National School-Based Health Lifestyles Intervention in Chinese Children and Adolescents on Obesity and Hypertension

Interventions to prevent obesity in children aged 5 to 11 years old

BACKGROUND

Prevention of obesity in children is an international public health priority given the prevalence of the condition (and its significant impact on health, development and well-being). Interventions that aim to prevent obesity involve behavioural change strategies that promote healthy eating or 'activity' levels (physical activity, sedentary behaviour and/or sleep) or both, and work by reducing energy intake and/or increasing energy expenditure, respectively. There is uncertainty over which approaches are more effective and numerous new studies have been published over the last five years, since the previous version of this Cochrane review.

OBJECTIVES

To assess the effects of interventions that aim to prevent obesity in children by modifying dietary intake or 'activity' levels, or a combination of both, on changes in BMI, zBMI score and serious adverse events.

SEARCH METHODS

We used standard, extensive Cochrane search methods. The latest search date was February 2023.

SELECTION CRITERIA

Randomised controlled trials in children (mean age 5 years and above but less than 12 years), comparing diet or 'activity' interventions (or both) to prevent obesity with no intervention, usual care, or with another eligible intervention, in any setting. Studies had to measure outcomes at a minimum of 12 weeks post baseline. We excluded interventions designed primarily to improve sporting performance.

DATA COLLECTION AND ANALYSIS

We used standard Cochrane methods. Our outcomes were body mass index (BMI), zBMI score and serious adverse events, assessed at short- (12 weeks to < 9 months from baseline), medium- (9 months to < 15 months) and long-term (≥ 15 months) follow-up. We used GRADE to assess the certainty of the evidence for each outcome.

MAIN RESULTS

This review includes 172 studies (189,707 participants); 149 studies (160,267 participants) were included in meta-analyses. One hundred forty-six studies were based in high-income countries. The main setting for intervention delivery was schools (111 studies), followed by the community (15 studies), the home (eight studies) and a clinical setting (seven studies); one intervention was conducted by telehealth and 31 studies were conducted in more than one setting. Eighty-six interventions were implemented for less than nine months; the shortest was conducted over one visit and the longest over four years. Non-industry funding was declared by 132 studies; 24 studies were funded in part or wholly by industry. Dietary interventions versus control Dietary interventions, compared with control, may have little to no effect on BMI at short-term follow-up (mean difference (MD) 0, 95% confidence interval (CI) -0.10 to 0.10; 5 studies, 2107 participants; low-certainty evidence) and at medium-term follow-up (MD -0.01, 95% CI -0.15 to 0.12; 9 studies, 6815 participants; low-certainty evidence) or zBMI at long-term follow-up (MD -0.05, 95% CI -0.10 to 0.01; 7 studies, 5285 participants; low-certainty evidence). Dietary interventions, compared with control, probably have little to no effect on BMI at long-term follow-up (MD -0.17, 95% CI -0.48 to 0.13; 2 studies, 945 participants; moderate-certainty evidence) and zBMI at short- or medium-term follow-up (MD -0.06, 95% CI -0.13 to 0.01; 8 studies, 3695 participants; MD -0.04, 95% CI -0.10 to 0.02; 9 studies, 7048 participants; moderate-certainty evidence). Five studies (1913 participants; very low-certainty evidence) reported data on serious adverse events: one reported serious adverse events (e.g. allergy, behavioural problems and abdominal discomfort) that may have occurred as a result of the intervention; four reported no effect. Activity interventions versus control Activity interventions, compared with control, may have little to no effect on BMI and zBMI at short-term or long-term follow-up (BMI short-term: MD -0.02, 95% CI -0.17 to 0.13; 14 studies, 4069 participants; zBMI short-term: MD -0.02, 95% CI -0.07 to 0.02; 6 studies, 3580 participants; low-certainty evidence; BMI long-term: MD -0.07, 95% CI -0.24 to 0.10; 8 studies, 8302 participants; zBMI long-term: MD -0.02, 95% CI -0.09 to 0.04; 6 studies, 6940 participants; low-certainty evidence). Activity interventions likely result in a slight reduction of BMI and zBMI at medium-term follow-up (BMI: MD -0.11, 95% CI -0.18 to -0.05; 16 studies, 21,286 participants; zBMI: MD -0.05, 95% CI -0.09 to -0.02; 13 studies, 20,600 participants; moderate-certainty evidence). Eleven studies (21,278 participants; low-certainty evidence) reported data on serious adverse events; one study reported two minor ankle sprains and one study reported the incident rate of adverse events (e.g. musculoskeletal injuries) that may have occurred as a result of the intervention; nine studies reported no effect. Dietary and activity interventions versus control Dietary and activity interventions, compared with control, may result in a slight reduction in BMI and zBMI at short-term follow-up (BMI: MD -0.11, 95% CI -0.21 to -0.01; 27 studies, 16,066 participants; zBMI: MD -0.03, 95% CI -0.06 to 0.00; 26 studies, 12,784 participants; low-certainty evidence) and likely result in a reduction of BMI and zBMI at medium-term follow-up (BMI: MD -0.11, 95% CI -0.21 to 0.00; 21 studies, 17,547 participants; zBMI: MD -0.05, 95% CI -0.07 to -0.02; 24 studies, 20,998 participants; moderate-certainty evidence). Dietary and activity interventions compared with control may result in little to no difference in BMI and zBMI at long-term follow-up (BMI: MD 0.03, 95% CI -0.11 to 0.16; 16 studies, 22,098 participants; zBMI: MD -0.02, 95% CI -0.06 to 0.01; 22 studies, 23,594 participants; low-certainty evidence). Nineteen studies (27,882 participants; low-certainty evidence) reported data on serious adverse events: four studies reported occurrence of serious adverse events (e.g. injuries, low levels of extreme dieting behaviour); 15 studies reported no effect. Heterogeneity was apparent in the results for all outcomes at the three follow-up times, which could not be explained by the main setting of the interventions (school, home, school and home, other), country income status (high-income versus non-high-income), participants' socioeconomic status (low versus mixed) and duration of the intervention. Most studies excluded children with a mental or physical disability.

AUTHORS' CONCLUSIONS

The body of evidence in this review demonstrates that a range of school-based 'activity' interventions, alone or in combination with dietary interventions, may have a modest beneficial effect on obesity in childhood at short- and medium-term, but not at long-term follow-up. Dietary interventions alone may result in little to no difference. Limited evidence of low quality was identified on the effect of dietary and/or activity interventions on severe adverse events and health inequalities; exploratory analyses of these data suggest no meaningful impact. We identified a dearth of evidence for home and community-based settings (e.g. delivered through local youth groups), for children living with disabilities and indicators of health inequities.

Interventions to prevent obesity in children aged 12 to 18 years old

BACKGROUND

Prevention of obesity in adolescents is an international public health priority. The prevalence of overweight and obesity is over 25% in North and South America, Australia, most of Europe, and the Gulf region. Interventions that aim to prevent obesity involve strategies that promote healthy diets or 'activity' levels (physical activity, sedentary behaviour and/or sleep) or both, and work by reducing energy intake and/or increasing energy expenditure, respectively. There is uncertainty over which approaches are more effective, and numerous new studies have been published over the last five years since the previous version of this Cochrane Review.

OBJECTIVES

To assess the effects of interventions that aim to prevent obesity in adolescents by modifying dietary intake or 'activity' levels, or a combination of both, on changes in BMI, zBMI score and serious adverse events.

SEARCH METHODS

We used standard, extensive Cochrane search methods. The latest search date was February 2023.

SELECTION CRITERIA

Randomised controlled trials in adolescents (mean age 12 years and above but less than 19 years), comparing diet or 'activity' interventions (or both) to prevent obesity with no intervention, usual care, or with another eligible intervention, in any setting. Studies had to measure outcomes at a minimum of 12 weeks post baseline. We excluded interventions designed primarily to improve sporting performance.

DATA COLLECTION AND ANALYSIS

We used standard Cochrane methods. Our outcomes were BMI, zBMI score and serious adverse events, assessed at short- (12 weeks to < 9 months from baseline), medium- (9 months to < 15 months) and long-term (≥ 15 months) follow-up. We used GRADE to assess the certainty of the evidence for each outcome.

MAIN RESULTS

This review includes 74 studies (83,407 participants); 54 studies (46,358 participants) were included in meta-analyses. Sixty studies were based in high-income countries. The main setting for intervention delivery was schools (57 studies), followed by home (nine studies), the community (five studies) and a primary care setting (three studies). Fifty-one interventions were implemented for less than nine months; the shortest was conducted over one visit and the longest over 28 months. Sixty-two studies declared non-industry funding; five were funded in part by industry. Dietary interventions versus control The evidence is very uncertain about the effects of dietary interventions on body mass index (BMI) at short-term follow-up (mean difference (MD) -0.18, 95% confidence interval (CI) -0.41 to 0.06; 3 studies, 605 participants), medium-term follow-up (MD -0.65, 95% CI -1.18 to -0.11; 3 studies, 900 participants), and standardised BMI (zBMI) at long-term follow-up (MD -0.14, 95% CI -0.38 to 0.10; 2 studies, 1089 participants); all very low-certainty evidence. Compared with control, dietary interventions may have little to no effect on BMI at long-term follow-up (MD -0.30, 95% CI -1.67 to 1.07; 1 study, 44 participants); zBMI at short-term (MD -0.06, 95% CI -0.12 to 0.01; 5 studies, 3154 participants); and zBMI at medium-term (MD 0.02, 95% CI -0.17 to 0.21; 1 study, 112 participants) follow-up; all low-certainty evidence. Dietary interventions may have little to no effect on serious adverse events (two studies, 377 participants; low-certainty evidence). Activity interventions versus control Compared with control, activity interventions do not reduce BMI at short-term follow-up (MD -0.64, 95% CI -1.86 to 0.58; 6 studies, 1780 participants; low-certainty evidence) and probably do not reduce zBMI at medium- (MD 0, 95% CI -0.04 to 0.05; 6 studies, 5335 participants) or long-term (MD -0.05, 95% CI -0.12 to 0.02; 1 study, 985 participants) follow-up; both moderate-certainty evidence. Activity interventions do not reduce zBMI at short-term follow-up (MD 0.02, 95% CI -0.01 to 0.05; 7 studies, 4718 participants; high-certainty evidence), but may reduce BMI slightly at medium-term (MD -0.32, 95% CI -0.53 to -0.11; 3 studies, 2143 participants) and long-term (MD -0.28, 95% CI -0.51 to -0.05; 1 study, 985 participants) follow-up; both low-certainty evidence. Seven studies (5428 participants; low-certainty evidence) reported data on serious adverse events: two reported injuries relating to the exercise component of the intervention and five reported no effect of intervention on reported serious adverse events. Dietary and activity interventions versus control Dietary and activity interventions, compared with control, do not reduce BMI at short-term follow-up (MD 0.03, 95% CI -0.07 to 0.13; 11 studies, 3429 participants; high-certainty evidence), and probably do not reduce BMI at medium-term (MD 0.01, 95% CI -0.09 to 0.11; 8 studies, 5612 participants; moderate-certainty evidence) or long-term (MD 0.06, 95% CI -0.04 to 0.16; 6 studies, 8736 participants; moderate-certainty evidence) follow-up. They may have little to no effect on zBMI in the short term, but the evidence is very uncertain (MD -0.09, 95% CI -0.2 to 0.02; 3 studies, 515 participants; very low-certainty evidence), and they may not reduce zBMI at medium-term (MD -0.05, 95% CI -0.1 to 0.01; 6 studies, 3511 participants; low-certainty evidence) or long-term (MD -0.02, 95% CI -0.05 to 0.01; 7 studies, 8430 participants; low-certainty evidence) follow-up. Four studies (2394 participants) reported data on serious adverse events (very low-certainty evidence): one reported an increase in weight concern in a few adolescents and three reported no effect.

AUTHORS' CONCLUSIONS

The evidence demonstrates that dietary interventions may have little to no effect on obesity in adolescents. There is low-certainty evidence that activity interventions may have a small beneficial effect on BMI at medium- and long-term follow-up. Diet plus activity interventions may result in little to no difference. Importantly, this updated review also suggests that interventions to prevent obesity in this age group may result in little to no difference in serious adverse effects. Limitations of the evidence include inconsistent results across studies, lack of methodological rigour in some studies and small sample sizes. Further research is justified to investigate the effects of diet and activity interventions to prevent childhood obesity in community settings, and in young people with disabilities, since very few ongoing studies are likely to address these. Further randomised trials to address the remaining uncertainty about the effects of diet, activity interventions, or both, to prevent childhood obesity in schools (ideally with zBMI as the measured outcome) would need to have larger samples.

The joint associations of high birth weight and not having siblings with metabolic obesity phenotype among school-aged children and adolescents: A National Survey in China

OBJECTIVE

Birth weight (BW) and sibling's status are two important indicators of early intrauterine environment and subsequent living environment, but no evidence has emerged on their joint associations on metabolic obesity phenotype. To determine the joint associations between BW and single-child status with childhood metabolic obesity phenotype was our purpose.

METHODS

A cross-sectional assessment of children and adolescents aged 7-18 years was performed in Chinese seven provinces in 2013. We obtained anthropometric, blood pressure and biochemical measurements, and distributed questionnaires covering demographic, neonatal and lifestyle characteristics. The metabolic obesity phenotype was defined by 2018 consensus-based criteria. Logistic regression and restricted cubic spline models were applied to evaluate the associations of BW and metabolic obesity phenotype, and estimate the multiplicative interactions and the combined associations of BW and single-child status with metabolic obesity phenotype.

RESULTS

Of enrolled 12 346 children and adolescents, the prevalence of metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) was 1.96% and 3.03%. There were 8.95% and 4.03% children with high BW or low BW, and 67.55% did not have siblings. High BW was positively associated with MHO (OR = 1.94, 95%CI = 1.28-2.94). Single-child also had increased odds of MHO and MUO (p < 0.05), and it had joint associations with high BW showing 0.85- to 2.58-fold higher odds of MUO and MHO.

CONCLUSIONS

High BW and single-child status have joint positive associations with the subsequent odds of MHO and MUO, which should be jointly prevented through earlier screening and subsequent preventive strategies.

Change of weight status during school age and its association with late adolescent blood pressure: Results from a 15-year longitudinal study in China

Background

Change in obesity risk could be related to shift in high blood pressure (HBP) risk, while individualized influence of weight change on high blood pressure is in need of exploration.

Methods

A total of 16,446 children (53.47% boys) and 13,9021 effective annual measurements from 2006 to 2020 were recruited. Children's weight status, both at baseline and endpoint, was categorized as underweight, normal, overweight, and obese according to the age and sex-specific Body Mass Index z scores. HBP at late adolescence was defined with the last two measurements for each child. Populational attributable risk (PAR) of weight trait on HBP risk was calculated.

Results

Compared to children who maintained normal weight during follow-up, staying obese was associated with the highest HBP risk with OR of 6.39 (95% CI: 4.46, 9.15; p < 0.001) and PAR of 28.71% (95% CI: 21.58, 35.54) in boys, and OR of 6.12 (95% CI: 2.80, 13.37; p < 0.001) and PAR of 12.75% (95% CI: 4.29, 21.02) in girls. Returning from obese to normal weight was associated with lowered HBP risk, with ORs of 1.07 (95% CI: 0.69, 1.66; p = 0.771) in boys and 0.73 (95% CI: 0.25, 2.12; p = 0.566) in girls.

Conclusion

Weight loss program could be effective to reduce HBP risk during school age, while the underlying mechanism needs further exploration.

Could greenness modify the effects of physical activity and air pollutants on overweight and obesity among children and adolescents?

Greenness could theoretically increase the impact of physical activity (PA) and reduce the adverse effects of air pollution on overweight/obesity. However, no evidence systematically compares these two pathways, especially in longitudinal studies of children and adolescent's cohort. Greenness, PA, and air pollution were assessed by Normalized Difference Vegetation Index (NDVI), International Physical Activity Short Form, and 7 pollutants (PM₁, PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃). Each exposure was divided into low-/high-level groups based on the 50% quantile. Proportional hazards and logistic regression model were used to assess the associations of greenness, PA, pollutants with overweight/obesity. The incidence of overweight/obesity was 1.98% in the national survey, and the cumulative incidence and incidence density were 12.76% and 3.43 per 100 person-year in the dynamic cohort, separately. An increase of 0.1 units in NDVI was associated with a 12% lower risk of overweight/obesity, but no significant link between PA and incidence was observed. The HRs of the high-level of PM₁, PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃ on the risk of overweight/obesity were 2.21, 2.63, 1.88, 2.38, 1.33, 2.43, and 1.33 in the low-level of greenness, which was higher than those in the high-level of greenness. The AFs of PM₁, PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃ were 25.58%, 44.37%, 22.96%, 29.15%, 11.55%, 29.50%, and 10.92% in the low-level of greenness, which simultaneously was higher than those in the high-level of greenness. Moreover, the risk of overweight/obesity associated with high-level of greenness in the high-level of PM₁₀, SO₂, CO were 0.83, 0.81, and 0.83 respectively. Our findings confirmed that greenness has a moderating effect on the effects of air pollutants on childhood overweight/obesity especially in heavy-industry areas where PM₁₀, SO₂, and CO are the major pollutants, although it did not influence the association between PA and overweight/obesity risks.

Meeting 24-Hour Movement and Dietary Guidelines: Prevalence, Correlates and Association with Weight Status among Children and Adolescents: A National Cross-Sectional Study in China

China is confronted with a “double burden” of underweight and overweight/obesity in children and adolescents. This study aimed to investigate the prevalence and correlates of meeting 24 h movement and dietary guidelines among Chinese children and adolescents. Further, the study aimed to examine the association of meeting 24 h movement and dietary guidelines with weight status in Chinese children and adolescents. A total of 34,887 Chinese children and adolescents were involved. Only 2.1% of participants met the 24 h movement guidelines. Compared to those who met all three 24 h movement guidelines, those who only met the sleep duration guideline was significantly associated with a higher risk of underweight (p < 0.05), and those who only met the moderate-to-vigorous physical activity, or screen time guidelines were significantly associated with a higher risk of overweight/obesity (p < 0.05). Compared with those meeting the dietary guidelines, those who did not meet the soft drink intake guideline had a significantly lower risk of underweight (p < 0.05), those who did not meet the fruit intake guideline had a significantly lower risk of overweight/obesity (p < 0.05), and those who did not meet the milk intake guideline showed a significantly higher risk of overweight/obesity (p < 0.001). These findings indicate a significant association between meeting the 24 h movement and dietary guidelines and weight status among Chinese children and adolescents.

Prevalence and associated factors of metabolic body size phenotype in children and adolescents: A national cross-sectional analysis in China

BACKGROUND

Metabolically healthy obesity (MHO) is a group of subjects with overweight/obesity who present a metabolically healthy profile; however, associated factors are complex and are far from completely understood. The aim of the current study was to estimate the prevalence of different metabolic body size phenotypes and investigate the associated factors in Chinese children and adolescents.

METHODS

A cross-sectional survey was conducted of 12,346 children and adolescents aged 7-18 years from seven provinces in China in 2013. Anthropometric, blood pressure, and biochemical measurements were obtained. A multi-component questionnaire covering demographic, neonatal, and lifestyle characteristics was administered. The classification of metabolic body size phenotype based on three definitions was compared. With metabolically healthy with normal weight (MHNW) as a reference group, logistic regression analyses were used to estimate the potential effects of associated risk factors, with adjustment for age, sex, single-child status, and residence area.

RESULTS

The prevalence of MHNW, MHO, metabolically unhealthy with normal weight (MUNW), and metabolically unhealthy overweight/obesity (MUO) phenotype was 68.6%, 2.0%, 26.4%, and 3.0%, respectively. There were 39.3% MHO and 60.7% MUO among obese participants and 72.2% MHNW and 27.8% MUNW among those with normal weight. Compared to cardiometabolic risk factor (CMRF) criteria and metabolic syndrome (MetS) component definition, the application of the 2018 consensus-based definition may identify more children with abnormal cardiovascular risks, independent of weight status. Compared to younger children, older-aged adolescents were positively associated with higher risks of MUNW (odds ratio (OR) = 1.38, 95% CI = 1.27-1.50) and MUO (OR = 1.29, 95% CI = 1.04-1.60), while factors positively associated with MHO were younger age, single-child status, urban residence, high birth weight, prolonged breastfeeding duration, parental overweight/obesity status, long screen time, and less physical activity.

CONCLUSION

There were still a high proportion of children and adolescents at high cardiometabolic risk in China. Our findings reinforce the need for cardiometabolic risk prevention in children and adolescents irrespective of their weight statuses, such as parental educational programs and healthy lifestyle interventions.

Effectiveness of national multicentric school-based health lifestyles intervention among chinese children and adolescents on knowledge, belief, and practice toward obesity at individual, family and schools' levels

BACKGROUND

This study aims to evaluate the effectiveness of the trial of national multicentric school-based health lifestyles intervention toward childhood obesity on the KBP at individual, family and schools' levels.

METHODS

The national trial was a multi-centered, cluster-controlled trial, which was conducted in seven provinces from September 2013 to February 2014, aiming at preventing childhood overweight and obesity. Integrated intervention strategies focused on changing specific practice related to energy intake and expenditure, such as decreasing the consumption of sweetened fizzy drinks, increasing the consumption of vegetables, ensuring proper protein intake, reducing sedentary practice including screen time, and maintaining at least 1 h of moderate to vigorous physical activity. A total of 27,477 children and adolescents in the control group and 30,997 in the intervention group were recruited with a mean follow-up period of 6.7 months. The binomial response mixed-effects model was used for assessing the effects of the national school-based health lifestyles intervention on obesity-related KBP at students individual, parents' and schools' levels.

RESULTS

Children and adolescents in the intervention group mastered better obesity-related knowledge, and they had higher correct response rates to all questions about obesity-related knowledge compared to the control group (P < 0.05). In terms of obesity-related belief, individuals in the intervention group was more motivated than the control group, participants in the intervention group had higher correctness of 71.18, 52.94, and 56.60% than the control group of 68.61, 49.86, and 54.43%, (P < 0.05). In addition, healthier habits of eating breakfast and drinking milk every day were observed in the intervention group. For the beliefs toward obesity, parents of the intervention group had higher correctness than the control group. At the same time except for the fruit consumption, other obesity-related practice in the intervention group were healthier than the control group (P < 0.05). Except for some beliefs and practice, the intervention effect at the parent level was not significant in other aspects.

CONCLUSION

The obesity-related knowledge and beliefs of children and adolescents got improved significantly. However, the effects on the knowledge, beliefs and certain practices of their parents and school administrators failed to reach significance.

Impact of short-term change of adiposity on risk of high blood pressure in children: Results from a follow-up study in China

This study aimed to examine the impact of short-term adiposity change on risk of high blood pressure (HBP), and to assess the low limit range of body mass index (BMI) and waist-to-height ratio (WHtR) reduction proposed to decrease the HBP risk in children. Children were longitudinally surveyed at baseline and after a short-term follow-up. General obesity (GOB) is categorized by age and gender-specific BMI cut-off points, abdominal obesity (AOB) by WHtR. Logistic regression model was used to estimate relations between adiposity change and HBP risk with adjustment of covariates. A total of 28,288 children (median of baseline age:10 years) were involved with follow-up of 6.88±1.20 months. After the follow-up, 9.4% of the children had persistent general obesity (GOB), 2.8% converted from GOB to non-GOB, 0.9% had newly developed GOB. When compared with children remained non-GOB, children with continuous GOB status, newly developed GOB, converting from GOB to non-GOB had 5.03-fold (95%CI: 4.32~5.86), 3.35-fold (95%CI: 1.99~5.65), 2.72-fold (2.03~3.63) HBP risk, respectively. Similar findings were observed for abdominal obesity (AOB). Reduction of 0.21–0.88 kg/m² of baseline BMI (0.86–3.59%) or 0.009–0.024 of baseline WHtR (1.66–4.42%) in GOB or AOB children, respectively, was associated with significant decrease in HBP risk. Children with persistent obesity, newly developed obesity, or converting from obese to non-obese had significantly higher HBP risk. For children with GOB or AOB, reduction of <3.6% in BMI or <4.5% in WHtR could decrease the HBP risk.

The Association Between Sedentary Screen Time, Non-screen-based Sedentary Time, and Overweight in Chinese Preschool Children: A Cross-Sectional Study

Introduction: Less is known about the effects of the different domains of sedentary behaviors on healthy weight in young children. This cross-sectional study examined the association between sedentary screen time (SST), non-screen-based sedentary time (NSST), and overweight (and obesity) in Chinese preschoolers. Methods: Data were collected from the Physical Activity and Health in Tianjin Chinese Children study (PATH-CC), involving healthy children 3-6 years old and their families. Children's overweight status was classified according to the international (IOTF) childhood BMI cut-offs. SST and NSST were reported in minutes/day by parents using the leisure-time sedentary behaviors questionnaire. Logistic regression models adjusted by sex, age, socioeconomic status, outdoor play, and sleep duration were used. Results: In a total of 971 children (55.4% boys), 11.8% were overweight. Generally, children spent 1 h/day in SST and 1 h/day in NSST. Multiple models showed that children who spent more time in SST were more likely to be overweight [OR and 95% CI: 1.22 (1.03-1.45)]. No correlation between time spent on NSST and children with overweight was found (P > 0.05). Conclusions: This study indicated that children who spent more time in SST were more likely to be overweight, but a null correlation between NSST and overweight was found. Longitudinal studies designed to identify associations between exposures to screen media and changes in metabolic parameters during a child's early years are needed.