Growth and health outcomes at school age in HIV-exposed, uninfected Zambian children: Follow-up of two cohorts studied in infancy

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Study Justification:
This study aimed to investigate the long-term effects of early HIV exposure on the growth and health outcomes of HIV-exposed, uninfected (HEU) children in Zambia. The justification for this study is that previous research has shown that HEU children have poorer growth and health outcomes compared to their HIV-unexposed, uninfected (HUU) counterparts. However, there is limited information on the longer-term effects of early HIV exposure on these children. This study aimed to fill this knowledge gap and provide insights into the potential factors contributing to the poorer outcomes observed in HEU children.
Highlights:
– The study recruited 111 HEU and 279 HUU children aged 6-12 years in Zambia.
– Anthropometric measures showed that HEU children had lower hip circumference and mid-upper-arm circumference compared to HUU children.
– HEU children also had lower total, trunk, and limb fat percentages.
– More HEU children reported minor illnesses and were prescribed medication at the time of the visit.
– HEU children had lower math grades compared to HUU children, even after adjusting for socioeconomic variables.
– Biochemical markers did not show significant differences between the two groups.
Recommendations:
Based on the findings of this study, the following recommendations can be made:
1. Further research is needed to understand the reasons for lower school grades among HEU children.
2. Interventions should focus on improving the socioeconomic status of HEU children to address the observed differences in growth and health outcomes.
3. Health programs should provide support and resources to HEU children to address their higher prevalence of minor illnesses and medication use.
Key Role Players:
To address the recommendations, the following key role players are needed:
1. Researchers and scientists to conduct further research on the factors influencing school grades in HEU children.
2. Policy makers and government officials to develop and implement interventions aimed at improving the socioeconomic status of HEU children.
3. Healthcare professionals to provide support and resources to HEU children to address their health needs.
Cost Items:
While the actual cost of implementing the recommendations cannot be estimated without detailed planning, the following cost items should be considered in the budget:
1. Research funding for further studies on the factors influencing school grades in HEU children.
2. Resources and support programs to improve the socioeconomic status of HEU children, such as educational initiatives and financial assistance.
3. Healthcare services and medication provision for HEU children to address their health needs.
Please note that the above cost items are general suggestions and may vary depending on the specific context and requirements of the interventions.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is relatively strong, but there are some limitations. The study design is observational, which means causality cannot be determined. Additionally, the sample size is relatively small, which may limit the generalizability of the findings. To improve the evidence, a larger sample size could be used to increase statistical power and improve generalizability. Additionally, a randomized controlled trial could be conducted to establish causality.

Background: Early growth and health of HIV-exposed, uninfected (HEU) children is poorer than that of their HIV-unexposed, uninfected (HUU) counterparts but there is little information about longer term effects of early HIV exposure. We previously recruited two cohorts of HEU and HUU Zambian infants and documented the poorer infant growth and health of the HEU compared to the HUU children. We followed up HEU and HUU children from these cohorts when they were school-aged and compared their growth, health, biochemical markers of acute or chronic disease, and school grades. Methods: We recruited 111 HEU and 279 HUU children aged 6-12 years. We measured anthropometry, determined health by questionnaire and clinical examination, viewed the child’s most recent school report, and measured blood pressure, haemoglobin (Hb), HbA1c, glucose, cholesterol, and C-reactive protein (CRP). Results: Anthropometric measures were lower among HEU than HUU children, significantly so for hip circumference (age- and sex-adjusted difference -1.74 cm; 95 % confidence interval (CI) -3.24, -0.24; P = 0.023) and mid-upper-arm circumference (adjusted difference -0.63 cm, 95 % CI -1.23, -0.04; P = 0.037) and with borderline effects for body mass index, thigh circumference and subscapular skinfolds. HEU children had significantly lower total, trunk, and limb fat percentages. All anthropometric and body composition differences became non-significant after adjustment for sociodemographic variables which differed between HEU and HUU children. More HEU than HUU children reported minor illnesses and were prescribed medication at the time of visit. There were no differences in biochemical markers between groups. HEU children had lower math grades than HUU children even after adjustment for socioeconomic variables. Conclusions: Although HEU children were smaller and had lower percent fat than HUU children, this appeared to be due mainly to their poorer socioeconomic status. Reasons for lower school grades require further research.

The children were previous participants in one of two research projects conducted by the team in Chilenje, Lusaka, Zambia. HIV-infected and uninfected mothers of the children in the Breastfeeding and Postpartum Health (BFPH) longitudinal cohort study [11] were recruited when pregnant. BFPH children were born between 2001 and 2004. Detailed information on maternal and infant health, infant feeding, and infant growth was collected until age 16 weeks. HIV status of all mothers was known through antenatal testing at the local government clinic. At the time of the study the only antiretroviral regimen available for prevention of mother-to-child transmission (PMTCT) in the area was perinatal nevirapine to both mother and infant. The median duration of exclusive breastfeeding was 6 weeks for HIV-infected women and 9 weeks for HIV-uninfected women [9] and the median duration of any breastfeeding was 17 months and 19 months for these groups, respectively (unpublished). The only sociodemographic factors which differed between HIV-infected and uninfected women were that the infected women were slightly older and less likely to be primiparous. Children in the Chilenje Infant Growth, Nutrition and Infection Study (CIGNIS) trial were born between 2005 and 2007. They were recruited at age 6 months and participated until they were 18 months in a randomised controlled trial comparing two locally made complementary foods differing in micronutrient content [10]. At the time of the study perinatal nevirapine was the local regimen for PMTCT. ART was available only for adults with CD4 count < 200 cells/μL until towards the end of the study when the cut-off was changed to < 350 cells/μL; few of the CIGNIS children’s mothers were on any ART. Agreement to HIV-testing of children by antibodies at 18 months, the only test available locally throughout most of the trial, was an inclusion criterion of the study. Children who died or defaulted before 18 months were not tested for HIV. Knowledge of maternal HIV status was not required, although antenatal HIV status from routine government health services was known for 90 % of the women. HIV-infected mothers were older than uninfected mothers, were of lower education and more likely to be in the lowest tertile of an asset index. HIV-infected mothers were less likely to initiate breastfeeding and stopped earlier compared to uninfected mothers [18]. Follow-up for both cohorts of children was March to May 2014, a time chosen based on availability of staff and funding. We used a combination of methods to find the children. First, we remain in touch with some of the mothers through a women’s support group set up originally in Chilenje by mothers in the BFPH study. Second, we tried addresses and mobile phone numbers from the original studies. This was more successful for CIGNIS than BFPH mothers since CIGNIS was more recent and families were thus less likely to have moved or changed phone numbers; in addition, mobile phones were less common at the time of the earlier BFPH study and only wealthier families owned them. Finally, we asked mothers we did find if they were aware of addresses or phone numbers of any other mothers and children from the studies. Parents and children were invited to Chilenje clinic for a scheduled individual assessment. The visit included demographic, socioeconomic, and morbidity history data by questionnaire and a clinical examination. In addition to general health, outcomes measured focussed on growth and biochemical markers of acute or chronic disease since these are potential concerns among HEU children. Anthropometry (weight, height, mid-upper arm circumference (MUAC), waist, hip and thigh circumferences, triceps and subscapular skinfolds) was measured by an experienced anthropometrist (MC) in triplicate by standard methods [19]; the median was used in analyses. Height and BMI Z scores were calculated using the World Health Organization standards for children aged 5–19 years [20]. Body composition was measured by bioelectrical impedance (Tanita BC418, Chasmors, London, UK) only in children over 7 years since the machine is not designed for younger children. The machine uses internal equations to calculate total and individual limb and trunk lean and fat mass; since fat and lean are calculated by difference, we focussed on percent fat. Blood pressure was measured in all children using a Diamond Mercury B.P. Apparatus (India). Fingerprick blood samples were used for measurement of haemoglobin (Hb), HbA1c, and glucose, all using hand-held instruments from Hemocue (Dronfield, UK). There was a problem with the glucose monitor during part of the study so many results are missing. Venous blood samples were collected in plain tubes for measurement of total cholesterol using a commercial kit on a Pointe 180 analyser (Bactlabs, Nairobi, Kenya) and serum C-reactive protein (CRP), an indicator of systemic inflammation, by commercial ELISA kit (AssayPro, St Charles, MO, USA). At follow-up parents were asked whether they or their child had been tested for HIV since the previous BFPH or CIGNIS study. The most recent test result was used to define child HIV status. HIV-infected children had all measurements taken for ethical reasons but were excluded from statistical analyses. Since we were primarily interested in children’s HIV exposure in utero or through breastfeeding, children’s HIV exposure was defined by mother’s status during the earlier study. We excluded from analysis children of the 70 CIGNIS mothers of unknown status. Children of HIV-uninfected mothers who had never themselves been tested for HIV were assumed to be HUU. Children of HIV-infected mothers who had not themselves been tested were included as HEU since we expected that by school age most HIV-infected children would show symptoms. The study clinical officer (JS) examined all children and would have referred any children suspected of HIV infection to local services but did not, in fact, find any likely HIV-positive children other than those already known to be positive. We also conducted restricted analyses including as HEU only children confirmed HIV-negative. Mothers were asked to bring their child’s most recent school report to the clinic visit. For some of the younger children the schools did not provide grades, only an indication of how children were performing according to expectation, so these reports were omitted. We took from the reports the children’s grades in English (the language of instruction in Zambian schools) and math/arithmetic as well as the maximum achievable grades in these subjects according to the particular school’s grading system. Grades were expressed as a percent of the maximum achievable. Data were double-entered into Access databases, cross-checked, cleaned and imported into Stata for analysis. Using principal components analysis [21], an asset index was generated from data on possession of car, bicycle, radio, television, phone, fan and refrigerator plus type of toilet, household water source and whether they owned, rented or shared their accommodation. This index was divided into tertiles of low, middle and high socioeconomic status. Primary analyses used linear regression to compare HEU and HUU children for all outcomes: anthropometry, total, trunk and limb fat percentage, blood pressure, blood Hb, HbA1c, glucose and CRP, and school grades. These analyses were then adjusted for sociodemographic factors which differed between HUU and HEU children. We also compared baseline characteristics from the original studies which differed between children who were and were not later followed up in order to adjust for these in a missing at random analysis [22]. The sample size was determined pragmatically by the number of children we could find with the limited available time and funds. With the number of children who were available, and given there were about 2 HUU controls per HEU child, we could detect, at 5 % significance, differences in outcomes between groups of about a third of a standard deviation (SD) at 80 % power and 0.4 SD at 90 % power. The study was approved by the University of Zambia Biomedical Research Ethics Committee and the ethics committee of the London School of Hygiene and Tropical Medicine. Parents provided written informed consent for their children to participate. Children who could not read provided verbal assent and those who could read and write also signed a written assent form; this protocol was considered locally appropriate for school-aged children. Particular care was given to ensure confidentiality of HIV status, including that no child was provided with information about his/her mother’s HIV status. Children requiring medical intervention were referred to the local government clinic on the same site as the project clinic. HIV-infected children were included in all data collection even though their data were not analysed and they were referred to local HIV services if not already attending these.

Based on the provided information, it is difficult to identify specific innovations for improving access to maternal health. The description focuses on the growth and health outcomes of HIV-exposed, uninfected children in Zambia. However, to improve access to maternal health, some potential innovations could include:

1. Mobile health (mHealth) applications: Developing mobile applications that provide pregnant women with information on prenatal care, nutrition, and maternal health services. These apps can also send reminders for appointments and medication adherence.

2. Telemedicine: Implementing telemedicine programs that allow pregnant women in remote areas to consult with healthcare providers through video calls. This can help overcome geographical barriers and provide access to specialized care.

3. Community health workers: Training and deploying community health workers to provide education, support, and basic healthcare services to pregnant women in underserved areas. These workers can also help with referrals to higher-level healthcare facilities when needed.

4. Maternal health clinics: Establishing dedicated maternal health clinics that provide comprehensive prenatal care, including regular check-ups, screenings, and counseling services. These clinics can be equipped with necessary medical equipment and staffed by skilled healthcare professionals.

5. Health financing schemes: Implementing innovative health financing schemes, such as micro-insurance or conditional cash transfer programs, to improve access to maternal health services for low-income women. These schemes can help reduce financial barriers and ensure affordability of care.

It is important to note that these recommendations are general and may need to be adapted to the specific context and challenges faced in improving access to maternal health in Zambia.
AI Innovations Description
Based on the provided description, the recommendation to improve access to maternal health is to focus on addressing the socioeconomic factors that contribute to poorer growth and health outcomes in HIV-exposed, uninfected (HEU) children compared to HIV-unexposed, uninfected (HUU) children. This can be achieved through the following steps:

1. Enhance maternal support programs: Implement programs that provide comprehensive support to HIV-infected and uninfected mothers, including access to healthcare services, education on infant feeding and nutrition, and counseling on the importance of early childhood development.

2. Improve access to antiretroviral therapy (ART): Ensure that all HIV-infected mothers have access to ART for prevention of mother-to-child transmission (PMTCT) to reduce the risk of HIV transmission to their infants and improve overall maternal health.

3. Strengthen early childhood nutrition interventions: Implement interventions that promote optimal nutrition during pregnancy and early childhood, including breastfeeding support, access to nutrient-rich complementary foods, and micronutrient supplementation.

4. Enhance healthcare infrastructure: Invest in improving healthcare infrastructure, particularly in underserved areas, to ensure that mothers and children have access to quality healthcare services, including regular check-ups, immunizations, and treatment for minor illnesses.

5. Promote maternal education and empowerment: Implement programs that focus on improving maternal education and empowerment, including access to education and vocational training, to enhance socioeconomic status and improve overall maternal and child health outcomes.

By addressing these recommendations, it is possible to improve access to maternal health and ultimately enhance the growth and health outcomes of HEU children, reducing the disparities between HEU and HUU children.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations to improve access to maternal health:

1. Strengthening antenatal care services: Enhance the quality and availability of antenatal care services to ensure that pregnant women receive comprehensive care, including HIV testing, counseling, and prevention of mother-to-child transmission (PMTCT) interventions.

2. Improving access to HIV testing and treatment: Implement strategies to increase HIV testing rates among pregnant women and ensure timely initiation of antiretroviral therapy (ART) for HIV-positive mothers. This will help reduce the risk of mother-to-child transmission and improve the health outcomes of HIV-exposed, uninfected children.

3. Enhancing postpartum care: Develop and implement postpartum care programs that focus on the physical and mental well-being of mothers, including support for breastfeeding, nutrition, and family planning.

4. Strengthening health systems: Invest in improving the overall health system infrastructure, including healthcare facilities, equipment, and human resources. This will help ensure that maternal health services are accessible, available, and of high quality.

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

1. Define the indicators: Identify key indicators that reflect access to maternal health, such as the percentage of pregnant women receiving antenatal care, the percentage of HIV-positive pregnant women receiving PMTCT interventions, and the percentage of women accessing postpartum care.

2. Collect baseline data: Gather data on the current status of these indicators in the target population. This can be done through surveys, interviews, or analysis of existing health records.

3. Develop a simulation model: Create a mathematical or statistical model that simulates the impact of the recommendations on the selected indicators. The model should take into account factors such as population size, healthcare infrastructure, and the effectiveness of the interventions.

4. Input intervention scenarios: Define different scenarios that represent the implementation of the recommendations. For example, one scenario could assume a 20% increase in antenatal care coverage, while another scenario could assume improved access to HIV testing and treatment.

5. Run simulations: Use the simulation model to calculate the projected impact of each intervention scenario on the selected indicators. This can be done by adjusting the relevant parameters in the model and running multiple iterations to account for variability.

6. Analyze results: Analyze the simulation results to determine the potential impact of each intervention scenario on improving access to maternal health. Compare the outcomes of different scenarios to identify the most effective strategies.

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

By following this methodology, policymakers and healthcare providers can gain insights into the potential impact of different interventions on improving access to maternal health and make informed decisions on resource allocation and program implementation.

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