Statistics Population Data Research Articles

The association between low-dose aspirin intake and osteoarthritis: a population-based cross-sectional study based on NHANES.

Low-dose aspirin is widely used as a preventive medication for cardiovascular diseases. However, there is controversy regarding the impact of low-dose aspirin on articular cartilage. The aim of this study is to explore the association between low-dose aspirin intake and osteoarthritis (OA). We conducted a cross-sectional study based on the United States population data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018. The investigation of low-dose aspirin intake and the diagnosis of OA was based on self-reporting in questionnaires. Multivariate regression models was used to assess the relationship between low-dose aspirin intake and OA. In addition, subgroup and interaction analysis were performed to assess the robustness of the results. A total of 12,215 participants were included in this study. Multivariate logistic regression analysis showed that low-dose aspirin use had significantly increased the odds of OA (OR = 1.14; 95% CI: 1.01-1.28; p = 0.035). A significant and consistent association of low-dose aspirin intake with OA was still observed in each subgroup stratified by gender, age, and the presence of comorbidities including diabetes, coronary heart disease, hypertension, and stroke. The results illustrated that the relationship between low-dose aspirin intake and OA was stable in all subgroups and had no interaction. Our study confirmed that low-dose aspirin intake may increase the risk of OA. Attention should be paid to the possibility of joint degenerative changes in patients who take low-dose aspirin chronically. However, further studies are needed to explore the possible mechanisms behind this association.

Mortality due to falls by county, age group, race, and ethnicity in the USA, 2000–19: a systematic analysis of health disparities

Fall-related mortality has increased rapidly over the past two decades in the USA, but the extent to which mortality varies across racial and ethnic populations, counties, and age groups is not well understood. The aim of this study was to estimate age-standardised mortality rates due to falls by racial and ethnic population, county, and age group over a 20-year period. Redistribution methods for insufficient cause of death codes and validated small-area estimation methods were applied to death registration data from the US National Vital Statistics System and population data from the US National Center for Health Statistics to estimate annual fall-related mortality. Estimates from 2000 to 2019 were stratified by county (n=3110) and five mutually exclusive racial and ethnic populations: American Indian or Alaska Native (AIAN), Asian or Pacific Islander (Asian), Black, Latino or Hispanic (Latino), and White. Estimates were corrected for misreporting of race and ethnicity on death certificates using published misclassification ratios. We masked (ie, did not display) estimates for county and racial and ethnic population combinations with a mean annual population of less than 1000. Age-standardised mortality is presented for all ages combined and for age groups 20-64 years (younger adults) and 65 years and older (older adults). Nationally, in 2019, the overall age-standardised fall-related mortality rate for the total population was 13·4 deaths per 100 000 population (95% uncertainty interval 13·3-13·6), an increase of 65·3% (61·9-68·8) from 8·1 deaths per 100 000 (8·0-8·3) in 2000, with the largest increases observed in older adults. Fall-related mortality at the national level was highest across all years in the AIAN population (in 2019, 15·9 deaths per 100 000 population [95% uncertainty interval 14·0-18·2]) and White population (14·8 deaths per 100 000 [14·6-15·0]), and was about half as high among the Latino (8·7 deaths per 100 000 [8·3-9·0]), Black (8·1 deaths per 100 000 [7·9-8·4]), and Asian (7·5 deaths per 100 000 [7·1-7·9]) populations. The disparities between racial and ethnic populations varied widely by age group, with mortality among younger adults highest for the AIAN population and mortality among older adults highest for the White population. The national-level patterns were observed broadly at the county level, although there was considerable spatial variation across ages and racial and ethnic populations. For younger adults, among almost all counties with unmasked estimates, there was higher mortality in the AIAN population than in all other racial and ethnic populations, while there were pockets of high mortality in the Latino population, particularly in the Mountain West region. For older adults, mortality was particularly high in the White population within clusters of counties across states including Florida, Minnesota, and Wisconsin. Age-standardised mortality due to falls increased over the study period for each racial and ethnic population and almost every county. Wide variation in mortality across geography, age, and race and ethnicity highlights areas and populations that might benefit most from efficacious fall prevention interventions as well as additional prevention research. US National Institutes of Health (Intramural Research Program, National Institute on Minority Health and Health Disparities; National Heart, Lung, and Blood Institute; Intramural Research Program, National Cancer Institute; National Institute on Aging; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Office of Disease Prevention; and Office of Behavioral and Social Sciences Research).

Per Capita Cropland Estimations for Traditional Agricultural Areas of China over Past Millennium

Studying changes in land use per capita is critical for understanding the interactions between humans and ecosystems, and for modeling the impacts of land use changes on climate systems. However, many uncertainties in historical estimates significantly hinder climate modeling. This study estimated the per capita cropland area in traditional agricultural regions of China over the past millennium using historical-document-based and modern statistical cropland and population data. The findings showed that changes in the per capita cropland area in the provinces of the middle and lower reaches of the Yellow River could be characterized into three stages: slow decrease, rapid increase, and fluctuating decrease, whereas, in the provinces of the middle and lower reaches of the Yangtze River, there was a continuous decrease. Spatially, the per capita cropland area was higher in the middle and lower reaches of the Yellow River and lower in the middle and lower reaches of the Yangtze River during the study period. The per capita cropland areas showed clear differences in the HYDE dataset and our study; the corresponding values of our study were 2.1–8.0, 1.7–8.2, and 1.6–8.8 times higher than those from the HYDE dataset for the early Song, Yuan, and Ming dynasties, respectively.

Cancer incidence, treatment, and survival in the prison population compared with the general population in England: a population-based, matched cohort study

The growing and ageing prison population in England makes accurate cancer data of increasing importance for prison health policies. This study aimed to compare cancer incidence, treatment, and survival between patients diagnosed in prison and the general population. In this population-based, matched cohort study, we used cancer registration data from the National Cancer Registration and Analysis Service in England to identify primary invasive cancers and cervical cancers in situ diagnosed in adults (aged ≥18 years) in the prison and general populations between Jan 1, 1998, and Dec 31, 2017. Ministry of Justice and Office for National Statistics population data for England were used to calculate age-standardised incidence rates (ASIR) per year and age-standardised incidence rate ratios (ASIRR) for the 20-year period. Patients diagnosed with primary invasive cancers (ie, excluding cervical cancers in situ) in prison between Jan 1, 2012, and Dec 31, 2017 were matched to individuals from the general population and linked to hospital and treatment datasets. Matching was done in a 1:5 ratio according to 5-year age group, gender, diagnosis year, cancer site, and disease stage. Our primary objectives were to compare the incidence of cancer (1998-2017); the receipt of treatment with curative intent (2012-17 matched cohort), using logistic regression adjusted for matching variables (excluding cancer site) and route to diagnosis; and overall survival following cancer diagnosis (2012-17 matched cohort), using a Cox proportional hazards model adjusted for matching variables (excluding cancer site) and route to diagnosis, with stratification for the receipt of any treatment with curative intent. We identified 2015 incident cancers among 1964 adults (1556 [77·2%] men and 459 [22·8%] women) in English prisons in the 20-year period up to Dec 31, 2017. The ASIR for cancer for men in prison was initially lower than for men in the general population (in 1998, ASIR 119·33 per 100 000 person-years [95% CI 48·59-219·16] vs 746·97 per 100 000 person-years [742·31-751·66]), but increased to a similar level towards the end of the study period (in 2017, 856·85 per 100 000 person-years [675·12-1060·44] vs 788·59 per 100 000 person-years [784·62-792·57]). For women, the invasive cancer incidence rate was low and so ASIR was not reported for this group. Over the 20-year period, the incidence of invasive cancer for men in prison increased (incidence rate ratio per year, 1·05 [95% CI 1·04-1·06], during 1999-2017 compared with 1998). ASIRRs showed that over the 20-year period, overall cancer incidence was lower in men in prison than in men in the general population (ASIRR 0·76 [95% CI 0·73-0·80]). The difference was not statistically significant for women (ASIRR 0·83 [0·68-1·00]). Between Jan 1, 2012, and Dec 31, 2017, patients diagnosed in prison were less likely to undergo curative treatment than matched patients in the general population (274 [32·3%] of 847 patients vs 1728 [41·5%] of 4165; adjusted odds ratio (OR) 0·72 [95% CI 0·60-0·85]). Being diagnosed in prison was associated with a significantly increased risk of death on adjustment for matching variables (347 deaths during 2021·9 person-years in the prison cohort vs 1626 deaths during 10 944·2 person-years in the general population; adjusted HR 1·16 [95% CI 1·03-1·30]); this association was partly explained by stratification by curative treatment and further adjustment for diagnosis route (adjusted HR 1·05 [0·93-1·18]). Cancer incidence increased in people in prisons in England between 1998 and 2017, with patients in prison less likely to receive curative treatments and having lower overall survival than the general population. The association with survival was partly explained by accounting for differences in receipt of curative treatment and adjustment for diagnosis route. Improved routine cancer surveillance is needed to inform prison cancer policies and decrease inequalities for this under-researched population. UK National Institute for Health and Care Research, King's College London, and Strategic Priorities Fund 2019/20 of Research England via the University of Surrey.

Abstract LB139: Disparities in oral precancerous lesion surveillance in the United States upper Midwest

Abstract Objective: To determine whether geographic representation and race of patients in a regional oral cancer surveillance program (University of Minnesota Cancer Active Surveillance Population (UMN CASP)) mirror characteristics in the corresponding National Cancer Institute (NCI) designated comprehensive cancer center catchment. Introduction: Oral cancer poses a significant public health concern that may be mitigated through lesion surveillance. Representation of patients for clinical trials throughout an NCI cancer center catchment area is a crucial goal to promote improved health outcomes. This study investigates the demographic landscape of patients with preneoplastic oral lesions seen at the CASP. Methods: Through the UMN Clinical and Translational Sciences Institute, we queried 30 International Classification of Disease (ICD) 9 and 10 codes corresponding to 120 unique mucosal oral precancerous lesion descriptors of CASP patients. Automated extraction of electronic medical record (EMR) data for 4,496 patients treated by the senior author between 2011 and 2023 identified 1,375 patients with preneoplastic lesions. The proportion of patients residing in three-digit zip code regions of Minnesota were compared to 2021 American Community Survey state population data. Additionally, race data were compared between CASP patients and the UMN Masonic Cancer Center (MCC) patient catchment data. Results: CASP patients were over-represented relative to state population distributions within the Minneapolis-St. Paul metropolitan area and surrounding suburbs (region 554 p<0.0001 and region 551 p<0.0001). Under-representation of CASP patients was observed in all western and southern border regions (regions 559 p<0.0001, 560 p<0.0001, 561 p<0.0001, 562 p=0.0037, 565 p<0.0001, and 567 p=0.0006) as well as portions of central (563 p<0.0001), northern (566 p=0.0015), and north-eastern (558 p<0.0001) Minnesota. Proportional representation was observed in several regions of central (553 and 564), eastern (550), and north-eastern (557 and 556) Minnesota. Comparisons of CASP race data revealed a higher proportion of black patients (CASP 8.59% [95% CI 7.17-10.27%] vs. MCC 7.16% [95% CI 7.14-7.17%]) and a lower proportion of Asian/Pacific Islander patients (CASP 3.74% [95% CI 2.82-4.94%] vs. MCC 5.32% [95% CI 5.30-5.34%]) relative to MCC catchment patients. White, American Indian/Alaskan Native, and mixed-race groups were proportionally represented in both data sets. Conclusions: These data show that system wide EMR searches can be implemented to identify patients in an NCI cancer center catchment area with precancerous or other at-risk conditions for cancer. Importantly, Native patients were proportionally represented in the screening program while several rural locations were under-represented. This information can instruct the expenditure of additional resources for under-represented groups and permit streamlined enrollment of patients for cancer prevention clinical trials. Citation Format: Alexander J. Dwyer, Lindsey Mortensen, Beverly R. Wuertz, Frank G. Ondrey. Disparities in oral precancerous lesion surveillance in the United States upper Midwest [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB139.

Burden of liver cancer mortality by county, race, and ethnicity in the USA, 2000–19: a systematic analysis of health disparities

Understanding how specific populations are affected by liver cancer is important for identifying priorities, policies, and interventions to mitigate health risks and reduce disparities. This study aims to provide comprehensive analysis of rates and trends in liver cancer mortality for different racial and ethnic populations in the USA nationally and at the county level from 2000 to 2019. We applied small-area estimation methods to death registration data from the US National Vital Statistics System and population data from the US National Center for Health Statistics to estimate liver cancer mortality rates by county, racial and ethnic population, and year (2000-19) in the USA. Race and ethnicity were categorised as non-Latino and non-Hispanic American Indian or Alaska Native (AIAN), non-Latino and non-Hispanic Asian or Pacific Islander (Asian), non-Latino and non-Hispanic Black (Black), Latino or Hispanic (Latino), and non-Latino and non-Hispanic White (White). Estimates were adjusted using published misclassification ratios to correct for inaccuracies in race or ethnicity as recorded on death certificates, and then age-standardised. Mortality rate estimates are presented for all county and racial and ethnic population combinations with a mean annual population greater than 1000. Nationally, the age-standardised liver cancer mortality rate increased between the years 2000 (4·2 deaths per 100 000 population [95% uncertainty interval 4·1-4·3]) and 2016 (6·0 per 100 000 [5·9-6·1]), followed by a stabilisation in rates from 2016 to 2019 (6·1 per 100 000 [6·0-6·2]). Similar trends were observed across the AIAN, Black, Latino, and White populations, whereas the Asian population showed an overall decrease across the 20-year study period. Qualitatively similar trends were observed in most counties; however, the mortality rate and the rate of change varied substantially across counties, both within and across racial and ethnic populations. For the 2016-19 period, mortality continued to increase at a substantial rate in some counties even while it stabilised nationally. Nationally, the White population had the lowest mortality rate in all years, while the racial and ethnic population with the highest rate changed from the Asian population in 2000 to the AIAN population in 2019. Racial and ethnic disparities were substantial: in 2019, mortality was highest in the AIAN population (10·5 deaths per 100 000 [9·1-12·0]), notably lower for the Asian (7·5 per 100 000 [7·1-7·9]), Black (7·6 per 100 000 [7·3-7·8]), and Latino (7·7 per 100 000 [7·5-8·0]) populations, and lowest for the White population (5·5 [5·4-5·6]). These racial and ethnic disparities in mortality were prevalent throughout the country: in 2019, mortality was higher in minoritised racial and ethnic populations than in the White population living in the same county in 408 (87·7%) of 465 counties with unmasked estimates for the AIAN population, 604 (90·6%) of 667 counties for the Asian population, 1207 (81·2%) of 1486 counties for the Black population, and 1073 (73·0%) of 1469 counties for the Latino population. Although the plateau in liver cancer mortality rates in recent years is encouraging, mortality remains too high in many locations throughout the USA, particularly for minoritised racial and ethnic populations. Addressing population-specific risk factors and differences in access to quality health care is essential for decreasing the burden and disparities in liver cancer mortality across racial and ethnic populations and locations. US National Institutes of Health (Intramural Research Program, National Institute on Minority Health and Health Disparities; National Heart, Lung, and Blood Institute; Intramural Research Program, National Cancer Institute; National Institute on Aging; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Office of Disease Prevention; and Office of Behavioral and Social Sciences Research).

Measurement opportunities for studying sexual and gender diverse partnerships in population‐based surveys

AbstractObjectiveThis article outlines for family scholars and researchers designing surveys or searching for data on sexual and gender‐diverse (SGD) families the latest methodological advancements in United States population‐based surveys for studying SGD partnerships by reviewing five recently collected, publicly available, population‐representative data sets.BackgroundLGBTQIA+ adults and SGD partnerships are an expanding demographic group in the United States. Yet, measurement limitations have restricted studies of these partnerships that use population‐based studies. To address this issue, researchers designing population‐representative data collections have adopted new strategies to measure SGD partnerships accurately. However, most population representative surveys continue to lack data on growing segments of the LGBTQIA+ population by relying solely on the sex of partners or limited sexual and gender identity measures.ConclusionWe recommend expanding population‐based surveys to incorporate inclusive measures of sexual and gender identity, directly asking about the gender composition of a couple and measurement of cohabiting and other nonmarital relationships. These approaches are especially important for understanding relationships among younger populations who do not follow heteronormative relationship trajectories and hold diverse gender and sexual identities.ImplicationsAlthough the research opportunities on SGD individuals and partnerships are expanding; researchers must remain mindful of the limitations of current data sets and advocate for updates to the United States population data infrastructure.

Association of low-dose aspirin use for primary prevention with self-reported kidney stones prevalence: a cross-sectional study.

To investigate the association between low-dose aspirin use for primary prevention and self-reported kidney stones prevalence in the 40-79years old population. We conducted a cross-sectional study based on the United States population data from the National Health and Nutrition Examination Survey 2011-2018. Baseline demographical and clinical data were collected. The univariate and multivariate regression was performed to identify confounding factors and assess the relationship between aspirin use for primary prevention and the prevalence of self-reported kidney stones. A propensity-score matching was used to identify patients with similar baseline characteristics to adjust for the bias caused by confounding factors. A total of 10,256 low-dose aspirin-use participants were included in this study. 10.4% of participants reported a history of kidney stones, and 18.5% reported a continuous use of low-dose prophylactic aspirin. Multivariate logistic regression analysis showed that low-dose preventive aspirin use had significantly increased the odds of self-reported kidney stones (OR = 1.245; 95% CI: 1.063-1.459; p = 0.007). In subgroup analysis, this finding was primarily limited to males (OR = 1.311), non-hypertensive participants (OR = 1.443), diabetic participants (OR = 1.380), and older (60 ≤ Age < 80) (OR = 1.349). The propensity-score matched analyses supported this result after adjusting for the bias caused by potential confounders (OR = 1.216; 95% CI: 1.011-1.462; p = 0.038). In this study, there exists a significant relationship between low-dose aspirin for primary prevention and self-reported kidney stones, primarily among males, no hypertensive participants, diabetics, or older adults. Further studies are needed to elucidate the mechanisms underlying these findings in the future.

Mapping grasslands' preservation potential: A case study from the northern Carpathians

AbstractThe grasslands which are an important part of an ecosystem are endangered due to abandonment of traditional forms of land use. Preservation of biodiversity of semi‐natural grassland communities is of great importance, therefore it is important to identify threats and prepare a sustainable plan for their protection The goal of this study was to develop an approach to predict threatened grasslands hotspots, basing on multi‐factor machine learning analyses. The Gorce Mountains in the Polish Carpathians were chosen as a study area, as it is region partially protected by National Park, surrounded by villages with different socio‐economic conditions (agriculture or touristic oriented). The grasslands were identified and classified on Sentinel‐2 multispectral imagery. As lack of regular mowing of grasslands was found as main factor promoting forest succession. Therefore, in order to find endangered grasslands areas, support vector machines' algorithm was used to classify them in mowed and unmowed categories. Then the preservation potential of grasslands was modeled with the random forest method, based on the grasslands' mowing classification, digital terrain model, land‐use and population statistical data, and the historical forest extent. We found the grasslands above 750 m above sea level to be the most endangered. Also, the tourism activity and ongoing changes in employment structure from agriculture to services has had a negative influence on the grasslands preservation potential. On the other hand, the Gorce National Park's active grassland conservation by mowing and grazing was shown as a positive element in keeping with the high biodiversity of the area.

Risk of Severe Maternal Morbidity (SMM) in patients with Placenta Accreta Spectrum (PAS) disorders referred from rural communities to a regional PAS center.

The primary objective of this study was to assess the risk of Severe Maternal Morbidity (SMM) experienced by patients residing in rural communities when delivered by a multidisciplinary team within a single urban academic center for Placenta Accreta Spectrum (PAS). Subsequently, we aimed to determine a distance dependent relationship between PAS morbidity and distance travelled by patients in rural communities. This was a retrospective cohort study of patients who had PAS histopathologic confirmation and delivery at our institution from 2005-2022. Our objective was to determine the relationship between patient locations (rural vs. urban) and maternal morbidity associated with PAS delivery. Socio-geographic determination of rurality was determined using the National Center for Health Statistics and most recent national census population data. Distance travelled was calculated by patient zip code to our PAS center using global positioning system data. During the study period, 139 patients were managed by cesarean hysterectomy with confirmed PAS histopathology. Of these, ninety-four (67.6%) were from our urban community and forty-five (32.4%) were from surrounding rural communities. The overall SMM incidence was 85% including blood transfusion and 17% without blood transfusions. Patient from rural communities were more likely to experience SMM (28.9% vs. 12.8%, p=0.03) and this was driven by acute renal failure (1.1 vs 11.1%, p=0.01) and disseminated intravascular coagulopathy (1.1 vs 8.8%, p=0.04). SMM did reveal a a distance-dependent relationship with SMM rates of 13.2%, 33.3%, and 43.8% at 50, 100 and 150 miles, respectively (p=0.005). Patients with PAS experience high rates of SMM. Geographic distance to a PAS center appears to significantly impact the overall morbidity a patient experiences. Further research is warranted to address this disparity and optimize patient outcomes for patients in rural communities.

Cause-specific mortality by county, race, and ethnicity in the USA, 2000–19: a systematic analysis of health disparities

Large disparities in mortality exist across racial-ethnic groups and by location in the USA, but the extent to which racial-ethnic disparities vary by location, or how these patterns vary by cause of death, is not well understood. We aimed to estimate age-standardised mortality by racial-ethnic group, county, and cause of death and describe the intersection between racial-ethnic and place-based disparities in mortality in the USA, comparing patterns across health conditions. We applied small-area estimation models to death certificate data from the US National Vital Statistics system and population data from the US National Center for Health Statistics to estimate mortality by age, sex, county, and racial-ethnic group annually from 2000 to 2019 for 19 broad causes of death. Race and ethnicity were categorised as non-Latino and non-Hispanic American Indian or Alaska Native (AIAN), non-Latino and non-Hispanic Asian or Pacific Islander (Asian), non-Latino and non-Hispanic Black (Black), Latino or Hispanic (Latino), and non-Latino and non-Hispanic White (White). We adjusted these mortality rates to correct for misreporting of race and ethnicity on death certificates and generated age-standardised results using direct standardisation to the 2010 US census population. From 2000 to 2019, across 3110 US counties, racial-ethnic disparities in age-standardised mortality were noted for all causes of death considered. Mortality was substantially higher in the AIAN population (all-cause mortality 1028·2 [95% uncertainty interval 922·2-1142·3] per 100 000 population in 2019) and Black population (953·5 [947·5-958·8] per 100 000) than in the White population (802·5 [800·3-804·7] per 100 000), but substantially lower in the Asian population (442·3 [429·3-455·0] per 100 000) and Latino population (595·6 [583·7-606·8] per 100 000), and this pattern was found for most causes of death. However, there were exceptions to this pattern, and the exact order among racial-ethnic groups, magnitude of the disparity in both absolute and relative terms, and change over time in this magnitude varied considerably by cause of death. Similarly, substantial geographical variation in mortality was observed for all causes of death, both overall and within each racial-ethnic group. Racial-ethnic disparities observed at the national level reflect widespread disparities at the county level, although the magnitude of these disparities varied widely among counties. Certain patterns of disparity were nearly universal among counties; for example, in 2019, mortality was higher among the AIAN population than the White population in at least 95% of counties for skin and subcutaneous diseases (455 [97·8%] of 465 counties with unmasked estimates) and HIV/AIDS and sexually transmitted infections (458 [98·5%] counties), and mortality was higher among the Black population than the White population in nearly all counties for skin and subcutaneous diseases (1436 [96·6%] of 1486 counties), diabetes and kidney diseases (1473 [99·1%]), maternal and neonatal disorders (1486 [100·0%] counties), and HIV/AIDS and sexually transmitted infections (1486 [100·0%] counties). Disparities in mortality among racial-ethnic groups are ubiquitous, occurring across locations in the USA and for a wide range of health conditions. There is an urgent need to address the shared structural factors driving these widespread disparities. National Institute on Minority Health and Health Disparities; National Heart, Lung, and Blood Institute; National Cancer Institute; National Institute on Aging; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Office of Disease Prevention; and Office of Behavioral and Social Sciences Research, US National Institutes of Health.

The burden of stomach cancer mortality by county, race, and ethnicity in the USA, 2000–2019: a systematic analysis of health disparities

There are persistent disparities in stomach cancer mortality among racial-ethnic groups in the USA, but the extent to which these patterns vary geographically is not well understood. This analysis estimated age-standardised mortality for five racial-ethnic groups, in 3110 USA counties over 20 years, to describe spatial-temporal variations in stomach cancer mortality and disparities between racial-ethnic groups. Redistribution methods for insufficient cause of death codes and validated small area estimation methods were applied to death registration data from the US National Vital Statistics System and population data from the US National Center for Health Statistics to estimate annual stomach cancer mortality rates. Estimates were stratified by county and racial-ethnic group (non-Latino and non-Hispanic [NL] American Indian or Alaska Native [AIAN], NL Asian or Pacific Islander [Asian], NL Black [Black], Latino or Hispanic [Latino], and NL White [White]) from 2000 to 2019. Estimates were corrected for misreporting of racial-ethnic group on death certificates using published misclassification ratios. We masked (ie, did not display) estimates for county and racial-ethnic group combinations with a mean annual population of less than 1000; thus, we report estimates for 3079 (of 3110) counties for the total population, and 474, 667, 1488, 1478, and 3051 counties for the AIAN, Asian, Black, Latino, and White populations, respectively. Between 2000 and 2019, national age-standardised stomach cancer mortality was lowest among the White population in every year. Nationally, stomach cancer mortality declined for all racial-ethnic groups across this time period, with the most rapid declines occurring among the Asian (percent decline 48.3% [45.1-51.1]) and Black populations (42.6% [40.2-44.6]). Mortality among the other racial-ethnic groups declined more moderately, decreasing by 36.7% (35.3-38.1), 35.1% (32.2-37.7), and 31.6% (23.9-38.0) among the White, Latino, and AIAN populations, respectively. Similar patterns were observed at the county level, although with wide geographic variation. In 2019, a majority of counties had higher mortality rates among minoritised racial-ethnic populations compared to the White population: 81.1% (377 of 465 counties with unmasked estimates for both racial-ethnic groups) among the AIAN population, 88.2% (1295 of 1469) among the Latino population, 99.4% (663 of 667) among the Asian population, and 99.9% (1484 of 1486) among the Black population. However, the size of these disparities ranged widely across counties, with the largest range from 0.3 to 17.1 among the AIAN population. Stomach cancer mortality has decreased substantially across populations and geographies in the USA. However, disparities in stomach cancer mortality among racial-ethnic groups are widespread and have persisted over the last two decades. Local-level data are crucial to understanding the scope of this unequal burden among minoritised groups in the USA. National Institute on Minority Health and Health Disparities; National Heart, Lung, and Blood Institute; National Cancer Institute; National Institute on Aging; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Office of Disease Prevention; and Office of Behavioral and Social Sciences Research, National Institutes of Health (contract #75N94019C00016).

(454) Variations in Practice Patterns of Xiaflex Providers Throughout the United States

Abstract Introduction Intralesional Collagenase Clostridium Histolyticum (CCH; Xiaflex; Endo Pharmaceuticals, Dublin, Ireland) is the only FDA-approved intralesional therapy to treat bothersome penile curvature in men with Peyronie’s Disease (PD). Clinicians who administer CCH must be certified through a risk evaluation and management strategy (REMS) program. However, provider availability is highly dependent on geography and many patients must travel great distances to undergo evaluation and treatment with CCH by an experienced injector. Objective The goal of the current study is to describe the landscape of certified CCH injectors with respect to location and clinical background/training. Methods Patients are currently able to use an online “locate a specialist” tool through Endo Pharmaceuticals to identify clinicians in their local geographic area who are certified to administer CCH. Using this tool, a list of all providers who offer CCH injections was compiled throughout the continental United States. Pertinent information that was gathered included geographic location, type of provider or level of training [Medical Doctor (MD), Doctor of Osteopathic Medicine (DO), Physician Assistant (PA), Nurse Practitioner (NP), and Registered Nurse (RN)], and gender of providers. This information was compared to state population data (United State Census Bureau) to determine per capita coverage. Results A total of 1947 Xiaflex providers were identified: 1749 Doctors of Medicine (MD; 90%), 115 Doctor of Osteopathic Medicine (DO; 6%), 60 Physician Assistants (PA; 3%), 21 Nurse Practitioners (NP; 1%), and 1 Registered Nurse (RN; 0.05%). Out of the 1947 providers, only 95 (4.9%) were women. Most women administering Xiaflex were MDs (73%), followed by PAs (12%), NP and DOs (7%), and RN (1%). Xiaflex providers were available in all states except for Hawaii and Alaska. Providers were distributed throughout the United States with the average provider per capita ratio of 230,240. Wyoming, Washington D.C., Rhode Island, and Georgia had the best provider per capita at &amp;lt;10,000 while New Mexico had the worst provider per capita ratio at 2,117,522. Conclusions Our results show significant variation in certified CCH injector availability for patients across the United States. &amp;lt; 5% of all certified clinicians are female and 4% were advanced practice providers. Further work is needed to characterize and remedy gender disparities amongst providers, and ensure greater access for patients who desire an FDA-approved non-surgical treatment for their PD-associated curvature. Disclosure No

Suicide Mortality by Place, Gender, and Age Group - China, 2010-2021.

Suicide is an important public health concern in China. We examined suicide mortality by place, sex, and age group from 2010 to 2021 to identify and quantify significant suicide mortality changes in China. We retrieved age-standardized and age-specific suicide mortality rates by place (urban vs. rural) and sex from the Chinese Health Statistical Yearbook and population data from the 2010 and 2020 Chinese National Population Census. Line graphs were used to demonstrate trends in suicide mortality. Joinpoint regression models were fitted to detect the time periods experiencing significant suicide mortality changes, and average annual percent change (AAPC) and annual percent change were reported to quantify changes in suicide mortality from 2010 to 2021. The overall age-standardized suicide mortality rate decreased from 10.88 to 5.25 per 100,000 population between 2010 and 2021 (AAPC=-5.3%, 95% confidence interval: -6.5%, -4.0%). Similar reductions in suicide mortality were observed for both males and females, as well as in urban and rural settings during this period. From 2010 to 2021, significant declines in suicide mortality were observed among the three older age groups (25-44 years, 45-64 years, and 65 years or above), while a substantial increase was noted in the youngest age group (5-14 years). No significant change was found in suicide mortality rates for the 15-24 year age group. Subgroup analyses based on location and sex revealed consistent findings. The findings of this study suggest a probable overall success of suicide prevention efforts in China over the past decade. However, the recent increase in suicide mortality among children aged 5-14 years calls for the attention of injury researchers, policymakers, and public health practitioners.

Towards sustainable development exemplified by monitoring land use efficiency in Europe using SDG 11.3.1

Abstract Monitoring land use efficiency (LUE) is of great importance for the sustainable development of each country. The identification of regions where land consumption prevails over demographic growth should prompt public administrations to act and establish a recovery programme. This paper took Europe as the research area, and CORINE Land Cover and statistical population data to assess changes and spatial diversity of the LUE status from 2006 to 2018. Results show that, during the 2006–2012 period, LUE was more diversified than in 2012–2018. The differences concern both values of the indicator and the spatial differentiation between regions. Between 2012 and 2018, the number of countries moving towards efficient land use doubled compared to 2006–2012. Great progress towards achieving SDG 11.3.1 was seen in Portugal and Germany, and almost all Balkan countries are moving towards more efficient land use.

Fine-scale population spatialization data of China in 2018 based on real location-based big data

Accurate location-based big data has a high resolution and a direct interaction with human activities, allowing for fine-scale population spatial data to be realized. We take the average of Tencent user location big data as a measure of ambient population. The county-level statistical population data in 2018 was used as the assigned input data. The log linear spatially weighted regression model was used to establish the relationship between location data and statistical data to allocate the latter to a 0.01° grid, and the ambient population data of mainland China was obtained. Extracting street-level (lower than county-level) statistics for accuracy testing, we found that POP2018 has the best fit with the actual permanent population (R2 = 0.91), and the error is the smallest (MSEPOP2018 = 22.48 <MSEWorldPop = 37.24 <MSELandScan = 100.91). This research supplemented in the refined spatial distribution data of people between census years, as well as presenting the application technique of big data in ambient population estimation and zoning mapping.

A diversity index to measure underrepresented minority enrollment in United States colleges and schools of pharmacy

IntroductionWith an underrepresented minority (URM) student population of <20%, colleges and schools of pharmacy (CoPs) in the United States (US) lag behind the national population, in which URMs account for >30%. Few tools are available to assist the >140 US CoPs in tracking progress in URM diversity among student pharmacists. Thus, the study's purpose was to address this gap by: (1) creating a “diversity index” for pharmacy programs; and (2) determining changes in diversity index scores between 2011 and 2020. MethodsThis was a secondary analysis of 2011–2020 fall URM enrollment data for CoPs and national and state population data. The annual diversity index score for 2011–2020 was calculated for each CoP. Wilcoxon signed-rank tests and Mann-Whitney U tests were conducted. ResultsAmong all CoPs, median URM percent enrollment significantly increased from 7.7% in 2011 to 14.5% in 2020. Median diversity index scores for all CoPs increased from 0.66 in 2011 to 0.76 in 2020, but this change was not statistically significant. Historically Black Colleges and Universities (HBCUs) and Hispanic-Serving Institutions (HSIs) had significantly greater diversity index scores than non-HBCUs/HSIs. Diversity index scores of public vs. private colleges did not differ significantly. ConclusionThis diversity index represents an important step in tracking progress in increasing URM student pharmacist representation in CoPs. The index may be utilized as a tool to support development of diversity best practices and more inclusive environments for student pharmacists, faculty, staff, and stakeholders.

Alcohol-Attributable Deaths Help Drive Growing Socioeconomic Inequalities In US Life Expectancy, 2000-18.

Socioeconomic gaps in life expectancy have widened substantially in the United States since 2000. Yet the contribution of specific causes to these growing disparities remains unknown. We used death records from the National Vital Statistics System and population data from Current Population Surveys to quantify the contribution of alcohol-attributable causes of death to changes in US life expectancy between 2000 and 2018 by sex and socioeconomic status (as measured by educational attainment). During the study period, the gap in life expectancy between people with low (high school diploma or less) compared with high (college degree) levels of education increased by three years among men and five years among women. Between 2000 and 2010 declines in cardiovascular disease mortality among people with high education made major contributions to growing inequalities. In contrast, between 2010 and 2018 deaths from a cause with an alcohol-attributable fraction of 20percent or more were a dominant driver of socioeconomic divergence. Increased efforts to implement cost-effective alcohol control policies will be essential for reducing health disparities.

Monitoring the Distribution and Variations of City Size Based on Night-Time Light Remote Sensing: A Case Study in the Yangtze River Delta of China

Effectively monitoring the size of a city in real time enables the scientific planning of urban development. Models that utilize the distribution and variations in city size generally use population data as inputs, which cannot be obtained in a timely and rapid manner. However, night-time light (NTL) remote sensing may be an alternative method. A case study was carried out on the Yangtze River Delta (YRD) in China, and the rank–size rule, the law of primate cities, and the Gini coefficient were employed to monitor the variation in city size in the study area. The urban areas extracted based on NTL remote sensing were utilized instead of the traditionally used population data to evaluate the variations in city size from 2012 to 2017. Considering the empiricism and subjectivity of the thresholding method, urban areas were extracted from NTL data combined with the normalized differential vegetation index and land-surface temperature data based on the artificial neural network algorithm. Based on the results, the YRD did not fit the distribution of the primate cities from 2012 to 2017. However, this region satisfied the rank–size rule well, which indicated that the development of medium–small cities was more prominent than that of larger cities, and the dispersed force was larger than the concentrated force. Notably, the city size reached a relatively balanced level in the study area. Further, sensitivity analysis revealed that the relatively low extraction accuracy of urban areas of few small cities had little effect on the results of city size variations. Moreover, the validation of city size computed from statistical population data and its comparison with results calculated based on the statistical data of urban areas aligned with the results of this study, which indicates the rationality and applicability of monitoring the variations in city size using the urban areas extracted from NTL remote sensing instead of population data.

Spatial and Temporal Changes of Urban Built-Up Area in the Yellow River Basin from Nighttime Light Data

Nighttime light (NTL) images obtained by the Visible Infrared Imaging Radiometer (VIIRS) mounted on the National Polar-orbiting Partnership (NPP) could objectively represent human activities and instantly identify urban shapes on a temporal and spatial scale. From 2013 to 2020, the built-up areas of eight provincial capital cities were extracted using NPP/VIIRS NTL data to examine the dynamic changes in city expansion and socioeconomic development in the Yellow River Basin during the urbanization process. The spatial characteristics of urban built-up area expansion were generated using the eight-quadrant analysis method and combined with the statistical data of population and (gross domestic product) GDP to analyze the correlations between the light intensity of built-up areas, population and GDP; this enables an understanding of the changes in population and economy in the development of urban built-up area expansion. The findings show that: (1) unbalanced city development existed in the Yellow River Basin’s upper, middle, and lower reaches, and the expansion and light intensity of cities in the upper reaches were slower than those in the middle and lower reaches; (2) the spatial differentiation of urban expansion was significant between each of the reaches in the Yellow River Basin, and greatly influenced by natural geographical elements; and (3) positive correlation exists between light intensity, population, and GDP in the built-up areas of the middle and lower reaches, while the correlations in the upper reaches were not stable. In conclusion, light data indirectly reflects urban development and could be used as a substitute variable for socioeconomic development indicators under certain conditions.