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The twenty-first century has been a period of rising inequality in both income and health. In this paper, we find that geographic inequality in mortality for midlife Americans increased by about 70 percent between 1992 and 2016. This was not simply because states like New York or California benefited from having a high fraction of college-educated residents who enjoyed the largest health gains during the last several decades. Nor was higher dispersion in mortality caused entirely by the increasing importance of \"deaths of despair,\" or by rising spatial income inequality during the same period. Instead, over time, state-level mortality has become increasingly correlated with state-level income; in 1992, income explained only 3 percent of mortality inequality, but by 2016, state-level income explained 58 percent. These mortality patterns are consistent with the view that high-income states in 1992 were better able to enact public health strategies and adopt behaviors that, over the next quarter-century, resulted in pronounced relative declines in mortality. The substantial longevity gains in high-income states led to greater cross-state inequality in mortality.

Geographic inequities are known to affect access to liver transplant (LT); however, the impact of these disparities postoperatively remains unknown. We focus on primary care physicians (PCPs), as frequent managers of long-term LT recipient care. Clinical data on adults undergoing liver-only transplant 2010–2021 were obtained from the Organ Procurement and Transplantation Network and linked to zip code-based PCP density and social vulnerability index (SVI) data to quantify the impact of PCP density on graft and overall survival. 64,593 patients were divided into quintiles by PCP density. Compared to patients in the lowest PCP quintile, patients in the 3rd, 4th, and 5th quintiles had 6%–8% lower mortality risk (HR3rd ​= ​0.94, HR4th ​= ​0.92, HR5th ​= ​0.94, p for trend ​= ​0.002). PCP density remained significant after accounting for SVI and local surgeon and gastroenterologist availability (p ​= ​0.002). Increased PCP availability is associated with improved survival, emphasizing the importance of establishing longitudinal care. •Liver transplant recipients often transition long-term care to primary care doctors.•Geographic disparities persist in both transplant and primary care access.•Decreased primary care access alone is significantly associated with worse survival.•Establishing longitudinal care in low-primary care areas may improve OS.

Life expectancy varies substantially across local regions within a country, raising conjectures that place of residence affects health. However, population sorting and other confounders make it difficult to disentangle the effects of place on health from other geographic differences in life expectancy. Recent studies have overcome such challenges to demonstrate that place of residence substantially influences health and mortality. Whether policies that encourage people to move to places that are better for their health or that improve areas that are detrimental to health are desirable depends on the mechanisms behind place effects, yet these mechanisms remain poorly understood.

Background China’s family planning policies have experienced stages of one-child policy, partial two-child policy, and universal two-child policy. However, the impact of these policy shifts on the spatial accessibility to maternal and child health (MCH) services for women and children remains uncertain. This study aimed to evaluate the spatiotemporal trends and geographic disparities in spatial accessibility to MCH services in the context of two-child polices. Methods This study was conducted in Nanning prefecture, China, from 2013 to 2019. Data on the transportation networks, MCH institutes, the annual number of newborns, and the annual number of pregnant women in Nanning prefecture were collected. Gaussian two-step floating catchment area (Ga2SFCA) method was employed to measure the spatial accessibility to MCH services at county, township, and village levels. Temporal trends in spatial accessibility were analyzed using Joinpoint regression analysis. Geographic disparities in spatial accessibility were identified using geographic information system (GIS) mapping techniques. Results Overall, the spatial accessibility to MCH services showed an upward trend from 2013 to 2019 at county, town, and village levels, with the average annual percent change (AAPC) being 5.04, 4.73, and 5.39, respectively. Specifically, the spatial accessibility experienced a slight downward trend during the period of partial two-child policy for both parents only children (i.e., 2013–2014), a slight upward trend during the period of partial two-child policy for either parent only child (i.e., 2014–2016) and the early stages of universal two-child policy (i.e., 2016–2018), and a large upward trend in the later stages of universal two-child policy (i.e., 2018–2019). Spatial accessibility to MCH services gradually decreased from central urban areas to surrounding rural areas. Regions with low spatial accessibility were predominantly located in remote rural areas. Conclusion With the gradual opening of the two-child policies, the spatial accessibility to MCH services for women and children has generally improved. However, significant geographic disparities have persisted throughout the stages of the two-child policies. Comprehensive measures should be considered to improve equity in MCH services for women and children.

A rich literature shows that early-life conditions shape later-life outcomes, including health and migration events. However, analyses of geographic disparities in mortality outcomes focus almost exclusively on contemporaneously measured geographic place (e.g , state of residence at death), thereby potentially conflating the role of early-life conditions, migration patterns, and effects of destinations. We employ the newly available Mortality Disparities in American Communities data set, which links respondents in the 2008 American Community Survey to official death records, and estimate consequential differences based on the method of aggregation we use: the unweighted mean absolute deviation of the difference in life expectancy at age 50 measured by state of birth versus state of residence is 0.58 years for men and 0.40 years for women. These differences are also spatially clustered, and we show that regional inequality in life expectancy is based on life expectancies by state of birth, implying that interstate migration baseline geographic inequality in mortality outcomes. Finally, we assess how state-specific features of in-migration, out-migration, and nonmigration together shape measures of mortality disparities by state (of residence), further demonstrating the difficulty of clearly interpreting these widely used measures.

Background COVID-19 is an important public health concern due to its high morbidity, mortality and socioeconomic impact. Its burden varies by geographic location affecting some communities more than others. Identifying these disparities is important for guiding health planning and service provision. Therefore, this study investigated geographical disparities and temporal changes of the percentage of positive COVID-19 tests and COVID-19 incidence risk in North Dakota. Methods COVID-19 retrospective data on total number of tests and confirmed cases reported in North Dakota from March 2020 to September 2021 were obtained from the North Dakota COVID-19 Dashboard and Department of Health, respectively. Monthly incidence risks of the disease were calculated and reported as number of cases per 100,000 persons. To adjust for geographic autocorrelation and the small number problem, Spatial Empirical Bayesian (SEB) smoothing was performed using queen spatial weights. Identification of high-risk geographic clusters of percentages of positive tests and COVID-19 incidence risks were accomplished using Tango’s flexible spatial scan statistic. ArcGIS was used to display and visiualize the geographic distribution of percentages of positive tests, COVID-19 incidence risks, and high-risk clusters. Results County-level percentages of positive tests and SEB incidence risks varied by geographic location ranging from 0.11% to 13.67% and 122 to 16,443 cases per 100,000 persons, respectively. Clusters of high percentages of positive tests were consistently detected in the western part of the state. High incidence risks were identified in the central and south-western parts of the state, where significant high-risk spatial clusters were reported. Additionally, two peaks (August 2020-December 2020 and August 2021-September 2021) and two non-peak periods of COVID-19 incidence risk (March 2020-July 2020 and January 2021-July 2021) were observed. Conclusion Geographic disparities in COVID incidence risks exist in North Dakota with high-risk clusters being identified in the rural central and southwest parts of the state. These findings are useful for guiding intervention strategies by identifying high risk communities so that resources for disease control can be better allocated to communities in need based on empirical evidence. Future studies will investigate predictors of the identified disparities so as to guide planning, disease control and health policy.

Background Denmark, Finland and Sweden pursue equity in health for their citizens through universal health care. However, it is unclear if these services reach the older adult population equally across different socioeconomic positions or living areas. Thus, we assessed geographic and socioeconomic equity in primary health care (PHC) performance among the older adults in the capital areas of Denmark (Copenhagen), Finland (Helsinki) and Sweden (Stockholm) in 2000–2015. Hospitalisations for ambulatory care sensitive conditions (ACSC) were applied as a proxy for PHC performance. Methods We acquired individual level ACSCs for those aged ≥ 45 in 2000–2015 from national hospitalisation registers. To identify whether the disparities varied by age, we applied three age groups (those aged 45–64, 65–75 and ≥ 75). Socioeconomic disparities in ACSCs were described with incidence rate ratios (IRR) and annual rates by education, income and living-alone; and then analysed with biennial concentration indices by income. Geographic disparities were described with biennial ACSC rates by small areas and analysed with two-level Poisson multilevel models. These models provided small area estimates of IRRs of ACSCs in 2000 and their slopes for development over time, between which Pearson correlations were calculated within each capital area. Finally, these models were adjusted for income to distinguish between geographic and socioeconomic disparities. Results Copenhagen had the highest IRR of ACSCs among those aged 45–64, and Helsinki among those aged ≥ 75. Over time IRRs decreased among those aged ≥ 45, but only in Helsinki among those aged ≥ 75. All concentration indices slightly favoured the affluent population but in Stockholm were mainly non-significant. Among those aged ≥ 75, Pearson correlations were low in Copenhagen (-0.14; p  = 0.424) but high in both Helsinki (-0.74; < 0.001) and Stockholm (-0.62; < 0.001) – with only little change when adjusted for income. Among those aged ≥ 45 the respective correlations were rather similar, except for a strong correlation in Copenhagen (-0.51, 0.001) after income adjustment. Conclusions While socioeconomic disparities in PHC performance persisted among older adults in the three Nordic capital areas, geographic disparities narrowed in both Helsinki and Stockholm but persisted in Copenhagen. Our findings suggest that the Danish PHC incorporated the negative effects of socio-economic segregation to a lesser degree.

Race and ethnicity, socioeconomic class, and geographic location are well-known social determinants of health in the US. Studies of population mortality often consider two, but not all three of these risk factors. To disarticulate the associations of race (whiteness), class (socioeconomic status), and place (county) with risk of cause-specific death in the US. We conducted a retrospective analysis of death certificate data. Bayesian regression models, adjusted for age and race/ethnicity from the American Community Survey and the county Area Deprivation Index, were used for inference. County-level mortality for 11 leading causes of death (1999-2019) and COVID-19 (2020-2021). County \"whiteness\" and socioeconomic status modified death rates; geospatial effects differed by cause of death. Other factors equal, a 20% increase in county whiteness was associated with 5-8% increase in death from three causes and 4-15% reduction in death from others, including COVID-19. Other factors equal, advantaged counties had significantly lower death rates, even when juxtaposed with disadvantaged ones. Patterns of residual risk, measured by spatial county effects, varied by cause of death; for example: cancer and heart disease death rates were better explained by age, socioeconomic status, and county whiteness than were COVID-19 and suicide deaths. There are important independent contributions from race, class, and geography to risk of death in the US.

This study examined the impact of geographic distance on survival outcomes for patients receiving treatment for ovarian cancer at the only NCI-designated cancer center (NCI-CC) in Kansas. We identified ovarian cancer patients treated at the University of Kansas Cancer Center between 2010 and 2015. Demographic factors and clinical characteristics were abstracted. The main outcome measure was overall survival according to geographic distance from the institution. Kaplan Meier survival curves and Cox proportional hazard models were generated using SAS v9.4. 220 patients were identified. Survival analysis based on distance from the institution demonstrated that patients who lived ≤10 miles from the institution had worse overall survival (p = 0.0207) and were more likely to have suboptimal cytoreductive surgery (p = 0.0276). Lower estimated median income was also associated with a 1.54 increased risk of death, 95% CI (1.031–2.292), p = 0.0347. We determined that ovarian cancer survival disparities exist in our patient population. Lower rates of optimal cytoreductive surgery has been identified as a possible driver of poor prognosis for patients who lived in proximity to our institution. •Geographic distance of less than 10 miles to NCI-CC is associated with worse ovarian cancer survival.•Lower estimated median income is associated with worse ovarian cancer survival.•Geographic distance of less than 10 miles to NCI-CC is associated with lower rates of optimal cytoreduction.

Although pigs are naturally susceptible to Reston virus and experimentally to Ebola virus (EBOV), their role in Orthoebolavirus ecology remains unknown. We tested 888 serum samples collected from pigs in Guinea during 2017-2019 (between the 2013-16 epidemic and its resurgence in 2021) by indirect ELISA against the EBOV nucleoprotein. We identified 2 hotspots of possible pig exposure by IgG titer levels: the northern coast had 48.7% of positive serum samples (37/76), and Forest Guinea, bordering Sierra Leone and Liberia, where the virus emerged and reemerged, had 50% of positive serum samples (98/196). The multitarget Luminex approach confirms ELISA results against Ebola nucleoprotein and highlights cross-reactivities to glycoprotein of EBOV, Reston virus, and Bundibugyo virus. Those results are consistent with previous observations of the circulation of Orthoebolavirus species in pig farming regions in Sierra Leone and Ghana, suggesting potential risk for Ebola virus disease in humans, especially in Forest Guinea.