Maternal anthropometry as a predictor of birth weight

Abstract

Objective: 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. Design: Community-based longitudinal study. Setting: A rural union of Bhaluka Upazila, Mymensingh, located 110 km north-west of Dhaka, the capital of Bangladesh. Participants: 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. Results: 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 R 2 values) were in general weight at registration and weight at month 9, with adjusted R 2 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 R 2 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%. Conclusion: 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.

Relationship between maternal anthropometry and birth weight in a Sri Lankan cohort of term neonates

“…In contrast to these findings some studies 2, 3, 5, 6, 17 did not report significant relationships between neonatal Our data indicated that, of all the maternal measurements evaluated in this study, prepregnancy maternal weight was the strongest predictor of neonatal BW. This is in complete agreement with studies done in Bangladesh 18 and USA 4 . Based on the standardized regression coefficient, increase in the pre-pregnancy weight by 1 standard deviation, will increase by 0.222 standard deviations of neonatal BW.…”

Maternal “Junk Food” Diet During Pregnancy as a Predictor of High Birthweight: Findings from the Healthy Beginnings Trial

“…In addition, a birthweight greater than 4.0 kg is associated with an increased risk of obesity in both childhood and adolescence . This increased birthweight could be due in part to a decreased prevalence of smoking, and increases in maternal age, gestational diabetes , and maternal overweight and obesity .…”

Faktor Risiko Kejadian Berat Badan Lahir Rendah di Area Pertanian (Studi di Kabupaten Brebes)

“…Status gizi Ibu sebelum hamil dapat ditentukan dengan indikator berat badan, tinggi badan, Indeks Massa Tubuh (IMT), dan Lingkar Lengan Atas (LiLA). Status gizi yang baik pada ibu sebelum hamil menggambarkan ketersediaan cadangan zat gizi dalam tubuh ibu yang siap untuk mendukung pertumbuhan janin pada awal kehamilan (Nahar 2007;Rosha et al 2012). Hasil penelitian di Kabupaten Magelang menunjukkan adanya hubungan yang signifikan antara paparan pestisida dengan kejadin BBLR (Setyobudi et al 2013) serta penelitian yang dilakukan di Soppeng menunjukkan adanya pengaruh faktor maternal terhadap kejadian BBLR (Rahmawati & Nur 2010).…”