Discussion
tests/diagnosis, infection, LBW
INFECTION, SECONDARY
This study presented findings indicating that newborns from mothers who received the ENAT intervention exhibited significantly higher birth weights in comparison to newborns from mothers who did not receive the intervention. We found an effect size of 108 g for mean birth weight and a 36% reduction in LBW in the intervention arm compared to the control arm. These findings were further confirmed by multivariate analyses that adjusted for clustering and selected covariates.Available studies on the relationship between birthweight and the quality of ANC services suggested a lower risk of LBW associated with high-quality ANC services [The ENAT intervention strengthened the quality of existing routine ANC-based services in public health centers through training health workers, gap filling, mentoring and supportive supervision, and data use. Most importantly, ENAT has improved infection prevention in pregnant women by strengthening and providing point-of-care testing in health centers, which otherwise are not always available in public health facilities despite the national ANC guideline recommendations [The main strength of this study was the use of a CRCT design with adequate statistical power that allowed for the detection of changes in the primary and secondary outcomes. Second, we tested whether the pregnant women who participated in the intervention and control arms were similar in terms of selected background characteristics, and this analysis found no statistically significant differences between the two arms in terms of participants’ age, education, household wealth, number of pregnancies, number of living children, birth-to-pregnancy interval, maternal weight, MUAC and the gestational age at first ANC booking. Indeed, the balance between study arms of observed and unobserved factors is a goal of randomization for unbiased estimation of intervention effects in a CRCT design [Nevertheless, this study was not without limitations. There were 29.2% of the pregnant women in the intervention and 33.7% in the control arms who did not have birth weight data and were thus considered lost to follow-up. However, this study was powered considering a 41% loss to follow-up and achieved more than the anticipated sample size for birth weight in both study arms. We assessed for any selection bias associated with lost to follow-up by comparing the enrollment characteristics of the pregnant women who were the basis for the final analysis and those participants originally recruited and lost to follow-up. Those with the outcome and those lost to follow-up were broadly similar in terms of several enrollment characteristics, suggesting that the main outcome was unlikely to be biased by the lost to follow-up of the participants. However, we could not rule out the presence of unmeasured factors that could vary between those with the outcome and those lost to follow-up. Our study lacked data on the pregnant women’s health status at their ANC booking and during follow-up, and there were no detailed and organized data that indicated the results of the screening tests/diagnosis, the types of treatments provided as well as the outcomes of the treatments received. This information is crucial to examine how the different components of ANC services influence the recorded birthweight. Another limitation that should be acknowledged is that apart from the birth weight data, there was no similar quality assurance or monitoring of the large array of ANC data that were extracted from the ANC and delivery registration books because this study could not interfere with the routine activities of the health centers. Nonetheless, we assume that any data quality issues related to the uptake of ANC services are randomly distributed between both study arms, without any systematic relationship to bias the findings.