PurposeWe aimed to describe the prevalence of undernutrition in hospitalised infants aged under 6 months and test the utility of simple index measures to detect undernutrition.DesignDiagnostic accuracy study: weight, length, mid-upper arm circumference (MUAC), triceps and subscapular skinfolds were measured in infants aged 2 weeks to 6 months admitted to a Teaching Hospital in Enugu, Nigeria. Index criteria: low (<−2SD) weight-for-age Z-scores (WAZ), weight-for-length Z-scores (WLZ); MUAC <11 cm. Reference definition: weight faltering (conditional weight gain below fifth percentile for healthy Nigerian infants) or sum of skinfolds (SSF) <10 mm.ResultsOf 125 hospitalised infants, only 5% (6) were admitted specifically for undernutrition, but low SSF were found in 33% (41) and, 24% (25) with known birth weight had weight faltering, giving an undernutrition prevalence of 36%. Low WAZ was the most discriminating predictor of undernutrition (sensitivity 69%, positive predictive value 86%, likelihood ratio 5.5; area under receiver operator curves 0.90) followed by MUAC (73%, 73%, 4.9; 0.86), while WLZ performed least well (49%, 67%, 2.9; 0.84). Where both MUAC and WAZ were low, there was sensitivity 90%, positive predictive value 82% and likelihood ratio 8.7.ConclusionsInfants aged under 6 months admitted to hospital in Nigeria had a high prevalence of undernutrition. In young, high-risk population, a low WAZ alone was a valuable screening criterion, while combining weight with MUAC gave even higher discrimination. Measurement of length to calculate WLZ was a less useful predictor in this population.

43We aimed to compare plotting accuracy and interpretation of weight gain patterns in average 44 and small infants on Road-to-Health (RTH) and the new WHO growth charts in Enugu, 45Nigeria. Child health staff plotted standard weights on both formats. Twelve plotted charts 46 were created, permutating 3 different weight trajectories (fast, steady, slow) ending at two 47 attained weights (average, small), with each plotted on both chart formats. Respondents 48 were shown four of these charts and asked to describe the weight gain pattern shown and 49 what action this pattern would prompt. There were 222 respondents, of whom 78% were 50 hospital-based; 54% were nurses, 32% medical doctors, and 13% nutritionists. Plotting 51 accuracy was good on both the WHO and RTH charts, but rating of weight gain was 52 generally poor. On the RTH chart, slow weight gain was correctly recognised in only 19% 53 average and 35% small infants and responses were not significantly associated with the 54 pattern shown. On the WHO charts, slow weight gain was correctly recognised in 40% 55 average and 65% small infants (p=0.002 and <0.001), but they were also more likely to rate 56 small children with normal growth as slow weight gain. In a logistic regression model, final 57 weight predicted a slow weight gain rating more strongly (OR=2.4; 1.8 to 3.2) than an actual 58 slow weight gain pattern (OR 1.8; 1.1 to 1.6). Health staff seemed unable to recognize slow 59 weight gain and were influenced more by current weight than actual weight gain pattern, 60 though the new WHO format improved recognition. 61 62