Trends in overweight and socioeconomic inequality among children and adolescents aged 7–18 years in China from 2010 to 2020

Abstract

Objectives

The aim of this study was to investigate the trends in overweight and the trends in socioeconomic inequality in overweight among Chinese children and adolescents aged 7–18 years in China from 2010 to 2020.

Methods

Data for this study were obtained from the China Family Panel Studies (CFPS), which conducted surveys every 2 years between 2010 and 2020. A total of 27,703 records were included, involving 12,263 children and adolescents aged 7–18 years. Height and weight were self- or parent/guardian-reported. The prevalence of overweight was calculated on the basis of 3 socioeconomic indicators (father’s education level, mother’s education level, and household income) using WHO and Chinese standards. According to WHO standards, overweight is defined as a sex- and age-specific BMI-Z score > 1. According to China’s WS/T 586–2018 “Screening for Overweight and Obesity in School-Aged Children and Adolescents,” overweight is defined as a sex- and age-specific BMI greater than or equal to the corresponding “overweight” threshold. And socioeconomic inequality was quantified by the relative index of inequality (RII). Trends in the RII of prevalence were estimated by sample-weighted linear regression.

Results

Between 2010 and 2020, the overall prevalence of overweight among children and adolescents aged 7 to 18 in China continued to rise, increasing from 15.8% in 2010 to 24.8% in 2020. After adjusting for sex and age, it was found that the prevalence rate was higher among boys and children. During the study period, socioeconomic inequalities in overweight among children and adolescents persisted (RII ≠ 1). In the father’s educational attainment subgroup, the RII for girls decreased from 1.087 in 2010 to 1.016 in 2020, indicating a narrowing of socioeconomic inequalities (P = 0.029). Girls with higher levels of father’s educational attainment had a greater risk of overweight. In the mother’s educational attainment subgroup, the RII for boys increased from 0.889 in 2010 to 1.025 in 2020, indicating an expansion of socioeconomic inequality (P = 0.038). The high-risk group for overweight among boys shifted from lower to higher levels of maternal educational attainment. In 2020, the RIIs for children and adolescents on the basis of family income, fathers’ education level and mothers’ education level were 0.936, 0.997 and 1.012, respectively.

Conclusions

This study revealed that the prevalence of overweight among Chinese children and adolescents continue to increase from 2010 to 2020 and that socioeconomic inequality in overweight prevalence increase among boys and decrease among girls. Intervention policies and measures should be developed for high-risk groups to prevent the prevalence of overweight and reduce socioeconomic inequality.

Electronic supplementary material

The online version of this article (10.1186/s12889-025-24170-5) contains supplementary material, which is available to authorized users.

Introduction

Overweight and obesity in children and adolescents is associated with poor health outcomes across the life course and is now a public health issue of shared global concern [1]. The Noncommunicable Disease Risk Factor Collaboration (NCD-RisC; a global network of health scientists that provides data on risk factors for NCDs in 200 countries and territories.) reported that global obesity rates among children and adolescents in 2022 (6.9%) were more than four times higher than those reported in 1990 (1.7%) [1], and in Asia, the prevalence of overweight among children and adolescents has significantly increased between 2010 and 2022. For example, in China, (the prevalence of overweight among girls rose from 13.0% in 2010 to 19.9% in 2022, and the prevalence of overweight among boys increased from 21.1% in 2010 to 24.9% in 2022), and South Korea (the prevalence of overweight among girls increased from 21.5% in 2010 to 24.6% in 2022, and the prevalence of overweight among boys increased from 33.4% in 2010 to 43.0% in 2022). China saw the largest increase [2]. Overweight and obesity increase the risk of of diabetes, hypertension [3], cardiovascular diseases, and some cancers [4], posing significant health risks to children and adolescents. In addition, overweight in children and adolescents can persist into adulthood [5], necessitating routine weight monitoring of child and adolescent weight.

In recent years, many studies have noted that the prevalence of overweight and obesity among children and adolescents appear to have stabilized or declined [6], but this is not the case for all socioeconomic backgrounds and regions [7]. To systematically examine the multidimensional drivers of childhood overweight and obesity, this study is based on a socioecological model that assumes that health outcomes result from dynamic interactions at the individual, community, and societal levels [8]. In the context of childhood adolescent overweight and obesity, this framework emphasizes how childhood adolescent biometrics (e.g., sex and age), influences from the family and school levels related to social and environmental dimensions, and community and societal externalities combine to influence obesity risk [9, 10].Research has shown that the prevalence of overweight and obesity in children and adolescents is associated with socioeconomic status (SES) [11]. In general, socioeconomic inequality is related to classical socioeconomic indicators (education, occupation and income), while the level of occupation is influenced by the level of education [12]. Many studies have used parental education level and household economy to measure individual SES and have reported social gradients in overweight and obesity rates among children and adolescents. The direction of these social gradients varies depending on the level of economic development of the country [13–15].

In addition, trends in overweight and obesity prevalence among children and adolescents with different SES are not consistent. Significant increases in the prevalence of overweight and obesity among children and adolescents with low SES and stabilization of the prevalence of overweight and obesity among children and adolescents with high SES have been reported in many countries with high SES, such as Israel, Sweden, and the United States[16–19], due to the fact that trends in overweight and obesity among economically advantaged children and adolescents mask changes among marginalized children and adolescents[18, 20], and there is an urgent need to reduce the disparities in social inequalities in overweight and obesity among children and adolescents. However, opposite trends were found in middle-income and low-income countries, whereby overweight and obesity rates among children and adolescents with high SES have increased over time and underlying factors such as lack of physical activity, prolonged screen time, poor dietary patterns, sedentary behaviors, and barriers to breastfeeding, which accompanied high SES, were reported as contributing to higher rates of overweight and obesity among children and adolescents. This phenomenon has been observed in Malaysia, India, and some South Asian countries, Morocco, and some South African countries, as well as Mexico, all of which are middle- and low-income countries [21–26].

In China, government reports show that despite significant results in the prevention and control of chronic noncommunicable diseases [27], the national overweight and obesity rates continue to rise. Moreover, studies have indicated a dramatic increase in overweight and obesity among Chinese children and adolescents since the 1980s, with overweight rates increasing over 18-fold and obesity rates increasing more than 75-fold by 2019 [28]. This upward trajectory is projected to continue, potentially affecting tens of millions of youths [29] and underscoring the urgency of targeted interventions. However, there is a lack of research on trends in overweight and obesity among Chinese children and adolescents across different socioeconomic gradients. Guided by the socioecological model, the analytic design of this study reflects this multilevel perspective. First, this study stratified the analysis by sex and age to capture individual-level heterogeneity. Second, socioeconomic status indicators (household income, parental education) were selected to characterize interpersonal and community-level resource differences. Third, repeated cross-sectional data allowed for tracking how the above included indicators influenced the prevalence of overweight among children and adolescents over time.

Therefore, by using data from the 2010 to 2020 China Family Panel Studies (CFPS; a nationally representative repeated cross-sectional survey tracking social, economic, and health dynamics in Chinese households), this study aimed to investigate the trends in overweight and the trends in socioeconomic inequality in overweight among Chinese children and adolescents aged 7–18 years in China from 2010 to 2020.

Data and methods

Data sources

Data for this study were obtained from the CFPS, a nationally representative repeated cross-sectional survey in China that is conducted every 2 years. The CFPS collects data about individuals, households, and communities at three levels, reflecting changes in China’s society, economy, demographics, education, and health [30]. The baseline survey for the CFPS was conducted in 2010 via multistage, implicitly stratified, population size-proportional systematic probability sampling to include 16,000 households in 25 provinces/autonomous regions/municipalities directly under the central government (excluding Tibet, Qinghai, Xinjiang, Ningxia, Inner Mongolia, Hainan, Hong Kong, Macao, and Taiwan). Given that the 25 provinces/autonomous regions account for approximately 95% of the total population of the country (excluding Hong Kong, Macau and Taiwan), they can be considered a nationally representative sample. Sampling was conducted in three stages: administrative district/county sampling, village council sampling, and household sampling. Stratification was based on administrative divisions and socioeconomic levels, with local gross domestic product (GDP) per capita as the main socioeconomic indicator. The detailed sampling information has been described previously [30]. The CFPS data are obtained via public release, and this study uses data from 2010, 2012, 2014, 2016, 2018 and 2020.

Data on children aged 7–18 years in the CFPS from 2010 to 2020 were extracted in September 2024 for this study. A total of 39,192 records were first included on the basis of age, and then 10,162 records with missing data (including missing information on sex, height, weight, parents’ educational attainment, and household income) were excluded. Next, the WHO Anthro Survey Analyzer (a standardized tool for promoting best practices on data collection, analyses and reporting of anthropometric indicators) [31] was then used to exclude 1,327 records with extreme values of height, weight or body mass index(BMI), defined as an age- and sex- adjusted z-score of <  − 5 or >  + 5, as these were probably due to registration errors or a severe disorder [32]. And the points selected for the Z scores are arbitrary cutoff points specified by the NHMS [33]. A total of 27,703 records were eventually included, with 12,263 individuals tracked longitudinally, averaging 2.3 follow-ups per person. The number of records in 2010, 2012, 2014, 2016, 2018, and 2020 were 5,289, 4,827, 4,727, 3,494, 5,029, and 4,337, respectively. The sample size was generally consistent across sexes and ages.

Measurement methods

BMI was calculated as weight (kg)/height (m)2, where height and weight were reported for children by their parents/ guardians or by themselves. Self-reported for those aged 16 and above, reported by parents/guardians for those under 16. Overweight was defined as sex- and age-specific BMI-Z scores > 1 according to the WHO criteria [34, 35]. According to China’s WS/T 586–2018 “Screening for Overweight and Obesity in School-Aged Children and Adolescents”, overweight was defined as having a sex- and age-specific BMI greater than or equal to the corresponding “overweight” cutoff value [36].

SES

SES is usually measured by indicators of income, education, and occupation, and since occupation is an unordered categorical variable with some subjective indicators [37] and is influenced by education level [12], this study uses per capita household income per year (yuan per/year), the father’s education level, and the mother’s education level as SES indicators. The highest level of completed education of the parents represents their education level. The answers include: illiterate/semi-illiterate, elementary school, junior high school, high school, three-year college, four-year college/undergraduate, master’s degree, doctoral degree (post-doctoral degrees not mentioned in the questionnaire are included in doctoral degrees by default), and never studied, which are categorized in this study into three levels such as elementary school and below, junior high school, high school and above. Household income (yuan/year) is the annual net income of all members of the household, which better reflects the economic level of the household throughout the year by deducting production costs from the total income. It is based on the self-reported annual income of all members of the household, including income from all economic sources such as wages, funds, relief and subsidies. If the annual income of a household is negative, it is recorded as 0. Per capita household income for each survey year is the total household income divided by the size of the household, which is divided equally into three categories, tertiles 1 to 3, with tertile 1 representing the lowest income level and tertile 3 representing the highest income level.

Data analysis

Descriptive data are expressed as the means and 95% confidence intervals, and categorical data are expressed as percentages and 95% confidence intervals. Trends in height for the total population were estimated by linear regression models adjusted for sex and age, with the dependent variable being height and the independent variables being year, sex (male and female) and age (continuous variables). To analyze trends in height for boys and girls, the independent variables of the linear regression model were year and age (continuous). When analyzing height trends for the two age-classified populations (children aged 7–12 years and adolescents aged 13–18 years), the independent variables for the linear regression models were year, sex, and age (continuous). Trends in weight and BMI for the total population and subgroups were estimated in the same way as those for height. The prevalence of overweight in the total study population and subgroups was calculated for each survey year and categorized by sex and age. Trends in the prevalence of overweight in the total population were estimated by log-binomial regression to estimate prevalence ratios (PR) by year (continuous variable), with sex and age included in the model. Prevalence trend estimates for each subgroup were consistent with the total population trend estimates, with age included in the sex subgroup, sex and age in the age-categorized subgroup, and sex and age in the SES indicator subgroup. The relative index of inequality (RII) based on the PR was calculated for each year as an indicator of inequality. PR was calculated for each SES indicator for each year by logit binomial regression adjusting for sex and age, with elementary school and below as the reference for parental education and tertile 1 for household economy per capita. The RII is a measure of relative inequality, i.e., the ratio of the health status of the subgroups of the highest to the lowest SES levels.

The RII was calculated by Stata’s “riigen” command, where an RII equal to 1 indicates no inequality, an RII greater than 1 indicates a higher risk of overweight for economically advantaged groups, and an RII less than 1.0 indicates a higher risk of overweight for economically disadvantaged groups [38]. Trends in the RII were estimated by linear regression, with year as the independent variable and sample size as the weight. p < 0.05 was considered a statistically significant difference. All the statistical analyses were performed by Stata 17.0 (StataCorp LLC, College Station, TX).

Results

Table 1 shows the distribution of the study sample by sex, age group and three socioeconomic indicators. Over the study period, boys and children (7–12 years) represented an increasing proportion of the sample, while girls and adolescents (13–18 years) declined. Income distribution shifted marginally: middle-income families increased slightly, while both low- and high-income families declined. Parental education levels shifted toward higher attainment, with the most educated group steadily increasing, whereas the least educated group peaked in 2016 before declining.

Table 1.

General characteristics of the study population from 2010 to 2020

Characteristics	Year						Annual change	p for trend1
	2010	2012	2014	2016	2018	2020
Total (n)	5289	4827	4727	3494	5029	4337
Age,mean(year)	12.58 ± 3.34	12.60 ± 3.50	12.30 ± 3.44	12.23 ± 3.50	12.01 ± 3.36	11.99 ± 3.32	− 0.069	< 0.001
Subgroups
Sex (%)
Boys	51.4(50.0–52.7)	51.7(50.3–53.1)	52.1(50.7–53.6)	53.7(52.0–55.3)	53.4(52.0–54.7)	53.4(52.0–54.9)	0.239	0.16
Girls	48.6(47.3–50.0)	48.3(46.9–49.7)	47.9(46.4–49.3)	46.3(44.7–48.0)	46.6(45.3–48.0)	46.6(45.1–48.0)	− 0.239	0.16
Age class (%)
Children	48.4(47.0–49.7)	48.0(46.6–49.4)	52.4(51.0–53.9)	54.4(52.7–56.0)	55.9(54.5–57.3)	56.5(55.0–57.9)	0.946	0.003
Adolescents	51.6(50.3–53.0)	52.0(50.6–53.4)	47.6(46.1–49.0)	45.6(44.0–47.3)	44.1(42.7–45.5)	43.5(42.1–45.0)	− 0.946	0.03
Household income (%)
High	33.4(32.2–34.7)	33.0(31.7–34.3)	33.0(31.7–34.4)	33.0(31.5–34.6)	33.0(31.7–34.3)	33.0(31.6–34.4)	− 0.029	0.158
Middle	33.5(32.3–34.8)	34.0(32.7–35.3)	33.9(32.6–35.3)	34.0(32.4–35.6)	34.0(32.7–35.3)	34.0(32.6–35.4)	0.037	0.125
Low	33.3(31.8–34.3)	33.0(31.7–34.3)	33.1(31.7–34.4)	33.0(31.5–34.6)	33.0(31.7–34.3)	33.0(31.6–34.4)	− 0.023	0.117
Father’s education (%)
Junior high school and more	18.6(17.6–19.7)	20.6(19.5–21.8)	20.2(19.0–21.3)	13.4(12.3–14.6)	24.1(22.9–25.3)	30.4(29.1–31.8)	0.896	0.219
Junior middle school	38.6(37.2–39.9)	46.1(44.7–47.5)	36.2(34.9–37.6)	22.2(20.9–23.6)	40.3(38.9–41.6)	41.5(40.0–43.0)	− 0.241	0.835
Primary school and below	42.9(41.5–44.2)	33.3(32.0–34.7)	43.6(42.2–45.0)	64.3(62.7–65.9)	35.7(34.4–37.0)	28.1(26.8–29.4)	− 0.659	0.713
Mother’s education (%)
Junior high school and more	13.5(12.6–14.5)	14.9(12.6–14.5)	14.6(13.6–15.6)	7.7(6.9–8.6)	19.6(18.6–20.8)	25.3(24.0–26.6)	0.946	0.214
Junior middle school	28.7(27.5–30.0)	35.4(34.0–36.7)	30.7(29.4–32.0)	15.9(14.7–17.1)	37.1(35.8–38.5)	41.1(39.6–42.5)	0.747	0.541
Primary school and below	57.7(56.4–59.1)	49.7(48.3–51.1)	54.8(53.3–56.2)	76.4(75.0–77.8)	43.2(41.9–44.6)	33.6(32.2–35.0)	− 1.691	0.388

Values are presented as %. ¹The p-value for trend was tested for each row of the table

Table 2 reports self-reported anthropometric measurements and the overall prevalence of overweight using the WHO and Chinese standard definitions. Height, weight and BMI increased linearly in all subgroups (P < 0.01). According to the WHO criteria, the overall prevalence of overweight increased annually from 2010 to 2020, from 15.8% in 2010 to 24.8% in 2020. The same trend was found in the prevalence of overweight defined according to the Chinese criteria, increasing from 15.4% in 2010 to 23.7% in 2020. Increasing trends were also observed in all the subgroups (Fig. 1 and Table 2). The prevalence of overweight was greater in boys than in girls and in children than in adolescents under both criteria.

Table 2.

Self-reported anthropometric indicators of height, weight, BMI, and overall prevalence of overweight based on WHO and Chinese overweight criteria

Variables	Year						Annual change	p for trend1
	2010	2012	2014	2016	2018	2020
Height (cm)
Total	146.17 ± 19.66	147.37 ± 19.83	146.69 ± 19.64	146.62 ± 19.79	147.05 ± 18.92	148.70 ± 18.30	0.163	< 0.001
Sex
Boys	147.27 ± 21.46	148.99 ± 21.37	148.20 ± 20.88	148.08 ± 21.37	148.85 ± 20.26	150.42 ± 19.60	0.217	< 0.001
Girls	145.01 ± 17.49	145.63 ± 17.88	145.05 ± 18.07	144.94 ± 17.65	144.99 ± 17.02	146.72 ± 16.47	0.087	0.047
Age class
Children	130.88 ± 15.07	131.86 ± 15.41	132.66 ± 15.20	133.00 ± 15.15	134.53 ± 14.38	136.78 ± 14.14	0.540	< 0.001
Adolescents	160.50 ± 10.57	161.67 ± 10.52	162.16 ± 10.00	162.84 ± 10.06	162.92 ± 9.94	164.16 ± 9.32	0.325	< 0.001
Weight (kg)
Total	39.27 ± 18.87	40.50 ± 14.28	40.14 ± 14.21	40.35 ± 14.90	40.82 ± 14.70	42.18 ± 15.18	0.223	< 0.001
Sex
Boys	40.57 ± 15.27	30.80 ± 12.34	41.59 ± 15.43	41.78 ± 16.20	42.49 ± 15.92	43.99 ± 16.52	0.263	< 0.001
Girls	37.89 ± 12.06	42.10 ± 15.71	38.56 ± 12.55	38.70 ± 13.04	38.91 ± 12.90	40.10 ± 13.18	0.162	< 0.001
Age class
Children	29.17 ± 8.88	30.04 ± 9.00	30.61 ± 9.33	30.67 ± 9.37	31.78 ± 9.79	33.24 ± 10.53	0.367	< 0.001
Adolescents	48.73 ± 10.66	50.16 ± 11.08	50.64 ± 10.87	51.88 ± 11.70	52.28 ± 11.55	53.77 ± 12.15	0.467	< 0.001
BMI(kg/m2)
Total	17.85 ± 3.32	18.14 ± 3.41	18.15 ± 3.51	18.21 ± 3.63	18.34 ± 3.69	18.53 ± 3.82	0.059	< 0.001
Sex
Boys	18.10 ± 3.44	18.38 ± 3.55	18.36 ± 3.58	18.42 ± 3.68	18.60 ± 3.83	18.84 ± 3.95	0.063	< 0.001
Girls	17.59 ± 3.17	17.88 ± 3.21	17.91 ± 3.43	17.96 ± 3.55	18.05 ± 3.50	18.18 ± 3.63	0.051	< 0.001
Age class
Children	16.88 ± 3.52	17.17 ± 3.64	17.26 ± 3.72	17.19 ± 3.66	17.37 ± 3.68	17.55 ± 3.84	0.056	< 0.001
Adolescents	18.76 ± 2.83	19.03 ± 2.90	19.12 ± 2.98	19.41 ± 3.19	19.58 ± 3.30	19.81 ± 3.39	0.102	< 0.001

Variables	Year						Annual change	p for trend1
	2010	2012	2014	2016	2018	2020
WHO definition
Total	15.8(14.9–16.9)	18.1(17.1–19.2)	19.4(18.3–20.5)	20.9(19.5–22.2)	23.4(22.2–24.6)	24.8(23.5–26.1)	1.028	< 0.001
Sex
Boys	19.6(18.1–21.1)	22.3(20.8–24.0)	23.3(21.7–25.0)	25.1(23.2–27.1)	28.6(26.9–30.3)	30.5(28.6–32.4)	1.030	< 0.001
Girls	11.9(10.7–13.2)	13.6(12.3–15.1)	15.1(13.7–16.6)	15.9(14.2–17.8)	17.4(15.9–19.0)	18.3(16.7–20.0)	1.024	< 0.001
Age class
Children	26.5(24.9–28.3)	29.9(28.0–31.8)	30.0(28.2–31.8)	29.9(27.9–32.0)	31.4(29.7–33.1)	31.8(30.0–33.7)	1.013	< 0.001
Adolescents	5.8(5.0–6.8)	7.3(6.3–8.4)	7.6(6.6–8.8)	10.1(8.7–11.7)	13.2(11.9–14.7)	15.7(14.1–17.4)	1.100	< 0.001
China definition
Total	15.4(14.4–16.3)	17.5(16.5–18.6)	18.8(17.7–19.9)	19.8(18.5–21.1)	22.4(21.2–23.5)	23.7(22.5–25.0)	1.027	< 0.001
Sex
Boys	18.7(17.3–20.2)	21.1(19.5–22.7)	22.2(20.6–23.9)	23.3(21.4–25.3)	26.9(25.2–28.6)	28.6(26.8–30.4)	1.029	< 0.001
Girls	11.8(10.6–13.1)	13.7(12.4–15.2)	15.1(13.7–16.6)	15.7(14.0–17.6)	17.2(15.7–18.9)	18.1(16.5–19.9)	1.024	< 0.001
Age class
Children	24.7(23.1–26.5)	28.1(26.3–29.9)	28.0(26.3–29.8)	27.3(25.4–29.4)	29.2(27.6–30.9)	29.5(27.7–31.4)	1.011	0.005
Adolescents	6.6(5.7–7.5)	7.8(6.8–8.9)	8.6(7.5–9.8)	10.8(9.4–12.4)	13.7(12.3–15.2)	16.2(14.6–17.9)	1.094	< 0.001

¹The p-value for trend was tested for each row of the table. BMI, body mass index

Fig. 1.

Trends in the prevalence of overweight among Chinese children and adolescents of different sexes and ages according to family income, parents’ education level from 2010 to 2020

Figure 2 shows the temporal trends in socioeconomic inequality using the PR-based RII. Overall, socioeconomic inequality in terms of overweight among children and adolescents was present during the study period (RII ≠ 1). Significant time trends (p < 0.05) were found only in two subgroups, girls in father’s education and boys in mother’s education. Socioeconomic inequality among girls in the father’s education subgroup narrowed over time, with the RII decreasing from 1.087 (95% CI, 1.032–1.145) in 2010 to 1.016 (95% CI, 0.994–1.040) in 2020, consistently reflecting the greater risk of disease associated with higher levels of father’s education. Socioeconomic inequality among boys in the subgroup of mothers’ education level widened over time, with the RII increasing from 0.889 (95% CI, 0.850–0.930) in 2010 to 1.025 (95% CI, 1.005–1.044) in 2020, suggesting that the high-risk group for the disease reversed from a lower level of mothers’ education to a higher level of mothers’ education. No clear trends (p > 0.05) over time were found in the other subgroups (supplementary Table 3–6). For most socioeconomic indicators, RIIs were higher for girls than for boys; similarly, RIIs were higher for children than for adolescents. In terms of the most recent RIIs, children and adolescents with lower family incomes (RII = 0.936, 95% CI, 0.826–1.062), lower fathers’ education levels (RII = 0.997, 95% CI, 0.983–1.010) and higher mothers’ education levels were at greater risk (RII = 1.012, 95% CI, 1.000–1.025) (supplementary Table 5 and 6).

Fig. 2.

Trends of the relative index of inequality based on the prevalence ratio according to household income, father’s education, and mother’s education from 2010 to 2020. The closed dashed lines represent 95% confidence intervals. B: boys; G: girls; C: children; A: adolescents

Overweight was defined as sex- and age-specific BMI-Z scores > 1 according to the WHO criteria.

Discussion

This study investigated trends in the prevalence of overweight among children and adolescents and socioeconomic inequalities in overweight among Chinese children and adolescents using nationally representative data. The study revealed that the prevalence of overweight among Chinese children and adolescents increased between 2010 and 2020, from 15.8% in 2010 to 24.8% in 2020 under international standards, and from 15.4% in 2010 to 23.7% in 2020 under Chinese standards. Overweight prevalence was higher for boys than for girls, and for children than for adolescents. Also, the study pronounced socioeconomic inequalities in overweight among Chinese children and adolescents. No significant trends over time were found in any of the subgroups, except that socioeconomic inequality decreased over time for girls in the father’s education subgroup (annual change of RII =  − 0.008, p = 0.029) and increased over time for boys in the mother’s education subgroup(annual change of RII = 0.011, p = 0.038). The most substantial socioeconomic inequality was observed in the mother’s education subgroup for boys, where the RII increased from 0.889 (2010) to 1.025 (2020).This widening gap (annual change RII = 0.011, p = 0.038) represented the strongest socioeconomic gradient across all indicators.

In recent years, to address the growing trend of overweight and obesity among children and adolescents, the Chinese government has implemented a series of national intervention programs and established a government-led, multisectoral prevention and control system for overweight and obesity among children and adolescents [39]. Some studies have also monitored and predicted trends in overweight and obesity among Chinese children and adolescents [28] and proposed corresponding prevention and control strategies [4]. However, many studies have shown that the prevalence of overweight among Chinese children and adolescents continues to increase [28, 40–42], which is consistent with the results of the present study. This may be related to insufficient intake of dietary micronutrients among children and adolescents [43], the increased consumption of ultra-processed foods (i.e., foods with low nutritional value but high energy density) during the process of rapid economic development [44], the lack of health awareness [45] and the change in the mode of transportation to school from walking to using motor vehicles [46], the decrease in energy consumption due to the increase in the use of media among children and adolescents during the process of information technology [24], and the influence of advertisements of energy-rich foods [47], among others. In addition, the “Nutrition Improvement Program for Rural Compulsory Education Students” implemented by the Government of China in 2011, has ameliorated the problem of malnutrition among children and adolescents, but has not been effective in limiting over-nutrition, which may be associated with an increased risk of overweight among children and adolescents [48]. This will pose a serious threat to the current health of children and adolescents in China and increase the burden of health care in China in the future. There are sex differences in overweight among children and adolescents, with the prevalence of overweight being greater among boys than among girls. The similar results consistent with those of the present study have been reported in several studies on trends in the prevalence of overweight and obesity in Chinese children and adolescents [42, 49–51]. This may be due to the psychological differences accompanying sex differences in the Chinese social context [52] and aesthetic differences (girls’ slimness is regarded as beautiful) in the Chinese social context [53]. Also, In the context of the traditional Confucian “patriarchal” culture in China, where boys are required to be present at religious ceremonies, inherit property from boys [54], and where the physical strength of boys has higher economic rewards in the context of the traditional agrarian economy [55], the traditional belief that boys are more important than girls may have led parents to invest more in boys [56], and boys may be more likely to be over-cared for and over-nourished [57], among other important links. In addition, estrogens may prevent the development of overweight and obesity by improving the metabolic phenotype of adipose tissue, whereas androgens promote fat accumulation and increase the risk of overweight and obesity [58]. Maternal exposure to excessive hormones and endocrine disruptors during pregnancy or early postpartum may transmit obesity susceptibility to offspring through epigenetic mechanisms, promoting the programming of adipocytes in children [59], and increasing susceptibility to overweight and obesity in children.

Moreover, in terms of age stratification, the detection rate of overweight in children is consistently higher than that in adolescents, and several studies comparing the prevalence of overweight and obesity in different age groups have reported the same trend as that reported in the present study [60, 61], which suggests that the tendency toward overweight is more serious in the elementary school stage and early pubertal development. However, this age difference contrasts with Europe, where the prevalence of overweight and obesity in children and adolescents increases with age [62, 63]. This may be related to differences in family parenting behaviors in the context of Chinese Eastern culture, such as parental indulgence and poor self-control in the younger age groups [64, 65], grandparents’ erroneous perceptions (e.g., obese children are healthy), knowledge (e.g., foods high in energy or fat content are nutritious), and behaviors (e.g., overfeeding and not allowing children to do household chores) in the Chinese family, and the conflict between the concepts of childcare and the parents and school teachers [66]. In Europe, reduced physical activity, increased sedentary time [67], and decreased resting energy expenditure [68] in adolescents indirectly contribute to metabolic slowdown. Notably, prevalence of overweight increased by 5.3% in absolute terms in children and 9.9% in adolescents over the ten-year period, with a greater increase in adolescents than in children. This may be related to the fact that China’s recent “Healthy China 2030” policies and measures have been effective in regulating children’s diet and physical activity in schools, but have not adequately covered the adolescent population [29]. At the same time, adolescents at the secondary school level are increasingly burdened with schoolwork in a “score-first” society, where time for physical activity has been compressed, resulting in poor implementation of physical fitness interventions [69].

In addition, the socioeconomic inequalities that persist in overweight children and adolescents are worrisome. In 2020, children and adolescents whose mothers had higher levels of education were at greater risk of being overweight (RII = 1.012, 95% CI, 1.000 to 1.025), and those with lower family income (RII = 0.936, 95% CI, 0.826 to 1.062) and fathers with lower levels of education (RII = 0.997, 95% CI, 0.983 to 1.010) were at greater risk of being overweight. Globally, overweight and obesity is concentrated in low household income groups in developed countries and in high household income groups in developing countries [70, 71], and although China is a developing country, this study found similar trends to developed countries under the household income indicator. However, a recent, study that ranked the per capita gross domestic product (GDP) of Chinese provinces reported that children and adolescents in economically developed regions were at greater risk of overweight and obesity [41]. In addition to economic income, household income inequality in childhood and adolescent overweight and obesity is also shaped by different cultural backgrounds and ethnicities [7]. In some developed countries, this pattern of inequality is in turn influenced by race [72], reflected in the fact that high household income is protective against overweight and obesity in whites but not in blacks [73]. These findings suggest that the effect of household income on overweight and obesity is associated with multiple factors.

Some studies have reported a negative association between parental education and childhood adolescent overweight and obesity [18], with an even greater effect than other socioeconomic indicators in Korea [7]. Notably, a study in China that specifically addressed the effect of parental socioeconomic status on offspring overweight and obesity using data from four surveys conducted by the CFPS between 2010 and 2016 revealed that children and adolescents at high risk of overweight and obesity were concentrated in families with parents who had lower levels of education and higher levels of maternal education appear to have a stronger impact on preventing overweight and obesity in offspring [37]. However, in the present study, higher levels of maternal education were found to be associated with the risk of overweight among children and adolescents, which may be influenced by multiple factors. For example, China’s tertiary education expansion policy has reduced employment opportunities and incomes for labor market entrants [74], and under the dual influence of market-oriented economic transformation and traditional Chinese Confucian patriarchal cultural values, men are usually seen as the breadwinners of the family, and women are more likely to be responsible for childcare and housework [75], and employers may thus expect women to devote less time and energy to their work [76]. As a result, women are more likely to experience inequality in employment and to be excluded from the market [77]. The work-family conflict may have a negative impact on the time and effort that mothers with higher levels of education devote to the scientific feeding of their offspring, and this social context may also result in the separation of children and adolescents from their mothers, which may negatively affect the quality of their diet and their weight [78]. Children and adolescents without maternal care are more likely to develop poor eating habits, which may have a negative effect on weight management in children and adolescents.

The socioeconomic inequality of overweight among children and adolescents remained unchanged under all economic indicators, but after disaggregating the population by sex, the socioeconomic inequality of overweight prevalence among girls in the subgroup of fathers’ education level narrowed and widened for boys in the subgroup of mothers’ education, with a reversal from lower to higher levels of education. The trend of widening socioeconomic inequality for boys is similar to that of Korea [7], and the trend of narrowing socioeconomic inequality for girls is the same as that of most developed countries; however, studies have reported the opposite result, with socioeconomic inequality of overweight for girls consistently widening in both parents’ education subgroups [7, 79]. In addition, a study in China showed that widening socioeconomic inequality for girls was more strongly associated with mothers with higher levels of education [80], whereas the present study revealed that narrowing socioeconomic inequality for girls was more strongly associated with fathers with higher levels of education. Potential explanations for the sex differences in socioeconomic inequality in overweight children and adolescents are that mothers with low levels of education have a greater effect on boys’ BMI [81] and that, in China’s particular economic and social context, a large number of low-educated mothers in the early years who are committed to their work can lead to the development of undesirable habits, such as sedentary behavior and fast-food eating, in their children [82], whereas with rapid socioeconomic and educational development, mothers with high education levels tend to provide their children with high-sugar and high-fat foods [83], which may account for the widening of socioeconomic inequality in the boys of the present study and its reversal at the mothers’ education level. Moreover, fathers are role models for children and adolescents during adolescence [81], and fathers’ level of education is positively associated with their level of physical activity [84]. Coupled with the fact that adolescent girls have a stronger perception of being overweight and a desire to be thinner [85], it is possible that girls may be affected by their fathers’ ability to progressively increase physical activity participation and healthy lifestyle adoption, this may be one of the reasons for the gradual narrowing of socioeconomic inequalities. With respect to age differences in socioeconomic inequalities in overweight and obesity among children and adolescents, studies have shown that children are more dependent on their parenting environment, that parents value their children’s emotional and physical health more than their weight, and that parents do not worry about their children’s overweight and think “chubby” is cute when they are not exposed to the potential health risks associated with being overweight and parents also usually assume that their children will grow out of the problem and that it will not affect them in adolescence [86, 87].and that being overweight in childhood is not a concern for physicians [88]. Moreover, in addition to adolescents being prone to greater academic stress, the rapid development of puberty also leads to a more positive self-image and stronger perceptions of overweight [81].

Strengths and limitations

The CFPS covers 95% of China, providing a representative sample of Chinese children and adolescents for this study. Moreover, this study utilized the five most recent CFPS surveys from 2010 to 2020 to estimate the prevalence of overweight among Chinese children and adolescents and its long-term trend of socioeconomic inequality. This information will help the Chinese government and relevant parts of the country formulate future physical health promotion measures for children and adolescents and promote the healthy and equal development of children and adolescents. The simultaneous use of the WHO and Chinese growth reference standards allows for better global comparisons. However, there are several limitations of this study. Height and weight were self-reported or parental surrogate responses, which may have caused some errors due to recall bias. However, the use of standardized questionnaires and consistent sampling procedures for data collection by trained staff in each survey ensured comparability of data between years. Second, The prevalence of overweight in children and adolescents may be influenced by other factors such as physical activity, diet, parental BMI family residence (urban or rural), or education, which were not controlled for in this study, and the inclusion of these factors as control variables in future studies may provide a more precise analysis of the relationship between socioeconomic inequality and overweight. Finally, owing to the uneven distribution of the population across ethnic groups as well as across regions, the ethnic and geographic characteristics of socioeconomic inequality were not investigated in this study. Given the diversity of China, which is a limitation of this study, future surveys with large samples of specific populations are needed to provide more information to explore racial and regional inequalities and how they affect policy interventions, leading to more specific localized research.

Conclusion

In conclusion, this study reveals three key findings from 2010 to 2020: Firstly, prevalence of overweight increased significantly among Chinese children and adolescents, demonstrating a clear social gradient. Secondly, socioeconomic inequality persistently disadvantaged low-income groups, though parental education showed divergent trends: for girls, inequality narrowed in the father’s education subgroup, and for boys, inequality widened in the mother’s education subgroup. These patterns highlight the need for targeted interventions addressing sex- and SES-specific risk factors. Therefore, when designing public health interventions, the relevant authorities should focus on low-income families and reinforce the concept of “healthy weight” in health education according to the sex and age differences of children and adolescents, so as to correct the overfeeding behaviors that may be derived from traditional concepts. The “family-school” setting should be used as the main venue to formulate targeted strategies to address the psychological and behavioral characteristics of different age groups. According to the socio-economic inequality of parents’ education level, government departments should promote the popularization of social education and at the same time take into account the employment-family conflict of mothers with a high level of education, strengthen the popularization of basic nutritional knowledge to families, and advocate “scientific feeding”, so as to avoid high-calorie feeding.

Electronic supplementary material

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Authors’ contributions

Z. D. Z: Conceptualization; methodology; formal analysis; writing—original draft; data curation. J. H. Z: Software; Visualization; methodology; formal analysis. Y. W: Conceptualization; methodology; writing—review and editing; supervision; validation. C. Y. L: Conceptualization; writing—review and editing; validation. J. W. L: Software; Visualization; validation. T.H:Data curation; Formal analysis; validation.

Funding

This study is supported by the Jishou University 2024 Graduate School Research Program (Jdy24108).

Data availability

The datasets analyzed in this study are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

The study was performed in accordance with the ethical standards of the Declaration of Helsinki. The studies involving human participants were reviewed and approved by the Medical Research Ethics Committee of the Peking University Health Science Center (IRB00001052–14010). Written informed consent to participate in this study was provided by all the study participants and the participants’ legal guardian/next of kin.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.