Association between maternal psychological adversity and lung function in South African infants: A birth cohort study

listen audio

Study Justification:
This study aimed to investigate the association between maternal perinatal psychological adversity (such as stressors and distress) and infant lung function (ILF) in South African infants. This topic is important because the impact of psychological adversity on lung development in infants is not well studied, particularly in Africa. Understanding this association can help identify children at risk of altered lung development and inform approaches to treatment.
Highlights:
– The study included 762 infants aged 6 to 10 weeks and 485 infants with data on both maternal perinatal psychological adversity and ILF.
– The main analyses were based on cross-sectional measures of ILF at 6 to 10 weeks and 12 months, using generalized linear models.
– The study found associations between prenatal intimate partner violence (IPV) exposure and reduced respiratory resistance, postnatal IPV and reduced ratio of time to peak tidal expiratory flow over total expiratory time (tPTEF/tE), and prenatal depression and lower respiratory rate.
– Longitudinal analysis showed associations between prenatal IPV and reduced tPTEF/tE, postnatal IPV and decreased functional residual capacity (FRC), prenatal posttraumatic stress disorder (PTSD) and increased FRC, and prenatal and postnatal depression with increased FRC.
Recommendations:
– Screening for psychological adversity should be implemented to identify infants at risk of altered lung development.
– Further research is needed to understand the mechanisms involved in the association between psychological adversity and ILF.
– Treatment approaches should be developed to support infants at risk and promote healthy lung development.
Key Role Players:
– Researchers and scientists specializing in child health and lung function.
– Healthcare professionals, including doctors, nurses, and psychologists, who can screen for and address psychological adversity in pregnant women and new mothers.
– Policy makers and government officials responsible for implementing screening programs and supporting interventions for infants at risk.
Cost Items for Planning Recommendations:
– Development and implementation of screening tools for psychological adversity.
– Training for healthcare professionals on screening and intervention strategies.
– Research funding for further studies on the mechanisms and long-term effects of psychological adversity on lung development.
– Development of treatment approaches, such as counseling or therapy programs, for infants and mothers affected by psychological adversity.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is rated 7 because it is based on a prospective longitudinal follow-up study with a large sample size. However, the evidence could be improved by providing more details on the methodology, such as the specific statistical tests used and the inclusion/exclusion criteria for participants.

Objective: The association of perinatal psychological adversity (ie, stressors and distress) with infant lung function (ILF) and development is not well studied in Africa and elsewhere. We determined the association between maternal perinatal psychological adversity and ILF in African infants. Design: Prospective longitudinal follow up of the Drakenstein Child Health Study birth cohort. Participants: Seven hundred and sixty-two infants aged 6 to 10 weeks and 485 infants who had data for both maternal perinatal psychological adversity and ILF (measured at 6 to 10 weeks and 12 months). Methods: The main analyses were based on cross-sectional measures of ILF at each assessment (6 to 10 weeks or 12 months), using generalized linear models, and then on the panel-data of both longitudinal ILF assessments, using generalised estimating equations, that allowed specification of the within-group correlation structure. Results: Prenatal intimate partner violence (IPV) exposure was associated with reduced respiratory resistance at 6 to 10 weeks (beta coefficient [β] = −.131, P =.023); postnatal IPV with reduced ratio of time to peak tidal expiratory flow over total expiratory time (tPTEF/tE) at 12 months (β = −.206, P =.016); and prenatal depression with lower respiratory rate at 6 to 10 weeks (β = −.044, P =.032) and at 12 months (β = −.053, P =.021). Longitudinal analysis found an association of prenatal IPV with reduced tPTEF/tE (β = −.052, P <.0001); postnatal IPV with decreased functional residual capacity (FRC; β = −.086, P <.0001); prenatal posttraumatic stress disorder with increased FRC (β =.017, P <.0001); prenatal depression with increased FRC (β =.026, P <.0001) and postnatal depression with increased FRC (β =.021, P <.0001). Conclusion: Screening for psychological adversity and understanding the mechanisms involved may help identify children at risk of altered lung development and inform approaches to treatment.

Mother‐infant dyads were enrolled into the Drakenstein Child Health Study, to investigate the epidemiology, aetiology, and determinants of child health with longitudinal follow‐up of children until they are at least 5‐years of age.13, 14 The study was conducted in a periurban, low socioeconomic community, about 60 km from Cape Town in SA. Pregnant mothers were enrolled in their second trimester through the local primary health care clinics. Psychological adversity was assessed before birth and soon after birth,13 environmental exposures, and clinical measures were obtained before birth,14 and ILF was measured at 6 to 10 weeks and 1 year of age.6, 9 Prenatal and postnatal psychological adversity included in this analysis were: (a) IPV, (b) posttraumatic stress disorder (PTSD), and (c) depressive symptoms. Prenatal assessments for psychological adversity were done before birth while postnatal assessments were evaluated either at 6 to 10 weeks after birth. IPV was assessed with an IPV tool, which was piloted in the local South African population and found to be reliable when used in this population.13, 15 The tool comprises three sub‐scales as well as an overall IPV score based on frequency of abuse: (emotional abuse [four questions], physical abuse [four questions], and sexual abuse [three questions]), both of which are scored on a Likert scale of 1‐4, representing the frequency an abuse happened (1 = never, 2 = once, 3 = few, and 4 = many). Lifetime or past 12 months exposure for each subscale is generated. Emotional abuse was assessed by asking the mother about being insulted or made to feel bad, being belittled or humiliated in public, and being purposefully scared or intimidated. Physical abuse included history of being beaten (eg, by fist), pushed by force, injured (eg, burns), or threatened by weapons. Sexual abuse was assessed by asking about history of forced sexual intercourse when unwilling or forced into sexual activity that was humiliating. The responses for each question and scale were summed up to generate a continuous total score based on the frequency of abuse. PTSD was assessed with the Modified PTSD Symptom Scale (MPSS) which has 18 questions, with responses organised into 4‐likert scale (0‐3).16 The scales measure the frequency of PTSD symptoms, with 0 representing absence of symptoms, 1 present once, 2 presence of two to four symptoms, and 3 presence of 5 or more symptoms.13 The final 18th item assesses for duration of symptoms, with response options including less than 1 month; 1 to 3 months; 3 months to 1 year; and more than 1 year. The PTSD scores were then organised into “no exposure,” “suspected exposure,” and “definite exposure i.e. suspected exposure to PTSD” as previously described.13, 15 Previous studies have used the MPSS due to its good diagnostic validity for PTSD and good psychometric properties including concurrent validity. The Edinburgh Postnatal Depression Rating Scale (EPDS), is a 10‐item self‐report measure of depressive symptoms in the past 1 week.17 Items are scored on a frequency scale, ranging from 0 to 3. A continuous score was obtained by summing the individual items; with the lowest scores representing absent or nonsevere depressive symptoms and vice versa.13 It has been piloted and used in SA and found to possess good psychometric properties.18 ILF was tested at 6 to 10 weeks and 1 year of age, with the child in quiet natural sleep and included tidal breathing, multiple breath washout measures, and the forced oscillation technique as previously described.6, 9 Measures of ILF were first validated on normative data and found to be reliable before their application in this cohort.5 The following ILF parameters were obtained: tidal volume (mL), ratio of time to peak tidal expiratory flow over total expiratory time (tPTEF/tE), respiratory rate (per minute), functional residual capacity (FRC, mL), respiratory system resistance (cmH2O·L·s−1), and compliance (cmH2O·mL−1). All lung function measurements conformed to American Thoracic Society/European Respiratory Society guidelines, as previously published.5 Tidal breathing and flow volume loops (TBFVL) and multiple breath washout (MBW), performed using 4% SF6 as a tracer gas, were collected using the Exhalyzer D with ultrasonic flow meter (Ecomedics AG, Duernten, Switzerland) and mean measures calculated with acquisition and analysis software (Wbreath v3.28.0, Ndd Medizintechnik AG). The forced oscillation technique (FOT) measurement was made with purpose‐built equipment (University of Szeged, Hungary). Composite medium frequency signal (8‐48 Hz) was delivered to the infants via a wave‐tube through a facemask covering the mouth and nose. Socioeconomic status was based on a composite score for education, employment, income, assets and market access, and organised into four quartiles ranging from high to low. Maternal smoking during pregnancy was based on maternal urine cotinine (IMMULITE 1000 Nicotine Metabolite Kit; Siemens Medical Solutions Diagnostics, Glyn, Rhonwy, UK), with levels more than 500 ng/mL considered active smokers, 10 to 500 passive, and less than 10 nonsmokers.19 Benzene was considered present if household levels more than 5 μg/m3.20 Maternal alcohol was assessed with the Alcohol, Smoking and Substance Involvement Screening Test self‐reported questionnaires. Maternal respiratory illnesses were considered present if there was history of asthma, chronic cough, or recurrent wheeze in previous 12 months and/or low forced expiratory volume.6, 9 The study was approved by the Ethics Committee of the Faculty of Health Sciences, University of Cape Town, by Stellenbosch University and the Western Cape Provincial Research committee. Written informed consent was obtained from parents and is renewed annually. All the analyses were done using R statistical software (version 3.1.0 [2014‐04‐10], http://www.r-project.org) and Stata version 13 (Stata Corp, TX). Some psychosocial adversity variables (IPV and depression) were continuous and skewed and thus logarithmic (natural) transformation was performed to try to reduce the skewness of the residuals from regression models. The main analyses were based on cross‐sectional measures of ILF at each assessment (at 6‐10 weeks and at 12 months), using gamma regression, a type of generalized linear model (GLM) that assumes a gamma distribution for the outcome. This is more appropriate than a Gaussian distribution since our outcomes can only take on positive values, are slightly skewed and are log‐transformed. In the cross‐sectional analysis, all children at each assessment were included to allow comparisons in future studies since those missed at 12 months assessments may reinter the study in future follow‐ups. For our panel‐data of two ILF assessments, we used generalised estimating equations (GEEs), that allowed specification of the within‐group correlation structure, using only those children included in both 6 to 10 weeks and 12 months; the response variables were measures of ILF, while assessments of maternal perinatal psychological adversity were the explanatory variables. As with the GLM models, we specified a gamma distribution for our outcomes and an exchangeable correlation structure. In these GLM and GEE analyses, we first constructed unadjusted models, then adjusted models (accounting for potential confounders in particular, sex, socioeconomic status, population group, exposure to benzene, perinatal complications and maternal age, height‐for‐age z scores, respiratory illness, and HIV), and finally tested if there was interaction in the adjusted model between psychological adversity and maternal health behaviour variables (smoking, alcohol consumption, and breastfeeding). Height‐for‐age z scores added into the GLM and GEE models were available for both assessments (at 6‐12 weeks and at 12 months assessments). Other comparisons between two groups were done with the Wilcoxon signed‐rank test for non‐normal continuous scores and Pearson's χ 2 tests for frequency distributions.

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

1. Telemedicine: Implementing telemedicine services can allow pregnant women to have remote access to healthcare professionals for prenatal check-ups, consultations, and mental health support.

2. Mobile health applications: Developing mobile apps that provide educational resources, appointment reminders, and personalized health information can empower pregnant women to take control of their own health and access necessary care.

3. Community health workers: Training and deploying community health workers who can provide maternal health education, support, and referrals in underserved areas can help improve access to care for pregnant women.

4. Transportation services: Establishing transportation services specifically for pregnant women in remote or low-income areas can help overcome barriers to accessing healthcare facilities.

5. Maternal health clinics: Creating dedicated maternal health clinics that offer comprehensive services, including prenatal care, mental health support, and postnatal care, can ensure that pregnant women receive the specialized care they need.

6. Public awareness campaigns: Launching public awareness campaigns to educate communities about the importance of maternal health and the available resources can help reduce stigma and increase utilization of maternal health services.

7. Financial incentives: Implementing financial incentives, such as subsidies or cash transfers, for pregnant women to seek prenatal care and deliver in healthcare facilities can help overcome financial barriers to accessing maternal health services.

8. Partnerships with local organizations: Collaborating with local organizations, such as community centers or women’s groups, can help reach pregnant women who may not typically seek healthcare services and provide them with information and support.

9. Maternal health hotlines: Establishing toll-free hotlines staffed by healthcare professionals who can provide information, guidance, and support to pregnant women can be a valuable resource, especially in areas with limited access to healthcare facilities.

10. Mobile clinics: Setting up mobile clinics that travel to underserved areas and provide prenatal care, screenings, and vaccinations can bring healthcare services directly to pregnant women who may have difficulty accessing traditional healthcare facilities.

These innovations aim to address various barriers to accessing maternal health services, such as geographical distance, lack of information, financial constraints, and social stigma. By implementing these recommendations, it is hoped that more pregnant women will have improved access to quality maternal healthcare.
AI Innovations Description
Based on the description provided, the recommendation to improve access to maternal health would be to implement screening for psychological adversity during the perinatal period. This would involve assessing pregnant mothers for factors such as intimate partner violence, posttraumatic stress disorder, and depressive symptoms. By identifying and addressing these psychological adversities, healthcare providers can help support the mental well-being of mothers, which in turn may have a positive impact on infant lung development and overall health. Additionally, understanding the mechanisms involved in the association between psychological adversity and infant lung function can inform approaches to treatment and intervention. This recommendation can be implemented through training healthcare providers on how to conduct screenings and providing resources for support and treatment for mothers who are identified as experiencing psychological adversity.
AI Innovations Methodology
Based on the provided description, it seems that the focus is on studying the association between maternal psychological adversity and infant lung function (ILF) in South African infants. The methodology used in this study involves a prospective longitudinal follow-up of a birth cohort, specifically the Drakenstein Child Health Study. The study enrolled mother-infant dyads in a periurban, low socioeconomic community in South Africa. Psychological adversity, including intimate partner violence (IPV), posttraumatic stress disorder (PTSD), and depressive symptoms, was assessed before and after birth. ILF measurements were taken at 6 to 10 weeks and 1 year of age using various techniques such as tidal breathing, multiple breath washout, and forced oscillation. Statistical analyses were conducted using generalized linear models (GLM) and generalized estimating equations (GEE) to examine the association between psychological adversity and ILF, while adjusting for potential confounders such as sex, socioeconomic status, exposure to benzene, perinatal complications, maternal age, respiratory illness, and HIV.

To improve access to maternal health, it is important to consider innovations that can address the identified associations between maternal psychological adversity and infant lung function. Here are some potential recommendations:

1. Integrated mental health services: Implementing integrated mental health services within maternal health programs can help identify and address psychological adversity in pregnant women. This can involve routine screening for IPV, PTSD, and depressive symptoms, as well as providing appropriate support and interventions.

2. Collaborative care models: Establishing collaborative care models that involve multidisciplinary teams can ensure that women experiencing psychological adversity receive comprehensive care. This can involve close collaboration between obstetricians, mental health professionals, social workers, and community health workers.

3. Community-based interventions: Developing community-based interventions that target psychological adversity can help reach women who may face barriers to accessing traditional healthcare settings. This can involve community outreach programs, support groups, and home visits by trained healthcare providers.

4. Telemedicine and digital health solutions: Utilizing telemedicine and digital health solutions can improve access to mental health services for pregnant women, particularly in remote or underserved areas. This can include virtual counseling sessions, mobile apps for self-management, and remote monitoring of mental health symptoms.

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

1. Define the target population: Identify the specific population of pregnant women who would benefit from improved access to maternal health services, considering factors such as geographical location, socioeconomic status, and prevalence of psychological adversity.

2. Collect baseline data: Gather data on the current state of access to maternal health services, including the prevalence of psychological adversity, utilization rates of mental health services, and outcomes related to maternal and infant health.

3. Develop a simulation model: Create a simulation model that incorporates the identified recommendations and their potential impact on access to maternal health. This model should consider factors such as the number of women reached, the effectiveness of the interventions, and the expected outcomes in terms of improved maternal and infant health.

4. Input data and run simulations: Input the collected baseline data into the simulation model and run multiple simulations to assess the impact of the recommendations. This can involve varying parameters such as the coverage of interventions, the level of collaboration among healthcare providers, and the utilization rates of telemedicine and digital health solutions.

5. Analyze results and make recommendations: Analyze the simulation results to determine the potential impact of the recommendations on improving access to maternal health. Identify key findings, such as the number of women reached, the expected improvements in maternal and infant health outcomes, and any potential challenges or limitations.

6. Refine and implement recommendations: Based on the simulation results, refine the recommendations and develop an implementation plan. Consider factors such as scalability, sustainability, and feasibility in the local context. Collaborate with relevant stakeholders to implement the recommendations and monitor their impact over time.

By following this methodology, it is possible to simulate the impact of innovative recommendations on improving access to maternal health and inform decision-making for policy and program development.

Share this:
Facebook
Twitter
LinkedIn
WhatsApp
Email