Socio-demographic association of multiple modifiable lifestyle risk factors and their clustering in a representative urban population of adults: a cross-sectional study in Hangzhou, China

International Journal of Behavioral Nutrition and Physical Activity

Liming Li²  Shengfeng Wang²  Ting Gong²  Yanjun Ren¹  Qingmin Liu¹  Jun Lv² 

[1] Division for Chronic and Non-Communicable Disease Control and Prevention, Hangzhou Center for Disease Control and Prevention, Mingshi Road, Jianqiao Town, Hangzhou 310021, China;Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, 38 Xueyuan Road, Beijing 100191, China

关键词: diet;    physical activity;    smoking;    cluster analysis;    cross-sectional studies;    socio-economic factors;    lifestyle;   

Others  :  1154094
DOI  :  10.1186/1479-5868-8-40

 received in 2010-12-20, accepted in 2011-05-15,  发布年份 2011

【 摘 要 】

Background

To plan long-term prevention strategies and develop tailored intervention activities, it is important to understand the socio-demographic characteristics of the subpopulations at high risk of developing chronic diseases. This study aimed to examine the socio-demographic characteristics associated with multiple lifestyle risk factors and their clustering.

Methods

We conducted a simple random sampling survey to assess lifestyle risk factors in three districts of Hangzhou, China between 2008 and 2009. A two-step cluster analysis was used to identify different health-related lifestyle clusters based on tobacco use, physical activity, fruit and vegetable consumption, and out-of-home eating. Multinomial logistic regression was used to model the association between socio-demographic factors and lifestyle clusters.

Results

A total of 2016 eligible people (977 men and 1039 women, ages 18-64 years) completed the survey. Three distinct clusters were identified from the cluster analysis: an unhealthy (UH) group (25.7%), moderately healthy (MH) group (31.1%), and healthy (H) group (43.1%). UH group was characterised by a high prevalence of current daily smoking, a moderate or low level of PA, low FV consumption with regard to the frequency or servings, and more occurrences of eating out. H group was characterised by no current daily smoking, a moderate level of PA, high FV consumption, and the fewest times of eating out. MH group was characterised by no current daily smoking, a low or high level of PA, and an intermediate level of FV consumption and frequency of eating out. Men were more likely than women to have unhealthy lifestyles. Adults aged 50-64 years were more likely to live healthy lifestyles. Adults aged 40-49 years were more likely to be in the UH group. Adults whose highest level of education was junior high school or below were more likely to be in the UH group. Adults with a high asset index were more likely to be in the MH group.

Conclusions

This study suggests that Chinese urban people who are middle-aged, men, and less educated are most likely to be part of the cluster with a high-risk profile. Those groups will contribute the most to the future burden of major chronic disease and should be targeted for early prevention programs.

【 授权许可】

   
2011 Lv et al; licensee BioMed Central Ltd.

【 参考文献 】

• [1]World Health Organization: The world health report 2002. Reducing risks, promoting healthy life. Geneva: WHO; 2002.
• [2]World Health Organization: Global strategy on diet, physical activity and health. Geneva: WHO; 2004.
• [3]World Health Organization: Preventing chronic diseases: a vital investment. Geneva: WHO; 2005.
• [4]Rose G, Khaw K, Marmot M: Rose's strategy of preventive medicine. New York: Oxford University Press; 2008.
• [5]Gu D, Kelly TN, Wu X, Chen J, Samet JM, Huang JF, Zhu M, Chen JC, Chen CS, Duan X, Klag MJ, He J: Mortality Attributable to Smoking in China. N Engl J Med 2009, 360(2):150-159.
• [6]Muntner P, Gu D, Wildman RP, Chen J, Qan W, Whelton PK, He J: Prevalence of physical activity among Chinese adults: results from the International Collaborative Study of Cardiovascular Disease in Asia. Am J Public Health 2005, 95(9):1631-1636.
• [7]Zhai FY, He YN, Ma GS, Li YP, Wang ZH, Hu YS, Zhao LY, Cui ZH, Li Y, Yang XG: [Study on the current status and trend of food consumption among Chinese population]. Zhonghua Liu Xing Bing Xue Za Zhi 2005, 26(7):485-488.
• [8]Bes-Rastrollo M, Basterra-Gortari FJ, Sanchez-Villegas A, Marti A, Martinez JA, Martinez-Gonzalez MA: A prospective study of eating away-from-home meals and weight gain in a Mediterranean population: the SUN (Seguimiento Universidad de Navarra) cohort. Public Health Nutr 2010, 13(9):1356-1363.
• [9]Guthrie JF, Lin BH, Frazao E: Role of food prepared away from home in the American diet, 1977-78 versus 1994-96: changes and consequences. J Nutr Educ Behav 2002, 34(3):140-150.
• [10]Orfanos P, Naska A, Trichopoulos D, Slimani N, Ferrari P, van Bakel M, Deharveng G, Overvad K, Tjønneland A, Halkjær J, Santucci De Magistris M, Tumino R, Pala V, Sacerdote C, Masala G, Skeie G, Engeset D, Lund E, Jakszyn P, Barricarte A, Chirlaque MD, Martinez-Garcia C, Amiano P, Quir SJR, Bingham S, Welch A, Spencer EA, Key TJ, Rohrmann S, Linseisen J, Ray J, Boeing H, Peeters PH, Bueno-de-Mesquita HB, Ocke M, Johansson I, Johansson G, Berglund G, Manjer J, Boutron-Ruault MC, Touvier M, Clavel-Chapelon F, Trichopoulou A: Eating out of home and its correlates in 10 European countries. The European Prospective Investigation into Cancer and Nutrition (EPIC) study. Public Health Nutrition 2007, 10(12):1515-1525.
• [11]Ma GS, Kong LZ: Report on National Survey of Nutrition and Health Status in 2002: behavior and lifestyle. Volume 9. Beijing: People's Health Press; 2006.
• [12]Naska A, Orfanos P, Trichopoulou A, May AM, Overvad K, Jakobsen MU, Tjonneland A, Halkjaer J, Fagherazzi G, Clavel-Chapelon F, Boutron-Ruault MC, Rohrmann S, Hermann S, Steffen A, Haubrock J, Oikonomou E, Dilis V, Katsoulis M, Sacerdote C, Sieri S, Masala G, Tumino R, Mattiello A, Bueno-de-Mesquita HB, Skeie G, Engeset D, Barricarte A, Rodriguez L, Dorronsoro M, Sanchez MJ, Chirlaque MD, Agudo A, Manjer J, Wirfalt E, Hellstrom V, Shungin D, Khaw KT, Wareham NJ, Spencer EA, Freisling H, Slimani N, Vergnaud AC, Mouw T, Romaguera D, Odysseos A, Peeters PH: Eating out, weight and weight gain. A cross-sectional and prospective analysis in the context of the EPIC-PANACEA study. Int J Obes (Lond) 2010.
• [13]Duffey KJ, Gordon-Larsen P, Jacobs DJ, Williams OD, Popkin BM: Differential associations of fast food and restaurant food consumption with 3-y change in body mass index: the Coronary Artery Risk Development in Young Adults Study. Am J Clin Nutr 2007, 85(1):201-208.
• [14]Ayala GX, Rogers M, Arredondo EM, Campbell NR, Baquero B, Duerksen SC, Elder JP: Away-from-home food intake and risk for obesity: examining the influence of context. Obesity (Silver Spring) 2008, 16(5):1002-1008.
• [15]Vandevijvere S, Lachat C, Kolsteren P, Van Oyen H: Eating out of home in Belgium: current situation and policy implications. Br J Nutr 2009, 102(6):921-928.
• [16]Orfanos P, Naska A, Trichopoulou A, Grioni S, Boer JM, van Bakel MM, Ericson U, Rohrmann S, Boeing H, Rodriguez L, Ardanaz E, Sacerdote C, Giurdanella MC, Niekerk EM, Peeters PH, Manjer J, van Guelpen B, Deharveng G, Skeie G, Engeset D, Halkjaer J, Jensen AM, McTaggart A, Crowe F, Stratigakou V, Oikonomou E, Touvier M, Niravong M, Riboli E, Bingham S, Slimani N: Eating out of home: energy, macro- and micronutrient intakes in 10 European countries. The European Prospective Investigation into Cancer and Nutrition. Eur J Clin Nutr 2009, 63(Suppl 4):S239-S262.
• [17]Poortinga W: The prevalence and clustering of four major lifestyle risk factors in an English adult population. Prev Med 2007, 44(2):124-128.
• [18]Yusuf S, Hawken S, Ounpuu S, Dans T, Avezum A, Lanas F, McQueen M, Budaj A, Pais P, Varigos J, Lisheng L: Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet 2004, 364(9438):937-952.
• [19]Stampfer MJ, Hu FB, Manson JE, Rimm EB, Willett WC: Primary prevention of coronary heart disease in women through diet and lifestyle. N Engl J Med 2000, 343(1):16-22.
• [20]Chou KL: The prevalence and clustering of four major lifestyle risk factors in Hong Kong Chinese older adults. J Aging Health 2008, 20(7):788-803.
• [21]Liang W, Shediac-Rizkallah MC, Celentano DD, Rohde C: A population-based study of age and gender differences in patterns of health-related behaviors. Am J Prev Med 1999, 17(1):8-17.
• [22]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):18-24.
• [23]Hausdorf K, Eakin E, Whiteman D, Rogers C, Aitken J, Newman B: Prevalence and correlates of multiple cancer risk behaviors in an Australian population-based survey: results from the Queensland Cancer Risk Study. Cancer Causes Control 2008, 19(10):1339-1347.
• [24]Alamian A, Paradis G: Clustering of chronic disease behavioral risk factors in Canadian children and adolescents. Prev Med 2009, 48(5):493-499.
• [25]Lawder R, Harding O, Stockton D, Fischbacher C, Brewster DH, Chalmers J, Finlayson A, Conway DI: Is the Scottish population living dangerously? Prevalence of multiple risk factors: the Scottish Health Survey 2003. BMC Public Health 2010, 10:330. BioMed Central Full Text
• [26]Chiolero A, Wietlisbach V, Ruffieux C, Paccaud F, Cornuz J: Clustering of risk behaviors with cigarette consumption: A population-based survey. Prev Med 2006, 42(5):348-353.
• [27]Schneider S, Huy C, Schuessler M, Diehl K, Schwarz S: Optimising lifestyle interventions: identification of health behaviour patterns by cluster analysis in a German 50+ survey. Eur J Public Health 2009, 19(3):271-277.
• [28]Dodd LJ, Al-Nakeeb Y, Nevill A, Forshaw MJ: Lifestyle risk factors of students: A cluster analytical approach. Prev Med 2010, 51(1):73-77.
• [29]French S, Rosenberg M, Knuiman M: The clustering of health risk behaviours in a Western Australian adult population. Health Promot J Austr 2008, 19(3):203-209.
• [30]Duffany KOC, Finegood DT, Matthews D, McKee M, Narayan KMV, Puska P, Siegel K, Stevens D, Wong F, Woodward M, Yach D, on behalf of the CIH investigators and expert panel: Community Interventions for Health (CIH): A novel approach to tackling the worldwide epidemic of chronic diseases. CVD Prev Control 2011, (6):47-56.
• [31]Office Information Processing Center, CPC Hangzhou Committee And Hangzhou Municipal Government: About Hangzhou. [http://eng.hangzhou.gov.cn/main/zpd/English/AboutHangZhou/index.shtml] webcite 2010.
• [32]Zhao Z: Registered households and micro-social structure in China: residential patterns in three settlements in Beijing area. J Fam Hist 2001, 26(1):39-65.
• [33]World Health Organization: The WHO STEPS surveillance manual - WHO STEPwise approach to chronic disease risk-factor surveillance. [http://www.who.int/chp/steps/manual/en/index.html] webcite 2010.
• [34]Lu J, Liu QM, Ren YJ, Wang WF, Gong T, Li LM: [Application of a simple random sampling method on surveys at the community level.]. Zhonghua Liu Xing Bing Xue Za Zhi 2010, 31(4):421-423.
• [35]World Health Organization: WHO STEPS Surveillance Manual. Geneva: World Health Organization; 2008.
• [36]IPAQ core group: International Physical Activity Questionnaire. [http://www.ipaq.ki.se/ipaq.htm] webcite 2002. (accessed Apr 2011)
• [37]Craig CL, Marshall AL, Sjostrom M, Bauman AE, Booth ML, Ainsworth BE, Pratt M, Ekelund U, Yngve A, Sallis JF, Oja P: International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc 2003, 35(8):1381-1395.
• [38]Centers for Disease Control and Prevention: Global Adult Tobacco Survey. [http://www.cdc.gov/tobacco/global/gats/] webcite 2007. (accessed Apr 2011)
• [39]Filmer D, Pritchett LH: Estimating wealth effects without expenditure data-or tears: an application to educational enrollments in states of India. Demography 2001, 38(1):115-132.
• [40]Morris SS, Carletto C, Hoddinott J, Christiaensen LJ: Validity of rapid estimates of household wealth and income for health surveys in rural Africa. J Epidemiol Community Health 2000, 54(5):381-387.
• [41]Sahn DE, Stifel D: Exploring alternative measures of welfare in the absence of expenditure data. Review of Income and Wealth 2003, 49(4):463-489.
• [42]StataCorp: Stata multivariate statistics reference manual: release 10. College Station, TX: StataCorp LP; 2007:300-325.
• [43]Chinese Nutrition Society: The dietary guidelines for Chinese residents. Beijing: Tibert People Publishing House; 2008.
• [44]IPAQ Core Group: Guidelines for the data processing and analysis of the International Physical Activity Questionnaire - short and long forms. [http://www.ipaq.ki.se/scoring.pdf] webcite (accessed Sep 2010)
• [45]Hosmer DW, Lemeshow S (Eds): The multinomial logistic regression model In Applied logistic regression (Second Edition). New York: Wiley-Interscience; 2000:260-287.
• [46]StataCorp: Stata base reference manual volume 2 I-P: release 10. College Station, TX: StataCorp LP; 2007:315-326.
• [47]StataCorp: Stata Statistical Software: Release 10. College Station, TX: StataCorp LP; 2007.
• [48]SPSS Inc: PASW Statistics: Release 17.0.2. New York: SPSS Inc; 2009.
• [49]Yang GH, Hu AG: Tobacco control and China's future: the joint evaluation of the tobacco use and tobacco control in China conducted by international and national experts. Beijing: The Economic Daily Press; 2011:109.
• [50]Adabonyan I, Loustalot F, Kruger J, Carlson SA, Fulton JE: Prevalence of highly active adults--Behavioral risk factor surveillance system, 2007. Prev Med 2010, 51(2):139-143.
• [51]Varo JJ, Martinez-Gonzalez MA, De Irala-Estevez J, Kearney J, Gibney M, Martinez JA: Distribution and determinants of sedentary lifestyles in the European Union. Int J Epidemiol 2003, 32(1):138-146.
• [52]Martínez-González M, Varo J, Santos J, De Irala J, Gibney M, Kearney J, Martínez J: Prevalence of physical activity during leisure time in the European Union. Med Sci Sports Exerc 2001, 33(7):1142-1146.
• [53]Center for Health Statistics and Information MOH: An analysis report of National Health Services Survey in China, 2008. Beijing: Peking Union Medical College Press; 2009.
• [54]Fong CW, Bhalla V, Heng D, Chua AV, Chan ML, Chew SK: Educational inequalities associated with health-related behaviours in the adult population of Singapore. Singapore Med J 2007, 48(12):1091-1099.
• [55]Schatzer M, Rust P, Elmadfa I: Fruit and vegetable intake in Austrian adults: intake frequency, serving sizes, reasons for and barriers to consumption, and potential for increasing consumption. Public Health Nutr 2010, 13(4):480-487.
• [56]Li FX, Robson PJ, Chen Y, Qiu Z, Lo SG, Bryant HE: Prevalence, trend, and sociodemographic association of five modifiable lifestyle risk factors for cancer in Alberta and Canada. Cancer Causes Control 2009, 20(3):395-407.
• [57]Fornari C, Donfrancesco C, Riva MA, Palmieri L, Panico S, Vanuzzo D, Ferrario MM, Pilotto L, Giampaoli S, Cesana G: Social status and cardiovascular disease: a Mediterranean case. Results from the Italian Progetto CUORE cohort study. Bmc Public Health 2010, 10(1):574. BioMed Central Full Text
• [58]Rakowski W, Assaf AR, Lefebvre RC, Lasater TM, Niknian M, Carleton RA: Information-seeking about health in a community sample of adults: correlates and associations with other health-related practices. Health Educ Q 1990, 17(4):379-393.
• [59]Dean K: Self-care components of lifestyles: the importance of gender, attitudes and the social situation. Soc Sci Med 1989, 29(2):137-152.
• [60]Verbrugge LM: Gender and health: an update on hypotheses and evidence. J Health Soc Behav 1985, 26(3):156-182.
• [61]Hermalin AI, Lowry D: The age prevalence of smoking among Chinese women: a case of arrested diffusion? [http://www.psc.isr.umich.edu/pubs/pdf/rr10-718.pdf] webcite 2011.
• [62]Whitt-Glover MC, Taylor WC, Heath GW, Macera CA: Self-reported physical activity among blacks: estimates from national surveys. Am J Prev Med 2007, 33(5):412-417.
• [63]Ding D, Hovell MF, Ji M, Hofstetter CR, Zheng P, Fu H, Hughes SC: Employment and social "determinants" of smoking in urbanizing China: a representative survey. Nicotine Tob Res 2009, 11(7):779-784.
• [64]Cochrane J, Chen H, Conigrave KM, Hao W: Alcohol use in China. Alcohol Alcoholism 2003, 38(6):537-542.
• [65]Falkingham J, Namazie C: Identifying the poor: a critical review of alternative approaches. [http://www.sarpn.org.za/documents/d0000133/P127-Falkingham.pdf] webcite 2010.
• [66]Prakongsai P: An application of asset index for measuring household living standards in Thailand. [http://www.nesdb.go.th/econSocial/macro/TNCE/Download/5/Phusit.pdf] webcite 2010.
• [67]Yin XJ, Shi XM, Si X, Gao X, Zhai Y: Assessment of capacity for chronic noncommunicable diseases prevention and control of the Center for Disease Control and Prevention Organizations in China. Chin J Epidemiol 2010, 31(10):1125-1129.
• [68]Nigg CR, Allegrante JP, Ory M: Theory-comparison and multiple-behavior research: common themes advancing health behavior research. Health Educ Res 2002, 17(5):670-679.
• [69]Atkins D, Clancy C: Multiple risk factors interventions. Are we up to the challenge? Am J Prev Med 2004, 27(2 Suppl):102-103.
• [70]Edited by Szklo M, Nieto FJ (Eds): Basic study designs in analytical epidemiology In Epidemiology - beyond the basics. Sudbury: Jones and Bartlett Publishers, Inc; 2007:3-42.
• [71]Gorber SC, Schofield-Hurwitz S, Hardt J, Levasseur G, Tremblay M: The accuracy of self-reported smoking: a systematic review of the relationship between self-reported and cotinine-assessed smoking status. Nicotine Tob Res 2009, 11(1):12-24.
• [72]Ainsworth BE, Macera CA, Jones DA, Reis JP, Addy CL, Bowles HR, Kohl HR: Comparison of the 2001 BRFSS and the IPAQ Physical Activity Questionnaires. Med Sci Sports Exerc 2006, 38(9):1584-1592.
• [73]Johnson-Kozlow M, Sallis JF, Gilpin EA, Rock CL, Pierce JP: Comparative validation of the IPAQ and the 7-Day PAR among women diagnosed with breast cancer. Int J Behav Nutr Phys Act 2006, 3:7. BioMed Central Full Text
• [74]Vereecken C, Covents M, Maes L: Comparison of a food frequency questionnaire with an online dietary assessment tool for assessing preschool children's dietary intake. J Hum Nutr Diet 2010, 23(5):502-510.
• [75]Troiano RP, Berrigan D, Dodd KW, Masse LC, Tilert T, McDowell M: Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc 2008, 40(1):181-188.
• [76]Hjartaker A, Andersen LF, Lund E: Comparison of diet measures from a food-frequency questionnaire with measures from repeated 24-hour dietary recalls. The Norwegian Women and Cancer Study. Public Health Nutr 2007, 10(10):1094-1103.