Factors associated with adolescents' overweight and obesity ... - Nature

European Journal of Clinical Nutrition (2008) 62, 635–643

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ORIGINAL ARTICLE

Factors associated with adolescents’ overweight and obesity at community, school and household levels in Xi’an City, China: results of hierarchical analysis M Li1,2, MJ Dibley2, D Sibbritt3 and H Yan1 1 Department of Public Health, School of Medicine, Xi’an Jiaotong University, Xi’an, China; 2School of Public Health, George Institute for International Health, University of Sydney, Sydney, Australia and 3Centers for Clinical Epidemiology and Biostatistics, Faculty of Health, University of Newcastle, Australia

Objective: To identify personal and environmental factors associated with adolescent overweight and obesity in Xi’an city, China. Subjects/Methods: A total of 1804 adolescents from 30 junior high schools in six districts in Xi’an City. Community, school, household and individual characteristics were self reported by parents, school doctors and students. Factors associated with adolescent overweight and obesity were identified using a hierarchical logistic regression. Results: In all adolescents, after adjustment for age and gender, factors significantly associated with overweight and obesity were: living in urban districts (odds ratio (OR): 4.0, 95% confidence interval (CI): 2.7–6.0); limited use of school sports facilities (OR: 1.7, 95% CI: 1.1–2.6); wealthy households (OR: 1.7, 95% CI: 1.1–2.6); parental restrictions on purchasing snacks (OR: 1.5, 95% CI: 1.03–2.0); having an overweight/obese parent (OR: 1.8, 95% CI: 1.3–2.5); having soft drinks more than four times per week (OR: 1.6, 95% CI: 1.02–2.5) and not fussy about foods (OR: 1.7, 95% CI: 1.2–2.2). Eating sweets was negatively associated with overweight/obesity (OR: 0.6, 95% CI: 0.4–0.9). Separate gender analyses revealed that in boys, low physical activity (OR: 2.0, 95% CI: 1.1–3.8) and higher energy intake (OR: 1.8, 95% CI: 1.1–2.9) were also associated with overweight/obesity. In girls, less school sports meetings (OR: 2.3, 95% CI: 1.3–4.0); parental decisions about eating fast foods (OR: 1.8, 95% CI: 1.1–2.9) and availability of home video games (OR: 1.7, 95% CI: 1.1–2.5) were also significant. Conclusions: Preventive strategies for adolescent overweight and obesity in Xi’an should address the community and school environments to reinforce behavioral change. Gender differences also need to be considered when planning interventions.

European Journal of Clinical Nutrition (2008) 62, 635–643; doi:10.1038/sj.ejcn.1602757; published online 18 April 2007 Keywords: adolescents; overweight; obesity; hierarchical analysis; community; school

Introduction Overweight and obesity in children and adolescents has emerged as an important public health problem both in developed and developing countries. The China National Nutrition and Health survey in 2002 revealed that the prevalence of overweight and obesity using local Chinese body mass index (BMI) cutoffs had reached 13 and 8% in urban children and adolescents (aged 7–17 years), respectively (Ye, 2004). In the population, the overall prevalence of Correspondence: Professor MJ Dibley, School of Public Health,George Institute for International Health, University of Sydney, PO Box M201, Missenden Road, NSW 2050, Sydney, Australia. E-mail: [email protected] Received 11 October 2006; revised 14 February 2007; accepted 9 March 2007; published online 18 April 2007

overweight increased by 39% compared with the prevalence in 1992 (Wang, 2005). In Xi’an City, a large urban area in northwestern China, the prevalence of overweight and obesity for 11–17 year adolescents reached 16% using International Obesity Task Force (IOTF) cutoffs in 2004 (Li et al., 2006a). This was similar to that observed in the United States (25%) in 2001–2002 and Australia (19–23%) in 1995 based on IOTF cutoffs (Booth et al., 2001; Janssen et al., 2005). It has been well established that overweight and obesity in childhood and adolescents is a risk factor for cardiovascular diseases, diabetes, sleep disorders and psychological and social consequences (Lobstein et al., 2004). Childhood and adolescent obesity persists into adulthood and is associated with adult health problems (Reilly et al., 2003). Treatment of overweight and obesity in children and adolescents is challenging. Prevention is the only feasible

Factors associated with adolescent overweight and obesity M Li et al

636 option to curb this emerging public health problem (Lobstein et al., 2004). Programs to prevent overweight and obesity in children and adolescents may start by identifying factors associated with overweight and obesity in a population to ensure targeted and efficient strategies. Studies have identified predictors of overweight and obesity, including heredity (Marti et al., 2004), lifestyle (Hernandez et al., 1999; Robertson et al., 1999; Hanley et al., 2000) and environmental factors (Ma, 2002). However, the results of these studies are limited primarily to a series of simple or bivariate relationships. The lifestyle of children and adolescents is greatly influenced by parents in a family and teachers at a school, and family and school are in turn embedded in a complex social context. Therefore, it is necessary to examine a comprehensive list of factors implicated in the development of childhood overweight and obesity, such as dietary and activity patterns, parents and family habits and household and community environment. School environments exert a great influence on children’s behavior due to their long hours of attendance at school in China, which is typically 8–10 h per day. A contextual model presents a holistic picture of the factors considered in the development of childhood overweight and obesity based on ‘Ecological System Theory’ (Davison and Birch, 2001). According to this model, development of overweight and obesity in childhood occurs as interactions of characteristics of a child with processes in the family and the school, which in turn are influenced by characteristics of the community and society at large. The purpose of this study was to identify risk factors associated with overweight and obesity in adolescents in Xi’an City, a major city with 7 million people in northwest China, at community, school and household levels, and parental and child characteristics, based on a conceptual hierarchical framework linking all these factors.

Methods Study population and design From May to November 2004, a representative sample of 1804 adolescents, aged 11–17 years attending 30 junior high schools in Xi’an City out of 183 schools with a total of 145 000 students, were enrolled in this cross-sectional survey. A multistage cluster sampling method was used in which the 30 schools were selected proportionate to student population size, by systematic random sampling from junior high schools across the city. In each selected school, one class in each grade was randomly selected and from each class, 20 students were selected using systematic random sampling. Consent was sought hierarchically from Municipal Education Department, to the school health division at district level, to principal at school level and to the participants and their parents. Survey measurements were only taken from those children who agreed and whose parents had signed consent forms. The study protocol was approved by Human Research Ethics Committee at the University of Newcastle European Journal of Clinical Nutrition

and Ethical Committee in Medical Research at Xi’an Jiaotong University. Among the 1804 enrolled, 1792 (99.3%) students and their parents agreed to participate in the survey. Among them, 899 were boys (50.2%) and 893 were girls with a mean age of 13.9 (s.d.: 1.0) ranging from 11.1 to 17.1 years.

Information collected Anthropometric measurements were obtained from all consenting participants by trained field staff using standard methods as described in an anthropometric standardization reference manual (Lohman et al., 1991). Height without shoes was measured using a measuring tape (214 Rodt, Seca, USA) and was recorded to the nearest 0.1 cm. Body weight of participants without shoes, but with underwear in the summer session or light clothes in the autumn session, was measured by digital scale (Tanita HD-305, Tanita Corporation, Japan) to the nearest 0.1 kg. Environmental factors at community and household levels were collected with self-administered questionnaires completed by consenting parents. Parental information included parental education, occupation and self-reported height and weight. An inventory of household assets (house, TV, camera, DVD, air conditioner, transportation facilities and kitchen utensils) was recorded for computing a wealth index as an indicator of the socioeconomic status of the household (Filmer and Pritchett, 1998a). Factors at the school level were obtained by asking school doctors to complete a pre-coded ‘School Environment Questionnaire’. Items in the questionnaires assessing environmental factors were identified from literatures and from focus group discussions with students, parents and schoolteachers. The questionnaires were also discussed at expert panel meeting at Xi’an Jiaotong Universtiy and piloted in two schools before data collection. Dietary habits of adolescents were recorded using selfadministered questionnaires composed of 19 multiplechoice questions, and the topics in the questionnaire included usual venues for meals, frequency of eating at and outside home, frequency of selected foods and beverages and food habits and attitudes. This questionnaire was adapted from the US NHANES III (Centres of Disease Control and Prevention, 2003). Nutrient intake was obtained from a faceto-face interview with a standard 24-h recall method conducted by trained research staff on the random basis of weekday and weekend. Physical activity of the participants was recorded using the adaptation of a validated questionnaire designed specifically for adolescents, namely ‘The Adolescents Physical Activity Recall Questionnaire (APARQ)’ (Booth et al., 2002). Sedentary time was recorded using a ‘Sedentary Time Recording Form’, in which the time spent watching TV, playing computer games or video games, doing homework after school, and listening to music or other sedentary habits on both weekdays and weekends was recorded. The ques-


637 tionnaires were completed by all participants after school and usually took approximately 10 min to complete. Pubertal development of adolescents was assessed using confidential validated pictograms (Morris and Udry, 1980). All the questionnaires developed in the west were adapted by conducting focus group discussions with parents and students and piloted to assess the appropriateness of the language used in the measurement instruments.

Data analysis BMI was used to assess the adiposity of adolescents. Overweight and obesity was defined using the IOTF BMI cutoffs (Cole et al., 2000). The outcome variable is binary with subjects being categorized as being either normal weight or a combined overweight/obesity. The categories of overweight and obesity were combined to optimize statistical power. Independent variables were selected from each level of the conceptual framework, including community, school, household, family and parental characteristics and children’s behavioral variables and characteristics. Within each level, all the candidate variables (Pp0.30) from the univariate regression were included in the logistic regression models initially to identify significant variables for inclusion in the subsequent hierarchical models (Hosmer and Lemeshow, 1989). According to the conceptual hierarchical modeling approach (Victora et al., 1997), factors at the community level may determine directly or indirectly all variables being studied; the next hierarchical level comprises school factors, which are partly determined by community factors; the third level includes household and the fourth level the parental and family factors. The next level was adolescents’ behavioral factors, such as nutrient intake and diet, physical activity level and sedentary behavior and finally adolescents’ personal characteristics. In this approach, the first step was to examine the association of overweight/obesity with factors at the community level. All screened candidate variables at the community level were added into the model. Only those significantly associated with overweight/obesity (Po0.05) were retained for subsequent model building; in the second step, school variables were added into the first model, and only those significantly associated with overweight/obesity were retained; to this new model, the household-level variables were then added. A similar procedure was repeated for all other levels. The adjusted ORs and the 95% CIs of this hierarchical procedure presented in the results section were not derived from the final model, but from the equation corresponding to the level when the factor of interest was first entered to avoid the possibility that mediating variables might take away some of the explanatory power of more distant determinants. For example, part of the effect of community on overweight/obesity may be mediated through parental education. The overall effect of community therefore should

be examined in a model without parental education; otherwise, the role of community would be underestimated. Data were analyzed using the statistical package STATA 9 (STATACorp, College Station, TX, USA).

Results Out of 1804 invited participants, 1792 (99. 3%) consenting adolescents were measured for weight and height. 1786 parents completed the household questionnaire. A doctor from each of the 30 schools completed the school environmental questionnaire. A total of 1790 adolescents were interviewed for 24-h food intakes, but 90 records were excluded from analysis according to the exclusion criteria (Rockett et al., 1997). A physical activity questionnaire was completed by 1787 (99.1%) adolescents, with two cases excluded from analysis according to the exclusive criteria (Marshall et al., 2002). Sedentary activity forms were completed by 1761 (98.3%) adolescents, while 1763 (98.4%) participants completed pubertal questionnaires among which 377 male records and 26 female records were excluded (World Health Organization, 1995). Among the participants, 19.9% were considered to be overweight/obese. Table 1 shows the factors associated with overweight and obesity from the hierarchical model using the complete sample. At the community level, the risk of overweight and obesity in adolescents was associated with place of residence where, in comparison to those living in a rural area, adolescents in suburban areas (OR: 2.5, 95% CI: 1.8–3.4) or urban area (OR: 4.0, 95% CI: 2.7–6.0) had greater risks of being overweight/obese. Other factors at this level such as access to public recreational facilities, neighborhood safety, transportation and fast-food restaurants were excluded. At the school level, limitations in the use of ovals for physical education classes only increased the risk of overweight/obesity by 70% (95% CI: 1.1–2.6) compared with allowing access to the oval during school days only. Other school factors such as availability of playgrounds and sports equipment, morning exercise and recess activity, sports meetings, physical education and health education sessions, school policies on riding bicycle and snacking and fast-food restaurants were excluded during the regressions. At the household level, adolescents from wealthy families were 1.7 times (95% CI: 1.1–2.6) more likely to be overweight/obese than those from poorer families. Having rules for buying snacks with pocket money was associated with an increased risk of overweight/obese in adolescents (OR: 1.5, 95% CI: 1.03–2.0). Those whose parents were overweight and/or obese were 1.8 (95% CI: 1.3–2.5) times more likely to be overweight/obese than those parents with normal weight. Factors such as parental education, occupation and their involvement in exercising with children were excluded from the multivariate analysis. Having soft drinks four or more times per week increased the risk of overweight and obesity by 60% (OR: 1.6, 95% CI: European Journal of Clinical Nutrition


638 Table 1 Factors-associated overweight/obesitya in overall sample Block of factor

n/N

cOR

aOR

95% CI

Community environmental factors Location Rural Suburban Urban

19/300 95/660 178/839

1.0 2.5 4.0

1.0 2.5 4.0

1.8–3.4 2.7–6.0

School environmental factors Rules for school oval On school days At PE class No restriction

138/901 69/241 66/481

1.0 2.3 0.9

1.0 1.7 0.9

1.1–2.6 0.7–1.3

Household factors Rules for buying snacks Freely Getting permission Forbidden

66/491 141/774 39/230

1.0 1.4 1.3

1.0 1.5 1.5

1.03–2.0 0.9–2.5

Household wealthb Poorest Middle Richest

38/589 94/589 155/590

1.0 1.6 2.4

1.0 1.1 1.7

0.8–1.6 1.1–2.6

Parental factors Parents’ BMI statusc Normal Overweight/obese

139/1035 137/609

1.0 1.9

1.0 1.8

1.3–2.5

Adolescents’ behaviors Having soft drink (times/week) None 1–3 X4

120/866 109/629 63/305

1.0 1.3 1.6

1.0 1.2 1.6

0.8–1.8 1.02–2.5

Fussy on foodsd Yes No

133/982 150/783

1.0 1.8

1.0 1.7

1.2–2.2

Having preserved fruit Yes No

214/1188 70/583

1.0 0.6

1.0 0.7

0.5–1.0

Adolescents’ characteristics Gender Female Male

118/893 174/899

1.0 1.6

1.0 1.5

1.1–2.2

Age (years) o13 13–13.9 14–14.9 X15

92/401 82/507 90/600 28/284

1.0 0.6 0.6 0.4

1.0 0.7 0.6 0.4

0.4–1.2 0.4–0.9 0.2–0.6

Abbreviations: aOR, adjusted odds ratio by retaining significant variable in the hierarchical multivariate logistic analysis; CI, confidence interval; cOR, unadjusted odds ratio from univariate logistic analysis; n/N, number of overweight/obesity over the total number of the risk category. a Overweight/obesity in adolescents defined by IOTF cutoffs (Cole et al., 2000). b Household wealth as an indicator of the socioeconomic status of the household by categorizing into tertile an index based on an inventory of household assets (house, TV, camera, DVD, air conditioner, transportation facilities and kitchen utensils) and calculated using principal analysis. c Parents’ overweight/obesity defined by WHO cutoffs (World Health Organization, 2000) based on self reported weight and height, normal means both parents having BMIo25 kg/m2; overweight/obese means at least one parent having BMIX25 kg/m2. d Fussy on food means only having favorite food and avoid unfavored foods.

1.02–2.5). Nonfussy eaters were 1.5 (95% CI: 1.2–2.2) times more likely to be overweight/obese than fussy eaters. Adolescents who consumed preserved fruit (OR: 0.7, 95% European Journal of Clinical Nutrition

CI: 0.5–1.0) were 30% less likely to be overweight/obese than those who did not eat preserved fruits. The availability of soft drinks at home was associated with an increased frequency


639 of the consumption compared to children without soft drinks at home (31.7 vs 11.6%, Po0.01). Also, wealthier households had a higher percentage of stored soft drinks (46.3% vs 24.8%, Po0.01). Other behavioral factors such as eating out, sedentary time were excluded from the analysis. Boys were 1.5 (95% CI: 1.1–2.2) times more likely to be overweight/obese than girls. Those children aged over 13 years were 40% (OR: 0.6, 95% CI: 0.4–0.9) less likely to be overweight and obese than those aged less than 13 years. Demographic factors such as ethnicity, birth weight and pubertal stage were excluded in the multivariate analysis.

Table 2 shows the factors associated with overweight/ obesity in boys. There were other risk factors identified other than those already identified in the overall sample (Table 1). Three sessions of physical education per week was associated with an increased risk of overweight/obesity in males by 200% (OR: 3.0, 95% CI: 1.4–6.3) compared with once a week. Boys living in houses without lanes nearby were 1.6 times (95% CI: 1.04–2.4) more likely to be overweight and obese. Boys whose mothers had attained tertiary education were 2.2 (95% CI: 1.1–4.3) times more likely to be overweight and obese than those mothers who had primary education.

Table 2 Factors associated with overweight/obesitya from hierarchical models in boys n/N

cOR

aOR

95% CI


12/149 56/320 106/430

1.0 2.4 3.7

1.0 2.4 3.7

1.6–3.6 2.2–6.3

School environmental factors Rules for school oval On school days At PE class No restriction

74/447 45/123 45/248

1.0 2.9 1.0

1.0 2.4 1.02

1.4–4.2 0.7–1.6

PE sessions per week Once Twice Three times

4/32 138/778 17/89

1.0 1.5 3.9

1.0 1.4 3.0

0.7–2.6 1.4–6.3

Household factors Lane around the house Available Unavailable

54/319 117/560

1.0 1.3

1.0 1.6

1.04–2.4

Rules for buying snacks Freely Getting permission Forbidden

36/249 89/379 23/121

1.0 1.8 1.4

1.0 2.0 1.4

1.2–3.4 0.6–3.0

Parental characteristics Maternal education Primary Secondary Tertiary

53/365 67/353 51/162

1.0 1.4 2.7

1.0 1.2 2.2

0.7–2.2 1.1–4.3

Parental BMI statusb Normal Overweight/obese

83/496 82/325

1.0 1.7

1.0 1.6

1.01–2.6

Adolescents behaviors Having soft drink (times/week) None 1–3 X4

65/386 63/327 46/186

1.0 1.2 1.6

1.0 1.1 1.9

0.7–1.8 1.1–3.2

Having preserved fruit Yes No

129/600 40/283

1.0 0.6

1.0 0.6

0.4–0.99

Physical activity levelc Active Inactive

150/798 24/100

1.0 1.4

1.0 2.0

1.1–3.8

European Journal of Clinical Nutrition


640 Table 2 Continued n/N

cOR

aOR

95% CI

Energy intake tertiled Lowest Middle Highest

46/181 64/297 56/356

1.0 1.5 1.9

1.0 1.8 1.8

0.99–3.3 1.1–2.9

Adolescents characteristics Age (years) o13 13–13.9 14–14.9 X15

53/197 48/250 57/298 16/154

1.0 0.6 0.6 0.3

1.0 0.7 0.7 0.3

0.4–1.3 0.4–1.1 0.2–0.6

Abbreviations: aOR, adjusted odds ratio by retaining significant variable in the hierarchical multivariate logistic analysis; BMI, body mass index; n/N, number of overweight/obesity over the total number of the risk category; CI, confidence interval; cOR, unadjusted odds ratio from univariate logistic analysis; PE, physical education. a Overweight/obesity in adolescents defined by IOTF cutoffs (Cole et al., 2000). b Parents’ overweight/obesity defined by WHO cutoffs (World Health Organization, 2000) based on self–reported weight and height, normal means both parents having BMIo25 kg/m2; overweight/obese means at least one parent having BMIX25 kg/m2. c Physically active defined as equal to or more than 150 min/week of moderate activity (4–6 METS) or 60 min/week vigorous activity (6 þ METS); inactive defined as less than 150 min/week of moderate activity (4–6 METS) or 60 min/week vigorous activity (6 þ METS) (Sallis and Patrick, 1994). d Energy intake was adjusted to remove the within person variation and categorized into tertile from low to high (lowest: adjusted energy intake o2493 kcal; middle: adjusted energy intake 2494–2867 kcal; highest: adjusted energy intake42867 kcal).

Those physically inactive were 2.0 times (95% CI: 1.1–3.8) more likely to be overweight and obese. Boys with the highest intake of energy tertile were 1.8 times (95% CI: 1.1– 2.9) more likely to be overweight and obese. Table 3 reveals significant factors associated with overweight/obesity in girls. Apart from significant factors identified in overall sample (Table 1), free playground use decreased the risk of overweight and obesity by 40% (OR: 0.6, 95% CI: 0.4–0.9). Having fewer sports meetings increased the risk of overweight and obesity by 50% (annual OR: 1.5, 95% CI: 1.02–2.3) or 40% (once in two years OR: 2.3 95% CI: 1.3–4.0) compared with sports meetings being held twice yearly. Lack of a video game machine at home decreased the risk of overweight and obesity by 40% (OR: 0.6, 95% CI: 0.4–0.9). The risk of overweight and obesity was 1.8 times (95% CI: 1.1– 2.9) greater if the parents decided to have Western fast foods than if the children decided by themselves. Having snacks one to three times in a week decreased the risk of overweight and obesity by 40% (OR: 0.6, 95% CI: 0.3–0.99).

Discussion The identification of risk factors associated with overweight and obesity in adolescents is important for China. It can guide the development of evidence-based strategies to tackle the increasing public health problem of adolescent overweight and obesity in a society undergoing a nutritional transition. Although previous studies in China and other countries have explored socioeconomic and behavioral factors associated with overweight and obesity in childhood and adolescents (Hernandez et al., 1999; Ma, 2002), the analyses have been based on one group of factors, such as socioeconomic status of the family, or diet or physical European Journal of Clinical Nutrition

activity. In addition, intervention studies based on behavior change to prevent rapid increases of overweight and obesity do not seem to be effective in the long term (Summerbell et al., 2005). This implies intervention strategies only aiming at behavior change of individuals are not sufficient. Therefore, identification of community, school and household environment factors associated with overweight and obesity has added importance. This is the first study to integrate environmental factors at the levels of community, school and household with behavioral factors of individuals to identify possible environmental factors associated with overweight and obesity in Chinese adolescents. Overweight and obesity in adolescents in Xi’an city is associated with a combination of environmental, family and behavioral factors, not just lifestyle factors. Significant factors associated with behaviors of adolescents were found at the community, school and household levels. Specifically, in urban and suburban areas, adolescents were more likely to be overweight or obese. These areas have convenient public transportation systems and easy access to commercial food products and restaurants, which in turn influence the adolescents’ behavior. In addition, parents living in urban areas are working during the day, and adolescents are highly likely to have fast foods outside their homes, which are high in energy and fat (Prentice and Jebb, 2003). Also, urban and suburban adolescents spend more time doing homework (mean time doing homework in urban adolescents: 3.4, 95% CI: 3.2–3.5, suburban adolescents: 2.9, 95% CI: 2.7–3.2; rural adolescents: 2.7, 95% CI: 2.4–3.0, Po0.01). Associated factors at the school level included school rules and school schedule of sport meetings. Chinese students spend most of their day (8–10 h) at school, and playing at school constitutes a large part of their physical activities. Sport meetings can promote physical activities by peer model and


641 Table 3 Factors associated with overweight/obesitya from hierarchical models in girls n/N

cOR

aOR

95% CI


7/150 39/339 72/404

1.0 2.7 4.3

1.0 2.7 4.4

1.1–6.2 1.9–10.4

School factors Rules for school playground On school days At PE class No restriction

77/513 7/60 34/320

1.0 1.6 0.7

1.0 0.5 0.6

0.2–1.0 0.4–0.9

Frequency of sports meetings Twice a year Once a year Once in 2 years

39/386 76/441 15/61

1.0 1.5 2.9

1.0 1.5 2.3

1.02–2.3 1.3–4.0

Household factors Decision maker for Western food Children Parents Whole family

49/428 51/291 12/94

1.0 1.6 1.1

1.0 1.8 1.4

1.1–2.9 0.7–2.7

Video game machine at home Available Unavailable

51/269 66/613

1.0 0.5

1.0 0.6

0.4–0.9

Household wealthb Poor Middle Rich

20/288 47/303 50/291

1.0 2.5 2.8

1.0 2.0 1.8

1.04–4.0 0.9–3.6

Parental factors BMI statusc Normal Overweight/obese

55/535 55/281

1.0 2.1

1.0 2.3

1.3–3.8

Behavioral factors Frequency of snackingd None 1–3 X4

60/358 42/404 15/124

1.0 0.6 0.7

1.0 0.6 0.9

0.3–0.99 0.4–1.7

Abbreviations: aOR, adjusted odds ratio by retaining significant variable in the hierarchical multivariate logistic analysis; BMI, body mass index; CI, confidence interval; cOR, unadjusted odds ratio from univariate logistic analysis; n/N, number of overweight/obesity over the total number of the risk category. a Overweight/obesity in adolescents defined by IOTF cutoffs (Cole et al., 2000). b Household wealth as an indicator of the socioeconomic status of the household by categorizing into tertile an index based on an inventory of household assets (house, TV, camera, DVD, air conditioner, transportation facilities, and kitchen utensils) and calculated using principle analysis. c Parents’ overweight/obesity defined by WHO cutoffs (World Health Organization, 2000) based on self–reported weight and height, normal means both parents having BMIo25 kg/m2; overweight/obese means at least one parent having BMIX25 kg/m2. d Snacking means having any food beyond three meals.

establish a positive and active atmosphere for adolescents during school hours and after school. This is consistent with an intervention study in elementary schools conducted in the United States, indicating that sports provides students with substantial amounts of physical activities (Sallis et al., 1997). Therefore, strategies for obesity prevention should take into account the need to adjust school curricula by increasing opportunities for physical activity during the school day. The longer duration of school sports meetings was negatively associated with overweight and obesity. Longer duration or

sports meetings were related to larger school enrollment of students from wealthier families (mean enrollment of schools having 3 days of sports meetings 2840, 95% CI: 2720–2959; mean enrollment of school having 2 days of sports meetings 1887, 95% CI: 1818–1957; mean enrollment of school having 1 day of sports meetings 653, 95% CI 601–704, Po0.01). This relationship explains both multiple logistic regressions; when residence or wealth index was included, the association between overweight/obesity and duration of sports meetings at school level disappeared. European Journal of Clinical Nutrition


642 At the household level, besides household wealth, family control of the child’s snacking was associated with increased prevalence of overweight and obesity in adolescents, especially boys. While in girls, parental control of the consumption of Western fast foods was associated with an increased risk of overweight and obesity. We think parents were more likely to limit children’s intake of snacks and fast-food consumption if their children were already overweight or obese. It is reported that Chinese and Chinese-American parents have a more authoritarian parenting style than do Western parents, suggesting Chinese parents are stricter and more controlling (Chao, 1994). Studies of the relationship between parenting style and the children’s BMI have provided inconsistent results. A study involving Chinese parents in Taiwan and the United States suggested that a more democratic parenting style was associated with higher BMI (Chen and Kennedy, 2004). While other studies have shown that democratic parenting was associated with better health in children (Russell et al., 1992; Hill and Franklin, 1998), which was consistent with our results. A parent’s expression of nurturing emotion with clear communication and realistic behavioral expectations is imperative to a child’s development and healthy behavior, as it provides motivation for a child, allows the parent to help establish healthy behaviors and reinforces self-regulation, thereby allowing the child to develop new and healthy activities (Goetz and Caron, 1999). As a proxy of family socio-economic status, parental education had an impact on the development of overweight and obesity in their offspring as revealed in the hierarchical model. Parents may shape their children’s behaviors such as eating and physical activity via pathways including parents’ knowledge, the types of foods and facilities parents make available to children and parent child-feeding and exercising practices. Parents are the likely role models for children’s eating and activity behavior. Eating and exercise behaviors can also be shaped and cultivated by family regulations based on the parents’ knowledge and practice (Freedson and Evenson, 1991; Gibson et al., 1998). Behavioral factors such as frequency of having soft drinks and fussiness about food was associated with overweight and obesity. This has been demonstrated either in longitudinal studies or cross-sectional studies, both in Western countries like the United States and developing countries like China (Ludwig et al., 2001; Hesketh et al., 2002; Nicklas et al., 2003). What is more, the current study also shown that the availability of soft drinks at home increased the soft drink consumption, and rich families were more likely to store soft drinks at home. Fussiness about food was associated with a decreased risk of overweight and obesity in adolescents. An exploration of adolescents who were fussy about food showed they had a lower consumption of cereals, while girl fussy eaters consumed more snacks and male fussy eaters had less vegetables and fruits than nonfussy eaters. The snacks adolescent girls usually consumed need to be studied in Xi’an city. Children’s consumption of fruit and vegetables was reported to be positively associated with preference for European Journal of Clinical Nutrition

fruit and vegetables (Resnicow et al., 1997), but the relationship between preference for fruits and vegetables and children’s weight status was not assessed in our study. It should be noted that physical activity and energy intake were associated with overweight and obesity in boys, but not in girls. One possible reason could be the physical activity levels and food intake in girls was too homogeneous to allow the detection of any association between these factors with overweight and obesity. Another reason is that the dietary habits of girls differed from boys. For example, girls snacked more frequently than boys, while boys had soft drinks more frequently than girls. These dietary differences may be related to energy intake. In girls, an associated factor with overweight and obesity was having video games at home, which provided more opportunities for girls to play video games taking up the time that would be otherwise spent on physical activity. This was different from the relationship of video games in the neighborhood and physical activity found in boys. The availability of video game shops in the neighborhood promoted boys to have more moderate to vigorous street physical activities, such as skateboarding as a group (Li et al., 2006b). This study revealed factors associated with overweight and obesity were not only individual lifestyle factors such as physical activity, dietary habit and energy intake, but also environmental factors at community, school and household levels. These findings imply that effective obesity intervention strategies should include both the components at the individual level and components at the community, school and household levels. Therefore, obesity intervention programs should be composed of the following components: (1) cooperation between government policymaking for infrastructure development, food supply and surveillance of policy implementation; (2) school involvement in the development of curriculum and school policies; (3) family involvement in food storage and parenting style and parents’ modeling; with the final target to foster a healthy lifestyle for children at the early stage of their life and benefit from a sustainable lifestyle for their whole life. For the behavioral and lifestyle change, the strategies developed in Western countries could be adjusted as part of future programs. A recent Cochrane review of obesity intervention studies showed that interventions focused on behavior change alone in adolescents did not show promising effects either on a short-term basis or on a longer term more sustainable basis. This also suggests that future obesity interventions should include change of the environment, which has an impact on individual behavior and thus improve the sustainability of behavior change (Summerbell et al., 2005). School should be an ideal setting for implementing strategies to tackle the emerging public problem of adolescent obesity in Xi’an city due to its unique function to convey knowledge and skills to students and its links with society and families. It is also cost effective to utilize the group effect of education, peer interaction and organization. In view of the findings of this study, health policy planners should develop targeted strategies for obesity intervention in adolescents in Xi’an city, China.


643

Acknowledgements This research was sponsored by a research training fellowship (066971/2/02/A) from the Health Consequences of Population Change Program of The Wellcome Trust. We thank the Municipal Education Department in Xi’an city for coordination and all the field workers for their contribution in the data collection. Conflict of interest statement None of the authors have any financial support from or relationships with organizations that might benefit from the publication of these research findings.

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