Mid-thigh circumference as an indicator of nutritional status to predict adverse pregnancy outcomes among HIV-infected and HIV-uninfected women in Malawi

BMC Pregnancy and Childbirth, Volume 21, No. 1, Year 2021

Interpretação

Background: High rates of adverse pregnancy outcomes globally raise the need to understand risk factors and develop preventative interventions. The Pregnancy Outcomes in the Era of Universal Antiretroviral Treatment in Sub-Saharan Africa (POISE Study) was a prospective, observational cohort study conducted from 2016 to 2017 in Blantyre, Malawi. We examine the associations between indicators of nutritional status, specifically mid-thigh circumference (MTC) and body-mass index (BMI), and adverse pregnancy outcomes, low birth weight (LBW), preterm birth (PTB), and small-for-gestational age (SGA), in a cohort of HIV-infected and HIV-uninfected women. Methods: Sociodemographic, clinical, laboratory, and maternal height, weight and MTC data were collected immediately before or after delivery at the Queen Elizabeth Central Hospital (QEHC) and 4 affiliated health centers in Blantyre, Malawi. LBW was defined as birth weight < 2.5 kg; PTB as gestational age < 37 weeks using Ballard score; and SGA as birth weight < 10th percentile for gestational age. Descriptive, stratified, and multivariable logistic regression were conducted using R. Results: Data from 1298 women were analyzed: 614 HIV-infected and 684 HIV-uninfected. MTC was inversely associated with LBW (adjusted odds ratio [aOR] = 0.95, p = 0.03) and PTB (aOR 0.92, p < 0.001), after controlling for HIV status, age, socioeconomic status and hemoglobin. The association between MTC and SGA was (aOR 0.99, p = 0.53). Similarly, higher BMI was significantly associated with lower odds of PTB (aOR 0.90, p < 0.001), LBW (aOR 0.93, p = 0.05), and SGA (aOR 0.95, p = 0.04). Conclusions: We observed an inverse relationship between MTC and adverse pregnancy outcomes in Malawi irrespective of HIV infection. MTC performs comparably to BMI; the ease of measuring MTC could make it a practical tool in resource-constrained settings for identification of women at risk of adverse pregnancy outcomes. The parent POISE study was conducted at the Queen Elizabeth Central Hospital (QEHC) and 4 affiliated health centers in Blantyre, Malawi from January 2016 to September 2017. At these health facilities, eligible women were screened and enrolled in the study at delivery. Full details of the study have been published [12]. Briefly, POISE was a prospective observational study. Women were enrolled at the five health facilities at time of delivery (before or after delivery) and followed for one year post-delivery with their infants. Inclusion criteria were the following: confirmed HIV status, written informed consent and live singleton births. Participants were excluded if they were unable to provide informed consent or had multiple births. HIV-infected women were eligible for the study if they had a CD4 cell count ≥ 350 cells/mm3, were on ART for at least 1 week before delivery and did not have WHO stage 3 or 4 HIV disease. The parent study aimed to assess the impact of ART among clinically healthy HIV-infected women (i.e., they did have low CD4 cell count or stage 3 or 4 HIV disease stage). Participants were counseled and consented to enroll along with their infants. Eligible HIV-uninfected women were concurrently enrolled in the same health facilities at which the HIV-infected women were enrolled. Trained study nurses administered structured questionnaires and conducted physical examinations after obtaining informed consent at delivery. The questionnaires collected sociodemographic characteristics, medical history, and sexual and reproductive health information, which included information on risk factors and potential confounders. For HIV-infected women, additional information on ART use and adherence was included and blood samples were collected to measure the HIV viral load and CD4 cell count. The physical examination of all women following delivery included anthropometric measurements of height, weight, and MTC, which were the primary anthropometric indicators in this study. Weight was measured to the nearest 0.1 kg; height and MTC were measured to the nearest 0.5 cm. Body mass index (BMI) was calculated as kg/m2 using the height and weight measurements. Measurement of MTC was conducted by trained study workers on the right thigh while the woman was standing using a flexible measuring tape. The mid-point between the top of the femur and the knee was marked and MTC was determined in centimeters. Based on previous research conducted in Malawi, women who reported having electricity in the home were identified as having high socioeconomic status and women without electricity in the home were identified as having low socioeconomic status [12]. After birth, a physical examination of the infant was conducted, which included birth weight and other anthropometric measurements. Gestational age was calculated using the Ballard score within 36 h of birth by a trained study nurse. Gestational age was estimated using the date of last menstrual period when the Ballard score was missing. Estimates based on Ballard score and date of last menstrual period were compared to assess potential misclassifications [13]. Data were entered using a database deisgned in Microsoft Access and data cleaning was done in a regular interval in Microsoft Excel and Stata (version 14.2). Data double entry was done and anonymized prior to analysis. The primary outcomes of this study were PTB, LBW, and SGA. PTB was defined as a gestational age < 37 completed weeks. LBW was defined as birth weight < 2.5 kg. SGA was defined as birth weight less than the 10th percentile for gestational age, using the reference population as described by Oken et. al [14]. Descriptive analyses were conducted first on the sociodemographic and clinical data and primary outcomes of interest. Stratified analyses, graphical presentations, and data transformations were also used. We first assessed the associations between MTC and the outcomes of birth weight and gestational age as continuous variables using linear regression models. We modeled the associations between MTC and the three pregnancy outcomes (PTB, LBW, and SGA as binary outcomes) using univariable and multivariable logistic regression analyses, which controlled for potential cofounders. Univariable and multivariable models were also created to examine the associations between BMI and the three pregnancy outcomes. The following baseline risk factors were controlled for in the multivariable analyses: HIV status (infected/uninfected; all HIV-infected women were taking the standard national ART regimen in Malawi at the time of study conduct [tenofovir, lamivudine and efavirenz]), maternal age in years (continuous), hemoglobin level (< 10 g/dL/ ≥ 10 g/dL) and socioeconomic status measured as having electricity at home (yes/no). These were selected based on the risk factors assessed in the parent study, which were of biological and epidemiological importance [12]. The final multivariable model included these potential confounders in addition to the exposure of interest– MTC. The analyses were run at a p < 0.05 significance level, and crude and adjusted odds ratios with 95% confidence intervals are presented. All analyses were done in R statistical software package version 3.6.3 (Vienna, Austria).

AI Digest

Study Justification:

– High rates of adverse pregnancy outcomes globally necessitate understanding risk factors and developing preventative interventions.
– This study aimed to examine the associations between mid-thigh circumference (MTC) and body-mass index (BMI) as indicators of nutritional status, and adverse pregnancy outcomes among HIV-infected and HIV-uninfected women in Malawi.
– The study aimed to determine if MTC could be a practical tool for identifying women at risk of adverse pregnancy outcomes in resource-constrained settings.

Highlights:

– Data from 1298 women (614 HIV-infected and 684 HIV-uninfected) were analyzed.
– MTC was inversely associated with low birth weight (LBW) and preterm birth (PTB), even after controlling for HIV status, age, socioeconomic status, and hemoglobin levels.
– Higher BMI was also significantly associated with lower odds of PTB, LBW, and small-for-gestational age (SGA).
– The study suggests that MTC performs comparably to BMI as an indicator of nutritional status in predicting adverse pregnancy outcomes.
– The ease of measuring MTC makes it a practical tool for identifying women at risk of adverse pregnancy outcomes in resource-constrained settings.

Recommendations:

– Implement routine measurement of mid-thigh circumference (MTC) as a part of antenatal care to identify women at risk of adverse pregnancy outcomes.
– Provide targeted nutritional interventions for women with low MTC or BMI to improve pregnancy outcomes.
– Conduct further research to validate the use of MTC as an indicator of nutritional status in different populations and settings.

Key Role Players:

– Healthcare providers: Responsible for measuring mid-thigh circumference (MTC) during antenatal care visits and providing appropriate interventions based on the results.
– Policy makers: Responsible for implementing guidelines and policies that include routine measurement of MTC as part of antenatal care.
– Researchers: Responsible for conducting further studies to validate the use of MTC as an indicator of nutritional status in different populations and settings.

Cost Items for Planning Recommendations:

– Training: Budget for training healthcare providers on how to measure mid-thigh circumference (MTC) accurately.
– Equipment: Budget for purchasing flexible measuring tapes for measuring MTC.
– Monitoring and Evaluation: Budget for monitoring and evaluating the implementation of routine MTC measurement and the effectiveness of targeted nutritional interventions.
– Research: Budget for conducting further research to validate the use of MTC as an indicator of nutritional status in different populations and settings.

Força da prova

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 described as a prospective, observational cohort study, which provides valuable information. The sample size is relatively large with data from 1298 women. The associations between mid-thigh circumference (MTC) and adverse pregnancy outcomes (low birth weight, preterm birth, and small-for-gestational age) are analyzed using descriptive, stratified, and multivariable logistic regression. The results show significant associations between MTC and adverse pregnancy outcomes, after controlling for potential confounders such as HIV status, age, socioeconomic status, and hemoglobin. However, the abstract does not provide information on the representativeness of the study population or the generalizability of the findings. Additionally, there is no mention of any limitations or potential biases in the study. To improve the strength of the evidence, it would be helpful to include information on the sampling method used to select the study participants and provide a discussion of the limitations and potential biases in the study. This would provide a more comprehensive understanding of the study’s findings and their implications.

Resumo

The parent POISE study was conducted at the Queen Elizabeth Central Hospital (QEHC) and 4 affiliated health centers in Blantyre, Malawi from January 2016 to September 2017. At these health facilities, eligible women were screened and enrolled in the study at delivery. Full details of the study have been published [12]. Briefly, POISE was a prospective observational study. Women were enrolled at the five health facilities at time of delivery (before or after delivery) and followed for one year post-delivery with their infants. Inclusion criteria were the following: confirmed HIV status, written informed consent and live singleton births. Participants were excluded if they were unable to provide informed consent or had multiple births. HIV-infected women were eligible for the study if they had a CD4 cell count ≥ 350 cells/mm3, were on ART for at least 1 week before delivery and did not have WHO stage 3 or 4 HIV disease. The parent study aimed to assess the impact of ART among clinically healthy HIV-infected women (i.e., they did have low CD4 cell count or stage 3 or 4 HIV disease stage). Participants were counseled and consented to enroll along with their infants. Eligible HIV-uninfected women were concurrently enrolled in the same health facilities at which the HIV-infected women were enrolled. Trained study nurses administered structured questionnaires and conducted physical examinations after obtaining informed consent at delivery. The questionnaires collected sociodemographic characteristics, medical history, and sexual and reproductive health information, which included information on risk factors and potential confounders. For HIV-infected women, additional information on ART use and adherence was included and blood samples were collected to measure the HIV viral load and CD4 cell count. The physical examination of all women following delivery included anthropometric measurements of height, weight, and MTC, which were the primary anthropometric indicators in this study. Weight was measured to the nearest 0.1 kg; height and MTC were measured to the nearest 0.5 cm. Body mass index (BMI) was calculated as kg/m2 using the height and weight measurements. Measurement of MTC was conducted by trained study workers on the right thigh while the woman was standing using a flexible measuring tape. The mid-point between the top of the femur and the knee was marked and MTC was determined in centimeters. Based on previous research conducted in Malawi, women who reported having electricity in the home were identified as having high socioeconomic status and women without electricity in the home were identified as having low socioeconomic status [12]. After birth, a physical examination of the infant was conducted, which included birth weight and other anthropometric measurements. Gestational age was calculated using the Ballard score within 36 h of birth by a trained study nurse. Gestational age was estimated using the date of last menstrual period when the Ballard score was missing. Estimates based on Ballard score and date of last menstrual period were compared to assess potential misclassifications [13]. Data were entered using a database deisgned in Microsoft Access and data cleaning was done in a regular interval in Microsoft Excel and Stata (version 14.2). Data double entry was done and anonymized prior to analysis. The primary outcomes of this study were PTB, LBW, and SGA. PTB was defined as a gestational age < 37 completed weeks. LBW was defined as birth weight < 2.5 kg. SGA was defined as birth weight less than the 10th percentile for gestational age, using the reference population as described by Oken et. al [14]. Descriptive analyses were conducted first on the sociodemographic and clinical data and primary outcomes of interest. Stratified analyses, graphical presentations, and data transformations were also used. We first assessed the associations between MTC and the outcomes of birth weight and gestational age as continuous variables using linear regression models. We modeled the associations between MTC and the three pregnancy outcomes (PTB, LBW, and SGA as binary outcomes) using univariable and multivariable logistic regression analyses, which controlled for potential cofounders. Univariable and multivariable models were also created to examine the associations between BMI and the three pregnancy outcomes. The following baseline risk factors were controlled for in the multivariable analyses: HIV status (infected/uninfected; all HIV-infected women were taking the standard national ART regimen in Malawi at the time of study conduct [tenofovir, lamivudine and efavirenz]), maternal age in years (continuous), hemoglobin level (< 10 g/dL/ ≥ 10 g/dL) and socioeconomic status measured as having electricity at home (yes/no). These were selected based on the risk factors assessed in the parent study, which were of biological and epidemiological importance [12]. The final multivariable model included these potential confounders in addition to the exposure of interest– MTC. The analyses were run at a p < 0.05 significance level, and crude and adjusted odds ratios with 95% confidence intervals are presented. All analyses were done in R statistical software package version 3.6.3 (Vienna, Austria).

Materiais

N/A

Inovações

Based on the information provided, one potential innovation to improve access to maternal health is the use of mid-thigh circumference (MTC) as an indicator of nutritional status to predict adverse pregnancy outcomes among HIV-infected and HIV-uninfected women in Malawi. This innovation was explored in the Pregnancy Outcomes in the Era of Universal Antiretroviral Treatment in Sub-Saharan Africa (POISE) study conducted in Blantyre, Malawi.

The study found that MTC was inversely associated with low birth weight (LBW) and preterm birth (PTB), after controlling for HIV status, age, socioeconomic status, and hemoglobin levels. Similarly, higher body mass index (BMI) was significantly associated with lower odds of PTB, LBW, and small-for-gestational age (SGA). These findings suggest that measuring MTC and BMI could be practical tools in resource-constrained settings for identifying women at risk of adverse pregnancy outcomes.

By incorporating MTC and BMI measurements into routine maternal health assessments, healthcare providers can identify women who may require additional support and interventions to improve their nutritional status and reduce the risk of adverse pregnancy outcomes. This innovation has the potential to enhance access to maternal health services by providing a simple and cost-effective method for identifying at-risk women, particularly in resource-limited settings like Malawi.

AI Innovations Description

The recommendation based on the study findings is to use mid-thigh circumference (MTC) as an indicator of nutritional status to predict adverse pregnancy outcomes among HIV-infected and HIV-uninfected women in Malawi. The study found that MTC was inversely associated with low birth weight (LBW) and preterm birth (PTB), after controlling for HIV status, age, socioeconomic status, and hemoglobin. Similarly, higher body mass index (BMI) was significantly associated with lower odds of PTB, LBW, and small-for-gestational age (SGA).

The ease of measuring MTC makes it a practical tool in resource-constrained settings for identifying women at risk of adverse pregnancy outcomes. By incorporating MTC measurements into routine antenatal care, healthcare providers can identify women who may require additional support and interventions to improve maternal and fetal health outcomes. This innovation can help improve access to maternal health by providing a simple and cost-effective method for assessing nutritional status and identifying high-risk pregnancies.

AI Innovations Methodology

Based on the provided information, here are some potential recommendations for improving access to maternal health:

1. Implement mid-thigh circumference (MTC) measurement: Based on the study’s findings, MTC can be used as an indicator of nutritional status to predict adverse pregnancy outcomes. Implementing MTC measurement as part of routine antenatal care can help identify women at risk and provide appropriate interventions.

2. Strengthen nutrition education and counseling: Promote nutrition education and counseling programs for pregnant women, focusing on the importance of maintaining a healthy diet and adequate nutrient intake during pregnancy. This can be done through antenatal care visits, community health programs, and mobile health platforms.

3. Enhance antenatal care services: Improve access to antenatal care services by increasing the number of health facilities, extending their operating hours, and ensuring availability of skilled healthcare providers. This can help ensure that pregnant women receive regular check-ups, screenings, and appropriate interventions.

4. Strengthen referral systems: Establish effective referral systems between primary healthcare facilities and higher-level facilities equipped to handle complications during pregnancy and childbirth. This can ensure timely access to emergency obstetric care for women with high-risk pregnancies.

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: Determine the specific population group that will be the focus of the simulation, such as pregnant women in a particular region or healthcare facility.

2. Collect baseline data: Gather relevant data on the current state of maternal health access, including indicators such as antenatal care coverage, nutritional status, and pregnancy outcomes. This can be done through surveys, medical records, and existing databases.

3. Define simulation parameters: Determine the variables and parameters that will be used to simulate the impact of the recommendations. This may include factors such as the number of additional healthcare facilities, the percentage of pregnant women receiving nutrition education, and the improvement in referral systems.

4. Develop a simulation model: Use statistical or mathematical modeling techniques to create a simulation model that incorporates the defined parameters. This model should simulate the potential changes in access to maternal health services and the resulting impact on pregnancy outcomes.

5. Run simulations: Run multiple simulations using different combinations of parameters to assess the potential impact of the recommendations. This can help identify the most effective strategies for improving access to maternal health.

6. Analyze results: Analyze the simulation results to determine the projected changes in access to maternal health services and the potential improvements in pregnancy outcomes. This can involve comparing baseline data with simulated data and calculating relevant indicators and statistics.

7. Validate and refine the model: Validate the simulation model by comparing the simulated results with real-world data, if available. Refine the model based on feedback and further analysis to improve its accuracy and reliability.

8. Communicate findings: Present the findings of the simulation study in a clear and concise manner, highlighting the potential impact of the recommendations on improving access to maternal health. This can help inform decision-making and guide the implementation of interventions.

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

Autor

Dima Health

Statistics:

Citations: 1

Identifiers:

DOI: 10.1186/s12884-021-04118-4

Research Areas:

Community Interventions, Health System and Policy, Infectious Diseases, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health, Social Determinants

Study Countries:

Malawi

Study Design:

Case-Control Study, Cohort Study, Cross Sectional Study

Study Approach:

Quantitative

Participants Gender:

Female

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