Abstract
Background
With the increasing prevalence of abdominal obesity among children and adolescents, identifying easily measurable, safe, efficient, low-cost, and highly effective indicators is crucial in public health management. While neck-to-height ratio (NHtR) is a better indicator of upper body fat than neck circumference (NC), current research on this indicator mainly assesses its role in obesity and related metabolic diseases among adults. Therefore, this study aimed to investigate the clinical significance of the (NHtR) in screening for abdominal obesity among children and adolescents.
Methods
The cross-sectional study enrolled 3,728 children and adolescents aged 7–17 years. Participants were categorized into three groups: abdominal obesity, pre-abdominal obesity, and normal. Continuous variables (NC, NHtR, WC, WHtR) were compared using analysis of variance or the Kruskal–Wallis H test. Partial correlation analysis was conducted between NHtR and WC/WHtR.ROC curve analysis assessed NHtR’s accuracy in screening abdominal obesity. A subset of 970 participants underwent model validation using both internal (7:3 split) and external datasets, evaluated by receiver operating characteristic (ROC), area under the curve (AUC), and calibration curves.
Results
The prevalence of abdominal obesity was 22.91% among participants. Significant statistical differences were observed in NC and NHtR among the three groups. After controlling for age, partial correlation analysis revealed positive correlations between NHtR and both WC and WHtR in boys and girls. Receiver operating characteristic curve analysis revealed that the area under the curve for NHtR, in assisting with the screening of abdominal obesity, was 0.810. The optimal cutoff values of NHtR were 0.21 and 0.20 for boys and girls, respectively, with age-specific values ranging from 0.20 to 0.22. Furthermore, the NHtR model demonstrated strong predictive ability for abdominal obesity, with excellent goodness of fit.
Conclusions
This study highlights NHtR as an effective indicator for screening abdominal obesity in children and adolescents, supporting early detection and intervention strategies to improve public health outcomes related to abdominal obesity.
Keywords: Neck-to-height ratio, Children, Adolescents, Abdominal obesity, Screening
Background
Abdominal obesity, also termed visceral or central obesity, is a condition characterized by the accumulation of subcutaneous, omental, mesenteric, and retroperitoneal fat in the abdominal region. It is associated with an increased risk of various diseases, including cardiovascular diseases, diabetes, heart disease, metabolic dysfunction-associated fatty liver disease (MAFLD), cancers, and kidney diseases, significantly impacting physical and mental health [1, 2]. The incidence of abdominal obesity among children and adolescents varies regionally; however, the general tendency is increasing. Five nationwide cross-sectional surveys conducted in Australia found that its prevalence among children and adolescents aged 7–15 years increased from 8.6 to 23.3% between 1985 and 2015 [3]. Similarly, the prevalence of abdominal obesity among Chinese children and adolescents aged 6–17 years increased from 5.0% in 1993 to 19.3% in 2015 [4]. A study conducted in Nanjing, China, in 2023 indicated that its prevalence among children and adolescents was approximately 29.4% [5]. Since obesity is preventable, identifying easily measurable, safe, efficient, low-cost, highly effective, and rapidly interpretable indicators of abdominal obesity in children and adolescents will be of great significance for managing public health.
Anthropometry is a simple, efficient, economical, and widely recognized method that has been widely applied in large-scale screening [4]. Waist circumference (WC) and waist-to-height ratio (WHtR) are associated with childhood central obesity and are commonly used indicators for its evaluation [6, 7]. While the WC has different reference values based on age and sex, the WHtR overcomes this limitation as an adjusted index and has been widely applied to assess central obesity during growth and development [8, 9]. However, WC measurement can be influenced by various factors, including diet, bowel movements, breathing patterns, gastrointestinal diseases, and history of abdominal surgeries, which limit the application of WC and WHtR in large-scale screenings. Neck circumference (NC) is a reliable indicator of upper body fat tissue, unaffected by factors such as eating, has higher stability, and avoids the inconvenience of exposing privacy by requiring clothing removal [10–12]. Recent studies have suggested that NC could serve as an indicator of overweight and obesity, as well as abdominal obesity in children [13–15]. However, NC is influenced by factors such as sex, age, and body shape, leading to significant fluctuations. The neck-height ratio (NHtR) retains the basic characteristics of NC, avoids the effects of age and gender, and exhibits a small degree of variation among children of different ages [16–18].NHtR is considered a better indicator of upper body fat than NC [16–19]. Currently, research on the NHtR mainly focuses on assessing obesity and related metabolic diseases in adults and the assessment of children’s obesity and sleep apnea syndrome. There is no study on the screening of abdominal obesity in children and adolescents[12, 20–22]. Therefore, this study aimed to explore the application value of NHtR in assessing abdominal obesity among children and adolescents, as well as evaluate its correlation with existing classic indicators.
Methods
General information
In this cross-sectional study, a cluster random sampling method was applied to select students from two primary and two secondary schools in Zhengzhou, Henan Province, as research participants for the training set for model construction between May 2023 and May 2024. A total of 4,049 children and adolescents aged 7–17 years participated in the survey. After excluding 321 children and adolescents with obvious errors and incomplete information in the physical examination data, 3,728 (2,081 males (55.82%) and 1,647 females (44.18%)) were included, accounting for 92.07% of the total sample.
Overall, 970 patients aged 7–17 years who visited an Endocrinology and Genetic Metabolism Department outpatient clinic at a Children’s Hospital in Henan Province between May 2024 and August 2024 were selected as an external validation set for model construction and validation.
The inclusion criteria were ① age between 7 and 17 years and ② the ability to cooperate with the completion of physical measurement indicators. In contrast, the exclusion criteria comprised: ① children and adolescents with cervical deformities, cervical trauma, thyroid disorders, mumps, or other cervical region pathologies, and ② secondary obesity.
This study was conducted with informed consent obtained from the participants and their parents, who signed the consent forms. Its protocol was approved by the Medical Ethics Committee of Zhengzhou University Children’s Hospital (Ethics No.: 2021-H-K31) and was performed following the ethical standards outlined in the 1964 Declaration of Helsinki and its later amendments or other comparable ethical standards.
Research methods
Physical examination data collection
A unified basic information collection form was established to obtain the name, sex, date of birth, and age of children and adolescents. This form was completed by the class teachers (training set) or specialist doctors (validation set) and verified by the parents. Age was calculated as the precise number of days between the survey date and the date of birth. Subsequently, the actual age was calculated by dividing this exact number of days by 365, with two decimal points retained. Age was categorized into groups ranging from 7 to < 17 years, with each group representing 1 year. The measurements of height, weight, NC, WC, and hip circumference (HC) were taken following established standards [14]. All measurement instruments were uniform and rigorously calibrated. The child was required to stand upright, remove shoes and socks, take off the hat, and wear only a single garment. The child was required to fast and empty the bladder. The electronic column scale (model 704, produced by Hangzhou Saikang Medical Measurement System Co., Ltd.) was used for height and weight measurement. The flexible tape measure (LYRC-01, China Pengyi Company) was used in NC, WC, and HC. Take the average value after measuring three times. Height, weight, NC, WC, and HC were measured three times simultaneously, and the average value was recorded. Measurements of height, NC, WC, and HC were recorded to the nearest 0.1 cm, while weight was recorded to the nearest 0.1 kg. The following ratios were calculated: NHtR = NC (cm)/height (cm), WHtR = WC (cm)/height (cm), waist-to-hip ratio (WHR) = WC (cm)/HC (cm), and body mass index (BMI) = weight (kg)/height squared (m2), calculated to an accuracy of 0.01.
Diagnostic criteria
Criteria for abdominal obesity and prediabetes of abdominal obesity
Abdominal obesity and pre-abdominal obesity were classified as WC values above the 90th percentile and between the 75th and 90th percentiles for sex and age, respectively [6, 23].
The study participants were categorized into three groups: abdominal obesity, pre-abdominal obesity, and normal.
Criteria for determining obesity in children and adolescents
Overweight/obesity was determined by a BMI equal to or greater than the corresponding age and sex group’s thresholds for “overweight” or “obesity” according to the “Screening for Overweight and Obesity in School-age Children and Adolescents” (WS/T586-2018) [24].
Quality control
Project and quality control teams were formed to develop and implement standardized plans. Centralized training was provided to all participating medical staff and class teachers, with only those who passed the training being eligible to participate in on-site work. Before implementation, the venues were deemed suitable, all instruments and equipment were verified for accuracy and completeness, and the consistency of the measurement tools used across different stages was ensured. All data were carefully recorded and organized, adhering to the double-entry principle, and verified to guarantee authenticity and accuracy.
Statistical analysis
All statistical analyses were conducted using IBM SPSS Statistics for Windows, version 24.0 (IBM Corp., Armonk, N.Y., USA). Normality was tested using the Kolmogorov-Smirnov method. Normally distributed data are presented as mean ± standard deviation, while between-group comparisons were performed using t-tests. Non-normally distributed data were expressed as median (P25–P75) and compared using rank-sum tests. Categorical variables were reported as frequency (percentage) and analyzed using chi-square tests. Continuous variables were compared using analysis of variance or the Kruskal–Wallis H test, based on normality. Pearson’s and Spearman’s correlation analyses were applied for normally and non-normally distributed data, respectively, with partial correlation analysis used to adjust for age in NHtR and WC/WHtR associations. Receiver operating characteristic (ROC) curve analysis was used to assess the accuracy of NHtR in screening for abdominal obesity in children. Statistical tests were two-tailed with α = 0.05. R, version 4.2.2 (R Core Team, R Foundation for Statistical Computing, Vienna, Austria) was used for model validation and calibration curves.
Establishment and validation of predictive models
Data from children with abdominal obesity included in the study were classified into training and internal validation sets in a 7:3 ratio. Those from children without obesity were used as an external validation set. This study designated NHtR as the core variable, with age, sex, BMI, and WC included as predictors. BMI and WC were incorporated as established obesity metrics to evaluate NHtR’s incremental predictive value beyond conventional indicators. Age and sex—key determinants of growth and body composition—served as stratification/adjustment variables. The predictive ability of the NtHR for abdominal obesity was quantified using the odds ratios, while the quality of the model’s fit was evaluated using the Akaike Information Criterion. ROC curves were constructed, and the area under the curve (AUC) was determined to assess the model’s predictive performance within the training dataset. Calibration curves were also plotted to evaluate the model’s calibration accuracy. The optimal cutoff value for classification was determined using the Youden index in the training set. Predicted patients were categorized into the abdominal and non-abdominal obesity groups, and their consistency with the actual abdominal and non-abdominal obesity groups was tested. Clinical decision curves were employed to evaluate the model’s potential clinical utility. For the internal and external validation cohorts, the established risk prediction model was used to determine the probability of abdominal obesity for each child, and ROC curves were constructed, and AUCs were calculated to validate the predictive ability. Similarly, calibration curves were plotted in the internal and external validation sets to verify the model’s calibration ability. The “glmnet” and “rms” packages were used to plot calibration curves and assess model calibration, while the Hosmer–Lemeshow test (HL test) was used to evaluate model fit. Two-sided tests were conducted, with a significance level set at P < 0.05.
Results
General characteristics of the study population
A total of 3,728 children aged 7–17 (mean age, 11.55 ± 2.82) years were enrolled. The detection rate of abdominal obesity and obesity incidence were 22.91% (854 individuals) and 16.52% (616 individuals), respectively. Specifically, the detection rates of abdominal obesity in boys and girls were 24.27% (508) and 21.01% (346), respectively. Table 1 presents the comparisons of the detection rates of obesity, body weight, BMI, NC, WC, HC, NHtR, WHtR, and WHR among children and adolescents in the abdominal obesity, pre-abdominal obesity, and normal groups.
Table 1.
Comparison of basic information and body measurement indicators among the three groups
| Item | Abdominal Obesity Group (n = 854) |
Pre-Abdominal Obesity Group (n = 703) | Normal Group (n = 2,171) |
F/χ3 | P |
|---|---|---|---|---|---|
| Age [(mean ± SD) years] | 11.60 ± 2.79 | 11.86 ± 2.83c | 11.33 ± 2.82b | 6.247 | < 0.01 |
| Sex, n (%) | 47.581 | < 0.001 | |||
| Male | 508 (59.48%) | 311 (44.24%) | 1,262 (58.13%) | ||
| Female | 346 (40.51%)b | 392 (55.76%) | 909 (41.85%)b | ||
| Obesity, n (%) | 540 (63.23%)b, c | 63 (8.96%)a, c | 13 (0.60%)a, b | 1,779.053 | < 0.001 |
| Height (mean ± SD) cm | 151.6 ± 15.25c | 150.4 ± 15.95c | 145.8 ± 16.35a, b | 50.200 | < 0.001 |
| Weight (mean ± SD) kg | 57.7 ± 19.08b, c | 47.00 ± 14.63a, c | 38.20 ± 11.98a, b | 578.914 | < 0.001 |
| BMI (mean ± SD) kg/m2 | 24.39 ± 4.33b, c | 20.20 ± 3.17a, c | 18.13 ± 2.85a, b | 1,568.086 | < 0.001 |
| NC (mean ± SD) cm | 32.36 ± 3.74b, c | 30.23 ± 3.29a, c | 28.50 ± 2.88a, b | 484.341 | < 0.001 |
| WC (mean ± SD) cm | 80.6 ± 10.26b, c | 68.80 ± 6.75a, c | 59.09 ± 6.91a, b | 2,403.592 | < 0.001 |
| HC (mean ± SD) cm | 91.80 ± 11.27b, c | 84.60 ± 9.34a, c | 78.15 ± 10.78a, b | 751.551 | < 0.001 |
| NHtR (mean ± SD) | 0.21 ± 0.01b, c | 0.20 ± 0.01a, c | 0.19 ± 0.01a, b | 420.503 | < 0.001 |
| WHtR (mean ± SD) | 0.53 ± 0.05b, c | 0.45 ± 0.02a, c | 0.40 ± 0.03a, b | 3,580.248 | < 0.001 |
| WHR (mean ± SD) | 0.87 ± 0.06b, c | 0.82 ± 0.04a, c | 0.78 ± 0.06a, b | 833.606 | < 0.001 |
aCompared to the abdominal obesity group; P < 0.05. bCompared to the pre-abdominal obesity group, P < 0.05. cCompared to the normal group, P < 0.05
HC Hip circumference, NC Neck circumference, NHtR Neck-height ratio, WC Waist circumference, WHR Waist-to-hip ratio, WHtR Waist-to-height ratio, BMI Body mass index, SD Standard deviation
NHtR of children and adolescents across the three groups
The NHtR of children and adolescents with abdominal obesity across different ages was significantly higher than that of the pre-abdominal obesity group and the normal group. In children aged between 11 and < 17 years, the NHtR of pre-abdominal obesity children and adolescents was significantly lower than that of the abdominal obesity group and higher than that of the normal group.With significant differences (all P < 0.05) (Table 2).In all age groups, the neck height ratio of boys was higher than that of girls (Fig. 1).
Table 2.
Comparison of the NHtR across three groups categorized by age
| Age (years) | N | Abdominal Obesity Group (n = 854) |
Pre-Abdominal Obesity Group (n = 703) | Normal Group (n = 2,171) |
F | P |
|---|---|---|---|---|---|---|
| 7 | 485 | 0.216 ± 0.012bc | 0.209 ± 0.010a | 0.208 ± 0.016a | 8.794 | 0.000 |
| 8 | 399 | 0.216 ± 0.152bc | 0.207 ± 0.019a | 0.204 ± 0.017a | 19.204 | 0.000 |
| 9 | 442 | 0.217 ± 0.017bc | 0.202 ± 0.014a | 0.199 ± 0.014a | 56.942 | 0.000 |
| 10 | 365 | 0.216 ± 0.017bc | 0.201 ± 0.015a | 0.200 ± 0.013a | 43.601 | 0.000 |
| 11 | 390 | 0.208 ± 0.018bc | 0.197 ± 0.009ac | 0.189 ± 0.012ab | 67.617 | 0.00 |
| 12 | 341 | 0.208 ± 0.012bc | 0.201 ± 0.014ac | 0.186 ± 0.010ab | 133.960 | 0.000 |
| 13 | 354 | 0.212 ± 0.014bc | 0.198 ± 0.013ac | 0.189 ± 0.010ab | 102.345 | 0.000 |
| 14 | 344 | 0.210 ± 0.012bc | 0.198 ± 0.012ac | 0.190 ± 0.010ab | 93.388 | 0.000 |
| 15 | 348 | 0.216 ± 0.013bc | 0.202 ± 0.014ac | 0.193 ± 0.009ab | 105.495 | 0.000 |
| 16 | 348 | 0.216 ± 0.013bc | 0.202 ± 0.014ac | 0.193 ± 0.009ab | 105.495 | 0.000 |
aCompared with the abdominal obesity group, P < 0.05; bCompared with the pre-abdominal obesity group, P < 0.05; cCompared with the normal group, P < 0.05. NHtR, Neck-height ratio
Fig. 1.
Age trends in the NHtR of children and adolescents by sex
Correlation of NHtR with WC and WHtR among children and adolescents
After controlling for age, partial correlation analysis showed positive correlations between NHtR and WC in boys (r = 0.537, P < 0.001) and girls (r = 0.515, P < 0.001), as well as between NHtR and WHtR in boys (r = 0.540, P < 0.001) and girls (r = 0.637, P < 0.001).
ROC Curve analysis of NHtR for assessing abdominal and pre-abdominal obesity among children and adolescents
Using abdominal obesity and NHtR as the status and test variables, respectively, ROC curve analysis identified an AUC value of 0.810 for NHtR in assisting abdominal obesity screening in boys (95% confidence interval [CI]: 0.788–0.832) and girls (95% CI: 0.781–0.838). The optimal cutoff values of NHtR were 0.21 for boys and 0.20 for girls, with sensitivities of 0.793 and 0.850, respectively, and specificities of 0.698 and 0.630.
With pre-abdominal obesity and NHtR as the status and test variables, respectively, the ROC curve analysis identified AUC values of 0.654 and 0.623 for NHtR in assisting pre-abdominal obesity screening in boys (95% CI: 0.622–0.686) and females (95% CI: 0.590–0.655), respectively. The optimal cutoff values of NHtR were 0.20 for boys and 0.19 for females, with sensitivities of 0.842 and 0.875, respectively, and specificities of 0.399 and 0.289.
ROC Curve analysis of NHtR across various age groups to aid in abdominal obesity assessment among children and adolescents
Using abdominal obesity and NHtR as the status and test variables, respectively, the ROC curve analysis results showed that the AUC value across the different age groups of boys and girls ranged from 0.704 to 0.992. Tables 3 and 4 presents the optimal cutoffs for boys and girls.
Table 3.
ROC curve analysis of NHtR in assessing abdominal obesity among children and adolescents of different ages in males
| Age(years) | AUC | 95%CI | Cutoff value | Sensitivity | Specificity |
|---|---|---|---|---|---|
| 7 | 0.704 | 0.630–0.778 | 0.22 | 0.706 | 0.694 |
| 8 | 0.757 | 0.679–0.853 | 0.22 | 0.879 | 0.766 |
| 9 | 0.821 | 0.760–0.881 | 0.22 | 0.654 | 0.694 |
| 10 | 0.762 | 0.681–0.843 | 0.22 | 0.621 | 0.857 |
| 11 | 0.886 | 0.819–0.953 | 0.22 | 0.698 | 1.000 |
| 12 | 0.876 | 0.815–0.937 | 0.20 | 0.864 | 0.731 |
| 13 | 0.930 | 0.889–0.971 | 0.21 | 0.767 | 0.959 |
| 14 | 0.904 | 0.853–0.955 | 0.21 | 0.750 | 0.935 |
| 15 | 0.940 | 0.895–0.986 | 0.21 | 0.953 | 0.835 |
| 16 | 0.873 | 0.807–0.940 | 0.21 | 0.789 | 0.844 |
ROC Receiver operating characteristic, CI Confidence interval, AUC Area under the curve, NHtR Neck-height ratio
Table 4.
ROC curve analysis of NHtR in assessing abdominal obesity among children and adolescents of different ages in females
| Age (years) | AUC | 95%CI | Cutoff value | Sensitivity | Specificity |
|---|---|---|---|---|---|
| 7 | 0.714 | 0.598–0.829 | 0.22 | 0.618 | 0.865 |
| 8 | 0.760 | 0.651–0.868 | 0.22 | 0.600 | 0.923 |
| 9 | 0.814 | 0.721–0.907 | 0.21 | 0.762 | 0.835 |
| 10 | 0.794 | 0.697–0.892 | 0.21 | 0.700 | 0.881 |
| 11 | 0.820 | 0.733–0.906 | 0.20 | 0.630 | 0.957 |
| 12 | 0.992 | 0.980–1.000 | 0.20 | 1.000 | 0.965 |
| 13 | 0.939 | 0.891–0.986 | 0.20 | 0.885 | 0.861 |
| 14 | 0.902 | 0.837–0.968 | 0.20 | 0.906 | 0.756 |
| 15 | 0.907 | 0.857–0.957 | 0.20 | 0.970 | 0.759 |
| 16 | 0.927 | 0.881–0.973 | 0.20 | 1.000 | 0.792 |
ROC Receiver operating characteristic, CI Confidence interval, AUC Area under the curve, NHtR Neck-height ratio
Internal and external validation of the predictive value of NHtR for abdominal obesity risk assessment among children and adolescents
Figure 1 presents the ROC curve analyses of the model in the training, internal validation, and external validation sets. In the training set of males, the AUC value of the model was 0.813 (95% CI: 0.788–0.838), while the corresponding values in the internal and external validation sets were 0.776 (95% CI: 0.733–0.819) and 0.618 (95% CI: 0.568–0.669), respectively. The AUC value of the model in the training set of girls was 0.790 (95% CI: 0.755–0.825), while the corresponding values in the internal and external validation sets were 0.804 (95% CI: 0.755–0.852) and 0.756 (95% CI: 0.691–0.822), respectively. Therefore, the AUC values of the model in the training, internal validation, and external validation sets indicate that the NHtR has good predictive ability for abdominal obesity among children and adolescents of both sexes (Fig. 2).
Fig. 2.
a, (b), and (c) represent the ROC curves for the training, internal validation, and external validation sets of boys, respectively. d, (e), and (f) represent the ROC curves for the training, internal validation, and external validation sets of girls, respectively ROC, Receiver operating characteristic
The model shows good agreement between the predicted and actual values in the training, internal validation, and external validation sets, indicating good calibration ability. Figure 2 shows the HL test results in the training, internal validation, and external validation sets for boys. The HL test results in the training, internal validation, and external validation sets for girls show that the model has a good fit (Fig. 3).
Fig. 3.
a, (b), and (c) represent the calibration curves for the training, internal validation, and external validation sets of boys, respectively. d, (e), and (f) represent the calibration curves for the training, internal validation, and external validation sets of girls, respectively
Discussion
Abdominal obesity is closely associated with systemic inflammation and insulin resistance [25]. Various screening indicators for abdominal obesity have been established, including WC, WHtR, WHR, NC, Serum adiponectin, Serum leptin, lipid accumulation index, abdominal subcutaneous and visceral fat volumes [26, 27]. Magnetic resonance imaging and CT scans usually require professional equipment and operators, and the examination costs are high. Moreover, there may be a certain radiation risk for children and adolescents (such as CT scans), so the application of magnetic resonance imaging and CT scans in large-scale screening is limited. The detection of biochemical markers requires venous blood sampling, which is relatively complex and affected by many factors, and the stability of the results needs to be further improved. In contrast, simple, non-invasive, and easy-to-operate anthropometric indicators can be measured quickly without specialized equipment, which is more suitable for large-scale screening of abdominal obesity in children and adolescents. This study explored the feasibility of using height-adjusted NHtR as a screening indicator for abdominal and pre-abdominal obesities in children and adolescents aged 7–17 years. The results indicated that the NHtR of children and adolescents in the abdominal obesity group was higher than that of the pre-abdominal obesity group and the normal group across different age groups. After controlling for age, the NHtR of males and females showed a positive correlation with classical indicators of abdominal obesity, such as WC and WHtR. NHtR has relatively high accuracy in screening for abdominal obesity, with optimal cutoff values of 0.21 and 0.20 for boys and girls, respectively. The risk model for predicting abdominal obesity in children and adolescents aged 7–17 years in this study showed high AUC values in the training, internal validation, and external validation sets, indicating that the NHtR has good predictive ability for abdominal obesity in both sexes. However, the external validation AUC for boys (0.618) was lower compared to the training and internal validation sets. This reduction may stem from demographic cohort differences, variability in assessment of neck circumference and height, and potential discrepancies in temporal data collection. To enhance the generalizability of the NHtR model, future studies could employ external-data recalibration or stratified XXXodelling. The calibration curve showed that the NHtR model had good calibration ability, as the predicted values were well-aligned with the actual values in the training, internal validation, and external validation sets. These results indicate that the NHtR is a novel method for screening abdominal obesity in children and adolescents. Our study findings align with those of previous studies that have linked NHtR with metabolic syndrome, obstructive sleep apnea syndrome, MAFLD, and other metabolic disorders [16, 17, 19, 28].
In the present study, the prevalence of abdominal obesity among children and adolescents aged 7–17 years in Henan Province was 22.91%, which is higher than the 19.4% reported in 2019 for the urban area of Henan Province. This may be attributable to the significant increase in overweight and obesity rates among children and adolescents following the coronavirus disease 2019 pandemic, indicating the need for more attention to childhood obesity [29]. The prevalence of abdominal obesity was higher in boys than in girls in this study, which aligns with the findings of Lewitt and Baker [30] and Kuk and Lee [31]. Possible reasons for this may be that males have lower perceptual ability and expend less effort in weight control than females [32]. Estrogen can also prevent body fat increase by suppressing appetite and increasing energy consumption [33]. Furthermore, the distribution of fat tissue differs between boys and girls, with boys having a higher proportion of visceral fat in total fat [28, 30]. The high rate of abdominal obesity among boys demonstrates the value of concentrating on this demographic. However, Heshmat et al. [34] obtained different results, showing through a cross-sectional study of 4,200 children aged 7–18 years from 30 provinces that the prevalence of abdominal obesity was significantly higher in girls (12.4%) than in boys (11.9%). This difference may be related to socio-demographic factors and racial differences.
In the present study, the optimal cutoff for NHtR remained consistent across different sex and age groups, ranging from 0.21 to 0.22 for boys with abdominal obesity across various age groups and from 0.20 to 0.21 for girls. The ROC curve analysis further showed that NHtR has good accuracy in screening for abdominal obesity, although it was unsuitable for pre-obesity screening in children and adolescents. The low specificity of NHtR restricts its clinical utility for detecting pre-abdominal obesity, whereas its greater sensitivity in established abdominal obesity correlates with elevated NHtR. Current diagnostic thresholds may lack efficacy for detecting earlier stages of adiposity. Future research should pursue composite metrics (e.g., NHtR + BMI) or ensemble XXXodelling with multiple anthropometric parameters to enhance the accuracy of early detection. A previous study analyzing the value of NHtR and other anthropometric indicators as obesity screening tools in 2,812 adults aged 18–65 years found that the AUCs of the ROC curve for NHtR were 0.95 and 0.83 for males and females, respectively, with an optimal cutoff value of 0.22 [21]. This suggests that the NHtR has good accuracy in assisting the diagnosis of abdominal obesity in children and adolescents, as well as in overweight and obesity in adults, and is a relatively stable and convenient measurement tool. Population-specific variations in somatometry and adiposity patterns may compromise the universal applicability of the neck-to-height ratio (NHtR) threshold, necessitating further validation across diverse groups. NHtR’s sensitivity (false-negative cases) and specificity (false positives) for detecting pre-abdominal obesity limit clinical utility. Low sensitivity delays progression-prevention interventions, while low specificity triggers unnecessary investigations. Consequently, although NHtR demonstrates utility for screening abdominal obesity, its limitations in pre-abdominal detection necessitate the integration of other anthropometric measures or clinical assessments. Future research could explore the development of adjusted cutoffs or combined indices to improve the accuracy of NHtR for early detection. The ROC curve analysis shows that NHtR has better accuracy in screening for abdominal obesity in some age groups. Specifically, the optimal cutoff range for screening abdominal obesity in boys and girls was relatively stable, ranging from 0.20 to 0.22. The same optimal cutoff values for boys and girls aged 7–8 years may be attributed to the similar growth rates of NC before puberty, along with comparable height growth rates in pre-pubertal boys and girls [35, 36]. A significant decreasing trend in NHtR was observed in girls aged 9–11 years and boys after 12 years of age, which is related to the different timings of puberty onset and peak height velocity between the two sexes. Indeed, global studies have revealed a trend of earlier puberty onset. A meta-analysis [37], which included four multi-center studies in China, revealed that the median age of puberty onset in Chinese girls was 9.18 years, whereas other studies found a value of 10.65 years in Chinese boys [38]. The proportion of females experiencing peak height velocity in Tanner stages II, III, and IV is 40%, 30%, and 20%, respectively, while it is 8%, 60%, and 28% in boys. This finding indicates that the peak height velocity mostly occurs within 0–1 and 1–2 years after puberty onset in girls and boys, respectively [38]. After the pubertal growth spurt, the growth rate gradually decreases until the final adult height is reached; similarly, NC growth follows this trend, resulting in a stabilization of the NHtR in the late pubertal period [35]. This finding aligns with our study, which showed that the optimal cutoff values of NHtR in screening for abdominal obesity become more stable after puberty, at 0.21 and 0.20 for boys and girls, respectively, after the age of 13 [10]. Pubertal growth has a significant influence on anthropometric indices, necessitating consideration in age- and sex-specific analyses. Pronounced alterations in body composition during puberty alter neck circumference-height relationships, thereby modifying the neck-to-height ratio (NHtR). Earlier pubertal onset in girls versus boys contributes to sex-specific variations in optimal NHtR thresholds across age cohorts. Consequently, age- and sex-stratified NHtR thresholds reflect the effects of pubertal growth, underscoring the necessity of incorporating developmental stage alongside chronological age for pediatric abdominal obesity screening. Therefore, the optimal cutoff values of NHtR in evaluating abdominal obesity among children and adolescents vary slightly with age due to the influence of pubertal development, with the lowest values occurring during the pubertal growth spurt.
This study has limitations. First, this study employed a cross-sectional design, examining children and adolescents in four schools in Zhengzhou City, which may introduce geographical bias and is subject to the limitations inherent in observational studies. The cross-sectional design prevents the establishment of temporal relationships or causal inferences. While NHtR associates with current abdominal obesity, it cannot predict the development of future abdominal obesity or associated health risks. Longitudinal studies must assess NHtR’s predictive value for long-term cardiometabolic outcomes. Therefore, multicenter, cohort studies should be conducted to validate this study’s results further. Second, the efficacy of the optimal cutoff value of NHtR in evaluating metabolic syndrome, cardiovascular diseases, and other abdominal obesity-related diseases needs further validation, and future studies are expected to further improve this approach.
Conclusion
Our study demonstrated that NHtR is a reliable indicator for evaluating abdominal obesity among children and adolescents, which could assist in abdominal obesity screening in this population. NHtR has the advantages of fewer interfering factors and faster interpretation than the classic abdominal obesity indicators, such as WC and WHtR.However, attention should be paid to the changes in the optimal cutoff value of NHtR before and after puberty. Before the NHtR can be applied to large-scale screening, it needs to be validated in a broader population to ensure its reliability and validity in different contexts.
Acknowledgements
We would like to sincerely thank all the students, teachers, parents, and on-site staff for their hard work and support.
Abbreviations
- AUC
Area under the curve
- BMI
Body mass index
- CI
Confidence Interval
- HC
Hip circumference
- MAFLD
Metabolic dysfunction-associated fatty liver disease
- NC
Neck circumference
- ROC
Receiver operating characteristic
- WC
Waist circumference
- WHR
Waist-to-hip ratio
- WHtR
Waist-to-height ratio
Authors’ contributions
Fang Liu: Writing—original draft, Writing—review and editing, Supervision, and Project administration. Shuxian Yuan: Investigation, Data curation, and Project administration. Xiaocui Ma: Data curation and Conceptualization. Yangshiyu Li: Software. Shiqi Wang: Project administration and Resources. Yifan Lin: Investigation. Yongxing Chen: Project administration and Visualization. Haiyan Wei: Conceptualization, Formal analysis, Funding acquisition, and Investigation. All authors read and approved the final manuscript.
Funding
This work was supported by the National Key R&D Program of China (grant number: 2021YFC2701900). The funder had no role in the conceptualization, design, data collection, analysis, decision to publish, or preparation of the manuscript.
Data availability
The datasets generated and/or analysed during the current study are not publicly available due ethical and privacy restrictions but are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
This study was approved by the Medical Ethics Committee of Zhengzhou University Children’s Hospital (Ethics No.: 2021-H-K31). The study was performed in accordance with the ethical standards outlined in the 1964 Declaration of Helsinki and its later amendments or other comparable ethical standards. This study was conducted after informed consent to participate was obtained from the research participants and their parents, who signed the consent forms.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Clinical trial number
Not applicable
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets generated and/or analysed during the current study are not publicly available due ethical and privacy restrictions but are available from the corresponding author on reasonable request.