Correlation of body mass index and serum 25-hydroxyvitamin D levels with advanced bone age in children from northwest China: a cross-sectional study

Introduction

Background

Globally, child nutrition remains a major public health challenge for all countries (1). Body mass index (BMI) is one of the important indicators to measure the degree of obesity or thinness in children and adolescents, and is often used to quickly assess nutritional status. However, recent studies have shown that bone age (BA) can more accurately reflect the level and trend of growth and development in children and adolescents. Unlike chronological age (CA), BA is primarily utilized for the assessment of children and adolescents aged 3 years and older, especially for screening for potential disorders related to abnormal pathways of growth hormone or sex steroids, such as precocious or delayed puberty, skeletal developmental abnormalities, short stature, tall stature, and growth hormone deficiency (2,3). Previous studies have reported an indirect association between abnormal skeletal maturation and childhood metabolic syndrome, including hypertension (4). The difference between BA and CA (BA-CA; BA minus CA) can be used to measure the maturity of the skeleton, and when the difference is greater than 1 year, it is generally considered that skeletal maturation is accelerated (5). Accelerated skeletal maturation promotes early epiphyseal closure in children, leading to early termination of growth and thus affecting final adult height (6,7).

Rationale and knowledge gap

Nutritional status strongly influences skeletal development: chronic malnutrition impairs bone maturation, with underweight children showing higher rates of delayed BA (8), while obesity is linked to multiple comorbidities (e.g., dyslipidemia, early puberty) and potential advanced BA (9-14). Previous studies have reported inconsistent associations between overweight/obesity and advanced BA: Artioli et al. (15) and Akridge et al. (16) found that obese children had significantly advanced BA. However, other studies have shown no significant association between overweight or obesity and advanced BA in adolescents. Russell et al. (17) suggested that obesity was not a major driver. The heterogeneity of the results of previous studies may be related to the differences in study population, sample size, BA measurement methods, and criteria for assessing nutritional status. Therefore, further studies are necessary to validate the findings.

Additionally, vitamin D deficiency is prevalent in children and adolescents, and several studies have confirmed that obese children and adolescents are at higher risk of vitamin D deficiency (18,19). Serum 25-hydroxyvitamin D [25(OH)D] plays an important role in skeletal development by regulating the uptake of calcium and phosphorus, which is essential for maintaining normal skeletal mineralization and skeletal growth (20-23). Vitamin D deficiency is more likely to affect BA advancement in obese school-aged children (19,24). Therefore, it is necessary to analyze the association between vitamin D deficiency or insufficiency and skeletal maturation.

Most existing evidence focuses on Western populations, with limited data on Asian children—particularly those in underdeveloped regions of China. Northwest China has unique environmental and dietary characteristics (e.g., cereal-dominant diets, high altitude reducing sunlight exposure) that may modify the relationship between nutrition and advanced BA (19). We hypothesized that: (I) elevated BMI (overweight/obesity) is associated with a higher risk of advanced BA in preschool and school-aged children from northwest China; and (II) vitamin D deficiency/insufficiency correlates with increased advanced BA risk. This study focuses on isolated advanced BA in healthy children, excluding children with precocious puberty or abnormal sex hormone levels, to explore the association between nutritional factors [BMI and serum 25(OH)D] and isolated advanced BA in the pediatric population.

Objective

This cross-sectional study explores the association between nutritional status (assessed by BMI), serum 25(OH)D levels, and advanced BA in children from northwest China, with the goal of informing regional nutrition interventions and health education. We present this article in accordance with the STROBE reporting checklist (available at https://tp.amegroups.com/article/view/10.21037/tp-2026-0378/rc).

Methods

Study design and subjects

A cross-sectional study was conducted at Gansu Provincial Maternity and Child-Care Hospital (a tertiary care facility in northwest China). The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study protocol was approved by the Ethics Committee of Gansu Provincial Maternity and Child-Care Hospital (ethics approval No. 2018-GSFY-019). Written informed consent has been obtained from the legal guardians of all patients.

In this study, the original data of 1,462 children aged 3 to 12 years (698 boys and 764 girls) who underwent physical examinations at the Gansu Provincial Maternity and Child-Care Hospital between February 2019 and October 2023 were collected for analysis. Inclusion criteria: (I) age 3 to 12 years old; (II) normal cognitive function; and (III) children’s guardians understood and signed the informed consent. Children with any clinical signs suggestive of pubertal onset or endocrine disorders were further evaluated or referred and were not included in the present analysis. All enrolled children were therefore considered clinically prepubertal and had not entered the Tanner stage of pubertal development, so Tanner stage data were not collected in this study. Exclusion criteria: (I) history of preterm birth or low birth weight; (II) complicated with organ dysfunction; (III) complicated with rickets, metabolic bone disease and other 25(OH)D metabolic disorders; (IV) idiopathic central precocious puberty, peripheral precocious puberty, advanced or delayed pubertal development, and other diseases associated with abnormal sex hormone levels; (V) precocious puberty; (VI) antiepileptic drugs that affect the absorption of 25(OH)D or 25(OH)D-containing nutritional supplements within the past 3 months; (VII) secondary obesity caused by endocrine diseases or genetic diseases; (VIII) drug-induced obesity; (IX) recent use of weight-loss drugs; and (X) combined infectious diseases or malignant tumors. In this study, all enrolled children underwent standardized physical examinations performed by pediatricians from the Department of Child Health Care who are experienced in growth and pubertal assessment, including inspection and palpation for breast development in girls and testicular volume or scrotal changes in boys, as well as evaluation of pubic and axillary hair and inquiry about pubertal symptoms such as rapid growth, body odour, or menstrual bleeding.

Clinical examination and anthropometric measurements

The height and weight of all included children were measured by trained specialists using standardized measurement tools and methods, and the values were accurate to 0.1 cm and 0.1 kg, respectively. For children aged 3 to 6 years, height was based on the Growth Standard for Children under 7 Years of Age by the National Health Commission of the People’s Republic of China in 2022: height < 3^rd percentile (P₃) was defined as low, P₃ ≤ height < 25^th percentile (P₂₅) as lower-middle, P₂₅ ≤ height < 75^th percentile (P₇₅) as middle, P₇₅ ≤ height < 97^th percentile (P₉₇) as upper-middle, and height ≥ P₉₇ as high. For children aged 7 to 12 years, height was according to the Standard for Height Level Classification among Children and Adolescents Aged 7 to 18 Years by the National Health Commission of the People’s Republic of China in 2018: height < −2 standard deviation (SD) was considered as low, −2SD ≤ height < −1SD was lower-middle, −1SD ≤ height < +1SD was middle, −1SD < height ≤ +2SD was upper-middle, and height > +2SD was high. BMI was calculated by the formula: BMI (kg/m²) = weight (kg)/[height (m)]². Multivariate regression models were adjusted for age and sex to account for basic demographic confounding in this clinical-focused analysis. In this study, children aged 3 to 6 years were defined as underweight, normal, overweight, and obesity using the Growth Standard for Children under 7 Years of Age by the National Health Commission of the People’s Republic of China in 2022: BMI < P₃ was considered underweight, P₃ ≤ BMI < 90^th percentile (P₉₀) was considered normal, P₉₀ ≤ BMI < P₉₇ was considered overweight, and BMI ≥ P₉₇ was obese; children aged 7 years and older were defined as underweight, normal, overweight, and obese using the Body Mass Index Growth Carves for Chinese Children and Adolescents Aged 0 to 18 Years in 2009 (25): BMI < P₃ was considered as underweight, P₃ ≤ BMI < 85^th percentile (P₈₅) was normal, P₈₅ ≤ BMI < 95^th percentile (P₉₅) was overweight, and BMI ≥ P₉₅ was obese.

Laboratory methods

Fasting venous blood samples were collected, and serum was stored at −20 ℃ until analysis. Serum 25(OH)D levels were measured via electrochemical luminescence immunoassay (Cobas e601, Roche Diagnostics, Rotkreu, Switzerland) with the following performance metrics: detection range 3–100 ng/mL; intra-batch coefficient of variation (CV) <3%; inter-batch CV <5%. Vitamin D status was defined as: deficiency, 25(OH)D <20 ng/mL; insufficiency, 25(OH)D 20–30 ng/mL; normal, 25(OH)D ≥30 ng/mL (26).

BA assessment

BA was evaluated via anteroposterior X-ray of the left wrist using the TW3 RUS method (27). Two experienced pediatricians independently interpreted the X-rays; inter-rater reliability was confirmed by an ICC of 0.91. Discrepancies (≥0.5 years difference) were resolved by a third senior pediatrician specializing in pediatric endocrinology. BA-CA <−1 is delayed BA; −1≤ BA-CA ≤+1 is normal BA; and BA-CA >+1 is advanced BA (28). The threshold of BA-CA >1 year was used as the primary definition of advanced BA because it is widely adopted in Chinese pediatric clinical practice and is clinically intuitive for identifying accelerated skeletal maturation in routine assessment. A post-hoc sensitivity analysis using the classical statistical definition of advanced BA (BA-CA > 2SD) confirmed the robustness of our findings.

Statistical analysis

Data were analyzed using SPSS 23.0 (IBM Corp.) and R 4.2.0 (R Foundation for Statistical Computing). Continuous variables are presented as mean ± SD (normal distribution) or median [interquartile range (IQR)] (non-normal distribution); categorical variables as n (%). Group comparisons used one-way analysis of variance (ANOVA) (continuous) or χ² tests (categorical).

Correlations between BMI/25(OH)D and BA-CA were analyzed using Spearman’s rank correlation because BA-CA and related continuous variables did not fully satisfy normality assumptions and the observed relationships appeared non-linear, particularly at higher BMI values. Multivariate logistic regression was used to assess the associations of BMI and vitamin D status with advanced BA and delayed BA, using the normal BA group as the clinical reference category and adjusting for age and sex. This approach was chosen to provide clinically interpretable comparisons between children with advanced or delayed BA and those with normal BA, which was the primary analytical objective of the study. ROC curves were plotted to evaluate the predictive value of BMI/25 (OH) D for advanced BA, with optimal cutoffs stratified by age (3–5, 6–8, and 9–12 years) to avoid age-related bias. A two-tailed P<0.05 was considered statistically significant.

Results

Baseline characteristics

The details of the population selection procedures are depicted in (Figure 1). Of 1,462 children, the mean age was 6.88±2.46 years (40.8% aged 3–5 years, 34.1% 6–8 years, and 25.0% 9–12 years). The overall prevalence of advanced BA was 7.9% (n=115), and delayed BA was 35.2% (n=514). Mean BMI was 16.14±2.55 kg/m²: 7.1% underweight, 71.1% normal, 8.4% overweight, and 13.3% obese. Mean serum 25(OH)D was 24.72±6.70 ng/mL: 56.2% deficient, 24.8% insufficient, and 19.1% normal (Table 1).

Figure 1 Study flowchart of participant selection, including the exact numbers excluded for each predefined exclusion criterion and key conclusions. 25(OH)D, 25-hydroxyvitamin D; BA, bone age; BMI, body mass index; TW3, Tanner-Whitehouse 3.

Comparative analyses based on BMI and 25(OH)D levels

BMI-related characteristics

The average BMI of the overall population was 16.14±2.55 kg/m², 71.14% of children had a normal BMI, while 7.11% were underweight, 8.41% were overweight, and 13.34% were obese (Table 1). The overweight and obesity groups exhibited significantly higher values in height, weight, BA, and BA-CA compared to the normal group (P<0.001 for all). However, no significant differences were found in age and 25(OH)D levels among the groups with different BMI status. While no significant age differences existed across BMI categories (P>0.05), vitamin D groups showed statistically distinct age distributions (P<0.001, Table 2). Children with vitamin D deficiency were older (7.33±2.30 years) than those with insufficiency (6.89±2.48 years) or normal status (6.27±2.49 years), possibly reflecting age-related declines in outdoor activity or increased skeletal demand during growth spurts (Table 2). The underweight group had significantly lower weight (P<0.001) and BA-CA (P<0.05) compared to the normal group, with no significant differences in height, age, BA, and 25(OH)D level. As shown in Figure 2A, median BA-CA of overweight boys (−0.08) and obese boys (0.00) was significantly higher than that of normal boys (−1.08) (P<0.05), while the median BA-CA of low weight boys (−1.17) was insignificantly different from that of normal boys. The analysis among girls in each group also revealed a similar trend (Figure 2B).

Figure 2 Boxplot of BA-CA according to BMI group in boys (A) and girls (B). Boxes represent P₂₅–P₇₅; horizontal lines, median; whiskers, 1.5× IQR; dots, outliers. ***, P<0.001; ****, P<0.0001; ns, not significant (P≥0.05) vs. normal BMI. The grouping criteria for “BMI” are detailed in the “Methods” section. BA, bone age; BA-CA, difference between BA and CA (BA minus CA); BMI, body mass index; CA, chronological age; IQR, interquartile range; P₂₅, 25^th percentile; P₇₅, 75^th percentile.

25(OH)D-related characteristics

The average serum 25(OH)D level of the overall population was 24.72±6.70 ng/mL. Among them, 19.08% of children had normal 25(OH)D levels, 56.16% were in the deficiency group, and 24.76% were in the insufficiency group (Table 1). The deficiency and insufficiency groups had significantly higher height, weight, age, and BA compared to the normal group. However, there was no significant difference in BA-CA and BMI among the three groups classified by serum 25(OH)D levels (Table 2).

BA status across different sub-groups

Genders

Out of the 1,462 children, 56.98% had normal BA, 7.87% had advanced BA, and 35.16% had delayed BA. The mean BA-CA for girls (−0.34±1.24) was significantly higher than that for boys (−0.92±1.14, P<0.001). Moreover, the proportion of girls with normal BA (61.39%) and advanced BA (11.91%) was significantly higher than that of boys (52.15% and 3.44%, respectively; P<0.05 for both) (Table 3).

Ages

The mean BA-CA for the aged 9 to 12 years group (−0.21±1.54) was significantly higher than that in aged 6 to 8 years (−0.75±1.34) and aged 3 to 5 years (−0.76±0.77) groups (P<0.001). The aged 9 to 12 years group had a significantly higher proportion of children with advanced BA compared to the other two age groups (P<0.05 for both comparisons). The aged 6 to 8 years group had a significantly higher proportion of children with delayed BA than aged 3 to 5 years and 9 to 12 years groups (P<0.05).

BMI

Although the average BA-CA did not differ significantly among the normal weight, overweight, and obese groups within the same BA status, the proportion of advanced BA in the overweight and obese group was significantly higher than that in the normal group (P<0.05). No significant differences were observed in the proportion of delayed BA and the average BA-CA between the underweight group and the normal group within the same BA status.

25(OH)D

No significant differences were found in the average BA-CA among the groups with different 25(OH)D levels within the same BA status. Also, there was no significant difference in the proportion of advanced or delayed BA in the vitamin D insufficiency and deficiency groups compared with the normal group.

Risk assessment of skeletal maturation and BA advancement

Nutritional status

In the overall population, both overweight and obesity were associated with an increased risk of advanced BA after adjustment for age and sex [overweight: odds ratio (OR) =2.49, 95% confidence interval (CI): 1.435–4.314, P<0.05; obesity: OR =2.33, 95% CI: 1.463–3.71, P<0.001]. Conversely, they were protective factors for delayed BA, with ORs of 0.356 (95% CI: 0.216–0.584, P<0.001) and 0.298 (95% CI: 0.195–0.454, P<0.001), respectively (Table 4). Similar trends were observed in the separate analyses of boys and girls.

Vitamin D

Analysis of the overall population and the female subgroup revealed no statistically significant effect of vitamin D deficiency or insufficiency on the advancement or lag of BA. In the male subgroup, vitamin D deficiency was not a risk factor for advanced BA, with OR of 0.245 (95% CI: 0.084–0.716, P<0.05).

Correlation analysis of BMI and serum 25(OH)D level with BA-CA and advanced BA

BMI-related correlations

Figure 3 demonstrates a robust dose-dependent relationship between BMI and BA-CA using non-parametric analyses. Spearman correlation revealed a significant positive association overall (ρ=0.361, P<0.001), with progressively stronger correlations across nutritional status subgroups: normal weight (ρ=0.22), overweight (ρ=0.31), and obese (ρ=0.42) (all P<0.001), while underweight children showed no association (ρ=0.03, P=0.60). This pattern was further supported by Kendall’s Tau analysis of BMI categories vs. BA-CA groups (τ=0.228, P<0.001). Notably, within the advanced BA subgroup specifically, BMI maintained significant correlations with both BA-CA (ρ=0.217, P=0.02) and absolute BA values (ρ=0.361, P<0.001). The consistently stronger Spearman coefficients compared to Pearson correlations (e.g., ρ=0.36 vs. R=0.14 for overall analysis) suggest non-linear relationships, particularly influenced by high-BMI outliers.

Figure 3 BMI correlates with BA advancement in northwest Chinese children. Scatter plots show BMI-BA-CA relationships in (A) all participants (R=0.14, P<0.001) and (B) by nutritional status: underweight (P=0.60), normal (P<0.001), overweight (P<0.001), and obese (P<0.001). Dots represent individual children. Higher BMI categories show progressively stronger associations with BA-CA, except the underweight group. The grouping criteria for “BMI” are detailed in the “Methods” section. BA, bone age; BA-CA, difference between BA and CA (BA minus CA); BMI, body mass index; CA, chronological age.

25(OH)D-related correlations

Serum 25(OH)D level had no correlation with BA-CA (Spearman correlation coefficient =−0.024, P=0.35). Correlation analysis between different serum 25(OH)D subgroups (including vitamin D deficiency, insufficiency, and normal) and BA-CA subgroups (including normal, advancement, and lagging of BA) also showed no correlation (Spearman correlation coefficient =0.001, P=0.97). In the advanced BA group, there was no correlation between serum 25(OH)D levels and BA-CA (Spearman correlation coefficient =−0.141, P=0.13) or BA (Spearman correlation coefficient =−0.069, P=0.46).

Predictive value of BMI and 25(OH)D for advanced BA

BMI

The ROC curve analysis for BMI predicting advanced BA (Figure 4A) demonstrated an area under the curve (AUC) of 0.735 (standard error =0.026, 95% CI: 0.684–0.786, P<0.001). Age-stratified analysis revealed optimal BMI cut-off values of 15.8 kg/m² for 3–5 years, 16.9 kg/m² for 6–8 years, and 18.2 kg/m² for 9–12 years. The ROC analysis showed that BMI had moderate discriminative performance for advanced BA in this sample.

Figure 4 ROC curves of BMI (A) and serum 25(OH)D levels (B) for predicting advanced BA. 25(OH)D, 25-hydroxyvitamin D; AUC, area under the curve; BA, bone age; BMI, body mass index; CI, confidence interval; ROC, receiver operating characteristic.

25(OH)D

The ROC curve of serum 25(OH)D levels predicting advanced BA (Figure 4B) showed an AUC of 0.483(standard error =0.029, 95% CI: 0.426–0.540, P>0.05), suggesting that serum 25(OH)D levels did not demonstrate discriminative value for advanced BA in this cross-sectional analysis.

Discussion

Key findings

In this study of children in northwest China, advanced BA (defined as BA-CA exceeding a specified threshold) was observed, with higher rates in girls, older children, and those with overweight or obesity compared with normal-weight children. BMI showed a positive correlation with BA advancement and demonstrated moderate predictive value for advanced BA. Both overweight and obesity were associated with advanced BA after adjustment for age and sex, although residual confounding by unmeasured factors cannot be excluded, whereas serum 25(OH)D levels were not significantly associated. Notably, the advanced BA observed was isolated, occurring without sex hormone abnormalities or precocious puberty, supporting an independent link between nutritional status and skeletal maturation in otherwise healthy children. The prevalence of overweight/obesity in this cohort was lower than the national average, and the advanced BA rate in obese children was also lower than reports from more economically developed regions of China, suggesting region-specific dietary and environmental influences.

Strengths and limitations

A key strength of this study is providing some of the first large-scale evidence from northwest China—an economically transitioning and underrepresented region—on the association between BMI, vitamin D, and advanced BA in children. BA was assessed using the reliable Tanner-Whitehouse 3 (TW3) RUS (radius, ulna, and short bones) method, and the definition of advanced BA aligns with Chinese clinical practice. The large sample size and use of ROC analysis to demonstrate BMI’s predictive value are additional strengths. However, limitations include the cross-sectional design, which precludes causal inference and allows possible reverse causation; the single-center setting in Gansu Province, limiting generalizability; the use of a fixed-year threshold that differs from SD-based criteria, complicating cross-study comparisons; only a single 25(OH)D measurement, potentially missing critical exposure windows; a small number of advanced BA cases, reducing statistical power; and the absence of sex hormone and insulin-like growth factor-1 (IGF-1), leptin, and insulin resistance data, limiting mechanistic exploration, though the study focused on isolated advanced BA without precocious puberty. In addition, we did not collect formal Tanner staging or sex hormone measurements, particularly in children aged 9–12 years, which may result in residual confounding by early pubertal maturation and limit our ability to disentangle the effects of adiposity from pubertal progression on BA advancement. Our receiver operating characteristic (ROC) estimates were derived from a single cohort without internal validation, calibration assessment, or external validation, and we did not provide detailed sensitivity, specificity, positive predictive value (PPV), or negative predictive value (NPV); therefore, these findings are exploratory and should not be used as definitive clinical thresholds.

Comparison with similar research

Interpretation of BA advancement rates across studies requires caution because assessment criteria differ across cohorts. In this study, advanced BA was defined as BA-CA >1 year, which is widely used in Chinese clinical practice, whereas Klein et al. applied both year- and SD-based thresholds and reported higher prevalence with SD-based definitions (25% vs. 19% in obese children), and Zhou et al. used Chinese-adapted TW3-Chinese standards with higher rates (29–39% in overweight/obese children) (28-30). These methodological variations in operational definitions and reference standards help explain differences in reported prevalence and underscore that our advancement rate (7.87% overall, 16.92% in obese children) should be interpreted within the specific diagnostic framework used. Our choice of a 1-year threshold was based on clinical relevance and prior validation in similar populations, but future work would benefit from standardized BA assessment criteria to improve cross-study comparability, particularly when extending population-specific findings from underrepresented regions such as northwest China.

Explanations of findings

These findings gain additional significance when considered in the context of northwest China’s unique socioeconomic and nutritional transition. The observed associations between adiposity and skeletal maturation may reflect region-specific factors including dietary patterns, physical activity levels, and environmental influences that warrant further investigation.

Here, we reported the prevalence of overweight and obesity in the overall analysis population. 21.75% of children were overweight or obesity (8.41% overweight and 13.34% obesity), lower than 23.4% (13.9% overweight and 9.6% obesity) among children and adolescents aged 7 to 18 years in 31 provinces of China (excluding Hong Kong, Macao, and Taiwan) in 2019 (31). This difference might be related to the demographic characteristics and level of economic development of northwest China. Among 1,462 children included in this study, the proportions of advanced BA and delayed BA were 7.87% and 35.16%. In terms of gender, the average BA-CA in girls (−0.34±1.24) was significantly higher than that in boys (−0.92±1.14), and the proportion of girls with advanced BA (11.91%) was also significantly higher than that in boys (3.44%). This trend aligns with Zhou et al. (28). However, unlike the results of Shu et al. (32), the proportion of girls and boys with advanced BA was 21.2% and 40.9%, respectively. This may be attributed to the study by Shu et al. employed a longitudinal design, with participants reaching an average age of 11.1 years by the third wave of assessment. In contrast, both our current study and Zhou et al.’s research utilized cross-sectional designs. This methodological difference is particularly significant as Shu’s cohort evaluated children at a more advanced pubertal stage, with 55.8% of boys having entered Tanner II genital development (mean testicular volume: 5.7±4.1 mL). Our northwest China cohort, with a younger mean age of 6.9 years, primarily examined prepubertal children. This study did not include Tanner stage data. For children aged 9–12 years with pubertal initiation, we could not analyze the synergistic effect of pubertal development stage and advanced BA. In subsequent longitudinal cohort studies, we will supplement Tanner stage data for this subgroup and further explore its interaction with advanced BA and nutritional factors. In this study, we utilized raw anthropometric values (height, weight, BMI) rather than Standard Deviation Scores (SDS). This choice aligns with routine clinical practice in China, where raw values are used alongside the clinical threshold of BA-CA ±1 year to evaluate skeletal maturation. Adjustment for age and gender in regression models effectively controls for age- and sex-related variation, ensuring the statistical robustness of our findings without SDS transformation. This age disparity may account for our potential underestimation of testosterone-mediated bone maturation effects that typically become pronounced during mid-puberty in male adolescents. In terms of age, the average BA-CA (−0.21±1.54) and the proportion of advanced BA (19.4%) in the aged 9 to 12 years old group were significantly higher than those in the aged 6 to 8 years old group and the aged 3 to 5 years old group, consistent with Khadilkar et al. (33) who found that the average magnitude of Advanced BA gradually increased with age. In terms of BMI, the percentage of advanced BA in overweight (17.07%, P<0.05) and obese (16.92%, P<0.05) children was higher than normal children (5.77%, P<0.05), similar to the survey by Oh et al. (34) that 21.1% of overweight or obese children had advanced BA. However, it is lower than the study of Zhou et al. (28) and Klein et al. (29). Zhou et al. (28) analyzed 23,305 children aged 7.7 to 11.5 years and found the presence of advanced BA in 29% of overweight boys, 33% of obese boys, 39% of overweight girls and 37% of obese girls. Klein et al. (29) showed that the prevalence of advanced BA in obese children aged 3 to 18 years was 25%. The lower prevalence of advanced BA in our study compared to Zhou et al. and Klein et al. may reflect regional differences, as their studies in more economically developed areas (e.g., Beijing) had higher obesity rates and different dietary patterns (including greater protein intake) that could accelerate skeletal maturation.

Although previous studies have focused on the relationship between skeletal development and obesity in children and adolescents, the results have been inconsistent. This study, with its relatively large sample size, provides more reliable evidence. We confirmed that BMI was positively correlated with BA (Spearman correlation coefficient =0.361, P<0.001), and that both overweight and obesity were risk factors for advanced BA, with ORs of 2.488 (P<0.05) and 2.33 (P<0.001), respectively, consistent with previous studies (16,28). This could be attributed to several mechanisms (35). Adipose tissue in obese patients secretes a large amount of adipocytokines, which leads to an increase in the levels of sex hormones (e.g., estrogen and testosterone). These hormones accelerate bone maturation and closure and accelerate the advancement of BA (5,36). Obesity is often accompanied by insulin resistance, which leads to an increase in sex hormone levels and may be associated with more rapid bone maturation and earlier closure (5,37). In addition, the low-level chronic inflammatory state triggered by obesity may also accelerate skeletal advancement by promoting cellular signaling pathways related to skeletal maturation (37). Our study found that obese children had an increased BA-CA (0.11±1.20 years), an observation that may be mediated through the aforementioned pathways involving adipokine secretion, insulin resistance, and related hormonal fluctuations. To elucidate the temporal sequence and relative contributions of these mechanisms, future longitudinal studies are warranted. Such studies should incorporate regular monitoring of dynamic changes in BMI, sex hormones, IGF-1, and 25(OH)D levels throughout childhood and adolescence. Under the joint effect of these mechanisms, the skeletal development process of obese children is accelerated, and their BA is advanced compared to that of non-obese children of the same age. Meanwhile, this study fitted the ROC curve for predicting advanced BA based on BMI levels (AUC =0.735, 95% CI: 0.684–0.786, P<0.001), indicating that BMI had moderate discriminative ability for advanced BA within this cross-sectional dataset. This has not been reported in previous studies, and this analysis provides new ideas and methods for subsequent in-depth research on the correlation between BMI and advanced BA.

In addition, children and adolescents are undergoing a period of rapid skeletal growth, and the serum 25(OH)D plays a key role in the metabolism of calcium and phosphorus, which is essential for skeletal growth and skeletal mineral metabolism (38). Our study investigated the potential association between vitamin D deficiency and BA progression in children. The results showed no correlation between serum 25(OH)D levels and advanced BA. Among those with advanced BA, the proportion of children with serum 25(OH)D levels insufficiency (8.56%, P>0.05) and deficiency (7.31%, P>0.05) did not show significant difference compared to children with normal serum 25(OH)D levels (8.60%). This is in contrast to a domestic study of girls with idiopathic central precocious puberty (ICPP), which pointed out that there was a significant negative correlation between serum 25(OH)D levels and BA-CA (r=−0.400, P<0.001) (39).

Regarding the differing BAs among the three vitamin D groups, multiple factors may be responsible. Vitamin D is pivotal in calcium and phosphorus metabolism, essential for skeletal growth and mineralization (20-22). In groups with sufficient vitamin D, normal calcium and phosphorus metabolism likely provides an optimal environment for bone development, promoting relatively “normal” BA progression. Conversely, in groups with vitamin D deficiency or insufficiency, disrupted calcium and phosphorus metabolism may derail normal bone building (23). Insufficient vitamin D can reduce intestinal calcium absorption, forcing the body to draw calcium from bones to maintain physiological balance (40). This may affect bone growth and maturation rates, causing BA-CA compared to the vitamin D-sufficient group. Moreover, vitamin D influences the activities of osteoblasts and osteoclasts, the cells responsible for bone formation and resorption, respectively (40). Inadequate vitamin D levels may imbalance these cell activities, further contributing to BA variations among the groups.

This study could not confirm a direct association between vitamin D deficiency and advanced BA, possibly due to the small number of children with advanced BA in the analysis, which accounted for only 115 of the 1,462 cases, and such a sample distribution may have led to biased results. Moreover, the definitions of vitamin D deficiency by academic institutions vary significantly among national academic institutions, including 50.0, 37.5, 30.0, and 27.5 nmol/L (41). This lack of standardization may not only affect the classification of the study population, but may further affect the reliability and comparability of the study results. Furthermore, since we only conducted one test, the essential exposure window of skeletal effects might not be captured by a single 25(OH)D measurement. Therefore, in order to more fully understand the effects of vitamin D deficiency on bone development in children, future studies need to consider standardized serum diagnostic thresholds and larger sample sizes in order to reveal potential biologic mechanisms and clinical implications.

Implications and actions needed

This study has important implications for clinical practice and public health in economically transitioning regions like northwest China. Clinically, overweight/obesity is strongly and independently associated with advanced BA with moderate BMI predictability, supporting routine BA assessment for children ≥3 years with high BMI even without precocious puberty; since vitamin D shows no significant association, weight management should be prioritized over isolated supplementation. These findings support careful growth monitoring and clinical judgment in overweight or obese children, while prospective studies are still needed before broader screening or guideline changes can be recommended. From a public health viewpoint, the unique regional context of northwest China warrants targeted community interventions focusing on healthy diet, physical activity and parental education, with preventive strategies implemented before school age.

For future research, longitudinal studies are urgently needed to confirm causality and clarify the temporal sequence between BMI gain and advanced BA, with repeated measurements of BMI, hormones, IGF-1, vitamin D and Tanner staging to explore synergistic effects; multicentre cohorts across China are required to improve generalizability, and standardization of BA and vitamin D criteria will enhance cross-study comparability. Mechanistic studies on adipokines, insulin resistance and chronic inflammation are also warranted in this understudied population.

Conclusions

Significant differences in skeletal maturation were observed among children with different nutritional statuses. Overweight and obesity are associated with advanced BA after adjustment for age and sex in this cross-sectional cohort, and a positive correlation was found between BMI and advanced BA, but no significant correlation was observed between serum 25(OH)D levels and BA-CA. These findings support closer growth and nutritional monitoring in overweight and obese children, while the role of BA assessment should be interpreted in clinical context and requires further validation in prospective studies.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://tp.amegroups.com/article/view/10.21037/tp-2026-0378/rc

Data Sharing Statement: Available at https://tp.amegroups.com/article/view/10.21037/tp-2026-0378/dss

Peer Review File: Available at https://tp.amegroups.com/article/view/10.21037/tp-2026-0378/prf

Funding: This work was supported by the Lanzhou Science and Technology Plan Project (No. 2022-5-862), the Gansu Provincial Health and Health Industry Scientific Research Plan Project (No. GSSWSK2021-0403), and the Gansu Provincial Natural Science Foundation Project (Nos. 23JRRA1378 and 26JRRA724).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-2026-0378/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Gansu Provincial Maternity and Child-Care Hospital (ethics approval No. 2018-GSFY-019), informed consent has been obtained from the legal guardians of all patients.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Hadi H, Fatimatasari F, Irwanti W, et al. Exclusive Breastfeeding Protects Young Children from Stunting in a Low-Income Population: A Study from Eastern Indonesia. Nutrients 2021;13:4264. [Crossref] [PubMed]
2. Huang S, Su Z, Liu S, et al. Combined assisted bone age assessment and adult height prediction methods in Chinese girls with early puberty: analysis of three artificial intelligence systems. Pediatr Radiol 2023;53:1108-16. [Crossref] [PubMed]
3. Mohanraj S, Prasad HK. Delayed Puberty. Indian J Pediatr 2023;90:590-7. [Crossref] [PubMed]
4. Gaston LS, Stafford DE. Premature adrenarche in Prader-Willi syndrome is associated with accelerated pre-pubertal growth and advanced bone age. J Pediatr Endocrinol Metab 2023;36:185-94. [Crossref] [PubMed]
5. Ke D, Lu D, Cai G, et al. Accelerated skeletal maturation is associated with overweight and obesity as early as preschool age: a cross-sectional study. BMC Pediatr 2020;20:452. [Crossref] [PubMed]
6. Ng SM, Stepien KM, Krishan A. Glucocorticoid replacement regimens for treating congenital adrenal hyperplasia. Cochrane Database Syst Rev 2020;3:CD012517. [Crossref] [PubMed]
7. Ni Y, Beckmann J, Gandhi R, et al. Growth to early adulthood following extremely preterm birth: the EPICure study. Arch Dis Child Fetal Neonatal Ed 2020;105:496-503. [Crossref] [PubMed]
8. Uday S, Manaseki-Holland S, Bowie J, et al. The effect of vitamin D supplementation and nutritional intake on skeletal maturity and bone health in socio-economically deprived children. Eur J Nutr 2021;60:3343-53. [Crossref] [PubMed]
9. Kumar V, Venkataraghavan K, Krishnan R, et al. The relationship between dental age, bone age and chronological age in underweight children. J Pharm Bioallied Sci 2013;5:S73-9. [Crossref] [PubMed]
10. Leung AKC, Wong AHC, Hon KL. Childhood Obesity: An Updated Review. Curr Pediatr Rev 2024;20:2-26. [Crossref] [PubMed]
11. Zhang Y, Yuan X, Yang X, et al. Associations of Obesity With Growth and Puberty in Children: A Cross-Sectional Study in Fuzhou, China. Int J Public Health 2023;68:1605433. [Crossref] [PubMed]
12. Liu LJ, Kang YR, Xiao YF. Increased asprosin is associated with non-alcoholic fatty liver disease in children with obesity. World J Pediatr 2021;17:394-9. [Crossref] [PubMed]
13. Zeljkovic A, Vekic J, Stefanovic A. Obesity and dyslipidemia in early life: Impact on cardiometabolic risk. Metabolism 2024;156:155919. [Crossref] [PubMed]
14. Soliman A, Alyafei F, Elawwa A, et al. Impact of BMI on childhood growth, pubertal timing, and bone maturation: A comprehensive review and clinical implications. World Journal of Advanced Research and Reviews 2024;23:2093-106.
15. Artioli TO, Alvares MA, Carvalho Macedo VS, et al. Bone age determination in eutrophic, overweight and obese Brazilian children and adolescents: a comparison between computerized BoneXpert and Greulich-Pyle methods. Pediatr Radiol 2019;49:1185-91. [Crossref] [PubMed]
16. Akridge M, Hilgers KK, Silveira AM, et al. Childhood obesity and skeletal maturation assessed with Fishman’s hand-wrist analysis. Am J Orthod Dentofacial Orthop 2007;132:185-90. [Crossref] [PubMed]
17. Russell DL, Keil MF, Bonat SH, et al. The relation between skeletal maturation and adiposity in African American and Caucasian children. J Pediatr 2001;139:844-8. [Crossref] [PubMed]
18. Fu Z, Xu C, Shu Y, et al. Serum 25-hydroxyvitamin D is associated with obesity and metabolic parameters in US children. Public Health Nutr 2020;23:1214-22. [Crossref] [PubMed]
19. Fiamenghi VI, Mello ED. Vitamin D deficiency in children and adolescents with obesity: a meta-analysis. J Pediatr (Rio J) 2021;97:273-9. [Crossref] [PubMed]
20. Benameur T. Seasonal Variations in 25-Hydroxyvitamin D Levels among Pediatric Patients Attending the Healthcare Centre. Nutrients 2024;16:379. [Crossref] [PubMed]
21. Ming D, Zheng R. Monitoring of serum 25-(OH)D level in infants and its correlation with bone density and development. Cell Mol Biol (Noisy-le-grand) 2023;69:64-8. [Crossref] [PubMed]
22. Xiong T, Wu Y, Li Y, et al. Association of serum 25-hydroxyvitamin D with bone health measured by calcaneal quantitative ultrasound: a large cross-sectional analysis in children and adolescents. Food Funct 2024;15:1379-89. [Crossref] [PubMed]
23. Xu Y, Song L, Zhou L. The association of vitamin D insufficiency with the prevalence of obesity in children: implications for serum calcium levels, alkaline phosphatase activity, and bone maturation. Front Nutr 2024;11:1466270. [Crossref] [PubMed]
24. Pereira-Santos M, Costa PR, Assis AM, et al. Obesity and vitamin D deficiency: a systematic review and meta-analysis. Obes Rev 2015;16:341-9. [Crossref] [PubMed]
25. Li H, Ji CY, Zong XN, et al. Body mass index growth curves for Chinese children and adolescents aged 0 to 18 years. Zhonghua Er Ke Za Zhi 2009;47:493-8.
26. Płudowski P, Kos-Kudła B, Walczak M, et al. Guidelines for Preventing and Treating Vitamin D Deficiency: A 2023 Update in Poland. Nutrients 2023;15:695. [Crossref] [PubMed]
27. Keylock L, Cameron N. Reproducibility of bone age assessment from DXA hand scans: expert versus novice. Ann Hum Biol 2021;48:343-5. [Crossref] [PubMed]
28. Zhou B, Qu X, Li M, et al. Correlation of bone age development with overweight and obesity in 23,305 children from Beijing. Endocrine 2025;87:304-13. [Crossref] [PubMed]
29. Klein KO, Newfield RS, Hassink SG. Bone maturation along the spectrum from normal weight to obesity: a complex interplay of sex, growth factors and weight gain. J Pediatr Endocrinol Metab 2016;29:311-8. [Crossref] [PubMed]
30. Wang Y, Lan T, Zhang Q, et al. Myeloma cell-derived CXCL7 facilitates proliferation of tumor cells and occurrence of osteolytic lesions through JAK/STAT3 pathway. Cell Death Dis 2025;16:74. [Crossref] [PubMed]
31. Dong YH, Chen L, Liu JY, et al. Epidemiology and prediction of overweight and obesity among children and adolescents aged 7-18 years in China from 1985 to 2019. Zhonghua Yu Fang Yi Xue Za Zhi 2023;57:11-9. [Crossref] [PubMed]
32. Shu W, Li M, Vermund SH, et al. Body composition trajectories during childhood predict skeletal maturation at puberty: A longitudinal study. Heliyon 2024;10:e36381. [Crossref] [PubMed]
33. Khadilkar V, Oza C, Khadilkar A. Relationship between height age, bone age and chronological age in normal children in the context of nutritional and pubertal status. J Pediatr Endocrinol Metab 2022;35:767-75. [Crossref] [PubMed]
34. Oh MS, Kim S, Lee J, et al. Factors associated with Advanced Bone Age in Overweight and Obese Children. Pediatr Gastroenterol Hepatol Nutr 2020;23:89-97. [Crossref] [PubMed]
35. Mitra AT, Das B, Sarraf KM, et al. Bone health following paediatric and adolescent bariatric surgery: a systematic review and meta-analysis. EClinicalMedicine 2024;69:102462. [Crossref] [PubMed]
36. Sopher AB, Jean AM, Zwany SK, et al. Bone age advancement in prepubertal children with obesity and premature adrenarche: possible potentiating factors. Obesity (Silver Spring) 2011;19:1259-64. [Crossref] [PubMed]
37. Chávez-Vázquez AG, Klünder-Klünder M, Lopez-Gonzalez D, et al. Association between bone age maturity and childhood adiposity. Pediatr Obes 2024;19:e13166. [Crossref] [PubMed]
38. Hu Y, Jiang S, Lu J, et al. Vitamin D Status for Chinese Children and Adolescents in CNNHS 2016-2017. Nutrients 2022;14:4928. [Crossref] [PubMed]
39. Liang ZH, Dai Y, Tao MJ, et al. Study on the Relationship Between Vitamin D Level and the ICPP of Girls. China Health Standard Management 2020;11:5-8.
40. Charoenngam N, Shirvani A, Holick MF. Vitamin D for skeletal and non-skeletal health: What we should know. J Clin Orthop Trauma 2019;10:1082-93. [Crossref] [PubMed]
41. Child Health Care Group, Pediatrics Branch of Chinese Medical Association. Editorial Board of Chinese Journal of Pediatrics. Practical guidelines for clinical issues related to vitamin D nutrition in Chinese children. Chinese Journal of Pediatrics 2022;60:387-94.