Aflatoxin exposure in pregnant women of mixed status of human immunodeficiency virus infection and rate of gestational weight gain: a Ugandan cohort study

Tropical Medicine and International Health, Volume 25, No. 9, Year 2020

Ukuhunyushwa

Objectives: To examine the association between aflatoxin (AF) exposure during pregnancy and rate of gestational weight gain (GWG) in a sample of pregnant women of mixed HIV status in Gulu, northern Uganda. Methods: 403 pregnant women were included (133 HIV-infected on antiretroviral therapy (ART), 270 HIV-uninfected). Women’s weight, height and socio-demographic characteristics were collected at baseline (~19 weeks’ gestation); weight was assessed at each follow-up visit. Serum was collected at baseline and tested for aflatoxin B1-lysine adduct (AFB-lys) levels using high-performance liquid chromatography (HPLC). Linear mixed-effects models were used to examine the association between AFB-lys levels and rate of GWG. Results: AFB-lys levels (detected in 98.3% of samples) were higher among HIV-infected pregnant women than HIV-uninfected pregnant women [median (interquartile range): 4.8 (2.0, 15.0) vs. 3.5 (1.6, 6.1) pg/mg of albumin, P < 0.0001]. Adjusting for HIV status, a one-log increase in aflatoxin levels was associated with a 16.2 g per week lower rate of GWG (P = 0.028). The association between AFB-lys and the rate of GWG was stronger and significant only among HIV-infected women on ART [−25.7 g per week per log (AFB-lys), P = 0.009 for HIV-infected women vs. −7.5 g per week per log (AFB-lys), P = 0.422 for HIV-uninfected women]. Conclusions: Pregnant women with higher levels of AF exposure had lower rates of GWG. The association was stronger for HIV-infected women on ART, suggesting increased risk. Data for this study were collected from 2012 to 2013 as part of the Prenatal Nutrition and Psychosocial Health Outcomes (PreNAPs) study. PreNAPs was an observational, longitudinal cohort study designed to explore relationships among food access, nutritional and psychosocial exposures, and several physical and mental health outcomes in a sample of 403 HIV‐infected (n = 133) and HIV‐uninfected (n = 270) pregnant women in Gulu, northern Uganda. The study was approved by Cornell University’s Institutional Review Board (IRB), Gulu University’s Institutional Review Committee and the Uganda National Council for Science and Technology (UNCST). Written informed consent was obtained from all participants prior to enrolment. The parent study was registered at ClinicalTrials.gov as {"type":"clinical-trial","attrs":{"text":"NCT02922829","term_id":"NCT02922829"}}NCT02922829. PreNAPs methodology (i.e. recruitment process, inclusion and exclusion criteria, response rates, and reasons for refusal to participate) has been previously reported [39, 40]. Briefly, pregnant women were recruited from the antenatal clinic (ANC) of Gulu Regional Referral Hospital (GRRH; i.e. Gulu Hospital), located in Gulu, northern Uganda. HIV‐infected and HIV‐uninfected pregnant women who presented at the ANC between 10‐ and 26‐week gestation (assessed according to women’s recall of the first date of their last menstrual period), resided within 30 km of GRRH and had a known HIV status were eligible to participate in PreNAPs. Women whose HIV status was unknown were excluded from participation. Of the 415 pregnant women asked to participate in PreNAPs, 405 accepted, while 10 refused citing lack of time. Of the 405 participating women, complete data on all the variables of interest for this analysis were available for 403 women. In PreNAPs, HIV‐infected women were oversampled in order to achieve a minimum ratio of 1 HIV‐infected: 2 HIV‐uninfected participants. The sample size for PreNAPs was designed to provide 80% power to detect a 50‐g difference in weight gain between HIV‐infected and HIV‐uninfected women at a 5% level of significance and accounting for a 10% loss to follow‐up. Women in PreNAPs were followed monthly throughout their pregnancy (mean ± SD prenatal visits per woman: 5.0 ± 1.1). Women were tested for HIV at the ANC of GRRH per Government of Uganda (GoU) guidelines [41]. All HIV‐infected pregnant women were participating in a GoU ART programme to prevent mother‐to‐child transmission of HIV. Antiretroviral drugs were provided to all HIV‐infected pregnant women following the GoU [41] and WHO [42] guidelines. At enrolment, socio‐demographic data were collected for all women including age, parity (nulliparous vs. other), marital status (separated, divorced or widowed vs. other) and education level (primary level or lower vs. higher than primary level). Maternal height and weight were measured at enrolment (Seca 206 for height; Seca 874 for weight; Seca North America, Chino, CA, USA). Weight was re‐assessed at all follow‐up visits. Gestational age of the index pregnancy was determined using women’s recall of the first date of their last menstrual period. Rate of GWG was calculated by dividing the difference of maternal weight between the last and first monthly visit by the corresponding difference of gestational weeks. Dietary diversity was assessed using the Minimum Dietary Diversity for Women (MDD‐W) indicator [43]. Finally, women were asked about possession of 20 household assets contained in the socio‐economic module of the 2009–2010 Uganda National Panel Survey Questionnaire [44]. An asset index was generated using principal components analysis methodology [45]. Serum samples were temporarily stored at −20 °C in Gulu, northern Uganda, and then transferred to Kampala, Uganda, where they were stored at −80 °C. Samples were then shipped to the laboratory at the University of Georgia, Athens, GA, USA, for analysis. AF exposure was assessed via serum levels of the AFB‐lys adduct using previously described high‐performance liquid chromatography (HPLC)‐fluorescence methods [46, 47]. 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‐lysine adduct, and finally separation and quantification by HPLC. Household geographic coordinates were obtained for 150 women in the sample. Women’s households were then mapped using geographic information system (GIS) software (ArcGIS, Esri, Redlands, CA, USA) according to HIV status (infected vs. uninfected) as well as serum AFB‐lys level. AF exposure data were grouped into five ranges of values determined by the natural breaks (jenks) classification method [48]. The Anselin Local Moran's I statistic tool [49] was used to determine whether there were statistically significant hot spots, cold spots and/or cluster outliers of HIV infection or AF levels using an inverse distance relationship. The main objective of this study was to determine the effect of AF exposure on the rate of GWG in a sample of pregnant women of mixed HIV status. Due to their skewed distribution, AFB‐lys levels were log‐transformed prior to analyses. Baseline characteristics for mothers were calculated and are presented as mean ± SD or n (%). Student’s t‐tests were used to compare baseline characters between HIV‐infected and HIV‐uninfected women. Associations between AFB‐lys levels and baseline characteristics were assessed using either Spearman’s correlation coefficients in the case of continuous variables or Mann–Whitney tests in the case of categorical variables. Linear mixed‐effects models were used to determine the unadjusted and HIV status‐adjusted differences in the rate of GWG per unit increase in baseline log AFB‐lys levels. Thereafter, separate models were fit for HIV‐infected women and HIV‐uninfected women to examine whether the effect of AFs on the rate of GWG differed in the two study groups. Data were analysed using Stata 15 software (StataCorp, College Station, TX, USA). For all analyses, P < 0.05 was considered statistically significant.

I-AI Digest

Study Justification:

This study aimed to investigate the association between aflatoxin (AF) exposure during pregnancy and the rate of gestational weight gain (GWG) in a sample of pregnant women in Gulu, northern Uganda. The study is important because AF exposure has been linked to adverse health outcomes, and understanding its impact on GWG is crucial for maternal and child health.

Highlights:

– A total of 403 pregnant women were included in the study, with 133 HIV-infected women on antiretroviral therapy (ART) and 270 HIV-uninfected women.
– AFB-lys (a biomarker for AF exposure) levels were higher among HIV-infected pregnant women compared to HIV-uninfected pregnant women.
– Adjusting for HIV status, higher levels of AFB-lys were associated with a lower rate of GWG.
– The association between AFB-lys and the rate of GWG was stronger and significant only among HIV-infected women on ART.
– These findings suggest that pregnant women with higher levels of AF exposure, particularly HIV-infected women on ART, may be at increased risk for lower rates of GWG.

Recommendations:

Based on the study findings, the following recommendations can be made:

1. Increase awareness and education about the potential risks of AF exposure during pregnancy, especially for HIV-infected women on ART.
2. Implement strategies to reduce AF exposure among pregnant women, such as improving food storage and handling practices.
3. Conduct further research to explore the mechanisms underlying the association between AF exposure and GWG, and to develop interventions to mitigate the negative effects.

Key Role Players:

To address the recommendations, the following key role players are needed:

1. Healthcare professionals: Obstetricians, gynecologists, and nutritionists can provide guidance and support to pregnant women regarding AF exposure and GWG.
2. Public health officials: Government agencies and organizations can develop and implement public health campaigns to raise awareness and educate the public about AF exposure.
3. Researchers: Further studies are needed to investigate the mechanisms and develop interventions to reduce AF exposure and mitigate its effects on GWG.

Cost Items for Planning Recommendations:

While the actual cost may vary, the following budget items should be considered in planning the recommendations:

1. Research funding: Grants and funding should be allocated for further research on AF exposure and GWG.
2. Education and awareness campaigns: Resources should be allocated for developing and implementing educational materials and campaigns targeting pregnant women and healthcare providers.
3. Intervention programs: Funding should be allocated for implementing interventions to reduce AF exposure, such as training programs for food handlers and improving food storage facilities.
Please note that the provided information is based on the description and findings of the study and may not cover all aspects of the research.

Amandla Obufakazi

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong, but there are some areas for improvement. The study design is observational and longitudinal, which provides valuable data. The sample size is adequate, with 403 pregnant women included. The statistical analysis using linear mixed-effects models adds to the strength of the evidence. However, there are a few areas that could be improved. Firstly, the abstract does not mention any control group or comparison, which makes it difficult to fully assess the association between aflatoxin exposure and gestational weight gain. Secondly, the abstract does not provide information on potential confounding factors that were considered in the analysis. It would be helpful to know if other variables, such as age, parity, or education level, were adjusted for in the models. Lastly, the abstract does not mention any limitations or potential sources of bias in the study. Including this information would provide a more comprehensive assessment of the evidence. To improve the evidence, future studies could consider including a control group for comparison, adjusting for potential confounding factors, and addressing any limitations or biases in the study design.

Abstract

Data for this study were collected from 2012 to 2013 as part of the Prenatal Nutrition and Psychosocial Health Outcomes (PreNAPs) study. PreNAPs was an observational, longitudinal cohort study designed to explore relationships among food access, nutritional and psychosocial exposures, and several physical and mental health outcomes in a sample of 403 HIV‐infected (n = 133) and HIV‐uninfected (n = 270) pregnant women in Gulu, northern Uganda. The study was approved by Cornell University’s Institutional Review Board (IRB), Gulu University’s Institutional Review Committee and the Uganda National Council for Science and Technology (UNCST). Written informed consent was obtained from all participants prior to enrolment. The parent study was registered at ClinicalTrials.gov as {"type":"clinical-trial","attrs":{"text":"NCT02922829","term_id":"NCT02922829"}}NCT02922829. PreNAPs methodology (i.e. recruitment process, inclusion and exclusion criteria, response rates, and reasons for refusal to participate) has been previously reported [39, 40]. Briefly, pregnant women were recruited from the antenatal clinic (ANC) of Gulu Regional Referral Hospital (GRRH; i.e. Gulu Hospital), located in Gulu, northern Uganda. HIV‐infected and HIV‐uninfected pregnant women who presented at the ANC between 10‐ and 26‐week gestation (assessed according to women’s recall of the first date of their last menstrual period), resided within 30 km of GRRH and had a known HIV status were eligible to participate in PreNAPs. Women whose HIV status was unknown were excluded from participation. Of the 415 pregnant women asked to participate in PreNAPs, 405 accepted, while 10 refused citing lack of time. Of the 405 participating women, complete data on all the variables of interest for this analysis were available for 403 women. In PreNAPs, HIV‐infected women were oversampled in order to achieve a minimum ratio of 1 HIV‐infected: 2 HIV‐uninfected participants. The sample size for PreNAPs was designed to provide 80% power to detect a 50‐g difference in weight gain between HIV‐infected and HIV‐uninfected women at a 5% level of significance and accounting for a 10% loss to follow‐up. Women in PreNAPs were followed monthly throughout their pregnancy (mean ± SD prenatal visits per woman: 5.0 ± 1.1). Women were tested for HIV at the ANC of GRRH per Government of Uganda (GoU) guidelines [41]. All HIV‐infected pregnant women were participating in a GoU ART programme to prevent mother‐to‐child transmission of HIV. Antiretroviral drugs were provided to all HIV‐infected pregnant women following the GoU [41] and WHO [42] guidelines. At enrolment, socio‐demographic data were collected for all women including age, parity (nulliparous vs. other), marital status (separated, divorced or widowed vs. other) and education level (primary level or lower vs. higher than primary level). Maternal height and weight were measured at enrolment (Seca 206 for height; Seca 874 for weight; Seca North America, Chino, CA, USA). Weight was re‐assessed at all follow‐up visits. Gestational age of the index pregnancy was determined using women’s recall of the first date of their last menstrual period. Rate of GWG was calculated by dividing the difference of maternal weight between the last and first monthly visit by the corresponding difference of gestational weeks. Dietary diversity was assessed using the Minimum Dietary Diversity for Women (MDD‐W) indicator [43]. Finally, women were asked about possession of 20 household assets contained in the socio‐economic module of the 2009–2010 Uganda National Panel Survey Questionnaire [44]. An asset index was generated using principal components analysis methodology [45]. Serum samples were temporarily stored at −20 °C in Gulu, northern Uganda, and then transferred to Kampala, Uganda, where they were stored at −80 °C. Samples were then shipped to the laboratory at the University of Georgia, Athens, GA, USA, for analysis. AF exposure was assessed via serum levels of the AFB‐lys adduct using previously described high‐performance liquid chromatography (HPLC)‐fluorescence methods [46, 47]. 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‐lysine adduct, and finally separation and quantification by HPLC. Household geographic coordinates were obtained for 150 women in the sample. Women’s households were then mapped using geographic information system (GIS) software (ArcGIS, Esri, Redlands, CA, USA) according to HIV status (infected vs. uninfected) as well as serum AFB‐lys level. AF exposure data were grouped into five ranges of values determined by the natural breaks (jenks) classification method [48]. The Anselin Local Moran's I statistic tool [49] was used to determine whether there were statistically significant hot spots, cold spots and/or cluster outliers of HIV infection or AF levels using an inverse distance relationship. The main objective of this study was to determine the effect of AF exposure on the rate of GWG in a sample of pregnant women of mixed HIV status. Due to their skewed distribution, AFB‐lys levels were log‐transformed prior to analyses. Baseline characteristics for mothers were calculated and are presented as mean ± SD or n (%). Student’s t‐tests were used to compare baseline characters between HIV‐infected and HIV‐uninfected women. Associations between AFB‐lys levels and baseline characteristics were assessed using either Spearman’s correlation coefficients in the case of continuous variables or Mann–Whitney tests in the case of categorical variables. Linear mixed‐effects models were used to determine the unadjusted and HIV status‐adjusted differences in the rate of GWG per unit increase in baseline log AFB‐lys levels. Thereafter, separate models were fit for HIV‐infected women and HIV‐uninfected women to examine whether the effect of AFs on the rate of GWG differed in the two study groups. Data were analysed using Stata 15 software (StataCorp, College Station, TX, USA). For all analyses, P < 0.05 was considered statistically significant.

Izinto zokwakha

https://efashare.b-cdn.net/materials/ba1f165f85eb5f8156cda1ae1a7cdaedad1c9da95f7c2ee1905190a58d1032d5/TMI-25-1145-s001.docx

Emisha

Based on the provided information, the innovation for potential recommendations to improve access to maternal health could include:

1. Implementing regular screening for aflatoxin exposure during pregnancy: This would involve incorporating aflatoxin testing into routine prenatal care visits to identify pregnant women who are at risk of exposure. By identifying high-risk individuals, appropriate interventions and support can be provided to mitigate the negative effects of aflatoxin on gestational weight gain.

2. Developing targeted interventions for HIV-infected pregnant women on antiretroviral therapy (ART): The study found that the association between aflatoxin exposure and rate of gestational weight gain was stronger among HIV-infected women on ART. Therefore, it is important to develop specific interventions tailored to this population, such as nutritional counseling and support, to address the increased risk and promote healthy weight gain during pregnancy.

3. Increasing awareness and education about aflatoxin exposure: Many pregnant women may not be aware of the potential risks associated with aflatoxin exposure. Implementing educational programs and campaigns to raise awareness about aflatoxin and its impact on maternal health can help women make informed decisions and take necessary precautions to reduce exposure.

4. Strengthening food safety regulations and monitoring: Aflatoxin contamination is often linked to poor food storage and handling practices. Strengthening food safety regulations and monitoring systems can help ensure that food products, especially those consumed by pregnant women, are free from aflatoxin contamination. This can be achieved through regular inspections, testing, and enforcement of quality standards.

5. Improving access to nutritious and diverse food options: A healthy and diverse diet is essential for maternal health and optimal gestational weight gain. Efforts should be made to improve access to nutritious food options, especially for vulnerable populations, through initiatives such as community gardens, food assistance programs, and support for local agriculture.

It is important to note that these recommendations are based on the specific findings of the study mentioned and may need to be further evaluated and adapted to the local context and resources available.

AI Innovations Description

The study titled “Aflatoxin exposure in pregnant women of mixed status of human immunodeficiency virus infection and rate of gestational weight gain: a Ugandan cohort study” aims to examine the association between aflatoxin (AF) exposure during pregnancy and the rate of gestational weight gain (GWG) in pregnant women of mixed HIV status in Gulu, northern Uganda.

The study collected data from 403 pregnant women, including 133 HIV-infected women on antiretroviral therapy (ART) and 270 HIV-uninfected women. The women’s weight, height, and socio-demographic characteristics were collected at baseline, and weight was assessed at each follow-up visit. Serum samples were collected and tested for aflatoxin B1-lysine adduct (AFB-lys) levels using high-performance liquid chromatography (HPLC).

The results showed that AFB-lys levels were higher among HIV-infected pregnant women compared to HIV-uninfected pregnant women. Adjusting for HIV status, a one-log increase in aflatoxin levels was associated with a lower rate of GWG. The association between AFB-lys and the rate of GWG was stronger and significant only among HIV-infected women on ART.

The study suggests that pregnant women with higher levels of AF exposure had lower rates of GWG, particularly among HIV-infected women on ART. This finding highlights the potential risk of aflatoxin exposure on maternal health outcomes.

To improve access to maternal health, based on the findings of this study, it is recommended to:

1. Raise awareness: Educate pregnant women, healthcare providers, and the community about the potential risks of aflatoxin exposure during pregnancy and its impact on gestational weight gain.

2. Implement screening programs: Develop screening programs to identify pregnant women at higher risk of aflatoxin exposure, such as HIV-infected women on ART. This can help target interventions and support for those most vulnerable.

3. Improve food safety measures: Implement measures to reduce aflatoxin contamination in food, especially in regions where aflatoxin exposure is prevalent. This can include promoting good agricultural practices, proper storage, and processing techniques to minimize aflatoxin contamination.

4. Provide nutritional support: Offer nutritional counseling and support to pregnant women, particularly those at higher risk of aflatoxin exposure. This can include guidance on dietary diversification, ensuring a balanced and nutritious diet, and promoting safe food handling practices.

5. Strengthen healthcare systems: Enhance the capacity of healthcare systems to provide comprehensive maternal health services, including regular monitoring of weight gain during pregnancy and early detection of any potential complications.

By implementing these recommendations, it is possible to improve access to maternal health and mitigate the negative impact of aflatoxin exposure on gestational weight gain and overall maternal well-being.

AI Innovations Methodology

Based on the provided description, the study examines the association between aflatoxin (AF) exposure during pregnancy and the rate of gestational weight gain (GWG) in pregnant women of mixed HIV status in Gulu, northern Uganda. The methodology includes collecting data on weight, height, socio-demographic characteristics, and serum samples from 403 pregnant women. Aflatoxin B1-lysine adduct (AFB-lys) levels are measured using high-performance liquid chromatography (HPLC). Linear mixed-effects models are used to analyze the association between AFB-lys levels and the rate of GWG.

To improve access to maternal health, the following innovations could be considered:

1. Mobile Health (mHealth) Applications: Develop mobile applications that provide pregnant women with information on maternal health, including nutrition, prenatal care, and potential risks such as aflatoxin exposure. These apps can also send reminders for prenatal visits and provide access to telemedicine consultations.

2. Community Health Workers: Train and deploy community health workers to provide education and support to pregnant women in remote areas. These workers can conduct regular check-ups, provide nutritional counseling, and raise awareness about the risks of aflatoxin exposure.

3. Telemedicine: Establish telemedicine services to connect pregnant women in remote areas with healthcare professionals. This can help overcome geographical barriers and provide timely advice and guidance on maternal health issues, including aflatoxin exposure.

4. Mobile Clinics: Set up mobile clinics that can travel to underserved areas to provide prenatal care, including screening for aflatoxin exposure. These clinics can offer comprehensive maternal health services, including check-ups, vaccinations, and nutritional support.

To simulate the impact of these recommendations on improving access to maternal health, the following methodology can be employed:

1. Define the target population: Identify the specific population that will benefit from the innovations, such as pregnant women in remote areas with limited access to healthcare facilities.

2. Collect baseline data: Gather data on the current state of maternal health in the target population, including indicators such as prenatal care utilization, maternal mortality rates, and aflatoxin exposure levels.

3. Implement the innovations: Introduce the recommended innovations, such as mHealth applications, community health worker programs, telemedicine services, or mobile clinics, in the target population.

4. Monitor and evaluate: Track the implementation of the innovations and collect data on key indicators, including the uptake of the innovations, changes in prenatal care utilization, improvements in maternal health outcomes, and reduction in aflatoxin exposure levels.

5. Analyze the data: Use statistical analysis techniques to assess the impact of the innovations on improving access to maternal health. Compare the baseline data with the post-implementation data to identify any significant changes and measure the effectiveness of the innovations.

6. Adjust and refine: Based on the findings, make adjustments and refinements to the innovations to optimize their impact on improving access to maternal health. This may involve scaling up successful interventions, addressing any barriers or challenges identified during the evaluation, and continuously monitoring and evaluating the impact of the innovations.

By following this methodology, it is possible to simulate the impact of the recommended innovations on improving access to maternal health and assess their effectiveness in addressing the specific challenges faced by pregnant women, such as aflatoxin exposure.

Umbhali

Dima Health

Statistics:

Citations: 5

Identifiers:

DOI: 10.1111/tmi.13457

ISSN: 13602276

Research Areas:

Disparities, Food Security, Health System and Policy, Infectious Diseases, Maternal Access, Maternal and Child Health, Mental Health, Quality of Care, Sexual and Reproductive Health, Social Determinants, Technology and Innovations

Study Countries:

Uganda

Study Design:

Cohort Study, Cross Sectional Study

Study Approach:

Quantitative

Participants Gender:

Female

Yabelana ngalokhu: