adults.17,18 We pooled the 2000 BRFSS responses from all 50 states and the District of Columbia, and restricted the sample to respondents aged 18 to 74 years. The median cooperation rate of the state-specific surveys was 51.3% (range, 33.4%-75.5%).

All data were based on self-report. Healthy weight was defined as a body mass index (calculated as weight in kilograms divided by the square of height in meters) between 18.5 and 25.0.10 Food frequency questions were used to measure the consumption of fruit juice, fruit, green salad, potatoes (excluding fried products), carrots, and other vegetables, and adequate consumption was defined as eating fruits and vegetables 5 or more times per day.7 Leisure time physical activity was based on questions regarding the frequency and duration of up to 2 activities. Regular LTPA was defined as 30 minutes or more of at least moderate-intensity physical activity 5 or more times per week.6

We created an index of healthy lifestyle by summing the total number of HLCs for each respondent (range, 0-4), and then defined the pattern of following all 4 HLCs as a single indicator of healthy lifestyle (ie, index of healthy lifestyle = 4). We then estimated the prevalence of each individual HLC by age, sex, race, education, household income, and self-reported health status, and generated age-adjusted prevalence estimates for the indicator of healthy lifestyle by direct age standardization using the internal age distribution.19 We chose not to report P values and limited the reporting of confidence intervals (CIs), because the large number of observations result in even minor differences being statistically significant. To account for weighting and complex sampling design, statistical software (SUDAAN) was used.20

The 2000 BRFSS included 164 940 respondents aged 18 to 74 years. We excluded respondents with missing information, resulting in a working sample size of 153 805. The prevalence estimates of each HLC by the 6 demographic and health-related variables are shown in Table 1. Seventy-six percent (95% CI, 75.6%-76.4%) of US adults did not currently smoke cigarettes. Nonsmoking showed strong positive trends with increasing age, education, household income, and health status. Only 40.1% (95% CI, 39.7-40.5%) of adults had healthy weight, which showed a strong inverse trend with age and positive trends with education and health status. Healthy weight was more common in women and among whites. Only 23.3% (95% CI, 22.9%-23.7%) of persons consumed fruits and vegetables 5 or more times per day, while regular LTPA was undertaken by only 22.2% (95% CI, 21.8%-22.6%).

Table Graphic Jump LocationTable 1. Prevalence of Individual HLCs*

The healthy lifestyle index was distributed as follows: 9.4% (95% CI, 9.1%-9.7%) had 0 HLCs, 39.6% (95% CI, 39.2%-40.0%) had 1, 34.2% (95% CI, 33.8%-34.6%) had 2, 13.8% (95% CI, 13.5%-14.1%) had 3, and only 3.0% (95% CI, 2.8%-3.2%) followed all 4 HLCs (and, therefore, met the criteria for the healthy lifestyle indicator). There are 16 possible unique permutations or combinations of the 4 HLCs; however, only 2 were followed by more than 10% of the population (nonsmokers with no other HLCs made up 29.0%, and nonsmokers with a healthy weight represented 16.1%). The 9.4% of subjects who did not engage in any of the 4 HLCs was the next most common group.

The age-adjusted prevalence estimates of the healthy lifestyle indicator (ie, engaging in all 4 HLCs) by the 6 demographic and health-related variables are shown in Table 2. The overall prevalence was only 3.0%, and the absolute differences across subgroups were small, ranging from 0.8% (in persons with less than high school education) to only 5.7% (in persons in excellent health).

Table Graphic Jump LocationTable 2. Age-Adjusted Prevalence of the Healthy Lifestyle Indicator by Subgroup*

The results generated from this nationally representative database indicate that just 3.0% of US adults followed a combination of 4 modifiable lifestyle characteristics—nonsmoking, healthy weight, adequate fruit and vegetable consumption, and regular physical activity. No subgroup engaged in all 4 healthy lifestyles to any important degree— the highest prevalence being only 5.7%. These results illustrate the extraordinarily low prevalence of healthy lifestyles in the US adult population. While the overall prevalence of 3.0% was extremely low, it is identical to that reported in the Nurses’ Health Study15,16 and similar to reports generated from the Third National Health and Nutrition Examination Survey.21,22

The low prevalence of the healthy lifestyle indicator in our study is a function of the prevalences of the individual HLCs and how they aggregate or cluster together. While three quarters of US adults do not smoke, the prevalences of the other 3 lifestyles were quite low. Only two fifths of the population had a healthy weight, while only a quarter consumed adequate fruits and vegetables or engaged in regular LTPA. How these factors then combine together is dependent on the degree to which they are correlated. While it is commonly recognized that smoking and alcohol are associated with one another,23 the degree of association between other lifestyle characteristics is less clear.22,2427 If the 4 HLCs were statistically independent, the expected prevalence of the indicator would be 1.5%, which indicates that the actual magnitude of association among these HLCs is small to nonexistent. This finding is in agreement with those of other studies that have found that while health behaviors are interrelated, the magnitude of the relationship is not large and the aggregation of factors beyond simple pairwise correlations is complex.22,2427

There are several potential limitations to our study. First, these data are open to the limitations inherent in self-reported data.28 Second, the BRFSS captures information on LTPA only, which may underestimate total activity, and BRFSS estimates of daily fruit and vegetable consumption are lower than those based on more extensive food frequency questionnaires.29 Noncoverage and nonresponse biases typical of telephone surveys may affect our estimates. Specifically, comparisons made to the US census indicate that BRFSS respondents are slightly more likely to be older, female, white, and more educated. These facts, along with declining response rates, have led to concerns about response bias. However, recent work has found that such worries may be exaggerated, because in general household population random digit–dialed surveys, response rates ranging from 30% to 70% were not associated with significant bias.3032

We also recognize that obesity is, in part, a consequence of dietary and physical activity behaviors. It is for this reason that some health behavior studies have not included body mass index22; however, we chose to include it because of its public health importance. Other studies15,16,22 have included moderate alcohol consumption as a healthy lifestyle factor because of its overall benefits in reducing cardiovascular risk. However, we chose not to include alcohol consumption in our index because of the difficulty in developing a clear, unified, public health recommendation on this topic.33 Finally, it could be argued that combining all 4 HLCs into a single indicator is too extreme, because the prevalence of the indicator is unlikely to change in response to public health interventions. However, we believe that our approach offers a single figure that can serve as a useful population-level indicator of healthy lifestyle behaviors for surveillance purposes, and a measure that could be useful when counseling individual patients about healthier lifestyles.

In summary, we found that only 3.0% of US adults followed 4 common modifiable HLCs. We believe that these findings serve to illustrate the health promotion crisis in the United States, characterized by excessive caloric intake, inadequate LTPA, increasing obesity, and high rates of cigarette use. These data, along with those that illustrate the benefit of following a healthy lifestyle,15,16 support the need for comprehensive primary prevention activities to increase healthy lifestyles and to reduce the prevalence of chronic disease risk factors at the population level.13,33,34

Correspondence: Mathew J. Reeves, PhD, Department of Epidemiology, College of Human Medicine, Michigan State University, B601 West Fee Hall, East Lansing, MI 48823 (Reevesm@msu.edu).

Accepted for Publication: January 6, 2005.

Previous Presentation: This study was presented at the National Cardiovascular Health Conference; April 13, 2002; Washington, DC.

Financial Disclosure: None.

Murray  CJLopez  AD Mortality by cause for eight regions of the world: Global Burden of Disease Study. Lancet 1997;3491269- 1276
PubMed Link to Article
Brownson  RCedRemington  PLedDavis  JRed Chronic Disease Epidemiology and Control 2nd ed. Washington, DC American Public Health Association1998;
Mokdad  AHMarks  JSStroup  DFGerberding  JL Actual causes of death in the United States, 2000. JAMA 2004;2911238- 1245
PubMed Link to Article
US Department of Health and Human Services, Reducing Tobacco Use: A Report of the Surgeon General.  Atlanta, Ga Office on Smoking and Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention2000;
US Department of Health and Human Services, Women and Smoking: A Report of the Surgeon General.  Atlanta, Ga Office on Smoking and Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention2001;
US Department of Health and Human Services, Physical Activity and Health: A Report of the Surgeon General.  Atlanta, Ga National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention1996;
US Department of Health and Human Services, National Cancer Institute’s 5-A-Day Program. Available at: http://www.5aday.gov. Accessed June 8, 2004
Chobanian  AVBakris  GLBlack  HR  et al.  The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA 2003;2892560- 2572
PubMed Link to Article
Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults, Executive summary of the Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). JAMA 2001;2852486- 2497
PubMed Link to Article
National Heart, Lung, and Blood Institute, National Institutes of Health, Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults: The Evidence Report.  Bethesda, Md National Heart, Lung, and Blood Institute1998;
Yusuf  HRGiles  WHCroft  JBAnda  RFCasper  ML Impact of multiple risk factor profiles on determining cardiovascular disease risk. Prev Med 1998;271- 9
PubMed Link to Article
Stamler  JDyer  ARShekelle  RBNeaton  JStamler  R Relationship of baseline major risk factors to coronary and all-cause mortality, and to longevity: findings from long-term follow-up of Chicago cohorts. Cardiology 1993;82191- 222
PubMed Link to Article
Stamler  JStamler  RNeaton  JD  et al.  Low risk-factor profile and long-term cardiovascular and noncardiovascular mortality and life expectancy. JAMA 1999;2822012- 2018
PubMed Link to Article
Wilson  PWD’Agostino  RBLevy  D  et al.  Prediction of coronary heart disease using risk factor categories. Circulation 1998;971837- 1847
PubMed Link to Article
Stampfer  MJHu  FBManson  JERimm  EBWillet  WC Primary prevention of coronary heart disease in women through diet and lifestyle. N Engl J Med 2000;34316- 22
PubMed Link to Article
Hu  FBManson  JEStampfer  MJ  et al.  Diet, lifestyle and the risk of type 2 diabetes mellitus in women. N Engl J Med 2001;345790- 797
PubMed Link to Article
Nelson  DEHoltzman  DWaller  M  et al.  Objectives and design of the Behavioral Risk Factor Surveillance System.  Paper presented at: Section on Survey Research Methods, American Statistical Association National Meeting August 10, 1998 Dallas, Tex
National Center for Chronic Disease Prevention and Health Promotion Centers for Disease Control and Prevention, Behavioral Risk Factor Surveillance System: technical information and data. Available at: http://www.cdc.gov/brfss/technical_infodata/index.htm. Accessed June 8, 2004
Rothman  KJ Modern Epidemiology.  Boston, Mass Little Brown & Co Inc1986;
Shah  BVBarnwell  BGBieler  GS SUDAAN Users Manual: Release 7.5.  Research Triangle Park, NC Research Triangle Institute1997;
Ford  ESFord  MAWill  JCGaluska  DABallew  C Achieving a healthy lifestyle among United States adults: a long way to go. Ethn Dis 2001;11224- 231
PubMed
Berrigan  DDodd  KTroiano  RPKrebs-Smith  SMBarbush  RB Patterns of health behavior in US adults. Prev Med 2003;36615- 623
PubMed Link to Article
Istvan  JMatarazzo  JD Tobacco, alcohol, and caffeine use: a review of their interrelationships. Psychol Bull 1948;95301- 326
Link to Article
Patterson  REHaines  PSPopkin  BM Health lifestyle patterns of US adults. Prev Med 1994;23453- 460
PubMed Link to Article
Sobal  JRevicki  DDe Forge  BR Patterns of interrelationships among health-promotion behaviors. Am J Prev Med 1992;8351- 359
PubMed
Ma  JBets  NMHampl  JS Clustering of lifestyle behaviors: the relationship between cigarette smoking, alcohol consumption, and dietary intake. Am J Health Promot 2000;15107- 117
PubMed Link to Article
Johnson  MFNichols  JFSallis  JFCalfas  KJHovell  MF Interrelationships between physical activity and other health behaviors among university women and men. Prev Med 1998;27536- 544
PubMed Link to Article
Nelson  DEHoltzman  DBolen  JStanwyck  CAMack  KA Reliability and validity of measures from the Behavioral Risk Factor Surveillance System (BRFSS). Soz Praventivmed 2001;46 ((suppl 1)) S3- S42
PubMed Link to Article
Serdula  MCoates  RByers  T  et al.  Evaluation of a brief telephone questionnaire to estimate fruit and vegetable consumption in diverse study populations. Epidemiology 1993;4455- 463
PubMed Link to Article
Mariolis  P Response rates and accuracy of the BRFSS data.  Paper presented at: Nineteenth Annual BRFSS Conference March 13, 2002 Atlanta, Ga
Curtin  RPresser  SSinger  E The effects of response rate changes on the Index of Consumer Sentiment. Public Opin Q 2000;64413- 428
PubMed Link to Article
Keeter  SMiller  CKohut  AGroves  RMPresser  S Consequences of reducing nonresponse in a national telephone survey. Public Opin Q 2000;64125- 148
Link to Article
Labarthe  DR Epidemiology and Prevention of Cardiovascular Diseases.  Gaithersburg, Md Aspen Publishers Inc1998;
Rose  G The Strategy of Preventive Medicine.  New York, NY Oxford University Press Inc1992;

Figures

Tables

Table Graphic Jump LocationTable 1. Prevalence of Individual HLCs*
Table Graphic Jump LocationTable 2. Age-Adjusted Prevalence of the Healthy Lifestyle Indicator by Subgroup*

References

Murray  CJLopez  AD Mortality by cause for eight regions of the world: Global Burden of Disease Study. Lancet 1997;3491269- 1276
PubMed Link to Article
Brownson  RCedRemington  PLedDavis  JRed Chronic Disease Epidemiology and Control 2nd ed. Washington, DC American Public Health Association1998;
Mokdad  AHMarks  JSStroup  DFGerberding  JL Actual causes of death in the United States, 2000. JAMA 2004;2911238- 1245
PubMed Link to Article
US Department of Health and Human Services, Reducing Tobacco Use: A Report of the Surgeon General.  Atlanta, Ga Office on Smoking and Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention2000;
US Department of Health and Human Services, Women and Smoking: A Report of the Surgeon General.  Atlanta, Ga Office on Smoking and Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention2001;
US Department of Health and Human Services, Physical Activity and Health: A Report of the Surgeon General.  Atlanta, Ga National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention1996;
US Department of Health and Human Services, National Cancer Institute’s 5-A-Day Program. Available at: http://www.5aday.gov. Accessed June 8, 2004
Chobanian  AVBakris  GLBlack  HR  et al.  The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA 2003;2892560- 2572
PubMed Link to Article
Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults, Executive summary of the Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). JAMA 2001;2852486- 2497
PubMed Link to Article
National Heart, Lung, and Blood Institute, National Institutes of Health, Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults: The Evidence Report.  Bethesda, Md National Heart, Lung, and Blood Institute1998;
Yusuf  HRGiles  WHCroft  JBAnda  RFCasper  ML Impact of multiple risk factor profiles on determining cardiovascular disease risk. Prev Med 1998;271- 9
PubMed Link to Article
Stamler  JDyer  ARShekelle  RBNeaton  JStamler  R Relationship of baseline major risk factors to coronary and all-cause mortality, and to longevity: findings from long-term follow-up of Chicago cohorts. Cardiology 1993;82191- 222
PubMed Link to Article
Stamler  JStamler  RNeaton  JD  et al.  Low risk-factor profile and long-term cardiovascular and noncardiovascular mortality and life expectancy. JAMA 1999;2822012- 2018
PubMed Link to Article
Wilson  PWD’Agostino  RBLevy  D  et al.  Prediction of coronary heart disease using risk factor categories. Circulation 1998;971837- 1847
PubMed Link to Article
Stampfer  MJHu  FBManson  JERimm  EBWillet  WC Primary prevention of coronary heart disease in women through diet and lifestyle. N Engl J Med 2000;34316- 22
PubMed Link to Article
Hu  FBManson  JEStampfer  MJ  et al.  Diet, lifestyle and the risk of type 2 diabetes mellitus in women. N Engl J Med 2001;345790- 797
PubMed Link to Article
Nelson  DEHoltzman  DWaller  M  et al.  Objectives and design of the Behavioral Risk Factor Surveillance System.  Paper presented at: Section on Survey Research Methods, American Statistical Association National Meeting August 10, 1998 Dallas, Tex
National Center for Chronic Disease Prevention and Health Promotion Centers for Disease Control and Prevention, Behavioral Risk Factor Surveillance System: technical information and data. Available at: http://www.cdc.gov/brfss/technical_infodata/index.htm. Accessed June 8, 2004
Rothman  KJ Modern Epidemiology.  Boston, Mass Little Brown & Co Inc1986;
Shah  BVBarnwell  BGBieler  GS SUDAAN Users Manual: Release 7.5.  Research Triangle Park, NC Research Triangle Institute1997;
Ford  ESFord  MAWill  JCGaluska  DABallew  C Achieving a healthy lifestyle among United States adults: a long way to go. Ethn Dis 2001;11224- 231
PubMed
Berrigan  DDodd  KTroiano  RPKrebs-Smith  SMBarbush  RB Patterns of health behavior in US adults. Prev Med 2003;36615- 623
PubMed Link to Article
Istvan  JMatarazzo  JD Tobacco, alcohol, and caffeine use: a review of their interrelationships. Psychol Bull 1948;95301- 326
Link to Article
Patterson  REHaines  PSPopkin  BM Health lifestyle patterns of US adults. Prev Med 1994;23453- 460
PubMed Link to Article
Sobal  JRevicki  DDe Forge  BR Patterns of interrelationships among health-promotion behaviors. Am J Prev Med 1992;8351- 359
PubMed
Ma  JBets  NMHampl  JS Clustering of lifestyle behaviors: the relationship between cigarette smoking, alcohol consumption, and dietary intake. Am J Health Promot 2000;15107- 117
PubMed Link to Article
Johnson  MFNichols  JFSallis  JFCalfas  KJHovell  MF Interrelationships between physical activity and other health behaviors among university women and men. Prev Med 1998;27536- 544
PubMed Link to Article
Nelson  DEHoltzman  DBolen  JStanwyck  CAMack  KA Reliability and validity of measures from the Behavioral Risk Factor Surveillance System (BRFSS). Soz Praventivmed 2001;46 ((suppl 1)) S3- S42
PubMed Link to Article
Serdula  MCoates  RByers  T  et al.  Evaluation of a brief telephone questionnaire to estimate fruit and vegetable consumption in diverse study populations. Epidemiology 1993;4455- 463
PubMed Link to Article
Mariolis  P Response rates and accuracy of the BRFSS data.  Paper presented at: Nineteenth Annual BRFSS Conference March 13, 2002 Atlanta, Ga
Curtin  RPresser  SSinger  E The effects of response rate changes on the Index of Consumer Sentiment. Public Opin Q 2000;64413- 428
PubMed Link to Article
Keeter  SMiller  CKohut  AGroves  RMPresser  S Consequences of reducing nonresponse in a national telephone survey. Public Opin Q 2000;64125- 148
Link to Article
Labarthe  DR Epidemiology and Prevention of Cardiovascular Diseases.  Gaithersburg, Md Aspen Publishers Inc1998;
Rose  G The Strategy of Preventive Medicine.  New York, NY Oxford University Press Inc1992;

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