Trends and distributional characteristics in handgrip strength of 1,082,296 children and adolescents in China: an analysis from five representative cross-sectional surveys from 2000 to 2019

Abstract

Objective

Previous nationally representative health surveys in China found that handgrip strength (HGS) of children and adolescents has declined since 2000. However, these data are not only lacking in updates but also have limitations in identifying high-risk groups. This paper aims to estimate the trends in HGS adjusted for height and weight among Chinese children and adolescents from 2000 to 2019 and to investigate differences in demographic characteristics and distribution.

Methods

Height, weight, and HGS data among Chinese 1,082,296 children and adolescents aged 7–18 years (543,118 boys) were obtained from five waves of the Chinese National Surveillance on Students’ Constitution and Health from 2000 to 2019. General linear models were used to estimate trends in absolute HGS and HGS adjusted for height and weight in each sex-region-age group, respectively. Population-based trends were estimated by a post-stratification population weighting procedure. The trends in the distributional characteristics were visually described.

Results

For the total population, HGS increased by an average of 2.2 kg (95% confidence interval [CI]: 2.1 to 2.1 kg) or 0.44 effect size (ES) (95% CI: 0.43 to 0.45 ES), with a small but statistically significant improvement. There was a moderate improvement (0.62 ES) among children aged 7–12 years and a small improvement (0.27 ES) among adolescents aged 13–18 years, respectively. However, HGS adjusted for height and weight increased by an average of 0.6 kg (95% CI: 0.5 to 0.7 kg) or 0.05 ES (95% CI: 0.04 to 0.06 ES), with a negligible improvement observed overall. Urban boys aged 7–9 years and urban girls aged 7–12 years experienced small improvements (ranging from 0.22 to 0.38 ES). Urban boys aged 15, 18 years and rural boys aged 15–18 years experienced small decreases (ranging from − 0.31 to -0.23 ES) In general, the distribution of trends was uneven, with decreases primarily observed at higher percentiles but improvements observed at lower percentiles.

Conclusion

No significant changes were observed in HGS adjusted for height and weight, but there were significant differences in sex, age and distribution. Policies and intervention strategies need to prioritize low-health groups, especially among post-pubertal boys or high-fitness performers.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-025-25848-6.

Introduction

Handgrip strength (HGS) is typically measured using a grip dynamometer to assess the maximum isometric muscle strength of the hand and forearm [1]. Compared to other muscle strength tests, HGS is highly correlated with overall muscle strength; therefore, in many fields of epidemiology and sports science, HGS can serve as a valuable tool for assessing an individual’s overall muscle strength [2]. Strong evidence has shown that HGS testing is feasible in children and adolescents, and moderate evidence has shown that it is safe (no adverse events, such as pain or injury, were reported during testing) [3]. Many countries have accepted HGS testing, and it is widely used as one of the items in school fitness tests [1]. In children and adolescents, low muscle strength was associated with a higher risk of cardiometabolic syndrome, sarcopenic obesity, and poor musculoskeletal health, and HGS demonstrated higher health discriminative ability compared to other muscle strength tests [4]. Several studies have shown that low HGS is associated with metabolic syndromes (MetS) and cardiometabolic risk factors (obesity, systemic low-grade inflammation, insulin resistance) [5, 6]. Recently, several countries have established HGS cut-points associated with MetS and cardiometabolic risk in children and adolescents, which can help clinicians screen for high-risk individuals [4, 7, 8]. Observational studies reported that HGS was positively correlated with psychological symptoms and cognitive function [9, 10]. A systematic review reported that HGS was closely associated with health outcomes in later life [11]. Given the benefits of improving musculoskeletal health, the World Health Organization recommends that children and adolescents engage in musculoskeletal strengthening exercises at least three times per week in its physical activity guidelines [12].

The Healthy China Initiative (2019–2030) and the China Child Development Outline (2021–2030) clearly set national goals for improving the physical fitness and mental health levels and curbing obesity among children and adolescents [13, 14]. HGS has been demonstrated to be a simple and low-cost assessment indicator of health that is closely associated with the health status of children and adolescents. Therefore, continuous monitoring and trend analysis of HGS can provide insights for governments, public health departments, and physical fitness coaches to assess current or improve future musculoskeletal health and general health in populations. A previous large-scale meta-analysis that pooled data from 2,216,320 children and adolescents across 18 countries reported a 19.4% improvement in global HGS performance from 1967 to 2017, with the improvement accelerating [15]. This study also included nationally representative data from China between 2000 and 2014, showing an increase in HGS among children and adolescents. However, there is a lack of updated data, and no research has estimated trends in HGS adjusted for body size in China, such as height and weight. When assessing muscular strength in children and adolescents, it was important to account for differences in body size. Controlling for these factors helped identify changes in motor performance driven by actual physiological capacity, rather than solely by changes in body size or composition [16, 17]. Compared to fat-free mass (FFM) (closely related to HGS [17]), body height and weight were the most commonly used adjusted anthropometric measurements for assessing HGS in children and adolescents; they were easy to measure and highly associated with HGS [18, 19]. Height, in particular, was not only strongly correlated with FFM but also included the influence of the lever arm effect (taller individuals had greater leverage, thereby gaining a mechanical advantage), which was the preferred anthropometric measurement for standardizing HGS [18]. Over the past three decades in China, the height and weight of children and adolescents have continued to increase [20], it is necessary to estimate the trend in HGS adjusted for height and weight to understand the actual changes in muscular fitness. Several studies have reported trends in body size-adjusted HGS in some provinces of China. From 2003 to 2015, there was no significant change in body size-adjusted HGS among children aged 6–12 years in Hong Kong, China [21]. From 2005 to 2020, the body size-adjusted HGS among children and adolescents aged 6–18 years in Macao significantly decreased, especially among boys and adolescents [22]. Several national surveys have only reported trends in lower body muscular strength, upper body muscular strength, and abdominal muscular strength in China [23–25]. Despite previous studies, the recent trends in body size-adjusted HGS among children and adolescents from national representative survey in China have not been fully explored. Recently, Japan [26, 27], South Korea [28], France [29], Poland [30], the United Kingdom [31], and Brazil [32] have updated trends in HGS or HGS adjusted for certain factors among children and adolescents. Current research primarily focuses on populations in Western or developed countries, with varying trends. Evidence from Eastern and developing countries is needed to determine country-specific health intervention programs. Moreover, many studies have reported differing trends in HGS among children and adolescents at various levels [21, 22, 29]. It is essential to understand the distribution characteristics of changes in HGS nationwide in China to provide insights for identifying priority populations for future health policies and public health interventions.

The Chinese National Surveillance on Students’ Constitution and Health (CNSSCH) was a large-scale, representative, and authoritative survey of the physical fitness and health of Chinese children and adolescents. Since 1985, CNSSCH has been organized by the Ministry of Education, the Ministry of Health, the Ministry of Science and Technology, the State Ethnic Affairs Commission, and the General Administration of Sport, with support from the Ministry of Finance, and has been performed approximately every five years, with eight successive cross-sectional surveys. Since 2000, HGS testing has been added. Therefore, using data from the five waves of 2000, 2005, 2010, 2014, and 2019 [33–37], this paper aimed to examine temporal trends in body size-adjusted HGS and distributional characteristics among Chinese children and adolescents aged 7–18 years.

Methods

Study design and subjects

Height, weight, and handgrip strength data among Han Chinese children and adolescents aged 7–18 years were obtained from published summary data by the CNSSCHs in 2000, 2005, 2010, 2014 and 2019 [33–37]. The CNSSCH used a multistage stratified cluster sampling design and sampled Chinese students from 30 provincial regions, except for Tibet, Hong Kong, Macau and Taiwan. The sampling procedure was performed as previously described in detail [23–25]. In brief, in the first stage, all prefecture-level cities in each province, except those in Tibet, were divided into three nearly equal socioeconomic status (SES) groups (high, medium, and low) based on SES. A prefecture-level city was randomly selected from each SES group. In the second stage, participants were stratified by residence into urban and rural areas. In the third stage, within these stratified areas, sample schools were randomly selected to include elementary, junior middle, and junior high school students aged 7–18 years. Subsequently, the sampled schools remained hardly unchanged. In the fourth phase, classes were randomly selected by grade level within these sampled schools, with all students in each class included in the survey. Finally, at least 50 Han Chinese students were included in each sex-region-age group. Age was calculated as the actual age based on the date of birth relative to the measurement date. Before the test, all participants must complete a medical examination by a specialist physician, and those who fail will be excluded. Exclusion criteria were as follows: (1) participants with diseases of vital organs such as the heart, lungs, liver, or kidneys (e.g., heart disease, hypertension, pulmonary tuberculosis, asthma, hepatitis, nephritis); (2) participants with physical developmental abnormalities (e.g., dwarfism, gigantism); (3) participants with physical disabilities or deformities (severe scoliosis, pectus carinatum, clubfoot, markeble bowlegs/knock knees, etc.); (4) participants with acute illnesses, or those who have suffered acute illnesses such as high fever or diarrhea within one month before test and have not fully recovered; (5) girls who were menstruating (If a female physician asks a girl, “Have you started menstruating?” and she answers “no,” she will not participate in the test). Given that the survey before 2000 did not test handgrip strength, data from five waves between 2000 and 2019 were selected. A total of 1,082,296 children and adolescents (543,118 boys) were tested. The sex-, region- and age-specific sample sizes in each wave are shown in Table 1. CNSSCH was performed in accordance with the ethical standards of the Declaration of Helsinki. The participants provided their written informed consent to participate.

Table 1.

Sample size distribution for handgrip strength among Chinese children and adolescents

Region	Age (years)			Boys					Girls
		2000	2005	2010	2014	2019	2000	2005	2010	2014	2019
Urban	7	3719	4920	4471	4463	4521	3397	4847	4453	4475	4401
	8	4160	4922	4481	4487	4569	3933	4845	4461	4482	4439
	9	4349	4920	4480	4474	4571	4158	4877	4485	4489	4481
	10	4464	4903	4488	4479	4415	4467	4915	4487	4484	4473
	11	4461	5048	4498	4487	4522	4413	4886	4495	4473	4511
	12	4458	4916	4483	4474	4530	4452	4766	4481	4476	4503
	13	4488	4913	4486	4487	4482	4457	4922	4485	4491	4451
	14	4491	4852	4487	4484	4537	4444	4845	4494	4480	4477
	15	4509	4979	4489	4477	4422	4465	4931	4482	4480	4483
	16	4499	4891	4476	4472	4438	4455	4911	4453	4476	4319
	17	4457	4917	4488	4494	4471	4468	4849	4484	4483	4321
	18	4492	4978	4475	4286	4224	4579	5030	4434	4287	3918
Rural	7	3786	4761	4474	4480	4527	3205	4708	4476	4459	4515
	8	4134	4785	4480	4443	4470	3769	4708	4488	4440	4425
	9	4201	4805	4483	4484	4502	4119	4742	4487	4488	4369
	10	4395	4955	4485	4483	4488	4263	4829	4487	4475	4603
	11	4402	4813	4487	4496	4421	4370	4813	4493	4460	4527
	12	4414	4800	4492	4472	4392	4418	4747	4497	4473	4481
	13	4279	4763	4487	4484	4358	4423	4817	4481	4484	4414
	14	4397	4814	4484	4484	4346	4389	4757	4476	4482	4359
	15	4437	4950	4489	4488	4474	4392	4879	4493	4489	4426
	16	4441	4908	4485	4482	4394	4429	4825	4485	4470	4377
	17	4366	4869	4464	4483	4308	4407	4855	4483	4487	4389
	18	4519	5136	4488	4292	4165	4501	5134	4487	4256	4139

Measurements

The test time ranged from September to November of 2000 to 2019. All staff received rigorous training. The sampled schools were nearly identical across all waves. The sampling methods and measurement procedures were consistent across all testing sites, and the same testing equipment was used. Instruments were calibrated before each measurement. Data were entered using a double-entry method and underwent comparison, verification, and correction. Following the random sampling method, 3% of all records were selected for review.

Height was measured by a stadiometer, accurate to 0.1 centimetre (cm). Participants stand barefoot with their backs toward the pillar on the base plate of the stadiometer. Their trunks were naturally straight, their heads were upright, and their eyes looked straight ahead. Weight was measured by an electronic scale, accurate to 0.1 kg (kg). Participants wore shorts and bare feet, stood naturally in the center of the platform of the electronic scale, and kept their bodies steady. Handgrip strength was measured by a digital grip dynamometer, accurate to 0.1 kg. Before the test, participants gripped the inner and outer handles of the digital grip dynamometer with their dominant hands, while using the other hand to turn the wheel to adjust the grip distance to a suitable level. During the test, participants stand upright with their feet shoulder-width apart and arms hanging down at their sides, palms facing inward. They gripped the inner and outer handles with maximum force, performed the test twice, and recorded the maximum value. If participants were unable to determine their dominant hand, they could test twice with each hand and record the maximum value.

Statistical analysis

All results for height, weight and handgrip strength indicators are expressed as the mean and standard deviation (SD). A general linear model was used to estimate the trends, with the year as the independent variable and the means handgrip strength as the dependent variable. General linear models were chosen for trend estimation as they provide an efficient means for summarizing overall changes over time, adjusted for potential confounders [21]. The trends in handgrip strength were estimated in each sex-region-age group for unadjusted and adjusted for height, and weight, respectively. Estimates were performed using the regression procedures of aggregate continuous data developed by Moineddin & Urquia [38, 39]. This procedure allowed the regression results of aggregated continuous data to be close to the regression results of raw data, including coefficients and variances [38]. The change and 95% confidence interval (CI) was expressed as absolute change (i.e., the slope B of the regression), percentage change (% per year, i.e., the slope of the regression as a percentage of the sample-weighted mean of all means in the regression), and standardized (Cohen’s) effect sizes (ES) (i.e., the slope of the regression divided by the combined SD of all SDs in the regression). Percentage changes represented relative changes, which could eliminate the influence of dimension. Cohen’s ES, in units of SD, reflected the significance and magnitude of differences; it eliminated constraints such as dimension and variability levels, facilitating comparisons across studies and groups [40]. Following the procedure described by Tomkinson et al. [41], population-weighted average changes (for both sexes, urban boys, rural boys, urban girls, and rural girls) were calculated by combining age-specific changes using stratified population weighting (Eq. 1). The sex-region-age-specific population data were derived from the 2020 Population Census in China [42]. The population census is the largest and most authoritative survey of China’s population status and is conducted every ten years. The formula was as follows:

1

, (1) where‾Δ was the population-weighted average change, Δ was the sex-region-age-specific change, w was the sex-region-age-specific population, and k was the number of sex-region-age groups. The 95% confidence intervals (CIs) for the weighted average changes were calculated as average change ± 1.96 standard errors (SEs). The corresponding standard errors (SEs) were calculated using Eq. 2.

2

where‾Δ_SE = the SE of the population-weighted average change, Δ was the SE of the sex-region-age-specific change, w was the sex-region-age-specific population, and k was the number of sex-region-age groups.

To account for the magnitude of changes in the mean, ESs of 0.2, 0.5, and 0.8 were used as thresholds for small, medium, and large, respectively, with ESs of < 0.2 considered negligible changes [40]. Trends were estimated for each percentile value using the method described above. The sex-region-age-specific 3rd (worst level), 5th, 10th, 15th, 25th, 30th, 50th, 70th, 75th, 85th, 90th, 95th, and 97th (best level) percentile values were extracted. Locally weighted scatterplot smoother (LOWESS) curves were used to plot ESs of changes for a series of percentiles (from the 3rd to the 97th), and the variation in change was visually examined. All the statistical analyses were performed by R software 4.5.1.

Results

Overall trends in absolute HGS and body size-adjusted HGS

Table 2 shows means and SDs for height, weight, and handgrip strength among Chinese children and adolescents by wave, sex, region, and age. Height, weight and HGS increased from 148.7 cm, 40.9 kg, and 20.6 kg in 2000 to 152.8 cm, 46.8 kg, and 22.5 kg, respectively. For the total population, HGS performance increased 2.1 kg (95% CI: 2.1 to 2.1 kg) or 12.0% (95% CI: 11.9 to 12.1%) or 0.44 ES (95% CI: 0.43 to 0.45 ES), with a small but statistically significant improvement (0.20 ≤ ES < 0.5). Urban boys, rural boys, urban girls, and rural girls all experienced small improvements in HGS (ranging from 0.39 to 0.49 ES). With adjustment for height and weight, there was a negligible improvement in overall HGS performance (ES < 0.20), with an increase of 0.6 kg (95% CI: 0.5 to 0.7 kg) or 1.8% (95% CI: 1.6 to 2.0%) or 0.05 ES (95% CI: 0.04 to 0.06 ES). However, urban girls experienced a small improvement in body size-adjusted HGS (0.20 ES, 95% CI: 0.19 to 0.21 ES). There were negligible changes in body size-adjusted HGS among urban boys (0.02 ES), rural boys (−0.08 ES), and rural girls (0.01 ES) (Table 3).

Table 2.

Descriptive statistics (mean ± standard deviation) for height, weight, and handgrip strength among Chinese children and adolescents aged 7–18 years by wave, sex, region and age

Test	Age (years)			Boys					Girls
		2000	2005	2010	2014	2019	2000	2005	2010	2014	2019
Height (cm)	Urban
	7	124.3 ± 5.9	125.7 ± 5.8	126.9 ± 5.8	127.8 ± 5.6	127.5 ± 5.7	123.2 ± 5.8	124.1 ± 5.7	125.5 ± 5.6	126.1 ± 5.4	126.0 ± 5.4
	8	129.8 ± 6.0	131.2 ± 6.2	132.2 ± 5.9	133.2 ± 5.9	133.3 ± 5.7	128.6 ± 6.1	129.8 ± 6.0	130.7 ± 6.0	131.6 ± 5.7	132.0 ± 5.9
	9	134.5 ± 6.3	136.1 ± 6.3	137.4 ± 6.3	138.8 ± 6.1	138.7 ± 6.4	134.4 ± 6.6	135.4 ± 6.6	136.6 ± 6.5	137.6 ± 6.3	138.0 ± 6.8
	10	139.9 ± 6.6	141.1 ± 6.7	142.5 ± 6.9	143.6 ± 6.8	144.1 ± 6.8	140.6 ± 7.2	141.5 ± 7.2	142.9 ± 7.2	144.0 ± 7.0	144.9 ± 7.2
	11	145.2 ± 7.2	146.7 ± 7.4	148.1 ± 7.9	149.8 ± 7.8	150.8 ± 7.9	146.9 ± 7.5	148.0 ± 7.4	149.2 ± 7.4	150.9 ± 7.2	151.8 ± 7.0
	12	151.3 ± 8.6	152.8 ± 8.5	154.2 ± 8.6	155.9 ± 8.5	157.5 ± 8.9	152.1 ± 6.9	152.6 ± 7.1	153.5 ± 6.9	154.8 ± 6.7	155.7 ± 6.5
	13	159.4 ± 8.8	160.1 ± 8.6	161.7 ± 8.2	162.7 ± 8.4	164.6 ± 8.2	155.9 ± 6.1	156.3 ± 6.1	157.1 ± 5.9	158.0 ± 5.9	159.0 ± 6.0
	14	164.8 ± 7.7	165.9 ± 7.7	167.0 ± 7.3	167.9 ± 7.2	169.6 ± 7.0	157.9 ± 5.7	158.1 ± 5.9	158.9 ± 5.7	159.6 ± 5.8	160.3 ± 5.7
	15	168.6 ± 6.7	169.4 ± 6.6	170.0 ± 6.6	170.9 ± 6.6	172.0 ± 6.5	158.8 ± 5.4	159.1 ± 5.7	159.3 ± 5.8	160.1 ± 5.7	160.8 ± 5.9
	16	170.7 ± 6.3	171.1 ± 6.3	171.5 ± 6.3	172.2 ± 6.3	173.3 ± 6.2	159.4 ± 5.6	159.5 ± 5.7	159.9 ± 5.6	160.6 ± 5.7	161.4 ± 5.8
	17	171.5 ± 6.1	171.8 ± 6.4	172.2 ± 6.2	172.7 ± 6.3	173.7 ± 6.2	159.5 ± 5.8	159.9 ± 5.6	160.0 ± 5.6	160.5 ± 5.7	161.5 ± 5.8
	18	171.4 ± 6.2	171.9 ± 6.4	172.2 ± 6.3	172.6 ± 6.2	173.3 ± 6.4	159.2 ± 5.6	159.8 ± 5.6	159.9 ± 5.6	159.9 ± 5.8	160.7 ± 5.7
	Rural
	7	121.1 ± 6.0	122.5 ± 6.0	124.1 ± 5.8	125.4 ± 5.7	126.3 ± 5.8	120.1 ± 5.9	121.2 ± 6.1	122.8 ± 5.9	124.1 ± 5.7	125.0 ± 5.8
	8	126.4 ± 6.0	127.8 ± 6.2	129.3 ± 6.1	130.8 ± 6.0	131.5 ± 5.9	125.2 ± 6.3	126.7 ± 6.2	128.1 ± 6.2	129.3 ± 6.2	130.6 ± 6.2
	9	131.3 ± 6.5	132.8 ± 6.3	134.2 ± 6.4	135.6 ± 6.4	136.9 ± 6.4	130.7 ± 6.7	132.2 ± 6.8	133.5 ± 6.8	135.1 ± 6.6	136.7 ± 7.0
	10	136.1 ± 6.6	137.6 ± 6.6	139.3 ± 6.7	140.6 ± 6.7	142.1 ± 6.8	136.6 ± 7.3	138.1 ± 7.5	139.6 ± 7.2	141.3 ± 7.2	143.0 ± 7.4
	11	140.9 ± 7.1	142.7 ± 7.4	144.4 ± 7.4	146.4 ± 7.6	148.5 ± 7.9	142.8 ± 7.5	144.1 ± 7.8	145.3 ± 7.6	147.8 ± 7.5	149.8 ± 7.3
	12	146.9 ± 8.4	148.3 ± 8.3	150.5 ± 8.7	153.2 ± 8.9	155.1 ± 8.9	148.3 ± 7.3	149.1 ± 7.3	150.9 ± 7.2	152.7 ± 7.0	154.1 ± 6.8
	13	154.6 ± 9.1	155.7 ± 8.9	158.1 ± 8.7	160.1 ± 8.7	162.4 ± 8.4	152.7 ± 6.3	153.5 ± 6.3	154.9 ± 6.2	156.0 ± 6.2	157.3 ± 5.9
	14	160.6 ± 8.5	161.6 ± 8.3	163.6 ± 7.9	165.1 ± 7.8	167.5 ± 7.2	155.3 ± 5.8	155.8 ± 5.8	156.7 ± 5.7	157.7 ± 5.7	158.9 ± 5.7
	15	165.0 ± 7.0	166.0 ± 7.1	167.5 ± 7.1	168.7 ± 6.9	170.5 ± 6.5	156.5 ± 5.6	156.8 ± 5.5	157.8 ± 5.6	158.7 ± 5.7	159.6 ± 5.8
	16	167.8 ± 6.2	168.4 ± 6.4	169.6 ± 6.5	170.5 ± 6.3	171.9 ± 6.2	157.3 ± 5.6	157.6 ± 5.5	158.2 ± 5.6	158.9 ± 5.8	160.1 ± 5.9
	17	168.9 ± 6.1	169.7 ± 6.2	170.5 ± 6.3	171.4 ± 6.3	172.4 ± 6.3	157.5 ± 5.4	158.0 ± 5.6	158.6 ± 5.7	159.1 ± 5.7	160.1 ± 5.9
	18	169.1 ± 6.2	170.1 ± 6.1	170.7 ± 6.3	171.4 ± 6.3	172.2 ± 6.2	157.6 ± 5.5	158.1 ± 5.4	158.5 ± 5.7	158.9 ± 5.8	159.5 ± 5.8
Weight (kg)	Urban
	7	24.6 ± 5.7	25.7 ± 5.4	26.7 ± 5.7	27.4 ± 5.9	27.3 ± 5.8	23.1 ± 4.1	23.9 ± 4.5	24.7 ± 4.6	25.2 ± 4.9	25.3 ± 4.7
	8	27.5 ± 5.8	29.0 ± 6.6	29.6 ± 6.5	30.8 ± 6.8	31.0 ± 6.9	25.7 ± 5.0	26.8 ± 5.3	27.4 ± 5.6	28.3 ± 5.7	28.5 ± 5.8
	9	30.2 ± 6.8	32.2 ± 7.4	33.4 ± 7.9	35.1 ± 8.3	35.1 ± 8.4	28.9 ± 5.8	29.9 ± 6.3	30.9 ± 6.5	32.2 ± 7.1	32.5 ± 7.5
	10	34.2 ± 8.0	36.0 ± 8.6	37.2 ± 9.2	38.6 ± 9.3	39.5 ± 9.9	32.8 ± 7.3	33.9 ± 7.5	35.1 ± 7.7	36.6 ± 8.1	37.6 ± 9.0
	11	37.8 ± 8.9	40.0 ± 9.7	41.7 ± 10.6	43.6 ± 11.0	45.2 ± 12.0	37.3 ± 8.4	38.8 ± 8.8	39.9 ± 8.9	42.0 ± 9.3	43.1 ± 9.6
	12	42.1 ± 10.5	44.3 ± 11.2	46.3 ± 11.8	48.3 ± 12.2	50.3 ± 13.0	41.5 ± 8.8	42.4 ± 9.0	43.6 ± 9.1	45.4 ± 9.5	47.3 ± 10.5
	13	47.8 ± 11.2	49.4 ± 11.8	51.8 ± 12.1	54.0 ± 13.0	55.9 ± 13.7	45.1 ± 8.2	46.0 ± 8.6	47.6 ± 8.9	49.0 ± 9.1	51.1 ± 10.1
	14	52.4 ± 11.3	54.4 ± 12.0	56.4 ± 12.2	58.3 ± 12.8	61.0 ± 13.8	47.9 ± 8.3	48.9 ± 8.6	49.8 ± 8.5	51.7 ± 9.2	53.5 ± 9.9
	15	56.6 ± 11.0	58.0 ± 11.6	59.4 ± 12.0	61.5 ± 12.6	63.4 ± 13.2	49.9 ± 8.0	50.6 ± 8.3	51.0 ± 8.2	52.5 ± 8.6	54.4 ± 9.3
	16	59.1 ± 10.5	60.3 ± 11.6	61.0 ± 11.2	63.1 ± 12.2	65.9 ± 13.4	51.1 ± 7.4	51.3 ± 7.6	51.9 ± 7.7	53.5 ± 8.5	55.5 ± 9.5
	17	60.9 ± 10.4	61.7 ± 11.1	62.7 ± 11.3	64.8 ± 12.5	67.3 ± 13.2	51.4 ± 7.6	51.9 ± 7.9	52.2 ± 7.6	53.8 ± 8.4	55.5 ± 9.3
	18	61.6 ± 10.1	62.0 ± 11.1	63.1 ± 11.2	64.9 ± 12.0	67.3 ± 13.5	51.8 ± 7.4	52.1 ± 7.8	52.1 ± 7.8	53.1 ± 8.4	55.0 ± 9.5
	Rural
	7	22.2 ± 4.1	23.3 ± 4.5	24.4 ± 4.9	25.8 ± 5.6	26.5 ± 5.9	21.4 ± 3.7	22.1 ± 3.9	23.0 ± 4.3	24.2 ± 4.7	24.9 ± 5.0
	8	24.6 ± 4.3	25.9 ± 5.3	27.3 ± 5.7	29.0 ± 6.6	29.5 ± 6.9	23.4 ± 4.2	24.6 ± 4.7	25.6 ± 5.0	27 ± 5.6	27.9 ± 5.9
	9	27.1 ± 4.9	28.6 ± 6.0	30.2 ± 6.7	32.1 ± 7.7	33.3 ± 8.2	26.3 ± 5.7	27.5 ± 5.5	28.6 ± 5.8	30.3 ± 6.8	31.7 ± 7.5
	10	30.0 ± 6.2	31.8 ± 7.0	33.8 ± 8.1	35.7 ± 8.6	37.7 ± 9.7	29.4 ± 6.0	31.0 ± 6.8	32.5 ± 7.1	34.4 ± 7.8	36.1 ± 8.7
	11	32.9 ± 7.2	34.9 ± 7.9	37.6 ± 9.2	40.2 ± 10.4	42.6 ± 11.5	33.4 ± 6.9	35.0 ± 7.5	36.4 ± 8.0	39.3 ± 9.0	41.5 ± 9.7
	12	37.0 ± 8.3	39.0 ± 9.2	41.7 ± 10.6	45.0 ± 11.2	47.6 ± 12.7	37.5 ± 7.3	38.8 ± 7.7	41.1 ± 8.5	43.6 ± 9.3	45.5 ± 9.9
	13	42.3 ± 9.1	44.1 ± 10.1	47.0 ± 10.6	50.0 ± 11.9	53.0 ± 13.3	41.8 ± 7.2	43.3 ± 7.7	44.9 ± 8.0	47.1 ± 8.8	49.5 ± 9.6
	14	47.2 ± 9.5	48.7 ± 10.0	51.3 ± 10.6	54.2 ± 11.9	57.7 ± 13.1	45.0 ± 6.9	46.0 ± 7.3	47.4 ± 7.5	49.2 ± 8.3	52.0 ± 9.6
	15	51.5 ± 8.9	52.5 ± 9.5	55.1 ± 10.4	57.5 ± 11.0	60.9 ± 12.8	47.4 ± 6.7	48.1 ± 7.1	49.3 ± 7.4	50.7 ± 7.8	53.4 ± 9.2
	16	54.8 ± 8.0	55.6 ± 9.1	57.4 ± 9.6	59.9 ± 11.3	63.0 ± 12.4	49.6 ± 6.4	49.8 ± 6.7	50.4 ± 6.9	51.8 ± 7.8	54.1 ± 8.9
	17	56.9 ± 8.6	57.4 ± 8.6	59.2 ± 9.5	61.8 ± 11.4	64.6 ± 12.5	50.4 ± 6.4	50.6 ± 6.6	51.2 ± 7.0	52.2 ± 8.0	54.4 ± 9.1
	18	58.1 ± 8.0	58.7 ± 8.7	59.9 ± 9.2	62.2 ± 11.0	64.7 ± 12.4	51.0 ± 6.8	50.9 ± 6.4	51.3 ± 6.8	52.1 ± 7.6	53.5 ± 8.7
Handgrip strength (kg)	Urban
	7	8.5 ± 3.0	10.3 ± 3.2	10.3 ± 3.0	10.5 ± 2.7	10.5 ± 3.4	7.7 ± 2.5	8.7 ± 2.5	9.0 ± 2.6	9.2 ± 2.4	9.2 ± 3.0
	8	10.0 ± 3.3	11.8 ± 3.0	12.0 ± 3.0	12.5 ± 3.0	12.3 ± 3.6	8.7 ± 2.9	10.2 ± 2.7	10.5 ± 3.0	10.9 ± 2.8	10.9 ± 3.2
	9	11.5 ± 3.8	13.7 ± 3.4	13.9 ± 3.6	14.5 ± 3.4	14.0 ± 3.5	10.1 ± 3.5	12.0 ± 3.1	12.3 ± 3.2	12.7 ± 3.1	12.7 ± 3.5
	10	13.3 ± 4.1	16.0 ± 4.4	16.0 ± 3.9	16.1 ± 3.6	16.3 ± 4.8	11.9 ± 4.0	14.1 ± 3.7	14.5 ± 3.7	14.8 ± 3.5	15.2 ± 4.6
	11	15.7 ± 4.8	17.9 ± 4.6	18.5 ± 4.7	19.0 ± 4.7	18.9 ± 5.1	14.2 ± 4.4	16.4 ± 4.5	17.1 ± 4.3	17.7 ± 4.1	18.0 ± 4.9
	12	19.1 ± 6.4	21.7 ± 6.2	22.6 ± 6.3	22.6 ± 5.9	22.7 ± 6.4	16.7 ± 4.9	18.9 ± 4.6	19.5 ± 4.9	19.8 ± 4.4	20.0 ± 4.9
	13	24.9 ± 7.9	27.8 ± 7.5	28.6 ± 7.3	28.6 ± 7.2	28.2 ± 7.7	19.1 ± 5.1	21.5 ± 4.7	22.0 ± 4.7	22.0 ± 4.6	21.8 ± 4.8
	14	29.6 ± 7.9	33.2 ± 7.9	33.8 ± 7.5	33.2 ± 7.4	32.9 ± 7.7	20.5 ± 5.1	23.0 ± 4.8	23.3 ± 4.8	23.3 ± 4.7	22.9 ± 5.0
	15	34.4 ± 7.4	37.2 ± 7.6	37.7 ± 7.4	37.1 ± 7.4	35.5 ± 8.3	21.9 ± 5.3	24.2 ± 5.0	24.4 ± 4.9	24.1 ± 4.7	23.5 ± 5.1
	16	36.7 ± 7.2	40.0 ± 8.0	40.2 ± 7.1	39.3 ± 7.2	38.5 ± 7.7	22.4 ± 5.6	24.8 ± 5.1	25.1 ± 4.8	24.8 ± 4.7	24.3 ± 5.4
	17	38.4 ± 7.1	41.3 ± 7.7	41.8 ± 7.1	41.1 ± 7.4	39.9 ± 7.8	22.8 ± 5.5	25.2 ± 5.1	25.8 ± 5.1	25.2 ± 4.8	24.7 ± 5.3
	18	39.6 ± 7.2	42.2 ± 8.0	42.8 ± 7.4	42.0 ± 7.5	39.9 ± 8.0	23.3 ± 6.1	25.7 ± 5.2	26.1 ± 4.9	25.5 ± 5.0	24.6 ± 5.6
	Rural
	7	9.0 ± 3.6	10.2 ± 3.0	10.2 ± 2.9	10.3 ± 2.7	10.6 ± 3.1	8.2 ± 3.3	8.8 ± 3.2	9.0 ± 3.3	9.0 ± 2.5	9.4 ± 2.9
	8	10.2 ± 4.1	12 ± 3.3.0	12.0 ± 3.0	12.4 ± 3.0	12.6 ± 3.9	9.0 ± 3.8	10.6 ± 3.6	10.4 ± 2.8	10.7 ± 2.7	11.0 ± 3.3
	9	11.5 ± 4.1	13.8 ± 3.6	13.9 ± 3.4	14.2 ± 3.3	14.1 ± 3.7	10.2 ± 4.2	12.0 ± 3.2	12.2 ± 3.1	12.4 ± 3.0	12.9 ± 4.0
	10	13.3 ± 4.4	16.0 ± 3.8	16.0 ± 3.8	16.1 ± 3.6	16.5 ± 4.6	11.9 ± 4.6	14.1 ± 3.9	14.4 ± 3.6	14.7 ± 3.5	15.3 ± 4.4
	11	15.5 ± 5.2	18.2 ± 4.6	18.6 ± 4.6	19.0 ± 4.6	19.0 ± 5.3	14.0 ± 4.8	16.7 ± 4.2	16.9 ± 4.2	17.7 ± 4.2	17.9 ± 5.1
	12	18.4 ± 6.0	21.5 ± 5.5	22.2 ± 6.0	23.3 ± 6.1	23.0 ± 6.8	16.4 ± 5.2	19.1 ± 4.6	19.5 ± 4.6	20.3 ± 4.7	20.1 ± 5.3
	13	23.7 ± 7.9	26.9 ± 7.3	28.0 ± 7.2	28.7 ± 7.2	28.5 ± 7.5	19.9 ± 5.4	21.7 ± 4.9	22.1 ± 4.6	22.4 ± 4.6	22.2 ± 5.2
	14	29.4 ± 8.2	32.2 ± 8.1	32.9 ± 7.5	33.6 ± 7.6	32.8 ± 7.3	21.5 ± 5.3	23.5 ± 4.9	23.6 ± 4.6	23.7 ± 4.6	23.4 ± 5.3
	15	33.7 ± 7.8	36.7 ± 8.1	37.1 ± 7.5	37.7 ± 7.8	36.2 ± 7.6	23.0 ± 5.3	24.8 ± 5.1	24.9 ± 4.8	24.7 ± 4.9	24.3 ± 5.2
	16	37.3 ± 7.7	40.1 ± 7.9	40.7 ± 7.0	40.5 ± 8.1	39.0 ± 7.7	23.9 ± 5.3	25.6 ± 5.3	26.0 ± 4.8	25.5 ± 5.0	25.0 ± 5.2
	17	39.3 ± 7.3	42.3 ± 8.3	42.3 ± 7.2	42.7 ± 8.3	40.6 ± 8.0	24.5 ± 5.5	26.6 ± 5.4	26.6 ± 5.2	26.0 ± 5.2	25.7 ± 5.3
	18	40.6 ± 7.6	43.1 ± 8.2	43.4 ± 7.0	44.0 ± 8.2	40.7 ± 7.9	24.8 ± 5.4	27.0 ± 5.3	26.9 ± 5.2	26.3 ± 5.2	25.5 ± 5.2

Table 3.

Temporal trends in means for handgrip strength among Chinese children and adolescents from 2000 and 2019 by sex, region and age category

Category	Change (95% CI)			Body size-adjusted changes (95% CI)
	Absolute (kg)	Percent (%)	Standardized (ES)	Absolute (kg)	Percent (%)	Standardized (ES)
Total	2.1 (2.1, 2.1)*	12.0 (11.9, 12.1)*	0.44 (0.43, 0.45)*	0.6 (0.5, 0.7)	1.8 (1.6, 2.0)	0.05 (0.04, 0.06)
Urban boys	2.0 (1.9, 2.1)*	10.5 (10.2, 10.8)*	0.39 (0.38, 0.40)*	0.1 (0.0, 0.2)	0.7 (0.5, 0.09)	0.02 (0.01, 0.03)
Rural boys	2.6 (2.5, 2.7)*	13.0 (12.7, 13.3)*	0.47 (0.46, 0.48)*	−0.4 (−0.5,−0.3)	−2.1 (−2.4,−1.8)	−0.08 (−0.09,−0.07)
Urban girls	2.1 (2.0, 2.2)*	12.8 (12.5, 13.1)*	0.49 (0.48, 0.50)*	0.9 (0.8, 0.10)*	5.3 (5.0, 5.6)*	0.20 (0.19, 0.21)*
Rural girls	1.9 (1.8, 2.0)*	12.4 (12.1, 12.7)*	0.45 (0.44, 0.46)*	0.0 (0.0, 0.0)	0.2 (0.0, 0.4)	0.01 (0.00, 0.02)

Positive trends indicated temporal improvement and negative trends indicated temporal decreases. Standardized ESs in means of 0.2, 0.5, and 0.8 are used as thresholds for small, moderate, and large, respectively, with an ES of < 0.2 considered to be negligible. CI is the confidence interval and ES is the effect size. * represents significant changes (ES≥0.20)

Trends in absolute HGS and body size-adjusted HGS by age

Figure 1 shows the sex-region-age-specific ES of changes in HGS performance with no adjustment and with adjustment for height and weight, respectively. Urban boys aged 7–14 years (ranging from 0.34 to 0.64 ES), rural boys aged 7–16 years (ranging from 0.20 to 0.70 ES), urban girls aged 7–18 years (ranging from 0.20 to 0.76 ES) and rural girls aged 7–15 years (ranging from 0.20 to 0.76 ES) experienced small to moderate improvements in HGS performance. There were negligible improvements in other sex-region-age groups. With adjustment for height and weight, urban boys aged 7–9 years and urban girls aged 7–12 years experienced small improvements in HGS performance (ranging from 0.22 to 0.38 ES). Urban boys aged 15, 18 years, and rural boys aged 15–18 years, experienced small decreases in HGS performance (ranging from − 0.31 to −0.23 ES). There were negligible changes in other sex-region-age groups (Table S1).

Fig. 1.

Standardized ESs and 95% CIs of changes in handgrip strength among Chinese children and adolescents from 2000 and 2019 by sex, region and age. (A): Standardized ESs and 95% CIs of changes with no adjustment; (B): Standardized ESs and 95% CIs of changes with adjustment for height and weight. Positive trends indicated temporal improvement and negative trends indicated temporal decreases. Standardized ESs in means of 0.2, 0.5, and 0.8 are used as thresholds for small, moderate, and large, respectively, with an ES of < 0.2 considered to be negligible. CI is the confidence interval and ES is the effect size. Red area represents significant changes

Distribution characteristics trends in body size-adjusted HGS

Table 4 shows changes in standardized ES of mean body size-adjusted HGS among Chinese children and adolescents from 2000 to 2019 across percentiles. The trends in performance varied across percentiles, with a more pronounced improvement observed at lower percentiles. As the percentile increased, the ES decreased. For the total population, there were small improvements at the 3rd to 15th percentile (ranging from 0.23 to 0.30 ES) and negligible decreases (ranging from − 0.19 to −0.05 ES) at the 70th percentile and above. The greatest improvement occurred at the lowest level (the 3rd percentile), while the largest decrease (though not statistically significant) occurred at the highest level (the 97th percentile). The distribution characteristics of urban boys, rural boys, urban girls, and rural girls were consistent with those of the total population. Urban boys, rural boys, urban girls, and rural girls experienced significantly small improvements at the 5th, 10th, 30th, and 15th percentiles and below, respectively (ranging from 0.20 to 0.43 ES). Significantly small decreases were observed only among rural boys and rural girls at the 70th and 85th percentiles and above, respectively (ranging from − 0.42 to −0.20 ES). Urban boys experienced negligible decreases at higher percentiles. Urban girls experienced improvements in all percentiles, though these improvements became negligible as percentiles increased (ranging from 0.01 to 0.43 ES).

Table 4.

Standardized ESs and 95% CIs of changes in handgrip strength among Chinese children and adolescents from 2000 and 2019 by sex, region, age category and percentile

Percentiles (%)	Total	Urban boys	Rural boys	Urban girls	Rural girls
3	0.30 (0.29, 0.31)*	0.23 (0.22, 0.24)*	0.24 (0.23, 0.26)*	0.43 (0.42, 0.44)*	0.27 (0.26, 0.28)*
5	0.29 (0.28, 0.30)*	0.20 (0.19, 0.21)*	0.24 (0.23, 0.25)*	0.43 (0.42, 0.44)*	0.31 (0.29, 0.32)*
10	0.26 (0.25, 0.27)*	0.17 (0.16, 0.18)	0.20 (0.19, 0.21)*	0.39 (0.38, 0.40)*	0.28 (0.27, 0.30)*
15	0.23 (0.22, 0.24)*	0.15 (0.14, 0.17)	0.17 (0.16, 0.18)	0.33 (0.31, 0.34)*	0.26 (0.25, 0.27)*
25	0.18 (0.17, 0.19)	0.12 (0.11, 0.13)	0.09 (0.08, 0.10)	0.30 (0.29, 0.31)*	0.19 (0.17, 0.20)
30	0.14 (0.13, 0.15)	0.10 (0.09, 0.11)	0.04 (0.03, 0.05)	0.26 (0.24, 0.27)*	0.15 (0.14, 0.16)
50	0.04 (0.03, 0.05)	0.01 (0.00, 0.02)	−0.09 (−0.10, −0.08)	0.18 (0.17, 0.19)	0.01 (0.00, 0.02)
70	−0.05 (−0.06, −0.04)	−0.06 (−0.07, −0.05)	−0.20 (−0.21, −0.19)*	0.10 (0.09, 0.11)	−0.11 (−0.12, −0.10)
75	−0.07 (−0.08, −0.06)	−0.08 (−0.09, −0.07)	−0.23 (−0.24, −0.22)*	0.08 (0.07, 0.09)	−0.15 (−0.16, −0.14)
85	−0.12 (−0.13, −0.11)	−0.10 (−0.11, −0.09)	−0.31 (−0.32, −0.30)*	0.05 (0.04, 0.06)	−0.21 (−0.22, −0.20)*
90	−0.15 (−0.16, −0.14)	−0.14 (−0.15, −0.13)	−0.35 (−0.36, −0.33)*	0.03 (0.01, 0.04)	−0.25 (−0.26, −0.24)*
95	−0.18 (−0.19, −0.17)	−0.13 (−0.14, −0.12)	−0.42 (−0.43, −0.40)*	0.01 (0.00, 0.02)	−0.30 (−0.31, −0.29)*
97	−0.19 (−0.20, −0.18)	−0.13 (−0.14, −0.12)	−0.42 (−0.43, −0.41)*	0.02 (0.01, 0.03)	−0.36 (−0.37, −0.35)*

Positive trends indicated temporal improvement and negative trends indicated temporal decreases. Standardized ESs in means of 0.2, 0.5, and 0.8 are used as thresholds for small, moderate, and large, respectively, with an ES of < 0.2 considered to be negligible. CI is the confidence interval and ES is the effect size. * represents significant changes (ES≥0.20)

Distribution characteristics trends in body size-adjusted HGS by age

Figure 2 shows the standardized ESs of changes in body size-adjusted handgrip strength performance among Chinese children and adolescents from 2000 to 2019 by sex, region, age, and percentile. Analysis of the visualization revealed that the distribution across percentiles was uneven in each age group. As the percentile increased, the trend became more negative, meaning the ES decreased. However, this unevenness gradually decreased or even disappeared as age increased. For boys aged 18 years, there were few differences in ES across percentiles (urban: −0.28 to −0.19 ES; rural: −0.35 to −0.26 ES). Furthermore, for girls aged 18 years, the curve between percentiles and ES became more gentle. Urban boys, rural boys, urban girls, and rural girls aged 7–12 years experienced small to moderate significant improvements in handgrip strength performance at most percentiles below the 50th percentile (ES ≥ 0.20). However, at most percentiles above the 50th percentile, the urban groups experienced negligible changes (ES < 0.20), while the rural groups experienced small decreases. Among those aged 13 years and older, the small improvements in the lower percentiles gradually disappeared, and small decreases were observed in more percentiles. However, urban girls experienced small to moderate improvements (ranging from 0.20 to 0.51 ES) in the lower percentiles, with small decreases (−0.24 ES) observed only at the 95th and 97th percentiles for 18-year-olds (Table S2).

Fig. 2.

Standardized ESs of changes in mean of body size (height and weight)-adjusted handgrip strength in Chinese children and adolescents aged 7–18 years from 2000 and 2019 across percentiles. Positive trends (i.e., ES > 0) indicate declines in fitness and negative trends (i.e., ES < 0) indicate improvements. The solid lines are the locally weighted scatterplot smoother curves (tension = 66), which are used to represent the trends across percentiles (range: 3rd to 97th). ES, effect size

Discussion

This study estimated the temporal trends of HGS in a representative sample of 10,822,966 children and adolescents in China from 2000 to 2019. The study found that absolute HGS increased by an average of 2.2 kg or 0.44 ES, with a small but statistically significant improvement. However, body size-adjusted HGS increased by an average of 0.6 kg or 0.05 ES, with a negligible improvement observed overall. Urban girls experienced a small improvement in body size-adjusted HGS. These trends in body size-adjusted HGS showed demographic variations, particularly in terms of age. Trends for younger groups were more positive compared to those for older groups. The distribution of trends was uneven, with trends for high performers being more negative in nature. To promote health equity, future policies and health interventions should prioritize high-risk groups, such as boys, adolescents, and low performers.

This study found an increase in HGS among Chinese children and adolescents since 2000, which was consistent with the trend reported in a large meta-analysis [15]. Studies from other countries or regions of China have provided updated trends in HGS, with varying results [26–32]. These temporal differences may attribute to regional variations, the span of measurement years, the assessment of HGS (with certain factors adjusted), and other potential confounding factors. A study of more than 16,000,000 Japanese children and adolescents reported a decline in HGS from 2013 to 2021, with the decline doubling after adjusting for body size and exercise time [26]. From 1999 to 2023, BMI-adjusted HGS increased among French children and adolescents aged 6–16 years [29]. From 2010 to 2020, both HGS and weight-adjusted HGS decreased in Poland [30]. Some studies have reported opposite trends between HGS (unadjusted [27], adjusted for height [31], or adjusted for height and weight [21, 22, 32]) and body size, i.e., an increase in body size but a decrease in HGS or body size-adjusted HGS. A Korean study reported that there were no significant changes in height, weight, and BMI among children and adolescents from 2014 to 2017, but HGS and handgrip-to-weight ratio decreased [28].

Since the force generated by muscles is directly proportional to their cross-sectional area, an increase in FFM should lead to a general increase in HGS [17]. Over the past few decades, the height, weight, and BMI of Chinese children and adolescents have continued to increase [23, 24], indicating a concurrent increase in both fat mass and FFM, which has contributed to an increase in HGS. Moreover, greater height yields greater leverage, resulting in increased absolute HGS [18]. A systematic review of trends in HGS reported that sexual maturation played a significant role in HGS development; older children typically outperformed younger ones, probably because of increased physical and neuromuscular maturity. Therefore, improvements in absolute HGS performance could be anticipated based solely on advances in maturity [15]. De Marco et al. [32] reported that trends in HGS align with trends in maturity. They reported a decline in body size-adjusted HGS, while the number of post-pubertal adolescents decreased. Reports from CNSSCH reported that the age at spermarche for Chinese boys decreased by 0.4 years from 2000 to 2019 and the age at menarche for Chinese girls decreased by 1.0 years from 1995 to 2019 [43, 44]. This study found no significant changes in HGS adjusted for height and weight over the past two decades, suggesting that increases in absolute HGS appear primarily attributable to increases in body size. However, heterogeneity analysis revealed different results, suggesting that certain confounding factors may be influencing muscle strength in Chinese children and adolescents.

This study revealed that trends in HGS vary by sex and region. Trends were relatively negative in body size-adjusted HGS for boys and rural groups. Only urban girls experienced significant improvement in body size-adjusted HGS. Chinese girls experienced faster biological maturation than boys [43, 44], which may provide girls with greater muscle strength benefits. This difference may also be related to demographic characteristics of trends in physical activity behavior. Many researchers have suggested that trends in physical activity are an important factor influencing trends in HGS [15, 27–32]. There was evidence that muscle fitness was positively related to physical activity, especially vigorous physical activity (VPA) [45]. Through physical activities involving muscle strengthening, neural adaptation will occur, thereby promoting greater activation and recruitment of motor units that contribute to generating muscular strength [46]. The CNHS reported that total sedentary time increased by 2.2, 1.3, 1.3 and 2.0 h per week for boys, girls, urban groups and rural groups, respectively, with larger increases for boys and rural groups [47]. A survey of 52,503 children and adolescents in grades 4 to 12 across 45 cities in China found that the compliance rate for boys engaging in more than 60 min of MVPA per day decreased from 2017 to 2019, but not for girls [48]. Moreover, as China’s urbanization progresses, lifestyles in urban and rural areas are converging, including dietary patterns, physical activity levels, and nutritional status. The CNSSCH survey reported that urban areas are typically high-risk areas for overnutrition. However, over the past few decades, the prevalence of overweight and obesity among rural children and adolescents has increased rapidly, narrowing or even eliminating the urban-rural gap [49]. There was a negative association between muscle strength and excess body fat. Although obesity may increase the absolute strength and power generated by extra muscles from the demand for supporting weight, individuals with obesity exhibit reduced neuromuscular activation, leading to reduced muscle performance [32, 50]. From 2002 to 2016, recreational electronic screen time increased significantly among boys and rural groups in China [51]. Compared to urban areas, the rapid increase in obesity rates in rural areas may exert a greater negative impact on muscle strength. Although these data came from different surveys, they all suggested that boys and rural groups had more negative trends in physical activity behavior and nutritional Status.

This study found significant age-related differences in trends of HGS. For absolute HGS, improvements occurred in all age groups, although some age groups showed no significant improvements. The most pronounced temporal improvements occurred during pre-puberty (at the age of 10–12), which can be explained by earlier maturation [43, 44]. It was suggested that controlling for height and weight when assessing HGS was similar to controlling for maturation [32, 52]. Although HGS was strongly associated with maturation, this association mainly could be attributed to changes in muscle growth (cross-sectional area) and the growth of anatomical structures (limb length) rather than maturation itself. After controlling for height and weight, the correlation between HGS and maturation was no longer significant [17, 32]. According to the Chinese HGS reference values for children and adolescents, HGS improved with each year of age by ~ 17% in boys and ~ 16% in girls between the ages of 7 and 12, and by ~ 11% in boys and ~ 4% in girls between the ages of 13 and 18 [53], which was nearly identical to the European reference values [15]. According to previous nationally representative studies, the maturation of urban boys, rural boys, urban girls, and rural girls has advanced by 0.3, 0.6, 0.6, and 1.1 years, respectively [43, 44]. Based on the advance in maturation alone, it can be predicted that the improvements for urban boys, rural boys, urban girls, and rural girls will be 5.1% (i.e., 0.3 [years of advancement] multiplied by 17% [age-related change]), 10.2%, 9.6%, and 17.6%, respectively, over the 19 years from 2000 to 2019 between the ages of 7 and 12. Between the ages of 13 and 18, the expected improvements for urban boys, rural boys, urban girls, and rural girls were 3.3%, 6.6%, 2.4%, and 4.4%, respectively. Although these estimates indicate that advances in biological maturation account for a large portion of the improvement in absolute HGS performance among children from 2000 to 2019, they do not explain changes in HGS among adolescents. For example, between 2000 and 2019, after adjusting for trends in biological maturation, absolute HGS in adolescents was expected to increase by 1.0% to 2.0% (the change in absolute HGS minus the expected change derived from maturation progress). However, this paper revealed that body size-adjusted HGS decreased in all age groups at the ages of 13 to 18, except urban girls, although not significant in some age groups. This suggests other factors influenced HGS trends. As previously mentioned, excessive weight gain and the rapid prevalence of obesity may explain this age-related disparity [32, 50]. Over the past decade, the prevalence of overweight and obesity among Chinese children has increased by approximately 0.2-fold, while that among adolescents has increased by more than 2-fold. The population at high risk of overnutrition is shifting from children to adolescents [54]. A meta-analysis reported that the trend in HGS during childhood, rather than during adolescence, was a good indicator of trends in MVPA and VPA; researchers speculate that any decrease in MVPA and VPA would lead to a greater decrease in HGS among adolescents than children [15]. In China, elementary school students typically face less academic pressure than secondary school students, who are under significant pressure from important entrance exams [55]. Adolescents had lower physical activity levels than children. Among adolescents aged 13–18 years, academic pressure increased with grade level, accompanied by a corresponding decrease in the time allocated to weekly physical education classes and extracurricular physical activity. The Ministry of Education stipulates three physical education classes per week for junior middle school and two classes per week for junior high school [56]. Furthermore, given the academic pressure during secondary school, the weekly physical education classes were often replaced by other subjects [55, 56]. Although China recently issued relevant documents proposing to ensure the amount and intensity of physical education classes [13, 57], the health benefits from these policies have a delayed effect. Future monitoring is needed to track changes in muscular fitness.

Trends in HGS were not consistent across different levels. In general, The trends for low-level performers are relatively more positive than those for high-level performers. Several studies reported similar distribution characteristics in China [21, 22]. In France, researchers found that the improvement in HGS mainly occurred in high-level groups [29]. From a psychosocial perspective, children with lower health levels may have lower motivation to engage in physical activity and adopt other healthy lifestyle habits compared to their peers with higher health levels [58]. They may also have lower self-efficacy and may not strive to perform well on tests [21]. On the other hand, this may be related to the baseline values of HGS. Individuals at lower levels may maintain their performance with little effort, while those at higher levels have significant potential for decline [23]. Weedon et al. [31] noted that, compared to those with higher fitness levels, those with lower fitness levels may not participate in sports or fitness-related activities outside of school, thus relying entirely on the structured physical training provided by physical education lessons. With the recent strengthening of physical education classes in China [57], low performers could gain greater health benefits compared to high performers. This distribution pattern also provides another insight: the gap between those at lower and higher levels has narrowed. This disparity may be influenced by differences in SES [29]. China has made significant efforts to eliminate health inequalities among children and adolescents, which may offer a potential explanation for the narrowing gap in muscular fitness. Specific initiatives, such as the School Milk Program (issued in 2000) and the Nutrition Improvement Program for Students in Rural Compulsory Education (issued by the State Council in 2011 and revised in 2022), have focused on providing nutritional meal subsidies to impoverished regions, thereby reducing nutritional disparities [59]. Decades ago, Chinese children and adolescents at high SES levels had better body size and nutritional status than those at low SES levels. However, this difference has nearly disappeared in recent years [20, 49]. Interestingly, as age increased, the distribution of trends in HGS became more uniform. Particularly among boys, the decreases across percentiles for 18-year-olds were nearly equal. This may be because at higher ages (junior high school), many children have reached higher levels of development in body size and skeletal muscle, and general physical activity stimuli (such as regular physical education classes) are no longer effective in improving physical fitness. Targeted programs for low performers in physical education classes may be needed in the future. Overall, there is no clear evidence regarding the causes of the differences in distribution trends of HGS. It can be speculated that certain factors may have differential impacts on specific subgroups of children and adolescents. Targeted intervention measures should be considered for groups of children and adolescents with higher health levels. In addition, formulate multi-level policies to prioritize the development of underdeveloped regions and narrow economic and health gaps.

Since children and adolescents spend most of their time in school, increased opportunities for physical activity participation in school settings may enhance health outcomes. A systematic review reported that school-based physical activity interventions could improve muscular strength levels in children and adolescents [60]. Over the past two decades, China has implemented multiple measures targeting school physical education classes and physical activities to increase physical activity among children and adolescents. The government implemented the Opinions of the Central Committee of the Communist Party of China on Strengthening Youth Sports to Enhance the Physical Fitness of Young People in 2007 to strengthen school physical education and to improve physical fitness in children and adolescents. Since then, Children and adolescents’ physical health promotion has been a national strategy [25]. The Sunshine Sports One-Hour Plan, released the same year, declared that students should engage in at least one hour of physical exercise on campus daily (including physical education classes, recess exercises, etc.), ensuring schools conduct the number of physical education classes required by the Ministry of Education [61]. The Healthy China Initiative 2019–2030 and China Child Development Outline (2021–2030) required that the excellent or good levels of national student physical fitness standards reach 60% by 2030 [13, 14]. The 2021 Double Reduction policy aimed to reduce homework and off-campus tutoring burdens for compulsory education students while encouraging extracurricular sports training and services [62]. In January 2025, the Outline of the National Education Development Plan (2024–2035) proposed implementing the Student Physical Fitness Enhancement Program, requiring primary and secondary school students to engage in at least two hours of comprehensive physical activity daily and effectively to control obesity rates [63]. Although numerous policies and strategies aim to improve the physical fitness of children and adolescents, the health benefits derived from them may not be immediately apparent. It is essential to strengthen implementation processes and feedback mechanisms, and to continuously monitor the muscular fitness of children and adolescents. Moreover, new educational policies are still needed to enhance their muscular strength. For example, new policies should aim to increase physical education class hours, the proportion of strength training time, and enhance teachers’ knowledge of muscle health through continuous professional education. Additionally, the development of muscular fitness and other components of physical fitness is imbalanced among Chinese children and adolescents [23–25]. Therefore, government initiatives should focus on priority groups to increase physical activity opportunities, particularly post-pubertal boys or high-fitness groups, in school settings.

A key strength of this study was that it was the first to reveal trends in HGS among children and adolescents nationwide in China, while adjusting for the influence of body size. Compared with other studies, the analysis of mean values and distribution characteristics provided a comprehensive understanding of the developmental characteristics of HGS among children and adolescents. The results of this study can provide a basis for the formulation of follow-up intervention measures in China and other developing countries. However, this study had several limitations. First, statistical adjustments for biological maturity and physical activity levels were not possible, and the influence of these confounding factors may affect the interpretation of trends. Second, this study was a cross-sectional study rather than a cohort study, and may be influenced by intergenerational trends. Finally, this study only included Han Chinese children and adolescents (although they account for nearly 90% of the total population), and the results should be cautiously extrapolated to other ethnic groups and the overall trend across all ethnic groups.

Conclusion

In conclusion, absolute HGS among Chinese children and adolescents has improved significantly from 2000 to 2019, but body size-adjusted HGS has not changed significantly. However, the body size-adjusted HGS significantly improved in rural girls, while decreases were observed in post-pubertal boys. The trends across distributions were uneven, with the improvement mainly occurring among those at low levels and the decline mainly occurring among those at high levels. It is recommended to strengthen health promotion strategies to improve children and adolescents’ growth and development, nutritional status, and physical activity levels. Additionally, government and relevant departments should consider that improving physical activity and promoting muscle strengthening exercises in school curricula could be key to reversing the observed trends in HGS, especially among post-pubertal boys or high-fitness groups.

Abbreviations

HGS

Handgrip strength

ES

Effect sizes

CNSSCH

Chinese National Surveillance on Students’ Constitution and Health

SES

Socioeconomic status

ES

Effect sizes

CI

Confidence interval

BMI

Body mass index

VPA

Vigorous physical activity

MVPA

Moderate-to-vigorous intensity physical activity

CHNS

China Health and Nutrition Survey

Authors’ contributions

Ziteng Li: Conceptualization, Methodology, Data curation, Formal analysis, Writing-original draft, Writing review & editing. Chengyue Li: Data curation, Visualization, Software, Validation, Resources, Writing review & editing.

Funding

This research did not receive any specific funding.

Data availability

The data analyzed during this study from CNSSCHs have been published openly and are freely available in the following publicly available books [33-37].

Declarations

Ethics approval and consent to participate

Not applicable. The study was performed in accordance with the ethical standards of the Declaration of Helsinki. The participants provided their written informed consent to participate in this study. The data analyzed during this study from CNSSCHs have been published openly and are freely available in the following publicly available books [33–37].

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.