The aim of this study was to examine the differences between selected lifestyle and socioeconomic parameters among preschool (3–7 years of age) children of differing adiposity status. The study was conducted from February to June 2018 in 20 randomly selected kindergartens in Kraków, Poland. Triceps, biceps, subscapular, suprailiac, abdominal and calf skinfold thicknesses were measured. The sum of all six skinfolds was calculated and the children were subsequently characterized by low (≤–1 SD [standard deviation]), normal (–1 to 1 SD) or high body fat (≥1 SD). Socioeconomic and lifestyle characteristics were obtained using a questionnaire filled out by the children’s parents or legal guardians. Preschool children in the high adiposity category had, on average, fewer siblings and longer screen time; additionally, their parents had lower education and more often worked in manual jobs, in comparison to the children in the low and average adiposity categories. In conclusion, it was observed that children in different adiposity categories varied in terms of some socioeconomic as well as lifestyle characteristics. Knowledge regarding the influence that those factors can have on the metabolic health of children is essential for children’s present as well as future well-being. Moreover, it can help health care professionals and parents decide what intervention and/ or preventive measures should be undertaken to ensure the best possible outcomes, as the development of successful obesity prevention strategies should rely on evidence-based information. Nonetheless, future research examining the issue of factors influencing the metabolic health of children, as well as these outcomes later in life, is crucial. Well-planned studies including a large number of individuals, as well as longitudinal research, will be particularly beneficial in this regard.

In the light of changes in the living conditions of populations, excess adiposity is currently a serious public health problem worldwide. The aim of this study was to assess the changes in the body fat ratio among preschool children aged 3–7 years from Kraków, Poland, between 2008 and 2018. The study group consisted of children examined in two cross-sectional studies. Analysed characteristics included triceps, calf, subscapular, abdominal and suprailiac skinfold thicknesses, and adiposity calculated according to Slaughter’s equations. The trunk adiposity index and limbs-to-trunk fat ratio were also calculated. Statistical significance was obtained using two-way ANOVA and Tukey’s tests. Lower-limb adiposity was largest in the 2008 cohort and trunk adiposity was greater in the 2018 cohort. The mean values of the trunk adiposity index and limbs-to-trunk fat ratio were lower in the 2018 cohort than in the 2008 cohort. The 2018 cohort was also characterized by a lower overall adiposity. Regardless of the lower body adiposity percentage, in 2018 there was a tendency towards the central allocation of fat tissue. This is a negative phenomenon because, especially when co-existing with reduced lower-limb adiposity, it is associated with an increased risk of metabolic and cardiovascular diseases, even in young children.

Anthropometric measures of body composition are often used for rapid and cost-effective estimation of percentage body fat (%BF) in field research, serial measurements and screening. Our aim was to develop a validated estimate of %BF for the general population, based on simple body circumferences measures. The study cohort consisted of two consecutive samples of health club members, designated as ‘development’ (n 476, 61 % men, 39 % women) and ‘validation’ (n 224, 50 % men, 50 % women) groups. All subjects underwent anthropometric measurements as part of their registration to a health club. Dual-energy X-ray absorptiometry (DEXA) scan was used as the ‘gold standard’ estimate of %BF. Linear regressions where used to construct the predictive equation (%BFcal). Bland–Altman statistics, Lin concordance coefficients and percentage of subjects falling within 5 % of %BF estimate by DEXA were used to evaluate accuracy and precision of the equation. The variance inflation factor was used to check multicollinearity. Two distinct equations were developed for men and women: %BFcal (men)=10·1−0·239H+0·8A−0·5N; %BFcal (women)=19·2−0·239H+0·8A−0·5N (H, height; A, abdomen; N, neck, all in cm). Bland–Altman differences were randomly distributed and showed no fixed bias. Lin concordance coefficients of %BFcal were 0·89 in men and 0·86 in women. About 79·5 % of %BF predictions in both sexes were within ±5 % of the DEXA value. The Durnin–Womersley skinfolds equation was less accurate in our study group for prediction of %BF than %BFcal. We conclude that %BFcal offers the advantage of obtaining a reliable estimate of %BF from simple measurements that require no sophisticated tools and only a minimal prior training and experience.

Asian populations have a higher percentage body fat (%BF) and are at higher risk for CVD and related complications at a given BMI compared with those of European descent. We explored whether %BF was disproportionately elevated in rural Bangladeshi women with low BMI. Height, weight, mid-upper arm circumference, triceps and subscapular skinfolds and bioelectrical impedance analysis (BIA) were measured in 1555 women at 3 months postpartum. %BF was assessed by skinfolds and by BIA. BMI was calculated in adults and BMI Z-scores were calculated for females <20 years old. Receiver operating characteristic (ROC) curves found the BMI and BMI Z-score cut-offs that optimally classified women as having moderately excessive adipose tissue (defined as >30 % body fat). Linear regressions estimated the association between BMI and BMI Z-score (among adolescents) and %BF. Mean BMI was 19·2 (sd 2·2) kg/m2, and mean %BF was calculated as 23·7 (sd 4·8) % by skinfolds and 23·3 (sd 4·9) % by BIA. ROC analyses indicated that a BMI value of approximately 21 kg/m2 optimised sensitivity (83·6 %) and specificity (84·2 %) for classifying subjects with >30 % body fat according to BIA among adults. This BMI level is substantially lower than the WHO recommended standard cut-off point of BMI ≥ 25 kg/m2. The equivalent cut-off among adolescents was a BMI Z-score of –0·36, with a sensitivity of 81·3 % and specificity of 80·9 %. These findings suggest that Bangladeshi women exhibit excess adipose tissue at substantially lower BMI compared with non-South Asian populations. This is important for the identification and prevention of obesity-related metabolic diseases.

Because of its strong association (r 0·85) with percentage of body fat determined by dual-energy X-ray absorptiometry, hip circumference divided by height1·5 (the body adiposity index) has recently been proposed as an index of body fatness among adults. We examined whether this proposed index was more strongly associated with skinfold thicknesses and levels of CVD risk factors (lipids, fasting insulin and glucose, and blood pressure) than was BMI among 2369 18- to 49-year-olds in the Bogalusa Heart Study. All analyses indicated that the body adiposity index was less strongly associated with skinfold thicknesses and CVD risk factors than was either waist circumference or BMI. Correlations with the skinfold sum, for example, were r 0·81 (BMI) v.r 0·75 (body adiposity index) among men, and r 0·87 (BMI) v.r 0·80 among women; P< 0·001 for both differences. An overall index of seven CVD risk factors was also more strongly associated with BMI (r 0·58) and waist circumference (r 0·61) than with the body adiposity index (r 0·49). The weaker associations with the body adiposity index were observed in analyses stratified by sex, race, age and year of examination. Multivariable analyses indicated that if either BMI or waist circumference were known, the body adiposity index provided no additional information on skinfold thicknesses or risk factor levels. These findings indicate that the body adiposity index is likely to be an inferior index of adiposity than is either BMI or waist circumference.

Generalised skinfold equations developed in the 1970s are commonly used to estimate laboratory-measured percentage fat (BF%). The equations were developed on predominately white individuals using Siri's two-component percentage fat equation (BF%-GEN). We cross-validated the Jackson–Pollock (JP) generalised equations with samples of young white, Hispanic and African–American men and women using dual-energy X-ray absorptiometry (DXA) as the BF% referent criterion (BF%-DXA). The cross-sectional sample included 1129 women and men (aged 17–35 years). The correlations between BF%-GEN and BF%-DXA were 0·85 for women and 0·93 for men. Analysis of measurement error showed that BF%-GEN underestimated BF%-DXA of men and women by 1·3 and 3·0 %. General linear models (GLM) confirmed that BF%-GEN systematically underestimated BF%-DXA of Hispanic men and women, and overestimated BF%-DXA of African–American men. GLM were used to estimate BF%-DXA from the JP sum of skinfolds and to account for race/ethnic group bias. The fit statistics (R and standard error of the estimate; see) of the men's calibration model were: white, R 0·92, see 3·0 %; Hispanic, R 0·91, see 3·0 %; African–American, R 0·95, see 2·6 %. The women's statistics were: white and African–American, R 0·86, see 3·8 %; Hispanic, R 0·83, see 3·4 %. These results showed that BF%-GEN and BF%-DXA were highly correlated, but the error analyses documented that the generalised equations lacked accuracy when applied to these racially and ethnically diverse men and women. The inaccuracy was linked to the body composition and race/ethnic differences between these Training Intervention and Genetics of Exercise Response (TIGER) study subjects and the men and women used to develop the generalised equations in the 1970s and using BF%-DXA as the referent criterion.

Asian Indians are at high risk for the development of atherosclerosis and related complications, possibly initiated by higher body fat (BF). The present study attempted to establish appropriate cut-off levels of the BMI for defining overweight, considering percentage BF in healthy Asian Indians in northern India as the standard. A total of 123 healthy volunteers (eighty-six males aged 18–75 years and thirty-seven females aged 20–69 years) participated in the study. Clinical examination and anthropometric measurements were performed, and percentage BF was calculated. BMI for males was 21·4 (SD 3·7) KG/M2 AND FOR FEMALES WAS 23·3 (sd 5·5) kg/m2. Percentage BF was 21·3 (sd 7·6) in males and 35·4 (sd 5·0) in females. A comparison of BF data among Caucasians, Blacks, Polynesians and Asian ethnic groups (e.g. immigrant Chinese) revealed conspicuous differences. Receiver operating characteristic (ROC) curve analysis showed a low sensitivity and negative predictive value of the conventional cut-off value of the BMI (25 kg/m2) in identifying subjects with overweight as compared to the cut-off value based on percentage BF (males >25, females >30). This observation is particularly obvious in females, resulting in substantial misclassification. Based on the ROC curve, a lower cut-off value of the BMI (21·5 kg/m2 for males and 19·0 kg/m2 for females) displayed the optimal sensitivity and specificity, and less misclassification in identification of subjects with high percentage BF. Furthermore, a novel obesity variable, BF:BMI, was tested and should prove useful for interethnic comparison of body composition. In the northern Indian population, the conventional cut-off level of the BMI underestimates overweight and obesity when percentage BF is used as the standard to define overweight. These preliminary findings, if confirmed in a larger number of subjects and with the use of instruments having a higher accuracy of BF assessment, would be crucial for planning and the prevention and treatment of various obesity-related metabolic diseases in the Asian Indian population.