Counseling women of reproductive age about emergency preparedness - Provider attitudes and practices.

We report healthcare provider attitudes and practices on emergency preparedness counseling for women of reproductive age (WRA), including pregnant, postpartum, and lactating women (PPLW), for disasters and weather emergencies. DocStyles is a web-based panel survey of primary healthcare providers in the United States. During March 17-May 17, 2021, obstetricians-gynecologists, family practitioners, internists, nurse practitioners, and physician assistants were asked about the importance of emergency preparedness counseling, level of confidence, frequency, barriers to providing counseling, and preferred resources to support counseling among WRA and PPLW. We calculated frequencies of provider attitudes and practices, and prevalence ratios with 95% CIs for questions with binary responses. Among 1503 respondents (family practitioners (33%), internists (34%), obstetrician-gynecologists (17%), nurse practitioners (8%), and physician assistants (8%)), 77% thought emergency preparedness was important, and 88% thought counseling was necessary for patient health and safety. However, 45% of respondents did not feel confident providing emergency preparedness counseling, and most (70%) had never talked to PPLW about this topic. Respondents cited not having time during clinical visits (48%) and lack of knowledge (34%) as barriers to providing counseling. Most respondents (79%) stated they would use emergency preparedness educational materials for WRA, and 60% said they were willing to take an emergency preparedness training. Healthcare providers have opportunities to provide emergency preparedness counseling; however, many have not, noting lack of time and knowledge as barriers. Emergency preparedness resources combined with training may improve healthcare provider confidence and increase delivery of emergency preparedness counseling.

Pandemic-related stressors and mental health among women with a live birth in 2020.

The objective of this analysis was to assess the associations between pandemic-related stressors and feeling more anxious/depressed, among women with a live birth. We analyzed data from the Pregnancy Risk Assessment Monitoring System (PRAMS) COVID-19 maternal experiences supplement, implemented in 29 U.S. jurisdictions from October 2020-June 2021, among women with a live birth during April-December 2020. We examined stressors by type (economic, housing, childcare, food insecurity, partner, COVID-19 illness) and score (number of stressor types experienced [none, 1-2, 3-4, or 5-6]). Outcomes were feeling 1) more anxious and 2) more depressed than usual due to the pandemic. We calculated adjusted prevalence ratios estimating associations between stressors and outcomes. Among 12,525 respondents, half reported feeling more anxious and 28% more depressed than usual. The prevalence of stressor types was 50% economic, 41% childcare, 18% partner, 17% food insecurity, 12% housing, and 10% COVID-19 illness. Respondents who experienced partner stressors (anxious aPR: 1.81, 95% CI: 1.73-1.90; depressed aPR: 3.01, 95% CI: 2.78-3.25) and food insecurity (anxious aPR: 1.79, 95% CI: 1.71-1.88; depressed aPR: 2.32, 95% CI: 2.13-2.53) had the largest associations with feeling more anxious and depressed than usual. As stressor scores increased, so did the aPRs for feeling more anxious and more depressed due to the pandemic. COVID-19 stressors, not COVID-19 illness, were found to be significantly associated with feeling more anxious and depressed. Pregnant and postpartum women might benefit from access to supports and services to address pandemic-related stressors/social-determinants and feelings of anxiety and depression.

SARS-CoV-2 outbreak among staff and evacuees at Operation Allies Welcome Safe Havens.

We report on five SARS-CoV-2 congregate setting outbreaks at U.S. Operation Allies Welcome Safe Havens/military facilities. Outbreak data were collected, and attack rates were calculated for various populations. Even in vaccinated populations, there was rapid spread, illustrating the importance of institutional prevention and mitigation policies in congregate settings.

Differences in delivery hospitalization experiences during the COVID-19 pandemic by maternal race and ethnicity, Pregnancy Risk Assessment Monitoring System, 2020.

OBJECTIVE: We investigated maternal COVID-19 related experiences during delivery hospitalizations, and whether experiences differed by maternal race and ethnicity. STUDY DESIGN: Data from the Pregnancy Risk Assessment Monitoring System among women with live births between April-December 2020 were used. Adjusted prevalence ratios (aPR) and 95% confidence intervals (CI) estimated associations between maternal race and ethnicity and COVID-19 related delivery experiences. RESULTS: Among 12,879 women, 3.6% reported infant separation and 1.8% reported not being allowed support persons. Compared with non-Hispanic White women, American Indian/Alaska Native (AI/AN) (aPR = 2.7; CI: 1.2-6.2), Hispanic (aPR = 2.2; CI: 1.5-3.1), non-Hispanic Black (aPR = 2.4; CI: 1.7-3.6), and non-Hispanic Asian (aPR = 2.8; CI: 1.6-4.9) women reported more infant separation due to COVID-19. Not being allowed support persons was more common among AI/AN (aPR = 5.2; CI: 1.8-14.8) and non-Hispanic Black (aPR = 2.3; CI: 1.3-4.1) women. CONCLUSIONS: COVID-19 related delivery hospitalization experiences were unequally distributed among racial and ethnic minorities.

Assessing racial residential segregation as a risk factor for severe maternal morbidity.

PURPOSE: To measure associations of area-level racial and economic residential segregation with severe maternal morbidity (SMM). METHODS: We conducted a retrospective cohort study of births at two Philadelphia hospitals between 2018 and 2020 to analyze associations of segregation, quantified using the Index of Concentration at the Extremes (ICE), with SMM. We used stratified multivariable, multilevel, logistic regression models to determine whether associations of ICE with SMM varied by self-identified race or hospital catchment. RESULTS: Of the 25,979 patients (44.1% Black, 35.8% White), 1381 (5.3%) had SMM (Black [6.1%], White [4.4%]). SMM was higher among patients residing outside (6.3%), than inside (5.0%) Philadelphia (P < .001). Overall, ICE was not associated with SMM. However, ICErace (higher proportion of White vs. Black households) was associated with lower odds of SMM among patients residing inside Philadelphia (aOR 0.87, 95% CI: 0.80-0.94) and higher odds outside Philadelphia (aOR 1.12, 95% CI: 0.95-1.31). Moran's I indicated spatial autocorrelation of SMM overall (P < .001); when stratified, autocorrelation was only evident outside Philadelphia. CONCLUSIONS: Overall, ICE was not associated with SMM. However, higher ICErace was associated with lower odds of SMM among Philadelphia residents. Findings highlight the importance of hospital catchment area and referral patterns in spatial analyses of hospital datasets.

CDC Division of Reproductive Health's Emergency Preparedness Resources and Activities for Radiation Emergencies: Public Health Considerations for Women's Reproductive Health.

Pregnant, postpartum, and lactating people, and infants have unique needs during public health emergencies, including nuclear and radiological incidents. This report provides information on the CDC Division of Reproductive Health's emergency preparedness and response activities to address the needs of women of reproductive age (aged 15-49 years), people who are pregnant, postpartum, or lactating, and infants during a radiation emergency. Highlighted preparedness activities include: (1) development of a quick reference guide to inform key questions about pregnant, postpartum, and lactating people, and infants during radiation emergencies; and (2) exercising the role of reproductive health experts during nuclear and radiological incident preparedness activities.

An algorithm to identify residential mobility from electronic health-record data.

BACKGROUND: Environmental, social and economic exposures can be inferred from address information recorded in an electronic health record. However, these data often contain administrative errors and misspellings. These issues make it challenging to determine whether a patient has moved, which is integral for accurate exposure assessment. We aim to develop an algorithm to identify residential mobility events and avoid exposure misclassification. METHODS: At Penn Medicine, we obtained a cohort of 12 147 pregnant patients who delivered between 2013 and 2017. From this cohort, we identified 9959 pregnant patients with address information at both time of delivery and one year prior. We developed an algorithm entitled REMAP (Relocation Event Moving Algorithm for Patients) to identify residential mobility during pregnancy and compared it to using ZIP code differences alone. We assigned an area-deprivation exposure score to each address and assessed how residential mobility changed the deprivation scores. RESULTS: To assess the accuracy of our REMAP algorithm, we manually reviewed 3362 addresses and found that REMAP was 95.7% accurate. In this large urban cohort, 41% of patients moved during pregnancy. REMAP outperformed the comparison of ZIP codes alone (82.9%). If residential mobility had not been taken into account, absolute area deprivation would have misclassified 39% of the patients. When setting a threshold of one quartile for misclassification, 24.4% of patients would have been misclassified. CONCLUSIONS: Our study tackles an important characterization problem for exposures that are assigned based upon residential addresses. We demonstrate that methods using ZIP code alone are not adequate. REMAP allows address information from electronic health records to be used for accurate exposure assessment and the determination of residential mobility, giving researchers and policy makers more reliable information.

Neighborhood deprivation increases the risk of Post-induction cesarean delivery.

OBJECTIVE: The purpose of this study was to measure the association between neighborhood deprivation and cesarean delivery following labor induction among people delivering at term (≥37 weeks of gestation). MATERIALS AND METHODS: We conducted a retrospective cohort study of people ≥37 weeks of gestation, with a live, singleton gestation, who underwent labor induction from 2010 to 2017 at Penn Medicine. We excluded people with a prior cesarean delivery and those with missing geocoding information. Our primary exposure was a nationally validated Area Deprivation Index with scores ranging from 1 to 100 (least to most deprived). We used a generalized linear mixed model to calculate the odds of postinduction cesarean delivery among people in 4 equally-spaced levels of neighborhood deprivation. We also conducted a sensitivity analysis with residential mobility. RESULTS: Our cohort contained 8672 people receiving an induction at Penn Medicine. After adjustment for confounders, we found that people living in the most deprived neighborhoods were at a 29% increased risk of post-induction cesarean delivery (adjusted odds ratio = 1.29, 95% confidence interval, 1.05-1.57) compared to the least deprived. In a sensitivity analysis, including residential mobility seemed to magnify the effect sizes of the association between neighborhood deprivation and postinduction cesarean delivery, but this information was only available for a subset of people. CONCLUSIONS: People living in neighborhoods with higher deprivation had higher odds of postinduction cesarean delivery compared to people living in less deprived neighborhoods. This work represents an important first step in understanding the impact of disadvantaged neighborhoods on adverse delivery outcomes.

Individual-Level and Neighborhood-Level Risk Factors for Severe Maternal Morbidity.

OBJECTIVE: To investigate the association between individual-level and neighborhood-level risk factors and severe maternal morbidity. METHODS: This was a retrospective cohort study of all pregnancies delivered between 2010 and 2017 in the University of Pennsylvania Health System. International Classification of Diseases codes classified severe maternal morbidity according to the Centers for Disease Control and Prevention guidelines. Logistic regression modeling evaluated individual-level risk factors for severe maternal morbidity, such as maternal age and preeclampsia diagnosis. Additionally, we used spatial autoregressive modeling to assess Census-tract, neighborhood-level risk factors for severe maternal morbidity such as violent crime and poverty. RESULTS: Overall, 63,334 pregnancies were included, with a severe maternal morbidity rate of 2.73%, or 272 deliveries with severe maternal morbidity per 10,000 delivery hospitalizations. In our multivariable model assessing individual-level risk factors for severe maternal morbidity, the magnitude of risk was highest for patients with a cesarean delivery (adjusted odds ratio [aOR] 3.50, 95% CI 3.15-3.89), stillbirth (aOR 4.60, 95% CI 3.31-6.24), and preeclampsia diagnosis (aOR 2.71, 95% CI 2.41-3.03). Identifying as White was associated with lower odds of severe maternal morbidity at delivery (aOR 0.73, 95% CI 0.61-0.87). In our final multivariable model assessing neighborhood-level risk factors for severe maternal morbidity, the rate of severe maternal morbidity increased by 2.4% (95% CI 0.37-4.4%) with every 10% increase in the percentage of individuals in a Census tract who identified as Black or African American when accounting for the number of violent crimes and percentage of people identifying as White. CONCLUSION: Both individual-level and neighborhood-level risk factors were associated with severe maternal morbidity. These factors may contribute to rising severe maternal morbidity rates in the United States. Better characterization of risk factors for severe maternal morbidity is imperative for the design of clinical and public health interventions seeking to lower rates of severe maternal morbidity and maternal mortality.

Feasibility and acceptability of monitoring personal air pollution exposure with sensors for asthma self-management.

BACKGROUND: Exposure to fine particulate matter (PM2.5) increases the risk of asthma exacerbations, and thus, monitoring personal exposure to PM2.5 may aid in disease self-management. Low-cost, portable air pollution sensors offer a convenient way to measure personal pollution exposure directly and may improve personalized monitoring compared with traditional methods that rely on stationary monitoring stations. We aimed to understand whether adults with asthma would be willing to use personal sensors to monitor their exposure to air pollution and to assess the feasibility of using sensors to measure real-time PM2.5 exposure. METHODS: We conducted semi-structured interviews with 15 adults with asthma to understand their willingness to use a personal pollution sensor and their privacy preferences with regard to sensor data. Student research assistants used HabitatMap AirBeam devices to take PM2.5 measurements at 1-s intervals while walking in Philadelphia neighborhoods in May-August 2018. AirBeam PM2.5 measurements were compared to concurrent measurements taken by three nearby regulatory monitors. RESULTS: All interview participants stated that they would use a personal air pollution sensor, though the consensus was that devices should be small (watch- or palm-sized) and light. Patients were generally unconcerned about privacy or sharing their GPS location, with only two stating they would not share their GPS location under any circumstances. PM2.5 measurements were taken using AirBeam sensors on 34 walks that extended through five Philadelphia neighborhoods. The range of sensor PM2.5 measurements was 0.6-97.6 µg/mL (mean 6.8 µg/mL), compared to 0-22.6 µg/mL (mean 9.0 µg/mL) measured by nearby regulatory monitors. Compared to stationary measurements, which were only available as 1-h integrated averages at discrete monitoring sites, sensor measurements permitted characterization of fine-scale fluctuations in PM2.5 levels over time and space. CONCLUSIONS: Patients were generally interested in using sensors to monitor their personal exposure to PM2.5 and willing to share personal sensor data with health care providers and researchers. Compared to traditional methods of personal exposure assessment, sensors captured personalized air quality information at higher spatiotemporal resolution. Improvements to currently available sensors, including more reliable Bluetooth connectivity, increased portability, and longer battery life would facilitate their use in a general patient population.

WellExplorer: an integrative resource linking hydraulic fracturing chemicals with hormonal pathways and geographic location.

Exposure to hydraulic fracturing fluid in drinking water increases the risk of many adverse health outcomes. Unfortunately, most individuals and researchers are unaware of the health risks posed by a particular well due to the diversity of chemical ingredients used across sites. We constructed WellExplorer (http://WellExplorer.org), an interactive tool for researchers and community members to use for retrieving information regarding the hormonal, testosterone and estrogen modulators located at each well. We found that wells in Alabama use a disproportionately high number of ingredients targeting estrogen pathways, while Illinois, Ohio and Pennsylvania use a disproportionately high number of ingredients targeting testosterone pathways. Researchers can utilize WellExplorer to study health outcomes related to exposure to fracturing chemicals in their population-based cohorts. Community members can use this resource to search their home or work locations (e.g. town or zip code) to determine proximity between where they live or work and specific hormonal exposures.