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To evaluate the effectiveness of netarsudil in combination with other ocular hypotensive agents in patients with open-angle glaucoma (OAG) or ocular hypertension (OHT).Retrospective cohort study.All patients with OAG or OHT with netarsudil added to a regimen of at least 1 other ocular hypotensive agent between March 2018 and March 2019.Subjects with at least 2 baseline intraocular pressure (IOP) measurements on the same medication regimen before initiation of netarsudil were included. Subjects were excluded if they experienced other changes in their ocular hypotensive medication regimen.Change in IOP after initiation of netarsudil was assessed using linear mixed-effect models. Kaplan-Meier survival analysis was used to evaluate the time to discontinuation of netarsudil for any reason.Netarsudil was prescribed for 191 eyes of 138 patients. All of these subjects were included in the analysis of adverse effects. Twelve subjects discontinued netarsudil before the first follow-up visit because of adverse effects, leaving 175 eyes of 126 patients with at least 1 follow-up visit while using netarsudil included in the effectiveness analysis. The mean baseline IOP ± standard deviation was 17.1 ± 5.2 mmHg on a median of 2 ocular hypotensive medications. Including all observations on the same medication regimen after the addition of netarsudil, the mean IOP was 15.0 ± 4.5 mmHg, with a mean reduction of 2.2 mmHg (P0.001). A reduction in IOP was observed in eyes on 1 (2.0 mmHg, P0.001), 2 (1.0 mmHg, P = 0.12), 3 (3.0 mmHg, P0.001), and 4 (2.9 mmHg, P = 0.002) medications at baseline. A sustained ≥ 20% IOP reduction was observed in 16.2% of 123 eyes with at least 2 observations on treatment with netarsudil. Of the 138 subjects who were treated with netarsudil, 26.8% discontinued it because of adverse effects. The median time to discontinuation of netarsudil for any reason was 88 days.This study demonstrates a modest reduction in IOP is achievable with netarsudil in patients with OAG or OHT who are taking as many as 4 ocular hypotensive medications. The incidence of discontinuation due to adverse effects or inadequate efficacy was high.

Objective:To investigate if food security mediated the impact of a nutrition-sensitive agroecology intervention on women’s depressive symptoms.Design:We used annual longitudinal data (four time points) from a cluster-randomised effectiveness trial of a participatory nutrition-sensitive agroecology intervention, the Singida Nutrition and Agroecology Project. Structural equation modelling estimation of total, natural direct and natural indirect effects was used to investigate food security’s role in the intervention’s impact on women’s risk of probable depression (Center for Epidemiologic Studies Depression Scale > 17) across 3 years.Setting:Rural Singida, Tanzania.Participants:548 food insecure, married, smallholder women farmers with children < 1 year old at baseline.Results:At baseline, one-third of the women in each group had probable depression (Control: 32·0 %, Intervention: 31·9 %, P difference = 0·97). The intervention lowered the odds of probable depression by 43 % (OR = 0·57, 95 % CI: 0·43, 0·70). Differences in food insecurity explained approximately 10 percentage points of the effects of the intervention on odds of probable depression (OR = 0·90, 95 % CI: 0·83, 0·95).Conclusions:This is the first evidence of the strong, positive effect that lowering food insecurity has on reducing women’s depressive symptoms. Nutrition-sensitive agricultural interventions can have broader impacts than previously demonstrated, i.e. improvements in mental health; changes in food security play an important causal role in this pathway. As such, these data suggest participatory nutrition-sensitive agroecology interventions have the potential to be an accessible method of improving women’s well-being in farming communities.

When reporting results from randomized experiments, researchers often choose to present a per-protocol effect in addition to an intention-to-treat effect. However, these per-protocol effects are often described retrospectively, for example, comparing outcomes among individuals who adhered to their assigned treatment strategy throughout the study. This retrospective definition of a per-protocol effect is often confounded and cannot be interpreted causally because it encounters treatment-confounder feedback loops, where past confounders affect future treatment, and current treatment affects future confounders. Per-protocol effects estimated using this method are highly susceptible to the placebo paradox, also called the “healthy adherers” bias, where individuals who adhere to placebo appear to have better survival than those who don’t. This result is generally not due to a benefit of placebo, but rather is most often the result of uncontrolled confounding. Here, we aim to provide an overview to causal inference for survival outcomes with time-varying exposures for static interventions using inverse probability weighting. The basic concepts described here can also apply to other types of exposure strategies, although these may require additional design or analytic considerations. We provide a workshop guide with solutions manual, fully reproducible R, SAS, and Stata code, and a simulated dataset on a GitHub repository for the reader to explore.

Background : Coronavirus disease 2019 (COVID-19) data from race/ethnic subgroups remain limited, potentially masking subgroup-level heterogeneity. We evaluated differences in outcomes in Asian American/Pacific Islander (AAPI) and Hispanic/Latino subgroups compared with non-Hispanic White patients hospitalized with COVID-19. Methods : In the American Heart Association COVID-19 registry including 105 US hospitals, mortality and major adverse cardiovascular events in adults age ≥18 years hospitalized with COVID-19 between March-November 2020 were evaluated. Race/ethnicity groups included AAPI overall and subgroups (Chinese, Asian Indian, Vietnamese, and Pacific Islander), Hispanic/Latino overall and subgroups (Mexican, Puerto Rican), compared with non-Hispanic White (NHW). Results : Among 13,511 patients, 7% were identified as AAPI (of whom 17% were identified as Chinese, 9% Asian Indian, 8% Pacific Islander, and 7% Vietnamese); 35% as Hispanic (of whom 15% were identified as Mexican and 1% Puerto Rican); and 59% as NHW. Mean [SD] age at hospitalization was lower in Asian Indian (60.4 [17.4] years), Pacific Islander (49.4 [16.7] years), and Mexican patients (57.4 [16.9] years), compared with NHW patients (66.9 [17.3] years, p

Background Cardiovascular disease mortality related to heart failure (HF) is rising in the United States. It is unknown whether trends in HF mortality are consistent across geographic areas and are associated with state‐level variation in cardiovascular health (CVH). The goal of the present study was to assess regional and state‐level trends in cardiovascular disease mortality related to HF and their association with variation in state‐level CVH. Methods and Results Age‐adjusted mortality rates (AAMR) per 100 000 attributable to HF were ascertained using the Centers for Disease Control and Prevention's Wide‐Ranging Online Data for Epidemiologic Research from 1999 to 2017. CVH at the state‐level was quantified using the Behavioral Risk Factor Surveillance System. Linear regression was used to assess temporal trends in HF AAMR were examined by census region and state and to examine the association between state‐level CVH and HF AAMR. AAMR attributable to HF declined from 1999 to 2011 and increased between 2011 and 2017 across all census regions. Annual increases after 2011 were greatest in the Midwest (β=1.14 [95% CI, 0.75, 1.53]) and South (β=0.96 [0.66, 1.26]). States in the South and Midwest consistently had the highest HF AAMR in all time periods, with Mississippi having the highest AAMR (109.6 [104.5, 114.6] in 2017). Within race‒sex groups, consistent geographic patterns were observed. The variability in HF AAMR was associated with state‐level CVH ( P Conclusions Wide geographic variation exists in HF mortality, with the highest rates and greatest recent increases observed in the South and Midwest. Higher levels of poor CVH in these states suggest the potential for interventions to promote CVH and reduce the burden of HF.

INTRODUCTION: Rates of gestational diabetes mellitus (GDM) are increasing in parallel with rates of overweight and obesity. This analysis examines nationwide trends in the population-attributable fraction for GDM associated with prepregnancy overweight and obesity. METHODS: A serial, cross-sectional study was performed using U.S. population-based Birth Data Files maintained by the National Center for Health Statistics between 2011 and 2019. Live singleton births to nulliparous women aged 15–44 years were included, and all analyses were stratified by race/ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, non-Hispanic Asian). Prevalences of prepregnancy overweight (25.0–29.9 kg/m(2), 23.0–27.4 kg/m(2)) and obesity (≥30.0 kg/m(2), ≥27.5 kg/m(2)) based on standard and Asian-specific BMI categories, respectively, were quantified. Logistic regression estimated adjusted associations between prepregnancy overweight and obesity and GDM with normal weight (18.0–24.9 kg/m(2), 18.0–22.9 kg/m(2)) as the ref. Annual population-attributable fractions for GDM associated with prepregnancy overweight and obesity were calculated, which account for both prevalence of the risk factor and the associated risk of GDM. RESULTS: Among 11,950,881 included women, mean maternal age was 26.3 years. Population-attributable fractions for GDM associated with overweight were stable (Hispanic: 12.0% to 11.3%, non-Hispanic Asian: 12.1% to 11.6%, p≥0.20) or decreased (non-Hispanic White: 10.8% to 9.4%, non-Hispanic Black: 12.3% to 9.2%, p

Background Given the increasing prevalence of diabetes mellitus (DM) in the United States, estimating the effects of population‐level increases in obesity on incident DM has substantial implications for public health policy. Therefore, we determined the population attributable fraction, which accounts for the prevalence and excess risk of DM associated with obesity. Methods and Results We included non‐Hispanic White, non‐Hispanic Black, and Mexican American participants without DM at baseline from MESA (Multi‐Ethnic Study of Atherosclerosis) with available data on body mass index and key covariates from 2000 to 2017 to calculate unadjusted and adjusted (age, study site, physical activity, diet, income, and education level) hazard ratios (HR) for obesity‐attributable DM. We calculated national age‐adjusted prevalence estimates for obesity using data from NHANES (National Health and Nutrition Examination Survey) in 4 pooled cycles (2001–2016) among adults with similar characteristics to MESA participants. Last, we calculated unadjusted and adjusted population attributable fractions from the race/ethnic and sex‐specific HR and prevalence estimates. Of 4200 MESA participants, the median age was 61 years, 46.8% were men, 53.9% were non‐Hispanic White, 32.9% were non‐Hispanic Black, and 13.3% were Mexican. Among MESA participants, incident DM occurred in 11.6% over a median follow‐up of 9.2 years. The adjusted HR for obesity‐related DM was 2.7 (95% CI, 2.2–3.3). Adjusted population attributable fractions were 0.35 (95% CI, 0.29–0.40) in 2001 to 2004 and 0.41 (95% CI, 0.36–0.46) in 2013 to 2016, and greatest among non‐Hispanic White women. Conclusions The contribution of obesity towards DM in the population remains substantial and varies significantly by race/ethnicity and sex, highlighting the need for tailored public health interventions to reduce obesity. Registration URL: https://www.clinicaltrials.gov ; Unique identifiers: NC00005487, NCT00005154.

Background Adults in rural counties in the United States (US) experience higher rates broadly of cardiovascular disease (CVD) compared with adults in urban counties. Mortality rates specifically due to heart failure (HF) have increased since 2011, but estimates of heterogeneity at the county-level in HF-related mortality have not been produced. The objectives of this study were 1) to quantify nationwide trends by rural-urban designation and 2) examine county-level factors associated with rural-urban differences in HF-related mortality rates. Methods and findings We queried CDC WONDER to identify HF deaths between 2011–2018 defined as CVD (I00-78) as the underlying cause of death and HF (I50) as a contributing cause of death. First, we calculated national age-adjusted mortality rates (AAMR) and examined trends stratified by rural-urban status (defined using 2013 NCHS Urban-Rural Classification Scheme), age (35–64 and 65–84 years), and race-sex subgroups per year. Second, we combined all deaths from 2011–2018 and estimated incidence rate ratios (IRR) in HF-related mortality for rural versus urban counties using multivariable negative binomial regression models with adjustment for demographic and socioeconomic characteristics, risk factor prevalence, and physician density. Between 2011–2018, 162,314 and 580,305 HF-related deaths occurred in rural and urban counties, respectively. AAMRs were consistently higher for residents in rural compared with urban counties (73.2 [95% CI: 72.2–74.2] vs. 57.2 [56.8–57.6] in 2018, respectively). The highest AAMR was observed in rural Black men (131.1 [123.3–138.9] in 2018) with greatest increases in HF-related mortality in those 35–64 years (+6.1%/year). The rural-urban IRR persisted among both younger (1.10 [1.04–1.16]) and older adults (1.04 [1.02–1.07]) after adjustment for county-level factors. Main limitations included lack of individual-level data and county dropout due to low event rates ( Conclusions Differences in county-level factors may account for a significant amount of the observed variation in HF-related mortality between rural and urban counties. Efforts to reduce the rural-urban disparity in HF-related mortality rates will likely require diverse public health and clinical interventions targeting the underlying causes of this disparity.

Introduction: Social determinants of health are multi-dimensional and span various interrelated domains. In order to inform community-engaged clinical and policy efforts, we sought to examine the association between a national social vulnerability index (SVI) and age-adjusted mortality rate (AAMR) of CVD. Hypothesis: Higher county-level SVI or greater vulnerability will be associated with higher AAMR of CVD between 1999-2018 in the United States. Methods: In this serial, cross-sectional analysis, we queried CDC WONDER for age-adjusted mortality rates (AAMRs) per 100,000 population for cardiovascular disease (I00-78) at the county-level between 1999-2018. We quantified the association of county-level SVI and CVD AAMR using Spearman correlation coefficients and examined trends in CVD AAMR stratified by median SVI at the county-level. Finally, we performed geospatial county-level analysis stratified by combined median SVI and CVD AAMR (high/high, high/low, low/high, and low/low). Results: We included data from 2766 counties (representing 95% of counties in the US) with median SVI 0.53 (IQR 0.28, 0.76). Overall SVI and the household and socioeconomic subcomponents were strongly correlated with 2018 CVD AAMR (0.47, 0.50, and 0.56, respectively with p Conclusion: County-level social vulnerability is associated with higher CVD mortality. High SVI and CVD AAMR coexist in more than 1 in 3 US counties and have persisted over the past 2 decades. Identifying counties that are disproportionately vulnerable may inform targeted and community-based strategies to equitably improve cardiovascular health across the country.

Introduction: Rural areas face greater challenges in access to cardiovascular care related to lower physician density compared with urban areas. However, whether the association between recent changes in primary care physicians (PCP) and cardiologist density and contemporary CVD mortality differs by county-level urbanization is unknown. Hypothesis: Decreases in county-level physician density per capita between 2011-2017 will be associated with higher CVD mortality in rural compared with urban counties in 2017-18 in the US. Methods: Death certificates from CDC WONDER with CVD (ICD-10 codes I00-09, I11, I13, I20-51) listed as the underlying cause of death between 2017-2018 were queried to calculate age-adjusted mortality rate (AAMR) at the county-level. Changes in county-level PCPs (2011-2017) and cardiologists (2011-2017) per 100,000 population were derived from the Area Health Resources Files. We performed univariable and multivariable linear regression to determine the association between change in physician density and county-level CVD AAMR adjusted for county-level demographic and socioeconomic characteristics and baseline physician density. Results: PCP and cardiologist density was lower in rural counties compared with urban counties (Table). Between 2011 and 2017, PCP density decreased in rural (-2.2 [SD 15.8]) and increased in urban counties (0.8 [9.1]). Conversely, cardiologist density increased in rural (0.1 [1.8]) and decreased in urban counties (-0.1 [2.1]). Increases in PCP density were associated with lower CVD AAMR in both rural and urban counties (p Conclusion: Cardiologist density in rural counties was less than one-third that of urban counties and was not associated with CVD mortality. Increases in PCP density between 2011-17 was significantly associated with lower CVD AAMR in 2017-18 in both rural and urban counties.

Introduction: Cardiovascular disease (CVD) is the leading cause of death in women and early onset of menopause before the age of 40 years has been identified as a risk enhancer for future CVD events. Quantifying the magnitude of risk for premature CVD among women with early menopause may inform and guide the intensity of sex-specific preventive strategies. Methods: We included all women in the Coronary Artery Risk Development in Young Adults (CARDIA) study who attended a follow-up exam after the age of 40 years, had available data on menopausal status, and had not experienced premature CVD before 40 years. We performed multivariable Cox proportional hazards regression to examine the relationship between early onset of menopause defined as Results: Among 2136 women with mean age of 43.0 (SD 3.0), 9.1% reported premature menopause before the age of 40 years (4.5% in white and 13.9% in black women). Over a median follow-up of 14.0 (IQR 11.5, 16.9) years, 81 premature CVD events occurred. Incidence rate (95% CI) of CVD was 6.46 (2.43, 17.22) and 1.41 (0.92, 2.17) per 1,000 per person-years for white women with and without early onset menopause, respectively; 4.94 (2.66, 9.16) and 3.92 (2.94, 5.24) per 1,000 person-years for black women with and without early onset menopause (FIGURE). Conclusions: In a population-based sample, white women with early onset of menopause had a 3-fold higher rate of premature CVD events, independent of perimenopausal risk factor levels. Interventions to intensify CVD prevention in at-risk women are needed following early onset of menopause.

Introduction: Women who experience premature menopause are known to have higher rates of long-term atherosclerotic cardiovascular disease (ASCVD). Specifically, menopause prior to age of 40 years has been identified as a risk enhancer by the 2019 AHA/ACC Primary Prevention guidelines. Coronary artery calcium (CAC) may have clinical utility for refinement of risk stratification in this high-risk group of women for the primary prevention of ASCVD. Methods: We included women from the Coronary Artery Risk Development in Young Adults (CARDIA) study who completed a coronary-gated CT scan at a baseline age of 43-55 years. We excluded women who had a myocardial infarction prior to CAC assessment. Menopausal status was self-reported as before the age of 40 years, at 40 years or older, or pre-menopausal. No significant interaction by race was observed. We performed multinomial logistic regression analysis to examine the association between premature menopause and 3 categories of CAC (0, 1-99, and ≥100 Agatston units). In separate multivariable models, we adjusted for demographic and cardiovascular risk factors at the time of CAC measurement. Results: Of 1786 women, 167 (9.4%) experienced premature menopause, 1175 (65.8%) reached menopause after the age of 40 years, and 444 (24.9%) were pre-menopausal at the time of CT. Presence of any CAC in these 3 groups was 18.0%, 19.6%, and 11.3% for premature menopause, ≥40 menopausal, and the pre-menopausal groups, respectively (FIGURE). Premature menopause was not associated with higher odds of non-zero CAC in unadjusted or adjusted analyses. Conclusions: Premature menopause was not associated with prevalent CAC score in these women in mid-life. Consideration of alternative approaches or biomarkers for risk stratification for ASCVD should be evaluated in this high-risk group.

OBJECTIVE Excessive childhood adiposity is a risk factor for adverse metabolic health. The objective was to investigate associations of newborn body composition and cord C-peptide with childhood anthropometrics and explore whether these newborn measures mediate associations of maternal midpregnancy glucose and BMI with childhood adiposity. RESEARCH DESIGN AND METHODS Data on mother/offspring pairs (N = 4,832) from the epidemiological Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study and HAPO Follow-up Study (HAPO FUS) were analyzed. Linear regression was used to study associations between newborn and childhood anthropometrics. Structural equation modeling was used to explore newborn anthropometric measures as potential mediators of the associations of maternal BMI and glucose during pregnancy with childhood anthropometric outcomes. RESULTS In models including maternal glucose and BMI adjustments, newborn adiposity as measured by the sum of skinfolds was associated with child outcomes (adjusted mean difference, 95% CI, P value) BMI (0.26, 0.12–0.39, CONCLUSIONS Newborn adiposity is independently associated with childhood adiposity and, along with fetal hyperinsulinemia, mediates, in part, associations of maternal glucose and BMI with childhood adiposity.

Importance The Surveillance, Epidemiology, and End Results (SEER)–Medicare linked database may provide insights into the comparative effectiveness of oncological treatments for elderly individuals who are underrepresented in clinical trials. Objective To evaluate the suitability of SEER-Medicare data for assessing the effectiveness of adding a drug to an existing treatment regimen on the overall survival of elderly patients with cancer. Design, Setting, and Participants This comparative effectiveness study analyzed SEER-Medicare data from 9549 individuals who received a new diagnosis of stage II colorectal cancer (2008-2012) and 940 patients who received a new diagnosis of advanced pancreatic adenocarcinoma (2007-2012), with follow-up to December 31, 2013 (SEER-Medicare data released in 2015). Two (hypothetical) target trials were designed and emulated based on 2 existing randomized clinical trials: (1) adjuvant fluorouracil after curative surgery for individuals with stage II colorectal cancer and (2) erlotinib added to gemcitabine for individuals with advanced pancreatic adenocarcinoma. Data were analyzed January 2018 to March 2019. Exposures The following treatment strategies were compared: (1) fluorouracil initiation vs no initiation within 3 months of tumor resection and (2) erlotinib initiation vs no initiation within 12 weeks of gemcitabine initiation. Main Outcomes and Measures All-cause mortality within 60 months of baseline for the fluorouracil trial and within 72 weeks for the erlotinib trial. Results Compared with 3293 individuals in the existing fluorouracil trial, 9549 eligible individuals included in the present analyses were more likely to have colon cancer (8565 [90%] vs 2291 [71%]) and were older (median [interquartile range], 79 [73-84] vs 63 [56-68] years). The 5-year risk difference for initiation vs noninitiation of fluorouracil after surgery was −3.8% (95% CI, −14.8% to 12.6%), and the mortality hazard ratio (HR) was 0.95 (95% CI, 0.85-1.04). Compared with 569 individuals in the existing erlotinib trial, 940 eligible patients included in the present analysis were older (median [range], 74 [66-93] vs 64 [36-92] years) and more likely to be male (547 [58%] vs 298 [52%]). The 1-year risk difference for initiation vs noninitiation of erlotinib was 4.7% (95% CI, −9.4% to 18.0%), and the corresponding mortality HR was 1.04 (95% CI, 0.86-1.42). In naive analyses, the mortality HR estimate was 1.14 (95% CI, 0.95-1.36) for the fluorouracil emulation and 0.68 (95% CI, 0.54-0.87) for the erlotinib emulation. Conclusions and Relevance The present estimates were similar to those from randomized clinical trials that studied adding the same cancer drugs to existing regimens. The published HR was 1.02 (95% CI, 0.70-1.48) in the fluorouracil trial for individuals aged 70 or older and 0.96 (95% CI, 0.74-1.24) in the erlotinib trial for individuals aged 65 years or older. The SEER-Medicare database may be adequate for studying the real-world effectiveness of adding a drug to treatment regimens used for elderly individuals with cancer.

Introduction: Clinicians widely use cardiac troponins I and T, sensitive and specific biomarkers of myocardial damage, as diagnostic criteria for myocardial infarction (MI). A common approach, dichotomizing based on whether troponin levels meet thresholds for MI, may miss meaningful heterogeneity in degree and pattern of troponin elevation, with wider clinical implications. Hypothesis: Using latent class trajectory modeling (LCTM) with patients’ patterns of troponin elevations will yield trajectories that represent clinically and prognostically distinct groups of patients. Methods: We used Northwestern Medicine’s Enterprise Data Warehouse to identify patients with at least 3 troponin measurements of which at least one was elevated during their inpatient stay. We built a LCTM to capture troponin trajectories from 13,432 patients with 65,162 measurements since 2000, using Bayesian Information Criterion to select the final model (# of classes varied from 3-7). We then described the clinical and prognostic factors associated with trajectory class membership. Results: LCTM identified 3 troponin trajectories: stable low (77.3%), moderate rise (9.5%), and severe rise-fall (13.2%). The average posterior probability of assignment was >0.95 for all classes. The low group had the most comorbidities vs moderate/severe groups, including cancer (21.9% vs 13.9%/11.3%), heart failure (12.6% vs 8.9%/7.5%), and COPD (15.0% vs 11.8%/10.1%). The moderate/severe rising trajectories had a greater rate of clinically-diagnosed MI than the stable group (34.5%/44.1% vs 5.6%), with relatively more ST-elevation MI in the severe group (19.8% vs 5.3%) and Non-ST-elevation MI in the moderate group (29.3% vs 24.3%). One-year mortality was greatest in the low group vs moderate/severe groups (25.5% vs 21.4%/18.8%). Conclusions: In a cohort of hospitalized patients with elevated troponins, LCTM identified 3 distinct, clinically interpretable troponin trajectories which were associated with differing clinical phenotypes.

Introduction: Estimating effects of population-level increases in obesity on diabetes has important implications for public health policy. Therefore, we used the population attributable fraction (PAF) to quantify trends in the burden of obesity on incident diabetes in key sex and race/ethnicity subgroups over time. Hypothesis: PAFs for obesity attributable incident diabetes will be greatest for women, differ by race/ethnicity and increase over time. Methods: Using data from the Multi-Ethnic Study of Atherosclerosis (MESA), we estimated unadjusted and adjusted hazard ratios (HRs) of obesity on incident diabetes mellitus (DM). We included non-Hispanic White (NHW), non-Hispanic Black (NHB) and Hispanic-Mexican (MA) MESA participants with available data on body mass index and key covariates and without DM at baseline. Next, we estimated the prevalence of obesity in four pooled groups of NHANES survey cycles from 2001-2016 with similar characteristics to MESA participants (age 45-80 years, NHW, NHB, and MA without cardiovascular disease). Lastly, we combined estimates from MESA and NHANES to quantify unadjusted and adjusted PAFs (adjusted for age, income, education, physical activity and diet). Leveraging the objective longitudinal assessment of incident DM in MESA and a nationally representative sample of NHANES, we estimated broadly generalizable PAF estimates over time. Results: Of 3869 MESA participants, mean age was 61 (± 10) years with 47% men, 56% NHW, 31% NHB, and 13% MA. Incidence of DM was 11% with overall adjusted HR of 2.75 (95% CI 2.26, 3.34) for obesity. Prevalence of obesity increased from 34% (32, 37) in 2001-2004 to 41% (39, 44) in 2013-2016. Overall adjusted PAFs ranged from 0.23 to 0.52 over the study period (TABLE), with greatest estimates in NHW women. Conclusions: In conclusion, over time, the proportion of diabetes due to obesity has increased across multiple subgroups of the population, further highlighting the health burden of obesity in the population.

BACKGROUND: Gestational weight gain may be a modifiable contributor to infant health outcomes, but the effect of gestational duration on gestational weight gain has limited the identification of optimal weight gain ranges. Recently developed z-score and percentile charts can be used to classify gestational weight gain independent of gestational duration. However, racial/ethnic variation in gestational weight gain and the possibility that optimal weight gain differs among racial/ethnic groups could affect generalizability of the z-score charts. The objectives of this study were (1) to apply the weight gain z-score charts in two different U.S. populations as an assessment of generalisability and (2) to determine whether race/ethnicity modifies the weight gain range associated with minimal risk of preterm birth. METHODS: The study sample included over 4 million live, singleton births in California (2007–2012) and Pennsylvania (2003–2013). We implemented a noninferiority margin approach in stratified subgroups to determine weight gain ranges for which the adjusted predicted marginal risk of preterm birth (gestation

Women's experience of childhood adversity may contribute to their children's risk of obesity. Possible causal pathways include higher maternal weight and gestational weight gain, which have been associated with both maternal childhood adversity and obesity in offspring.This study included 6718 mother-child pairs from the National Longitudinal Survey of Youth 1979 in the United States (1979-2012). We applied multiple log-binomial regression models to estimate associations between three markers of childhood adversity (physical abuse, household alcoholism, and household mental illness) and offspring obesity in childhood. We estimated natural direct effects to evaluate mediation by prepregnancy BMI and gestational weight gain.Among every 100 mothers who reported physical abuse in childhood, there were 3.7 (95% confidence interval: -0.1 to 7.5) excess cases of obesity in 2- to 5-year olds compared with mothers who did not report physical abuse. Differences in prepregnancy BMI, but not gestational weight gain, accounted for 25.7% of these excess cases. There was no evidence of a similar relationship for household alcoholism or mental illness or for obesity in older children.In this national, prospective cohort study, prepregnancy BMI partially explained an association between maternal physical abuse in childhood and obesity in preschool-age children. These findings underscore the importance of life-course exposures in the etiology of child obesity and the potential multi-generational consequences of child abuse. Research is needed to determine whether screening for childhood abuse and treatment of its sequelae could strengthen efforts to prevent obesity in mothers and their children.

Objective Identify the socio-economic correlates of sugar sweetened beverage (SSB) consumption among pregnant women and analyze to what extent SSB consumption is associated with diet quality and total energy intake. Additionally, we aim to predict how diet quality scores and totally energy intakes would change if SSB consumption was artificially set to 0. Design Repeated Cross Sectional Study. Setting United States. Subjects SSB consumption was estimated from 1–2 24-hour dietary recalls from 1,154 pregnant women who participated in the 1999–2006 National Health and Nutrition Examination Survey. Methods Linear regression models were used to identify socioeconomic and demographic factors associated with SSB consumption and to assess the associations between SSB consumption and diet quality and total energy intake. Diet quality was measured with the Alternate Healthy Eating Index modified for Pregnancy (AHEI-P). Results The mean SSB intake was 1.3 servings per day (sd 1.5). Having a household income ≤100% of the Federal Poverty Level, being born in the United States, and not being married or living with a partner were positively associated with SSB consumption. Every 12 oz. of SSBs consumed was associated with a 2.3 lower AHEI-P score (95% CI: 1.6, 2.9) and the consumption of 124 more calories (95% CI: 85, 163), after adjusting for age, country of birth, race/ethnicity, educational attainment, marital status, household income, survey year and day/s of the week the recall/s were collected. Our predictive models indicated that average AHEI-P would be 6.4 (5.4, 7.6) higher and average total energy intakes would be 203.5 calories (122.2, 284.8) lower if SSB intake was set to 0. Conclusions SSB consumption is associated with poorer diet quality and higher total energy intake among pregnant women.

Epidemiological studies have highlighted the disparate impact of coronavirus disease 2019 (COVID-19) on racial and ethnic minority and socioeconomically disadvantaged populations, but data at the neighborhood-level is sparse. The objective of this study was to investigate the disparate impact of COVID-19 on disadvantaged neighborhoods and racial/ethnic minorities in Chicago, Illinois. Using data from the Cook County Medical Examiner, we conducted a neighborhood-level analysis of COVID-19 decedents in Chicago and quantified age-standardized years of potential life lost (YPLL) due to COVID-19 among demographic subgroups and neighborhoods with geospatial clustering of high and low rates of COVID-19 mortality. We show that age-standardized YPLL was markedly higher among the non-Hispanic (NH) Black (559 years per 100,000 population) and the Hispanic (811) compared with NH white decedents (312). We demonstrate that geomapping using residential address data at the individual-level identifies hot-spots of COVID-19 mortality in neighborhoods on the Northeast, West, and South areas of Chicago that reflect a legacy of residential segregation and persistence of inequality in education, income, and access to healthcare. Our results may contribute to ongoing public health and community-engaged efforts to prevent the spread of infection and mitigate the disproportionate loss of life among these communities due to COVID-19 as well as highlight the urgent need to broadly target neighborhood disadvantage as a cause of pervasive racial inequalities in life and health.

Importance Despite recent advances in therapies for heart failure (HF), deaths from HF are increasing, with persistent disparities between Black and White adults. Recent national trends in the prevalence of HF need to be clarified to appropriately allocate resources and develop effective preventive interventions. Objectives To examine the prevalence of ambulatory HF overall and by race/ethnicity and age and the temporal changes in HF prevalence between 2001 and 2016. Design, Setting, and Participants This cross-sectional study of nationally representative data collected biennially through the National Health and Nutrition Examination Survey (NHANES) from January 1, 2001, to December 31, 2016, assessed nonpregnant adults 35 years and older who self-identified as non-Hispanic Black, non-Hispanic White, or Mexican American. Data analysis was performed from November 16, 2019, to April 12, 2020. Exposures Survey period, race/ethnicity, and age group. Main Outcomes and Measures Age-standardized prevalence was calculated within 4-year survey periods (2001-2004, 2005-2008, 2009-2012, and 2013-2016) based on self-report of ambulatory HF overall and by race/ethnicity and age group (35-64 and ≥65 years). Weighted multivariable logistic regression was used to examine trends in ambulatory HF prevalence over time by race/ethnicity and age group. Results A total of 26 097 participants (mean [SD] age, 55.9 [10.7] years; 13 192 [52%] female; 6519 [12%] non-Hispanic Black; and 4906 [7%] Mexican American) were studied. Overall age-standardized prevalence (per 100 000 population) of ambulatory HF was 3184 (95% CI, 2641-3728) from 2001 to 2005 and 3045 (95% CI, 2651-3438) from 2013 to 2016. The prevalence of ambulatory HF was highest among non-Hispanic Black adults: from 2013 to 2016, HF prevalence (per 100 000 population) was 5017 (95% CI, 3755-6279) among non-Hispanic Black adults, 2746 (95% CI, 2313-3179) among non-Hispanic White adults, and 2508 (95% CI, 1154-3862) among Mexican American adults. Differences between White and Black adults in HF prevalence were also present in younger and middle-aged adults (eg, 35-64 years of age in 2013-2016: 3864 [95% CI, 2369-5359] for non-Hispanic Black adults vs 1297 [95% CI, 878-1716] for non-Hispanic White adults). Conclusions and Relevance This study found that a high burden of ambulatory HF persisted between 2001 and 2016 in the US. Disparities were most prominent by age group. Alongside prevention and aggressive management of risk factors, targeted efforts aimed at mitigating racial disparities are needed.

SummaryBackground High weight gain in pregnancy has been associated with child adiposity, but few studies have assessed the relationship across childhood or in racially/ethnically diverse populations. Objectives The objectives of the study are to test if weight gain in pregnancy is associated with high birthweight and overweight/obesity in early, middle and late childhood and whether these associations differ by maternal race/ethnicity. Methods Mother-child dyads (n = 7539) were included from the National Longitudinal Survey of Youth 1979, a nationally representative cohort study in the USA (1979–2012). Log-binomial regression models were used to analyse associations between weight gain and the outcomes: high birthweight (>4000 g) and overweight/obesity at ages 2–5, 6–11 and 12–19 years. Results Excessive weight gain was positively associated, and inadequate weight gain was negatively associated with high birthweight after confounder adjustment (P

Introduction Mortality rates due to heart failure (HF) have increased since 2011, but estimates of heterogeneity at the county-level in HF-related mortality are not known. Differences between rural and urban counties and the impact of county-level factors on HF-related mortality are needed to inform public health strategies. Hypotheses Substantial variation in HF-related mortality trends between 2011-2018 exists by rural-urban designation. In addition, county-level factors account for a large proportion rural-urban differences in HF-related mortality rates. Methods We queried CDC WONDER to identify HF deaths between 2011-2018 defined as any mention of HF (I50) on the death certificate and cardiovascular disease (I00-78) as the underlying cause of death. First, we calculated age-adjusted mortality rates (AAMR) and examined trends stratified by rural-urban status (defined using 2013 NCHS Urban-Rural Classification Scheme), age (35-64 and 65-84 years), and race-sex subgroups per year. Second, we combined all deaths from 2011-2018 and estimated incidence rate ratios (IRR) in HF-related mortality for rural versus urban counties using multivariable negative binomial regression models with adjustment for sociodemographic factors, risk factor prevalence, and physician density. Results Between 2011-2018, AAMRs were consistently higher for rural compared with urban counties (e.g., 73.2 [95% CI: 72.2-74.2] vs. 57.2 [56.8-57.6] in 2018, respectively). The highest AAMR was observed in rural black men (131.1 [123.3-138.9] in 2018), and the greatest increases in HF-related mortality occurred in rural black men, age 35-64 years (+6.1%/year). Unadjusted models demonstrated significantly higher HF-related mortality in rural versus urban counties across the entire study period (IRR = 1.67 [95% CI: 1.57-1.78] and 1.16 [95% CI: 1.13-1.18] for younger and older adults, respectively). The rural-urban IRR was significantly attenuated after adjustment for county-level factors among both younger (1.10 [1.04-1.16]) and older adults (1.04 [1.02-1.07]). Conclusions Differences in county-level factors account for a significant amount of the observed variation in HF-related mortality between rural and urban counties.

Introduction A history of adversity in childhood is associated with cigarette smoking in adulthood, but there is less evidence for prenatal and next-generation offspring smoking. We investigated the association between maternal history of childhood adversity, pregnancy smoking, and early initiation of smoking in offspring, overall and by maternal race/ethnicity. Methods Data on maternal childhood exposure to physical abuse, household alcohol abuse, and household mental illness, prenatal smoking behaviors, and offspring age of smoking initiation were analyzed from the US National Longitudinal Survey of Youth 1979 (NLSY79, n = 2999 mothers) and the NLSY79 Children and Young Adults Survey (NLSYCYA, n = 6596 children). Adjusted risk ratios were estimated using log-linear regression models. We assessed multiplicative interaction by race/ethnicity for all associations and a three-way interaction by maternal exposure to adversity and race/ethnicity for the association between prenatal and child smoking. Results Maternal exposure to childhood physical abuse was significantly associated with 39% and 20% increased risks of prenatal smoking and child smoking, respectively. Household alcohol abuse was associated with significantly increased risks of 20% for prenatal smoking and 17% for child smoking. The prenatal smoking-child smoking relationship was modified by maternal exposure to household alcohol abuse and race. There were increased risks for Hispanic and white/other mothers as compared to the lowest risk group: black mothers who did not experience childhood household alcohol abuse. Conclusions Mothers in this national sample who experienced adversity in childhood are more likely to smoke during pregnancy and their offspring are more likely to initiate smoking before age 18. Findings varied by type of adversity and race/ethnicity. Implications These findings support the importance of a life-course approach to understanding prenatal and intergenerational smoking, and suggest that maternal early-life history is a potentially important risk factor that could be targeted with screening and interventions to reduce smoking in pregnant women and their children.

Long-term breast cancer trends in incidence in the United States (US) show rising estrogen receptor (ER)-positive rates and falling ER-negative rates. We hypothesized that these divergent trends reflect etiologic heterogeneity and that comparable trends should be observed in other countries with similar risk factor profiles. Therefore, we analyzed invasive female breast cancers in Denmark, a country with similar risk factors as the US. We summarized the overall trend in age-standardized rates with the estimated annual percentage change (EAPC) statistic (1993–2010) and used age-period-cohort models to estimate age-specific EAPCs, cohort rate ratios and projections for future time periods (2011–2018). In Denmark, the overall rate of ER-positive cancers rose between 1993 and 2010 by 3.0% per year (95% CI: 2.8–3.3% per year), whereas the overall rate of ER-negative cancers fell by 2.1% per year (95% CI: −2.5 to −1.6% per year). The ER-positive rate increased fastest among postmenopausal women and the ER-negative rate decreased fastest among premenopausal women, reflecting that cohorts born after 1944 were at relatively higher risk of ER-positive tumors and lower risk of ER-negative tumors. If current trends continue, ER-positive cancers will increase at least 13% by 2018 in Denmark, ER-negative cancers will fall 15% by 2018, and breast cancer overall will increase at least 7% by 2018. Divergent ER-specific trends are consistent with distinct etiologic pathways. If trends in known risk factors are responsible, the Danish and US experience may foreshadow a common pattern worldwide.

Introduction This study investigated associations between maternal prepregnancy BMI and child behaviors at ages 9–11 years and examine interaction by race and gender. Methods The National Longitudinal Survey of Youth and the Children and Young Adults surveys are U.S.-based, ongoing longitudinal studies, initiated in 1979 and 1986, respectively. Mothers ( n =2,952) reported pregnancy and child ( n =5,660) developmental information at multiple time points. Child total, internalizing, and externalizing problems at ages 9–11 years were assessed using the Behavior Problems Index (BPI), collected biennially until 2012. Associations between prepregnancy BMI and child BPI outcomes were examined, as well as two- and three-way interactions by race and gender. Analyses were conducted in 2017. Results Boys whose mothers had higher prepregnancy weights exhibited higher total BPI and externalizing scores at ages 9–11 years versus those with normal-weight mothers. Boys with severely obese mothers had higher total BPI (mean difference=7.99, 95% CI=3.53, 12.46) and externalizing (mean difference=5.77, 95% CI=1.50, 10.04) scores. Prepregnancy underweight was associated with boys’ higher total BPI (mean difference=2.34, 95% CI=0.02, 4.66) and externalizing (mean difference=3.30, 95% CI=0.69, 5.91); these associations were not significant in sensitivity analyses. No associations emerged for girls or internalizing problems. Two-way interactions by race and three-way interactions by race and gender were not significant. Conclusions Maternal prepregnancy weight was associated with BPI level among boys. Boys with severely obese mothers exhibited markedly higher behavioral problems at ages 9–11 years versus those with normal-weight mothers, regardless of race. Maintaining healthy prepregnancy weight may be important for preventing boys’ deleterious behavior outcomes in middle childhood.

Lung cancer screening guidelines recommend using individualized risk models to refer ever-smokers for screening. However, different models select different screening populations. The performance of each model in selecting ever-smokers for screening is unknown.To compare the U.S. screening populations selected by 9 lung cancer risk models (the Bach model; the Spitz model; the Liverpool Lung Project [LLP] model; the LLP Incidence Risk Model [LLPi]; the Hoggart model; the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial Model 2012 [PLCOM2012]; the Pittsburgh Predictor; the Lung Cancer Risk Assessment Tool [LCRAT]; and the Lung Cancer Death Risk Assessment Tool [LCDRAT]) and to examine their predictive performance in 2 cohorts.Population-based prospective studies.United States.Models selected U.S. screening populations by using data from the National Health Interview Survey from 2010 to 2012. Model performance was evaluated using data from 337 388 ever-smokers in the National Institutes of Health-AARP Diet and Health Study and 72 338 ever-smokers in the CPS-II (Cancer Prevention Study II) Nutrition Survey cohort.Model calibration (ratio of model-predicted to observed cases [expected-observed ratio]) and discrimination (area under the curve [AUC]).At a 5-year risk threshold of 2.0%, the models chose U.S. screening populations ranging from 7.6 million to 26 million ever-smokers. These disagreements occurred because, in both validation cohorts, 4 models (the Bach model, PLCOM2012, LCRAT, and LCDRAT) were well-calibrated (expected-observed ratio range, 0.92 to 1.12) and had higher AUCs (range, 0.75 to 0.79) than 5 models that generally overestimated risk (expected-observed ratio range, 0.83 to 3.69) and had lower AUCs (range, 0.62 to 0.75). The 4 best-performing models also had the highest sensitivity at a fixed specificity (and vice versa) and similar discrimination at a fixed risk threshold. These models showed better agreement on size of the screening population (7.6 million to 10.9 million) and achieved consensus on 73% of persons chosen.No consensus on risk thresholds for screening.The 9 lung cancer risk models chose widely differing U.S. screening populations. However, 4 models (the Bach model, PLCOM2012, LCRAT, and LCDRAT) most accurately predicted risk and performed best in selecting ever-smokers for screening.Intramural Research Program of the National Institutes of Health/National Cancer Institute.

Introduction Growing evidence suggests that exposure to childhood adversity may influence obesity across the life course. High maternal weight complicates pregnancy and increases the risk of child obesity. This study examined the association between maternal childhood adversity and pregnancy-related weight in a large U.S. sample. Methods Data on 6,199 pregnancies from 2,873 women followed from 1979 to 2012 by the National Longitudinal Survey of Youth 1979 were analyzed in 2014. Associations between three adversity exposures before age 18 years (history of physical abuse, alcohol problems, or mental illness in the household) and two maternal weight outcomes (prepregnancy obesity and excessive gestational weight gain) were modeled separately using survey-adjusted log-binomial models. Results After adjusting for race/ethnicity and early-life socioeconomic factors, childhood physical abuse was associated with a 60% increase in the risk of prepregnancy obesity (adjusted risk ratio=1.6, 95% CI=1.1, 2.2). Household alcohol abuse was associated with a 30% increase in prepregnancy obesity (adjusted risk ratio=1.3, 95% CI=1.0, 1.7), as was household mental illness (adjusted risk ratio=1.3, 95% CI=0.8, 1.9), but the mental illness exposure was not significant. Physical abuse and household alcohol abuse were associated with a significant 20% increase in the risk of excessive gestational weight gain; mental illness was not. Conclusions Adversity in early life may affect maternal weight before and during pregnancy. Screening and treating women of reproductive age for childhood adversity and its negative effects could significantly reduce obesity-related health outcomes for women and their children.

Purpose To quantify the relationship between pregnancy weight gain with early and late preterm birth and evaluate whether associations differed between non-Hispanic (NH) black and NH white women. Methods We analyzed a retrospective cohort of all live births to NH black and NH white women in the United States 2011–2015 (n = 10,714,983). We used weight gain z-scores in multiple logistic regression models stratified by prepregnancy body mass index (BMI) and race to calculate population attributable risk (PAR) percentages for the contribution of high and low pregnancy weight gain to early and late preterm birth. Results Pregnancy weight gain was related to early and late preterm birth, but associations varied by BMI and race. For early preterm birth, the PAR percentage for high pregnancy weight gain ranged from 8 to 10% in NH black women and from 6 to 8% in NH white women. There was little evidence of racial differences in late preterm birth: PAR percentages ranged from 2 to 7% in NH black women and from 3 to 7% in NH white women. Conclusions Moderate gestational weight gain is associated with lower rate of preterm birth, with greatest reductions for early preterm birth in NH black women.

The existing methods for evaluating resident operative performance interrupt the workflow of the attending physician, are resource intensive, and are often completed well after the end of the procedure in question. These limitations lead to low faculty compliance and potential significant recall bias. In this study, we deployed a smartphone-based system, the Procedural Autonomy and Supervisions System, to facilitate assessment of resident performance according to the Zwisch scale with minimal workflow disruption. We aimed to demonstrate that this is a reliable, valid, and feasible method of measuring resident operative autonomy.Before implementation, general surgery residents and faculty underwent frame-of-reference training to the Zwisch scale. Immediately after any operation in which a resident participated, the system automatically sent a text message prompting the attending physician to rate the resident's level of operative autonomy according to the 4-level Zwisch scale. Of these procedures, 8 were videotaped and independently rated by 2 additional surgeons. The Zwisch ratings of the 3 raters were compared using an intraclass correlation coefficient. Videotaped procedures were also scored using 2 alternative operating room (OR) performance assessment instruments (Operative Performance Rating System and Ottawa Surgical Competency OR Evaluation), against which the item correlations were calculated.Between December 2012 and June 2013, 27 faculty used the smartphone system to complete 1490 operative performance assessments on 31 residents. During this period, faculty completed evaluations for 92% of all operations performed with general surgery residents. The Zwisch scores were shown to correlate with postgraduate year (PGY) levels based on sequential pairwise chi-squared tests: PGY 1 vs PGY 2 (χ(2) = 106.9, df = 3, p0.001); PGY 2 vs PGY 3 (χ(2) = 22.2, df = 3, p0.001); and PGY 3 vs PGY 4 (χ(2) = 56.4, df = 3, p0.001). Comparison of PGY 4 to PGY 5 scores were not significantly different (χ(2) = 4.5, df = 3, p = 0.21). For the 8 operations reviewed for interrater reliability, the intraclass correlation coefficient was 0.90 (95% CI: 0.72-0.98, p0.01). Correlation of Procedural Autonomy and Supervisions System ratings with both Operative Performance Rating System items (each r0.90, all p's0.01) and Ottawa Surgical Competency OR Evaluation items (each r0.86, all p's0.01) was high.The Zwisch scale can be used to make reliable and valid measurements of faculty guidance and resident autonomy. Our data also suggest that Zwisch ratings may be used to infer resident operative performance. Deployed on an automated smartphone-based system, it can be used to feasibly record evaluations for most operations performed by residents. This information can be used to council individual residents, modify programmatic curricula, and potentially inform national training guidelines.

Background: Long-term breast cancer trends in incidence in the United States (US) show rising ER positive rates and falling ER negative rates. We hypothesized that these divergent trends reflect etiologic heterogeneity and that comparable trends should be observed in other countries with similar risk factor profiles. Methods: We analyzed invasive female breast cancers in Denmark from 1993-2010. We summarized the overall trend in age-standardized rates with the estimated annual percentage change (EAPC) statistic, and used age-period-cohort models to estimate age-specific EAPCs, cohort rate ratios (CRRs), and projections for future time periods (2011-2018). Results: In Denmark, the overall rate of ER positive cancers rose between 1993 and 2010 by 3·0%/year (95% CI: 2·8 to 3·3%/yr) while the overall rate of ER negative cancers fell by 2·1%/year (95% CI: -2·5 to -1·6%/yr). The ER positive rate increased fastest among postmenopausal women and the ER negative rate decreased fastest among premenopausal women, reflecting that cohorts born after 1944 were at relatively higher risk of ER positive tumors and lower risk of ER negative tumors. If current trends continue, ER positive cancers will increase at least 13% and ER negative cancers will fall as much as 15% by 2018. Conclusion: Divergent ER-specific trends are consistent with distinct etiologic pathways. If trends in known risk factors are responsible, the Danish and US experience may foreshadow a common pattern worldwide. Citation Format: William F. Anderson, Philip Rosenberg, Lucia Petito, Hormuzd A. Katki, Bent Ejlertsen, Marianne Ewertz, Birgitte B. Rasmussen, Maj-Britt Jensen, Niels Kroman. Divergent estrogen receptor positive and negative breast cancer trends and etiologic heterogeneity in Denmark . [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 132. doi:10.1158/1538-7445.AM2013-132