Birth weight and body fat mass in adults assessed by bioimpedance in the ELSA-Brasil study

Dietary patterns and adiposity over time - analysis of the ELSA-Brasil

PURPOSE

Combining different statistical methods to identify dietary patterns (DP) may provide new insights on how diet is associated with adiposity. This study investigated the association of DP derived from three data-driven methods and adiposity indicators over time.

METHODS

This study used data from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). DP were identified at baseline applying three statistical methods: Factor Analysis (FA), Treelet Transform (TT), and Reduced Rank Regression (RRR). The association between DP and adiposity indicators (weight, body mass index, waist circumference, body fat percentage and fat mass index) over the period of 8.2 years of follow-up was assessed by linear mixed-models.

RESULTS

Convenience DP, marked by unhealthy food groups, was associated with higher adiposity over the follow-up period, regardless of the method applied. The DP identified by TT and marked by high consumption of rice and beans was associated with lower adiposity, whereas the similar DP identified by FA, but additionally characterised by consumption of poultry and red meat was associated with higher adiposity. Prudent DP, marked by plant-based food groups and fish, identified by FA was associated with lower adiposity across the median follow-up time.

CONCLUSION

Applying different methods to identify DP showed that a convenience DP was associated with higher adiposity independent of the method applied. We also identified the nuances within adherence to a Brazilian traditional dietary pattern characterised by the consumption of rice and beans, that only when combined with reduced consumption of animal protein and unhealthy foods was associated with lower adiposity over time.

Small for gestational age and anthropometric body composition from early childhood to adulthood: the Aboriginal Birth Cohort study

Background

In Australia the estimated rate of small for gestational age (SGA) births is 9% among non-Indigenous births compared to 14% among Aboriginal and Torres Strait Islanders. There is limited research investigating the effect of being born SGA on body composition later in life in Indigenous Australians.

Methods

Using data from the Aboriginal Birth Cohort longitudinal study, we compared the body composition of those born SGA to non-SGA by analysing anthropometric measures (height, weight, waist circumference, fat percentage [FAT%], body mass index [BMI], waist-to-height ratio, and A body shape index [ABSI]) collected at four follow-up periods (from childhood to adult). For cross-sectional analyses, linear regression models were employed to assess factors associated with anthropometric measures. For longitudinal analyses linear mixed models were employed to assess differences in anthropometric measures among SGA versus non-SGA individuals while adjusting for repeated measures.

Results

The analytic baseline cohort were those who participated in Wave 2 (n = 570). In cross-sectional analyses, across all waves those born SGA had smaller anthropometric z-scores compared to non-SGA individuals (β ranging from -0.50 to -0.25). Participants residing in urban environments were significantly larger in Waves 2 to 4 (β ranged 0.26 to 0.65). Those born SGA had higher ABSI scores in Waves 2 and 4 (β 0.26 and 0.37, respectively). In longitudinal analyses, those born SGA had smaller measures of body composition across the life course; these differences were larger in urban communities. In remote communities those born SGA had significantly higher ABSI scores during adolescence and young adulthood, and this difference was not observed in urban communities.

Conclusion

Indigenous Australians born SGA are smaller anthropometrically later in life compared to their non-SGA counterparts. In remote communities, those born SGA had higher levels of central adiposity compared to non-SGA.

Predicting of excess body fat in children

PURPOSE OF REVIEW

Approximately 370 million children and adolescents worldwide showed overweight or obesity in 2016. The risk of developing severe comorbidities depends on the age of onset and the duration of obesity. This review discusses available methodologies to detect excess body fat in children as well as the early life factors that predict excess body fat and its development.

RECENT FINDINGS

Factors, such as parental nutritional status, maternal weight gain during pregnancy, maternal malnutrition, maternal smoking during pregnancy, low and high birth weight, rapid weight gain, and short infant sleep duration have been independently and positively associated with neonatal, infant, and children adiposity. Early detection of excess body fat in children through the use of various tools is the first step in preventing nutrition-related diseases in adulthood.

SUMMARY

The early detection of excess body fat and the implementation of efficient interventions to normalize the weight of children and adolescents at obesity risk are essential to prevent diseases in adult life.