To determine whether maternal anthropometry predicted birth weight, and if so, to identify which cut-offs provided the best prediction of low birth weight (LBW) in a field situation.
Community-based longitudinal study.
A rural union of Bhaluka Upazila, Mymensingh, located 110 km north-west of Dhaka, the capital of Bangladesh.
A total of 1104 normotensive, non-smoking pregnant women who attended community nutrition centres were studied from first presentation at the centre until delivery of their child.
Most of the pregnant mothers were between 20 and 34 years of age. Over one-third of the women were nulliparous, while 12.8% were multiparous (parity ≥ 4). Most (93%) mothers registered between the 3rd and 5th month of pregnancy. The frequency of LBW ( < 2500 g) was 17%. Polynomial regression analyses showed that the best predictors of birth weight (based on adjusted R2 values) were in general weight at registration and weight at month 9, with adjusted R2 ranging from 2.5% to nearly 20%. Sequential regression analyses with height and weight showed that there was a significant effect of height after removing the weight variables, and adjusted R2 increased in all analyses. Weight and height at registration month continued to be the best predictors of LBW. Sensitivity and specificity curves were drawn for each registration month, body mass index and different weight gain groups, and using different weight and height combinations. The results showed that, for registration month 3–5, a combination of weight ( ≤ 45 kg) and height ( ≤ 150 cm) gave the highest sensitivity, which was 50%. However, maternal weight ≤ 43 kg in pregnancy month 3–5 alone gave the highest sensitivity of 80%.
The best predictor of birth weight as a continuous variable was maternal weight at registration, each 1 kg increase in weight at registration being associated with an increase in birth weight of about 260 g. Maternal weight ≤ 43 kg in pregnancy month 3–5 alone gave the highest sensitivity of 80%. A combination of initial weight and height of the mother was not as good a predictor of LBW as weight alone.
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