Use of a Simple Anthropometric Measurement to Identify Low-Birth-Weight Infants in Enugu, Nigeria

The impact of intimate partner violence on adverse birth outcomes in public health facilities. A prospective cohort study

BACKGROUND

During pregnancy, intimate partner violence (IPV) is a health problem associated with severe adverse birth outcomes. The Ethiopian Demographic Health Survey showed that more than one-third of married women faced IPV. Therefore, this study aimed to investigate the effects of IPV during pregnancy on adverse birth outcomes.

METHODS

A prospective cohort study was conducted from September 1st, 2021 to April 30th, 2022. Using a systematic random sampling technique, participants were enrolled from 20 to 24 weeks of gestation at antenatal visits at the selected public health institutions. The validated and modified standards of the World Health Organization Domestic Violence Questionnaire were used to screen for IPV. Bivariate and multivariate logistic regression models were used in this study. The relative risk was also calculated to predict the occurrence of adverse birth outcomes.

RESULTS

Overall, 701 pregnant women were followed from 20 to 24 weeks of gestation until delivery in a 1:2 ratio (244 exposed to 457 non-exposed). Preterm birth increased by 1.02 times (RR=1.02, 95 CI; 0.979-1.047), low birth weight with RR= 2.023, 95% CI; 1.201-3.407 and stillbirth (RR= 1.124, 95%CI; 0.43-3.055). Among the exposed groups, 167(23.8%), 83 (11.8%), and 51 (7.3%) had emotional, physical, and sexual violence, respectively. The odds of developing adverse birth outcomes from IPV exposure were [AOR=1.63,95% CI: [1.23, 3.75], emotional violence [AOR= 1.70:95% CI: [1.24, 4.24], and physical violence [AOR= 3.99:95% CI: [1.51, 10.52] times higher than those of their counterparts. No significant association was observed between sexual violence and adverse birth outcomes. Being unsupported by the husband and having previous adverse birth outcomes increased IPV by nearly four-fold [AOR=3.80:95% CI; 1.19, 12.09] and [AOR= 3.70:95% CI:1.49, 9.17], respectively. The odds of mothers with a 2nd visit MUAC measurement of < 23 cm were [AOR=2.81:95% CI; 1.20, 6.61].

CONCLUSION

The incidence of adverse birth outcomes was significantly higher in the physically IPV-exposed group than in the non-exposed group. Therefore, pregnant women should be screened for IPV during their antenatal period. Thus, IPV-exposed pregnant women should be counseled and closely followed up.

Newborn Mid-Upper Arm Circumference Identifies Low-Birth Weight and Vulnerable Infants: A Secondary Analysis

Background

Low birth weight (LBW) infants are at increased risk of morbidity and mortality. Identification of LBW may not occur in settings where access to reliable scales is limited. Mid-upper arm circumference (MUAC) may be an accessible, low-cost measure to identify LBW and vulnerable infants.

Objectives

We explored the validity of newborn MUAC in identifying LBW and vulnerable newborns in rural Sierra Leone.

Methods

This study was a secondary analysis of infant data from a randomized controlled clinical trial of supplementary food and anti-infective therapies compared with standard care for undernourished pregnant women. Data for singleton liveborn infants with birth measurement and 6-mo survival data were included in this analysis. The primary outcome was validity of MUAC in identifying low-birth weight (LBW) neonates. Secondary outcomes included validity of MUAC and head circumference (HC) in identifying weight-for-length z-score (WLZ) <-2, length-for-age z-score (LAZ) <-2, neonatal mortality, and mortality within the first 6 mo of life.

Results

The study population included 1167 infants, 229 (19.6%) with LBW. Birth MUAC (r = 0.817) and HC (r = 0.752) were highly correlated with birth weight. MUAC (AUC: 0.905; 95% CI: 0.884, 0.925) performed superiorly to HC (AUC: 0.88; 95% CI: 0.856, 0.904) in identifying LBW. The MUAC for identifying LBW was 9.6 cm (sensitivity: 0.86; specificity: 0.78). Neither MUAC nor HC reliably identified newborns with WLZ <-2 or LAZ <-2. MUAC ≤9.0 cm was the ideal cutoff for neonatal mortality (sensitivity: 53.3%; specificity: 89.7%; HR: 9.57; 95% CI: 1.86, 49.30). Birth anthropometrics did not reliably identify infants at risk of death in the first 6 mo of life.

Conclusions

MUAC was used successfully to identify LBW infants and infants at risk of neonatal mortality in Sierra Leone. Further evidence is needed to support increased use of newborn MUAC measurement to identify LBW infants and infants at risk of neonatal mortality in community settings where scales are not available. Primary trial was registered at clinicaltrials.gov as NCT03079388.

Lay Summary

Mid-upper arm circumference (MUAC) can be used to identify infants with low birth weight and infants at risk for neonatal mortality, with an MUAC ≤9.0 cm indicating the highest risk.

Prediction of Birth Weight by Using Neonatal Anthropometric Parameters at Birth in Finote Selam Hospital, Ethiopia

Introduction

Birth weight is an indicator of a newborn’s chances for survival and growth. However, developing countries lack enough weighing scales to identify low birth weight babies. Therefore, finding an alternative to weighing scales is vital.

Objective

To predict birth weight from neonatal anthropometric parameters at birth in Finote Selam Hospital, Ethiopia.

Methods

A hospital-based cross-sectional study was carried out from July 13 to October 27, 2020. A total of 424 live-delivered neonates were enrolled. Based on eligibility, birth weight and neonatal anthropometric parameters like crown–heel length, foot length, hand length, mid-upper arm circumference, umbilical–nipple distance, intermammary distance and head circumference were measured within 24 hours of birth. The association between birth weight and neonatal anthropometric parameters was evaluated using correlation analysis. Birth weight predictive regression models were formulated by using simple and multiple linear regression analysis.

Results

All neonatal anthropometric parameters had positive significant correlation with birth weight at p<0.05. Amongst the neonatal anthropometric parameters, the highest significant correlation with birth weight was observed on mid-upper arm circumference (MUAC) followed by foot length (FL), each being r=0.474 and r=0.461, respectively. The best predictive regression models were formulated as birth weight (kg)=0.117+[0.284×MUAC (cm)] and birth weight (kg)=1.137+[0.254×FL (cm)]. As compared to individual neonatal anthropometric parameters, a combination of MUAC, hand length (HL), FL and crown–heel length (CHL) had the highest significant correlation (r=0.661), and a multiple regression equation used to estimate birth weight was formulated as birth weight (kg)=−2.489+[0.192×MUAC(cm)]+[0.078×HL(cm)]+[0.11×FL (cm)]+[0.036×CHL(cm)].

Conclusion

Using a combination of MUAC, HL, FL and CHL followed by individual MUAC neonatal anthropometric parameters has high significance to identify low birth weight. Prediction of neonatal birth weight from neonatal anthropometric parameters is crucial to minimize the death of neonates due to low birth weight.