Maternal psychosocial risk factors and lower respiratory tract infection (LRTI) during infancy in a South African birth cohort

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Study Justification:
This study aimed to investigate the association between maternal psychosocial risk factors (including depression, psychological distress, alcohol abuse, and intimate partner violence) and infant lower respiratory tract infection (LRTI) in a low- and middle-income country (LMIC) setting. The study was conducted in a South African birth cohort and focused on understanding the impact of these risk factors on LRTI outcomes in infants.
Highlights:
– The study found that maternal psychosocial risk factors were associated with both LRTI and severe LRTI in infants.
– Specific risk factors that were linked to LRTI included postnatal and long-term maternal psychological distress, antenatal maternal alcohol consumption, and postnatal maternal intimate partner violence.
– The study also identified different age groups during infancy that were associated with specific maternal psychosocial risk factors and LRTI outcomes.
– The findings highlight the importance of screening for maternal psychosocial risk factors in clinical settings and developing targeted interventions to improve maternal well-being and reduce the burden of infant LRTI in LMIC settings.
Recommendations:
Based on the study findings, the following recommendations can be made:
1. Healthcare providers should incorporate screening for maternal psychosocial risk factors, including depression, psychological distress, alcohol abuse, and intimate partner violence, as part of routine antenatal and postnatal care.
2. Targeted interventions should be developed to support mothers who are identified as having these psychosocial risk factors, with the aim of improving maternal well-being and reducing the risk of infant LRTI.
3. Public health policies should prioritize the implementation of these interventions in low- and middle-income country settings, where the burden of infant LRTI is high.
Key Role Players:
To address the recommendations, the following key role players are needed:
1. Healthcare providers: They play a crucial role in screening for maternal psychosocial risk factors and providing appropriate support and interventions.
2. Researchers: They can contribute by conducting further studies to explore effective interventions for addressing maternal psychosocial risk factors and reducing the burden of infant LRTI.
3. Policy makers: They are responsible for incorporating the study findings into public health policies and ensuring the implementation of targeted interventions in LMIC settings.
Cost Items for Planning Recommendations:
While the actual cost of implementing the recommendations will vary depending on the specific context, some key cost items to consider in planning the recommendations include:
1. Training and capacity building for healthcare providers to effectively screen for and address maternal psychosocial risk factors.
2. Development and implementation of intervention programs, including counseling services, support groups, and mental health services for mothers.
3. Research funding to conduct further studies on effective interventions and evaluate their impact on maternal well-being and infant LRTI outcomes.
4. Monitoring and evaluation of the implemented interventions to assess their effectiveness and make necessary adjustments.
Please note that the provided cost items are general considerations and a detailed budget would require a comprehensive analysis of the specific context and resources available.

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong, as it is based on a large sample size (n = 1137) and uses logistic regression to identify associations between maternal psychosocial risk factors and lower respiratory tract infection (LRTI) outcomes in infants. The study design is longitudinal, which allows for the examination of temporal relationships. The abstract also highlights the potential value of screening for maternal psychosocial risk factors in clinical settings and developing targeted interventions to reduce the burden of infant LRTI in low- and middle-income countries. To improve the evidence, it would be helpful to provide more details on the statistical methods used, such as the specific covariates adjusted for in the regression models. Additionally, including information on the effect sizes and confidence intervals for the associations found would further strengthen the evidence.

Objective To investigate the association between maternal antenatal and/or postnatal psychosocial risk factors (including depression, psychological distress, alcohol abuse and intimate partner violence (IPV) and infant lower respiratory tract infection (LRTI) in a low- and middleincome- country (LMIC). Study design Pregnant women (n = 1137) enrolled in a South African birth cohort study, the Drakenstein Child Health Study (DCHS) were longitudinally assessed for psychosocial risk factors including depression, psychological distress, alcohol abuse and/or intimate partner violence (IPV). Infants were followed from birth until one year of age for the development of LRTI by active surveillance. Two outcomes were evaluated: any LRTI, and severe and/or hospitalised LRTI. Logistic regression was used to identify associations between individual maternal psychosocial risk factors and LRTI outcomes. Analyses stratified by age were also performed to determine which age groups related to infant LRTI were linked with maternal psychosocial risk factors. Results There were 606 LRTI episodes in 369 infants in the first year (crude incidence rate = 0.53 episodes per person-year, 95%CI: 0.50; 0.56); 31% (n = 186) of episodes were severe or hospitalised events. Maternal psychosocial risk factors were associated with LRTI and severe LRTI, particularly postnatal and long-term maternal psychological distress, antenatal maternal alcohol consumption, and postnatal maternal IPV. Age stratified analyses found that antenatal maternal alcohol consumption was associated with early infant LRTI, while antenatal maternal depression was linked with infant severe LRTI between 3 and 6 months of age, and postnatal maternal IPV was associated with early LRTI and severe forms of LRTI. Conclusion The associations between maternal psychosocial risk factors and infant LRTI highlight the potential value of screening for maternal psychosocial risk factors in clinical settings and developing targeted interventions. Such interventions may not only improve maternal wellbeing, but also help reduce the burden of infant LRTI in LMIC settings.

Women in the 2nd trimester of pregnancy were enrolled between March 2012 and March 2015 in the Drakenstein Child Health Study (DCHS), a South African birth cohort study investigating the early life determinants of child health. Mothers were then followed through childbirth and mother-child dyads continue to be followed. For this study, the follow up period was censored at one year of age. The study was located in a peri-urban area in, South Africa, in a low socioeconomic population in which more than 90% of the population access public healthcare services [3, 24]. Enrolment occurred at two antenatal clinics (Mbekweni, serving predominately a population of black African ancestry, or TC Newman, serving a mixed-ancestry population). Consenting pregnant women 18 years or older, and who intended to remain in the area for at least 1 year were enrolled [3, 26]. Infants attended study visits at 6, 10, 14 weeks, 6, 9, 12 months, and were actively followed and investigated for any LRTI episode during the first year. In addition, a follow up visit 48 hours and 4–6 weeks after the LRTI episode was conducted. For the purpose of this study, a cut-off date for each participant was considered and any LRTI episode that happened prior to this date was included. The cut-off date was either the date of early termination, the date of the 12-month scheduled visit, or the expected date of the 12-month visit if this visit was missed but the child was still active in the study. Two binary LRTI outcomes were considered in this study; any LRTI episode and severe or hospitalised LRTI, as a measure of severity, in the first year of life. These outcomes were collected through active surveillance of LRTI episodes diagnosed by trained study staff (nurses) and assessed in real time [3, 27]. LRTI was defined according to World Health Organization (WHO) criteria, which included a cough or difficulty breathing with age-appropriate tachypnoea or lower chest wall indrawing [27, 28]. Study nurses were trained in respiratory examination of children with frequent re-training [27]. Severe LRTI, defined by WHO criteria, included any general danger sign in children older than 2 months or age specific tachypnea, lower chest indrawing or general danger sign in infants less than 2 months [27, 28]. Children were hospitalised or discharged based on a treating clinician’s recommendation. Maternal psychosocial risk factor data were collected at a scheduled antenatal visit during the third trimester (between 28–32 weeks of gestation) and postnatal visits at 10 weeks, 6 months and 12 months postpartum. Several validated questionnaires, that were administered in the preferred language (English, Afrikaans or isiXhosa) of the participant, were used to measure psychosocial risk factors as has been described [24]: The Edinburgh Postnatal Depression Scale (EPDS), was used to measure maternal depression [29]. The EPDS measure asked 10 questions related to how the women felt in the previous 7 days from the time of the visit. Each of 10 questions were scored 0–3 and summed [24]. A cut-off value of 13 was used to separate the participants into above- or below-threshold for depression [29, 30]. The presence of maternal psychological distress in the past month from the time of the visit was assessed with the validated Self-Reporting Questionnaire 20-item (SRQ20) [31, 32]. Each item had a binary scoring option (0–1), and a total score was generated [24]. A cut-off value of 8 dichotomised participants into an above- or below-threshold for psychological distress [24, 33, 34]. The Intimate Partner Violence (IPV) Questionnaire was used to assess maternal physical, emotional and sexual violence exposure. The questionnaire was adapted from previous studies and measures both lifetime IPV exposure as well as recent (past 12 months) IPV exposure [35, 36]. Exposure to emotional, physical and sexual abuse were considered individually. Participants were categorised as having experienced no IPV (either emotional, physical or sexual) if all responses for that exposure were “never”; an isolated incident of IPV if one response for that exposure happened “once”; a low frequency of exposure if the response was “once” to more than one item for a particular exposure; a mid-frequency if the participant responded “a few times” to at least one item, but did not respond “many times” to any item for a particular exposure; and a high frequency if there were any responses of “many times” for a particular exposure [24]. These were further categorised into above and below threshold; where low to high frequency was considered above threshold and no exposure or an isolated incident was considered to be below threshold. A participant was determined to be above threshold for “recent” IPV exposure if the participant was above threshold for any of the three IPV sub-types in the past 12 months. In addition, alcohol consumption during and post pregnancy were measured by the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) [37], which considers exposure of alcohol, smoking, and substance abuse in the previous 3 months from the time of the study visit. The scoring of ASSIST has been previously described [24, 37]. For this study, item responses related to frequency and timing of alcohol consumption were used to dichotomise into daily/weekly alcohol use vs no use. Since there were 3 postnatal time points considered in this study, each of these were considered in independent regression models for maternal depression, psychological distress, and alcohol use. The 12-month visit was used to investigate postnatal IPV exposure, as the measure enquired about physical, emotional and sexual abuse by a partner in the previous 12 months. This was done to avoid any overlap between the antenatal and postnatal periods. Clinical and socio-demographic risk factors were longitudinally measured including child feeding practices; HIV exposure; maternal smoking and environmental tobacco smoke (ETS) exposure, assessed by self-report and urine cotinine results (from the mother collected antenatally and at birth; infant results were collected within the first year of life). Continuous cotinine values were categorised into three levels: a score less than or equal to 10 ng/mL was consider not exposed, a score greater than 10 ng/mL and less than 500 ng/mL was considered to have passive smoke exposure, and a result greater than 500 ng/mL, was recorded as active smoking [38]. Indoor air pollution (IAP) related to the child’s home environment, was measured at an antenatal (within 4 weeks of enrolment) and postnatal (between 4 and 6 months postpartum) home visit [38]. The only pollutant considered was particulate matter (PM10), as this pollutant was previously found to be associated with LRTI in the DCHS [38]. The South African National Ambient Air Quality Standards [39] were used to define expected exposure levels for each pollutant based on an averaging period of 1 year for each measure: PM10 = 40 μg/m3 [38, 39]. Birth characteristics were collected, including gestational age and birth weight, measured by study staff as previously described [40]. Birth weight/height standardised z-scores were calculated using the updated Fenton new born growth charts, which account for prematurity [41]. In addition, socio-economic status (SES) at baseline was collected, based on a composite validated score comprising four socio-economic variables: level of maternal education, employment status, household income, and asset ownership [42]. Standardised scores were divided into quartiles, which are labelled ‘low’, ‘low-moderate’, ‘high-moderate’, and ‘high’ groups [42]. The infant’s vaccination schedule was also recorded longitudinally, at scheduled visits. The DCHS was approved by the Faculty of Health Sciences, Human Research Ethics Committee (HREC), University of Cape Town (401/2009) and by the Western Cape Provincial Health Research committee [3]. Mothers provided written informed consent at enrolment and annually thereafter. Analyses were conducted with STATA version 14.0 (College Station, Texas, USA). Descriptive data were presented as medians, interquartile range (IQR) and frequencies (proportions), as appropriate. Mann-Whitney rank sum and Kruskal-Wallis tests were used to test for associations between categorical and continuous variables, as all continuous variables were non-Gaussian. Pearson Chi-square test or Fisher Exact tests were used to determine if significant associations existed between categorical variables. Multiple logistic regression was used to model the association of maternal antenatal, postnatal, and long-term psychosocial risk factors with any LRTI and any severe/hospitalised LRTI episode in the first year of life adjusting for critical clinical and sociodemographic covariates. Directed acyclic graphs (DAGs) were used to identify the minimum set of confounding variables, which included sex, recruitment site, SES, maternal education achievement and HIV exposure (see Figs ​Figs11 and ​and2).2). Two sets of multiple regression models were run for each of the maternal psychosocial risk factors: the first set included the minimum set of confounder variables identified by the DAGs, and the second set included the confounding variables as well as additional variables (including mediators) based on prior literature: smoke exposure (maternal & infant urine cotinine results), indoor air pollution (assessed by PM10), weight for age z-score at birth, duration of exclusive breastfeeding and season of birth. [2, 23]. Season of birth was included to adjust for seasonality, as winter and autumn months are more commonly linked with LRTI episodes [27]. Each maternal psychosocial risk factor was considered in an individual model. In addition, antenatal and postnatal psychosocial risk factors were considered separately to estimate the association each of these exposures had on LRTI outcomes at different time points. The association of long-term psychosocial risk factor exposure on LRTI outcomes was also analysed; long-term exposure for each individual maternal psychosocial risk factor was defined as being above threshold for that psychosocial risk factor at two or more of the four time points considered in this analysis. Since LRTI episodes are more common in earlier months of age, stratified analyses by age were also constructed [43]. Four time points were considered: 0- 3months, 3–6 months, 6–9 months and 9–12 months of age. Stratifying by age presented an opportunity to consider temporality, particularly with postnatal psychosocial risk factors, as episodes after the exposure could be analysed. This analysis also provided an opportunity to determine if the exposure took place after the outcome (reverse causation). The stratified models adjusted for sex, recruitment site, HIV exposure, maternal education achievement, SES quartile, maternal urine cotinine (smoke exposure), PM10 exposure, weight for age z-score at birth, duration of breastfeeding, season of birth and LRTI in previous age period. Diagnostic checks were performed for all the multiple logistic regression models. These included checks for specification error, Hosmer and Lemeshow’s goodness of fit test, and checks for multicollinearity using the variance inflation factor (VIF). Influential observations were also considered using Pearson residuals, deviance residuals and leverage.

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

1. Telemedicine: Implementing telemedicine services can provide remote access to healthcare professionals for pregnant women, allowing them to receive prenatal care, counseling, and support without the need for in-person visits.

2. Mobile health (mHealth) applications: Developing mobile applications that provide educational resources, reminders for prenatal appointments, and access to teleconsultations 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 education, support, and basic healthcare services to pregnant women in underserved areas can improve access to maternal health services.

4. Integrated care models: Implementing integrated care models that bring together different healthcare providers, such as obstetricians, midwives, and mental health professionals, can ensure comprehensive and coordinated care for pregnant women, addressing both physical and psychosocial risk factors.

5. Maternal health clinics: Establishing dedicated maternal health clinics that offer a range of services, including prenatal care, mental health support, and screening for psychosocial risk factors, can provide a centralized and accessible location for pregnant women to receive comprehensive care.

6. Health education programs: Developing targeted health education programs that focus on maternal psychosocial risk factors, such as depression, psychological distress, alcohol abuse, and intimate partner violence, can raise awareness and promote early identification and intervention.

7. Policy changes: Advocating for policy changes that prioritize maternal health and address social determinants of health, such as poverty and gender inequality, can help improve access to maternal health services and support for at-risk populations.

It’s important to note that these recommendations are based on the information provided and may need to be tailored to specific contexts and resources available in different settings.
AI Innovations Description
Based on the study findings, the recommendation to improve access to maternal health and reduce the burden of infant lower respiratory tract infection (LRTI) in low- and middle-income countries (LMIC) is to implement screening for maternal psychosocial risk factors in clinical settings and develop targeted interventions.

The study found that maternal psychosocial risk factors, including depression, psychological distress, alcohol abuse, and intimate partner violence (IPV), were associated with LRTI and severe LRTI in infants. Specifically, postnatal and long-term maternal psychological distress, antenatal maternal alcohol consumption, and postnatal maternal IPV were linked to LRTI outcomes.

To address this issue, healthcare providers can incorporate routine screening for maternal psychosocial risk factors during antenatal and postnatal visits. Validated questionnaires, such as the Edinburgh Postnatal Depression Scale (EPDS) for depression, the Self-Reporting Questionnaire 20-item (SRQ20) for psychological distress, and the IPV Questionnaire for IPV exposure, can be used to assess these risk factors.

Based on the screening results, targeted interventions can be developed to support mothers who are identified as having psychosocial risk factors. These interventions may include counseling, therapy, support groups, and referrals to specialized services, depending on the specific needs of the mother. By addressing these risk factors and providing appropriate support, maternal well-being can be improved, which in turn may help reduce the burden of infant LRTI.

It is important for healthcare systems in LMIC settings to prioritize the implementation of these recommendations to ensure that all pregnant women have access to comprehensive maternal health care that addresses both physical and psychosocial aspects. This can contribute to better maternal and child health outcomes and reduce health disparities in these populations.
AI Innovations Methodology
Based on the information provided, here are some potential recommendations to improve access to maternal health:

1. Implement routine screening for maternal psychosocial risk factors: Based on the findings of the study, it is important to screen pregnant women for psychosocial risk factors such as depression, psychological distress, alcohol abuse, and intimate partner violence. This can be done during antenatal visits to identify women who may be at risk and provide appropriate support and interventions.

2. Develop targeted interventions: Once maternal psychosocial risk factors are identified, it is crucial to develop targeted interventions to address these issues. This may include providing mental health support services, counseling, and referral to appropriate resources such as support groups or therapy.

3. Strengthen collaboration between healthcare providers: To improve access to maternal health, it is important to strengthen collaboration between different healthcare providers involved in the care of pregnant women and new mothers. This can include obstetricians, midwives, nurses, psychologists, and social workers. By working together, they can provide comprehensive care and support to women with psychosocial risk factors.

4. Increase awareness and education: There is a need to increase awareness and education about maternal psychosocial risk factors among healthcare providers, pregnant women, and the general public. This can be done through training programs, educational materials, and public health campaigns to reduce stigma and promote early identification and intervention.

Methodology to simulate the impact of these recommendations on improving access to maternal health:

1. Define the target population: Identify the specific population that will be the focus of the simulation, such as pregnant women in a particular region or healthcare facility.

2. Collect baseline data: Gather data on the current access to maternal health services, including the prevalence of maternal psychosocial risk factors, the availability of screening and intervention programs, and the outcomes related to maternal health.

3. Develop a simulation model: Create a mathematical or computational model that represents the population and the factors that influence access to maternal health. This model should include variables such as the prevalence of psychosocial risk factors, the effectiveness of screening and intervention programs, and the impact of these factors on maternal health outcomes.

4. Input data and parameters: Input the baseline data and parameters into the simulation model. This includes data on the prevalence of psychosocial risk factors, the coverage and effectiveness of screening and intervention programs, and the desired outcomes related to maternal health.

5. Run simulations: Run the simulation model multiple times using different scenarios and assumptions. This can include varying the coverage and effectiveness of screening and intervention programs, as well as other factors that may influence access to maternal health.

6. Analyze results: Analyze the results of the simulations to assess the impact of the recommendations on improving access to maternal health. This can include evaluating changes in the prevalence of psychosocial risk factors, the coverage of screening and intervention programs, and the outcomes related to maternal health.

7. Refine and validate the model: Refine the simulation model based on the results and feedback from stakeholders. Validate the model by comparing the simulated results with real-world data and conducting sensitivity analyses to assess the robustness of the findings.

8. Communicate findings and implement recommendations: Communicate the findings of the simulation study to relevant stakeholders, such as healthcare providers, policymakers, and community organizations. Use the results to inform decision-making and implement the recommendations to improve access to maternal health services.

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