| Literature DB >> 26510135 |
Fei Xu1, Robert S Ware2, Eva Leslie3, Lap Ah Tse4, Zhiyong Wang5, Jiequan Li5, Youfa Wang6.
Abstract
BACKGROUND: Childhood obesity has been increasing rapidly worldwide. There is limited evidence for effective lifestyle interventions to prevent childhood obesity worldwide, especially in developing countries like China. The objective of this study was to assess the effectiveness of a school-based multi-component lifestyle childhood obesity prevention program (the CLICK-Obesity study) in Mainland China.Entities:
Mesh:
Year: 2015 PMID: 26510135 PMCID: PMC4625022 DOI: 10.1371/journal.pone.0141421
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Fig 1Flow diagram for enrollment and follow-up of students in the CLICK-Obesity Study.
Baseline demographic, social and clinical characteristics of study participants (4th graders, n = 1108) by treatment group, Nanjing City, China.
| Treatment group | |||
|---|---|---|---|
| Control (n = 503) | Intervention (n = 605) | ||
| Individual level | |||
| Mean (SD) age (years) | 10.2±0.5 | 10.2±0.5 | |
| Percentage of boys (95%CI) | 58.3 (53.5, 62.6) | 53.7 (49.6, 57.7) | |
| Mean (SD) weight (kg) | 36.9±8.0 | 37.6±8.5 | |
| Mean (SD) height (meters) | 140.6±6.4 | 141.3±6.1 | |
| Prevalence of obesity (%, 95%CI) | 10.3 (7.9, 13.4) | 11.6 (9.2, 14.5) | |
| Mean (SD) BMI | 18.54±2.92 | 18.71±3.17 | |
| Percentage of parents with educational attainment ≤9 years (95%CI) | 24.1 (20.5, 28.1) | 20.5 (17.4, 24.0) | |
| Cluster level | |||
| Students per cluster | 126 | 151 | |
| Classes per cluster | 4.0 | 4.5 | |
†Comparisons between two groups in the variables were conducted using either Student’s t-test (continuous outcomes) or the chi-square test (categorical outcomes), showing no significant difference for each variable.
‡ The cluster level referred to school level.
Intervention effectiveness: height, weight and BMI at follow-up among 1108 primary school students in Nanjing City, China .
| Obesity | Treatment group | Mean difference | 95%CI |
| ||
|---|---|---|---|---|---|---|
| Control | Intervention | |||||
| (n = 503) | (n = 605) | |||||
| Height (cm) | 148.17 | 149.00 | 0.83 | 0.01, 1.64 | 0.04 | |
| Weight (kg) | 40.41 | 41.22 | 0.81 | -0.32, 1.95 | 0.16 | |
| BMI | ||||||
| Mean value | 18.25 | 18.39 | 0.14 | -0.24, 0.53 | 0.43 | |
| Changes | -0.29 | -0.32 | -0.03 | -0.18, 0.14 | 0.09 | |
^The intervention lasted for two semesters from September 2010 to June 2011
† calculated from mean values at follow-up (intervention–control).
‡ calculated from BMI values at study end (follow-up–baseline); the intervention group had more BMI deduction than the control, which was marginally significant.
Intervention effectiveness: changes in selected lifestyle behaviors among 1108 primary school students in Nanjing City, China .
| Factors influencing obesity | Change in frequencies of influence factors | ||
|---|---|---|---|
| % (n) | OR (95%CI) | ||
| Control (ref.) N = 503 | Intervention N = 605 | ||
|
| |||
| Jogging/running | 32.4 (163) | 46.0 (278) | 1.55 (1.18, 2.02) |
| Walking | 45.7 (230) | 46.9 (284) | 0.98 (0.74, 1.25) |
| Ball playing | 35.8 (180) | 40.0 (242) | 1.21 (0.93, 1.58) |
|
| |||
| Walking or riding bicycles to school | 16.5 (49) | 28.9 (104) | 2.24 (1.47, 3.40) |
|
| |||
| TV or computers | 41.0 (206) | 49.4 (293) | 1.41 (1.09, 1.84) |
|
| |||
| Red meat | 35.0 (176) | 46.1 (279) | 1.50 (1.15, 1.95) |
| Fried snacks | 27.4 (138) | 29.1 (176) | 1.08 (0.81, 1.44) |
| Soft drinks | 28.2 (142) | 26.4 (160) | 0.89 (0.67, 1.19) |
| Vegetables | 47.1 (237) | 48.6 (294) | 1.20 (0.92, 1.55) |
† Change in frequency was defined as participants whose physical activity frequencies increased and unhealthy food intake frequencies decreased at the follow-up.
‡ for control group, N = 297; for intervention group, N = 360
* Odds ratios were estimated with control group as the reference and using multivariate logistic regression methods with adjustment for clustering effect at school level, participants' age, gender, baseline body weight and parents' educational attainment.
** Change in red meat, snacks and soft-drinks presented as reduced consumption frequency, while in vegetables as increased frequency.
Intervention effectiveness: changes in awareness of selected risk factors for obesity among students who were not aware of those at baseline in Nanjing City, China .
| Risk factors for obesity | Change in awareness (%) of risk factors (from ‘NO’ to ‘YES’) | ||
|---|---|---|---|
| % (N | OR (95%CI) | ||
| Control (ref.) | Intervention | ||
| Physical inactivity | 64.7 (102) | 83.7 (92) | 2.70 (1.25, 5.87) |
| Prolonged screen time | 27.8 (352) | 65.8 (403) | 5.16 (3.66, 7.27) |
| Frequent consumption of fatty meat | 43.4 (205) | 68.3 (183) | 2.16 (1.33, 3.48) |
| Frequent intake of fried snacks | 64.3 (168) | 79.7 (187) | 2.03 (1.22, 3.39) |
| Frequent intake of soft drinks | 39.6 (260) | 71.6 (320) | 3.91 (2.67, 5.71) |
† Change in awareness was defined as participants who did know the selected factors could increase the risk of gaining excess body weight at follow-up while they did not know at baseline.
‡ N, number of participants who were not aware of risk factors for excess body weight at baseline.
* Odds ratios were estimated with control group as the reference and using multivariate logistic regression methods with adjustment for clustering effect at school level, participants' age, gender, baseline body weight and parents' educational attainment.