Association of Prenatal Exposure to Maternal Drinking and Smoking with the Risk of Stillbirth

JAMA Network Open, Year 2021

Interpretation

Importance: Prenatal smoking is a known modifiable risk factor for stillbirth; however, the contribution of prenatal drinking or the combination of smoking and drinking is uncertain. Objective: To examine whether prenatal exposure to alcohol and tobacco cigarettes is associated with the risk of stillbirth. Design, Setting, and Participants: The Safe Passage Study was a longitudinal, prospective cohort study with data collection conducted between August 1, 2007, and January 31, 2015. Pregnant women from Cape Town, South Africa, and the Northern Plains region of the US were recruited and followed up throughout pregnancy. Data analysis was performed from November 1, 2018, to November 20, 2020. Exposure: Maternal consumption of alcohol and tobacco cigarettes in the prenatal period. Main Outcomes and Measures: The main outcomes were stillbirth, defined as fetal death at 20 or more weeks’ gestation, and late stillbirth, defined as fetal death at 28 or more weeks’ gestation. Self-reported alcohol and tobacco cigarette consumption was captured at the recruitment interview and up to 3 scheduled visits during pregnancy. Participants were followed up during pregnancy to obtain delivery outcome. Results: Of 11663 pregnancies (mean [SD] gestational age at enrollment, 18.6 [6.6] weeks) in 8506 women for whom the pregnancy outcome was known by 20 weeks’ gestation or later and who did not terminate their pregnancies, there were 145 stillbirths (12.4 per 1000 pregnancies) and 82 late stillbirths (7.1 per 1000 pregnancies). A total of 59% of pregnancies were in women from South Africa, 59% were in multiracial women, 23% were in White women, 17% were in American Indian women, and 0.9% were in women of other races. A total of 8% were older than 35 years. In 51% of pregnancies, women reported no alcohol or tobacco cigarette exposure (risk of stillbirth, 4 per 1000 pregnancies). After the first trimester, 18% drank and smoked (risk of stillbirth, 15 per 1000 births), 9% drank only (risk of stillbirth, 10 per 1000 pregnancies), and 22% smoked only (risk of stillbirth, 8 per 1000 pregnancies). Compared with the reference group (pregnancies not prenatally exposed or without any exposure after the first trimester), the adjusted relative risk of late stillbirth was 2.78 (98.3% CI, 1.12-6.67) for pregnancies prenatally exposed to drinking and smoking, 2.22 (98.3% CI, 0.78-6.18) for pregnancies prenatally exposed to drinking only after the first trimester, and 1.60 (98.3% CI, 0.64-3.98) for pregnancies prenatally exposed to smoking only after the first trimester. The adjusted relative risk for all stillbirths was 1.75 (98.3% CI, 0.96-3.18) for dual exposure, 1.26 (98.3% CI, 0.58-2.74) for drinking only, and 1.27 (98.3% CI, 0.69-2.35) for smoking only compared with the reference group. Conclusions and Relevance: These results suggest that combined drinking and smoking after the first trimester of pregnancy, compared with no exposure or quitting before the end of the first trimester, may be associated with a significantly increased risk of late stillbirth.. The network’s steering committee and an external advisory and safety monitoring board oversaw the research. Between August 1, 2007, and January 31, 2015, a prospective cohort of 8506 women (11 892 pregnancies) were enrolled in the Safe Passage Study. In South Africa, women were recruited from 2 residential areas within Cape Town, and in the Northern Plains of the US (South and North Dakota), from 5 clinical sites, including 2 American Indian reservations. Data analysis was performed from November 1, 2018, to November 20, 2020. Ethical approval was obtained at each clinical site; Stellenbosch University, Sanford Health, the Indian Health Service, and participating Tribal Nations. Institutional review board approval, including tribal review for reservation-based sites in the Northern Plains of the US, was obtained for all PASS entities.11,14 Written informed consent was provided at the time of recruitment. Data were not deidentified at the time of participant recruitment but were deidentified for the purpose of data analyses. The study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline. Inclusion and exclusion criteria are described elsewhere.11 In brief, consenting, pregnant women 16 years or older who were carrying 1 or 2 fetuses between 6 weeks’ gestation up to but not including the delivery admission and able to speak English or Afrikaans were eligible. Women planning to terminate their pregnancy or move out of the catchment area before the estimated date of delivery or were advised by a health care professional to not participate were excluded. The GA was determined during the recruitment visit using standard clinical practices: ultrasonography in South Africa and a combination of clinical examination, ultrasonography, and last menstrual period in the Northern Plains of the US. Women completed in-person study visits, which included a recruitment visit and up to 3 prenatal visits occurring at 20 to 24, 28 to 32, and 34 or more weeks of gestation, dependent on GA at enrollment. To reduce potential sources of bias, all participants presenting for prenatal care were approached for recruitment into the study, and subsequent study visits aligned with routine prenatal visits. At the recruitment visit in Cape Town, South Africa, and the Northern Plains of the US, pregnant women self-reported their racial background, choosing from the categories recommended by the National Institutes of Health: American Indian or Alaska Native, Asian, Black or African American, multiracial, Native Hawaiian or Pacific Islander, White, or other. Multiracial was defined in South Africa as having ancestry from more than 1 of the populations that inhabit the region, including Khoisan, Bantu, European, Austronesian, East Asian, or South Asian. In addition, participants self-reported their ethnic background as non-Hispanic or Latino or Hispanic or Latino. The primary goal of assessing race and ethnicity was to ensure that research can comprehensively describe the population and that findings can be generalizable. Clinical site coordinators monitored labor and delivery admissions daily to identify pregnancy outcome (ie, miscarriage, termination of pregnancy, stillbirth, and live birth). When a stillbirth occurred, the participant was asked to consent to fetal autopsy and to donate fetal brain tissue.15 For this analysis, the primary stillbirth outcome was defined as a fetal death delivered at 28 weeks’ gestation or later (late stillbirth ≥28 weeks), and the secondary outcome was defined as a fetal death delivered at 20 weeks or later (all stillbirth ≥20 weeks). Each stillbirth was adjudicated by a committee of multidisciplinary study investigators16 using the following clinical information: fetal autopsy and placental pathology (47% of cases), placental pathology only (32%), autopsy data only (5%), or clinical information only (16%). Diagnostic genetic testing was performed as indicated in 5% of cases. The most common cause of stillbirth was acute placental abruption (26%) followed by maternal vascular malperfusion (17%) and fetal vascular malperfusion (which includes umbilical cord pathology) (16%). Details of the methods used to collect and characterize alcohol and tobacco cigarette exposure were published elsewhere17,18 and are summarized here. Self-reported alcohol and tobacco cigarette consumption was captured at the recruitment interview and at up to 3 prenatal visits after recruitment, using a modified timeline follow-back interview for alcohol exposure and frequency and quantity of tobacco cigarettes for smoking exposure. In the event of fetal demise, exposure information was collected for the 30 days before the death. Standard drinks were calculated based on the specific alcohol content of the drinks reported. Prenatal drinking and smoking information was obtained at nearly 100% of prenatal visits. Drinking status was known for at least 6 months of the pregnancy among 94% of pregnancies and smoking status among 80% of pregnancies. Drinks per drinking-day and tobacco cigarettes per day were calculated for each month of pregnancy where exposure information was available before the stillbirth. Group-based trajectory models were used to classify pregnancies with similar prenatal drinking patterns into 1 of 5 drinking trajectory groups (based on 11 892 pregnancies): none (48%), moderate/quit early (25%), high/quit later (10%), low continuous (12%), and high continuous (6%). Similar prenatal smoking patterns were classified into 1 of 7 smoking trajectory groups: none (52%), moderate/quit early (8%), high/quit later (2%), low continuous (10%), moderate continuous (18%), high continuous (8%), and very high continuous (2%).18 Because of the small number of late stillbirths (n = 82) and stillbirths (n = 145), to improve precision in the estimates of stillbirth risk associated with exposure, we dichotomized the 5-level drinking and 7-level smoking exposure measures to create a 2-level drinking and a 2-level smoking exposure measure. The 2-level drinking and 2-level smoking measures were labeled as none/quit early, defined as no exposure during pregnancy or cessation by the end of the first trimester, and continuous/quit late, defined as continuous exposure throughout pregnancy or cessation some time after the first trimester. To address the primary hypothesis that associations exist between different combinations of drinking and smoking and stillbirth risk, we created a 4-level drinking and smoking measure: none/quit early (51%), defined as no drinking or smoking during pregnancy or cessation by the end of the first trimester; drinking only (8%), defined as continuous/quit late for drinking and none/quit early for smoking; smoking only (22%), defined as continuous/quit late for smoking and none/quit early for drinking; and dual (19%), defined as continuous/quit late for both exposures. Because stillbirth is a rare outcome, multivariable statistical approaches for adjustment were limited. Thus, propensity scores (PSs) were developed to balance the effect of nonrandom allocation of drinking and smoking exposure at baseline to increase efficiency and reduce bias caused by confounding and were included as covariates in multivariable models (K.A.D. and M.W., unpublished data, 2017). Propensity scores were developed for the 2-level and 4-level exposure measures, using baseline characteristics available on nearly the entire cohort (PS abbreviated, 2% missing) and included the following: recruitment location, maternal age, race, marital status, educational level, history of diabetes, parity, arm circumference, and statistical interactions. As a measure of nutritional status, arm circumference was used as a proxy for prepregnancy body mass index (correlation, 0.83), which was missing in 33% of pregnancies because many women did not have access to scales.19 An additional set of PSs were developed based on a more complete set of baseline characteristics (PS comprehensive, 19.5% missing). The PS comprehensive contained 40 baseline characteristics and statistical interactions between confounders (eTable 1 in Supplement 1). The primary analysis set includes all pregnancies. Maternal demographic characteristics, medical and obstetric history, and infant characteristics for each stillbirth outcome, compared with live births, were expressed as risk per 1000 pregnancies. Log binomial regression using generalized linear models and generalized estimating equations to account for correlation (exchangeable) among reenrollments were used to estimate crude and adjusted relative risks to quantify associations between exposure and outcome. Adjustment in multivariable models included the PSs described above, GA at enrollment, and multifetal pregnancy. For the death outcomes, late stillbirth (≥28 weeks) and stillbirth (≥20 weeks), the primary exposure analysis included 3 planned comparisons using the 4-level drinking and smoking measure, specifically comparing the none/quit early group with the drinking only, smoking only, or dual (drinking and smoking) exposure groups, adjusted for confounding as described. Conservatively, for statistical testing that involved multiple comparisons, 2-sided 98.3% (based on Bonferroni correction) CIs were provided; otherwise, 95% CIs were provided. A 2-sided P < .05 was considered to be statistically significant, and 95% CIs were provided for tests of interaction. The causes of stillbirth using the 4-level drinking and smoking exposure measure were presented descriptively. The study design and determination of sample size were described elsewhere.11 In brief, the study was sized for the outcome of SIDS that resulted in a sample size of 12 000 women. Assuming a sample size of 12 000, then 8 per 1000 stillbirths in the Northern Plains of the US, 15 per 1000 stillbirths in South Africa, and 49% of women prenatally exposed yields 95% power to detect a relative risk of at least 2 when comparing women with prenatal exposure with those without prenatal exposure using a χ2 test for proportions with continuity correction and a 2-sided P < .05. The study was not powered to detect effect measure modification (ie, statistical interaction between 2-level drinking and 2-level smoking main effects based on factorial design); however, the findings were provided. The study was not designed to investigate genetic and biological interactions or to perform subgroup analysis (eg, stratified by site and cause of death); however, crude assessments by site and cause of stillbirth death were provided. Analyses were performed using SAS/STAT software, version 9.4 (SAS Institute Inc).

AI Digest

Study Justification:

The study aimed to investigate the association between prenatal exposure to maternal drinking and smoking and the risk of stillbirth. This is an important area of research because while the link between prenatal smoking and stillbirth is known, the contribution of prenatal drinking or the combination of smoking and drinking is uncertain. Understanding these associations can help inform public health policies and interventions to reduce the risk of stillbirth.

Study Highlights:

– The study included 11,663 pregnancies in 8,506 women from Cape Town, South Africa, and the Northern Plains region of the US.
– The main outcomes measured were stillbirth (fetal death at 20 or more weeks’ gestation) and late stillbirth (fetal death at 28 or more weeks’ gestation).
– The study found that combined drinking and smoking after the first trimester of pregnancy was associated with a significantly increased risk of late stillbirth.
– Pregnancies with prenatal exposure to drinking only or smoking only also had an increased risk of stillbirth, although the associations were not as strong as with combined exposure.

Recommendations for Lay Readers:

– Pregnant women should avoid drinking alcohol and smoking cigarettes, especially after the first trimester, to reduce the risk of stillbirth.
– Public health campaigns should emphasize the importance of abstaining from alcohol and tobacco during pregnancy.
– Healthcare providers should provide education and support to pregnant women to help them quit smoking and drinking.

Recommendations for Policy Makers:

– Develop and implement policies that restrict the availability and marketing of alcohol and tobacco products to pregnant women.
– Allocate resources for public health campaigns and interventions aimed at preventing prenatal exposure to alcohol and tobacco.
– Enhance access to smoking cessation programs and support services for pregnant women.
– Strengthen monitoring and enforcement of regulations related to alcohol and tobacco use during pregnancy.

Key Role Players:

– Researchers and scientists to conduct further studies and monitor the impact of interventions.
– Healthcare providers to deliver education, counseling, and support to pregnant women.
– Public health officials to develop and implement policies and interventions.
– Community organizations and advocacy groups to raise awareness and provide resources for pregnant women.

Cost Items for Planning Recommendations:

– Development and dissemination of educational materials and campaigns.
– Training and capacity building for healthcare providers.
– Implementation of smoking cessation programs and support services.
– Monitoring and enforcement of regulations.
– Research and evaluation of interventions.
Please note that the cost items provided are for planning purposes and do not represent actual costs. The specific budget required will depend on the context and scale of implementation.

Strength of Evidence

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong, but there are some areas for improvement. The study design is a prospective cohort study, which is generally considered to provide robust evidence. The sample size is large, with over 11,000 pregnancies included. The study collected data from multiple sites in different regions, which increases the generalizability of the findings. The main outcomes were clearly defined and measured. The analysis included adjustment for confounding variables using propensity scores. However, there are a few areas that could be improved. First, the abstract does not provide information on the statistical methods used for the analysis, such as the specific regression models employed. Second, the abstract does not mention any limitations of the study, such as potential sources of bias or confounding. Finally, the abstract does not provide any information on the strength of the associations found, such as effect sizes or confidence intervals. To improve the evidence, the abstract should include these missing details and discuss any limitations of the study.

Abstract

The network’s steering committee and an external advisory and safety monitoring board oversaw the research. Between August 1, 2007, and January 31, 2015, a prospective cohort of 8506 women (11 892 pregnancies) were enrolled in the Safe Passage Study. In South Africa, women were recruited from 2 residential areas within Cape Town, and in the Northern Plains of the US (South and North Dakota), from 5 clinical sites, including 2 American Indian reservations. Data analysis was performed from November 1, 2018, to November 20, 2020. Ethical approval was obtained at each clinical site; Stellenbosch University, Sanford Health, the Indian Health Service, and participating Tribal Nations. Institutional review board approval, including tribal review for reservation-based sites in the Northern Plains of the US, was obtained for all PASS entities.11,14 Written informed consent was provided at the time of recruitment. Data were not deidentified at the time of participant recruitment but were deidentified for the purpose of data analyses. The study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline. Inclusion and exclusion criteria are described elsewhere.11 In brief, consenting, pregnant women 16 years or older who were carrying 1 or 2 fetuses between 6 weeks’ gestation up to but not including the delivery admission and able to speak English or Afrikaans were eligible. Women planning to terminate their pregnancy or move out of the catchment area before the estimated date of delivery or were advised by a health care professional to not participate were excluded. The GA was determined during the recruitment visit using standard clinical practices: ultrasonography in South Africa and a combination of clinical examination, ultrasonography, and last menstrual period in the Northern Plains of the US. Women completed in-person study visits, which included a recruitment visit and up to 3 prenatal visits occurring at 20 to 24, 28 to 32, and 34 or more weeks of gestation, dependent on GA at enrollment. To reduce potential sources of bias, all participants presenting for prenatal care were approached for recruitment into the study, and subsequent study visits aligned with routine prenatal visits. At the recruitment visit in Cape Town, South Africa, and the Northern Plains of the US, pregnant women self-reported their racial background, choosing from the categories recommended by the National Institutes of Health: American Indian or Alaska Native, Asian, Black or African American, multiracial, Native Hawaiian or Pacific Islander, White, or other. Multiracial was defined in South Africa as having ancestry from more than 1 of the populations that inhabit the region, including Khoisan, Bantu, European, Austronesian, East Asian, or South Asian. In addition, participants self-reported their ethnic background as non-Hispanic or Latino or Hispanic or Latino. The primary goal of assessing race and ethnicity was to ensure that research can comprehensively describe the population and that findings can be generalizable. Clinical site coordinators monitored labor and delivery admissions daily to identify pregnancy outcome (ie, miscarriage, termination of pregnancy, stillbirth, and live birth). When a stillbirth occurred, the participant was asked to consent to fetal autopsy and to donate fetal brain tissue.15 For this analysis, the primary stillbirth outcome was defined as a fetal death delivered at 28 weeks’ gestation or later (late stillbirth ≥28 weeks), and the secondary outcome was defined as a fetal death delivered at 20 weeks or later (all stillbirth ≥20 weeks). Each stillbirth was adjudicated by a committee of multidisciplinary study investigators16 using the following clinical information: fetal autopsy and placental pathology (47% of cases), placental pathology only (32%), autopsy data only (5%), or clinical information only (16%). Diagnostic genetic testing was performed as indicated in 5% of cases. The most common cause of stillbirth was acute placental abruption (26%) followed by maternal vascular malperfusion (17%) and fetal vascular malperfusion (which includes umbilical cord pathology) (16%). Details of the methods used to collect and characterize alcohol and tobacco cigarette exposure were published elsewhere17,18 and are summarized here. Self-reported alcohol and tobacco cigarette consumption was captured at the recruitment interview and at up to 3 prenatal visits after recruitment, using a modified timeline follow-back interview for alcohol exposure and frequency and quantity of tobacco cigarettes for smoking exposure. In the event of fetal demise, exposure information was collected for the 30 days before the death. Standard drinks were calculated based on the specific alcohol content of the drinks reported. Prenatal drinking and smoking information was obtained at nearly 100% of prenatal visits. Drinking status was known for at least 6 months of the pregnancy among 94% of pregnancies and smoking status among 80% of pregnancies. Drinks per drinking-day and tobacco cigarettes per day were calculated for each month of pregnancy where exposure information was available before the stillbirth. Group-based trajectory models were used to classify pregnancies with similar prenatal drinking patterns into 1 of 5 drinking trajectory groups (based on 11 892 pregnancies): none (48%), moderate/quit early (25%), high/quit later (10%), low continuous (12%), and high continuous (6%). Similar prenatal smoking patterns were classified into 1 of 7 smoking trajectory groups: none (52%), moderate/quit early (8%), high/quit later (2%), low continuous (10%), moderate continuous (18%), high continuous (8%), and very high continuous (2%).18 Because of the small number of late stillbirths (n = 82) and stillbirths (n = 145), to improve precision in the estimates of stillbirth risk associated with exposure, we dichotomized the 5-level drinking and 7-level smoking exposure measures to create a 2-level drinking and a 2-level smoking exposure measure. The 2-level drinking and 2-level smoking measures were labeled as none/quit early, defined as no exposure during pregnancy or cessation by the end of the first trimester, and continuous/quit late, defined as continuous exposure throughout pregnancy or cessation some time after the first trimester. To address the primary hypothesis that associations exist between different combinations of drinking and smoking and stillbirth risk, we created a 4-level drinking and smoking measure: none/quit early (51%), defined as no drinking or smoking during pregnancy or cessation by the end of the first trimester; drinking only (8%), defined as continuous/quit late for drinking and none/quit early for smoking; smoking only (22%), defined as continuous/quit late for smoking and none/quit early for drinking; and dual (19%), defined as continuous/quit late for both exposures. Because stillbirth is a rare outcome, multivariable statistical approaches for adjustment were limited. Thus, propensity scores (PSs) were developed to balance the effect of nonrandom allocation of drinking and smoking exposure at baseline to increase efficiency and reduce bias caused by confounding and were included as covariates in multivariable models (K.A.D. and M.W., unpublished data, 2017). Propensity scores were developed for the 2-level and 4-level exposure measures, using baseline characteristics available on nearly the entire cohort (PS abbreviated, 2% missing) and included the following: recruitment location, maternal age, race, marital status, educational level, history of diabetes, parity, arm circumference, and statistical interactions. As a measure of nutritional status, arm circumference was used as a proxy for prepregnancy body mass index (correlation, 0.83), which was missing in 33% of pregnancies because many women did not have access to scales.19 An additional set of PSs were developed based on a more complete set of baseline characteristics (PS comprehensive, 19.5% missing). The PS comprehensive contained 40 baseline characteristics and statistical interactions between confounders (eTable 1 in Supplement 1). The primary analysis set includes all pregnancies. Maternal demographic characteristics, medical and obstetric history, and infant characteristics for each stillbirth outcome, compared with live births, were expressed as risk per 1000 pregnancies. Log binomial regression using generalized linear models and generalized estimating equations to account for correlation (exchangeable) among reenrollments were used to estimate crude and adjusted relative risks to quantify associations between exposure and outcome. Adjustment in multivariable models included the PSs described above, GA at enrollment, and multifetal pregnancy. For the death outcomes, late stillbirth (≥28 weeks) and stillbirth (≥20 weeks), the primary exposure analysis included 3 planned comparisons using the 4-level drinking and smoking measure, specifically comparing the none/quit early group with the drinking only, smoking only, or dual (drinking and smoking) exposure groups, adjusted for confounding as described. Conservatively, for statistical testing that involved multiple comparisons, 2-sided 98.3% (based on Bonferroni correction) CIs were provided; otherwise, 95% CIs were provided. A 2-sided P < .05 was considered to be statistically significant, and 95% CIs were provided for tests of interaction. The causes of stillbirth using the 4-level drinking and smoking exposure measure were presented descriptively. The study design and determination of sample size were described elsewhere.11 In brief, the study was sized for the outcome of SIDS that resulted in a sample size of 12 000 women. Assuming a sample size of 12 000, then 8 per 1000 stillbirths in the Northern Plains of the US, 15 per 1000 stillbirths in South Africa, and 49% of women prenatally exposed yields 95% power to detect a relative risk of at least 2 when comparing women with prenatal exposure with those without prenatal exposure using a χ2 test for proportions with continuity correction and a 2-sided P < .05. The study was not powered to detect effect measure modification (ie, statistical interaction between 2-level drinking and 2-level smoking main effects based on factorial design); however, the findings were provided. The study was not designed to investigate genetic and biological interactions or to perform subgroup analysis (eg, stratified by site and cause of death); however, crude assessments by site and cause of stillbirth death were provided. Analyses were performed using SAS/STAT software, version 9.4 (SAS Institute Inc).

Materials

Innovations

Based on the provided information, 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 information and resources related to maternal health, including prenatal care, nutrition, and lifestyle choices. These apps can also offer reminders for prenatal visits and medication schedules.

2. Telemedicine Services: Implement telemedicine services that allow pregnant women to consult with healthcare providers remotely. This can help overcome geographical barriers and provide access to medical advice and support, especially for women in rural or underserved areas.

3. Community Health Workers: Train and deploy community health workers who can provide education, support, and basic healthcare services to pregnant women in their communities. These workers can bridge the gap between healthcare facilities and remote areas, ensuring that women receive the necessary care and information.

4. Maternal Health Hotlines: Establish hotlines staffed by trained healthcare professionals who can provide immediate assistance and guidance to pregnant women. These hotlines can address concerns, provide information, and connect women to appropriate healthcare services.

5. Public Awareness Campaigns: Launch public awareness campaigns to educate women and their families about the importance of maternal health and the available resources. These campaigns can help reduce stigma, increase knowledge, and encourage women to seek timely prenatal care.

6. Maternal Health Vouchers: Introduce voucher programs that provide financial assistance to pregnant women, enabling them to access essential maternal health services, such as prenatal check-ups, ultrasounds, and vaccinations.

7. Transportation Support: Develop transportation support programs that ensure pregnant women have access to reliable and affordable transportation to healthcare facilities. This can include partnerships with local transportation providers or the provision of dedicated transportation services.

8. Maternal Health Clinics: Establish specialized maternal health clinics that offer comprehensive care for pregnant women, including prenatal check-ups, counseling, and support services. These clinics can be designed to be easily accessible and provide a comfortable and welcoming environment for women.

9. Maternal Health Education Programs: Implement educational programs in schools and communities to raise awareness about maternal health, reproductive rights, and family planning. These programs can empower women to make informed decisions about their health and well-being.

10. Partnerships and Collaboration: Foster partnerships and collaboration between healthcare providers, government agencies, non-profit organizations, and community groups to improve access to maternal health services. By working together, these stakeholders can leverage their resources and expertise to address the barriers faced by pregnant women.

It’s important to note that the specific implementation of these innovations would require careful planning, coordination, and evaluation to ensure their effectiveness and sustainability.

AI Innovations Description

The study you provided examines the association between prenatal exposure to maternal drinking and smoking and the risk of stillbirth. The findings suggest that combined drinking and smoking after the first trimester of pregnancy may be associated with a significantly increased risk of late stillbirth.

Based on this research, a recommendation to improve access to maternal health and reduce the risk of stillbirth could be the implementation of targeted interventions and support programs for pregnant women who engage in drinking and smoking behaviors. These interventions could include:

1. Education and Awareness: Develop educational materials and campaigns to raise awareness about the risks of drinking and smoking during pregnancy. Provide information on the potential consequences for both the mother and the baby, including the increased risk of stillbirth.

2. Prenatal Care: Strengthen prenatal care services by integrating screening and counseling for alcohol and tobacco use. Healthcare providers should routinely ask pregnant women about their alcohol and tobacco consumption and provide appropriate guidance and support to help them quit or reduce their use.

3. Behavioral Interventions: Offer evidence-based behavioral interventions, such as motivational interviewing and cognitive-behavioral therapy, to pregnant women who are struggling to quit drinking or smoking. These interventions can help women develop coping strategies, set goals, and overcome barriers to behavior change.

4. Access to Treatment: Ensure that pregnant women who need additional support to quit drinking or smoking have access to specialized treatment services. This may include referrals to substance abuse treatment programs, counseling services, or support groups specifically tailored for pregnant women.

5. Peer Support: Establish peer support programs where pregnant women can connect with and receive support from other women who have successfully quit drinking or smoking during pregnancy. Peer support can provide encouragement, understanding, and practical tips for managing cravings and stress.

6. Policy and Legislation: Advocate for policies and legislation that promote a healthy and supportive environment for pregnant women. This may include restrictions on the marketing and availability of alcohol and tobacco products, as well as workplace policies that protect pregnant women from secondhand smoke exposure.

By implementing these recommendations, it is possible to improve access to maternal health services and support pregnant women in making healthier choices, ultimately reducing the risk of stillbirth and improving maternal and infant outcomes.

AI Innovations Methodology

Based on the provided description, here are some potential recommendations for improving access to maternal health:

1. Increase awareness and education: Implement comprehensive public health campaigns to raise awareness about the risks of prenatal exposure to alcohol and tobacco cigarettes. This can include targeted messaging for pregnant women and their families, as well as healthcare providers.

2. Strengthen prenatal care services: Enhance prenatal care services by ensuring that healthcare providers are trained to screen for and address alcohol and tobacco use during pregnancy. This can involve incorporating standardized screening tools and interventions into routine prenatal visits.

3. Provide support for smoking cessation and alcohol reduction: Offer evidence-based interventions and resources to support pregnant women in quitting smoking and reducing alcohol consumption. This can include counseling, behavioral interventions, and referrals to specialized programs.

4. Collaborate with community organizations: Partner with community organizations and stakeholders to develop and implement programs that address the social determinants of health and provide support to pregnant women. This can involve initiatives to reduce stress, improve access to healthy food options, and promote overall well-being.

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 geographic area for which the simulation will be conducted. This could be based on factors such as demographics, prevalence of maternal health issues, or availability of resources.

2. Collect baseline data: Gather relevant data on the current state of maternal health in the target population. This can include information on maternal mortality rates, access to prenatal care, prevalence of alcohol and tobacco use during pregnancy, and other relevant indicators.

3. Develop a simulation model: Create a mathematical or computational model that represents the target population and simulates the impact of the recommendations. This model should incorporate factors such as population size, demographics, healthcare infrastructure, and the potential effects of the recommendations on access to maternal health services.

4. Define outcome measures: Determine the specific outcomes that will be measured to assess the impact of the recommendations. This can include indicators such as changes in maternal mortality rates, improvements in prenatal care utilization, reductions in alcohol and tobacco use during pregnancy, and other relevant outcomes.

5. Input data and run simulations: Input the baseline data into the simulation model and run multiple simulations to assess the potential impact of the recommendations. This can involve varying parameters such as the implementation rate of the recommendations, the effectiveness of interventions, and other relevant factors.

6. Analyze results: Analyze the results of the simulations to determine the potential impact of the recommendations on improving access to maternal health. This can involve comparing the outcomes of the simulations to the baseline data and identifying key trends or patterns.

7. Interpret and communicate findings: Interpret the findings of the simulations and communicate them to relevant stakeholders. This can involve presenting the results in a clear and concise manner, highlighting the potential benefits of the recommendations, and identifying any limitations or uncertainties in the simulations.

8. Refine and iterate: Use the findings from the simulations to refine and iterate on the recommendations. This can involve adjusting parameters, exploring alternative scenarios, and incorporating feedback from stakeholders to further optimize the potential impact on improving access to maternal health.

It is important to note that the methodology for simulating the impact of recommendations may vary depending on the specific context and available data. The steps outlined above provide a general framework for conducting such simulations.

Author

Dima Health

Statistics:

Citations: 9

Identifiers:

DOI: 10.1001/jamanetworkopen.2021.21726

Research Areas:

Genetics and Genomics, Health System and Policy, Maternal Access, Maternal and Child Health, Noncommunicable Diseases, Sexual and Reproductive Health, Social Determinants, Substance Abuse, Technology and Innovations

Study Countries:

South Africa

Study Design:

Cohort Study, Cross Sectional Study, Grounded Theory

Study Approach:

Quantitative

Participants Gender:

Female