Regional variation and temporal trends in transcatheter and surgical aortic valve replacement in Switzerland: A population-based small area analysis.

BACKGROUND: Aortic valve stenosis (AS) is the most common valvular heart disease and if severe, is treated with either transcatheter (TAVR) or surgical aortic valve replacement (SAVR). We assessed temporal trends and regional variation of these interventions in Switzerland and examined potential determinants of geographic variation. METHODS: We conducted a population-based analysis using patient discharge data from all Swiss public and private acute care hospitals from 2013 to 2018. We generated hospital service areas (HSAs) based on patient flows for TAVR. We calculated age-standardized mean procedure rates and variation indices (extremal quotient [EQ] and systematic component of variation [SCV]). Using multilevel regression, we calculated the influence of calendar year and regional demographics, socioeconomic factors (language, insurance status), burden of disease, and number of cardiologists/cardiovascular surgeons on geographic variation. RESULTS: Overall, 8074 TAVR and 11,825 SAVR procedures were performed in 8 HSAs from 2013 to 2018. Whereas the age-/sex-standardized rate of TAVR increased from 12 to 22 procedures/100,000 persons, the SAVR rate decreased from 33 to 24 procedures during this period. After full adjustment, the predicted TAVR and SAVR rates varied from 12 to 22 and 20 to 35 per 100,000 persons across HSAs, respectively. The regional procedure variation was low to moderate over time, with a low overall variation in TAVR (EQ 1.9, SCV 3.9) and SAVR (EQ 1.6, SCV 2.2). In multilevel regression, TAVR rates increased annually by 10% and SAVR rates decreased by 5%. Determinants of higher TAVR rates were older age, male sex, living in a German speaking area, and higher burden of disease. A higher proportion of (semi)private insurance was also associated with higher TAVR and lower SAVR rates. After full adjustment, 10.6% of the variance in TAVR and 18.4% of the variance in SAVR remained unexplained. Most variance in TAVR and SAVR rates was explained by language region and insurance status. CONCLUSION: The geographic variation in TAVR and SAVR rates was low to moderate across Swiss regions and largely explained by differences in regional demographics and socioeconomic factors. The use of TAVR increased at the expense of SAVR over time.

Large regional variation in cardiac closure procedures to prevent ischemic stroke in Switzerland a population-based small area analysis.

BACKGROUND: Percutaneous closure of a patent foramen ovale (PFO) or the left atrial appendage (LAA) are controversial procedures to prevent stroke but often used in clinical practice. We assessed the regional variation of these interventions and explored potential determinants of such a variation. METHODS: We conducted a population-based analysis using patient discharge data from all Swiss hospitals from 2013-2018. We derived hospital service areas (HSAs) using patient flows for PFO and LAA closure. We calculated age-standardized mean procedure rates and variation indices (extremal quotient [EQ] and systematic component of variation [SCV]). SCV values >5.4 indicate a high and >10 a very high variation. Because the evidence on the efficacy of PFO closure may differ in patients aged <60 years and ≥60 years, age-stratified analyses were performed. We assessed the influence of potential determinants of variation using multilevel regression models with incremental adjustment for demographics, cultural/socioeconomic, health, and supply factors. RESULTS: Overall, 2574 PFO and 2081 LAA closures from 10 HSAs were analyzed. The fully adjusted PFO and LAA closure rates varied from 3 to 8 and from 1 to 9 procedures per 100,000 persons per year across HSAs, respectively. The regional variation was high with respect to overall PFO closures (EQ 3.0, SCV 8.3) and very high in patients aged ≥60 years (EQ 4.0, SCV 12.3). The variation in LAA closures was very high (EQ 16.2, SCV 32.1). In multivariate analysis, women had a 28% lower PFO and a 59% lower LAA closure rate than men. French/Italian language areas had a 63% lower LAA closure rate than Swiss German speaking regions and areas with a higher proportion of privately insured patients had a 86% higher LAA closure rate. After full adjustment, 44.2% of the variance in PFO closure and 30.3% in LAA closure remained unexplained. CONCLUSIONS: We found a high to very high regional variation in PFO closure and LAA closure rates within Switzerland. Several factors, including sex, language area, and insurance status, were associated with procedure rates. Overall, 30-45% of the regional procedure variation remained unexplained and most probably represents differing physician practices.

Understanding Factors Influencing Geographic Variation in Healthcare Expenditures: A Small Areas Analysis Study.

Dramatic geographic variations in healthcare expenditures were documented by developed countries, but little is known about such variations under China's context, and what causes such variations. This study aims to examine variations of healthcare expenditures among small areas and to determine the associations between demand-, supply-factors, and per capita inpatient expenditures. This cross-sectional study utilized hospital discharge data aggregated within delineated hospital service areas (HSAs) using the small-area analysis approach. Linear multivariate regression modeling with robust standard errors was used to estimate the sources of variation of per capita inpatient expenditures across HSAs covering the years 2017 to 2019; the Shapley value decomposition method was used to measure the respective contributions of demand-, supply-side to such variations. Among 149 HSAs, demand factors explained most of the (87.4%) overall geographic variation among HSAs. With each 1% increase in GDP per capita and urbanization rate was associated with 0.099% and 0.9% increase in inpatient expenditure per capita, respectively, while each 1% increase in the share of females and the unemployment rate was associated with a 0.7% and 0.4% reduction in the per capita inpatient expenditures, respectively. In supply-side, for every 1 increase in hospital beds per 1000 population, the per capita inpatient expenditures rose by 2.9%, while with every 1% increase in the share of private hospitals, the per capita inpatient expenditures would decrease by 0.4%. With Herfindahl-Hirschman Index decrease 10%, the per capita inpatient expenditures would increase 1.06%. This study suggests demand-side factors are associated with large geographic variation in per capita inpatient expenditures among HSAs, while supply-side factors played an important role. The evaluation of geographic variations in per capita inpatient expenditures as well as its associated factors have great potential to provide an indirect approach to identify possibly existing underutilized or overutilized healthcare procedures.

Emergency Department Syndromic Surveillance to Monitor Tick-Borne Diseases: A 6-Year Small-Area Analysis in Northeastern Italy.

Tick-borne diseases (TBD) are endemic in Europe. However, surveillance is currently incomplete. Alternative strategies need to be considered. The aim of this study was to test an Emergency Department Syndromic Surveillance (EDSyS) system as a complementary data source to describe the impact of tick bites and TBD using a small-area analysis approach and to monitor the risk of TBD to target prevention. ED databases in the Local Health Authority 8 District (Veneto, Italy) were queried for tick-bite and TBD-related visits between January 2017 and December 2022. Hospitalisations were also collected. Events involving the resident population were used to calculate incidence rates. A total of 4187 ED visits for tick-bite and 143 for TBD were recorded; in addition, 62 TBD-related hospitalisations (of which 72.6% in over 50 s and 22.6% in over 65 s). ED visits peaked in spring and in autumn, followed by a 4-week lag in the increase in hospital admissions. The small-area analysis identified two areas at higher risk of bites and TBD. The use of a EDSyS system allowed two natural foci to be identified. This approach proved useful in predicting temporal and geographic risk of TBD and in identifying local endemic areas, thus enabling an effective multidisciplinary prevention strategy.

Effect Modifications of Overhead-View and Eye-Level Urban Greenery on Heat-Mortality Associations: Small-Area Analyses Using Case Time Series Design and Different Greenery Measurements.

BACKGROUND: The protective effect of urban greenery from adverse heat impacts remains inconclusive. Existing inconsistent findings could be attributed to the different estimation techniques used. OBJECTIVES: We investigated how effect modifications of urban greenery on heat-mortality associations vary when using different greenery measurements reflecting overhead-view and eye-level urban greenery. METHODS: We collected meteorological and daily mortality data for 286 territory planning units between 2005 and 2018 in Hong Kong. Three greenery measurements were extracted for each unit: a) the normalized difference vegetation index (NDVI) from Landsat remote sensing images, b) the percentage of greenspace based on land use data, and c) eye-level street greenery from street view images via a deep learning technique. Time-series analyses were performed using the case time series design with a linear interaction between the temperature term and each of the three greenery measurements. Effect modifications were also estimated for different age groups, sex categories, and cause-specific diseases. RESULTS: Higher mortality risks were associated with both moderate and extreme heat, with relative risks (RRs) of 1.022 (95% CI: 1.000, 1.044) and 1.045 (95% CI: 1.013, 1.079) at the 90th and 99th percentiles of temperatures relative to the minimum mortality temperature (MMT). Lower RRs were observed in greener areas whichever of the three greenery measurements was used, but the disparity of RRs between areas with low and high levels of urban greenery was more apparent when using eye-level street greenery as the index at high temperatures (99th percentile relative to MMT), with RRs for low and high levels of greenery, respectively, of 1.096 (95% CI: 1.035, 1.161) and 0.985 (95% CI: 0.920, 1.055) for NDVI (p=0.0193), 1.068 (95% CI: 1.021, 1.117) and 0.990 (95% CI: 0.906, 1.081) for the percentage of greenspace (p=0.1338), and 1.103 (95% CI: 1.034, 1.177) and 0.943 (95% CI: 0.841, 1.057) for eye-level street greenery (p=0.0186). Health discrepancies remained for nonaccidental mortality and cardiorespiratory diseases and were more apparent for older adults (≥65 years of age) and females. DISCUSSION: This study provides new evidence that eye-level street greenery shows stronger associations with reduced heat-mortality risks compared with overhead-view greenery based on NDVI and percentage of greenspace. The effect modification of urban greenery tends to be amplified as temperatures rise and are more apparent in older adults and females. Heat mitigation strategies and health interventions, in particular with regard to accessible and visible greenery, are needed for helping heat-sensitive subpopulation groups in coping with extreme heat. https://doi.org/10.1289/EHP12589.

Small area analysis methods in an area of limited mapping: exploratory geospatial analysis of firearm injuries in Port-au-Prince, Haiti.

BACKGROUND: The city of Port-au-Prince, Haiti, is experiencing an epidemic of firearm injuries which has resulted in high burdens of morbidity and mortality. Despite this, little scientific literature exists on the topic. Geospatial research could inform stakeholders and aid in the response to the current firearm injury epidemic. However, traditional small-area geospatial methods are difficult to implement in Port-au-Prince, as the area has limited mapping penetration. Objectives of this study were to evaluate the feasibility of geospatial analysis in Port-au-Prince, to seek to understand specific limitations to geospatial research in this context, and to explore the geospatial epidemiology of firearm injuries in patients presenting to the largest public hospital in Port-au-Prince. RESULTS: To overcome limited mapping penetration, multiple data sources were combined. Boundaries of informally developed neighborhoods were estimated from the crowd-sourced platform OpenStreetMap using Thiessen polygons. Population counts were obtained from previously published satellite-derived estimates and aggregated to the neighborhood level. Cases of firearm injuries presenting to the largest public hospital in Port-au-Prince from November 22nd, 2019, through December 31st, 2020, were geocoded and aggregated to the neighborhood level. Cluster analysis was performed using Global Moran's I testing, local Moran's I testing, and the SaTScan software. Results demonstrated significant geospatial autocorrelation in the risk of firearm injury within the city. Cluster analysis identified areas of the city with the highest burden of firearm injuries. CONCLUSIONS: By utilizing novel methodology in neighborhood estimation and combining multiple data sources, geospatial research was able to be conducted in Port-au-Prince. Geospatial clusters of firearm injuries were identified, and neighborhood level relative-risk estimates were obtained. While access to neighborhoods experiencing the largest burden of firearm injuries remains restricted, these geospatial methods could continue to inform stakeholder response to the growing burden of firearm injuries in Port-au-Prince.

Small-Area Analysis of Treatment and Clinical Outcomes in Patients with Venous Thromboembolism in Denmark: A Nationwide Cohort Study.

OBJECTIVES: To investigate geographical variation in initiation and extended treatment with anticoagulants and clinical outcomes among patients hospitalized with first-time venous thromboembolism (VTE) in Denmark between 2007 and 2018. METHODS: Using nationwide health care registries, we identified all patients with a first-time VTE hospital diagnosis supported by imaging data from 2007 to 2018. Patients were grouped according to residential region (5) and municipality (98) at the time of VTE diagnosis. Cumulative incidence of initiation of and extended (beyond 365 days) anticoagulation treatment as well as clinical outcomes, including recurrent VTE, major bleeding, and all-cause death, were assessed. Sex- and age-adjusted relative risks (RRs) of the outcomes were computed when comparing across individual regions and municipalities. Overall geographic variation was quantified by computing the median RR. RESULTS: We identified 66,840 patients with a first-time VTE hospitalization. A difference in initiation of anticoagulation treatment of more than 20 percentage points between regions was observed (range: 51.9-72.4%, median RR: 1.09, 95% confidence interval [CI]: 1.04-1.13). Variation was also observed for extended treatment (range: 34.2-46.9%, median RR: 1.08, 95% CI: 1.02-1.14). The cumulative incidence of recurrent VTE ranged from 3.6 to 5.3% at 1 year (median RR: 1.08, 95% CI: 1.01-1.15). The difference remained after 5 years, and variation was also observed for major bleeding (median RR: 1.09, 95% CI: 1.03-1.15), whereas it appeared smaller for all-cause mortality (median RR: 1.03, 95% CI: 1.01-1.05). CONCLUSION: Substantial geographical variation in anticoagulation treatment and clinical outcomes occurs in Denmark. These findings indicate a need for initiatives to ensure uniform high-quality care for all VTE patients.

A comparison of small-area deprivation indicators for public-health surveillance in Sweden.

AIMS: The aims of this study were to construct a small-area index of multiple deprivation (IMD) from single deprivation indicators (SDIs) and to compare the explanatory power of the IMD and SDIs with regard to mortality. We considered a small-area division of Sweden consisting of 5985 DeSO (Demografiska statistikområden), each with a population size between 653 and 4243 at the end of 2018. METHODS: Four SDIs were provided by open-source data: (a) the proportion of inhabitants with a low economic standard; (b) the proportion of inhabitants aged 25-64 years with ⩽12 years of schooling; (c) the proportion of inhabitants aged 16-64 years who were not in paid employment; and (d) the proportion of inhabitants who lived in a rented apartment/house. A four-indicator IMD was constructed using factor analysis. As a validation, the IMD and SDIs were compared by exploring their DeSO-level associations with spatially smoothed death rates, with robustness checks of associations across different small-area contexts defined by degree of urbanisation and distribution of immigrants from non-Western countries. RESULTS: The constructed IMD and SDI1 performed essentially equally and outperformed SDI2, SDI3 and SDI4. Associations between IMD/SDI1 and the spatially smoothed death rates were most pronounced within the age range 60-79 years, showing 5-8% lowered rates among those categorised in the least deprived quintiles of IMD and SDI1, respectively, and 7-9% elevated rates among those categorised in the most deprived quintiles. These associations were consistent within each small-area context. CONCLUSIONS: We suggest prioritisation of SDI1, that is, a DeSO-level deprivation indicator based on open-access data on economic standard, for public-health surveillance in Sweden.

Small Area Variation in the Quality of Maternal and Newborn Care in India.

Importance: In India, the district serves as the primary policy unit for implementing and allocating resources for various programs aimed at improving key developmental and health indicators. Recent evidence highlights that high-quality care for mothers and newborns is critical to reduce preventable mortality. However, the geographic variation in maternal and newborn health service quality has never been investigated. Objective: To examine the variation between smaller areas within districts in the quality of maternal and newborn care in India. Design, Setting, and Participants: This cross-sectional study assessed data from women aged 15 to 49 years on the most recent birth (singleton or multiples) in the 5 years that preceded the fifth National Family Health Survey (June 17, 2019, to April 30, 2021). Exposures: Maternal and newborn care in 36 states and union territories (UTs), 707 districts, and 28 113 clusters (small areas) in India. Main Outcomes and Measures: The composite quality score of maternal and newborn care was defined as the proportion of components of care received of the total 11 essential components of antenatal and postnatal care. Four-level logistic and linear regression was used for analyses of individual components of care and composite score, respectively. Precision-weighted prevalence of each component of care and mean composite score across districts as well as their between-small area SD were calculated. Results: The final analytic sample for the composite score was composed of 123 257 births nested in 28 113 small areas, 707 districts, and 36 states/UTs. For the composite score, 58.3% of the total geographic variance was attributable to small areas, 29.3% to states and UTs, and 12.4% to districts. Of 11 individual components of care, the small areas accounted for the largest proportion of geographic variation for 6 individual components of care (ranging from 42.3% for blood pressure taken to 73.0% for tetanus injection), and the state/UT was the largest contributor for 4 components of care (ranging from 41.7% for being weighed to 52.3% for ultrasound test taken). District-level composite score and prevalence of individual care components and their variation across small areas within the districts showed a consistently strong negative correlation (Spearman rank correlation ρ = -0.981 to -0.886). Low-quality scores and large between-small area disparities were not necessarily concentrated in aspirational districts (mean district composite score [SD within districts], 92.7% [2.1%] among aspirational districts and 93.7% [1.8%] among nonaspirational districts). Conclusions and Relevance: The findings of this cross-sectional study suggest that the policy around maternal and child health care needs to be designed more precisely to consider district mean and between-small area heterogeneity in India. This study may have implications for other low- and middle-income countries seeking to improve maternal and newborn outcomes, particularly for large countries with geographic heterogeneity.

Neighbourhood income inequalities in mental health in Barcelona 2001-2016: a Bayesian smoothed estimate / Desigualdades de renta por barrios en salud mental en Barcelona 2001-2016: una estimación de alisado bayesiano

Objective: Obtaining reliable health estimates at the small area level (such as neighbourhoods) using survey data usually poses the problem of small sample sizes. To overcome this limitation, we explored smoothing techniques in order to estimate poor mental health prevalence at the neighbourhood level and analyse its profile by income in Barcelona city (Spain). Method: A Bayesian smoothing model with a logit-normal transformation was applied to four repeated cross-sectional waves of the Barcelona health survey for 2001, 2006, 2011 and 2016. Mental health status was identified from the 12-item General Health Questionnaire. Income inequalities were analysed with neighbourhood income in quantiles for each year and trends in the pooled analysis. Results: The prevalence of poor mental health ranged from 14.6% in 2001 to 18.9% in 2016. The yearly difference between neighbourhoods was 12.4% in 2001, 16.7% in 2006, 14.2% in 2011, and 20.0% in 2016. The odds ratio and 95% credible interval (95%CI) of experiencing poor mental health was 1.40 times higher (95%CI: 1.02-1.91) in less advantaged neighbourhoods than in more advantaged neighbourhoods in 2001, 1.61 times higher (95%CI: 1.01-2.59) in 2006 and 2.31 times higher (95%CI: 1.57-3.40) in 2016. Conclusions: This study shows that the Bayesian smoothed techniques allows detection of inequalities in health in neighbourhoods and monitoring of interventions against them. In Barcelona, mental health problems are more prevalent in low-income neighbourhoods and raised in 2016. (AU)

Objetivo: Obtener estimadores de salud en áreas pequeñas (como los barrios) utilizando datos de encuestas supone hacer frente al problema de insuficiente tamaño muestral. Para superar esta limitación exploramos técnicas de alisado con el fin de estimar la prevalencia de mala salud mental a nivel de barrio y analizar su patrón por renta en la ciudad de Barcelona (España). Método: Se aplicó un modelo de alisado bayesiano con transformación logística-normal a cuatro muestras transversales repetidas de la Encuesta de Salud de Barcelona para los años 2001, 2006, 2011 y 2016. La salud mental fue identificada con el Cuestionario General de Salud de 12-items. Las desigualdades de ingreso se analizaron por cuantiles de la renta por barrio para cada año y las tendencias en el análisis conjunto. Resultados: La prevalencia de mala salud mental oscila entre el 14,6% en 2001 y el 18,9% en 2016. La diferencia entre barrios fue del 12,4% en 2001, del 16,7% en 2006, del 14,2% en 2011 y del 20,0% en 2016. La odds ratio y el intervalo creíble al 95% (IC95%) de experimentar mala salud mental fue 1,4 veces superior (IC95%: 1,02-1,91) en los barrios menos aventajados respecto de los más aventajados en 2001, de 1,61 (IC95%: 1,01-2,59) en 2006 y de 2,31 (IC95%: 1,57-3,40) en 2016. Conclusiones: Este estudio muestra que las técnicas de alisado bayesiano permiten la detección de desigualdades en salud a nivel de barrios para su monitorización e intervención con el fin de reducirlas. En Barcelona, los problemas de salud mental son más prevalentes en los barrios de menor renta y se incrementaron en 2016. (AU)

Small area variation in severe, moderate, and mild anemia among women and children: A multilevel analysis of 707 districts in India.

India is home to the highest global number of women and children suffering from anemia, with one in every two women impacted. India's current strategy for targeting areas with a high anemia burden is based on district-level averages, yet this fails to capture the substantial small area variation in micro-geographical (small area) units such as villages. We conducted statistical and econometric analyses to quantify the extent of small area variation in the three grades of anemia (severe, moderate, and mild) among women and children across 36 states/union territories and 707 districts of India. We utilized data from the fifth round of the National Family Health Survey conducted in 2019-21. The final analytic sample for analyses was 183,883 children aged 6-59 months and 690,153 women aged 15-49 years. The primary outcome variable for the analysis was the three anemia grades among women and children. We adopted a three-level and four-level logistic regression model to compute variance partitioning of anemia among women and children. We also computed precision-weighted prevalence estimates of women and childhood anemia across 707 districts and within-district, between-cluster variation using standard deviation (SD). For severe anemia among women, small area (villages or urban blocks) account for highest share (46.1%; Var: 0.494; SE: 0.150) in total variation followed by states (39.4%; Var: 0.422; SE: 0.134) and districts (12.8%; Var: 0.156; SE: 0.012). Similarly, clusters account for the highest share in the variation in severe (61.3%; Var: 0.899; SE: 0.069) and moderate (46.4%: Var: 0.398; SE: 0.011) anemia among children. For mild and moderate anemia among women, however, states were the highest source of variation. Additionally, we found a high and positive correlation between mean prevalence and inter-cluster SD of moderate and severe anemia among women and children. In contrast, the correlation was weaker for mild anemia among women (r = 0.61) and children (0.66). In this analysis, we are positing the critical importance of small area variation within districts when designing strategies for targeting high burden areas for anemia interventions.

Geographical disparities in obesity prevalence: small-area analysis of the Chilean National Health Surveys.

BACKGROUND: Previous representative health surveys conducted in Chile evidenced a high obesity prevalence rate among adults, especially in female and urban areas. Nevertheless, these have limited utility for targeted interventions and local source allocation for prevention. This study analyzes the increments in obesity prevalence rates in populations ≥15 years of age and the geographic variation at the regional level. We also assessed whether the obesity rates have different patterns on a smaller geographic level than national and regional ones. METHODS: This ecological study analyzed data from two representative national samples of adolescents and adults ≥15 years old, who participated in the last Chilean health surveys, 2009 (n = 5412) and 2016 (n = 6233). Obesity (body mass index≥30 kg/m2) rates were calculated on the national, regional, and Health service (HS) levels, being HS the smallest unit of analysis available. Obesity rates and relative increase to early identify target populations and geographic areas, with 95% confidence intervals (95% CI), were calculated using the sampling design of the national surveys, at the national and regional level, and by gender, age groups, and socioeconomic status. The Fay-Herriot (FH) models, using auxiliary data, were fitted for obesity rate estimates at the HS level. RESULTS: The relative increase in obesity rate was 37.1% (95%CI 23.3-52.9) at the national level, with a heterogeneous geographic distribution at the regional one. Southern regions had the highest obesity rates in both surveys (Aysén: 35.2, 95%CI 26.9-43.5 in 2009, 44.3 95%CI 37-51.7 in 2016), but higher increases were predominantly in the northern and central areas of the country (relative increase 91.1 95%CI 39.6-110.1 in Valparaiso and 81.6 95%CI 14.4-196.2 in Tarapacá). Obesity rates were higher in females, older age, and lower socioeconomic groups; nevertheless, relative increases were higher in the opposite ones. The FH estimates showed an obesity rates variation at the HS level, where higher rates tend to converge to specific HS areas of each region. CONCLUSION: Obesity rates and relative increase are diverse across subnational levels and substantially differ from the national estimates, highlighting a pattern that converges to areas with low-middle income households. Our results emphasize geographical disparities in obesity prevalence among adults and adolescents.

PriorVAE: encoding spatial priors with variational autoencoders for small-area estimation.

Gaussian processes (GPs), implemented through multivariate Gaussian distributions for a finite collection of data, are the most popular approach in small-area spatial statistical modelling. In this context, they are used to encode correlation structures over space and can generalize well in interpolation tasks. Despite their flexibility, off-the-shelf GPs present serious computational challenges which limit their scalability and practical usefulness in applied settings. Here, we propose a novel, deep generative modelling approach to tackle this challenge, termed PriorVAE: for a particular spatial setting, we approximate a class of GP priors through prior sampling and subsequent fitting of a variational autoencoder (VAE). Given a trained VAE, the resultant decoder allows spatial inference to become incredibly efficient due to the low dimensional, independently distributed latent Gaussian space representation of the VAE. Once trained, inference using the VAE decoder replaces the GP within a Bayesian sampling framework. This approach provides tractable and easy-to-implement means of approximately encoding spatial priors and facilitates efficient statistical inference. We demonstrate the utility of our VAE two-stage approach on Bayesian, small-area estimation tasks.

The geographical epidemiology of smoking-related premature mortality: A registry-based small-area analysis of the Czech death statistics.

OBJECTIVES: Smoking-related mortality varies over different social, environmental, and policy contexts. However, spatial patterns, examined at a small area level, have been seldom considered. Therefore, the study provides a detailed analysis of socio-spatial inequalities in premature mortality related to smoking in the contemporary Czech adult population. DESIGN, SETTINGS, AND METHODS: We conducted a population-based, cross-sectional study to investigate the spatial pattern of the age-adjusted smoking-related mortality across Czechia. The spatial inequalities, as measured at the municipality level, were investigated using geostatistical modeling techniques. The ecological regression of the local mortality risk on socioeconomic composition of municipalities was also conducted. The target population was defined as permanent adult residents of Czechia aged 25-64 years in the period of 2011-2015. RESULTS: Among both sexes, a significant spatial gradient in the South-East (lower relative risk) - North-West (higher relative risk) axis was detected. The local mortality risk was significantly related to the level of relative deprivation of the municipalities (a composite index comprised from unemployment rate and level of education): adjusted RR among males (for an increase by 1 SD): 1.21 [95% CI: 1.158-1.256], p < 0.001; adjusted RR among females (for an increase by 1 SD): 1.14 [95% CI: 1.090-1.186], p < 0.001. Mortality among males was approximately twice as high as opposed to females. Regarding the spatial inequalities of the phenomena, however, only rather minor sex-specific patterns were identified. Contrasted to males, mortality among females was unrelated to unemployment rates. CONCLUSIONS: Consistent spatial patterns of the premature mortality were identified. The mortality risk was significantly related to socioeconomic composition of the Czech municipalities. The higher the level of local deprivation, the higher the local mortality risk. The results of the study can be found beneficial for planning of both socially and spatially integrated public health policy.

A tutorial on the case time series design for small-area analysis.

BACKGROUND: The increased availability of data on health outcomes and risk factors collected at fine geographical resolution is one of the main reasons for the rising popularity of epidemiological analyses conducted at small-area level. However, this rich data setting poses important methodological issues related to modelling complexities and computational demands, as well as the linkage and harmonisation of data collected at different geographical levels. METHODS: This tutorial illustrated the extension of the case time series design, originally proposed for individual-level analyses on short-term associations with time-varying exposures, for applications using data aggregated over small geographical areas. The case time series design embeds the longitudinal structure of time series data within the self-matched framework of case-only methods, offering a flexible and highly adaptable analytical tool. The methodology is well suited for modelling complex temporal relationships, and it provides an efficient computational scheme for large datasets including longitudinal measurements collected at a fine geographical level. RESULTS: The application of the case time series for small-area analyses is demonstrated using a real-data case study to assess the mortality risks associated with high temperature in the summers of 2006 and 2013 in London, UK. The example makes use of information on individual deaths, temperature, and socio-economic characteristics collected at different geographical levels. The tutorial describes the various steps of the analysis, namely the definition of the case time series structure and the linkage of the data, as well as the estimation of the risk associations and the assessment of vulnerability differences. R code and data are made available to fully reproduce the results and the graphical descriptions. CONCLUSIONS: The extension of the case time series for small-area analysis offers a valuable analytical tool that combines modelling flexibility and computational efficiency. The increasing availability of data collected at fine geographical scales provides opportunities for its application to address a wide range of epidemiological questions.

Small area variations in low birth weight and small size of births in India.

The states and districts are the primary focal points for policy formulation and programme intervention in India. The within-districts variation of key health indicators is not well understood and consequently underemphasised. This study aims to partition geographic variation in low birthweight (LBW) and small birth size (SBS) in India and geovisualize the distribution of small area estimates. Applying a four-level logistic regression model to the latest round of the National Family Health Survey (2015-2016) covering 640 districts within 36 states and union territories of India, the variance partitioning coefficient and precision-weighted prevalence of LBW (<2.5 kg) and SBS (mother's self-report) were estimated. For each outcome, the spatial distribution by districts of mean prevalence and small area variation (as measured by standard deviation) and the correlation between them were computed. Of the total valid sample, 17.6% (out of 193,345 children) had LBW and 12.4% (out of 253,213 children) had SBS. The small areas contributed the highest share of total geographic variance in LBW (52%) and SBS (78%). The variance of LBW attributed to small areas was unevenly distributed across the regions of India. While a strong correlation between district-wide percent and within-district standard deviation was identified in both LBW (r = 0.88) and SBS (r = 0.87), they were not necessarily concentrated in the aspirational districts. We find the necessity of precise policy attention specifically to the small areas in the districts of India with a high prevalence of LBW and SBS in programme formulation and intervention that may be beneficial to improve childbirth outcomes.

Small area variations and factors associated with blood pressure and body-mass index in adult women in Accra, Ghana: Bayesian spatial analysis of a representative population survey and census data.

BACKGROUND: Body-mass index (BMI) and blood pressure (BP) levels are rising in sub-Saharan African cities, particularly among women. However, there is very limited information on how much they vary within cities, which could inform targeted and equitable health policies. Our study aimed to analyse spatial variations in BMI and BP for adult women at the small area level in the city of Accra, Ghana. METHODS AND FINDINGS: We combined a representative survey of adult women's health in Accra, Ghana (2008 to 2009) with a 10% random sample of the national census (2010). We applied a hierarchical model with a spatial term to estimate the associations of BMI and systolic blood pressure (SBP) and diastolic blood pressure (DBP) with demographic, socioeconomic, behavioural, and environmental factors. We then used the model to estimate BMI and BP for all women in the census in Accra and calculated mean BMI, SBP, and DBP for each enumeration area (EA). BMI and/or BP were positively associated with age, ethnicity (Ga), being currently married, and religion (Muslim) as their 95% credible intervals (95% CrIs) did not include zero, while BP was also negatively associated with literacy and physical activity. BMI and BP had opposite associations with socioeconomic status (SES) and alcohol consumption. In 2010, 26% of women aged 18 and older had obesity (BMI ≥ 30 kg/m2), and 21% had uncontrolled hypertension (SBP ≥ 140 and/or DBP ≥ 90 mm Hg). The differences in mean BMI and BP between EAs at the 10th and 90th percentiles were 2.7 kg/m2 (BMI) and in BP 7.9 mm Hg (SBP) and 4.8 mm Hg (DBP). BMI was generally higher in the more affluent eastern parts of Accra, and BP was higher in the western part of the city. A limitation of our study was that the 2010 census dataset used for predicting small area variations is potentially outdated; the results should be updated when the next census data are available, to the contemporary population, and changes over time should be evaluated. CONCLUSIONS: We observed that variation of BMI and BP across neighbourhoods within Accra was almost as large as variation across countries among women globally. Localised measures are needed to address this unequal public health challenge in Accra.

Measuring health-related social deprivation in small areas: development of an index and examination of its association with cancer mortality.

BACKGROUND: The small-area deprivation indices are varied across countries due to different social context and data availability. Due to lack of chronic disease-related social deprivation index (SDI) in Hong Kong, China, this study aimed to develop a new SDI and examine its association with cancer mortality. METHODS: A total of 14 socio-economic variables of 154 large Tertiary Planning Unit groups (LTPUGs) in Hong Kong were obtained from 2016 population by-census. LTPUG-specific all-cause and chronic condition-related mortality and chronic condition inpatient episodes were calculated as health outcomes. Association of socio-economic variables with health outcomes was estimated for variable selection. Candidates for SDI were constructed with selected socio-economic variables and tested for criterion validity using health outcomes. Ecological association between the selected SDI and cancer mortality were examined using zero-inflated negative binomial regression. RESULTS: A chronic disease-related SDI constructed by six area-level socio-economic variables was selected based on its criterion validity with health outcomes in Hong Kong. It was found that social deprivation was associated with higher cancer mortality during 2011-2016 (most deprived areas: incidence relative risk [IRR] = 1.40, 95% confidence interval [CI]: 1.27-1.55; second most deprived areas: IRR = 1.34, 95%CI: 1.21-1.48; least deprived areas as reference), and the cancer mortality gap became larger in more recent years. Excess cancer death related to social deprivation was found to have increased through 2011-2016. CONCLUSIONS: Our newly developed SDI is a valid and routinely available measurement of social deprivation in small areas and is useful in resource allocation and policy-making for public health purpose in communities. There is a potential large improvement in cancer mortality by offering relevant policies and interventions to reduce health-related deprivation. Further studies can be done to design strategies to reduce the expanding health inequalities between more and less deprived areas.

Monitoring the spatiotemporal epidemiology of Covid-19 incidence and mortality: A small-area analysis in Germany.

Timely monitoring of incidence risks of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and associated deaths at small-area level is essential to inform containment strategies. We analysed the spatiotemporal epidemiology of the SARSCoV- 2 pandemic at district level in Germany to develop a tool for disease monitoring. We used a Bayesian spatiotemporal model to estimate the district-specific risk ratios (RR) of SARS-CoV-2 incidence and the posterior probability (PP) for exceedance of RR thresholds 1, 2 or 3. Of 220 districts (55% of 401 districts) showing a RR > 1, 188 (47%) exceed the RR threshold with sufficient certainty (PP ≥ 80%) to be considered at high risk. 47 districts show very high (RR > 2, PP ≥ 80%) and 15 extremely high (RR > 3, PP ≥ 80%) risks. The spatial approach for monitoring the risk of SARS-CoV-2 provides an informative basis for local policy planning.

Trends and regional variation in vertebroplasty and kyphoplasty in Switzerland: a population-based small area analysis.

Regional variation in procedure use often reflects the uncertainty about the risks and benefit of procedures. In Switzerland, regional variation in vertebroplasty and balloon kyphoplasty rates was high, although the variation declined between 2013 and 2018. Substantial parts of the variation remained unexplained, and likely signal unequal access and differing physician opinion. PURPOSE: To assess trends and regional variation in percutaneous vertebroplasty (VP) and balloon kyphoplasty (BKP) use across Switzerland. METHODS: We conducted a population-based analysis using patient discharge data from all Swiss acute care hospitals for 2013-2018. We calculated age/sex-standardized mean procedure rates and measures of variation across VP/BKP-specific hospital areas (HSAs). We assessed the influence of potential determinants of variation using multilevel regression models with incremental adjustment for demographics, cultural/socioeconomic, health, and supply factors. RESULTS: We analyzed 7855 discharges with VP/BKP from 31 HSAs. The mean age/sex-standardized procedure rate increased from 16 to 20/100,000 persons from 2013 to 2018. While the variation in procedure rates across HSAs declined, the overall variation remained high (systematic component of variation from 56.8 to 6.9 from 2013 to 2018). Determinants explained 52% of the variation. CONCLUSIONS: VP/BKP procedure rates increased and regional variation across Switzerland declined but remained at a high level. A substantial part of the regional variation remained unexplained by potential determinants of variation.