Maternal aflatoxin exposure during pregnancy and adverse birth outcomes in Uganda

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Study Justification:
– Aflatoxins are toxic metabolites found in food, particularly in low- and middle-income countries.
– Previous research has shown that exposure to aflatoxin B1 (AFB1) during pregnancy can negatively impact child growth and development.
– This study aimed to investigate the association between maternal aflatoxin exposure during pregnancy and adverse birth outcomes, specifically lower birth weight, in a sample of mother-infant pairs in Uganda.
Study Highlights:
– The study was conducted in Mukono district, Uganda, from February to November 2017.
– A total of 220 mother-infant pairs were included in the analysis.
– Maternal aflatoxin exposure was assessed by measuring the serum concentration of AFB1-lysine (AFB-Lys) adduct at 17.8 ± 3.5 weeks gestation using high-performance liquid chromatography.
– Birth outcome characteristics, including weight, head circumference, and z-scores, were obtained within 48 hours of delivery.
– The study found that higher maternal AFB-Lys levels were significantly associated with lower birth weight, lower weight-for-age z-score, smaller head circumference, and lower head circumference-for-age z-score in infants at birth.
– These findings suggest an association between maternal aflatoxin exposure during pregnancy and adverse birth outcomes, particularly lower birth weight and smaller head circumference.
Recommendations for Lay Reader:
– Pregnant women should be aware of the potential risks of aflatoxin exposure on their baby’s health.
– Measures should be taken to reduce aflatoxin contamination in the food supply, especially in low- and middle-income countries.
– Further research is needed to better understand the mechanisms behind the association between aflatoxin exposure and adverse birth outcomes.
Recommendations for Policy Maker:
– Implement policies and regulations to monitor and control aflatoxin contamination in the food supply.
– Provide education and awareness programs for pregnant women about the risks of aflatoxin exposure and ways to minimize it.
– Allocate resources for further research to explore the long-term effects of aflatoxin exposure on child growth and development.
Key Role Players:
– Researchers and scientists specializing in food safety and public health.
– Government officials and policymakers responsible for food safety regulations.
– Healthcare professionals, including obstetricians and midwives, who can educate and counsel pregnant women about aflatoxin exposure.
Cost Items for Planning Recommendations:
– Research funding for further studies on aflatoxin exposure and its effects on birth outcomes.
– Resources for monitoring and controlling aflatoxin contamination in the food supply.
– Budget for education and awareness programs targeting pregnant women.
– Funding for training healthcare professionals on aflatoxin-related risks and prevention strategies.

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong, but there are some areas for improvement. The study design is a prospective cohort study, which is generally considered to provide reliable evidence. The sample size of 220 mother-infant pairs is adequate for detecting associations. The statistical analysis includes adjustment for confounding factors. The results show significant associations between maternal aflatoxin exposure and adverse birth outcomes. However, there are no details provided about the representativeness of the sample or the generalizability of the findings. Additionally, the abstract does not mention any limitations of the study. To improve the evidence, it would be helpful to provide information about the representativeness of the sample and any limitations of the study. This would enhance the transparency and reliability of the findings.

Aflatoxins are toxic metabolites of Aspergillus moulds and are widespread in the food supply, particularly in low- and middle-income countries. Both in utero and infant exposure to aflatoxin B 1 (AFB 1 ) have been linked to poor child growth and development. The objective of this prospective cohort study was to investigate the association between maternal aflatoxin exposure during pregnancy and adverse birth outcomes, primarily lower birth weight, in a sample of 220 mother–infant pairs in Mukono district, Uganda. Maternal aflatoxin exposure was assessed by measuring the serum concentration of AFB 1 -lysine (AFB-Lys) adduct at 17.8 ± 3.5 (mean ± SD)-week gestation using high-performance liquid chromatography. Anthropometry and birth outcome characteristics were obtained within 48 hr of delivery. Associations between maternal aflatoxin exposure and birth outcomes were assessed using multivariable linear regression models adjusted for confounding factors. Median maternal AFB-Lys level was 5.83 pg/mg albumin (range: 0.71–95.60 pg/mg albumin, interquartile range: 3.53–9.62 pg/mg albumin). In adjusted linear regression models, elevations in maternal AFB-Lys levels were significantly associated with lower weight (adj-β: 0.07; 95% CI: −0.13, −0.003; p = 0.040), lower weight-for-age z-score (adj-β: −0.16; 95% CI: −0.30, −0.01; p = 0.037), smaller head circumference (adj-β: −0.26; 95% CI: −0.49, −0.02; p = 0.035), and lower head circumference-for-age z-score (adj-β: −0.23; 95% CI: −0.43, −0.03; p = 0.023) in infants at birth. Overall, our data suggest an association between maternal aflatoxin exposure during pregnancy and adverse birth outcomes, particularly lower birth weight and smaller head circumference, but further research is warranted.

This was a prospective cohort study conducted in Mukono district, Uganda, from February to November 2017. Women were initially enrolled during their first prenatal visit at Mukono Health Center IV (MHC IV). Women qualified for the study if they were between 18 and 45 years old, resided within 10 km of MHC IV, carried a singleton pregnancy, and planned to remain in Mukono district throughout their pregnancy. Women were excluded if they were 45 years old, HIV‐positive (verified via routine rapid HIV test conducted at first prenatal visit), severely malnourished (defined as body mass index [BMI] <16.0 kg/m2), severely anaemic (defined as Hb 50 specific foods in the previous 24 hr. Foods were selected based on their inclusion in the Ugandan Demographic and Health Survey, with minor modifications to account for the norms and preferences of the study site. Foods consumed by >10% of the participants are presented in Table S1. Responses were used to generate a Minimum Dietary Diversity for Women score, based on the number of food groups (0–10) consumed (Food and Agriculture Organization, 2016). Groups were considered (1) grains, white roots and tubers, and plantains; (2) pulses (beans, peas, and lentils); (3) nuts and seeds; (4) dairy; (5) meat, poultry, and fish; (6) eggs; (7) dark green leafy vegetables; (8) other vitamin A‐rich fruits and vegetables; (9) other vegetables; and (10) other fruits. Infant anthropometry data, including length (0.1‐cm precision; Infant/Child/Adult ShorrBoard, Shorr Production, Olney, MD, USA), weight (0.1‐kg precision; Seca 874, Hanover, MD, USA), and head circumference (0.1‐cm precision; flexible measuring tape), were assessed within 48 hr of delivery. All anthropometry measurements were taken in triplicate and averaged. Head circumference was measured as the largest possible occipital‐frontal circumference. AFB1 (> 98% purity), albumin determination reagent bromocreosol purple, and normal human serum were purchased from Sigma Aldrich Chemical Co. (St. Louis, MO, USA). Pronase (25 kU, Nuclease‐free) was purchased from Calbiochem (La Jolla, CA, USA). Protein assay dye reagent concentrate and protein standards were purchased from Bio‐Rad Laboratories Inc. (Hercules, CA, USA). Mixed mode solid phase extraction cartridges were purchased from the Waters Corp. (Milford, MA, USA). Authentic AFB‐Lys was synthesized as previously described (Sabbioni, Skipper, Büchi, & Tannenbaum, 1987). All other chemicals and solvents used were of highest grade commercially available. Midgestation maternal aflatoxin exposure was assessed using the serum AFB‐Lys adduct biomarker. Serum samples were transported on dry ice to the Wang laboratory at the University of Georgia, Athens, USA, and analysed with a high‐performance liquid chromatography (HPLC)‐fluorescence method. This included measurement of albumin and total protein concentrations for each sample, digestion with protease to release amino acids, concentration and purification of the AFB‐Lys adduct, and finally separation and quantification by HPLC (Qian et al., 2013a; Qian, Tang, Liu, & Wang, 2010). Specifically, thawed serum samples were inactivated for possible infectious agents via heating at 56°C for 30 min, followed by measurement of albumin and total protein concentrations using modified procedures as previously described (Qian et al., 2013b). A portion of each sample (approximately 150 μL) was digested by pronase (pronase: total protein, 1:4, w: w) at 37°C for 3 hr to release AFB‐Lys. AFB‐Lys in digests were further extracted and purified by passing through a Waters MAX solid phase extraction cartridge, which was preprimed with methanol and equilibrated with water. The loaded cartridge was sequentially washed with 2 ml water, 1 ml 70% methanol, and 1 ml 1% ammonium hydroxide in methanol at a flow rate of 1 ml/min. Purified AFB‐Lys was eluted with 1 ml 2% formic acid in methanol. The eluent was vacuum‐dried with a Labconco Centrivap concentrator (Kansas City, MO, USA) and reconstituted for HPLC‐fluorescence detection. The analysis of AFB‐Lys adduct was conducted in an Agilent 1200 HPLC‐fluorescence system (Santa Clara, CA, USA). The mobile phases consisted of buffer A (20 mM NH4H2PO4, pH 7.2) and buffer B (100% Methanol). The Zorbax Eclipse XDB‐C18 reverse phase column (5 micron, 4.6 × 250 mm) equipped with a guard column was used (Agilent, Santa Clara, CA, USA). Column temperature was maintained at 25°C during analysis, and a volume of 100 μL was injected at a flow rate of 1 ml/min. A gradient was generated to separate the AFB‐Lys adduct within 25 min of injection. Adduct was detected by fluorescence at maximum excitation and emission wavelengths of 405 and 470 nm, respectively. Calibration curves of authentic standard were generated weekly, and the standard AFB‐Lys was eluted at approximately 13.0 min. The limit of detection was 0.2 pg/mg albumin. The average recovery rate was 90%. The AFB‐Lys concentration was adjusted by albumin concentration. Quality assurance and quality control procedures were maintained during analyses, which included simultaneous analysis of one authentic standard in every 10 samples and two quality control samples daily. Furthermore, following completion of the laboratory analysis, sets of three samples were selected and pooled into 11 intraday reproducibility samples, which were analysed twice on the same day by the same analyst, and 11 interday reproducibility samples, which were analysed on different days by different analysts, to demonstrate laboratory precision and sampling reproducibility. All statistical analyses were performed using STATA 15 software (Stata Corps, College Station, TX, USA). Variables were first assessed for outliers and normality. Because of their skewed distribution, AFB‐Lys levels were natural log (ln) transformed prior to all analyses. Weight, length, and head circumference measurements were converted to z‐scores for WAZ, LAZ, WLZ, and HCZ using the World Health Organization standards. Outliers were defined as −6 > WAZ > +5, −5 > WLZ > +5, −6 > LAZ > +6, and −5 > HCZ > +5 based on the World Health Organization’s recommendation for biologically implausible values and were excluded from analysis. (Group, 2006). Enrolment characteristics for mothers were calculated and presented as mean ± SD. Pearson’s correlation coefficients were calculated to assess the relationship between maternal characteristics and ln AFB‐Lys levels and between maternal characteristics and infant birth weight. T tests were used to compare maternal ln AFB‐Lys levels by foods consumed in the 24‐hr dietary recall. Associations between ln maternal AFB‐Lys levels and infant birth characteristics were assessed using unadjusted and adjusted linear regression models. Covariates with a bivariate association with infant birth weight (p‐value < 0.10) were included in the adjusted models except in cases of collinearity with other covariates. For all adjusted models, the absence of multi‐collinearity was verified using variance inflation factor. For all analyses, p < 0.05 was considered statistically significant.

Based on the information provided, here are some potential innovations that could be used to improve access to maternal health:

1. Mobile Health (mHealth) Applications: Develop mobile applications that provide information and resources on maternal health, including nutrition, prenatal care, and birth planning. These apps can be easily accessible to pregnant women in low- and middle-income countries, providing them with essential knowledge and guidance.

2. Telemedicine: Implement telemedicine programs that allow pregnant women to consult with healthcare professionals remotely. This can help overcome geographical barriers and provide access to prenatal care and medical advice, especially in rural areas where healthcare facilities are limited.

3. Community Health Workers: Train and deploy community health workers who can provide basic prenatal care, education, and support to pregnant women in their communities. These workers can help identify high-risk pregnancies, provide health screenings, and refer women to appropriate healthcare facilities when necessary.

4. Nutritional Interventions: Implement programs that focus on improving nutrition during pregnancy, specifically targeting aflatoxin exposure. This can include promoting safe food storage and handling practices, as well as providing nutritional supplements to pregnant women to mitigate the effects of aflatoxin exposure.

5. Public Health Campaigns: Launch public health campaigns to raise awareness about the risks of aflatoxin exposure during pregnancy and the importance of seeking prenatal care. These campaigns can use various media channels, such as radio, television, and community outreach programs, to reach a wide audience.

6. Maternal Health Financing: Develop innovative financing mechanisms to ensure that pregnant women have access to affordable and quality maternal healthcare services. This can include micro-insurance schemes, community-based health financing models, or public-private partnerships to support maternal health services.

It is important to note that these recommendations are based on the specific context of the study conducted in Mukono district, Uganda. Further research and contextual adaptation may be required for effective implementation in other settings.
AI Innovations Description
Based on the description provided, the recommendation to improve access to maternal health and address the adverse birth outcomes associated with maternal aflatoxin exposure during pregnancy in Uganda is as follows:

1. Increase awareness and education: Implement comprehensive public health campaigns to raise awareness about the risks of aflatoxin exposure during pregnancy and its impact on birth outcomes. This can include community outreach programs, educational materials, and workshops targeting pregnant women, their families, and healthcare providers.

2. Strengthen food safety measures: Enhance food safety regulations and monitoring systems to reduce aflatoxin contamination in the food supply. This can involve implementing good agricultural practices, promoting proper storage and handling of food, and conducting regular inspections and testing of food products for aflatoxin levels.

3. Improve antenatal care services: Enhance access to quality antenatal care services, including regular check-ups, nutritional counseling, and screening for aflatoxin exposure. This can be achieved by increasing the number of healthcare facilities, training healthcare providers on maternal health issues, and ensuring the availability of necessary resources and equipment.

4. Enhance nutrition support: Provide pregnant women with access to a diverse and nutritious diet to mitigate the effects of aflatoxin exposure. This can involve promoting the consumption of locally available foods that are less prone to aflatoxin contamination, promoting breastfeeding, and providing nutritional supplements when necessary.

5. Conduct further research: Support and conduct additional research to better understand the mechanisms through which aflatoxin exposure affects birth outcomes and to identify effective interventions. This can include longitudinal studies, intervention trials, and collaborations between researchers, policymakers, and healthcare providers.

By implementing these recommendations, it is possible to improve access to maternal health and reduce the adverse birth outcomes associated with maternal aflatoxin exposure in Uganda.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations for improving access to maternal health:

1. Increase awareness and education: Implement programs to educate pregnant women and their families about the risks of aflatoxin exposure during pregnancy and the potential adverse birth outcomes. This can be done through community health workers, antenatal care clinics, and mass media campaigns.

2. Improve food safety and quality control: Strengthen food safety regulations and monitoring systems to reduce aflatoxin contamination in the food supply. This can involve training farmers on proper storage and handling practices, promoting the use of aflatoxin-resistant crops, and implementing regular testing of food samples.

3. Enhance antenatal care services: Ensure that antenatal care clinics have the necessary resources and trained healthcare providers to identify and address maternal health issues, including aflatoxin exposure. This can involve providing regular screenings for aflatoxin exposure, offering nutritional counseling, and promoting healthy behaviors during pregnancy.

4. Strengthen healthcare infrastructure: Invest in improving healthcare facilities, especially in rural areas, to ensure that pregnant women have access to quality maternal health services. This can include upgrading facilities, providing essential medical equipment and supplies, and training healthcare providers on maternal health management.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could be developed as follows:

1. Define the indicators: Identify specific indicators that can measure the impact of the recommendations, such as the reduction in aflatoxin exposure levels, improvement in birth outcomes (e.g., increase in birth weight), increase in antenatal care utilization, and decrease in maternal mortality rates.

2. Collect baseline data: Gather data on the current status of maternal health, including aflatoxin exposure levels, birth outcomes, antenatal care utilization rates, and maternal mortality rates. This can be done through surveys, medical records, and existing databases.

3. Develop a simulation model: Create a mathematical model that incorporates the identified indicators and their relationships. This model should consider the potential impact of the recommendations on the indicators and how they interact with each other.

4. Input data and run simulations: Input the baseline data into the simulation model and run multiple simulations to estimate the potential impact of the recommendations. This can involve adjusting the input parameters based on the expected effects of the recommendations and running the model iteratively.

5. Analyze results: Analyze the simulation results to assess the potential impact of the recommendations on improving access to maternal health. This can involve comparing the simulated outcomes with the baseline data and identifying any significant changes or improvements.

6. Validate the model: Validate the simulation model by comparing the simulated outcomes with real-world data, if available. This can help ensure the accuracy and reliability of the model’s predictions.

7. Refine and iterate: Based on the simulation results and validation, refine the model and iterate the process to further improve its accuracy and reliability. This may involve adjusting the input parameters, incorporating additional data sources, or refining the model’s structure.

By following this methodology, policymakers and healthcare providers can gain insights into the potential impact of the recommendations on improving access to maternal health and make informed decisions on implementing the most effective interventions.

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