Relationship of BMI z score to fat percent and fat mass in multiethnic prepubertal children

Associations of bioelectrical impedance and anthropometric variables among populations and within the full spectrum of malnutrition

OBJECTIVES

The aim of this study was to evaluate body composition variability assessed by bioimpedance in relation to nutritional status assessed by anthropometry in children and adolescents living in countries characterized by contrasting nutritional conditions.

METHODS

The sample was comprised of 8614 children (4245 males; 4369 females), aged 3 to 19 years, from Nepal (477 children), Uganda (488 children and adolescents), UK (297 children and adolescents) and US (7352 children and adolescents). Height-for-age (HAZ) and body mass index-for-age (BAZ) z-scores were calculated according to WHO growth references. Specific bioelectrical impedance vector analysis (BIVA) was used to evaluate body composition variability. In each population sample, the relationship of HAZ and BAZ with bioelectrical outcomes was analysed by confidence ellipses and cubic spline regression, controlling for sex and age.

RESULTS

The participants from Uganda and Nepal were more affected by undernutrition, and those from the US and UK by obesity. In all groups, phase angle and specific vector length were weakly associated with HAZ, with null or opposite relationships in the different samples, whereas they were positively associated with BAZ. The stronger association was between vector length, indicative of the relative content of fat mass, and BAZ in the UK and US samples. Confidence ellipses showed that the relationships are more strongly related to phase angle in Nepalese and Ugandan samples.

CONCLUSIONS

Bioelectrical values were more strongly associated with BAZ than HAZ values in all population samples. Variability was more related to markers of muscle mass in Ugandan and Nepalese samples and to indicators of fat mass in UK and US samples. Specific BIVA can give information on the variability of body composition in malnourished individuals.

Critical body fat percentage required for puberty onset: the Taiwan Pubertal Longitudinal Study

PURPOSE

Prepubescent body fat percentage (BFP) is associated with puberty onset; however, the association between the timing of puberty onset and BFP remains unclear. This study aimed to determine whether and how the timing of puberty onset is associated with various anthropometric measures, and to investigate the critical time period of the BFP transition before and after puberty.

METHODS

The Taiwan Pubertal Longitudinal Study (TPLS) has a multicenter, population-based prospective cohort and was established in July 2018 at 4 pediatric departments. We included girls aged 6-14 years and boys aged 9-17 years evaluated as having puberty onset and excluded those with precocious puberty diagnosis. The anthropometric measures were collected every 3 months. The main outcome was age at puberty onset. Data were analyzed between July 2018 and September 2020.

RESULTS

For 153 girls and 83 boys, BFP was significantly related to puberty onset for girls. Longitudinal analysis revealed that BFP in the girls was reduced to less than 18% 6 months before puberty and rapidly increased by 2.85% over 3 months, then exceeding 20% before puberty onset. After puberty onset, BFP was no longer lower than 22%.

CONCLUSIONS

BFP is an essential predictor of age at puberty onset. BFP first decreases and then begins to increase 3-6 months before puberty in girls. Parents and schools could monitor the BFP of prepubescent girls every 6 months to predict puberty onset.

Birth Weight and Body Composition as Determined by Isotopic Dilution with Deuterium Oxide in 6- to 8-Year-Old South African Children

Low and high birth weight (BW) are associated with obesity later in life; however, this association has not been extensively studied in African countries. This study determines the association between BW and body composition derived from deuterium oxide (D2O) dilution in 6- to 8-year-old South African children (n = 91; 40 boys, 51 girls). BW was recorded retrospectively from the children’s Road-to-Health cards. Weight and height were measured using standard procedures, and D2O dilution was used to determine total body water and, subsequently, to determine body fat. Fatness was classified using the McCarthy centiles, set at 2nd, 85th, and 95th (underfat, overfat and obese). BW correlated with body composition measures, such as body weight (r = 0.23, p = 0.03), height (r = 0.33, p < 0.001), and fat free mass (FFM; r = 0.27, p = 0.01). When multiple regression analysis was employed, BW significantly and positively associated with FFM (β = 0.24, p = 0.013; 95% CI: 0.032; 0.441) and fat mass (β = 0.21, p = 0.02, 95%CI: 0.001; 0.412) in girls and boys combined. A total of 13% of the children had a low BW, with 21% being overweight and 17% obese. More girls than boys were overweight and obese. Intervention strategies that promote healthy uterine growth for optimal BW are needed in order to curb the global obesity pandemic.

Comparing different data sources by examining the associations between surrounding greenspace and children's weight status

Background

Studies on the association between surrounding greenspace and being overweight in childhood show inconsistent results, possibly because they differ widely in their definition and measurement of surrounding greenspace. Our aim was to evaluate whether the association of greenspace with being overweight depends on the measurement of greenspace in different data sources.

Methods

Based on data from the school entry examinations of 22,678 children in the city of Hannover, Germany, from 2010 to 14, the association between greenspace availability and overweight was examined. Three different sources of greenspace availability were derived for a set of 51 areas of the city: The Normalized Difference Vegetation Index (NDVI), the OpenStreetMap (OSM) dataset, and the European Urban Atlas (UA) dataset. Agreement between the indicators on the quantity of greenspace coverage was compared. The association with children's BMI z-score, including potential interaction terms, was assessed using multilevel regression analysis.

Results

Greenspace availability per district area derived by NDVI was on average 42%, by OSM 29% and UA 22%, with OSM and UA being strongly correlated. Only the greenspace availability derived by NDVI showed an association with children's BMI z-score: The higher the greenspace availability was, the lower the BMI. The trend of association was higher for boys and migrant children than for girls and non-migrants and was restricted to the highest levels of greenspace availability.

Conclusions

Associations of greenspace with children's weight status depend on the greenspace measurement chosen. Surrounding greenspace was measured more comprehensively by NDVI. Data sources based on land use categories such as UA and OSM may be less suitable to reflect surrounding greenspace relevant for health outcomes. Potential mechanisms warrant further analysis and investigation.

Associations of mothers' source of feeding information with longitudinal trajectories of sugar-sweetened beverage intake, 100% juice intake and adiposity in early childhood

BACKGROUND

There remains a need to understand how information sources can promote young children's healthy beverage consumption and prevent obesity.

OBJECTIVES

To examine associations of mothers' primary feeding information source with children's sugar-sweetened beverage (SSB) intake, 100% juice intake and adiposity between ages 3 and 7 years.

METHODS

We analyzed data from a prospective cohort study (n = 371 children; 13 visits). Mothers reported their primary feeding information source at baseline and completed child 3-day dietary records each visit. Child adiposity indicators were calculated from repeated height/weight measurements and dual-energy X-ray absorptiometry. Longitudinal models examined beverage intakes and adiposity over time by source.

RESULTS

Primary feeding information sources included doctors (48.2%), mothers (17.5%), grandmothers (13.5%), other healthcare professionals (11.3%) and other family/friends (9.4%). Children's juice intake with age differed by source (P interaction = 0.03), with steepest and slightest intake decreases in the doctor (-19.7% each year; 95% CI: -23.7%, -15.5%) and grandmother (-5.0%; -14.5%, 5.5%) subgroups, respectively. Children's SSB intake did not differ by source, but increased annually by 7.1% (4.5%, 9.8%) overall. The grandmother subgroup had the greatest child adiposity over time.

CONCLUSIONS

Mothers' primary feeding information source may have important, yet heterogeneous, influences on young children's beverage intakes and adiposity over time. Consistent evidence-based messages are likely needed.

Multi-disciplinary weight management compared to routine care in youth with obesity: what else should be monitored?

PURPOSE

Efficacy of multi-disciplinary weight management (MDM) in youth has not been compared to their routine care.

OBJECTIVES

To compare body mass index z-score (zBMI) and blood test (lab) changes (Δ) in youth before and after MDM and to correlate bio-impedance analysis (BIA) and lab measurements.

METHODS

We compared zBMI Δ (from referring providers' records), within 3 months prior to MDM, to monthly zBMI Δ after MDM, in a retrospective cohort of youth at a tertiary MDM center. BIA and lab measurements after 6 months, MDM were compared to baseline.

RESULTS

We reviewed 316 records (12.9 ± 3.5 years, 49% males, 104.8 ± 35.1 kgs). The pre-MDM zBMI Δ (0.02 ± 0.1) was reversed after MDM (-0.03 ± 0.09, visit 2, P < 0.001). The zBMI Δ progressed on follow-up (-0.14 ± 0.05, visit 6). Baseline BIA components correlated with Homeostatic Model Assessment of Insulin resistance (HOMA-IR), triglycerides, and systolic blood pressure. HbA1c, HOMA-IR, and liver functions significantly improved on follow-up. MDM participation showed progressive attrition and dropped to 11.6% at visit 6.

CONCLUSION

MDM in youth resulted in zBMI and lab improvements compared to their pre-MDM measurements. BIA provided additional outcome measures that correlated with metabolic markers. MDM follow-up was limited by the progressive participant drop-out. Behavioral economic strategies are needed to improve adherence.