Determinants of early-life lung function in African infants

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Study Justification:
– Low lung function in early life is associated with later respiratory illness.
– Limited data on lung function in African infants despite a high prevalence of respiratory disease.
– Aim of the study is to assess the determinants of early lung function in African infants.
Study Highlights:
– Successful tests were obtained in 645/675 (95%) infants, median age of 51 (46-58) days.
– Factors associated with altered early lung function include infant size, age, male gender, maternal smoking, maternal alcohol, maternal HIV, and household benzene.
– Many of these factors are amenable to public health interventions.
– Long-term study of lung function and respiratory disease in these children is a priority to develop strategies to strengthen child health.
Study Recommendations:
– Conduct long-term study of lung function and respiratory disease in African infants to develop strategies to improve child health.
– Implement public health interventions to address factors associated with altered early lung function, such as maternal smoking, maternal alcohol, and household benzene exposure.
Key Role Players:
– Researchers and scientists to conduct the long-term study and analyze the data.
– Healthcare professionals to implement public health interventions and provide medical care.
– Policy makers to develop and implement policies to address the determinants of early lung function in African infants.
Cost Items for Planning Recommendations:
– Research funding for the long-term study, including costs for data collection, analysis, and publication.
– Funding for public health interventions, such as educational campaigns, smoking cessation programs, and measures to reduce household benzene exposure.
– Healthcare resources and infrastructure to support the implementation of interventions and provide medical care to infants and their families.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is relatively strong, as it is based on a birth cohort study with a high number of successful tests. However, there are some limitations that could be addressed to improve the evidence. Firstly, the abstract does not mention the sample size of the study, which is important for assessing the generalizability of the findings. Secondly, the abstract does not provide information on the statistical methods used to analyze the data, which makes it difficult to evaluate the robustness of the results. Additionally, the abstract does not mention any potential confounding factors that were controlled for in the analysis. To improve the evidence, it would be helpful to include these details in the abstract.

Background Low lung function in early life is associated with later respiratory illness. There is limited data on lung function in African infants despite a high prevalence of respiratory disease. Aim To assess the determinants of early lung function in African infants. Method Infants enrolled in a South African birth cohort, the Drakenstein child health study, had lung function measured at 6-10 weeks of age. Measurements, made with the infant breathing via a facemask during natural sleep, included tidal breathing, sulfur hexafluoride multiple breath washout and the forced oscillation technique. Information on antenatal and early postnatal exposures was collected using questionnaires and urine cotinine. Household benzene exposure was measured antenatally. Results Successful tests were obtained in 645/675 (95%) infants, median (IQR) age of 51 (46-58) days. Infant size, age and male gender were associated with larger tidal volume. Infants whose mothers smoked had lower tidal volumes (-1.6 mL (95% CI -3.0 to -0.1), p=0.04) and higher lung clearance index (0.1 turnovers (95% CI 0.01 to 0.3), p=0.03) compared with infants unexposed to tobacco smoke. Infants exposed to alcohol in utero or household benzene had lower time to peak tidal expiratory flow over total expiratory time ratios, 10% (95% CI -15.4% to -3.7%), p=0.002) and 3.0% (95% CI -5.2% to -0.7%, p=0.01) lower respectively compared with unexposed infants. HIVexposed infants had higher tidal volumes (1.7 mL (95% CI 0.06 to 3.3) p=0.04) compared with infants whose mothers were HIV negative. Conclusion We identified several factors including infant size, sex, maternal smoking, maternal alcohol, maternal HIV and household benzene associated with altered early lung function, many of which are factors amenable to public health interventions. Long-term study of lung function and respiratory disease in these children is a priority to develop strategies to strengthen child health.

Infants enrolled in a birth cohort study, the Drakenstein Child Health study,10 had lung function tested. This study, set in a periurban, low socioeconomic community in South Africa, aims to investigate the epidemiology and aetiology of childhood respiratory illness and the determinants of child health. Participants were enrolled at two primary care clinics, Mbekweni, serving a predominantly black African population and Newman, serving a predominantly mixed ancestry population. Lung function testing was undertaken at the local hospital. Infants underwent testing at 5–11 weeks of age corrected for prematurity (37 weeks). Infants born <32 weeks gestation or with congenital anomalies were excluded from this analysis. Mothers had spirometric lung function (Jaeger Masterscope, CareFusion, Switzerland) at the same visit, provided they had not had a respiratory infection within the last 2 weeks. Information regarding antenatal, birth and early-life exposures and events were collected by questionnaire at scheduled antenatal and study visits. These are comprehensively defined in online supplementary table S1. The socioeconomic status (SES) was defined in quartiles from lowest to highest status. This score was derived from employment status and standardised scores of educational attainment, household income, assets and market access (bank accounts, shops accessed, retail accounts); this methodology has been validated for capturing SES variation within an LMIC setting.11 LRTI was defined according to WHO criteria,12 and based on confirmatory examination by trained study staff (professional nurse and/or doctor). thoraxjnl-2015-207401supp001.pdf Maternal recurrent respiratory symptoms or low lung function was defined as at least one of doctor diagnosed asthma, chronic cough or recurrent wheeze in previous 12 months and/or low FEV1, defined as FEV1 500 ng/mL, passive smoker if urine cotinine 10–500 ng/mL and non-smoker if urine cotinine <10 ng/mL.16 Maternal urine was collected for cotinine testing at the second antenatal study visit (28–32 weeks gestation) and at birth, with the higher result used to classify smoking levels. Benzene, a household air pollutant, was measured at an antenatal home visit using a Markes thermal desorption tube left in the home for 2 weeks.17 The South African National Ambient Air Quality standard of 5 μg/m3 was used to define above and below threshold values for benzene.17 Lung function measurements included tidal breathing and flow volume loops (TBFVL), sulfur hexafluoride (SF6) multiple breath washout (MBW) and the forced oscillation technique (FOT). Infants were tested from July 2012 to December 2014 for TBFVL and MBW and, for operational reasons, from October 2012 to December 2014 for FOT. Lung function was measured in unsedated infants during quiet sleep and conformed to American Thoracic society/European Thoracic society (ATS/ERS) guidelines,18 19 as previously published.20 21 Tidal breathing measures of tidal volume (VT), respiratory rate and expiratory flow ratios were collected using the Exhalyser D with ultrasonic flow metre (Ecomedics, Duernton, Switzerland) and analysed using analysis software (WBreath V.3.28.0; Ndd Medizintechnik, Zurich, Switzerland), as described previously.20 MBWs measuring the functional residual capacity (FRC) and lung clearance index (LCI) were performed using 4% SF6 as a tracer gas and ultrasonic flow metre (Spirison, Ecomedics) with acquisition and analysis software (WBreath V3.28.0, Ndd Medizintechnik) as reported previously.22 Measurements of respiratory system resistance (RRS) and compliance (CRS) with the FOT were made with purpose built equipment (University of Szeged, Hungary) using a medium frequency signal, as previously reported.21 23 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. Mothers gave written informed consent in their first language for participation. Lung function outcomes were modelled using multiple linear regression to assess the impact of different antenatal and early-life exposures on lung function at 6–10 weeks. A base model was constructed using Directed Acyclic Graph (DAG) for confounder selection using graphical interface software DAGitty (http://www.dagitty.net V.2.2, 2014), (see online supplementary figure S2).24 DAG minimal adjusted set of variables were selected using a step-by-step approach.25 Interactions were then explored between infant growth and lung maturation (weight for age z score, gestation, birth weight z score), sex, ethnicity, environmental and socioeconomic factors (tobacco smoke exposure, high household benzene, SES), maternal factors (maternal stress score, infant feeding, maternal respiratory health, maternal HIV, antenatal alcohol) and previous LRTI, for each lung function outcome separately. Confounders and interactions were included in the final model for each outcome if they were associated with p value of <0.5 and/or the association had biological plausibility based on previous literature, as shown in online supplementary tables S2–S10. Statistical analyses were performed using STATA V.13 for windows (STATA, College Station, Texas, USA). Data are presented as mean and SD for normally distributed variables and median and IQR for non-normally distributed variables. Weight (WAZ) and height (HAZ) for age z scores were calculated using the WHO Child Growth Standards ‘I grow up’ STATA package.26

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

1. Mobile Health (mHealth) Applications: Develop mobile applications that provide pregnant women with access to information, resources, and support related to maternal health. These apps could include features such as appointment reminders, educational content, and communication with healthcare providers.

2. Telemedicine: Implement telemedicine services to allow pregnant women in remote or underserved areas to consult with healthcare professionals remotely. This could include virtual prenatal visits, remote monitoring of vital signs, and teleconsultations for high-risk pregnancies.

3. Community Health Workers: Train and deploy community health workers to provide education, support, and basic healthcare services to pregnant women in their communities. These workers could conduct home visits, provide antenatal care, and assist with referrals to healthcare facilities.

4. Maternal Health Clinics: Establish dedicated maternal health clinics that provide comprehensive antenatal care, including prenatal screenings, vaccinations, and counseling services. These clinics could be located in areas with high maternal health needs and staffed by specialized healthcare professionals.

5. Public Awareness Campaigns: Launch public awareness campaigns to educate communities about the importance of maternal health and encourage early and regular prenatal care. These campaigns could use various media channels, such as radio, television, and social media, to reach a wide audience.

6. Maternal Health Vouchers: Introduce voucher programs that provide pregnant women with financial assistance to access essential maternal health services, such as prenatal care, delivery, and postnatal care. These vouchers could be distributed to women in low-income communities or those facing financial barriers to healthcare.

7. Maternal Health Education Programs: Develop and implement educational programs that focus on maternal health, targeting both pregnant women and healthcare providers. These programs could cover topics such as nutrition during pregnancy, breastfeeding, and safe delivery practices.

8. Maternal Health Monitoring Systems: Establish systems for monitoring and tracking maternal health indicators, such as maternal mortality rates, access to prenatal care, and birth outcomes. These systems could help identify areas with inadequate access to maternal health services and inform targeted interventions.

9. Partnerships and Collaborations: Foster partnerships and collaborations between healthcare providers, government agencies, non-profit organizations, and community stakeholders to collectively address barriers to maternal health access. These partnerships could leverage resources, expertise, and networks to implement innovative solutions.

10. Maternal Health Financing Models: Explore alternative financing models for maternal health, such as social health insurance schemes or microinsurance programs, to ensure affordable and sustainable access to maternal healthcare services.

It’s important to note that the specific context and needs of the community should be considered when implementing these innovations.
AI Innovations Description
The recommendation to improve access to maternal health based on the given information is to implement public health interventions targeting the determinants of early lung function in African infants. This includes addressing factors such as infant size, sex, maternal smoking, maternal alcohol use, maternal HIV, and household benzene exposure. By addressing these factors through targeted interventions, it is possible to improve early lung function in infants and ultimately strengthen child health. Additionally, long-term studies on lung function and respiratory disease in these children should be prioritized to develop strategies for further improvement.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations to improve access to maternal health:

1. Increase awareness and education: Implement comprehensive public health campaigns to educate pregnant women and their families about the importance of maternal health, including prenatal care, nutrition, and healthy lifestyle choices.

2. Strengthen healthcare infrastructure: Improve access to quality healthcare facilities, especially in low-income areas, by increasing the number of maternal health clinics and trained healthcare professionals.

3. Enhance transportation services: Develop transportation systems or programs that provide affordable and reliable transportation for pregnant women to reach healthcare facilities for prenatal care and delivery.

4. Expand telemedicine services: Utilize technology to provide remote prenatal care consultations and follow-ups, especially for women in remote or underserved areas.

5. Provide financial support: Implement policies or programs that provide financial assistance to pregnant women, such as subsidies for prenatal care, delivery, and postnatal care expenses.

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: Identify the specific population or region where the recommendations will be implemented.

2. Collect baseline data: Gather data on the current state of maternal health access in the target population, including factors such as healthcare facilities, transportation availability, and awareness levels.

3. Define indicators: Determine key indicators to measure the impact of the recommendations, such as the number of pregnant women receiving prenatal care, the percentage of women delivering in healthcare facilities, or the reduction in maternal mortality rates.

4. Develop a simulation model: Create a simulation model that incorporates the baseline data and the potential impact of the recommendations. This model should consider factors such as population size, geographical distribution, and resource availability.

5. Run simulations: Use the simulation model to run various scenarios that reflect the implementation of the recommendations. Adjust parameters such as the number of healthcare facilities, transportation services, or the reach of public health campaigns.

6. Analyze results: Evaluate the outcomes of the simulations to determine the potential impact of the recommendations on improving access to maternal health. Compare the results of different scenarios to identify the most effective strategies.

7. Refine and iterate: Based on the analysis of the simulation results, refine the recommendations and simulation model if necessary. Repeat the simulation process to further optimize the strategies.

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

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