Gestational weight gain trajectories in GARBH-Ini pregnancy cohort in North India and a comparative analysis with global references

The impact of cohort inclusion/exclusion criteria on pregnancy weight gain chart percentiles

Pregnancy weight gain standards are charts describing percentiles of weight gain among participants with no risk factors that could adversely affect weight gain. This detailed information is burdensome to collect. We investigated the extent to which exclusion of various pre-pregnancy, pregnancy and postpartum factors impacted the values of pregnancy weight gain percentiles. We examined pregnancy weight gain (kg) among 3178 participants of the US nuMoM2b-Heart Health Study (HHS). We identified five groups of potential exclusion criteria for pregnancy weight gain standards: socio-economic characteristics (group 1), maternal morbidities (group 2), lifestyle/behaviour factors (group 3), adverse neonatal outcomes (group 4) and longer-term adverse outcomes (group 5). We established the impact of different exclusion criteria by comparing the median, 25th and 75th percentiles of weight gain in the full cohort with the values after applying each of the five exclusion criteria groups. Differences > 0·75 kg were considered meaningful. Excluding participants with group 1, 2, 3 or 4 exclusion criteria had no impact on the 25th, median or 75th percentiles of pregnancy weight gain. Percentiles were only meaningfully different after excluding participants in group 5 (longer-term adverse outcomes), which shifted the upper end of the weight gain distribution to lower values (e.g. 75th percentile decreased from 19·6 kg to 17·8 kg). This shift was due to exclusion of participants with excess postpartum weight retention > 5 kg or > 10 kg. Except for excess postpartum weight retention, most potential exclusion criteria for pregnancy weight gain standards did not meaningfully impact chart percentiles.

Incidence of and risk factors for small vulnerable newborns in north India: a secondary analysis of a prospective pregnancy cohort

BACKGROUND

Globally, recent estimates have shown there have been 3·6 million stillbirths and neonatal deaths in 2022, with nearly 60% occurring in low-income and middle-income countries. The Small Vulnerable Newborn Consortium has proposed a framework combining preterm birth (<37 weeks of gestation), small for gestational age (SGA) by INTERGROWTH-21st standard, and low birthweight (<2500 g) under the category small vulnerable newborns (SVN). Reliable data on SVN from sub-Saharan Africa, central Asia, and south Asia are sparse. We aimed to estimate the incidence of SVN and its types, and quantify risk factors, both overall and trimester-specific, from a pregnancy cohort in north India.

METHODS

In the GARBH-Ini (Interdisciplinary Group for Advanced Research on Birth Outcomes-DBT India Initiative) pregnancy cohort, 8000 participants were enrolled with less than 20 weeks' gestation between May 11, 2015, and Aug 8, 2020, at a secondary-care hospital in north India. The cohort was followed up across the antenatal period for a detailed study on preterm birth. We conducted a secondary analysis of cohort data for the outcome of SVN, classified into its types: preterm-SGA, preterm-nonSGA, and term-SGA. We estimated the relative risk and population attributable fraction of candidate risk factors for SVN (modified Poisson regression) and its types (multinomial regression).

FINDINGS

7183 (89·9%) of 7990 participants completed the study. Among 6206 newborns included for analysis, the incidence of SVN was 48·4% (35·1% term-SGA newborns [n=2179], 9·7% preterm-nonSGA newborns [n=605], and 3·6% preterm-SGA newborns [n=222]). Compared with term-nonSGA newborns, proportions of stillbirths and neonatal deaths within 72 h of birth among SVN were three times and 2·5 times higher, respectively. Preterm-SGA newborns had the highest incidence of stillbirth (15 [6·8%] of 222) and neonatal deaths (six [4·2%] of 142). Low body-mass index (BMI <18·5 kg/m2) of participants at the start of pregnancy was associated with higher risk for preterm-SGA (adjusted relative risk [RR] 1·61 [95% CI 1·17-2·22]), preterm-nonSGA (1·35 [1·09-1·68]), and term-SGA (1·44 [1·27- 1·64]), with population attributable fraction ranging from 8·7% to 13·8%. Pre-eclampsia (adjusted RR 1·48 [95% CI 1·30-1·71]), short cervical length (1·15 [1·04-1·26]), and bacterial vaginosis (1·13 [0·88-1·45]) were other important antenatal risk factors.

INTERPRETATION

In a comprehensive analysis of SVN and its types from north India, we identified risk factors to guide prioritisation of interventions. Complemented with risk-stratification tools, this focused approach will enhance antenatal care, and accelerate achievement of Sustainable Development Goals-namely, to end preventable deaths of newborns and children younger than 5 years by 2030 (target 3·2).

FUNDING

Department of Biotechnology, Government of India and Grand Challenges India-Biotechnology Industry Research Assistance Council, Government of India.

TRANSLATION

For the Hindi translation of the abstract see Supplementary Materials section.

The Impact of Excluding Adverse Neonatal Outcomes on the Creation of Gestational Weight Gain Charts Among Women from Low- and Middle-income Countries with Normal and Overweight BMI

BACKGROUND

Existing gestational weight gain (GWG) charts vary considerably in their choice of exclusion/inclusion criteria, and it is unclear to what extent these criteria create differences in the charts' percentile values.

OBJECTIVES

We aimed to establish the impact of including/excluding pregnancies with adverse neonatal outcomes when constructing GWG charts.

METHODS

This is an individual participant data analysis from 31 studies from low- and middle-income countries. We created a dataset that included all participants and a dataset restricted to those with no adverse neonatal outcomes: preterm < 37 wk, small or large for gestational age, low birth weight < 2500 g, or macrosomia > 4000 g. Quantile regression models were used to create GWG curves from 9 to 40 wk, stratified by prepregnancy BMI, in each dataset.

RESULTS

The dataset without the exclusion criteria applied included 14,685 individuals with normal weight and 4831 with overweight. After removing adverse neonatal outcomes, 10,479 individuals with normal weight and 3466 individuals with overweight remained. GWG distributions at 13, 27, and 40 wk were virtually identical between the datasets with and without the exclusion criteria, except at 40 wk for normal weight and 27 wk for overweight. For the 10th and 90th percentiles, the differences between the estimated GWG were larger for overweight (∼1.5 kg) compared with normal weight (<1 kg). Removal of adverse neonatal outcomes had minimal impact on GWG trajectories of normal weight. For overweight, the percentiles estimated in the dataset without the criteria were slightly higher than those in the dataset with the criteria applied. Nevertheless, differences were <1 kg and virtually nonexistent at the end of pregnancy.

CONCLUSIONS

Removing pregnancies with adverse neonatal outcomes has little or no influence on the GWG trajectories of individuals with normal and overweight.

Recommendations for India-specific multiple micronutrient supplement through expert consultation

Background & objectives Reducing maternal anaemia and enhancing feto-maternal health to achieve desired birth outcomes is a major health concern in India. Micronutrient deficiencies during pregnancy may impact fetal growth and neonatal outcomes. There is increasing interest in using multiple micronutrient supplement (MMS) during pregnancy. However, the World Health Organization (WHO) recommends use of MMS containing Iron and Folic Acid (IFA) in the context of "rigorous research". Against this backdrop, an Indian Council of Medical Research (ICMR)-led MMS design expert group met over six months to review the evidence and decide on the formulation of an India-specific MMS supplement for pregnant mothers for potential use in a research setting. Methods The India-MMS design expert group conducted a series of meetings to assess the available evidence regarding the prevalence of micronutrient deficiencies in pregnant women in India, the health benefits of supplementing with different micronutrients during pregnancy, as well as nutrient interactions within the MMS formulation. Based on these considerations, the expert group reached a consensus on the composition of the MMS tailored for pregnant women in India. Results The India-specific MMS formulation includes five minerals and 10 vitamins, similar to the United Nations International Multiple Micronutrient Antenatal Preparation (UNIMMAP) composition. However, the quantities of all vitamins and minerals except Zinc, Vitamin E, and Vitamin B6 differ. Interpretation & conclusions This report provides an overview of the process adopted, the evidence evaluated, and the conclusions from the expert working group meetings to finalize an MMS supplement in pregnancy for the Indian context to be used in a research setting.

Maternal weight latent trajectories and associations with adverse pregnancy outcomes using a smoothing mixture model

Class membership is a critical issue in health data sciences. Different types of statistical models have been widely applied to identify participants within a population with heterogeneous longitudinal trajectories. This study aims to identify latent longitudinal trajectories of maternal weight associated with adverse pregnancy outcomes using smoothing mixture model (SMM). Data were collected from the Khuzestan Vitamin D Deficiency Screening Program in Pregnancy. We applied the data of 877 pregnant women living in Shooshtar city, whose weights during the nine months of pregnancy were available. In the first step, maternal weight was classified and participants were assigned to only one group for which the estimated trajectory is the most similar to the observed one using SMM; then, we examined the associations of identified trajectories with risk of adverse pregnancy endpoints by applying logistic regression. Three latent trajectories for maternal weight during pregnancy were identified and named as low, medium and high weight trajectories. Crude estimated odds ratio (OR) for icterus, preterm delivery, NICU admission and composite neonatal events shows significantly higher risks in trajectory 1 (low weight) compared to trajectory 2 (medium weight) by 69% (OR = 1.69, 95%CI 1.20, 2.39), 82% (OR = 1.82, 95%CI 1.14, 2.87), 77% (OR = 1.77, 95%CI 1.17, 2.43), and 85% (OR = 1.85, 95%CI 1.38, 2.76), respectively. Latent class trajectories of maternal weights can be accurately estimated using SMM. It is a powerful means for researchers to appropriately assign individuals to their class. The U-shaped curve of association between maternal weight gain and risk of maternal complications reveals that the optimum place for pregnant women could be in the middle of the growth curve to minimize the risks. Low maternal weight trajectory compared to high had even a significantly higher hazard for some neonatal adverse events. Therefore, appropriate weight gain is critical for pregnant women.Trial registration International Standard Randomized Controlled Trial Number (ISRCTN): 2014102519660N1; http://www.irct.ir/searchresult.php?keyword=&id=19660&number=1&prt=7805&total=10&m=1 (Archived by WebCite at http://www.webcitation.org/6p3lkqFdV ).

Gestational weight gain in the REVAMP pregnancy cohort in Western India: Comparison with international and national references

Objective

To determine the trimester specific gestational weight gain (GWG) in a population of pregnant women from Western India and compare it with the Intergrowth-21st international and an Indian reference (GARBH-Ini cohort-Group for Advanced Research on BirtH outcomes).

Study design

A prospective longitudinal observational study was undertaken in Pune, West India and data for gestational weight gain was collected [the REVAMP study (Research Exploring Various Aspects and Mechanisms in Preeclampsia)]. Generalized Additive Models for Location, Scale and Shape method (GAMLSS model) were used to create GWG centile curves according to gestational age, stratified by BMI at recruitment (n = 640) and compared with Intergrowth-21st reference and GARBH-Ini cohort. Multivariable regression analysis was used to evaluate the relationship between GWG and antenatal risk factors.

Results

The median GWG was 1.68, 5.80, 7.06, and 11.56 kg at gestational ages 18, 26, 30, and 40 weeks, respectively. In our study, pregnant women gained less weight throughout pregnancy compared to Intergrowth-21st study, but more weight compared to the GARBH-Ini cohort centile curves in all the BMI categories. GWG in overweight/obese women (BMI ≥ 25) was significantly lower (<0.001) as compared to underweight (BMI < 18.5), or normal weight women (BMI ≥ 18.5 and <25). The median GWG at 40 weeks in underweight, normal and overweight/obese women was 13.18, 11.74, and 10.48 kg, respectively. Higher maternal BMI, older maternal age, higher parity and higher hemoglobin concentrations were associated with lower GWG, while taller maternal height was associated with greater GWG.

Conclusion

GWG of Indian women is lower than the prescriptive standards of the Intergrowth charts.