US Census Research Articles

Abstract 66: US Asian and Pacific Islander Adolescents With Obesity Have Triple the Risk of Prediabetes When Compared to Non Hispanic White Children

Introduction: Race and ethnicity and elevated body mass index (BMI) are risk factors for pre-diabetes (preDM) among adolescents. We recently observed high preDM prevalence among aggregated US Asian and Pacific Islander (API) children with obesity, but data pertaining to disaggregated API subgroups remain limited. Aim: To examine the risk of preDM among API subgroups compared to non-Hispanic White (NHW) adolescents with obesity. Methods: This retrospective study included 3233 API and 4150 NHW children age 13-17y with obesity and without DM who were identified at preventive health well-child visits in 2016-2019 and had hemoglobin A1c (HA1c) measured within 1 year of the visit. Visit data included self-reported diet/lifestyle behaviors and BMI measurement. PreDM (outcome) was defined by HA1c 5.7-6.4%. Obesity was categorized as Class 1-3 based on BMI percent of the 95th BMI percentile (obesity threshold). Four obesogenic behaviors were ascertained from clinic data: Fruit/vegetable consumption <5 servings/day; juice/sugary beverage intake >12 ounces/day; exercising <60 minutes/day; and screen time 2+ hours/day. A neighborhood deprivation index (NDI) was calculated using area of residence and 2010 US Census data. Log binomial regression was used to examine the association of API ethnicity and preDM, reporting relative risk (RR) and 95% confidence intervals [CI]. Results: The cohort included 210 Chinese, 900 Filipino, 200 South Asian, 132 Southeast Asian, 283 Native Hawaiian/Pacific Islander (NHPI), 1508 other/unspecified API ethnicity, and 4150 NHW children. Overall, 22.4% of API vs 9.4% NHW (p<0.001) children had preDM. PreDM prevalence ranged from 19.1% for Chinese, 21.7% for Filipino, 22.5% for South Asian, 24.2% for Southeast Asian, to 26.5% for NHPI subgroups. After adjusting for age, sex, NDI, obesity class, and obesogenic health behaviors, risk of preDM was about 3-fold higher (RR 2.9 [2.6-3.4] for API compared to NHW adolescents, ranging from RR 2.5 [1.8-3.6] for Chinese, RR 2.8 [2.3-3.4] for Filipino, RR 3.1 [2.2- 4.4] for South Asian, RR 3.2 [2.1-4.9] for Southeast Asian, RR 3.3 [2.5-4.4] for NHPI, and RR 3.0 [2.5-3.5] for other/unspecified API children. Obesity severity (RR 1.4 [1.2-1.6] for Class 2 and RR 2.1 [1.7-2.6] for Class 3 compared to Class 1 obesity) was also associated with preDM risk. Conclusion: PreDM risk was about 3-fold higher for API compared to NHW children with obesity even after adjusting for sociodemographic, lifestyle, and BMI differences. The risk of preDM ranged from 2.5-fold to 3.3-fold higher for the major API subgroups, especially Southeast Asian and Filipino groups compared to NHW children. These findings highlight the importance of preDM screening among API children and demonstrate heterogeneity of risk among API subgroups. Future efforts should focus on effective screening and monitoring of at-risk populations to prevent progression to Type 2 DM.

Neighborhood Deprivation, Race and Ethnicity, and Prostate Cancer Outcomes Across California Health Care Systems

Non-Hispanic Black (hereafter, Black) individuals experience worse prostate cancer outcomes due to socioeconomic and racial inequities of access to care. Few studies have empirically evaluated these disparities across different health care systems. To describe the racial and ethnic and neighborhood socioeconomic status (nSES) disparities among residents of the same communities who receive prostate cancer care in the US Department of Veterans Affairs (VA) health care system vs other settings. This cohort study obtained data from the VA Central Cancer Registry for veterans with prostate cancer who received care within the VA Greater Los Angeles Healthcare System (VA cohort) and from the California Cancer Registry (CCR) for nonveterans who received care outside the VA setting (CCR cohort). The cohorts consisted of all males with incident prostate cancer who were living within the same US Census tracts. These individuals received care between 2000 and 2018 and were followed up until death from any cause or censoring on December 31, 2018. Data analyses were conducted between September 2022 and December 2023. Health care setting, self-identified race and ethnicity (SIRE), and nSES. The primary outcome was all-cause mortality (ACM). Cox proportional hazards regression models were used to estimate hazard ratios for associations of SIRE and nSES with prostate cancer outcomes in the VA and CCR cohorts. Included in the analysis were 49 461 males with prostate cancer. Of these, 1881 males were in the VA cohort (mean [SD] age, 65.3 [7.7] years; 833 Black individuals [44.3%], 694 non-Hispanic White [hereafter, White] individuals [36.9%], and 354 individuals [18.8%] of other or unknown race). A total of 47 580 individuals were in the CCR cohort (mean [SD] age, 67.0 [9.6] years; 8183 Black individuals [17.2%], 26 206 White individuals [55.1%], and 13 191 individuals [27.8%] of other or unknown race). In the VA cohort, there were no racial disparities observed for metastasis, ACM, or prostate cancer-specific mortality (PCSM). However, in the CCR cohort, the racial disparities were observed for metastasis (adjusted odds ratio [AOR], 1.36; 95% CI, 1.22-1.52), ACM (adjusted hazard ratio [AHR], 1.13; 95% CI, 1.04-1.24), and PCSM (AHR, 1.15; 95% CI, 1.05-1.25). Heterogeneity was observed for the racial disparity in ACM in the VA vs CCR cohorts (AHR, 0.90 [95% CI, 0.76-1.06] vs 1.13 [95% CI, 1.04-1.24]; P = .01). No evidence of nSES disparities was observed for any prostate cancer outcomes in the VA cohort. However, in the CCR cohort, heterogeneity was observed for nSES disparities with ACM (AHR, 0.82; 95% CI, 0.80-0.84; P = .002) and PCSM (AHR, 0.86; 95% CI, 0.82-0.89; P = .007). Results of this study suggest that racial and nSES disparities were wider among patients seeking care outside of the VA health care system. Health systems-related interventions that address access barriers may mitigate racial and socioeconomic disparities in prostate cancer.

Abstract P246: Geographical Mapping and Cluster Analysis of Ischemic Stroke in Kentucky

Background: Stroke death is the third leading cause of death in the United States, the sixth leading cause of death in Kentucky (KY), and ischemic stroke (IS) is the most prevalent type in adults (~85%). Small area estimates of stroke incidence can help identify local interventions to lower the burden of vascular risk factors and risk of recurrent IS in these areas. Therefore, the goals of this study are to calculate small area IS incidence rates, examine clusters, and understand the distribution of IS in KY. Methods: Data was obtained from the Kentucky Hospital Inpatient Discharge and Outpatient Services Databases (HIDOSD) from 2012 to 2021; and the Kentucky Cabinet for Health and Family Services. HIDOSD represents KY emergency department discharges, inpatient data, and ambulatory facility services. We linked 5-digit Zip codes to (n=759) zip code tabulation areas (ZCTA) available from the US Census Bureau. The annualized IS rate per 100,000 was calculated by dividing the mean number of IS hospitalizations from 2012 to 2021 by the ZCTA 2020 population. We categorized IS rates by quartiles and calculated box plots in descriptive analyses. We tested for significant spatial clusters using the Local Moran’s I with Empirical Bayes rate smoothing in GeoDa. Results: From 2012-2021, 90,840 IS hospitalizations were reported in KY. The median IS rate was 226.5 per 100,000. The median rate in the highest quartile was 290.8 (IQR 171.7 - 290.8) vs 171.7 (IQR 171.7 - 290.8) in the lowest quartile. An area of high IS rate clusters (n=20) was identified in southeastern KY with lower clusters dispersed throughout the state. Figure. Conclusions: This 10-year analysis of IS hospitalizations across KY identified areas of potential intervention. Future efforts are needed to identify the social and medical contributors driving burden of IS in these areas and to design interventions targeted to improve health outcomes.

New Frontiers: The Origins and Content of New Work, 1940–2018

Abstract We answer three core questions about the hypothesized role of newly emerging job categories (“new work”) in counterbalancing the erosive effect of task-displacing automation on labor demand: what is the substantive content of new work, where does it come from, and what effect does it have on labor demand? We construct a novel database spanning eight decades of new job titles linked to U.S. Census microdata and to patent-based measures of occupations’ exposure to labor-augmenting and labor-automating innovations. The majority of current employment is in new job specialties introduced since 1940, but the locus of new-work creation has shifted from middle-paid production and clerical occupations over 1940–1980 to high-paid professional occupations and secondarily to low-paid services since 1980. New work emerges in response to technological innovations that complement the outputs of occupations and demand shocks that raise occupational demand. Innovations that automate tasks or reduce occupational demand slow new-work emergence. Although the flow of augmentation and automation innovations is positively correlated across occupations, the former boosts occupational labor demand while the latter depresses it. The demand-eroding effects of automation innovations have intensified in the past four decades while the demand-increasing effects of augmentation innovations have not.

Lead-associated mortality in the US 1999-2020: a time-stratified analysis of a national cohort.

We undertook time-stratified analyses of the National Health and Nutrition Examination Survey in the US to assess time trends (1999-2020) in the associations of blood lead (BL) with blood pressure, mortality, the BL-associated population attributable fraction (PAF). Vital status of participants, 20-79 years old at enrolment, was ascertained via the National Death Index. Regressions, mediation analyses and PAF were multivariable adjusted and standardized to 2020 US Census data. In time-stratified analyses, BL decreased from 1.76 μg/dl in 1999-2004 to 0.93 μg/dl in 2017-2020, while the proportion of individuals with BL < 1 μg/dl increased from 19.2% to 63.0%. Total mortality was unrelated to BL (hazard ratio (HR) for a fourfold BL increment: 1.05 [95% confidence interval, CI: 0.93-1.17]). The HR for cardiovascular death was 1.44 (1.01-2.07) in the 1999-2000 cycle, but lost significance thereafter. BL was directly related to cardiovascular mortality, whereas the indirect BL pathway via BP was not significant. Low socioeconomic status (SES) was directly related to BL and cardiovascular mortality, but the indirect SES pathway via BL lost significance in 2007-2010. From 1999-2004 to 2017-2020, cardiovascular PAF decreased ( P < 0.001) from 7.80% (0.17-14.4%) to 2.50% (0.05-4.68%) and number of lead-attributable cardiovascular deaths from 53 878 (1167-99 253) to 7539 (160-14 108). Due to implementation of strict environmental policies, lead exposure is no longer associated with total mortality, and the mildly increased cardiovascular mortality is not associated with blood lead via blood pressure in the United States.

Contextualizing Lives and Historical Time: Examining Changes in the Transition to Adulthood and Age-Arrest Trajectories from the 1960s to 2018

Objectives: The changing nature and timing of adult role acquisition during the transition to adulthood over the past several decades may hold implications for criminal offending as adult roles are fundamental to theories of desistance. This research explores whether changes in adult role attainment during young adulthood are associated with the changes in the level and slope of the age-arrest trajectory over the past half-century. Methods: Combining US Census and Uniform Crime Report data, we map the average rate of adult role attainment (e.g., marriage, parenthood, labor force, independent living) and aggregate age-arrest trajectories among young adults (ages 18-24) biennially from 1960 to 2018. We fit a multilevel growth curve model where ages are nested within years to examine whether variation in the aggregate age-arrest trajectory is associated with variation in the attainment of adulthood. Results: At the macro level, periods with higher levels of adult role attainment are associated with a swifter decline in the young adult arrest rate but not the level. Conclusions: This research positions sociohistorical context at the center of life course criminological inquiry and highlights how historical shifts in the attainment and timing of adult social roles can alter behavioral patterns during the transition to adulthood.

Survival analysis under imperfect record linkage using historic census data

BackgroundAdvancements in linking publicly available census records with vital and administrative records have enabled novel investigations in epidemiology and social history. However, in the absence of unique identifiers, the linkage of the records may be uncertain or only be successful for a subset of the census cohort, resulting in missing data. For survival analysis, differential ascertainment of event times can impact inference on risk associations and median survival.MethodsWe modify some existing approaches that are commonly used to handle missing survival times to accommodate this imperfect linkage situation including complete case analysis, censoring, weighting, and several multiple imputation methods. We then conduct simulation studies to compare the performance of the proposed approaches in estimating the associations of a risk factor or exposure in terms of hazard ratio (HR) and median survival times in the presence of missing survival times. The effects of different missing data mechanisms and exposure-survival associations on their performance are also explored. The approaches are applied to a historic cohort of residents in Ambler, PA, established using the 1930 US census, from which only 2,440 out of 4,514 individuals (54%) had death records retrievable from publicly available data sources and death certificates. Using this cohort, we examine the effects of occupational and paraoccupational asbestos exposure on survival and disparities in mortality by race and gender.ResultsWe show that imputation based on conditional survival results in less bias and greater efficiency relative to a complete case analysis when estimating log-hazard ratios and median survival times. When the approaches are applied to the Ambler cohort, we find a significant association between occupational exposure and mortality, particularly among black individuals and males, but not between paraoccupational exposure and mortality.DiscussionThis investigation illustrates the strengths and weaknesses of different imputation methods for missing survival times due to imperfect linkage of the administrative or registry data. The performance of the methods may depend on the missingness process as well as the parameter being estimated and models of interest, and such factors should be considered when choosing the methods to address the missing event times.

Institutional and Regional Variation in Opioid Prescribing for Hospitalized Infants in the US

High-risk infants, defined as newborns with substantial neonatal-perinatal morbidities, often undergo multiple procedures and require prolonged intubation, resulting in extended opioid exposure that is associated with poor outcomes. Understanding variation in opioid prescribing can inform quality improvement and best-practice initiatives. To examine regional and institutional variation in opioid prescribing, including short- and long-acting agents, in high-risk hospitalized infants. This retrospective cohort study assessed high-risk infants younger than 1 year from January 1, 2016, to December 31, 2022, at 47 children's hospitals participating in the Pediatric Health Information System (PHIS). The cohort was stratified by US Census region (Northeast, South, Midwest, and West). Variation in cumulative days of opioid exposure and methadone treatment was examined among institutions using a hierarchical generalized linear model. High-risk infants were identified by International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes for congenital heart disease surgery, medical and surgical necrotizing enterocolitis, extremely low birth weight, very low birth weight, hypoxemic ischemic encephalopathy, extracorporeal membrane oxygenation, and other abdominal surgery. Infants with neonatal opioid withdrawal syndrome, in utero substance exposure, or malignant tumors were excluded. Any opioid exposure and methadone treatment. Regional and institutional variations in opioid exposure. Overall, 132 658 high-risk infants were identified (median [IQR] gestational age, 34 [28-38] weeks; 54.5% male). Prematurity occurred in 30.3%, and 55.3% underwent surgery. During hospitalization, 76.5% of high-risk infants were exposed to opioids and 7.9% received methadone. Median (IQR) length of any opioid exposure was 5 (2-12) cumulative days, and median (IQR) length of methadone treatment was 19 (7-46) cumulative days. There was significant hospital-level variation in opioid and methadone exposure and cumulative days of exposure within each US region. The computed intraclass correlation coefficient estimated that 16% of the variability in overall opioid prescribing and 20% of the variability in methadone treatment was attributed to the individual hospital. In this retrospective cohort study of high-risk hospitalized infants, institution-level variation in overall opioid exposure and methadone treatment persisted across the US. These findings highlight the need for standardization of opioid prescribing in this vulnerable population.

Development of a Social Risk Score in the Electronic Health Record to Identify Social Needs Among Underserved Populations: Retrospective Study.

Patients with unmet social needs and social determinants of health (SDOH) challenges continue to face a disproportionate risk of increased prevalence of disease, health care use, higher health care costs, and worse outcomes. Some existing predictive models have used the available data on social needs and SDOH challenges to predict health-related social needs or the need for various social service referrals. Despite these one-off efforts, the work to date suggests that many technical and organizational challenges must be surmounted before SDOH-integrated solutions can be implemented on an ongoing, wide-scale basis within most US-based health care organizations. We aimed to retrieve available information in the electronic health record (EHR) relevant to the identification of persons with social needs and to develop a social risk score for use within clinical practice to better identify patients at risk of having future social needs. We conducted a retrospective study using EHR data (2016-2021) and data from the US Census American Community Survey. We developed a prospective model using current year-1 risk factors to predict future year-2 outcomes within four 2-year cohorts. Predictors of interest included demographics, previous health care use, comorbidity, previously identified social needs, and neighborhood characteristics as reflected by the area deprivation index. The outcome variable was a binary indicator reflecting the likelihood of the presence of a patient with social needs. We applied a generalized estimating equation approach, adjusting for patient-level risk factors, the possible effect of geographically clustered data, and the effect of multiple visits for each patient. The study population of 1,852,228 patients included middle-aged (mean age range 53.76-55.95 years), White (range 324,279/510,770, 63.49% to 290,688/488,666, 64.79%), and female (range 314,741/510,770, 61.62% to 278,488/448,666, 62.07%) patients from neighborhoods with high socioeconomic status (mean area deprivation index percentile range 28.76-30.31). Between 8.28% (37,137/448,666) and 11.55% (52,037/450,426) of patients across the study cohorts had at least 1 social need documented in their EHR, with safety issues and economic challenges (ie, financial resource strain, employment, and food insecurity) being the most common documented social needs (87,152/1,852,228, 4.71% and 58,242/1,852,228, 3.14% of overall patients, respectively). The model had an area under the curve of 0.702 (95% CI 0.699-0.705) in predicting prospective social needs in the overall study population. Previous social needs (odds ratio 3.285, 95% CI 3.237-3.335) and emergency department visits (odds ratio 1.659, 95% CI 1.634-1.684) were the strongest predictors of future social needs. Our model provides an opportunity to make use of available EHR data to help identify patients with high social needs. Our proposed social risk score could help identify the subset of patients who would most benefit from further social needs screening and data collection to avoid potentially more burdensome primary data collection on all patients in a target population of interest.

Compositional kriging analysis: A spatial interpolation method for distributions

Effective development of subsurface petroleum resources relies on the estimation of spatially distributed parameters at undrilled locations. Established geostatistical algorithms based on kriging exist for the estimation of scalar spatial variables such as porosity and permeability. This may not be suitable for the estimation of distributions of properties, such as grain size, whose whole distribution varies spatially. The current conventional approach is to fit a normal or log-normal distribution to the available data, and then to estimate the parameters of the distribution, the mean and standard deviation, spatially using kriging, taking care to consider any dependence between the mean and standard deviation. The assumption that all the grain size distributions can be approximated by a single distribution type is unsatisfactory, since datasets have very different-looking distributions, with variations in skewness, kurtosis, and modality. This paper presents an alternative approach that can handle significant variability in the distribution shape by separating the distribution into bins, like a histogram, and treating these bins as percentages in a composition. Compositional data needs to be mapped onto a simplex to overcome spurious correlations between those components, in addition, spatial estimation methods for compositional data have already been developed. However, the contribution to this field is the mapping of continuous data from distributions into a composition that enables the compositional kriging method to predict distributions at new locations. Moreover, the results showed the prediction distributions in the presence of varying modality, skewness, and kurtosis. Therefore, the grain size datasets in this paper have been working with the confidentiality restrictions so it explains the technique with a dataset of population ages from the US census 2010 for the state of Texas, which shows similar variability in distribution.

Lack of racial and ethnic diversity in pediatric ophthalmology clinical trials from 2000 to 2022

PurposeTo examine the prevalence of and factors associated with racial and ethnic reporting and trends in such reporting and to assess whether categories of race and ethnicity have been under- or over-represented in pediatric ophthalmology randomized control trials (RCTs) in the United States. MethodsWe systematically searched the literature on pediatric ophthalmology RCTs in high-impact factor ophthalmology journals published between 2000 and 2022. Logistic regression was used to assess parameters linked to race/ethnicity reporting; linear regression, to gauge the relationship between publication year and race/ethnicity reporting. The racial and ethnic composition of RCTs was contrasted with 2010 US census data by calculating percentage difference. ResultsOf 170 eligible articles, 89 (52.4%) included race/ethnicity data. Multivariable analysis showed that academic (OR = 12.19; 95% CI, 3.34-44.44) and government (OR = 3.91; 95% CI, 1.20-12.72) funding was linked to data reporting. During the study period, publication year and race/ethnicity reporting had a nonstatistically significant 1.0% annual increase (r = 0.29, P = 0.18). White participants were over-represented, with a percentage difference of 16.7% (95% CI, 11.8%-21.7%), whereas Hispanic individuals were under-represented, with a percentage difference of −7.6% (95% CI, −11.2% to −4.1%) compared to the 2010 US census data. ConclusionsOur results indicate a gradual rise in reported race and/or ethnicity in published pediatric ophthalmology RCTs, though not statistically significant, both in the United States and globally. Notably, under-representation of Hispanic, over-representation of White, and proportional representation of Black and Asian individuals were observed in US-based studies.

Non-family Living Arrangements Among Young Adults in the United States

The share of young adults living in married-couple family households in the USA has declined in recent decades. Research on alternative living arrangements focuses on cohabitation among unmarried couples and parent–adult child coresidence. Less is known about trends in non-family living arrangements and the characteristics of young adults living with non-relatives. This study documents trends over time in non-family living arrangements among young adults in the USA and examines the sociodemographic profile of those living with non-relatives. Using pooled US Census and American Community Survey microdata from 1990 to 2019, the authors document age patterns in non-family living arrangements over time and use logistic regression to estimate the likelihood of living with non-family based on individual-level characteristics. Results indicate that non-family living among young adults has increased over time, and that the arrangement is associated with markers of both advantage and disadvantage. Differences across age groups explain some of these mixed results. Trends among younger groups are linked to socioeconomic patterns around family formation. Among older groups, the demographic and labor force characteristics of the foreign born and constraints of their kin availability may be driving trends. The exploratory analysis provides relevant evidence around an increasingly common living arrangement in the USA and also identifies several areas for future research on living arrangements among young adults and the implications of these trends.

Association between neighborhood poverty and ovarian reserve: the ovarian aging study.

This study aimed to examine the association between neighborhood poverty and ovarian reserve. Among 1,019 healthy premenopausal women in the Ovarian Aging Study, aggregate exposure to neighborhood poverty was examined in relation to biomarkers of ovarian reserve, antimüllerian hormone (AMH) and antral follicle count (AFC). Specifically, the interaction of age-x-neighborhood poverty was assessed cross-sectionally to determine whether AMH and AFC declines across women may be greater in women exposed to more neighborhood poverty. Neighborhood poverty was assessed by geocoding and linking women's residential addresses in adulthood to US Census data. Independent of covariates, a significant interaction term showed the association between age and AMH varied by degree of exposure to neighborhood poverty in adulthood ( b = -0.001, P < 0.05). AMH declines increased progressively across women exposed to low, medium, and high levels of neighborhood poverty. In addition, main effects showed that higher neighborhood poverty was related to higher AMH in the younger women only ( b = 0.022, P < 0.01). Results related to AFC were all nonsignificant ( P > 0.05). Across women, greater aggregate exposure to neighborhood poverty in adulthood was related to lower ovarian reserve, indexed by AMH. In addition, there was a positive association between neighborhood poverty and AMH in younger women that attenuated in the older women. Together, results suggest that neighborhood disadvantage may have detrimental impacts that manifest as initially higher AMH, resulting in greater ovarian follicle loss over time. However, it remains unclear whether these results examining differences across women may replicate when AMH declines by neighborhood poverty are examined longitudinally.

(252) Has the COVID-19 Pandemic Impacted Penile Implant Public Interest in the US?

Abstract Introduction The COVID-19 pandemic has significantly impacted various aspects of society, including healthcare-seeking behaviors. Online search trends have become valuable indicators of public health concerns and interests. Objective This study focuses on the search trends for penile implants to understand how these trends have changed in different metro/county income levels pre- and post-COVID-19. Methods Data on Google search trends for penile implant procedures were collected for specific metropolitan areas before and after the COVID-19 pandemic. The metropolitan areas with the highest search intents were further analyzed. Average household income and per capita income, based off 2021 US Census Bureau, were calculated for the top five metropolitan hot spots (household income, per capita income before and after the pandemic) then visualized in a linear model. Results Between 2016 and 2023, pre- and post- COVID-19, the interest in penile implants has been steadily increasing on average in the US (figure 1). Within these interest groups, a handful of counties account for the most searches that result in the following surges, and are associated with specific socioeconomic backgrounds and events. Before COVID-19, the average household income of counties most interested in penile implants was $53,215.80 (39th percentile) and the per capita median income was $34,626.80 (37th percentile). Post-COVID-19, both of these averages decreased over time to $50, 945.17 (37th percentile) and $31, 435.17, respectively (34th percentile) (figure 2). Conclusions This study demonstrates significant increases in Google search trends for penile implant procedures after the COVID-19 pandemic. Before the pandemic, higher-income regions demonstrated more interest in penile implant searches, potentially linked to affluence and investment in men’s health, compared to more interest in lower income regions post-pandemic. Disclosure Any of the authors act as a consultant, employee or shareholder of an industry for: Advisory board and speaker for Coloplast; consultant for Cynosure; advisory board and speaker for Halozyme; intellectual property with Masimo; advisory board for Promescent; consultant for Sprout; advisory board for Xialla.

Firearm Access and Gun Violence Exposure Among American Indian or Alaska Native and Black Adults

American Indian or Alaska Native and Black adults experience elevated rates of firearm injury and death, but both groups are severely underrepresented in research on firearm exposure and behaviors. To explore geodemographic differences in firearm behaviors and violence exposure among American Indian or Alaska Native and Black adults in the US. In this survey study, nationally representative samples of American Indian or Alaska Native and/or Black adults recruited from KnowledgePanel were surveyed cross-sectionally. Surveys were administered online between April 12 and May 4, 2023. Firearm access, storage, and carrying behaviors and lifetime firearm violence exposure were the primary outcomes. Demographic factors such as age, geographic location, and political affiliation were considered. Data were weighted to geodemographic distributions from the US Census Bureau's 2022 Current Population Survey. Of 3542 participants, 527 (14.9%) were American Indian or Alaska Native (280 [53.1%] female) and 3015 (85.1%) were Black (1646 [54.6%] female). Both groups exhibited high firearm access rates (American Indian or Alaska Native adults: 238 [45.4%; 95% CI, 39.4%-51.7%]; Black adults: 909 [30.4%; 95% CI, 28.0%-32.9%]), predominantly owning handguns for home protection. The groups demonstrated similar firearm storage patterns, and a substantial proportion endorsed always or almost always carrying firearms outside the home (American Indian or Alaska Native adults: 18.9%; Black adults: 15.2%). Self-protection was a common reason for carrying a firearm (American Indian or Alaska Native adults: 104 [84.9%; 95% CI, 74.1%-91.7%]; Black adults: 350 [88.3%; 95% CI, 82.3%-92.4%]), and a minority of participants cited lack of faith in the police (American Indian or Alaska Native adults: 19 [15.2%; 95% CI, 8.2%-26.7%]; Black adults: 61 [15.4%; 95% CI, 10.3%-21.2%]), indicating potential shifts in public safety dynamics. In this survey study of American Indian or Alaska Native and Black US adults, a substantial percentage of both groups reported living in homes with firearms, storing firearms loaded and unlocked, frequently carrying firearms outside the home, and having been exposed directly and indirectly to gun violence. These findings underscore the need for nuanced public health campaigns and policies and highlight challenges for law enforcement in contexts of racial disparities and changing legal frameworks.

Steering, rowing, and bailing water: The role of government regulation and ownership in COVID-19 outcomes in nursing homes

Studies of organizations with limited capacity operating in uncertain environments and hit by crises can contribute important insights into public administration. Based on a large-N quantitative analysis of US nursing homes, which became ground zero of the COVID-19 pandemic, this article examines the effect of government regulation, ownership, and several distinct management strategies on organizational capacity to curb the threats posed by the pandemic. Using hybrid datasets including nursing home data, administrator surveys, COVID-19 outcome data, a COVID-19 regulatory stringency index, and US Census Bureau data, our analysis shows that restrictive COVID-19 state government policies and public/nonprofit ownership help minimize environmental threats and reduce COVID-19 impacts. Yet management strategies—external management, innovation management, distributive leadership, and regulation management—have only modest effects on COVID-19 outcomes. These findings inform our understanding of how organizations operate at the margins and the impact of management on outcomes during a crisis.

Abstract A004: TP53 mutational landscape in non-cancerous endometrium during the lifespan of Black and White individuals

Abstract Background TP53 somatic mutations accumulate and clonally expand in histologically normal tissues with aging, however, little is known about this process and how it influences cancer development. Within endometrial carcinoma, TP53 mutations tend to be found in aggressive, non-endometrioid histologies associated with poor survival outcomes, more commonly affecting Black women. We seek to understand the TP53 mutational burden in benign endometrium by characterizing mutations acquired throughout a lifespan with the integration of social determinants of health in Black and White women. Methods Endometrial tissue was collected at autopsy or hysterectomy, confirmed with H&amp;E staining, and macrodissected. Ultra-deep duplex sequencing (~10,000x) of isolated DNA was used to sequence TP53somatic mutations with high resolution. Each individual’s TP53 mutation frequency was calculated as the number of unique TP53 variants divided by the total duplex nucleotides sequenced. Mutations were classified as pathogenic if insertion-deletion, splice, or nonsense in addition to all pathogenic substitutions identified by the Seshat TP53 database. Socioeconomic metrics were acquired using zip codes and the 2021 US Census Bureau American Community Survey. Individuals with a history of endometriosis, prior malignancy, or prior chemotherapy were excluded. Results Benign endometrial tissue was collected from 69 individuals (24 Black, 45 White), including 22 aged 0-19 years, 25 aged 20-39 years, 17 aged 40-59 years, and 5 aged over 60 years. 174 TP53 variants were identified. Variant types included 66.7% missense (n=116), 13.2% insertion-deletion (n=23), 12.1% synonymous (n=21), 4.6% nonsense (n=8), and 3.4% splice (n=6). 102 TP53 mutations (58.6%) were pathogenic. TP53 mutation frequency increased linearly with age (Spearman correlation p&amp;lt;0.01). 12.6% of mutations were identified in more than one duplex mutant read (large clone) beginning at age 29 through age 81. The frequency of large TP53 mutant clones increased exponentially with age. In this limited dataset, there was no statistical association between socioeconomic metrics and the mutational burden of Black and White individuals. Conclusions The number and size of TP53 mutant clones in benign endometrium are associated with older age, indicating clonal evolution through life. Most somatic mutations identified were pathogenic substitutions or loss-of-function variants, confirming positive selection of cancer-like mutations. Additional data are needed to determine the role of socioeconomic factors in TP53 genomic burden. Citation Format: Eric Rios-Doria, Elizabeth U. Parker, Brendan F. Kohrn, Elena Latorre-Estevez, Jeanne Fredrickson, Elizabeth M. Swisher, Kemi M. Doll, Rosana Risques. TP53 mutational landscape in non-cancerous endometrium during the lifespan of Black and White individuals [abstract]. In: Proceedings of the AACR Special Conference on Endometrial Cancer: Transforming Care through Science; 2023 Nov 16-18; Boston, Massachusetts. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(5_Suppl):Abstract nr A004.

A Nationwide Survey Study of Recovery Community Centers Supporting People in Recovery From Substance Use Disorder.

The medical community has become aware of its role in contributing to the opioid epidemic and must be part of its resolution. Recovery community centers (RCCs) represent a new underused component of recovery support. This study performed an online national survey of all RCCs identified in the United States, and used US Census ZIP code tabulation area data to describe the communities they serve. Residents of areas with RCCs were more likely to be Black (16.5% vs 12.6% nationally, P = 0.005) and less likely to be Asian (4.7% vs 5.7%, P = 0.005), American Indian, or Alaskan Native (0.6% vs 0.8%, P = 0.03), or live rurally (8.5% vs 14.0%, P < 0.0001). More than half of RCCs began operations within the past 5 years. Recovery community centers were operated, on average, by 8.8 paid and 10.2 volunteer staff; each RCC served a median of 125 individuals per month (4-1,500). Recovery community centers successfully engaged racial/ethnic minority groups (20.8% Hispanic, 22.5% Black) and young adults (23.5% younger than 25 years). Recovery community centers provide addiction-specific support (eg, mutual help, recovery coaching) and assistance with basic needs, social services, technology access, and health behaviors. Regarding medications for opioid use disorder (MOUDs), RCC staff engaged members in conversations about MOUDs (85.2%) and provided direct support for taking MOUD (77.0%). One third (36.1%) of RCCs reported seeking closer collaboration with prescribers. Recovery community centers are welcoming environments for people who take MOUDs. Closer collaboration between the medical community and community-based peer-led RCCs may lead to significantly improved reach of efforts to end the opioid epidemic.

Increasing Racial and Ethnic Disparities in Ambient Air Pollution-Attributable Morbidity and Mortality in the United States.

Ambient nitrogen dioxide () and fine particulate matter with aerodynamic diameter () threaten public health in the US, and systemic racism has led to modern-day disparities in the distribution and associated health impacts of these pollutants. Many studies on environmental injustices related to ambient air pollution focus only on disparities in pollutant concentrations or provide only an assessment of pollution or health disparities at a snapshot in time. In this study, we compare injustices in and health burdens, considering health impacts across the entire US; document changing disparities in these health burdens over time (2010-2019); and evaluate how more stringent air quality standards would reduce disparities in health impacts associated with these pollutants. Through a health impact assessment, we quantified census tract-level variations in health outcomes attributable to and using health impact functions that combine demographic data from the US Census Bureau; two spatially resolved pollutant datasets, which fuse satellite data with physical and statistical models; and epidemiologically derived relative risk estimates and incidence rates from the Global Burden of Disease study. Despite overall decreases in the public health damages associated with and , racial and ethnic relative disparities in pediatric asthma and premature mortality have widened in the US during the last decade. Racial relative disparities in premature mortality and pediatric asthma have increased by 16% and 19%, respectively, between 2010 and 2019. Similarly, ethnic relative disparities in premature mortality have increased by 40% and pediatric asthma by 10%. Enacting and attaining more stringent air quality standards for both pollutants could preferentially benefit the most marginalized and minoritized communities by greatly reducing racial and ethnic relative disparities in pollution-attributable health burdens in the US. Our methods provide a semi-observational approach to track changes in disparities in air pollution and associated health burdens across the US. https://doi.org/10.1289/EHP11900.

Estimate of the revenue and economic contribution of the professional pest management industry in Georgia, United States.

The Professional Pest Management Industry (PPMI) dates back over a century in the United States. Stakeholder calls for economic studies of the PPMI include, in the 1980s, the National Research Council, although there has been little to no progress on that topic. US Census and Bureau of Labor Statistics data indicate that revenue and employment for the PPMI in Georgia increased 117% from 1997 to 2021. We determined the revenue, employment, and economic contributions for the PPMI in Georgia, United States, using 2 methodologies applied to IMPLAN: primary survey data in combination with an open records request and publicly available Federal Economic data. Estimates of average revenue for the Georgia PPMI in 2021 were $833-$988 million, using the survey/open records and publicly available data, respectively. We utilized an economic modeling program, IMPLAN, to estimate the economic contributions by the Georgia PPMI in 2021 to be between $1.7 and $2.0 billion, with 13,000-14,000 jobs for the 2 respective data sets. We describe the methods and provide tutorials for other states or national organizations to follow to generate justifiable, comparable economic information on the PPMI. In addition, we discuss the unique position of the PPMI as heavily regulated by State Departments of Agriculture to advocate for including the PPMI economic values when reporting agricultural economic contributions.