Influence of changes in body fat on clinical outcomes in a general population: a 12-year follow-up report on the Ansan-Ansung cohort in the Korean Genome Environment Study

BACKGROUND

The impact of the changes in the obesity status on mortality has not been established; thus, we investigated the long-term influence of body fat (BF) changes on all-cause deaths and cardiovascular outcomes in a general population.

METHODS

A total of 8374 participants were observed for 12 years. BF was measured at least two times using a bioimpedance method. The causes of death were acquired from the nationwide database. A major adverse cardiovascular event (MACE) was defined as a composite of myocardial infarction, coronary artery disease, stroke, and cardiovascular death. Standard deviations (SDs) were derived using a local regression model corresponding to the time elapsed between the initial and final BF measurements (SD_T) and were used to standardize the changes in BF (ΔBF/SD_T).

RESULTS

The incidence rates of all-cause death, cardiovascular death, and MACE were the highest in the participants with ΔBF/SD_T <-1 and lowest in the participants with ΔBF/SD_T ≥1. Multivariate Cox proportional hazard models adjusted for relevant covariates, including baseline obesity and physical activity, showed that the risks of all-cause deaths (hazard ratio [HR] 0.58; 95% confidence intervals [CI] 0.53-0.64), cardiovascular deaths (HR 0.63; 95% CI 0.51-0.78) and MACEs (HR 0.68; 95% CI 0.62-0.75) decreased as ΔBF/SD_T increased. Subgroup analyses showed that existing cardiovascular diseases weakened the associations between higher ΔBF/SD_T and better outcomes, while high physical activity and exercise did not impact the associations.

CONCLUSION

Increasing BF was associated with a lower risk of all-cause death, cardiovascular death, and MACE in the general population.Key messagesIncreasing body fat is associated with a lower risk of all-cause death, cardiovascular death, and major cardiovascular adverse events in a low-risk ageing general population, independently of physical activity, underlying cardiovascular disease burden, changes in muscle mass, and baseline obesity status.Fatness measured at baseline requires adjustment for the changes in fatness during the follow-up to reveal its impact on the clinical outcomes.

How Length Sizes Affect Body Composition Estimation in Adolescent Athletes Using Bioelectrical Impedance

Bioelectrical impedance analysis (BIA) is a common practice to assess body composition in athletes, however, when measuring athletes with specific body geometry, its accuracy may decrease. In this study we examined how length dimensions affect body composition estimation and we compared BIA and dual-energy X-ray absorptiometry (DXA) assessments in three sports. 738 male adolescent athletes (15.8 ± 1.4 years) from three sports (soccer, basketball, and handball) were measured. Body composition was estimated by BIA (InBody 720) and by DXA (Lunar Prodigy). Differences between the two methods were tested by Bland-Altman analysis and by paired t-test. ANOVA was used for inter-group comparisons. Pearson correlation and multivariate linear regression was used to look for the relationship between segmental lean body mass and length dimensions. BIA_{InBody 720} consistently underestimated percent body fat (PBF) and overestimated lean body mass (LBM) than DXA. The magnitude of the differences between the two methods varied among the examined sports. Handball (PBF = 8.3 ± 2.4 %; LBM = -5.0 ± 2.1 kg) and basketball players (PBF = 8.8 ± 2.3 %; LBM = -5.3 ± 1.8 kg) had significantly larger differences between the two methods than soccer players (PBF = 6.4 ± 2.2 %; LBM = -3.1 ± 1.4 kg). There was a negative correlation between differences in segmental LBM estimation and length sizes (trunk length, upper extremity length, lower extremity length). The highest correlation was found for lower extremity (r = -0.4). Longer lower extremity resulted in greater difference in LBM estimation. The differences between the sport disciplines are most probably attributed to body height differences. Length dimensions result in overestimation of LBM with BIA, thus body composition assessment with BIA_{InBody 720} needs to be carefully interpreted in athletes with extreme length sizes, especially, with basketball players.