Maternal cortisol and stress are associated with birth outcomes, but are not affected by lipid-based nutrient supplements during pregnancy: An analysis of data from a randomized controlled trial in rural Malawi

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Study Justification:
This study aimed to investigate the association between maternal cortisol concentration and stress during pregnancy with birth outcomes, specifically gestation duration and size at birth. The study also aimed to determine if lipid-based nutrient supplements (LNS) given during pregnancy would affect cortisol concentration. Understanding these relationships is important for improving maternal and child health outcomes.
Highlights:
– The study enrolled 1391 pregnant women in rural Malawi and collected saliva samples at baseline, 28 weeks, and 36 weeks gestation.
– There were no significant differences in cortisol concentrations between women who received LNS, multiple micronutrient (MMN), or iron-folic acid (IFA) supplements.
– Cortisol concentrations were negatively associated with gestation duration and birth weight, but not with length-for-age or head circumference-for-age z-scores.
– Perceived stress at 36 weeks was significantly associated with shorter newborn length-for-age z-scores.
– There were no significant associations with the risk of small for gestational age, preterm birth, or low birth weight.
Recommendations:
Based on the study findings, the following recommendations can be made:
1. Further research should be conducted to explore the mechanisms by which cortisol and stress during pregnancy affect birth outcomes.
2. Interventions to reduce maternal stress during pregnancy should be developed and implemented to improve birth outcomes.
3. The effectiveness of lipid-based nutrient supplements in improving birth outcomes should be further investigated.
Key Role Players:
To address the recommendations, the following key role players are needed:
1. Researchers and scientists to conduct further studies on the mechanisms and interventions related to cortisol, stress, and birth outcomes.
2. Healthcare providers and policymakers to implement interventions to reduce maternal stress during pregnancy.
3. Funding agencies to support research and implementation of interventions.
Cost Items:
While the actual cost of implementing the recommendations cannot be estimated without detailed planning, the following budget items should be considered:
1. Research funding for further studies and data collection.
2. Training and capacity building for healthcare providers on stress reduction interventions.
3. Implementation costs for interventions, such as counseling services or support programs for pregnant women.
4. Monitoring and evaluation costs to assess the effectiveness of interventions and measure outcomes.
Please note that the above information is based on the provided study description and publication.

The strength of evidence for this abstract is 6 out of 10.
The evidence in the abstract is moderately strong, but there are some areas for improvement. The study design is a randomized controlled trial, which is a strong design for evaluating interventions. The sample size is large, which increases the reliability of the findings. However, the abstract does not provide information on the statistical significance of the associations reported, which makes it difficult to fully evaluate the strength of the evidence. Additionally, the abstract does not provide information on potential confounding factors that were controlled for in the analysis, which could affect the validity of the results. To improve the evidence, it would be helpful to include p-values for the associations reported and provide a more detailed description of the covariates included in the analysis.

Background: Prenatal micronutrient supplements have been found to increase birth weight, but mechanisms for increased growth are poorly understood. Our hypotheses were that 1) women who receive lipid-based nutrient supplements (LNS) during pregnancy would have lower mean salivary cortisol concentration at 28 wk and 36 wk gestation compared to the multiple micronutrient (MMN) and iron-folic acid (IFA) supplement groups and 2) both salivary cortisol and perceived stress during pregnancy would be associated with shorter duration of gestation and smaller size at birth. Methods: Women were enrolled in the trial in early pregnancy and randomized to receive LNS, MMN, or iron-folic acid (IFA) supplements daily throughout pregnancy. At enrollment, 28 wk and 36 wk gestation, saliva samples were collected and their cortisol concentration was measured. Self-report of perceived stress was measured using questionnaires. Gestation duration was indicated by ultrasound dating and newborn anthropometric measurements (weight, length, head circumference) provided indicators of intrauterine growth. Results: Of the 1391 women enrolled in the trial, 1372, 906 and 1049 saliva samples were collected from women at baseline, 28 wk and 36 wk, respectively. There were no significant differences in mean cortisol concentrations by intervention group at 28 wk or 36 wk gestation. Cortisol concentrations were negatively associated with duration of gestation (Baseline: β = -0.05, p = 0.039; 36 wk: β = -0.04, p = 0.037) and birth weight (28 wk: β = -0.08, p = 0.035; 36 wk: β = -0.11, p = 0.003) but not associated with length-for-age or head circumference-for-age z-scores. Perceived stress at 36 wk was significantly associated with shorter newborn LAZ (p = 0.001). There were no significant associations with the risk of small for gestational age, preterm birth, or low birth weight. Conclusions: Maternal salivary cortisol concentration was strongly associated with birth weight and duration of gestation in rural Malawi, but these data do not support the hypothesis that LNS provision to pregnant women would influence their salivary cortisol concentrations. Trial registration: Clinicaltrials.gov identifier NCT01239693.

To evaluate these questions, we nested a substudy within the iLiNS trial in Malawi. Details of the overall study design methods and primary outcome results have been published previously [15]. In brief, the target population included pregnant women attending antenatal care through one of four hospitals or health facilities in Mangochi District in southern Malawi. Inclusion criteria were as follows: ≤20 wk gestation confirmed by ultrasound, residence in the defined catchment area, availability during the period of the study, and signed or thumb-printed informed consent. Exclusion criteria were: age <15 years old, need for medical attention due to a chronic or severe illness, diagnosed and medically treated asthma, history of peanut allergy, history of anaphylaxis or serious allergic reaction to any substance, pregnancy complications evident at enrolment visit (moderate to severe edema, blood Hb concentration  160 mmHg or diastolic BP > 100 mmHg), earlier participation in the trial during to a previous pregnancy or concurrent participation in any other clinical trial. A statistician independent of the research group generated randomization codes by creating four unique lists (one for each enrollment site) in blocks of nine (3 codes for each of the 3 interventions). The codes were inserted into individual opaque envelopes and eligible participants selected one from a shuffled stack of 6 envelopes. This code determined both the participant’s group allocation as well as her identification number. Based on their randomization code, women received one of three supplements to be consumed daily throughout pregnancy: 1) small quantity LNS; 2) MMN; or 3) IFA. The nutrient content for each of the supplements can be found in Table 1. Data collectors delivered supplements every two weeks to participants and they advised women to consume the supplements daily either after a meal (IFA or MMN groups) or mixed with a meal (LNS). Data collectors monitored adherence at each distribution visit by counting any unused supplements from participants. Nutrient content of the supplements At enrollment, trained nurses confirmed pregnancies and gestational age estimates using ultrasound imagers (EDAN DUS 3 Digital Ultrasonic Diagnostic Imaging System, EDAN Instruments, Inc., Shekou, Nanshan Shenzhen, China). Study nurses were trained in ultrasound assessment by two study physicians and they conducted all measurements in duplicate. Anthropometrists measured in triplicate maternal height using a stadiometer (Harpenden stadiometer, Holtain Limited, Crosswell, Crymych, UK), weight using a flat scale (SECA 874 flat scale, Seca GmbH & Co., Hamburg, Germany), and mid-upper arm circumference (MUAC) using a non-stretchable tape (Weigh and Measure, LLC, Maryland, USA). Research nurses tested for malaria using rapid diagnostic tests (Clearview Malaria Combo, British Biocell International Ltd., Dundee, UK), haemoglobin concentration (HemoCue AB, Angelholm, Sweden), and HIV (Alere Determine HIV-1/2, Alere Medical Co., Ltd., Chiba, Japan). Positive HIV tests were repeated using another whole blood antibody test (Uni-Gold HIV, Trinity Biotech plc, Bray, Ireland). During a follow-up home visit, trained interviewers asked mothers about demographic and socioeconomic characteristics, including questions on household food insecurity. Mothers were asked to return to the clinic for repeat visits at 32 and 36 wk gestation. A follow-up home visit was also conducted at 28 wk gestation. At enrolment, 28 wk, and 36 wk gestation, interviewers asked women about stress during the previous month using the 10-item Perceived Stress Scale [40], a tool that has been used in other low-income settings [41, 42]. The research nurses collected saliva samples during the clinic visits at baseline and 36 wk gestation and during the 28 wk home visit between 8 am and 4 pm after a 30 minute fast. Time of collection, time of waking, and time of last food or drink were recorded by the nurse. Saliva collection occurred before any other measurements or sample collection. Nurses asked each woman to place an inert polymer cylindrical swab (Salimetrics Oral Swab) under her tongue for approximately two minutes, while moving her tongue and jaw as if she were chewing to stimulate saliva. The woman removed the swab and placed it in a capped tube and then it was refrigerated or placed on ice packs. Swabs were brought to room temperature, then centrifuged for 15 min at 3,000 RPM (1500 x g) to extract saliva, which then was frozen at −20 °C. After a maximum of 2 days, samples were transferred to a −80 °C freezer for longer term storage. Samples were shipped to Davis, CA for analysis. Lab technicians measured cortisol concentrations in duplicate using an ELISA method (expanded range high sensitivity salivary cortisol kit, Salimetrics, State College, PA), which can detect cortisol concentrations ranging from 0.193 to 82.77 nmol/L (0.007-3.0 μg/dL). The intra- and inter-assay coefficient of variability is 3.5 % and 5.1 %. The mean of each duplicate measure was used for analysis. Research nurses collected venous blood samples at baseline and 36 wk gestation using 7.5 mL trace mineral-free syringe (Sarstedt Monovette, Nh4-heparin, Sarstedt Inc., Newton, NC). Lab technicians measured zinc protoporphyrin in washed red blood cells within 30 hr of collection using a hematofluorometer (Aviv Biomedical, Lakewood, NJ). They also measured soluble transferrin receptor, c-reactive protein (CRP), and alpha-1-acid glycoprotein (AGP) by immunoturbidimetry on the Cobas Integra 400 system (F. Hoffmann-La Roche Ltd, Basel, Switzerland). Research assistants measured infants’ weight as soon as possible after birth either at home or in the health center. Of the recorded birth weights, 89 % were measured within 48 h of delivery while the remainder were back-translated from a measurement within 14 days. They also collected early neonatal measurements, including length to the nearest 1 mm using an infantometer (Harpenden Infantometer, Holtain Limited, Crosswell, Crymych, UK), weight to the nearest 10 g using an infant scale (SECA 381 baby scale, Seca GmbH & Co., Hamburg, Germany), head circumference and arm circumference using non-stretchable tape. Women provided written informed consent or indicated their consent to participate in the study with a thumbprint. In Malawi, individuals ≥15 y are able to provide consent themselves and so parental consent was not obtained. The institutional review boards at the College of Medicine Research and Ethics Committee (COMREC), University of Malawi and the Ethics Committee of Pirkanmaa Hospital District, Finland reviewed and approved the trial protocols at all of the hospitals and health facilities. Sample size estimates for the main trial were calculated to be 370 per group, based on an effect size (difference between groups divided by the pooled SD) of 0.23, assuming a two-sided α = 0.05 and β = 0.2. That would correspond to a detectable difference of 0.83 nmol/L in cortisol and a 1.2 point difference in the perceived stress score (PSS). We used standard scoring methods to calculate the PSS [40]. We checked the salivary cortisol and PSS for normality using the Shapiro-Wilk test and cortisol was log transformed. We calculated Pearson’s correlation coefficients to compare log cortisol and the PSS at each time point. We also analyzed PSS and cortisol categorically. PSS was dichotomized into high or low values using a median cut-point and cortisol concentrations were grouped into quartiles based on the distributions at each measurement point (enrolment, 28 wk, 36 wk). We used the Household Food Insecurity Access Scale [43] to estimate food insecurity and created the scores using standard criteria. An asset index was created using principal components analysis [44] based on household ownership of a set of assets (radio, television, cell phone, bed, mattress, bednet, and bicycle), lighting source, drinking water supply, sanitation facilities, and flooring materials. For all analyses, participants were included if they had non-missing data on either cortisol or the perceived stress score at any time-point. We compared characteristics for those with complete data vs. those who were missing data on cortisol at 28 wk gestation. We also compared baseline characteristics between women in each of the three intervention groups. To evaluate the effect of the nutritional interventions on cortisol and PSS, we tested group-wise differences using ANOVA and ANCOVA models, using the Tukey-Kramer adjustment for multiple comparisons, and p-values <0.05 were considered statistically significant. We considered covariates for inclusion in the model if they were significantly (p < 0.1) associated with salivary cortisol. These included baseline cortisol, age, gestational age, maternal BMI and height, season, malaria infection, HIV status, hemoglobin, iron status, inflammatory markers, household food insecurity, asset index, parity (primiparous or multiparous), infant sex, site of enrollment, and maternal PSS. We included time since waking and time since last meal in all models, regardless of their association with the outcome variables. Interaction terms were created by the cross product of the intervention group and maternal age, parity, baseline BMI, and infant gender and these were evaluated in linear regression models. Interaction term p-values <0.1 were considered to be statistically significant. To examine the associations between cortisol or PSS and birth outcomes (duration of gestation, weight-for-age z-score [WAZ], length-for-age z-score [LAZ], head circumference z-score [HCZ]), we used linear regression models and present standardized regression coefficients. We used Poisson regression models with robust estimation of the standard errors to estimate relative risk for dichotomous birth outcomes, including preterm birth (<37 wk gestation), low birth weight (<2.5 kg, LBW), stunting (LAZ < −2), small head circumference (HCZ < −2), and small for gestational age [45]. We considered covariates for inclusion into the models based on previous literature and tested as described above. Because cortisol and the inflammatory markers are likely related to each other, but the causal pathways are unclear, we have analyzed models both with and without adjustment for the two inflammation variables. Missing data were considered in two ways. We first compared baseline characteristics between those with complete data and those with missing data. Secondly, we imputed missing values [46] for 28 wk and 36 wk cortisol concentrations and re-analyzed the data as a sensitivity test on the primary models. Model assumptions were also checked using standard regression diagnostics for linearity, normality, leverage, and influence. All analyses were performed using SAS 9.3 (SAS Institute, Cary, NC).

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Based on the provided information, it appears that the study focused on evaluating the association between maternal cortisol levels, stress, and birth outcomes in rural Malawi. The study also investigated the impact of different nutrient supplements on cortisol levels during pregnancy. Here are some potential recommendations for innovations to improve access to maternal health based on this study:

1. Mobile Health (mHealth) Applications: Develop mobile applications that provide pregnant women with information and resources to manage stress during pregnancy. These apps can include stress management techniques, relaxation exercises, and educational materials on the importance of stress reduction for maternal and fetal health.

2. Community-Based Interventions: Implement community-based programs that offer support and resources for pregnant women to manage stress. These programs can include group counseling sessions, peer support networks, and access to community resources such as prenatal yoga classes or meditation groups.

3. Integration of Mental Health Services: Integrate mental health services into existing maternal health programs to address stress and mental health concerns during pregnancy. This can involve training healthcare providers to identify and address stress and mental health issues, as well as providing access to counseling or therapy services for pregnant women.

4. Targeted Nutritional Interventions: Further research and development of targeted nutritional interventions that specifically address the impact of nutrient supplements on cortisol levels and stress during pregnancy. This can involve formulating supplements with specific nutrients known to reduce stress and improve maternal health outcomes.

5. Telemedicine and Telehealth Services: Expand access to prenatal care and support through telemedicine and telehealth services. This can include virtual prenatal visits, remote monitoring of maternal health indicators, and access to online support groups or counseling services.

It is important to note that these recommendations are based on the information provided and may need to be further evaluated and tailored to the specific context and needs of the target population.
AI Innovations Description
The study mentioned in the description aims to investigate the association between maternal cortisol (a stress hormone) and birth outcomes, as well as the impact of lipid-based nutrient supplements (LNS) on cortisol levels during pregnancy. The study was conducted in rural Malawi and involved pregnant women who were randomized to receive either LNS, multiple micronutrient (MMN), or iron-folic acid (IFA) supplements throughout their pregnancy.

The results of the study showed that there were no significant differences in cortisol concentrations between the intervention groups at 28 weeks or 36 weeks gestation. However, cortisol concentrations were negatively associated with duration of gestation and birth weight, indicating that higher cortisol levels were associated with shorter gestation and lower birth weight. Perceived stress at 36 weeks was also significantly associated with shorter length-for-age z-scores in newborns.

Based on these findings, it can be recommended that interventions aimed at improving access to maternal health should focus on reducing maternal stress and cortisol levels during pregnancy. This can be achieved through various approaches, such as providing psychological support, stress management techniques, and promoting overall well-being during pregnancy. Additionally, efforts should be made to ensure access to adequate nutrition and supplementation to support healthy fetal growth and development.

It is important to note that this study specifically focused on the association between cortisol levels and birth outcomes, and did not find a significant impact of LNS on cortisol concentrations. Therefore, further research is needed to explore the potential benefits of different interventions and strategies to reduce maternal stress and improve access to maternal health.
AI Innovations Methodology
Based on the provided description, here are some potential recommendations for innovations to improve access to maternal health:

1. Mobile Health (mHealth) Applications: Develop mobile applications that provide pregnant women with access to information and resources related to maternal health. These apps can provide educational content, appointment reminders, and access to healthcare professionals through telemedicine.

2. Community Health Workers: Train and deploy community health workers to provide prenatal care and education to pregnant women in rural areas. These workers can conduct regular check-ups, provide guidance on nutrition and healthy behaviors, and refer women to healthcare facilities when necessary.

3. Telemedicine: Establish telemedicine services to connect pregnant women in remote areas with healthcare professionals. This can enable remote consultations, monitoring of vital signs, and timely medical advice, reducing the need for women to travel long distances for routine check-ups.

4. Maternal Health Vouchers: Implement voucher programs that provide pregnant women with financial assistance to access maternal health services. These vouchers can cover the cost of prenatal care, delivery, and postnatal care, ensuring that women can afford the necessary healthcare services.

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

1. Define the target population: Identify the specific group of pregnant women who would benefit from the innovations, such as women in rural areas with limited access to healthcare facilities.

2. Collect baseline data: Gather information on the current state of maternal health access in the target population, including factors such as distance to healthcare facilities, availability of healthcare professionals, and utilization of prenatal care services.

3. Define indicators: Determine key indicators to measure the impact of the innovations, such as the number of prenatal care visits, rates of complications during pregnancy and childbirth, and maternal and infant mortality rates.

4. Develop a simulation model: Create a mathematical model that simulates the impact of the innovations on the defined indicators. This model should take into account factors such as the reach and effectiveness of the innovations, as well as the existing healthcare infrastructure and resources.

5. Input data and run simulations: Input the baseline data into the simulation model and run multiple simulations to assess the potential impact of the innovations on the defined indicators. Vary the parameters of the innovations, such as the coverage and utilization rates, to explore different scenarios.

6. Analyze results: Analyze the results of the simulations to determine the potential impact of the innovations on improving access to maternal health. Assess the changes in the defined indicators and compare them to the baseline data to evaluate the effectiveness of the innovations.

7. Refine and iterate: Based on the results of the simulations, refine the parameters of the innovations and rerun the simulations to further optimize their impact. Iterate this process until the desired level of improvement in access to maternal health is achieved.

It is important to note that this methodology is a general framework and the specific details and data requirements may vary depending on the context and scope of the simulation.

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