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ObjectiveThis cross-sectional study set in a single school on the outskirts of a large city aimed to document the extent of double burden of malnutrition (coexistence of overnutrition and undernutrition) among Indian schoolchildren from lower socioeconomic groups, and to determine if mid-upper arm circumference (MUAC) can be used as a proxy for body mass index (BMI).SubjectsThe total number of participants was 1444, comprising 424 girls and 1020 boys belonging to playgroups and grades 1 to 7.MeasurementsAnthropometric measurements, such as participants’ MUAC, height and weight were measured using standard techniques. Descriptive statistics for BMI and MUAC were obtained based on gender; z-scores were computed using age-specific and sex-specific WHO reference data. The distribution of variables was calculated for three groups: girls, boys and all participants. Homogeneous subsets for BMI and MUAC were identified in the three groups. Age-wise comparisons of BMI and MUAC were conducted for each gender.Main outcome measures(1) To know if MUAC and BMI are correlated among boys and girls. (2) To study BMI and MUAC z-score distribution among the participants.ResultsMUAC was positively correlated with BMI in both boys and girls. The following BMI z-score distribution was observed: severe acute malnutrition (SAM), 5 (0.3%); moderate acute malnutrition (MAM), 146 (10.1%) and undernourished, at risk of MAM/SAM, 141 (9.8%); obese, 21 (1.5%); overweight, 36 (2.5%) and pre-obese, 136 (9.4%). The distribution of categories of children based on MUAC z-scores was: SAM, 7 (0.5%); MAM, 181 (12.5%) and undernourished, at risk of MAM/SAM, 181 (12.5%); obese, 19 (1.3%); overweight, 178 (12.3%) and pre-obese, 135 (9.3%).ConclusionsSAM/MAM/undernourished states and obesity/overweight/pre-obese states, indicating undernutrition more than overweight, coexist among Indian schoolchildren from lower middle/lower socioeconomic categories. BMI and MUAC were significantly correlated. MUAC identifies both undernutrition and overnutrition by early detection of aberrant growth. |
