Hostname: page-component-76fb5796d-vfjqv Total loading time: 0 Render date: 2024-04-26T10:43:44.442Z Has data issue: false hasContentIssue false

Family average income and body mass index above the healthy weight range among urban and rural residents in regional Mainland China

Published online by Cambridge University Press:  02 January 2007

Fei Xu*
Affiliation:
Nanjing Municipal Center for Disease Control & Prevention, 2 Zizhulin, Nanjing 210003, People's Republic of China
Xiao-Mei Yin
Affiliation:
Nanjing Municipal Center for Disease Control & Prevention, 2 Zizhulin, Nanjing 210003, People's Republic of China
Min Zhang
Affiliation:
Nanjing Municipal Center for Disease Control & Prevention, 2 Zizhulin, Nanjing 210003, People's Republic of China
Eva Leslie
Affiliation:
Cancer Prevention Research Center, The University of Queensland, Australia
Robert Ware
Affiliation:
School of Population Health, The University of Queensland, Australia
Neville Owen
Affiliation:
Cancer Prevention Research Center, The University of Queensland, Australia
*
*Corresponding author: Email f_xufei@hotmail.com
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Objective

To explore the relationship between family average income (FAI; an index of socio-economic status) and body mass index (BMI; a widely used, inexpensive indicator of weight status) above the healthy weight range in a region of Mainland China.

Design

Population-based cross-sectional study, conducted between October 1999 and March 2000 on a sample of regular local residents aged 35 years or older who were selected by random cluster sampling.

Setting

Forty-five administrative villages selected from three urban districts and two rural counties of Nanjing municipality, Mainland China, with a regional population of 5.6 million.

Subjects

In total, 29 340 subjects participated; 67.7% from urban and 32.3% from rural areas; 49.8% male and 50.2% female. The response rate among eligible participants was 90.1%.

Results

The proportion of participants classified as overweight was 30.5%, while 7.8% were identified as obese. After adjusting for possible confounding variables (age, gender, area of residence, educational level, occupational and leisure-time physical activity, daily vegetable consumption and frequency of red meat intake), urban participants were more likely to be overweight or obese relative to their rural counterparts, more women than men were obese, and participants in the lowest FAI tertile were the least likely to be above the healthy weight range.

Conclusions

The proportion of adults with BMI above the healthy weight range was positively related to having a higher socio-economic status (indexed by FAI) in a regional Chinese population.

Type
Research Article
Copyright
Copyright © CABI Publishing 2005

References

1 World Health Organization (WHO). Obesity: Preventing and Managing the Global Epidemic. Report of a WHO Consultation on Obesity. Geneva: WHO, 1997.Google Scholar
2King, GA, Fitzhugh, EC, Bassett, DR Jr, McLaughlin, JE, Strath, SJ, Swartz, AM, et al. Relationship of leisure-time physical activity and occupational activity to the prevalence of obesity. International Journal of Obesity 2001; 25 606–12.CrossRefGoogle Scholar
3Katzmarzyk, PT. The Canadian obesity epidemic, 1985–1998.Canadian Medical Association Journal 2002; 166(8): 1039–40.Google ScholarPubMed
4McCarthy, SN, Gibney, MJ, Flynn, A. Overweight, obesity and physical activity levels in Irish adults: evidence from the North/South Ireland food consumption survey. Proceedings of the Nutrition Society 2002;61: 37.CrossRefGoogle ScholarPubMed
5Stam-Moraga, MC, Kolanowski, J, Dramaix, M, De Backer, G, Kornitzer, MD. Sociodemographic and nutritional determinants of obesity in Belgium. International Journal of Obesity and Related Metabolic Disorders. 1999; 23(Suppl. 1): 19.CrossRefGoogle ScholarPubMed
6 Australian Bureau of Statistics (ABS). Department of Health and Family Services. National Nutrition Survey: Selected Highlights 1995. Canberra: ABS & Department of Health and Family Services, 1997.Google Scholar
7Ismail, MN, Chee, SS, Nawawi, H, Yusoff, K, Lim, TO, James, WP. Obesity in Malaysia. Obesity Reviews 2002; 3: 203–8.CrossRefGoogle ScholarPubMed
8Wang, WJ, Wang, KA, Li, TL, Xiang, HD, Ma, LM, Fu, ZY, et al. Obesity epidemic patterns of Chinese adults: prevalence survey of overweight and obesity. Chinese Journal of Epidemiology 2001; 22: 129–32.Google Scholar
9Sinewy, E, Mbanya, JC, Unwin, NC, Kengne, AP, Fezeu, L, Minkoulou, EM, et al. Physical activity and its relationship with obesity, hypertension and diabetes in urban and rural Cameroon. International Journal of Obesity and Related Metabolic Disorders 2002; 26: 1009–16.Google Scholar
10Mokdad, AH, Ford, ES, Bowman, BA, Dietz, WH, Vinicor, F, Bales, VS, et al. Prevalence of obesity, diabetes, and obesity-related health risk factors, 2001. Journal of the American Medical Association 2003; 289: 76–9.CrossRefGoogle ScholarPubMed
11 Cooperative Meta-analysis Group of China Obesity Task Force. Predictive values of body mass index and waist circumference to risk factors of related diseases in Chinese adult population. Chinese Journal of Epidemiology 2002; 23: 510.Google Scholar
12 World Health Organization (WHO). Reducing Risks, Promoting Healthy Life. The World Health Report 2002. Geneva: WHO, 2002.Google Scholar
13Mokdad, AH, Bowman, BA, Ford, ES, Vinicor, F, Marks, JS, Koplan, JP. The continuing epidemics of obesity and diabetes in the United States. Journal of the American Medical Association 2001; 286: 1195–200.CrossRefGoogle ScholarPubMed
14Robinson, TN. Reducing children's television viewing to prevent obesity: a randomized controlled trial. Journal of the American Medical Association 1999; 282: 1561–7.CrossRefGoogle ScholarPubMed
15Salmon, J, Bauman, A, Crawford, D, Timperio, A, Owen, N. The association between television viewing and overweight among Australian adults participating in varying levels of leisure-time physical activity. International Journal of Obesity and Related Metabolic Disorders 2000; 24: 600–6.CrossRefGoogle ScholarPubMed
16Chen, M, You, Y, Zhao, W, Yang, X. Influences of diet and nutrition on obesity of pre-school children. Health Research 2003; 31: 370–2.Google Scholar
17Astrup, A. Healthy lifestyles in Europe: prevention of obesity and type II diabetes by diet and physical activity. Public Health Nutrition 2001; 4(2B): 499515.CrossRefGoogle ScholarPubMed
18Shepard, TY, Weil, KM, Sharp, TA, Grunwald, GK, Bell, ML, Hill, JO, et al. Occasional physical inactivity combined with a high-fat diet may be important in the development and maintenance of obesity in human subjects. American Journal of Clinical Nutrition 2001; 73: 703–8.CrossRefGoogle ScholarPubMed
19Wardle, J, Waller, J, Jarvis, MJ. Sex difference in the association of socioeconomic status with obesity. American Journal of Public Health 2002; 92: 1299–304.CrossRefGoogle ScholarPubMed
20Ball, K, Mishra, G, Crawford, D. Which aspects of socioeconomic status are related to obesity among men and women?. International Journal of Obesity and Related Metabolic Disorders 2002; 26: 559–65.CrossRefGoogle ScholarPubMed
21Everson, SA, Maty, SC, Lynch, JW, Kaplan, GA. Epidemiologic evidence for the relation between socioeconomic status and depression, obesity, and diabetes. Journal of Psychosomatic Research 2002; 53: 891–5.CrossRefGoogle ScholarPubMed
22Moore, DB, Howell, PB, Treiber, FA. Changes in overweight in youth over a period of 7 years: impact of ethnicity, gender and socioeconomic status. Ethnicity & Disease 2002; 12(Suppl. 1): 83–6.Google Scholar
23Gnavi, R, Spagnoli, TD, Galotto, C, Pugliese, E, Carta, A, Cesari, L. Socioeconomic status, overweight and obesity in prepuberal children: a study in an area of Northern Italy. European Journal of Epidemiology 2001; 16: 797803.CrossRefGoogle Scholar
24Kaluski, DN, Chinich, A, Leventhal, A, Ifrah, A, Cohen-Mannheim, I, Merom, D, et al. Overweight, stature, and socioeconomic status among women – cause or effect: Israel National Women's Health Interview Survey, 1998. Journal of Gender-Specific Medicine 2001; 4: 1824.Google ScholarPubMed
25De Spiegelaere, M, Dramaix, M, Hennart, P. The influence of socioeconomic status on the evolution of obesity during early adolescence. International Journal of Obesity and Related Metabolic Disorders 1998; 22: 268–74.CrossRefGoogle ScholarPubMed
26Sobal, J. Obesity and socioeconomic status: a framework for examining relationships between physical and social variables. Medical Anthropology 1992; 13: 231–47.CrossRefGoogle Scholar
27Sobal, J, Stunkard, AJ. Socioeconomic status and obesity: a review of the literature. Psychological Bulletin 1989; 105: 260–75.CrossRefGoogle ScholarPubMed
28Robbins, JM, Vaccarino, V, Zhang, H, Kasl, SV. Socioeconomic status and type 2 diabetes in African American and non-Hispanic white women and men: evidence from the Third National Health and Nutrition Examination Survey. American Journal of Public Health 2001; 91: 7683.Google ScholarPubMed
29Connolly, V, Unwin, N, Sherriff, P, Bilous, R, Kelly, W. Diabetes prevalence and socioeconomic status: a population based study showing increased prevalence of type 2 diabetes mellitus in deprived areas. Journal of Epidemiology and Community Health 2000; 54: 173–7.CrossRefGoogle ScholarPubMed
30Du, S, Lu, B, Zhai, F, Popkin, BM. A new stage of the nutrition transition in China. Public Health Nutrition 2002; 5(1A): 169–74.CrossRefGoogle ScholarPubMed
31Wang, WJ, Wang, KA, Li, TL, Xiang, HD, Ma, LM, Fu, ZY, et al. A discussion on utility and purposed value of obesity abdomen obesity when body mass index, waist circumference, waist to hip ratio used as indices hypertension and hyper blood glucose. Chinese Journal of Epidemiology 2002; 23: 16–9.Google Scholar
32Bell, AC, Ge, K, Popkin, BM. Weight gain and its predictors in Chinese adults. International Journal of Obesity and Related Metabolic Disorders 2001; 25: 1079–86.CrossRefGoogle ScholarPubMed