The developmental effects of HIV and alcohol: A comparison of gestational outcomes among babies from South African communities with high prevalence of HIV and alcohol use

AIDS Research and Therapy, Volume 14, No. 1, Year 2017

Interprétation

Background: There is growing evidence of the negative impact of alcohol on morbidity and mortality of individuals living with HIV but limited evidence of in utero effects of HIV and alcohol on exposure on infants. Methods: We conducted a population-based birth cohort study (N=667 mother-infant dyads) in South Africa to investigate whether maternal alcohol use and HIV affected gestational outcomes. Descriptive data analysis was conducted for all variables using frequency distributions, measures of central tendency, and estimates of variance. Hierarchical multiple regression was conducted to determine whether maternal alcohol use, maternal HIV status and other risk factors (socioeconomic status, smoking, depression) predicted infant outcomes. Results: Our results showed severity of recent alcohol use and lifetime alcohol use predicted low birth weight. Similarly lifetime alcohol use predicted shorter infant length, smaller head length, smaller head circumference, and early gestational age. However, HIV status was not a significant predictor of gestational outcomes. Conclusions: The unexpected finding that maternal HIV status did not predict any of the gestational outcomes may be due to high rates of ART usage among HIV-infected mothers. The potentially negative effects of HIV on gestational outcomes may have been attenuated by improved maternal health due to high coverage of antiretroviral treatment in South Africa. Interventions are needed to reduce alcohol consumption among pregnant mothers and to support healthy growth and psychosocial development of infants. Data was collected from an investigation of child health, called the Drakenstein Child Health Study (DCHS). The DCHS consisted of a multidisciplinary birth cohort study following mother–child dyads from the prenatal period through to five years of age [29, 30]. The aim of DCHS is to investigate the epidemiology, etiology, and risk factors of childhood respiratory disease and the determinants of child health in a low socioeconomic area of South Africa [30]. The study investigates the role and interaction of possible risk factors in 7 areas (environmental, infectious, nutritional, genetic, psychosocial, maternal and immunological risk factors) that may impact child health. Pregnant women were recruited from two primary care clinics in the Drakenstein sub-district near Cape Town, South Africa between March 2012 and September 2014. Data collection occurred at these two clinics (maternal data) and at a central hospital (newborn outcomes). Participants were enrolled in the study at 20–28 weeks gestation upon presenting for antenatal booking. The mothers were followed throughout pregnancy and mother–child dyads are followed until five years after birth. Data collection for the DCHS remains ongoing. Throughout the study, participants receive regular medical care as per the South Africa national program and expanded program for immunization (EPI) schedule. The DCHS is located in the Drakenstein area, a peri-urban area, 60 km outside Cape Town, South Africa with a population of approximately 200,000. The community is stable, with low levels of immigration or emigration. The local economy is based around commercial agriculture and light industry. More than 90% of the population access health care in the public sector including antenatal and child health services [31]. This area has a well-established, free primary health care system, with high coverage for childhood immunizations. The public health system is comprised of 23 primary health care clinics and one centralized hospital where all births and all hospital-based pediatric care, including admissions occur [30]. To be eligible for the study, participants were: (a) over age 18, (b) pregnant, (c) 20–28 weeks gestation, and (d) receiving antenatal care at a participating study site. The two primary clinics were TC Newman clinic (serving a predominantly “Coloured” or mixed ancestry community) and Mbekweni clinic (serving a predominantly black African community). Exclusion criteria were minimal in order to maximize generalizability, and focused primarily on those individuals who did not live in the region (and could not readily complete follow-up assessments) or those who were intending to move out of the district within the following 2 years. The cohort comprised mothers presenting in an unfiltered manner to the antenatal services and were not selected for any clinical risk factors or exposures. The study was approved by the Faculty of Health Sciences, Human Research Ethics Committee, University of Cape Town (401/2009), and by the Western Cape Provincial Health Research committee. Written informed parental consent was obtained from all participants at the time of enrolment. Demographic data was collected regarding participant age, education, employment, and socioeconomic status (SES). For our purposes, a composite SES score was developed in order to categorize participants into quartiles based on their relative SES. This composite score is calculated based on current employment status and standardized scores of educational attainment, household income, and a composite asset index based on access to household resources, amenities, and market access. Participants were categorized as being of low, low-moderate, moderate-high, or high SES based on their relative composite SES score. Maternal HIV status was determined using an HIV ELISA test, which all mothers in South Africa receive during pregnancy due to the high prevalence of HIV. Those who tested positive for HIV self-reported whether she was prescribed antiretroviral therapy. Mothers who were newly diagnosed received a second confirmatory HIV ELISA test and were referred for counseling and evaluation for treatment initiation as per standard management guidelines. All babies were born at a central hospital that serves the communities of both clinics. Trained clinical staff recorded newborn birth weight (kilograms) at the time of delivery, using a digital scale with a precision level of 10 g. Gestational age (weeks), head circumference and length in centimeters were also recorded at birth. We defined low birth weight and very low birth weight according to World Health Organization’s (WHO’s) parameters for weight for age, with low birth weight defined as less than 2.5 kilograms and very low birth weight as less than 1.5 kg [32]. Percentile for infant birth weight was then calculated using the formula proposed by Mikolajcyzk et al. [33]. This formula enabled us to calculate the birth weight percentile based on gestational week of each infant. We used full-term, low-risk infants (N = 100) as the reference group for anchoring our percentile estimates. This method for estimating fetal weight percentiles has a better ability to predict adverse perinatal outcomes than other unadjusted and fully individualized formulas [33]. Risk of substance use was assessed using the alcohol, smoking and substance involvement screening test (ASSIST) at the second antenatal visit (28–32 weeks gestation). This tool was developed by the WHO to detect psychoactive substance use and related disorders in primary care settings. It has shown good reliability, feasibility and validity in international, multisite studies [34, 35], and is useful for identifying risk of substance dependence in poly-substance abusers with varying degrees of psychopathology. Seven items are included to assess alcohol and other drug use across 10 categories (i.e., tobacco products; alcoholic beverages; cannabis; cocaine; amphetamine-type stimulants; inhalants, sedatives or sleeping pills; hallucinogens; opioids; and a general category entitled “other”, in which the participant is required to specify the substance used). ASSIST scores from 0 to 10 for alcohol and 0–3 for illicit drugs indicating low-risk, scores from 11 to 26 for alcohol and 4–26 for illicit drugs indicate moderate-risk and scores above 26 indicate high risk of severe problems, with the likelihood of substance dependence. The higher the score, the greater substance-related risk. The ASSIST has good reliability scores and has been validated in numerous populations [36], as well as primary care settings [37]. For our purposes, only data for alcohol were extracted from the ASSIST, as reports of other substance use were negligible with the exception of tobacco where a biochemical measure of exposure was used as detailed below. Lifetime alcohol use was a dichotomous variable coded as 0, 1. Past 3 month alcohol use severity was calculated as a continuous variable using standard scoring techniques to calculate a sum score based on past 3-month alcohol use frequency, craving, consequences, and other symptoms of alcohol use disorders as detailed above [38]. Biochemical verification of smoking status was determined through cotinine urine analysis collected on the same day as the baseline interview. Cotinine is a nicotine metabolite that is measurable among people who smoke, use smokeless tobacco, use nicotine products, or are exposed to environmental tobacco smoke. An antenatal urine cotinine cut-off value of 500 was used to distinguish active smokers from non-smokers [39]. The Beck Depression Inventory-II (BDI-II) [40] was used to assess depressive symptomatology. This is a widely used self-report measure of the severity of depressive symptoms with strong internal consistency and concurrent validity in clinical and non-clinical samples [41, 42]. Each item is assessed on a severity scale ranging from 0, “absence of symptoms”, to 3 “severe, often with functional impairment”. A total score was obtained by summing individual item responses, with higher scores indicative of more severe depressive symptoms. Descriptive data analysis was conducted for all variables using frequency distributions, measures of central tendency, and estimates of variance. Hierarchical multiple regression was conducted to determine whether maternal HIV status, alcohol use, and other risk factors (socioeconomic status or SES, smoking, depression) predicted infant outcomes. Infant outcomes included birth weight percentile, length, head circumference, and gestational age. All outcomes were entered as continuous variables in regression analyses. The analyses were conducted in a step-wise fashion to examine the unique contributions for each block of predictor variables. The four steps/blocks of variables in the regression analyses included (in order): (1) HIV status, (2) SES score, BDI-II score, and smoking status, (3) alcohol use, and (4) interaction variables (HIV by alcohol use and HIV by smoking status). We examined separate models using the predictors past 3-month alcohol use severity and lifetime alcohol. All regression models were examined for violations of normality, linearity, homoscedasticity, redundancy, and multicollinearity. Data performed excellently on all criteria except for length of gestation. Length of gestation was non-normal (skew = −2.04, kurtosis = 7.38) and the log of this variable was used in the analysis. Statistical significance was set at the 0.05 level.

Résumé de l’IA

Study Justification:

– The study aims to investigate the effects of maternal alcohol use and HIV on gestational outcomes.
– Limited evidence exists on the in utero effects of HIV and alcohol on infants.
– Understanding the impact of these factors is crucial for developing interventions to support healthy growth and development of infants.

Study Highlights:

– The study found that severity of recent alcohol use and lifetime alcohol use predicted low birth weight, shorter infant length, smaller head length, smaller head circumference, and early gestational age.
– Maternal HIV status was not found to be a significant predictor of gestational outcomes.
– The high rates of antiretroviral treatment usage among HIV-infected mothers may have attenuated the potentially negative effects of HIV on gestational outcomes.

Study Recommendations:

– Interventions are needed to reduce alcohol consumption among pregnant mothers.
– Support should be provided to promote healthy growth and psychosocial development of infants.

Key Role Players:

– Researchers and scientists involved in maternal and child health studies.
– Healthcare providers, including doctors, nurses, and midwives.
– Public health officials and policymakers.
– Community organizations and support groups.

Cost Items for Planning Recommendations:

– Education and awareness campaigns on the risks of alcohol consumption during pregnancy.
– Training programs for healthcare providers on identifying and addressing alcohol use among pregnant women.
– Development and implementation of support programs for pregnant women to reduce alcohol consumption.
– Monitoring and evaluation of interventions to assess their effectiveness.
– Research and data collection to further understand the impact of alcohol and HIV on gestational outcomes.

Force de la preuve

N/A

Abstrait

Data was collected from an investigation of child health, called the Drakenstein Child Health Study (DCHS). The DCHS consisted of a multidisciplinary birth cohort study following mother–child dyads from the prenatal period through to five years of age [29, 30]. The aim of DCHS is to investigate the epidemiology, etiology, and risk factors of childhood respiratory disease and the determinants of child health in a low socioeconomic area of South Africa [30]. The study investigates the role and interaction of possible risk factors in 7 areas (environmental, infectious, nutritional, genetic, psychosocial, maternal and immunological risk factors) that may impact child health. Pregnant women were recruited from two primary care clinics in the Drakenstein sub-district near Cape Town, South Africa between March 2012 and September 2014. Data collection occurred at these two clinics (maternal data) and at a central hospital (newborn outcomes). Participants were enrolled in the study at 20–28 weeks gestation upon presenting for antenatal booking. The mothers were followed throughout pregnancy and mother–child dyads are followed until five years after birth. Data collection for the DCHS remains ongoing. Throughout the study, participants receive regular medical care as per the South Africa national program and expanded program for immunization (EPI) schedule. The DCHS is located in the Drakenstein area, a peri-urban area, 60 km outside Cape Town, South Africa with a population of approximately 200,000. The community is stable, with low levels of immigration or emigration. The local economy is based around commercial agriculture and light industry. More than 90% of the population access health care in the public sector including antenatal and child health services [31]. This area has a well-established, free primary health care system, with high coverage for childhood immunizations. The public health system is comprised of 23 primary health care clinics and one centralized hospital where all births and all hospital-based pediatric care, including admissions occur [30]. To be eligible for the study, participants were: (a) over age 18, (b) pregnant, (c) 20–28 weeks gestation, and (d) receiving antenatal care at a participating study site. The two primary clinics were TC Newman clinic (serving a predominantly “Coloured” or mixed ancestry community) and Mbekweni clinic (serving a predominantly black African community). Exclusion criteria were minimal in order to maximize generalizability, and focused primarily on those individuals who did not live in the region (and could not readily complete follow-up assessments) or those who were intending to move out of the district within the following 2 years. The cohort comprised mothers presenting in an unfiltered manner to the antenatal services and were not selected for any clinical risk factors or exposures. The study was approved by the Faculty of Health Sciences, Human Research Ethics Committee, University of Cape Town (401/2009), and by the Western Cape Provincial Health Research committee. Written informed parental consent was obtained from all participants at the time of enrolment. Demographic data was collected regarding participant age, education, employment, and socioeconomic status (SES). For our purposes, a composite SES score was developed in order to categorize participants into quartiles based on their relative SES. This composite score is calculated based on current employment status and standardized scores of educational attainment, household income, and a composite asset index based on access to household resources, amenities, and market access. Participants were categorized as being of low, low-moderate, moderate-high, or high SES based on their relative composite SES score. Maternal HIV status was determined using an HIV ELISA test, which all mothers in South Africa receive during pregnancy due to the high prevalence of HIV. Those who tested positive for HIV self-reported whether she was prescribed antiretroviral therapy. Mothers who were newly diagnosed received a second confirmatory HIV ELISA test and were referred for counseling and evaluation for treatment initiation as per standard management guidelines. All babies were born at a central hospital that serves the communities of both clinics. Trained clinical staff recorded newborn birth weight (kilograms) at the time of delivery, using a digital scale with a precision level of 10 g. Gestational age (weeks), head circumference and length in centimeters were also recorded at birth. We defined low birth weight and very low birth weight according to World Health Organization’s (WHO’s) parameters for weight for age, with low birth weight defined as less than 2.5 kilograms and very low birth weight as less than 1.5 kg [32]. Percentile for infant birth weight was then calculated using the formula proposed by Mikolajcyzk et al. [33]. This formula enabled us to calculate the birth weight percentile based on gestational week of each infant. We used full-term, low-risk infants (N = 100) as the reference group for anchoring our percentile estimates. This method for estimating fetal weight percentiles has a better ability to predict adverse perinatal outcomes than other unadjusted and fully individualized formulas [33]. Risk of substance use was assessed using the alcohol, smoking and substance involvement screening test (ASSIST) at the second antenatal visit (28–32 weeks gestation). This tool was developed by the WHO to detect psychoactive substance use and related disorders in primary care settings. It has shown good reliability, feasibility and validity in international, multisite studies [34, 35], and is useful for identifying risk of substance dependence in poly-substance abusers with varying degrees of psychopathology. Seven items are included to assess alcohol and other drug use across 10 categories (i.e., tobacco products; alcoholic beverages; cannabis; cocaine; amphetamine-type stimulants; inhalants, sedatives or sleeping pills; hallucinogens; opioids; and a general category entitled “other”, in which the participant is required to specify the substance used). ASSIST scores from 0 to 10 for alcohol and 0–3 for illicit drugs indicating low-risk, scores from 11 to 26 for alcohol and 4–26 for illicit drugs indicate moderate-risk and scores above 26 indicate high risk of severe problems, with the likelihood of substance dependence. The higher the score, the greater substance-related risk. The ASSIST has good reliability scores and has been validated in numerous populations [36], as well as primary care settings [37]. For our purposes, only data for alcohol were extracted from the ASSIST, as reports of other substance use were negligible with the exception of tobacco where a biochemical measure of exposure was used as detailed below. Lifetime alcohol use was a dichotomous variable coded as 0, 1. Past 3 month alcohol use severity was calculated as a continuous variable using standard scoring techniques to calculate a sum score based on past 3-month alcohol use frequency, craving, consequences, and other symptoms of alcohol use disorders as detailed above [38]. Biochemical verification of smoking status was determined through cotinine urine analysis collected on the same day as the baseline interview. Cotinine is a nicotine metabolite that is measurable among people who smoke, use smokeless tobacco, use nicotine products, or are exposed to environmental tobacco smoke. An antenatal urine cotinine cut-off value of 500 was used to distinguish active smokers from non-smokers [39]. The Beck Depression Inventory-II (BDI-II) [40] was used to assess depressive symptomatology. This is a widely used self-report measure of the severity of depressive symptoms with strong internal consistency and concurrent validity in clinical and non-clinical samples [41, 42]. Each item is assessed on a severity scale ranging from 0, “absence of symptoms”, to 3 “severe, often with functional impairment”. A total score was obtained by summing individual item responses, with higher scores indicative of more severe depressive symptoms. Descriptive data analysis was conducted for all variables using frequency distributions, measures of central tendency, and estimates of variance. Hierarchical multiple regression was conducted to determine whether maternal HIV status, alcohol use, and other risk factors (socioeconomic status or SES, smoking, depression) predicted infant outcomes. Infant outcomes included birth weight percentile, length, head circumference, and gestational age. All outcomes were entered as continuous variables in regression analyses. The analyses were conducted in a step-wise fashion to examine the unique contributions for each block of predictor variables. The four steps/blocks of variables in the regression analyses included (in order): (1) HIV status, (2) SES score, BDI-II score, and smoking status, (3) alcohol use, and (4) interaction variables (HIV by alcohol use and HIV by smoking status). We examined separate models using the predictors past 3-month alcohol use severity and lifetime alcohol. All regression models were examined for violations of normality, linearity, homoscedasticity, redundancy, and multicollinearity. Data performed excellently on all criteria except for length of gestation. Length of gestation was non-normal (skew = −2.04, kurtosis = 7.38) and the log of this variable was used in the analysis. Statistical significance was set at the 0.05 level.

Matériaux

N/A

Innovations

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

1. Mobile health (mHealth) interventions: Develop mobile applications or text messaging services to provide pregnant women with information and reminders about prenatal care, nutrition, and healthy behaviors. This can help improve access to important health information, especially in low-resource settings.

2. Community-based interventions: Implement community health worker programs to provide education and support to pregnant women in their own communities. These workers can conduct home visits, offer counseling, and connect women to healthcare services.

3. Telemedicine: Use telecommunication technology to provide remote prenatal consultations and monitoring for pregnant women who have limited access to healthcare facilities. This can help overcome geographical barriers and improve access to specialized care.

4. Integrated care models: Implement integrated care models that combine maternal health services with other healthcare services, such as HIV testing and treatment, mental health support, and substance abuse counseling. This can help address multiple health needs of pregnant women in a comprehensive and efficient manner.

5. Public-private partnerships: Foster collaborations between public healthcare providers and private sector organizations to improve access to maternal health services. This can involve leveraging private sector resources, expertise, and technology to expand healthcare infrastructure and service delivery.

6. Health education and awareness campaigns: Develop targeted campaigns to raise awareness about the importance of prenatal care, healthy behaviors during pregnancy, and the risks of alcohol use and HIV. These campaigns can be conducted through various channels, such as mass media, community events, and social media.

7. Strengthening healthcare systems: Invest in strengthening healthcare systems, particularly in low-resource settings, by improving infrastructure, training healthcare providers, and ensuring the availability of essential medicines and equipment. This can help ensure that pregnant women have access to quality maternal healthcare services.

It is important to note that the specific recommendations for improving access to maternal health should be tailored to the local context and needs of the target population.

AI Innovations Description

Based on the information provided, the recommendation to improve access to maternal health would be to implement interventions that focus on reducing alcohol consumption among pregnant mothers and supporting healthy growth and psychosocial development of infants. This recommendation is based on the findings of the study, which showed that severity of recent alcohol use and lifetime alcohol use predicted low birth weight, shorter infant length, smaller head length, smaller head circumference, and early gestational age. Maternal HIV status was not found to be a significant predictor of gestational outcomes, possibly due to high rates of antiretroviral treatment usage among HIV-infected mothers.

To implement this recommendation, healthcare providers and public health organizations can:

1. Provide education and counseling on the risks of alcohol consumption during pregnancy and the importance of abstaining from alcohol.
2. Offer support services, such as substance abuse treatment programs, for pregnant women struggling with alcohol addiction.
3. Collaborate with community organizations to raise awareness about the negative effects of alcohol on maternal and infant health.
4. Develop and distribute informational materials, such as brochures and posters, that highlight the risks of alcohol use during pregnancy and provide resources for seeking help.
5. Train healthcare providers on how to screen and identify pregnant women who may be at risk for alcohol use and provide appropriate interventions.
6. Establish referral systems to connect pregnant women with support services, such as counseling or treatment programs, if needed.
7. Conduct research and evaluation to assess the effectiveness of interventions aimed at reducing alcohol consumption among pregnant women and improving maternal and infant health outcomes.

By implementing these recommendations, it is hoped that access to maternal health will be improved, leading to better outcomes for both mothers and infants.

AI Innovations Methodology

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

1. Increase awareness and education: Implement comprehensive public health campaigns to raise awareness about the importance of maternal health and the risks associated with alcohol use during pregnancy. This can include targeted messaging in healthcare facilities, community centers, and schools.

2. Strengthen antenatal care services: Enhance antenatal care services by providing comprehensive screenings for substance use, including alcohol, and integrating interventions for pregnant women who are at risk or have a history of alcohol use. This can involve training healthcare providers on effective screening techniques and providing resources for intervention and support.

3. Improve access to substance abuse treatment: Enhance access to substance abuse treatment programs that specifically cater to pregnant women. This can involve collaborating with existing treatment centers to develop specialized programs that address the unique needs of pregnant women and provide comprehensive care for both substance abuse and maternal health.

4. Enhance social support systems: Establish support systems for pregnant women, including peer support groups and counseling services, to address the psychosocial factors that contribute to alcohol use during pregnancy. This can involve partnering with community organizations and non-profit agencies to provide resources and support networks for pregnant women.

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

1. Define outcome measures: Determine specific outcome measures that reflect improved access to maternal health, such as increased rates of antenatal care attendance, reduced rates of alcohol use during pregnancy, and improved maternal and infant health outcomes.

2. Collect baseline data: Gather baseline data on the current rates of antenatal care attendance, alcohol use during pregnancy, and maternal and infant health outcomes in the target population. This can be done through surveys, medical records, and other relevant sources of data.

3. Implement interventions: Introduce the recommended interventions, such as public health campaigns, enhanced antenatal care services, improved access to substance abuse treatment, and social support systems.

4. Monitor and evaluate: Continuously monitor the implementation of the interventions and collect data on the targeted outcome measures. This can involve regular data collection through surveys, interviews, and medical records.

5. Analyze data: Analyze the collected data to assess the impact of the interventions on the targeted outcome measures. This can be done using statistical analysis techniques to compare pre- and post-intervention data and determine any significant changes.

6. Adjust and refine: Based on the analysis of the data, make adjustments and refinements to the interventions as needed. This can involve identifying areas of improvement and implementing additional strategies to further enhance access to maternal health.

7. Repeat evaluation: Continuously repeat the evaluation process to assess the ongoing impact of the interventions and make further adjustments as necessary. This can involve periodic data collection and analysis to track progress over time.

By following this methodology, it would be possible to simulate the impact of the recommended interventions on improving access to maternal health and determine their effectiveness in achieving the desired outcomes.

Auteur

Dima Health

Statistics:

Citations: 8

Identifiers:

DOI: 10.1186/s12981-017-0153-z

Research Areas:

Community Interventions, Disparities, Genetics and Genomics, Health System and Policy, Infectious Diseases, Maternal Access, Maternal and Child Health, Mental Health, Quality of Care, Sexual and Reproductive Health, Social Determinants, Substance Abuse

Study Countries:

South Africa

Study Design:

Cohort Study, Cross Sectional Study, Grounded Theory

Study Approach:

Quantitative

Participants Gender:

Female

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