OBJECTIVES: To examine US in-hospital exclusive breastfeeding (EBF) and the associations with Baby-Friendly designation and neighborhood sociodemographic factors. METHODS: Hospital data from the 2018 Maternity Practices in Infant Nutrition and Care survey were linked to hospital zip code tabulation area (ZCTA) sociodemographic data from the 2014-2018 American Community Survey (n = 2,024). The percentages of residents in the hospital ZCTA were dichotomized based on the relative mean percentage of the hospital's metropolitan area, which were exposure variables (high/low Black hospitals, high/low poverty hospitals, high/low educational attainment hospitals) along with Baby-Friendly designation. Using linear regression, we examined the associations and effect measure modification between Baby-Friendly designation and hospital sociodemographic factors with in-hospital EBF prevalence. RESULTS: US mean in-hospital EBF prevalence was 55.1%. Baby-Friendly designation was associated with 9.1% points higher in-hospital EBF prevalence compared to non-designated hospitals [95% confidence interval (CI): 7.0, 11.2]. High Black hospitals and high poverty hospitals were associated with lower EBF prevalence (difference= -3.3; 95% CI: -5.1, -1.4 and - 3.8; 95% CI: -5.7, -1.8). High educational attainment hospitals were associated with higher EBF prevalence (difference = 6.7; 95% CI: 4.1, 9.4). Baby-Friendly designation was associated with significant effect measure modification of the in-hospital EBF disparity attributed to neighborhood level poverty (4.0% points higher in high poverty/Baby-Friendly designated hospitals than high poverty/non-Baby-Friendly designated hospitals).

Objective: The aim of this study is to examine in-hospital exclusive breastfeeding (EBF) and its association with sociodemographic factors, medical factors, breastfeeding intentions, and health care system breastfeeding support. Materials and Methods: We conducted a retrospective cross-sectional study using medical records from 2015 to 2019 of healthy term infants without breastfeeding contraindications at a public teaching hospital serving a racially and ethnically diverse patient population. Using multivariable regression analysis, we examined the associations between in-hospital EBF and sociodemographic factors, medical factors, breastfeeding intentions, and health care system breastfeeding support (in-hospital breastfeeding education and lactation support). Results: The prevalence of in-hospital EBF was 29.0%. The statistically significant findings from our fully adjusted regression analysis include that there was a higher prevalence of in-hospital EBF among adult mothers (prevalence ratio [PR]: range 1.78-1.96), married mothers (PR: 1.35, 95% confidence interval [CI]: 1.23-1.44), and mothers who were White (PR: 1.41, 95% CI: 1.20-1.66, compared with Black). Factors associated with a lower prevalence of in-hospital EBF were maternal diabetes (PR: 0.82, 95% CI: 0.70-0.95), pre-eclampsia/eclampsia (PR: 0.82, 95% CI: 0.71-0.95), cesarean delivery (PR: 0.84, 95% CI: 0.77-0.92), neonatal hypoglycemia (PR: 0.46, 95% CI: 0.36-0.59), and intention in the prenatal period to formula feed only (PR: 0.15, 95% CI: 0.10-0.22). In-hospital lactation support was associated with higher prevalence of in-hospital EBF (PR: 1.24, 95% CI: 1.16-1.33). Conclusions: Prioritizing lactation support for Black mothers, adolescent mothers, those intending in the prenatal period to formula feed only, and mother-infant dyads with certain medical factors could improve in-hospital EBF.

BACKGROUND: Individual measures of socioeconomic status (SES) have been associated with an increased risk of neural tube defects (NTDs); however, the association between neighborhood SES and NTD risk is unknown. Using data from the National Birth Defects Prevention Study (NBDPS) from 1997 to 2011, we investigated the association between measures of census tract SES and NTD risk. METHODS: The study population included 10,028 controls and 1829 NTD cases. We linked maternal addresses to census tract SES measures and used these measures to calculate the neighborhood deprivation index. We used generalized estimating equations to calculate adjusted odds ratios (aORs) and 95% confidence intervals (CIs) estimating the impact of quartiles of census tract deprivation on NTDs adjusting for maternal race-ethnicity, maternal education, and maternal age at delivery. RESULTS: Quartiles of higher neighborhood deprivation were associated with NTDs when compared with the least deprived quartile (Q2: aOR = 1.2; 95% CI = 1.0, 1.4; Q3: aOR = 1.3, 95% CI = 1.1, 1.5; Q4 (highest): aOR = 1.2; 95% CI = 1.0, 1.4). Results for spina bifida were similar; however, estimates for anencephaly and encephalocele were attenuated. Associations differed by maternal race-ethnicity. CONCLUSIONS: Our findings suggest that residing in a census tract with more socioeconomic deprivation is associated with an increased risk for NTDs, specifically spina bifida.

BACKGROUND: In-hospital exclusive breastfeeding (EBF) is associated with longer breastfeeding durations, yet only 64% of US newborns are EBF for 7 days. The Ten Steps to Successful Breastfeeding (Ten Steps) are a set of evidenced-based maternity practices shown to improve breastfeeding outcomes; these were updated in 2018. METHODS: Using hospital-level data from the 2018 Maternity Practices in Infant Nutrition and Care Survey (n = 2045 hospitals), we examined the prevalence of implementation of Ten Steps indicators (each step and total number of steps implemented). Using linear regression, we also examined the association between the steps and EBF prevalence adjusted for hospital characteristics and all other steps. Discharge support was not included in the models since it primarily occurs after hospital discharge. RESULTS: The most frequently implemented step was the provision of prenatal breastfeeding education (95.6%). Steps with low implementation included rooming-in (18.9%), facility policies supportive of breastfeeding (23.4%), and limited formula supplementation (28.2%). After adjusting for hospital characteristics and all other steps, limited formula supplementation (difference = 14.4: 95% confidence interval [CI]: 12.6, 16.1), prenatal breastfeeding education (difference = 7.0; 95% CI: 3.3, 10.8), responsive feeding (difference = 6.3; 95% CI: 3.7, 9.0), care right after birth (skin-to-skin; difference = 5.8; 95% CI: 4.2, 7.4), and rooming-in (difference = 2.4; 95% CI: 0.4, 4.6) were associated with higher in-hospital EBF prevalence. We found a dose-response relationship between the number of steps implemented and in-hospital EBF prevalence. CONCLUSION: Increased implementation of the updated Ten Steps may improve EBF and infant and maternal health outcomes.

BACKGROUND: Pregnant women less frequently receive Coronavirus Disease 2019 (COVID-19) vaccination and are at increased risk for adverse pregnancy outcomes from COVID-19. OBJECTIVES: First, describe the vaccination status, treatment, and outcomes of hospitalized, symptomatic pregnant women with COVID-19 and second, estimate whether treatment differs by pregnancy status among treatment-eligible (i.e., requiring supplemental oxygen per National Institutes of Health guidelines at the time of the study) women. STUDY DESIGN: During January-November 2021, the COVID-19-Associated Hospitalization Surveillance Network completed medical chart abstraction for a probability sample of 2,715 hospitalized women aged 15-49 years with laboratory-confirmed SARS-CoV-2 infection. Of these, 1,950 women had symptoms of COVID-19 upon admission; 336 were pregnant. We calculated weighted prevalence estimates of demographic and clinical characteristics, vaccination status, and outcomes among pregnant women with symptoms of COVID-19 upon admission. We used propensity score matching to estimate prevalence ratios (PR), and 95% confidence intervals (CI) of treatment-eligible patients who received remdesivir or systemic steroids by pregnancy status. RESULTS: Among 336 hospitalized pregnant women with symptomatic COVID-19, 39.6% were non-Hispanic Black, 24.8% were Hispanic or Latino, and 61.9% were aged 25-34 years. Among those with known COVID-19 vaccination status, 92.9% were unvaccinated. One-third (32.7%) were treatment-eligible. Among treatment-eligible pregnant women, 74.1% received systemic steroids and 61.4% received remdesivir. Among those that were no longer pregnant at discharge (n=180), 5.4% had spontaneous abortions and 3.5% had stillbirths. Of the 159 live births, 29.0% were pre-term. Among a propensity score-matched cohort of treatment-eligible hospitalized women of reproductive age, pregnant women were less likely than non-pregnant women to receive remdesivir (PR: 0.82, 95% CI 0.69-0.97) and systemic steroids (PR: 0.80, 95% CI 0.73-0.87). CONCLUSION: Most hospitalized pregnant patients with symptomatic COVID-19 were unvaccinated. Hospitalized pregnant patients were less likely to receive recommended remdesivir and systemic steroids compared to similar hospitalized non-pregnant women. Our results underscore the need to identify opportunities for improving COVID-19 vaccination, implementation of treatment of pregnant women, and the inclusion of pregnant women in clinical trials.

OBJECTIVE: To characterize county-level differences in pregnancy-related mortality as a function of sociospatial indicators. METHODS: We conducted a cross-sectional multilevel analysis of all pregnancy-related deaths and all live births with available ZIP code or county data in the Pregnancy Mortality Surveillance System during 2011-2016 for non-Hispanic Black, Hispanic (all races), and non-Hispanic White women aged 15-44 years. The exposures included 31 conceptually-grounded, county-specific sociospatial indicators that were collected from publicly available data sources and categorized into domains of demographic; general, reproductive, and behavioral health; social capital and support; and socioeconomic contexts. We calculated the absolute difference of county-level pregnancy-related mortality ratios (deaths per 100,000 live births) per 1-unit increase in the median absolute difference between women living in counties with higher compared with lower levels of each sociospatial indicator overall and stratified by race and ethnicity. RESULTS: Pregnancy-related mortality varied across counties and by race and ethnicity. Many sociospatial indicators were associated with county-specific pregnancy-related mortality ratios independent of maternal age, population size, and Census region. Across domains, the most harmful indicators were percentage of low-birth-weight births (absolute ratio difference [RD] 6.44; 95% CI 5.36-7.51), percentage of unemployed adults (RD 4.98; 95% CI 3.91-6.05), and food insecurity (RD 4.92; 95% CI 4.14-5.70). The most protective indicators were higher median household income (RD -2.76; 95% CI -3.28 to -2.24), percentage of college-educated adults (RD -2.28; 95% CI -2.81 to -1.75), and percentage of owner-occupied households (RD -1.66; 95% CI -2.29 to -1.03). The magnitude of these associations varied by race and ethnicity. CONCLUSION: This analysis identified sociospatial indicators of pregnancy-related mortality and showed an association between pregnancy-related deaths and place of residence overall and stratified by race and ethnicity. Understanding county-level context associated with pregnancy-related mortality may be an important step towards building public health evidence to inform action to reduce pregnancy-related mortality at local levels.

In-hospital infant formula supplementation of breastfed infants reduces breastfeeding duration, yet little is known about common reasons for infant formula supplementation. We examined the three most common reasons for in-hospital infant formula supplementation of healthy, term, breastfed infants in the US reported by hospital staff. Hospital data were obtained from the 2018 Maternity Practices in Infant Nutrition and Care survey (n = 2045), which is completed by hospital staff. An open-ended question on the top three reasons for in-hospital infant formula supplementation was analyzed using thematic qualitative analysis and the frequencies for each reason were reported. The top three most common reasons for in-hospital infant formula supplementation reported by hospital staff included medical indications (70.0%); maternal request/preference/feelings (55.9%); lactation management-related issues (51.3%); physical but non-medically indicated reasons (36.1%); social influences (18.8%); perceived cultural/societal/demographic factors (8.2%) and medical staff/institutional practices (4.7%). These findings suggest that a variety of factors should be considered to address unnecessary infant formula supplementation. Lactation management support delivered in a timely and culturally sensitive manner and targeted to mother-infant dyads with potential medical and physical indications may reduce unnecessary in-hospital infant formula supplementation.

BACKGROUND: The U.S. pregnancy-related mortality ratio has not improved over the past decade and includes striking disparities by race/ethnicity and by state. Understanding differences in pregnancy-related mortality across and within urban and rural areas can guide the development of interventions for preventing future pregnancy-related deaths. OBJECTIVE: We sought to compare pregnancy-related mortality across and within urban and rural counties by race/ethnicity and age. STUDY DESIGN: We conducted a descriptive analysis of 3,747 pregnancy-related deaths during 2011-2016 (the most recent available) with available ZIP code or county data in the Pregnancy Mortality Surveillance System, among Hispanic and non-Hispanic White, Black, American Indian/Alaska Native, and Asian/Pacific Islander women ages 15-44 years. We aggregated data by U.S. county and grouped counties per the National Center for Health Statistics Urban-Rural Classification Scheme for Counties. We used R statistical software, epitools, to calculate the pregnancy-related mortality ratio (number of pregnancy-related deaths per 100,000 live births) for each urban-rural grouping, obtain 95% confidence intervals, and perform exact tests of ratio comparisons using the Poisson distribution. RESULTS: Of the total 3,747 pregnancy-related deaths analyzed, 52% occurred in large metro counties and 7% occurred in noncore (rural) counties. Large metro counties had the lowest pregnancy-related mortality ratio (14.8, 95% CI: 14.2-15.5) while noncore counties had the highest (24.1, 95% CI: 21.4-27.1), including for most race/ethnicity and age groups. Pregnancy-related mortality ratio age disparities increased with rurality. Women ages 25-34 years and ages 35-44 years living in noncore counties had pregnancy-related mortality ratios 1.5 and 3 times higher, respectively, than women of the same age groups in large metro counties. Within each urban-rural category, pregnancy-related mortality ratios were higher among non-Hispanic Black women compared to non-Hispanic White women. Non-Hispanic American Indian/Alaska Native pregnancy-related mortality ratios in small metro, micropolitan, and noncore counties were 2-3 times that of non-Hispanic White women in the same areas. CONCLUSION: Although more than half of pregnancy-related deaths occurred in large metro counties, the pregnancy-related mortality ratio rose with increasing rurality. Disparities existed among urban-rural categories, including by age group and by race/ethnicity. Geographic location is an important context for initiatives to prevent future deaths and eliminate disparities. Further research is needed to better understand reasons for the observed urban-rural differences and to guide a multifactorial response to reduce pregnancy-related deaths.

Understanding the role of place and space in shaping the geographic distributions of chronic disease is critical to informing appropriate public health responses for chronic disease prevention and treatment. A geospatial perspective on chronic disease expands the focus of public health efforts beyond the individual, providing insights and guidance for action at the community, regional, and/or national levels. Accordingly, the articles in this special collection advance our understanding of population health dynamics and geospatial disparities for a wide range of chronic disease outcomes across 3 broad themes: | | Examining connections between community-level characteristics and population health | Developing and applying spatial statistical methods and new geospatial tools | Using maps and geospatial results to guide program and policy decisions

The risk of maternal death in the U.S. is higher than peer nations and rising, and varies dramatically by the race and place of residence of the woman. Critical efforts to reduce maternal mortality include patient risk stratification and system-level quality improvement efforts targeting specific aspects of clinical care. These efforts are important for addressing the causes of an individual's risk, but research to date suggests that individual risk factors alone do not adequately explain between-group disparities in pregnancy-related death by race, ethnicity, or geography. The holistic review and multidisciplinary makeup of maternal mortality review committees (MMRC) make them well positioned to fill knowledge gaps about the drivers of racial and geographic inequity in maternal death. However, committees may lack the conceptual framework, contextual data, and evidence base needed to identify community-based contributing factors to death, and when appropriate to make recommendations for future action. By incorporating a multileveled, theory-grounded framework for causes of health inequity, along with indicators of the 'community vital signs' - the social and community context in which women live, work, and seek healthcare - MMRCs may identify novel underlying factors at the community level that enhance understanding of racial and geographic inequity in maternal mortality. By considering evidence-informed community and regional resources and policies for addressing these factors, novel prevention recommendations, including recommendations that extend outside the realm of the formal health care system, may emerge.

Summary | What is already known about this topic? | Health departments are keenly aware of the importance of local-level data to effectively and efficiently reduce the burden of chronic disease. We asked 4 state and local health departments about their experiences using GIS to address chronic disease priorities. | | What is added by this report? | These responses reveal the extent to which maps and spatial analyses help to 1) document the geographic patterns of chronic disease, 2) inform resource allocation and policy, 3) develop culturally competent programs, and 4) assist with program planning, monitoring, and evaluation. | | What are the implications for public health practice? | The continued and enhanced application of GIS to chronic disease surveillance, prevention, and treatment priorities can provide valuable benefits to both health departments and the communities they serve.

STUDY OBJECTIVE: Quantitative data suggest that adolescent users of long-acting reversible contraception (LARC), as compared to short-acting methods (pill, patch, ring, depot medroxyprogesterone acetate [DMPA]), may be less likely to use condoms. We qualitatively describe and explain adolescent contraceptive users' motivations for condom use, including variation by contraceptive type. DESIGN: Individual, in-depth qualitative interviews, analyzed thematically. PARTICIPANTS: Sexually active contraceptive users 17-19 years old (n=30), including LARC (n=10), DMPA (n=10), and oral contraceptive (n=10) users. SETTING: Participants were recruited from public family planning clinics and an adolescent medicine clinic as well as university and other community settings in Atlanta, GA. RESULTS: Overall, most participants (n=25; 83.3%) used condoms with their more effective contraceptive method, although many used them inconsistently (n=11; 44%). Oral contraceptive users were particularly motivated to use condoms for pregnancy prevention, given concerns about contraceptive method efficacy and a desire to be on "the safe side". In contrast, LARC users were primarily motivated by sexually transmitted infection (STI) prevention. DMPA users' motivations were more mixed. Across contraceptive type, factors influencing condom use motivations included sexual health education, personal awareness and/or experience, and perceived consequences and risk. CONCLUSIONS: Given that all participants were using an effective contraceptive method, it is notable that pregnancy prevention was a prominent motivator for using condoms, although LARC users reported STI prevention to be a more important motivation. Parental and school-based sexual health education that clearly addresses STI prevention in addition to pregnancy prevention has the potential to influence condom use motivations and behavior.

A holistic view of racial and gender disparities that simultaneously compares multiple groups can suggest associated underlying contextual factors. Therefore, to more comprehensively understand temporal changes in combined racial and gender disparities, we examine variations in the orders of county-level race-gender specific heart disease death rates by age group from 1973-2015. We estimated county-level heart disease death rates by race, gender, and age group (35-44, 45-54, 55-64, 65-74, 75-84, >/= 85, and >/= 35) from the National Vital Statistics System of the National Center for Health Statistics from 1973-2015. We then ordered these rates from lowest to highest for each county and year. The predominant national rate order (i.e., white women (WW) < black women (BW) < white men (WM) < black men (BM)) was most common in younger age groups. Inverted rates for black women and white men (WW<WM<BW<BM) was observed nationally only for ages 35-44, but was observed in at least some counties for all age groups < 75. From 1973 through 1979, national rates for black men aged >/= 35 were lower than those for white men. This national observation was found in a minority of counties, primarily among ages 55-64 and 65-74. The observed rates orders and their differences over time and place suggest that social and economic forces may be driving trends in heart disease mortality. Learning more about the places and times that deviate from the predominant rate order can further inform our understanding of these macro-level drivers of heart disease mortality trends.

One hypothesized explanation for the recent slowing of declines in heart disease death rates is the generational shift in the timing and accumulation of risk factors. However, directly testing this hypothesis requires historical age-group-specific risk factor data that do not exist. Using national death records, we compared spatiotemporal patterns of heart disease death rates by age group, time period, and birth cohort to provide insight into possible drivers of trends. To do this, we calculated county-level percent change for five time periods (1973-1980, 1980-1990, 1990-2000, 2000-2010, 2010-2015) for four age groups (35-44, 45-54, 55-64, 65-74), resulting in eight birth cohorts for each decade from the 1900s through the 1970s. From 1973 through 1990, few counties experienced increased heart disease death rates. In 1990-2000, 49.0% of counties for ages 35-44 were increasing, while all other age groups continued to decrease. In 2000-2010, heart disease death rates for ages 45-54 increased in 30.4% of counties. In 2010-2015, all four age groups showed widespread increasing county-level heart disease death rates. Likewise, birth cohorts from the 1900s through the 1930s experienced consistently decreasing heart disease death rates in almost all counties. Similarly, with the exception of 2010-2015, most counties experienced decreases for the 1940s birth cohort. For birth cohorts in the 1950s, 1960s, and 1970s, increases were common and geographically widespread for all age groups and calendar years. This analysis revealed variation in trends across age groups and across counties. However, trends in heart disease death rates tended to be generally decreasing and increasing for early and late birth cohorts, respectively. These findings are consistent with the hypothesis that recent increases in heart disease mortality stem from the beginnings of the obesity and diabetes epidemics. However, the common geographic patterns within the earliest and latest time periods support the importance of place-based macro-level factors.

PURPOSE: Long-acting reversible contraceptive (LARC) methods do not require annual clinic visits for continuation, potentially impacting receipt of recommended sexually transmitted infection (STI)/human immunodeficiency virus (HIV) services for young women. We assess service receipt among new and continuing LARC users versus moderately and less effective method users and non-contraceptors. METHODS: Using 2011-2015 National Survey of Family Growth data from sexually active women aged 15-24 years (n = 2,018), we conducted logistic comparisons of chlamydia, any STI and HIV testing, and sexual risk assessment in the past year by current contraceptive type. RESULTS: Less than half of respondents were tested for chlamydia (40.9%), any STI (47.3%), or HIV (25.9%); 66.5% had their sexual risk assessed. Differences in service receipt between new and continuing LARC users as compared with moderately effective method users were not detected in multivariable models, except that continuing LARC users were less likely to be tested for HIV (adjusted prevalence ratio [aPR] = .52, 95% confidence interval [CI] = .32-.85). New, but not continuing, LARC users were more likely than less effective method users (aPR = 1.35, 95% CI = 1.03-1.76) and non-contraceptors (aPR = 1.43, 95% CI = 1.11-1.85) to have their sexual risk assessed, although both groups were more likely than non-contraceptors to be tested for chlamydia (new: aPR = 1.52, 95% CI = 1.08-2.15; continuing: aPR = 1.69, 95% CI = 1.24-2.29). CONCLUSIONS: We found little evidence that LARC use was associated with lower prevalence of STI testing. However, new, but not continuing, LARC users, as compared with those not using a method requiring a clinic visit, were more likely to have had their risk assessed, suggesting that initiating LARC may offer an opportunity to receive services that does not persist.

PURPOSE: Recent national trends show decelerating declines in heart disease mortality, especially among younger adults. National trends may mask variation by geography and age. We examined recent county-level trends in heart disease mortality by age group. METHODS: Using a Bayesian statistical model and National Vital Statistics Systems data, we estimated overall rates and percent change in heart disease mortality from 2010 through 2015 for four age groups (35-44, 45-54, 55-64, and 65-74 years) in 3098 US counties. RESULTS: Nationally, heart disease mortality declined in every age group except ages 55-64 years. County-level trends by age group showed geographically widespread increases, with 52.3%, 58.5%, 69.1%, and 42.0% of counties experiencing increases with median percent changes of 0.6%, 2.2%, 4.6%, and -1.5% for ages 35-44, 45-54, 55-64, and 65-74 years, respectively. Increases were more likely in counties with initially high heart disease mortality and outside large metropolitan areas. CONCLUSIONS: Recent national trends have masked local increases in heart disease mortality. These increases, especially among adults younger than age 65 years, represent challenges to communities across the country. Reversing these trends may require intensification of primary and secondary prevention-focusing policies, strategies, and interventions on younger populations, especially those living in less urban counties.

BACKGROUND: Access to transportation is vital to reducing the travel time to emergency obstetric and neonatal care (EmONC) for managing complications and preventing adverse maternal and neonatal outcomes. This study examines the distribution of travel times to EmONC in Kigoma Region, Tanzania, using various transportation schemes, to estimate the proportion of live births (a proxy indicator of women needing delivery care) with poor geographic access to EmONC services. METHODS: The 2014 Reproductive Health Survey of Kigoma Region identified 4 primary means of transportation used to travel to health facilities: walking, cycling, motorcycle, and 4-wheeled motor vehicle. A raster-based travel time model was used to map the 2-hour travel time catchment for each mode of transportation. Live birth density distributions were aggregated by travel time catchments, and by administrative council, to estimate the proportion of births with poor access. RESULTS: Of all live births in Kigoma Region, 13% occurred in areas where women can reach EmONC facilities within 2 hours on foot, 33% in areas that can be reached within 2 hours only by motorized vehicles, and 32% where it is impossible to reach EmONC facilities within 2 hours. Over 50% of births in 3 of the 8 administrative councils had poor estimated access. In half the councils, births with poor access could be reduced to no higher than 12% if all female residents had access to motorized vehicles. CONCLUSION: Significant differences in geographic access to EmONC in Kigoma Region, Tanzania, were observed both by location and by primary transportation type. As most of the population may only have good EmONC access when using mechanized or motorized vehicles, bicycles and motorcycles should be incorporated into the health transportation strategy. Collaboration between private transportation sectors and obstetric service providers could improve access to EmONC services among most populations. In areas where residents may not access EmONC facilities within 2 hours regardless of the type of transportation used, upgrading EmONC capacity among nearby non-EmONC facilities may be required to improve accessibility.

BACKGROUND: Although many studies have documented the dramatic declines in heart disease mortality in the United States at the national level, little attention has been given to the temporal changes in the geographic patterns of heart disease mortality. METHODS AND RESULTS: Age-adjusted and spatially smoothed county-level heart disease death rates were calculated for 2-year intervals from 1973 to 1974 to 2009 to 2010 for those aged ≥35 years. Heart disease deaths were defined according to the International Classification of Diseases codes for diseases of the heart in the eighth, ninth, and tenth revisions of the International Classification of Diseases. A fully Bayesian spatiotemporal model was used to produce precise rate estimates, even in counties with small populations. A substantial shift in the concentration of high-rate counties from the Northeast to the Deep South was observed, along with a concentration of slow-decline counties in the South and a nearly 2-fold increase in the geographic inequality among counties. CONCLUSIONS: The dramatic change in the geographic patterns of heart disease mortality during 40 years highlights the importance of small-area surveillance to reveal patterns that are hidden at the national level, gives communities the historical context for understanding their current burden of heart disease, and provides important clues for understanding the determinants of the geographic disparities in heart disease mortality.

BACKGROUND: Examining small-area differences in the strength of declining heart disease mortality by race and sex provides important context for current racial and geographic disparities and identifies localities that could benefit from targeted interventions. We identified and described temporal trends in declining county-level heart disease mortality by race, sex, and geography between 1973 and 2010. METHODS AND RESULTS: Using a Bayesian hierarchical model, we estimated age-adjusted mortality with diseases of the heart listed as the underlying cause for 3099 counties. County-level percentage declines were calculated by race and sex for 3 time periods (1973-1985, 1986-1997, 1998-2010). Strong declines were statistically faster or no different than the total national decline in that time period. We observed county-level race-sex disparities in heart disease mortality trends. Continual (from 1973 to 2010) strong declines occurred in 73.2%, 44.6%, 15.5%, and 17.3% of counties for white men, white women, black men, and black women, respectively. Delayed (1998-2010) strong declines occurred in 15.4%, 42.0%, 75.5%, and 76.6% of counties for white men, white women, black men, and black women, respectively. Counties with the weakest patterns of decline were concentrated in the South. CONCLUSIONS: Since 1973, heart disease mortality has declined substantially for these race-sex groups. Patterns of decline differed by race and geography, reflecting potential disparities in national and local drivers of these declines. Better understanding of racial and geographic disparities in the diffusion of heart disease prevention and treatment may allow us to find clues to progress toward racial and geographic equity in heart disease mortality.

We appreciate Dr. Harper's thoughtful and thorough commentary (1) on our paper (2). From our vantage point, there are more areas of agreement than disagreement. Although we do not deny being intrigued by the “buried epidemiologic treasure” of an observed cohort effect, our motivation was not to champion age-period-cohort (APC) analysis as a faultless method but instead to use the APC toolbox to examine another elusive process: the temporal evolution of a population health disparity. | | The ubiquity of racial disparities in health can make them seem inevitable. However, trends in black-white disparities in heart disease mortality suggest that such inequity is not a fixed constant but a time-varying phenomenon. Instead of examining why disparities arose, we focused on when they arose. As a descriptive tool, the APC toolbox—consisting of nonparametric graphical tools in addition to the 3-factor regression on which Dr. Harper primarily focused attention—offers a set of analytical approaches for describing the time components conflated in secular trends. | | Regrettably, several assumptions underpinning our analysis were left unclear. Our decision to constrain the first 2 periods in order to make the 3-factor regression identifiable reflected our somewhat unorthodox approach to APC analysis, which primarily examined rate ratios rather than rates. While the first 2 periods saw substantial secular declines in death rates, these periods also had relatively stable rate ratios.

Against the backdrop of late 20th century declines in heart disease mortality in the United States, race-specific rates diverged because of slower declines among blacks compared with whites. To characterize the temporal dynamics of emerging black-white racial disparities in heart disease mortality, we decomposed race-sex-specific trends in an age-period-cohort (APC) analysis of US mortality data for all diseases of the heart among adults aged ≥35 years from 1973 to 2010. The black-white gap was largest among adults aged 35-59 years (rate ratios ranged from 1.2 to 2.7 for men and from 2.3 to 4.0 for women) and widened with successive birth cohorts, particularly for men. APC model estimates suggested strong independent trends across generations ("cohort effects") but only modest period changes. Among men, cohort-specific black-white racial differences emerged in the 1920-1960 birth cohorts. The apparent strength of the cohort trends raises questions about life-course inequalities in the social and health environments experienced by blacks and whites which could have affected their biomedical and behavioral risk factors for heart disease. The APC results suggest that the genesis of racial disparities is neither static nor restricted to a single time scale such as age or period, and they support the importance of equity in life-course exposures for reducing racial disparities in heart disease.

PURPOSE: To demonstrate the implications of choosing analytical methods for quantifying spatiotemporal trends, we compare the assumptions, implementation, and outcomes of popular methods using county-level heart disease mortality in the United States between 1973 and 2010. METHODS: We applied four regression-based approaches (joinpoint regression, both aspatial and spatial generalized linear mixed models, and Bayesian space-time model) and compared resulting inferences for geographic patterns of local estimates of annual percent change and associated uncertainty. RESULTS: The average local percent change in heart disease mortality from each method was -4.5%, with the Bayesian model having the smallest range of values. The associated uncertainty in percent change differed markedly across the methods, with the Bayesian space-time model producing the narrowest range of variance (0.0-0.8). The geographic pattern of percent change was consistent across methods with smaller declines in the South Central United States and larger declines in the Northeast and Midwest. However, the geographic patterns of uncertainty differed markedly between methods. CONCLUSIONS: The similarity of results, including geographic patterns, for magnitude of percent change across these methods validates the underlying spatial pattern of declines in heart disease mortality. However, marked differences in degree of uncertainty indicate that Bayesian modeling offers substantially more precise estimates.

Racial residential segregation has been associated with an increased risk for heart disease and stroke deaths. However, there has been little research into the role that candidate mediating pathways may play in the relationship between segregation and heart disease or stroke deaths. In this study, we examined the relationship between metropolitan statistical area (MSA)-level segregation and heart disease and stroke mortality rates, by age and race, and also estimated the effects of various educational, economic, social, and health-care indicators (which we refer to as pathways) on this relationship. We used Poisson mixed models to assess the relationship between the isolation index in 265 U.S. MSAs and county-level (heart disease, stroke) mortality rates. All models were stratified by race (non-Hispanic black, non-Hispanic white), age group (35-64 years, ≥65 years), and cause of death (heart disease, stroke). We included each potential pathway in the model separately to evaluate its effect on the segregation-mortality association. Among blacks, segregation was positively associated with heart disease mortality rates in both age groups but only with stroke mortality rates in the older age group. Among whites, segregation was marginally associated with heart disease mortality rates in the younger age group and was positively associated with heart disease mortality rates in the older age group. Three of the potential pathways we explored attenuated relationships between segregation and mortality rates among both blacks and whites: percentage of female-headed households, percentage of residents living in poverty, and median household income. Because the percentage of female-headed households can be seen as a proxy for the extent of social disorganization, our finding that it has the greatest attenuating effect on the relationship between racial segregation and heart disease and stroke mortality rates suggests that social disorganization may play a strong role in the elevated rates of heart disease and stroke found in racially segregated metropolitan areas.

OBJECTIVES: U.S. women experience high rates of unplanned pregnancy and sexually transmitted infections (STIs), yet they seldom combine condoms with highly effective contraceptives for optimal protection. Because oral contraceptives (OCs) have been the predominant form of highly effective contraception in the U.S., it is unknown whether condom use is similarly low with increasingly promoted user-independent methods. METHODS: We used weighted data from the National Survey of Family Growth to assess condom use odds among women relying on OCs vs. user-independent methods (i.e., injectibles, intrauterine devices, and implants). We also estimated the expected reduction in unplanned pregnancies and abortions if half or all of the women currently using a single highly effective method also used condoms. RESULTS: Across every demographic subgroup based on age, partner status, race/ethnicity, household income, and education, condom use prevalence was lower for women relying on user-independent methods vs. OCs. Multivariable models for adult women also revealed a significant reduction within most demographic subgroups in the odds of condom use among women relying on user-independent methods vs. OCs. Population estimates suggested that if half of all women using highly effective methods alone also used condoms, approximately 40% of unplanned pregnancies and abortions among these women could be prevented, for an annual reduction of 393,000 unplanned pregnancies and nearly 76,000 abortions. If all highly effective method users also used condoms, approximately 80% of unplanned pregnancies and abortions among these women could be prevented, for an annual reduction of 786,000 unplanned pregnancies and nearly 152,000 abortions. CONCLUSIONS: Adding condoms to other methods should be considered seriously as the first line of defense against unplanned pregnancy and STls. This analysis can serve to target interventions where dual-method promotion is needed most.