Dose-response association between adult height and all-cause mortality: a systematic review and meta-analysis of cohort studies

Comparison of body fat percentage assessments by bioelectrical impedance analysis, anthropometrical prediction equations, and dual-energy X-ray absorptiometry in older women

Background

Individuals with high body fat have a higher risk of mortality. Numerous anthropometric-based predictive equations are available for body composition assessments; furthermore, bioelectrical impedance analysis (BIA) estimates are available. However, in older adults, the validity of body fat estimates requires further investigation.

Objective

To assess the agreement between percentage body fat (BF%) estimates by BIA and five predictive equations based on anthropometric characteristics using dual X-ray absorptiometry (DXA) as reference method. A secondary objective was to identify whether excluding short-stature women improves the agreement of BF% estimates in a group of community-dwelling, older Mexican women.

Methods

A concordance analysis of BF% was performed. A total of 121 older women participated in the study. Anthropometric information, BIA, and DXA body composition estimates were obtained. Five equations using anthropometric data were evaluated in order to determine body fat percentage (BF%) using DXA as reference method. Paired t-test comparisons and standard error of estimates (SEE) were obtained. The Bland-Altman plot with 95% limits of agreement and the concordance correlation coefficient (CCC) were used to evaluate the BF% prediction equations and BIA estimates.

Results

The mean age of the study participants was 73.7 (±5.8) years old. BIA and the anthropometric based equations examined showed mean significant differences when tested in the entire sample. For the taller women (height > 145 cm), no significant difference in the paired comparison was found between DXA and BIA of BF% estimates. The mean BF% was 40.3 (±4.8) and 40.7 (±6.2) for DXA and BIA, respectively. The concordance between methods was good (CCC 0.814), (SEE 2.62). Also, in the taller women subset, the Woolcott equation using waist-to-height ratio presented no significant difference in the paired comparison; however, the error of the estimates was high (SEE 3.37) and the concordance was moderate (CCC 0.693).

Conclusion

This study found that BIA yielded good results in the estimation of BF% among women with heights over 145 cm. Also, in this group, the Woolcott predictive equation based on waist circumference and height ratio showed no significant differences compared to DXA in the paired comparison; however, the large error of estimates observed may limit its application. In older women, short stature may impact the validity of the body fat percentage estimates of anthropometric-based predictive equations.

Gender Differences Between the Phenotype of Short Stature and the Risk of Diabetes Mellitus in Chinese Adults: A Population-Based Cohort Study

OBJECTIVE

Previous studies have shown that there are significant regional and gender differences in the association between the phenotype of short stature and diabetes mellitus (DM). The purpose of this study was to investigate the gender difference between the phenotype of short stature and the risk of DM in the Chinese population.

METHODS

The sample included 116,661 adults from 32 locations of 11 cities in China, of which the average height of men and women was 171.65 and 160.06 cm, respectively. Investigators retrospectively reviewed annual physical examination results for follow-up observations and set confirmed DM events as the outcome of interest. Multivariate Cox regression, restricted cubic spline, and piecewise regression models were used to check the association between height and DM risk.

RESULTS

During an average observation period of 3.1 years, there were 2,681 of 116,661 participants who developed new-onset DM, with a male to female ratio of 2.4 to 1. After full adjustment for confounders, we confirmed that there was a significant negative correlation between height and DM risk in Chinese women (HR per 10 cm increase: 0.85, 95% CI: 0.74-0.98), but not in men (HR per 10 cm increase: 1.16, 95% CI: 0.98-1.14). Additionally, through restricted cubic spline and piecewise regression analysis, we determined that the height of 157-158 cm may be the critical point for short stature used to assess the risk of DM in Chinese women.

CONCLUSIONS

In the Chinese population, female short stature phenotype is related to increased DM risk, among which 157-158 cm may be the saturation effect point of female short stature for predicting DM risk.