Periconceptional multiple-micronutrient supplementation and placental function in rural Gambian women: A double-blind, randomized, placebo-controlled trial

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Study Justification:
The study aimed to investigate the effect of periconceptional multiple-micronutrient supplementation (MMS) on placental function in rural Gambian women. Maternal micronutrient deficiencies are known to be associated with placental dysfunction, so the study aimed to determine if MMS could improve placental function.
Highlights:
– The study was a double-blind, randomized, placebo-controlled trial.
– The primary outcomes measured were midgestational indexes of utero-placental vascular-endothelial function and placental active transport capacity at delivery.
– The study found that periconceptional MMS had a small but significant effect on placental vascular function, as measured by the uterine-artery resistance index.
– However, MMS did not have a significant effect on other variables of placental function.
Recommendations:
Based on the study findings, it is recommended that periconceptional multiple-micronutrient supplementation be considered as a potential intervention to improve placental vascular function. However, further research is needed to determine the long-term effects and potential benefits of MMS on other aspects of placental function.
Key Role Players:
– Researchers and scientists involved in conducting the study
– Medical professionals and healthcare providers involved in implementing the recommendations
– Policy makers and government officials responsible for implementing public health interventions
Cost Items for Planning Recommendations:
– Costs associated with producing and distributing the multiple-micronutrient supplement
– Costs of training healthcare providers on the use and administration of the supplement
– Costs of monitoring and evaluating the implementation of the intervention
– Costs of public health campaigns and education materials to raise awareness about the benefits of periconceptional multiple-micronutrient supplementation
Please note that the cost items provided are general examples and may vary depending on the specific context and implementation strategy.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is based on a double-blind, randomized, placebo-controlled trial with a large sample size. However, the primary outcome measures did not show significant differences between the treatment and placebo groups, except for a small reduction in uterine-artery resistance index. To improve the evidence, future studies could consider increasing the sample size, conducting longer follow-up periods, and including additional outcome measures related to placental function.

Background: Maternal micronutrient deficiencies are commonly associated with clinical indicators of placental dysfunction. Objective: We tested the hypothesis that periconceptional multiplemicronutrient supplementation (MMS) affects placental function. Design: We conducted a double-blind, randomized, placebo-controlled trial of MMS in 17- to 45-y-old Gambian women who were menstruating regularly and within the previous 3 mo. Eligible subjects were pre- randomly assigned to supplementation with the UNICEF/WHO/United Nations University multiple micronutrient preparation (UNIMMAP) or placebo on recruitment and until they reached their first antenatal checkup or for 1 y if they failed to conceive. Primary outcome measures were midgestational indexes of utero-placental vascular-endothelial function [ratio of plasminogen-activator inhibitor (PAI) 1 to PAI-2 and mean uterine-artery resistance index (UtARI)] and placental active transport capacity at delivery [fetal to maternal measles antibody (MMA) ratio]. Results: We recruited 1156 women who yielded 415 pregnancies, of which 376 met all of the inclusion criteria. With adjustment for gestational age at sampling, there were no differences in PAI-1 to PAI-2 or MMA ratios between trial arms, but there was a 0.02-unit reduction in UtARI between 18 and 32 wk of gestation (95% CI: 20.03, 20.00; P = 0.040) in women taking UNIMMAP. Conclusions: Placental vascular function was modifiable by periconceptional micronutrient supplementation. However, the effect was small and supplementation did not further affect other variables of placental function. This trial was registered at www.controlled-trials. com as ISRCTN 13687662.

The study was a double-blind, randomized, placebo-controlled trial of periconceptional MMS assessed on 3 primary outcomes. The first was the ratio of maternal plasminogen activation inhibitor (PAI) 1 (a marker of endothelial activation) to PAI-2 (a marker of placental function) at 18–22 wk of gestation (13). In a healthy pregnancy, the concentrations of both biomarkers should increase progressively, but their ratio should decline as placental mass, and PAI-2 production, increases (14). The second primary outcome was uterine-artery Doppler waveform at 18–22 wk of gestation [a surrogate marker of placental perfusion that correlates with trophoblast invasion (15)]. The uterine-artery pulsatility index (UtAPI) and uterine-artery resistance index (UtARI) were also measured at 28–32 wk of gestation, and diastolic notching was noted. These indexes quantify systolic and diastolic components of the flow velocity waveform in a specific blood vessel over a single cardiac cycle. The higher the values, the greater the downstream vascular resistance. The third primary outcome was the ratio of the delivery concentrations of fetal to maternal measles antibody (MMA), which was used as a proxy marker of placental transport capacity. The micronutrient supplement (Lomapharm) was a coated tablet containing 15 vitamins and trace elements, formulated to a composition specified by the UNICEF/WHO/United Nations University (UNICEF/WHO/UNU) for use by pregnant women in the developing world and known as the UNICEF/WHO/UNU international multiple micronutrient preparation (UNIMMAP) (16). UNIMMAP contains the following: vitamin A (800 retinol equivalents), vitamin D (200 IU), vitamin E (10 mg), vitamin C (70 mg), thiamin (1.4 mg), riboflavin (1.4 mg), niacin (18 mg), pyridoxine (1.9 mg), cobalamin (2.6 mg), folic acid (400 μg), iron (30 mg), zinc (15 mg), copper (2 mg), selenium (65 μg), and iodine (150 μg). The placebo was manufactured to be indistinguishable from the supplement (Lomapharm). The study took place between March 2006 and June 2008 in the Kiang West region of The Gambia among 33 villages under demographic surveillance by the United Kingdom Medical Research Council (MRC) field station staff at Keneba. Kiang West comprises 750 km2 of savannah scrub and is bordered on 3 sides by the River Gambia and its tributaries and on the fourth by a partially surfaced road. The population consists of ∼14,000 individuals, predominantly ethnic Mandinka, who live by subsistence farming. Nutritional status and morbidity patterns in this community have been well described and are largely defined by a distinct tropical seasonality, with a long dry season from November to June followed by a period of intense and daily rainfall between July and October (17–19). Local HIV seroprevalence at the time of the study was ∼1% (20). In this area, the incidence of low birth weight was 13%, PTB was 12%, and 25% of newborns were small for gestational age (<10th centile weight for gestational age) with FGR (18). Local maternal and child primary health care is provided by government nurse trekking teams, supported by the clinical staff of MRC Keneba. Most women deliver at home under the supervision of traditional birth attendants (TBAs) who undergo basic training in clean birth practices and recognition of common pregnancy complications (21). Secondary and tertiary health care services are provided at the Royal Victoria Teaching Hospital (RVTH) in Banjul, which is 4 h by road from Keneba. Women aged 17–45 y and residing in Kiang West during the recruitment phase of the study and who were registered in the MRC Keneba demographic database and not concurrently enrolled in other intervention studies were eligible to take part in the trial. Eligible women (and their guardians for those <18 y old) were invited to attend a recruitment clinic in their home villages. They were provided with oral and printed study information by a nurse-midwife (NM) and asked to give written consent if they wished to take part. Those who used no contraception, were not known to be pregnant, and had experienced menses in the past 3 mo and were not breastfeeding were included. Those who were severely anemic (hemoglobin concentration 24 wk of gestation at booking could not be accurately dated by ultrasound and were dated by maternally recalled last menstrual period (LMP). Because maternally recalled LMP is imprecise in this population (24), a restricted analysis of delivery outcomes alone was used for this subgroup. At ANC booking, a 5-mL blood sample was drawn and analyzed for hemoglobin concentration, presence of malaria parasites, and syphilis serology. As required by the Gambian Government Ethics Committee, each subject was offered serologic testing for HIV, with pre- and posttest counseling. HIV-positive participants were referred to the MRC HIV clinical service in Fajara. Women who delivered before attendance at the HIV clinic were offered maternal and infant nevirapine prophylaxis, in keeping with the national guideline at the time. An uncuffed 10-mL venous blood sample was drawn at the 18–22-wk and 28–32-wk review. Aliquots were prepared, stored, and analyzed within 1 h of venipuncture, as described for recruitment samples, except for ferritin concentration, which was not measured at 18–22 wk. Additional aliquots of chilled citrate-plasma aliquot and serum were analyzed for PAI-1 and PAI-2 concentrations and placental hormones [human prolactin (hPL) and human chorionic gonadotropin (hCG)], respectively. The subject was given directly observed intermittent preventative treatment with sulfadoxine-pyrimethamine at 18–22 wk and 28–32 wk. TBAs reported impending deliveries to their local resident fieldworker. A 10-mL cord blood sample taken from a large vein on the fetal side of the placenta of live-born infants. The placenta was transported as soon as it was collected to MRC Keneba, cleaned, the membranes trimmed, and the cord cut close to its insertion. Placental weight was recorded to the nearest 10 g by using a digital balance. Cord serum and whole-blood aliquots were prepared. The concentration of cord serum MMA was measured. Whole blood was analyzed for hematologic variables and the presence of malaria parasites. Within 72 h of delivery, an NM examined the mother and infant. Maternal weight, MUAC, urinalysis, and blood pressure were recorded. An uncuffed 10-mL venous blood sample was drawn from the mother and aliquots prepared and analyzed as for the cord samples. Neonatal anthropometric measurements were recorded. Dubowitz scoring was conducted to improve the detection of preterm infants, as part of standard clinical risk assessment. Maternal height, weight, MUAC, and blood pressure were measured by pairs of fieldworkers at recruitment and by 1 of 2 NMs at scheduled antenatal visits and at delivery. Standard techniques were used for each measurement. Weight was measured (to the nearest 0.1 kg) by using daily calibrated, digital scales (Tanita Corporation). Height (to the nearest 0.1 cm) was measured by using a daily calibrated stadiometer (Leicester height measure; Seca) and BMI was estimated [weight (kg)/height (m)2]. Underweight was defined as a BMI (in kg/m2) 139 mm Hg or diastolic blood pressure >89 mm Hg. Neonatal anthropometric measurements were performed by 1 of 2 NMs. Birth weights were measured (to the nearest 20 g) with sling and portable spring balances (CMS Weighing Equipment), and these were regularly checked with standard weights. Birth length (to the nearest 5 mm) was measured by using neonatal length mats (TALC Teaching Aids). Head circumference (to the nearest mm) was measured with graduated tapes (Henley Medical Supplies). Fieldworkers and NMs were trained and cross-compared in anthropometric techniques as part of their employment induction with the MRC, which was repeated at the start of this study. Refresher training was undertaken regularly. Hemoglobin measurements at pregnancy booking used a hemoglobinometer (HemoCue B). Analyses on venipuncture samples included hemoglobin concentration, white blood cell count, mean cell volume, mean cell hemoglobin, and reticulocyte count (Cel-Dyn 3700 Analyzer; Abbott Diagnostics). Anemia was defined as hemoglobin <12 g/dL in nonpregnant women and <11 g/dL in pregnant women. Malaria blood films were prepared and stained with Giemsa stain, and 100 high-power microscopic fields were examined to determine parasite count against 200 white blood cells. PAI-1 and PAI-2 antigen concentrations were measured with mouse-monoclonal antibody–based ELISAs (Elitest; Hyphen-BioMed) as was MMA in maternal and fetal blood (IBL International), hPL, and hCG (Addenbrookes Hospital). Vitamins A and E were measured by HPLC (25). Vitamin A deficiency was defined as a serum retinol concentration <0.7 μmol/L and vitamin E deficiency as a serum α-tocopherol concentration <12 μmol/L. Ferritin was measured by instrumental immunoassay (Dimension Xp; Siemens). Iron deficiency was defined as a plasma ferritin concentration 0.55 and bilateral notching, or a mean UtARI >0.65 and unilateral notching, were defined as “high resistance” waveforms (26). Women with high-resistance waveforms were monitored for pre-eclampsia and/or FGR and, if necessary, referred to RVTH. Intraobserver variation in sonographic variables was not estimated. We estimated that a sample of 200 women in each arm of the trial would generate 90% power to detect a 20% difference in the mean PAI-1 to PAI-2 ratio at 18–22 wk of gestation between supplementation groups at a 5% level of significance. This was based on variance parameters (population mean ratio: 0.40; SD: 0.23) drawn from a trial of antioxidant vitamin supplementation in British women at risk of pre-eclampsia (27) and allowed for 10% loss to follow-up. This sample size had 90% power to detect a change in mean UtARI equivalent to 0.35 SDs at the 5% significance level [assuming a mean UtARI of 0.30; SD: 0.01 (26)]. To detect a difference in mean MMA transplacental transfer ratio of 0.1, with 90% power at the 5% level of significance, ∼80 mother-infant pairs were required in each arm of the trial, assuming a mean transfer ratio of 1.01 and an SD of 0.18 (28). It was considered that this sample size would be readily available within the main pregnancy cohort. On the basis of MRC Keneba demographic survey data, we assumed that 16% of women aged between 17 and 45 y in this community would conceive in any given year. This suggested that at least 2400 women would be required over the course of the study to satisfy the largest estimate of required sample size, 400 pregnancies. We identified 3206 eligible subjects in the survey. Data were double-entered into a computerized database (MS-Access; Microsoft) and verified within 48 h of collection. Scheduled data validation checks were made. A copy of the raw data set was maintained with the MRC data management team. All available data on singleton pregnancies without fetal anomalies were included and analyzed according to the original randomization. Every effort was made to complete the data set for each subject, but specific outcomes on individual subjects were occasionally unavailable (e.g., on women who had withdrawn their consent, migrated out of the study area, or otherwise failed to attend within the predefined timeframe of a particular endpoint). In these cases, the remaining data were included in all other analyses. Continuous data were analyzed by using linear regression, assuming equal variance. Outcomes were regressed on a single predictor, trial arm. To improve the precision of primary analyses, multiple regression was used to adjust for the effects of gestational age at point of sampling, because gestational age is an a priori predictor of all pregnancy outcomes. Evidence for interaction between treatment effect and gestational age at point of sampling was also sought for primary outcome measures. Continuous data that were not normally distributed were log-transformed before analyses of their geometric means. Those that were not rendered normally distributed by this transformation were analyzed by using nonparametric tests. Binary responses were analyzed by logistic regression. Data collected on the same individuals at ≥2 time points were analyzed by using random-effects models fitted by generalized least squares. Although the study was not powered for subgroup analyses, we went on to assess treatment effects on the primary outcomes by season of conception (wet-hungry compared with dry-harvest) by fitting a season × treatment interaction term into the models. This stratification was justified as an exploratory analysis on the basis of previous data showing that PTB and small-for-gestational-age birth show strongly divergent patterns of seasonality in Kiang West (18). Significance was set at P 140 mm Hg or a diastolic blood pressure >90 mm Hg in a previously normotensive woman, in conjunction with dipstick proteinuria. Women with pre-eclampsia were referred to RVTH for further management. This trial was approved by the Scientific Coordinating Committee of MRC Laboratories, The Gambia, and by the MRC/Gambian Government Ethics Committee (L2005.111v2 SCC 1000). An independent trial monitor and data safety and monitoring board assessed trial activity at regular intervals, under the auspices of Good Clinical Practice guidelines (29). MRC Keneba offers free primary health care in collaboration with the Gambian Government Lower River Divisional Health Team. Apart from the structured clinical contacts outlined (during which subjects were given transport and a meal), no additional benefits were provided to trial participants. The trial was registered as ISRCTN 13687662 (www.controlled-trials.com/isrctn/pf/13687662).

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The study described is a double-blind, randomized, placebo-controlled trial that investigated the effects of periconceptional multiple-micronutrient supplementation (MMS) on placental function in rural Gambian women. The primary outcomes measured were the ratio of plasminogen-activator inhibitor (PAI) 1 to PAI-2, mean uterine-artery resistance index (UtARI), and fetal to maternal measles antibody (MMA) ratio.

The study found that periconceptional MMS had a small effect on placental vascular function, as indicated by a reduction in UtARI between 18 and 32 weeks of gestation. However, there were no significant differences in the PAI-1 to PAI-2 ratio or MMA ratios between the supplementation and placebo groups.

Based on the findings of this study, potential innovations to improve access to maternal health could include:

1. Development of targeted periconceptional MMS interventions: Further research could focus on developing more targeted interventions that specifically address placental vascular function and other variables of placental function. This could involve identifying specific micronutrients or combinations of micronutrients that have a greater impact on placental health.

2. Integration of MMS into existing maternal health programs: MMS interventions could be integrated into existing maternal health programs to improve access and reach a larger population of women. This could involve providing MMS supplements as part of routine antenatal care or incorporating them into existing nutrition programs.

3. Community-based education and awareness programs: Community-based education and awareness programs could be implemented to increase knowledge and understanding of the importance of periconceptional nutrition and MMS. These programs could target women of reproductive age, their families, and healthcare providers to promote the adoption of healthy nutrition practices and the use of MMS supplements.

4. Strengthening healthcare infrastructure and services: Improving access to maternal health requires a strong healthcare infrastructure and services. This could involve increasing the availability of skilled healthcare providers, improving transportation and communication systems, and ensuring the availability of essential maternal health supplies and equipment.

5. Research and innovation in delivery mechanisms: Research and innovation could focus on developing new delivery mechanisms for MMS supplements that are more convenient, cost-effective, and sustainable. This could include exploring options such as fortified foods, micronutrient powders, or other innovative delivery methods.

It is important to note that these recommendations are based on the findings of the specific study described and may need to be further evaluated and adapted to different contexts and populations.
AI Innovations Description
The study described is a double-blind, randomized, placebo-controlled trial that investigated the effects of periconceptional multiple-micronutrient supplementation (MMS) on placental function in Gambian women. The primary outcomes measured were the ratio of plasminogen-activator inhibitor (PAI) 1 to PAI-2, mean uterine-artery resistance index (UtARI), and fetal to maternal measles antibody (MMA) ratio.

The results of the study showed that periconceptional MMS had a small effect on placental vascular function, as indicated by a reduction in UtARI between 18 and 32 weeks of gestation. However, there were no significant differences in the PAI-1 to PAI-2 ratio or MMA ratios between the supplementation and placebo groups.

Based on these findings, a recommendation to improve access to maternal health could be to promote and provide periconceptional multiple-micronutrient supplementation to women in areas with limited access to healthcare. This could be done through community-based programs, antenatal clinics, and outreach initiatives. By ensuring that women have access to essential micronutrients during the periconceptional period, it may be possible to improve placental function and ultimately enhance maternal and fetal health outcomes.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations for improving access to maternal health:

1. Increase availability and accessibility of periconceptional multiple-micronutrient supplementation (MMS) in rural areas: This can be done by ensuring that MMS is readily available in health facilities and clinics in rural areas, and by implementing outreach programs to reach women who may not have easy access to healthcare facilities.

2. Improve antenatal care services: Enhancing antenatal care services can help identify and address maternal health issues early on. This can include regular check-ups, screenings, and education on proper nutrition and supplementation during pregnancy.

3. Strengthen community health worker programs: Community health workers can play a crucial role in improving access to maternal health services, especially in remote areas. Training and supporting community health workers can help ensure that pregnant women receive the necessary care and support throughout their pregnancy.

4. Implement mobile health (mHealth) interventions: Utilizing mobile technology can help bridge the gap in access to maternal health services. Mobile apps and text messaging can be used to provide information, reminders, and support to pregnant women, even in areas with limited healthcare infrastructure.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could include the following steps:

1. Define the indicators: Identify specific indicators that measure access to maternal health, such as the number of women receiving periconceptional MMS, the number of antenatal care visits, or the percentage of pregnant women reached through community health worker programs.

2. Collect baseline data: Gather data on the current status of these indicators in the target population or area. This can be done through surveys, interviews, or existing data sources.

3. Define the intervention: Specify the details of the recommended interventions, such as the number of health facilities offering MMS, the frequency and content of antenatal care visits, or the number of trained community health workers.

4. Simulate the impact: Use statistical modeling or simulation techniques to estimate the potential impact of the interventions on the defined indicators. This can involve projecting the changes in the indicators based on the assumed effectiveness and coverage of the interventions.

5. Evaluate the results: Analyze the simulated impact to assess the potential improvements in access to maternal health. Compare the projected indicators with the baseline data to determine the effectiveness of the recommendations.

6. Refine and adjust: Based on the evaluation results, refine the interventions and simulation methodology as needed. Iterate the process to further optimize the recommendations and improve access to maternal health.

It’s important to note that the specific methodology for simulating the impact may vary depending on the available data, resources, and context. Consulting with experts in the field of maternal health and utilizing appropriate statistical and modeling techniques can help ensure the accuracy and reliability of the simulation results.

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