Back

Hyperbolic weight-height correlation in children and adolescents: models and implications for obesity diagnosis

Xu, T.; Li, X.; Liu, W.; Na, Z.; Wu, Q.

2025-08-19 public and global health
10.1101/2025.08.16.25333345 medRxiv
Show abstract

Many weight-height (Wt-Ht) models were proposed since the derivation of the "Quetelet Index", though their credibility remains elusive. This raises an interesting question about the presence of numerous Wt-Ht models and reveals that our knowledge about the Wt-Ht correlation is still far from its essence. We identified a strong linear correlation between Wt and Wt*Htc (c=-2[~]2), based on data from 359,049 participants aged 1 to 21 years, recruited from China, Japan, South Korea, Slovakia, the USA, and Bangladesh. Then, we established a statistically-robust Wt-Ht model, which is expressed as Wt=a+b*Wt*Htc (Eq. 1) or 1=a/Wt+b*Htc (Eq. 2), through linear regression. When c=1 or -1, Eq. 2 is a standard hyperbolic function, which proves that Wt is hyperbolically correlated with Ht. The coefficients a and b are sex-, age-, and geography-specific constants. As the exponent c approaches 0, the correlation between Wt and Wt*Htc, along with the standardized Wt-Ht index (sWHI) (a/Wt+b*Htc in Eq. 2), approaches 1. Further, we incorporated total fat to determine the implications of our model in obesity diagnosis. When c=1, the sWHI (a/Wt+b*Ht) is capable of screening abnormal body fat percentage (BFP) based on deviations from the Wt-Ht equilibrium (sWHI=1). BMI demonstrates advantages over other anthropometric indexes in screening abnormal BFP; nonetheless, their performances are largely similar. This is probably attributed to the strong linear correlation between Wt and Wt*Htc. Overall, the hyperbolic Wt-Ht model reveals the nature of Wt-Ht correlation and offers key insights into obesity diagnosis using anthropometric indexes.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

1
International Journal of Obesity
25 papers in training set
Top 0.1%
42.5%
2
PLOS ONE
4510 papers in training set
Top 20%
9.8%
50% of probability mass above
3
Scientific Reports
3102 papers in training set
Top 8%
9.0%
4
Journal of The Royal Society Interface
189 papers in training set
Top 0.9%
4.2%
5
eLife
5422 papers in training set
Top 23%
3.8%
6
Journal of Clinical Medicine
91 papers in training set
Top 2%
3.5%
7
Current Developments in Nutrition
15 papers in training set
Top 0.4%
2.0%
8
BMC Public Health
147 papers in training set
Top 3%
1.8%
9
Frontiers in Public Health
140 papers in training set
Top 5%
1.4%
10
Frontiers in Physiology
93 papers in training set
Top 4%
1.3%
11
Diabetes, Obesity and Metabolism
17 papers in training set
Top 0.3%
1.2%
12
Frontiers in Neuroscience
223 papers in training set
Top 5%
1.2%
13
PLOS Computational Biology
1633 papers in training set
Top 21%
1.0%
14
Heliyon
146 papers in training set
Top 5%
0.8%
15
PeerJ
261 papers in training set
Top 17%
0.7%
16
Royal Society Open Science
193 papers in training set
Top 5%
0.7%
17
JMIR Public Health and Surveillance
45 papers in training set
Top 4%
0.7%
18
Bulletin of Mathematical Biology
84 papers in training set
Top 2%
0.7%
19
Journal of Theoretical Biology
144 papers in training set
Top 2%
0.7%
20
Journal of Biomedical Informatics
45 papers in training set
Top 2%
0.7%
21
Quantitative Biology
11 papers in training set
Top 0.9%
0.7%
22
Epidemics
104 papers in training set
Top 2%
0.7%
23
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 48%
0.5%
24
Nature Communications
4913 papers in training set
Top 66%
0.5%
25
Cellular & Molecular Immunology
14 papers in training set
Top 2%
0.5%