Abstract
South Asia has >50% of the global burden of low birth weight (LBW). The objective was to determine the extent to which maternal nutrition interventions commenced before conception or in the 1st trimester improved fetal growth in this region. This was a secondary analysis of combined newborn anthropometric data for the South Asian sites (India and Pakistan) in the Women First Preconception Maternal Nutrition Trial. Participants were 972 newborn of mothers who were poor, rural, unselected on basis of nutritional status, and had been randomized to receive a daily lipid-based micronutrient supplement commencing ≥3 months prior to conception (Arm 1), in the 1st trimester (Arm 2), or not at all (Arm 3). An additional protein-energy supplement was provided if BMI <20 kg/m2 or gestational weight gain was less than guidelines. Gestational age was established in the 1st trimester and newborn anthropometry obtained <48-hours post-delivery. Mean differences at birth between Arm 1 vs. 3 were length +5.3mm and weight +89g. Effect sizes (ES) and relative risks (RR) with 95% CI for Arm 1 vs. 3 were: length-for-age Z-score (LAZ) +0.29 (0.11–0.46, p = 0.0011); weight-for-age Z-score (WAZ) +0.22 (0.07–0.37, p = 0.0043); weight-to-length-ratio-for-age Z-score (WLRAZ) +0.27 (0.06–0.48, p = 0.0133); LAZ<-2, 0.56 (0.38–0.82, p = 0.0032); WAZ <-2, 0.68 (0.53–0.88, p = 0.0028); WLRAZ <-2, 0.76 (0.64–0.89, p = 0.0011); small-for-gestational-age (SGA), 0.74 (0.66–0.83, p<0.0001); low birth weight 0.81 (0.66–1.00, p = 0.0461). For Arm 2 vs. 3, LAZ, 0.21 (0.04–0.38); WAZ <-2, 0.70 (0.53–0.92); and SGA, 0.88 (0.79–0.97) were only marginally different. ES or RR did not differ for preterm birth for either Arm 1 vs. 3 or 2 vs. 3. In conclusion, point estimates for both continuous and binary anthropometric outcomes were consistently more favorable when maternal nutrition supplements were commenced ≥3 months prior to conception indicating benefits to fetal growth of improving women’s nutrition in this population.
Introduction
South Asian (S. Asian) countries, including India, Pakistan, Nepal, and Bangladesh, have wide intra- and inter-cultural diversity but much in common to encourage a regional perspective on women’s and children’s nutrition [1]. Despite recent declines in frequency of stunting, 38% of children under 5 years of age in S. Asia are still stunted, with rates exceeding one-third each in Pakistan, India, Bangladesh, and Nepal [2]. This region, because of the size of the population and high rates of stunting, accounts for 40% of the global burden of stunting [2–7]. Though wasting rates for children under the age of 5 years are lower, they remain unacceptably high, especially in India, as do rates of underweight in women of childbearing age. Only in Sri Lanka and Maldives is undernutrition now over-shadowed by excessive rates of obesity and diabetes [2]. The causes of early childhood stunting in S. Asia, as elsewhere, are multifactorial. However, low birth weight, especially low birth size for gestational age is a major factor [3, 8–10]. S. Asia accounts for over 50% of the global occurrence of low birth weight (LBW), with both Pakistan and India being major contributors to this high figure [11]. Furthermore, it has been postulated quite convincingly that recent figures are underestimates [9]. Even relatively mild fetal growth retardation is a strong predictor of stunting by two years of postnatal age. This applies whether the incidence of fetal growth failure is evaluated with birth weight or/and length measurements [12].
The importance of fetal growth directs attention to the in utero and, therefore, the maternal environment. Poverty is a common and overriding environmental cause of population fetal and postnatal growth retardation, and the apparent ‘enigma’ of the very high level of stunting and wasting in S. Asia has also been attributed specifically to the low social status of women in poor rural communities [13]. However, other factors contribute, among which malnutrition has a prominent primary and secondary role requiring specific preventive measures. In one study, birth size was strongly positively correlated with the intake of micronutrient-rich foods and with milk and fat intake [14]. Recent reviews of childhood stunting in S. Asia have included recognition of the importance of maternal nutrition and have given attention to the nutrition of non-pregnant women [4, 10, 15–20]. Priority attention to eliminating maternal undernutrition and fetal growth retardation are recognized to be central to health and sustainable development in S. Asia and elsewhere [21–24]. Public health measures focused on attention to nutrition at a community level are contributing to recent progress in India, Nepal, Bangladesh, and elsewhere [25–29]. However, current statistics reinforce the need to both ramp-up the application of existing evidence-based strategies and to test new strategies to improve women’s and, therefore, fetal nutrition [13].
Here we report the newborn anthropometric data for the combined S. Asian sites participating in the Women First Preconception Maternal Nutrition Trial [30].
Objectives
The primary objective of this study was to determine the quantitative improvements in the deficits in birth anthropometry resulting from commencing maternal nutrition supplements at least three months prior to conception or in the first trimester of pregnancy in the combined S. Asian sites participating in the Women First Preconception Maternal Nutrition Trial.
Methods
Ethics
The project was approved by the Colorado Multiple Institutional Review Board, University of Colorado; JNMC Institutional Ethics Committee on Human Subjects Research and the Indian Council of Medical Research (India); and The Aga Khan University Ethical Review Committee (Pakistan); and the Data Coordinating Center. All of these are registered with US Office of Human Research Protection and with Federal-wide Assurance in place. Written informed consent was obtained from all participants. The study protocol is available online: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4000057/. The Clinical Trial Registry number and website is ClinicalTrials.gov #NCT01883193; https://clinicaltrials.gov/ct2/show/NCT01883193?term=01883193&rank=1.
Study design and outcomes
This study was a secondary analysis of neonatal anthropometric outcomes in the Women First trial [30]. The parent study was an individually randomized, non-masked, multi-site randomized controlled efficacy trial conducted in four sites. The study sites are part of the of the Eunice Kennedy Shriver NICHD Global Network for Women’s and Children’s Health Research (GN) and are composed of a total of 24 geographic clusters from the GN Maternal Newborn Health Registry Each cluster has approximately 300 deliveries per year [31]. The trial included three arms: Arm 1 started the nutrition supplement for pregnant women at least three months prior to conception; Arm 2 commenced the same supplement near the end of the first trimester; and Arm 3 which did not receive any trial supplement. This South Asian sub-study was not included in the original Women First Preconception trial protocol or data analysis plan but was conceived as a separate sub-study prior to data analyses for those maternal / newborn dyads who had gestational age determined by ultrasound in the first trimester.
The continuous outcomes reported here by study arm include newborn length, weight, head circumference (HC), length-for-age Z-score (LAZ), weight-for-age Z-score (WAZ), HC-for-age Z-score (HCAZ), and weight to length ratio-for-age Z-scores (WLRAZ). Categorical outcomes include small for gestational age (SGA, weight <10th percentile for gestational age), low birth weight (LBW, <2500 g), preterm birth (PTB, gestational age <37 weeks), LAZ <-2, WAZ <-2, WLZ <-2 and WLRAZ <-2. Also included are RR for Z-scores <-1 because of their predictive value for subsequent infant growth [12].
Subjects and randomization
The participants included in this study were newborns whose mothers met all criteria for inclusion and retention in the parent study and who had ultrasound measurements of crown-rump length (CRL) in the first trimester. They were located in resource-poor rural communities in two S. Asian countries (India and Pakistan) and enrolled into the study between January and December 2014; data collection was completed in March 2017. The mothers of newborns in Arms 1 and 2 did not receive non-trial nutrition supplements during the trial intervention period. A high percentage of Arm 3 mothers in the India site received iron-folate supplements commencing by 12 weeks gestation, but the consumption of prenatal iron-folate was negligible in the Pakistan site. Women who had twin pregnancies were not excluded.
The Data Coordinating Center (DCC) created the randomization scheme and centrally generated the allocation sequence for each site. The scheme included a permuted block design stratified by GN clusters for assigning individual participants to a trial arm. The allocation ratio was 1:1:1 within blocks which randomly varied between sizes of 3, 6, or 9 for each site. Once an eligible participant was identified, the randomization assignment was generated by the site data manager from the centralized computerized data management system maintained by the DCC.
Nutrition intervention
The principal intervention was a lipid-based micronutrient supplement (Nutriset, Melauney, France) which also provided a favorable balance of polyunsaturated fatty acids and small quantities of protein and energy [32]. This product had minor modifications to a product previously designed for pregnant/lactating women [33]. Participants were instructed to take one sachet daily until delivery.
An additional protein-energy supplement was provided to women whose BMI was <20 kg/m2 from the time of randomization for Arm 1 participants and from the beginning of the 2nd trimester for Arm 2 participants. This protein-energy supplement was also provided to any Arm 1 or Arm 2 participant who failed to meet guidelines for gestational weight gain in the 2nd and 3rd trimesters [34]. Once the second supplement was commenced for either reason, it was provided until delivery. More than 90% of the women who had live births with newborn outcome measures received this additional protein energy supplement during the second and third trimesters.
Anthropometry and measurement of fetal crown-rump length (CRL)
Neonatal recumbent lengths, weights, and head circumferences were obtained within 48 hours of delivery by trained and periodically certified assessment teams. Measurements were obtained in triplicate, entered into the database, and the median value used for analysis. Equipment used were neonatal stadiometers (Ellard Instrumentation Ltd, Monroe WA), seca 334 electronic scales, and seca 201 measuring tapes (seca North America, Chino CA). CRL measurements were obtained in the first trimester by ultrasonography.
Home visits and compliance
Participants in all three arms were visited by the home visitor research assistants every two weeks to record an interim health history and to administer a urine pregnancy test. The pregnancy testing was combined with calendar records of menses to ascertain last menstrual period and to guide the timing of ultrasounds to be obtained between 10–12 weeks estimated gestation. For Arms 1 and 2, these visits were also used to replenish the supply of trial supplements. Compliance with supplement(s) use was documented by inspection of calendars the women completed daily and by collection of empty, partially eaten, and unused intervention sachets. Compliance was calculated for Supplement 1 as the total number of sachets fully eaten divided by the number of days between starting Supplement 1 and delivery. Supplement 2 compliance was calculated similarly; however, the numerator is the total number of Supplement 2 sachets fully or partially eaten.
Adverse events and safety monitoring
Adverse events were monitored continuously as per protocol [32] and reported to the overall study principal investigators and the DCC within 48 hours for all deaths and within seven days for other adverse events, including adverse pregnancy outcomes, adverse neonatal events, hospitalizations, and allergic reactions. The Data Monitoring Committee reviewed the study progress for safety, trial progress, data completion, supplement compliance, and protocol violations twice yearly.
Statistical methods
The Intergrowth-21st standards were applied to describe the results of newborn anthropometry [35, 36] in terms of Z-scores and centiles (not shown except for weight-for-age centile <10th percentile). Study outcomes were assessed with a modified intention-to-treat approach. The overall treatment effect and pairwise comparisons (Arm 1 vs. Arm 2, Arm 1 vs. 3, as well as Arm 2 vs. 3) for the continuous anthropometry outcomes were obtained from linear models for the continuous outcomes (newborn length, weight, HC, LAZ, WAZ, HCAZ, and WLRAZ). Model-generated measures of ES with 95% confidence intervals (CI) and P values were adjusted for site and GN cluster nested within site. For binary anthropometry outcomes (SGA, LBW, PTB, LAZ <-1, LAZ <-2, WAZ <-1, WAZ <-2, WLZ <-1, WLZ <-2, WLRAZ <-1 and WLRAZ <-2), generalized linear models with generalized estimating equations were utilized to calculate relative risks with 95% CI and P values after adjusting for site while controlling for GN cluster correlations. P values are presented for descriptive purposes.
Results
Maternal characteristics
Women First participants in the combined S. Asian sites who were screened, enrolled and randomized, had eligible pregnancies, first trimester ultrasound determination of gestational age, delivered live births, and whose newborn had measurements within 48 hours are given in Fig 1. Nine hundred and sixty one pregnancies (972 newborns) for the combined S. Asian sites qualified for inclusion in this analysis. The number of pregnancies ranged from 295–337 per arm (Table 1). Baseline maternal characteristics for S. Asian mothers with a primary outcome differed between arms only for maternal education, with a higher percentage of women in Arms 1 and 3 having no formal education (p = 0.04, Table 1). Mean ± SD duration of exposure to Supplement for Arm 1 was 72.6 ± 16.8 weeks with overall compliance of 89.6 ± 9.9%. For Arm 2, duration of exposure to Supplement 1 was 26.3 ± 2.2 weeks with estimated compliance of 87.7 ± 15.7%. Supplement 2 was started in 67% of Arm 1 women prior to conception and in an additional 29% during gestation. In Arm 2, 92% of the women received Supplement 2 starting after 12 weeks gestation. The duration of Supplement 2 was 56.2 ± 25.5 weeks for Arm 1 and 23.7 ± 5.1 weeks for Arm 2.
Table 1. Overall baseline characteristics among women in South Asian study sites who had the primary outcome and gestational age available for newborns by treatment arma.
Variable | Arm 1 (n = 329) |
Arm 2 (n = 337) |
Arm 3 (n = 295) |
---|---|---|---|
Maternal age, n (%) | |||
<20 | 79 (24.0) | 80 (23.7) | 61 (20.7) |
20–24 | 148 (45.0) | 146 (43.3) | 124 (42.0) |
25 + | 102 (31.0) | 111 (32.9) | 110 (37.3) |
Maternal education, n (%) | |||
No formal schooling | 152 (46.2) | 137 (40.7) | 133 (45.1) |
Primary | 28 (8.5) | 48 (14.2) | 46 (15.6) |
Secondary + | 149 (45.3) | 152 (45.1) | 116 (39.3) |
Body Mass Index (BMI), kg/m2 | |||
Mean ± SD | 19.9 ± 3.1 | 19.7 ± 3.0 | 19.7 ± 3.1 |
Median (P25—P75) | 19.4 (17.8, 21.7) | 19.4 (17.6, 21.4) | 19.3 (17.4, 21.5) |
BMI < 20.0, n (%) | 181 (55.0) | 190 (56.4) | 174 (59.0) |
BMI < 18.5, n (%) | 122 (37.1) | 127 (37.7) | 113 (38.3) |
Height, cm, n | |||
Mean ± SD | 152.0 ± 5.9 | 151.2 ± 6.5 | 151.9 ± 6.2 |
Median (P25—P75) | 151.9 (148.5, 156.0) | 150.8 (147.0, 155.1) | 151.5 (148.3, 156.0) |
Parity, n (%) | |||
0 (nulliparous) | 110 (33.4) | 85 (25.2) | 76 (25.8) |
1 | 111 (33.7) | 118 (35.0) | 95 (32.2) |
≥ 2 | 108 (32.8) | 134 (39.8) | 124 (42.0) |
Tally of indicators of higher SESb, n (%) | |||
None (0 present) | 6 (1.8) | 2 (0.6) | 6 (2.0) |
1–2 present | 92 (28.0) | 87 (25.8) | 68 (23.1) |
3–4 present | 159 (48.3) | 183 (54.3) | 160 (54.2) |
5–6 present | 72 (21.9) | 65 (19.3) | 61 (20.7) |
aPrimary outcome obtained from one or more newborn of the woman.
bThe socio-economic status (SES) tally provides the number of indicators available from the following list: electricity, improved water source, sanitation, man-made flooring, improved cooking fuels, and household assets.
Newborn outcomes
The number of newborn with anthropometric outcomes ranged from 299–340 per arm (Table 2). Fortuitously the twin pregnancies were equally distributed between the three arms accounting for 2.5% of total newborn included in this analysis.
Table 2. Women First Maternal Preconception Nutrition Trial in South Asia.
Treatment Group | |||
---|---|---|---|
Variable | Arm 1 (n = 333) |
Arm 2 (n = 340) |
Arm 3 (n = 299) |
Length (cm) | |||
Mean ± SD | 47.71 ± 2.21 | 47.60 ± 2.59 | 47.18 ± 2.60 |
Median (P25, P75) | 47.90 (46.50, 49.00) | 47.80 (46.30, 49.20) | 47.40 (45.80, 48.80) |
Length-for-Age Z-Score (LAZ)b | |||
Mean ± SD | -0.62 ± 0.99 | -0.69 ± 1.13 | -0.90 ± 1.15 |
Median (P25, P75) | -0.55 (-1.24, -0.03) | -0.68 (-1.44, 0.07) | -0.88 (-1.74, -0.12) |
LAZ <-1, n (%) | 110 (33.0) | 130 (38.2) | 134 (44.8) |
LAZ <-2, n (%) | 33 (9.9) | 45 (13.2) | 53 (17.7) |
Weight (gm) | |||
Mean ± SD | 2757 ± 451 | 2714 ± 459 | 2668 ± 431 |
Median (P25, P75) | 2785 (2480, 3030) | 2730 (2455, 3003) | 2660 (2400, 2955) |
Weight-for-Age Z-Score (WAZ)b | |||
Mean ± SD | -0.98 ± 0.97 | -1.11 ± 0.97 | -1.20 ± 0.99 |
Median (P25, P75) | -0.98 (-1.63, -0.36) | -1.16 (-1.73, -0.43) | -1.25 (-1.97, -0.53) |
WAZ <-1, n (%) | 164 (49.2) | 198 (58.2) | 180 (60.2) |
WAZ <-2, n (%) | 52 (15.6) | 55 (16.2) | 68 (22.7) |
Weight-Length Ratio-for-Age Z-Score (WLRAZ)b,c |
|||
Mean ± SD | -1.38 ± 1.37 | -1.58 ± 1.32 | -1.65 ± 1.39 |
Median (P25, P75) | -1.35 (-2.30, -0.55) | -1.71 (-2.38, -0.65) | -1.70 (-2.67, -0.72) |
WLRAZ <-1, n (%) | 200 (61.0) | 233 (69.1) | 202 (68.5) |
WLRAZ <-2, n (%) | 105 (32.0) | 126 (37.4) | 125 (42.4) |
Head circumference (HC, cm)d | |||
Mean ± SD | 32.94 ± 1.43 | 32.87 ± 1.55 | 32.78 ± 1.60 |
Median (P25, P75) | 33.00 (32.00, 33.90) | 33.00 (32.10, 33.80) | 32.90 (32.00, 33.80) |
HC-for-Age Z-Score (HCAZ)b,d | |||
Mean ± SD | -0.55 ± 1.05 | -0.62 ± 1.06 | -0.66 ± 1.15 |
Median (P25, P75) | -0.60 (-1.27, 0.15) | -0.59 (-1.31, 0.01) | -0.70 (-1.44, -0.02) |
HCAZ < -1, n (%) | 116 (34.9) | 119 (35.1) | 110 (36.8) |
HCAZ < -2, n (%) | 27 (8.1) | 29 (8.6) | 32 (10.7) |
Small for gestational age, n (%)e | 121 (36.3) | 148 (43.5) | 147 (49.2) |
Low birth weight (<2500 gm), n (%) | 92 (27.6) | 98 (28.8) | 102 (34.1) |
Preterm birth (<37 weeks GA), n (%) | 41 (12.3) | 29 (8.5) | 37 (12.4) |
aGestational age (GA) at birth is defined as the gestational age at the time of ultrasound measurement of fetal crown-rump length plus time until birth if the ultrasound was done between 6 weeks + 0 days to 13 weeks + 6 days and the GA at birth is between 24 weeks + 0 days and 42 weeks + 6 days.
bLength, weight, head circumference, and weight-length-ratio z-scores and percentiles based on measurements within 48 hours of age are calculated using the International Standards for Newborn Size and International Standards for Newborn Size for Very Preterm Infants published by the INTERGROWTH-21st Project [37–39] which provide Z-scores and percentiles by sex and GA at birth for infants born between 33 weeks + 0 days to 42 weeks + 6 days GA at birth and between 24 weeks + 0 days to 32 weeks + 6 days GA at birth respectively.
cArm 1 n = 328; Arm 2 n = 337; Arm 3 n = 295; total n = 960.
dArm 1 n = 332; Arm 2 n = 339; Arm 3 n = 299; total n = 970.
eSmall for Gestational Age (SGA) is a classification given to infants with a low birth weight, more specifically, a birth weight that is in 10th percentile or lower based on standards by gestational age at birth and sex developed by INTERGROWTH-21st Project.
Anthropometric measures for controls (Arm 3) were determined by sex. Mean ± SD lengths were 46.83 ± 2.48 and 47.53 ± 2.67 cm for females and males, respectively. Corresponding figures for weight were 2605 ± 421 and 2731 ± 433 g and for head circumference were 32.44 ± 1.62 and 33.12 ±1.51 cm. However, the effects of the maternal supplements on newborn anthropometry did not vary by sex (p = 0.2133). Accordingly, sexes have been combined for all analyses.
For the newborns of women who did not receive trial nutrition supplements (Arm 3), mean LAZ and WAZ were low with WAZ more impaired than LAZ. This disparity was reflected in the WLRAZ with a mean of -1.65, but considerable variability (standard deviation 1.39) (Table 2). Head circumference was least impaired with a mean HCAZ of -0.66. Eighteen percent of newborns in Arm 3 were stunted (LAZ <-2) and 42% were wasted (WLRAZ <-2). For more than two-thirds of the newborns, the WLRAZ was <-1. Twelve percent were preterm deliveries; thirty-four percent had LBW, and 49% of Arm 3 were SGA. Head circumference was <-2 Z-scores in 11% of Arm 3.
Ninety-five percent CI for the positive effect sizes of the nutrition intervention commencing ≥ 3 months prior to conception (Arm 1) in comparison with control Arm 3 did not include zero for LAZ, WAZ, and WLRAZ. In contrast, corresponding CI for effect sizes for continuous variables for the nutrition intervention commencing in the first trimester of pregnancy (Arm 2 vs. 3) included zero with the only exception of LAZ (Fig 2).
For binary variables, there was no reduction in relative risk for preterm delivery for either the preconception (Arm 1) or 1st trimester intervention (Arm 2) compared to the control arm (Arm 3). The intervention commencing in the preconception period (Arm 1) resulted in a reduction of 26% in the relative risk of SGA (p<0.0001) and a reduction in the incidence of LBW of 19% ((RR 0.81 (0.66–1.00, p = 0.0461)) in comparison with control arm (Arm 3). There were also substantial reductions (p<0.01) in the relative risks for stunting (LAZ <-2, 44%), underweight (WAZ <-2, 32%), and wasting (WLRAZ <-2, 24%) (Fig 3). For the intervention commencing in the first trimester (Arm 2) compared with the control arm (Arm 3), several outcomes were marginally different (P<0.05) but none of these outcomes differed at α = 0.01 level. Direct comparison of Arm 1 vs Arm 2 showed reduced risk for SGA, WAZ<-1 and WLRAZ<-1 for the preconception intervention. The only suggestion of the intervention commencing at either time in relation to conception having a benefit on head size was a RR for head circumference <3rd centile for Arm 1 vs. 3 of 0.73 (95% CI: 0.53–1.00).
Discussion
These newborn anthropometric outcomes for the combined data from the two S. Asian sites included in the Women First trial demonstrate that substantial corrections of deficits in both weight and linear measures of fetal growth can be achieved with maternal nutrition supplements commenced in the first trimester or earlier. Despite lack of significant differences for direct comparisons between Arms 1 and 2, the point estimates for the effect sizes were consistently more favorable for continuous and relative risks for binary anthropometric outcomes for the preconception intervention. These advantages of improving the nutrient and energy intake of women of childbearing age prior to conception were documented in S. Asian trial populations unselected for past or current nutritional status. These rural populations were, however, characterized by low income and sub-group dietary data in the first trimester documented low intakes of multiple micronutrients and, especially in India, borderline protein-energy intake [40].
The goal of this trial was not to evaluate a specific nutrition product or combination of products but rather to use these products to advance our understanding of the extent to which deficits in fetal growth could be corrected by commencing nutrition interventions very early in pregnancy or for a substantial time prior to conception in women of childbearing age in these and similar populations. It is quite possible that greater effects could be achieved with further modifications of the interventions, perhaps especially if guidelines for maternal gestational weight gain could be matched, and that these may be achievable with sustainable solutions including education and dietary improvements [41]. Meanwhile, the results of this trial extend our knowledge of the extent to which fetal growth deficits in poor S. Asian populations are attributable to undernutrition alone and can be corrected with nutrition interventions in women of childbearing age.
This trial addressed persistent shared and prominent challenges in this region [1]. A trial of iron-folate supplementation (IFS) early in this century documented a modest increase in birth weight, reduction in risk of low birth weight, and increase in head circumference [42–44]. The additional benefits of maternal multiple micronutrient supplements beyond those receiving IFS alone, either as trial supplements or standard of care, have been reviewed in detail [45], including data from India, Pakistan, Nepal, and Bangladesh. This analysis confirmed significantly but quite modestly lower relative risks for LBW, PTB, and SGA. A major contributor to this meta-analysis was the JiViTA-3 trial in Bangladesh, in which significant reductions in LBW were attributable to a longer mean gestational age and lower incidence of PTB rather than any effect on fetal growth rates [46]. This finding differed from the Women First trial in which gestational ages at delivery were the same for the three trial arms. The prematurity incidence in the control arm for the S. Asian sites in the current study (12.4%) was similar to that recently estimated for S. Asia [47]. The results for the meta-analysis of Smith, et al., on birth size were similar to those of an earlier meta-analysis of data from 12 sites [48] including four in S. Asia, one each in Pakistan [49] and Bangladesh [50], and two in Nepal [42, 51]. There has been only one lipid nutrition supplement trial in S. Asia that has been reported prior to Women First [52]. In comparison with the IFS control arm, this trial in rural Bangladesh resulted in statistically significant improvements in mean birth weight and length and in binary outcomes associated with these measurements. However, with the exception of sub-group analyses and reduction in the rate of stunting, all improvements were very modest.
The effect sizes for continuous outcomes and relative risks for binary outcomes in the current study compared favorably with those of previous trials in S. Asian countries in terms of improvements in fetal growth deficits whether the interventions were iron folate supplements, multi-micronutrients, or lipid nutrition supplements. The extent of the contribution to favorable outcomes of the additional protein-energy supplements is unknown. These were provided to two-thirds of Arm 1 participants prior to conception and to more than 90% of both Arm 1 and 2 participants during the 2nd and 3rd trimesters. Significant increases in birth weight resulting from maternal balanced protein energy supplements during pregnancy have been documented in S. Asia [53] and more widely [54]. However, this has not been a consistent finding [55]. Perhaps relevant and in contrast to the results of the Women First trial [30], these increases in birth weight in previous trials were specifically not accompanied by any increases in birth length. Though we did not observe any statistical differences between Arms 1 and 2 for newborn LAZ, the preconception (Arm 1) anthropometric outcomes had the largest point estimates for effect size compared to Arm 3 in this trial and compared favorably with corresponding outcomes of previous studies commenced during gestation. Both separately and combined with the data for the first trimester arm, these results are strongly supportive of commencing nutrition interventions as early as possible for women of childbearing age in resource poor populations.
A limitation of this trial has been its inevitable restriction to only part of one maternal life and to targeting only one environmental factor, namely maternal nutrition, when challenged with a multifactorial etiology [56]. The strengths of this trial include an intervention relatively comprehensive in nutrient content and quantity. The principal strength has been the early start of the intervention, especially the preconception arm, and the inclusion of women of childbearing age in these resource-poor communities irrespective of their long- or short-term nutritional status as defined by anthropometric indices.
Conclusions
Newborn anthropometric data for the Women First trial in the S. Asian region (combined data for the sites in India and Pakistan) provide further confirmation of the high incidence of stunting, wasting, low birth weight, and SGA in this region. Commencing a relatively comprehensive nutrition supplement at least three months prior to conception for women unselected for anthropometric indicators of nutritional status was associated with decreases of 44% in stunting, 24% in wasting, and 26% SGA when compared to the control group. These results provide quantitative information on the benefits to fetal growth achievable by improvement in intake of energy, protein, and micronutrients commencing before the start of the second trimester of gestation without any other interventions directed to improvement of the poor environments in which the participants lived. Furthermore, the relatively large point estimates for the effects of the nutrition supplement commenced ≥ 3 months prior to conception support enhanced efforts to improve the nutrition of all women of child-bearing age in resource-poor populations in these and similar environments in order to diminish impairment of fetal growth.
Acknowledgments
KMH and NFK conceived the original idea. The protocol was developed by KMH, SMD, NFK, VRT, AS, AD, and EM with intellectual input from SSG, SAA, SS, OP, RG, RD, MS, and MKT. NFK, KMH, JEW, VRT and EM coordinated the overall execution of the trial, while SSG, SMD, and MS (India), and OP, SS, and SAA (Pakistan) provided overall supervision and guidance to implement the study on site. SAA and UK oversaw data collection and quality monitoring in Pakistan and VH, SV, and YKS in India. AS and VRT performed the statistical analysis with supervision and input from AD and EMM. KMH, SMD, and NFK wrote the paper with support from JEW. Rebecca Lander (collaborator) contributed dietary data to the manuscript. All authors reviewed and approved the final manuscript.
Data Availability
All relevant data are available via ‘NICHD’s Data and Specimen Hub (DASH): https://dash.nichd.nih.gov/study/228833.
Funding Statement
This study was funded through The Bill & Melinda Gates Foundation OPP1055867 (www.gatesfoundation.org) (KMH and NFK); and The Eunice Kennedy Shriver NICHD (www.nichd.nih.gov) and the Office of Dietary Supplements (ods.od.nih.gov), NIH U10 HD 076474 (NFK and KMH). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
References
- 1.Akseer N, Kamali M, Arifeen SE, Malik A, Bhatti Z, Thacker N, et al. Progress in maternal and child health: how has South Asia fared? BMJ. 2017;357:j1608 Epub 2017/04/13. 10.1136/bmj.j1608 [DOI] [PubMed] [Google Scholar]
- 2.World Health Organization. World Health Statistics: monitoring health for the sustainable development goals (SDGs). Geneva: 2018. [Google Scholar]
- 3.Black RE, Victora CG, Walker SP, Bhutta ZA, Christian P, de Onis M, et al. Maternal and child undernutrition and overweight in low-income and middle-income countries. Lancet. 2013;382(9890):427–51. Epub 2013/06/12. 10.1016/S0140-6736(13)60937-X [DOI] [PubMed] [Google Scholar]
- 4.Aguayo VM, Menon P. Stop stunting: improving child feeding, women’s nutrition and household sanitation in South Asia. Matern Child Nutr. 2016;12 Suppl 1:3–11. Epub 2016/05/18. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.UNICEF. Stop stunting: improving child feeding, women’s nutrition and household sanitation in South Asia. Regional Conference; November 10–12; New Delhi, India: United Nations Children’s Fund; 2014.
- 6.UNICEF. Every child counts. United Nations Children’s Fund, 2014.
- 7.Stevens GA, Finucane MM, Paciorek CJ, Flaxman SR, White RA, Donner AJ, et al. Trends in mild, moderate, and severe stunting and underweight, and progress towards MDG 1 in 141 developing countries: a systematic analysis of population representative data. Lancet. 2012;380(9844):824–34. Epub 2012/07/10. 10.1016/S0140-6736(12)60647-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Danaei G, Andrews KG, Sudfeld CR, Fink G, McCoy DC, Peet E, et al. Risk factors for childhood stunting in 137 developing countries: a comparative risk assessment analysis at global, regional, and country levels. PLoS Med. 2016;13(11):e1002164 Epub 2016/11/02. 10.1371/journal.pmed.1002164 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Vir SC. Improving women’s nutrition imperative for rapid reduction of childhood stunting in South Asia: coupling of nutrition specific interventions with nutrition sensitive measures essential. Matern Child Nutr. 2016;12 Suppl 1:72–90. Epub 2016/05/18. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Aguayo VM, Nair R, Badgaiyan N, Krishna V. Determinants of stunting and poor linear growth in children under 2 years of age in India: an in-depth analysis of Maharashtra’s comprehensive nutrition survey. Matern Child Nutr. 2016;12 Suppl 1:121–40. Epub 2016/05/18. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.icddr b, UNICEF Bangladesh, GAIN, Institute of Public Health and Nutrition. National Micronutrients Status Survey 2011–12: Final Report. 2013.
- 12.Gough EK, Moodie EE, Prendergast AJ, Ntozini R, Moulton LH, Humphrey JH, et al. Linear growth trajectories in Zimbabwean infants. Am J Clin Nutr. 2016;104(6):1616–27. Epub 2016/11/04. 10.3945/ajcn.116.133538 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Rizvi A, Bhatti Z, Das JK, Bhutta ZA. Pakistan and the Millennium Development Goals for Maternal and Child Health: progress and the way forward. Paediatr Int Child Health. 2015;35(4):287–97. Epub 2016/01/09. 10.1080/20469047.2015.1109257 [DOI] [PubMed] [Google Scholar]
- 14.Rao S, Yajnik CS, Kanade A, Fall CH, Margetts BM, Jackson AA, et al. Intake of micronutrient-rich foods in rural Indian mothers is associated with the size of their babies at birth: Pune Maternal Nutrition Study. J Nutr. 2001;131(4):1217–24. Epub 2001/04/04. 10.1093/jn/131.4.1217 [DOI] [PubMed] [Google Scholar]
- 15.Ramakrishnan U, Grant F, Goldenberg T, Zongrone A, Martorell R. Effect of women’s nutrition before and during early pregnancy on maternal and infant outcomes: a systematic review. Paediatr Perinatal Epidemiol. 2012;26 Suppl 1:285–301. Epub 2012/07/07. [DOI] [PubMed] [Google Scholar]
- 16.Bhutta ZA, Das JK. Interventions to address maternal and childhood undernutrition: current evidence. Nestle Nutr Inst Workshop Ser. 2014;78:59–69. Epub 2014/02/08. 10.1159/000354941 [DOI] [PubMed] [Google Scholar]
- 17.Young MF, Martorell R. The public health challenge of early growth failure in India. Eur J Clin Nutr. 2013;67(5):496–500. Epub 2013/02/08. 10.1038/ejcn.2013.18 [DOI] [PubMed] [Google Scholar]
- 18.Dean SV, Lassi ZS, Imam AM, Bhutta ZA. Preconception care: nutritional risks and interventions. Reprod Health. 2014;11 Suppl 3:S3. Epub 2014/11/22. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Vaivada T, Gaffey MF, Das JK, Bhutta ZA. Evidence-based interventions for improvement of maternal and child nutrition in low-income settings: what’s new? Curr Opin Clin Nutr Metab Care. 2017;20(3):204–10. Epub 2017/02/17. 10.1097/MCO.0000000000000365 [DOI] [PubMed] [Google Scholar]
- 20.Young MF, Nguyen PH, Addo OY, Hao W, Nguyen H, Pham H, et al. The relative influence of maternal nutritional status before and during pregnancy on birth outcomes in Vietnam. Eur J Obstet Gynecol Reprod Biol. 2015;194:223–7. Epub 2015/10/11. 10.1016/j.ejogrb.2015.09.018 [DOI] [PubMed] [Google Scholar]
- 21.Christian P, Mullany LC, Hurley KM, Katz J, Black RE. Nutrition and maternal, neonatal, and child health. Semin Perinatol. 2015;39(5):361–72. Epub 2015/07/15. 10.1053/j.semperi.2015.06.009 [DOI] [PubMed] [Google Scholar]
- 22.International Food Policy Research Institute. Global Nutrition Report 2014: Actions and accountability to accelerate the world’s progress on nutrition. Washington, DC: 2014. [DOI] [PMC free article] [PubMed]
- 23.Maternal, Child Nutrition Study Group, Black RE, Alderman H, Bhutta ZA, et al. Maternal and child nutrition: building momentum for impact. Lancet. 2013;382(9890):372–5. Epub 2013/06/12. 10.1016/S0140-6736(13)60988-5 [DOI] [PubMed] [Google Scholar]
- 24.World Health Organization. World Health Assembly. Switzerland: 2014. [Google Scholar]
- 25.Ramakrishnan U, Lowe A, Vir S, Kumar S, Mohanraj R, Chaturvedi A, et al. Public health interventions, barriers, and opportunities for improving maternal nutrition in India. Food Nutr Bull. 2012;33(2 Suppl):S71–92. Epub 2012/08/24. 10.1177/15648265120332S105 [DOI] [PubMed] [Google Scholar]
- 26.Nahar S, Mascie-Taylor CGN, Begum HA. Impact of targeted food supplementation on pregnancy weight gain and birth weight in rural Bangladesh: an assessment of the Bangladesh Integrated Nutrition Program (BINP). Public Health Nutrition. 2009;12(8):1205–12. 10.1017/S1368980008003765 [DOI] [PubMed] [Google Scholar]
- 27.Victora CG, Barros FC, Assuncao MC, Restrepo-Mendez MC, Matijasevich A, Martorell R. Scaling up maternal nutrition programs to improve birth outcomes: a review of implementation issues. Food Nutr Bull. 2012;33(2 Suppl):S6–26. Epub 2012/08/24. 10.1177/15648265120332S102 [DOI] [PubMed] [Google Scholar]
- 28.Agarwal KN, Agarwal DK, Agarwal A, Rai S, Prasad R, Agarwal S, et al. Impact of the integrated child development services (ICDS) on maternal nutrition and birth weight in rural Varanasi. Indian Pediatr. 2000;37(12):1321–7. Epub 2000/12/19. [PubMed] [Google Scholar]
- 29.Khanam R, Lee ASC, Ram M, Quaiyum MA, Begum N, Choudhury A, et al. Levels and correlates of nutritional status of women of childbearing age in rural Bangladesh. Public Health Nutr. 2018:1–11. Epub 2018/08/16. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Hambidge KM, Westcott JE, Garces A, Figueroa L, Goudar S, Dhaded SM, et al. A multi-country randomized controlled trial of comprehensive maternal nutrition supplementation initiated prior to conception: the Women First trial. Am J Clin Nutr. 2019;109(2):457–69. 10.1093/ajcn/nqy228 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Bose CL, Bauserman M, Goldenberg RL, Goudar SS, McClure EM, Pasha O, et al. The Global Network Maternal Newborn Health Registry: a multi-national, community-based registry of pregnancy outcomes. Reprod Health. 2015;12 Suppl 2:S1. Epub 2015/06/13. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Hambidge KM, Krebs NF, Westcott JE, Garces A, Goudar SS, Kodkany BS, et al. Preconception maternal nutrition: a multi-site randomized controlled trial. BMC Pregnancy Childbirth. 2014;14:111 Epub 2014/03/22. 10.1186/1471-2393-14-111 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Arimond M, Zeilani M, Jungjohann S, Brown KH, Ashorn P, Allen LH, et al. Considerations in developing lipid-based nutrient supplements for prevention of undernutrition: experience from the International Lipid-Based Nutrient Supplements (iLiNS) Project. Matern Child Nutr. 2015;11 Suppl 4:31–61. Epub 2013/05/08. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Institute of Medicine and National Research Council. Weight gain during pregnancy: reexaming the guidelines. Washington, DC: The National Academies Press, 2009. [Google Scholar]
- 35.Villar J, Cheikh Ismail L, Victora CG, Ohuma EO, Bertino E, Altman DG, et al. International standards for newborn weight, length, and head circumference by gestational age and sex: the Newborn Cross-Sectional Study of the INTERGROWTH-21st Project. Lancet. 2014;384(9946):857–68. Epub 2014/09/12. 10.1016/S0140-6736(14)60932-6 [DOI] [PubMed] [Google Scholar]
- 36.Papageorghiou AT, Ohuma EO, Altman DG, Todros T, Cheikh Ismail L, Lambert A, et al. International standards for fetal growth based on serial ultrasound measurements: the Fetal Growth Longitudinal Study of the INTERGROWTH-21st Project. Lancet. 2014;384(9946):869–79. Epub 2014/09/12. 10.1016/S0140-6736(14)61490-2 [DOI] [PubMed] [Google Scholar]
- 37.INTERGROWTH-21st Project. International Standards for Newborn Size2018 06/01/2018 [cited 2018 June 1]. https://intergrowth21.tghn.org/newborn-size-birth/.
- 38.INTERGROWTH-21st Project. International Standards for Newborn Size for Very Preterm Infants2018 06/01/2018 [cited 2018 June 1]. https://intergrowth21.tghn.org/very-preterm-size-birth.
- 39.INTERGROWTH-21st Project. Standards and tools. 2018 [cited 2018 October 26, 2018]. https://intergrowth21.tghn.org/standards-tools/.
- 40.Lander RL, Hambidge KM, Westcott JE, Garces A, Figueroa L, Tejeda G, et al. High prevalence of first trimester pregnant women at risk of inadequate dietary intakes living in four low- and middle-income countries. Cur Dev Nutr. 2018;2(11):53–4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Hambidge KM, Krebs NF. Strategies for optimizing maternal nutrition to promote infant development. Reprod Health. 2018;15(Suppl 1):87 Epub 2018/06/28. 10.1186/s12978-018-0534-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Christian P, Khatry SK, Katz J, Pradhan EK, LeClerq SC, Shrestha SR, et al. Effects of alternative maternal micronutrient supplements on low birth weight in rural Nepal: double blind randomised community trial. BMJ. 2003;326(7389):571 Epub 2003/03/15. 10.1136/bmj.326.7389.571 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Christian P, Khatry SK, LeClerq SC, Dali SM. Effects of prenatal micronutrient supplementation on complications of labor and delivery and puerperal morbidity in rural Nepal. Int J Gynaecol Obstet. 2009;106(1):3–7. Epub 2009/04/17. 10.1016/j.ijgo.2009.03.040 [DOI] [PubMed] [Google Scholar]
- 44.Christian P, Stewart CP, LeClerq SC, Wu L, Katz J, West KP Jr., et al. Antenatal and postnatal iron supplementation and childhood mortality in rural Nepal: a prospective follow-up in a randomized, controlled community trial. Am J Epidemiol. 2009;170(9):1127–36. Epub 2009/09/26. 10.1093/aje/kwp253 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Smith ER, Shankar AH, Wu LS, Aboud S, Adu-Afarwuah S, Ali H, et al. Modifiers of the effect of maternal multiple micronutrient supplementation on stillbirth, birth outcomes, and infant mortality: a meta-analysis of individual patient data from 17 randomised trials in low-income and middle-income countries. Lancet Glob Health. 2017;5(11):e1090–e100. Epub 2017/10/14. 10.1016/S2214-109X(17)30371-6 [DOI] [PubMed] [Google Scholar]
- 46.West KP Jr., Shamim AA, Mehra S, Labrique AB, Ali H, Shaikh S, et al. Effect of maternal multiple micronutrient vs iron-folic acid supplementation on infant mortality and adverse birth outcomes in rural Bangladesh: the JiVitA-3 randomized trial. JAMA. 2014;312(24):2649–58. Epub 2014/12/24. 10.1001/jama.2014.16819 [DOI] [PubMed] [Google Scholar]
- 47.Blencowe H, Cousens S, Oestergaard MZ, Chou D, Moller AB, Narwal R, et al. National, regional, and worldwide estimates of preterm birth rates in the year 2010 with time trends since 1990 for selected countries: a systematic analysis and implications. Lancet. 2012;379(9832):2162–72. Epub 2012/06/12. 10.1016/S0140-6736(12)60820-4 [DOI] [PubMed] [Google Scholar]
- 48.Fall CH, Fisher DJ, Osmond C, Margetts BM. Multiple micronutrient supplementation during pregnancy in low-income countries: a meta-analysis of effects on birth size and length of gestation. Food Nutr Bull. 2009;30(4 Suppl):S533–46. Epub 2010/02/04. 10.1177/15648265090304S408 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Bhutta ZA, Rizvi A, Raza F, Hotwani S, Zaidi S, Moazzam Hossain S, et al. A comparative evaluation of multiple micronutrient and iron-folic acid supplementation during pregnancy in Pakistan: impact on pregnancy outcomes. Food Nutr Bull. 2009;30(4 Suppl):S496–505. Epub 2010/02/04. 10.1177/15648265090304S404 [DOI] [PubMed] [Google Scholar]
- 50.Tofail F, Persson LA, El Arifeen S, Hamadani JD, Mehrin F, Ridout D, et al. Effects of prenatal food and micronutrient supplementation on infant development: a randomized trial from the Maternal and Infant Nutrition Interventions, Matlab (MINIMat) study. Am J Clin Nutr. 2008;87(3):704–11. Epub 2008/03/11. 10.1093/ajcn/87.3.704 [DOI] [PubMed] [Google Scholar]
- 51.Osrin D, Vaidya A, Shrestha Y, Baniya RB, Manandhar DS, Adhikari RK, et al. Effects of antenatal multiple micronutrient supplementation on birthweight and gestational duration in Nepal: double-blind, randomised controlled trial. Lancet. 2005;365(9463):955–62. Epub 2005/03/16. 10.1016/S0140-6736(05)71084-9 [DOI] [PubMed] [Google Scholar]
- 52.Mridha MK, Matias SL, Chaparro CM, Paul RR, Hussain S, Vosti SA, et al. Lipid-based nutrient supplements for pregnant women reduce newborn stunting in a cluster-randomized controlled effectiveness trial in Bangladesh. Am J Clin Nutr. 2016;103(1):236–49. Epub 2015/11/27. 10.3945/ajcn.115.111336 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Imdad A, Bhutta ZA. Maternal nutrition and birth outcomes: effect of balanced protein-energy supplementation. Paediatr Perinat Epidemiol. 2012;26 Suppl 1:178–90. Epub 2012/07/07. [DOI] [PubMed] [Google Scholar]
- 54.Stevens B, Buettner P, Watt K, Clough A, Brimblecombe J, Judd J. The effect of balanced protein energy supplementation in undernourished pregnant women and child physical growth in low- and middle-income countries: a systematic review and meta-analysis. Matern Child Nutr. 2015;11(4):415–32. Epub 2015/04/11. 10.1111/mcn.12183 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Chen LW, Tint MT, Fortier MV, Aris IM, Bernard JY, Colega M, et al. Maternal macronutrient intake during pregnancy is associated with neonatal abdominal adiposity: The Growing Up in Singapore Towards healthy Outcomes (GUSTO) Study. J Nutr. 2016;146(8):1571–9. Epub 2016/07/08. 10.3945/jn.116.230730 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56.Fenske N, Burns J, Hothorn T, Rehfuess EA. Understanding child stunting in India: a comprehensive analysis of socio-economic, nutritional and environmental determinants using additive quantile regression. PLoS One. 2013;8(11):e78692 Epub 2013/11/14. 10.1371/journal.pone.0078692 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
All relevant data are available via ‘NICHD’s Data and Specimen Hub (DASH): https://dash.nichd.nih.gov/study/228833.