Dataset Information

An improved algorithm to harmonize child overweight and obesity prevalence rates.

ABSTRACT:

Background

Prevalence rates of child overweight and obesity for a group of children vary depending on the BMI reference and cut-off used. Previously we developed an algorithm to convert prevalence rates based on one reference to those based on another.

Objective

To improve the algorithm by combining information on overweight and obesity prevalence.

Methods

The original algorithm assumed that prevalence according to two different cut-offs A and B differed by a constant amount dz on the z-score scale. However the results showed that the z-score difference tended to be greater in the upper tail of the distribution and was better represented by b×dz , where b was a constant that varied by group. The improved algorithm uses paired prevalence rates of overweight and obesity to estimate b for each group. Prevalence based on cut-off A is then transformed to a z-score, adjusted up or down according to b×dz and back-transformed, and this predicts prevalence based on cut-off B. The algorithm's performance was tested on 228 groups of children aged 6-17 years from 20 countries.

Results

The revised algorithm performed much better than the original. The standard deviation (SD) of residuals, the difference between observed and predicted prevalence, was 0.8% (n = 2320 comparisons), while the SD of the difference between pairs of the original prevalence rates was 4.3%, meaning that the algorithm explained 96.7% of the baseline variance (88.2% with original algorithm).

Conclusions

The improved algorithm appears to be effective at harmonizing prevalence rates of child overweight and obesity based on different references.

SUBMITTER: Cole TJ

PROVIDER: S-EPMC10078258 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

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Publications

An improved algorithm to harmonize child overweight and obesity prevalence rates.

Cole Tim J TJ Lobstein Tim T

Pediatric obesity 20220823 1

<h4>Background</h4>Prevalence rates of child overweight and obesity for a group of children vary depending on the BMI reference and cut-off used. Previously we developed an algorithm to convert prevalence rates based on one reference to those based on another.<h4>Objective</h4>To improve the algorithm by combining information on overweight and obesity prevalence.<h4>Methods</h4>The original algorithm assumed that prevalence according to two different cut-offs A and B differed by a constant amoun ...[more]

PMID: 35997305

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Project description:ObjectivesThe purpose of this study is to assess the prevalence of overweight/obesity, abdominal obesity and obesity-related risk factors in southern China.MethodsA cross-sectional survey of 15,364 participants aged 15 years and older was conducted from November 2013 to August 2014 in Jiangxi Province, China, using questionnaire forms and physical measurements. The physical measurements included body height, weight, waist circumference (WC), body fat percentage (BFP) and visceral adipose index (VAI). Multivariate logistic regression analysis was performed to evaluate the risk factors for overweight/obesity and abdominal obesity.ResultsThe prevalence of overweight was 25.8% (25.9% in males and 25.7% in females), while that of obesity was 7.9% (8.4% in males and 7.6% in females). The prevalence of abdominal obesity was 10.2% (8.6% in males and 11.3% in females). The prevalence of overweight/obesity was 37.1% in urban residents and 30.2% in rural residents, and this difference was significant (P < 0.001). Urban residents had a significantly higher prevalence of abdominal obesity than rural residents (11.6% vs 8.7%, P < 0.001). Among the participants with an underweight/normal body mass index (BMI), 1.3% still had abdominal obesity, 16.1% had a high BFP and 1.0% had a high VAI. Moreover, among obese participants, 9.7% had a low /normal WC, 0.8% had a normal BFP and 15.9% had a normal VAI. Meanwhile, the partial correlation analysis indicated that the correlation coefficients between VAI and BMI, VAI and WC, and BMI and WC were 0.700, 0.666, and 0.721, respectively. A multivariate logistic regression analysis indicated that being female and having a high BFP and a high VAI were significantly associated with an increased risk of overweight/obesity and abdominal obesity. In addition, living in an urban area and older age correlated with overweight/obesity.ConclusionThis study revealed that obesity and abdominal obesity, which differed by gender and age, are epidemic in southern China. Moreover, there was a very high, significant, positive correlation between WC, BMI and VAI. However, further studies are needed to explore which indicator of body fat could be used as the best marker to indirectly reflect cardiometabolic risk.

Project description:BACKGROUND:In India, the prevalence of overweight and obesity has increased rapidly in recent decades. Given the association between overweight and obesity with many non-communicable diseases, forecasts of the future prevalence of overweight and obesity can help inform policy in a country where around one sixth of the world's population resides. METHODS:We used a system of multi-state life tables to forecast overweight and obesity prevalence among Indians aged 20-69 years by age, sex and urban/rural residence to 2040. We estimated the incidence and initial prevalence of overweight using nationally representative data from the National Family Health Surveys 3 and 4, and the Study on global AGEing and adult health, waves 0 and 1. We forecasted future mortality, using the Lee-Carter model fitted life tables reported by the Sample Registration System, and adjusted the mortality rates for Body Mass Index using relative risks from the literature. RESULTS:The prevalence of overweight will more than double among Indian adults aged 20-69 years between 2010 and 2040, while the prevalence of obesity will triple. Specifically, the prevalence of overweight and obesity will reach 30.5% (27.4%-34.4%) and 9.5% (5.4%-13.3%) among men, and 27.4% (24.5%-30.6%) and 13.9% (10.1%-16.9%) among women, respectively, by 2040. The largest increases in the prevalence of overweight and obesity between 2010 and 2040 is expected to be in older ages, and we found a larger relative increase in overweight and obesity in rural areas compared to urban areas. The largest relative increase in overweight and obesity prevalence was forecast to occur at older age groups. CONCLUSION:The overall prevalence of overweight and obesity is expected to increase considerably in India by 2040, with substantial increases particularly among rural residents and older Indians. Detailed predictions of excess weight are crucial in estimating future non-communicable disease burdens and their economic impact.

Dataset Information

An improved algorithm to harmonize child overweight and obesity prevalence rates.

Background

Objective

Methods

Results

Conclusions

Publications

An improved algorithm to harmonize child overweight and obesity prevalence rates.

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