Journal of Preventive Medicine and Public Health January 2010, Vol. 43, No. 1, 7383 doi: 10.3961/jpmph.2010.43.1.73 High Risk Groups in Health Behavior Defined by Clustering of Smoking, Alcohol, and Exercise Habits: National Heath and Nutrition Examination Survey Kiwon Kang, Joohon Sung, Changyup Kim Department of Preventive Medicine, School of Public Health, Seoul National University Objectives: We investigated the clustering of selected lifestyle factors (cigarette smoking, heavy alcohol consumption, lack of physical exercise) and identified the population characteristics associated with increasing lifestyle risks. Methods: Data on lifestyle risk factors, sociodemographic characteristics, and history of chronic diseases were obtained from 7,694 individuals 20 years of age who participated in the 2005 Korea National Health and Nutrition Examination Survey (KNHANES). Clustering of lifestyle risks involved the observed prevalence of multiple risks and those expected from marginal exposure prevalence of the three selected risk factors. Prevalence odds ratio was adopted as a measurement of clustering. Multiple correspondence analysis, Kendall tau correlation, ManWhitney analysis, and ordinal logistic regression analysis were conducted to identify variables increasing lifestyle risks. Results: In both men and women, increased lifestyle risks were associated with clustering of: (1) cigarette smoking and excessive alcohol consumption, and (2) smoking, excessive alcohol consumption, and lack of physical exercise. Patterns of clustering for physical exercise were different from those for cigarette smoking and alcohol consumption. The increased unhealthy clustering was found among men 2064 years of age with mild or moderate stress, and among women 3549 years of age who were nevermarried, with mild stress, and increased body mass index (>30 kg/m 2 ). Conclusions: Addressing a lack of physical exercise considering individual characteristics including gender, age, employment activity, and stress levels should be a focus of health promotion efforts. Key words: Lifestyle, Risk factors, Cluster analysis J Prev Med Public Health 2010;43(1):7383
Table 1. Characteristics of the study population Men Women Men Women n % n % n % n % Number of subject Age (yr) 20 34 35 49 50 64 65 Education Elementary High school University Occupation Professionals Clerks Service workers Farmers and Fishers Craft and trade workers Armed forces Students Housewives Unemployed Income (quartile) 1st (lowest) 2nd 3rd 4th (highest) Marital status Married Never married Divorced, widowed, separated Body mass index (kg/m 2 ) <23 23 24 25 29 30 Area of residence Rural Urban 3,455 932 1,280 815 428 490 1,635 1,330 450 393 499 260 1,082 22 130 0 618 890 707 741 890 2,533 692 227 820 612 735 70 714 2,741 27.0 37.0 23.6 12.4 14.2 47.3 38.5 13.0 11.4 14.4 7.5 31.3 0.6 3.8 0.0 17.9 [missing rate : 6.5%]0 31.4 25.0 26.2 17.4 73.3 20.0 6.6 [missing rate : 35.3%] 36.7 27.4 32.9 3.1 20.7 79.3 4,239 1,170 1,446 934 689 1,200 1,937 1,102 293 330 679 239 509 0 118 1,501 569 425 238 111 88 2,781 619 836 1441 709 811 109 845 3,394 27.6 34.1 22.0 16.3 28.3 45.7 26.0 6.9 7.8 16.0 5.6 12.0 0.0 2.8 35.4 13.4 [missing rate : 80.0%] 49.3 27.6 12.9 10.2 65.6 14.6 19.7 [missing rate : 27.6%] 47.0 23.1 26.4 3.6 19.9 80.1 Perceived stress Severe Moderate Mild Chronic disease Hypertension Diabetes Dyslipidemia Hypertension duration (yr) < 5 5 9 10 Diabetes duration (yr) < 5 5 9 10 Dyslipidemia duration (yr) < 5 5 9 10 Cigarette smoking Never smokers Exsmokers Current smokers Alcohol consumption None or minimal Moderate Excessive Physical exercise Health enhancing Minimal Inactive 245 975 2,235 829 327 1,247 [missing rate : 39.4%] 337 67.1 85 16.9 80 15.9 [missing rate : 27.2%] 142 42 54 [missing rate : 88.9%] 107 77.5 19 13.8 12 8.7 543 1,088 1,824 1,106 957 1,392 908 460 2,087 7.1 28.2 64.7 24.0 9.5 56.1 59.7 17.6 22.7 15.7 31.5 52.8 32.0 27.7 40.3 26.3 13.3 60.4 273 1,226 2,740 883 282 1,084 [missing rate : 26.5%] 408 62.9 109 16.8 132 20.3 [missing rate : 27.0%] 112 46 48 [missing rate : 88.6%] 113 79.6 21 14.8 8 5.6 3,811 183 245 2,929 997 313 765 544 2,930 6.4 28.9 64.6 20.8 6.7 35.5 54.4 22.3 23.3 89.9 4.3 5.8 69.1 23.5 7.4 18.0 12.8 69.1
Table 2. Clustering of cigarette smoking, excessive alcohol consumption, and lack of physical exercise Number of risk factors Cigarette smoking Excessive alcohol consumption Lack of physical exercise Observed frequency (O) (%) Men Expected frequency (E) (%) O/E Observed frequency (O) (%) Women Expected frequency (E) (%) O/E 3 2 1 0 15.07 10.53 16.90 7.75 10.27 6.91 20.66 11.86 12.85 8.42 19.03 11.48 12.48 7.53 17.01 11.15 1.17 1.25 0.88 0.67 0.82 0.91 1.21 1.06 1.08 0.61 3.01 3.44 1.06 2.24 61.57 26.96 0.29 0.13 3.71 4.81 1.65 2.15 60.27 26.95 3.65 4.62 0.81 0.71 0.63 1.04 1.02 Table 3. Observed of expected prevalence odds ratio for each combination of cigarette smoking, excessive alcohol consumption, and lack of physical exercise S() and A() among E() S() and A() among E() S() and E() among A() S() and E() among A() A() and E() among S() A() and E() among S() OR: odds ratio, CI confidence interval S: Cigarette smoking A: Excessive alcohol consumption E: Lack of physical exercise Men OR (95%CI) 2.38 (1.972.87) 1.76 (1.412.20) 1.28 (1.021.60) 0.94 (0.791.13) 0.87 (0.721.05) 0.64 (0.521.08) Women OR (95%CI) 6.93 (3.9212.07) 6.42 (4.309.46)0 1.15 (0.652.08)0 1.25 (0.871.80)0 0.62 (0.331.18)0 0.67 (0.510.89)0
Figure 1. Relationship between lifestyle risk factor and demographic, socioeconomic, and healthstatus. * Age_1: age 2034 years, Age_2: age 3549 years, Age_3: age 5064 years, Age_4: age 65 years, Risk_0: number of risk factors 0, Risk_1: number of risk factors 1, Risk_2: number of risk factors 2, Risk_3: number of risk factors 3. Smok_1: never smokers, Smok_2: exsmokers, Smok_3: current smokers, Alcol_1: none or minimal alcohol consumption, Alcol_2: moderate alcohol consumption, Alcol_3: excessive alcohol consumption, Exer_1: health enhancing physical exercise, Exer_2: minimal physical exercise, Exer_3: inactive physical exercise, Job_1: professionals, Job_2: clerks, Job_3: service workers, Job_4: farmers and fishers, Job_5: craft workers Job_6: armed forced, Job_7: students, Job_8: housewives, Job_9: unemployed, Income_1: 1st quartile(lowest) income, Income_2: 2nd quartile income, Income_3: 3rd quartile income, Income_4: 4th quartile(hightest) income, Mar_1: married, Mar_2: never married, Mar_3: divorced, widowed, separated, bmi_1: bmi <23 kg/m 2, bmi_2: bmi 23 ~<25 kg/m 2, bmi_3: bmi 25 ~<30 kg/m 2, bmi_4: 30 kg/m 2, Pla_0: urban, Pla_1: rural, Str_1: mild stress, Str_2: moderate stress, Str_3: severe stress. Htn_0: hypertensionno, Htn_1: hypertensionyes, m_0: diabetesno, Dm_1: diabetesyes, Lid_0: dyslipidemiano, Lid_1: dyslipidemiayes, Htn_age_1: hypertension duration <5 years, Htn_age_2: hypertension duration 59 years, Htn_age_3: hypertension duration 10 years, Dm_1: diabetes duration <5 years, Dm_2: diabetes duration 59 years, Dm_3: diabetes 10 years, Lid_age_1: dyslipidemia duration <5 years, Lid_age_2: dyslipidemia duration 59 years, Lid_age_3: dyslipidemia duration 10 years Invisible label variable (contribution score is low) : Edu_2, Lid_0, Dm_0, Pla_0, Htn_age_1, Lid_age_1
Table 4. Association between demographic and health status characteristics, and having multiple health risks Age (yr)* (2034, 3549, 5064, 65) Education* ( elementary, high school, university) Income(quartile)* (1st(lowest), 2nd, 3rd, 4th(highest)) Cigarette smoking (never smokers. exsmokers, current smokers) Alcohol consumption* (none or minimal, moderate, excessive) Lack of physical exercise* (health enhancing, minimal, inactive) Body mass index(kg/m2) (<23, 2324, 2529, 30.0) Perceived stress* (mild, moderate, severe) Diabetes (no, yes) Hypertension (no, yes) Dyslipidemia (no, yes) Diabetes duration (years)* (<5. 59, 10) Hypertension duration (years)* (<5. 59, 10) Dyslipidemia duration (years)* (<5. 59, 10) * Kendall s Tau correlation, MannWhitney U. Men Women Coefficient pvalue Coefficient pvalue 0.12 0.03 0.02 0.60 0.50 0.42 0.06 0.12 0.01 0.04 0.04 0.36 0.59 0.07 0.27 0.27 0.45 0.48 Table 5. Odds ratios (OR) and 95% confidence interval (CI) of predictors of the number of lifestyle risk factors Age (yr) 65 50 64 35 49 20 34 Education University High school Elementary Occupation Nonmanual Manual Unemployed, others Income (quartile) 4th (highest) 3rd 2nd 1st (lowest) Marital status Married Never married Divorced, widowed, separated Area of residence Rural Urban Perceived stress Severe Moderate Mild Body mass index (kg/m 2 ) < 23 23 24 25 29 30 0.00 0.03 0.22 0.32 0.20 0.76 0.00 0.04 0.01 0.01 0.02 Men OR (95% CI) 0.95 0.01 0.94 0.04 0.38 0.65 0.15 Women OR (95% CI) 1.84 (1.352.53) 01.59 (0.713.53) 3.13 (2.214.44) 02.84 (1.097.49) 3.11 (2.064.70) 2.90 (0.6911.69) 1.16 (0.921.47) 02.69 (0.938.88) 1.32 (0.931.88) 3.41 (0.9613.46) 0.99 (0.781.26) 01.06 (0.472.40) 1.15 (0.851.55) 01.52 (0.743.20) 1.11 (0.861.41) 00.50 (0.121.89) 1.03 (0.791.33) 00.91 (0.322.88) 1.15 (0.821.61) 01.01 (0.363.20) 1.42 (0.932.15) 3.82 (1.0214.53) 1.14 (0.781.66) 02.11 (0.865.75) 0.96 (0.771.20) 01.60 (0.773.64) 1.58 (1.301.93) 01.71 (0.973.03) 2.01 (1.412.87) 02.54 (1.065.70) 0.88 (0.711.11) 01.17 (0.572.34) 0.81 (0.651.01) 01.12 (0.562.22) 0.84 (0.491.44) 4.55 (1.6112.18)
1. World Health Organisation. The World Health Report 2002 Reducing Risks. Promoting Healthy Life. Geneva: WHO; 2002. 2. Lee JJ, Yang JH, Hwang TY. Clustering of lifestyle risk factors in urban poor and rural adults. J Korean Soc Health Educ Promot 2005; 22(4): 167177. (Korean) 3. Institute of Medicine. Health and Behavior: The Interplay of Biological, Behavioral and Social Influences. Washingron DC: National Academy Press.; 2001. 4. Schuit AJ, van Loon AJ, Tijhuis M, Ocke M. Clustering of lifestyle risk factors in a general adult population. Prev Med 2002; 35(3): 219224. 5. Berrigan D, Dodd K, Troiano RP, KrebsSmith SM, Barbash RB. Patterns of health behavior in U.S. adults. Prev Med 2003; 36(5): 615623. 6. Slattery ML, Potter JD. Physical activity and colon cancer: Confounding or interaction?. Med Sci Sports Exerc 2002; 34(6): 913919. 7. Yusuf S, Hawken S, Ounpuu S, Dans T, Avezum A, Lanas F, et al. Effect of potentially modifible risk associated with myocardial infarction in 52 countries(the INTERHEART study): Case control study. Lancet 2004; 364(9438): 937 952. 8. American Heart Association. Heart and Stroke Statistical Update. Dallas, Texas: American Heart Association; 1997. 9. Johansson SE, Sundquist J. Change in lifestyle factors and their influence on health status and allcause mortality. Int J Epidemiol 1999; 28(6): 10731080. 10. Prochaska JO. Multiple health behavior research represents the future of preventive medicine. Prev Med 2008; 46(3): 281285. 11. Prochaska JJ, Velicer WF, Nigg CR, Prochaska JO. Methods of quantifying change in multiple risk factor interventions. Prev Med 2008; 46(3): 260265. 12. Poortinga W. Prevalence and clustering of four major lifestyle risk factors in an English adult population. Prev Med 2007; 44(2): 124128. 13. Chiolero A, Wietlisbach V, Ruffieux C, Paccaud F, Cornuz J. Clustering of risk behaviors with cigarrette consumption; A populationbased survey. Prev Med 2006; 42(5): 348353. 14. Mistry R, McCarthy WJ, Yancey AK, Lu Y, Patel M. Resilience and patterns of health risk behaviors in California adoloscents. Prev Med 2009; 48(3): 291297. 15. Raitakari OT, Leino M, Rakkonen K, Porkka KV, Taimela S, Rasanen L, et al. Clustering of risk habits in young adults. The Cardiovascular Risk in Young Finns Study. Am J Epidemiol 1995; 142(1): 3644. 16. Keller S, Maddock JE, Hannover W, Thyrian JR, Basler HD. Multiple health risk behaviors in German first year university students. Prev Med 2008; 46(3): 189195. 17. Emmons KM, Marcus BH, Linnan L, Rossi JS, Abrams DB. Mechanisms in multiple risk factor interventions: Smoking, physical activity, and dietary fat intake among manufacturing workers. Working Well Research Group. Prev Med 1994; 23(4): 481489. 18. Pronk NP, Anderson LH, Crain AL, Martinson BC, O Connor PJ, Sherwood NE, 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 2005; 27(2): 2533. 19. Chou KL. Prevalence and clustering of four major lifestyle risk factors in Hong Kong Chinease older adults. J Aging Health 2008; 20(7): 788803. 20. Laaksonen M, Prattala R, Karisto A. Patterns of unhealthy behaviour in Finland. Eur J Public Health 2001; 11(3): 294300. 21. Fine LJ, Philogene GS, Gramling R, Coups EJ, Sinha S. Prevalence of multiple chronic disease risk factors: 2001 national health interview survey. Am J Prev Med 2004; 27(2 Suppl): 1824. 22. Rhee D, Yun SC, Khang YH. Cooccurrence of problem behaviors in South Korean adolescents: Findings from Korea Youth Panel Survey. J Adolesc Health 2007; 40(2): 195197. 23. Kang EJ. Clustering of lifestyle behaviors of Korean adults using smoking, drinking, and physical activity. Health Soc Welf Rev 2007; 27(2): 4466. (Korean) 24. Kim HC. Characteristic and Strategy of National Health and Nutrition Survey. Preventive Medicine Winter Symposium; 2007 Feb 13: Seoul, Korea. [cited 2009 Oct 28]; Available from: URL: http://web.richis.org/~prevent/ what/20070213a/ a02.pdf. (Korean) 25. Ministry of Health and Social Welfare. The Report of the 2005 Korean National Health and Nutrition Survey. Kwachon: Ministry of Health and Social Welfare; 2007.
(Korean) 26. World Health Organization Regional Office for the Western Pacific (WPRO). The Asiapacific perspective: Redefining obesity and its treatment. The International Association for the Study of Obesity (IASO) and the International Obesity Task Force (IOTF); 2000 [cited 2009 Oct 28]. Available from: URL: http://www.wpro. who.int/internet/resources. ashx/nut/redefiningobesity. pdf. 27. Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr, 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; 289(19): 25602572. 28. Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Report of the expert committee on the diagnosis and classification of diabetes mellitus. Diabetes Care 2003; 26(Suppl 1): S5S20. 29. National Cholesterol Education Program(NCEP) Expert Panel on Detection, Evaluation and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). 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) final report. Circulation 2002; 106(25): 31433421. 30. Guo XH, Zhang PH, Zeng ZC, Wang W, Li C, Shi Y et al. Combination patterns of cardiovascular risks and sequelase at different stage of hypertension in natural hypertensive population in Beijing. Clin Exp Hypertens 2009; 31(2): 142155. 31. Bezecri JP. Correspondence Analysis Handbook. New York: Marcel Dekker Inc.; 1992. 32. Bae MK, Lee WK, Song CH, Lee KM, Jung SP. The factors associated with body mass index of adults. J Korean Acad Fam Med 1999; 20(7): 906917. (Korean) 33. Unger JB. Stages of change of smoking cessation: Relationships with other health behaviors. Am J Prev Med 1996; 12(2): 134138. 34. Lee SY, Kim SW, Park JW. Health behavior patterns of Korean. Korean J Prev Med 1997; 30(1): 181194. 35. Oh JD, Lee SY, Lee GL, Kim YJ, Kim YJ, Cho BM. Health behavior and metabolic syndrome. J Korean Acad Fam Med 2009; 30(2): 120128. (Korean) 36. Lee KH, Chung WJ, Lee SM. Association of stress level with smoking. J Korean Acad Fam Med 2006; 27(1): 42 48. (Korean)