899Stepping up: identifying small-area variation in diabetes-related lower limb amputations

Background Diabetes-related foot disease is the leading cause of lower limb amputations in Queensland. Amputations can be either minor (below the ankle joint) or major (above the ankle joint). Minor amputations may be performed to prevent major amputations prophylactically, but how these forms of amputations interrelate, and where their interrelationships are weakest and strongest, is unknown. Knowledge of small-area variation in interrelations between minor and major amputations is relevant to prevention and improved management of foot disease. Methods Data on lower limb amputations performed between 2014 and 2018 on patients aged 20+ years with diabetes were obtained from the Queensland Hospital Admitted Patient Data Collection. Rates were calculated using the number of people, rather than the number of amputation procedures. A Bayesian hierarchical spatial multivariate model was used to examine patterns over 516 populated statistical areas 2 in Queensland. Results During 2014 to 2018, 3,548 Queenslanders had at least one minor amputation, and 1,114 had at least one major amputation. Modelled amputation rates varied markedly across the State (standardised morbidity ratio (SMR) IQR: 0.67 to 1.22), with areas in far north Queensland having extremely high rates. There was consistently high area-level correlation between minor and major amputation rates. The highest SMRs for both minor and major amputations were in the Northern Peninsula. Conclusions Elevated rates of minor and major amputations in areas in Queensland, most noticeably the far north, indicate an urgent need for greater support for people with diabetes-related foot disease. Key messages Text: Large differences in minor and major amputation rates across Queensland indicate that certain regions require greater assistance in managing diabetes-related foot disease.

Small area variation in crime effects of COVID-19 policies in England and Wales

It is well established that COVID-19 policies to restrict movement induced widespread falls in many crime types internationally. Much less is known about variation between areas in how these changes occurred. This study uses k-means clustering to examine local area variation in police notifiable offences across England and Wales. It finds that crime in most areas remained stable, a small proportion of areas accounting for disproportionate change. These were typically city centers with plentiful pre-pandemic crime opportunities, dominated by theft and shoplifting offences. We explore potential implications for policy, theory and further research.

Residential area and screening venue location features associated with spatial variation in breast cancer screening invitation response rates: an observational study in Greater Sydney, Australia

ObjectivesParticipation in breast cancer screening (BCS) varies at the small-area level, which may reflect environmental influences. This study assessed small-area variation in BCS invitation response rates (IRRs) and associations between small-area BCS IRR, sociodemographic factors, BCS venue distance and venue location features in Greater Sydney, Australia.MethodsBCS IRR data for 2011–2012 were compiled for 9528 Australian Bureau of Statistics Statistical Area Level 1 (SA1) units (n=227 474 women). A geographial information system was used to extract SA1-level sociodemographic features (proportions of women speaking English at home, full-time employed and university educated, and proportion of dwellings with motor vehicles), SA1-level distance to closest venue(s) (expressed as quartiles), and closest venue(s) colocated with bus stops, train station, hospital, general practitioner and shops. Associations between area-level features, BCS venue distance, venue location features and IRR were estimated using ordinary least square-type spatial lag models including area education as a covariate.ResultsBCS IRR varied across SA1s (mean=59.8%, range: 0%–100%), with notable spatial autocorrelation (Moran’s I=0.803). BCS IRR was positively associated with greater SA1-level proportion of women speaking English at home (β=2.283, 95% CI 2.024 to 2.543), women’s education (in the model including speaking English at home β=0.454, 95% CI 0.211 to 0.697), dwellings with motor vehicles (β=1.836, 95% CI 1.594 to 2.078), greater distance to venue (eg, most distant quartile compared with closest: β=6.249, 95% CI 5.489 to 7.008), and BCS venue colocated with shops (β=0.762, 95% CI 0.273 to 1.251). Greater SA1-level women employment (β=−0.613, 95% CI −0.898 to −0.328) and venue colocated with train station (β=−1.889, 95% CI −2.376 to −1.402) or hospital (β=−0.677, 95% CI −1.164 to −0.189) were inversely related to BCS IRR.ConclusionsSmall-area variation in BCS IRR exists for Greater Sydney and is strongly related to sociodemographic factors that, together with BCS venue location features, could inform targeted attempts to improve IRR.

Small area variation in child undernutrition across 640 districts and 543 parliamentary constituencies in India

In India, districts serve as central policy unit for program development, administration and implementation. The one-size-fits-all approach based on average prevalence estimates at the district level fails to capture the substantial small area variation. In addition to district average, heterogeneity within districts should be considered in policy design. The objective of this study was to quantify the extent of small area variation in child stunting, underweight and wasting across 36 states/Union Territories (UTs), 640 districts (and 543 PCs), and villages/blocks in India. We utilized the 4th round of Indian National Family Health Survey (NFHS-4) conducted in 2015–2016. The study population included 225,002 children aged 0–59 months whose height and weight information were available. Stunting was defined as height-for-age z-score below 2 SD from the World Health Organization child growth reference standards. Similarly, underweight and wasting were each defined as weight-for-age < -2 SD and weight-for-height < -2 SD from the age- and sex-specific medians. We adopted a four-level logistic regression model to partition the total variation in stunting, underweight and wasting. We computed precision-weighted prevalence of child anthropometric failures across districts and PCs as well as within-district/PC variation using standard deviation (SD) measures. For stunting, 56.4% (var: 0.237; SE: 0.008) of the total variation was attributed to villages/blocks, followed by 25.8% (var: 0.109; SE: 0.030) to states/UTs, and 17.7% (Var: 0.074; SE: 0.006) to districts. For underweight and wasting, villages/blocks accounted for 38.4% (var: 0.224; SE: 0.007) and 50% (var: 0.285; SE: 0.009), respectively, of the total contextual variance in India. Similar findings were shown in multilevel models incorporating PC as a geographical unit instead of districts. We found high positive correlations between mean prevalence and SD for stunting (r = 0.780, p < 0.001), underweight (r = 0.860, p < 0.001), and wasting (r = 0.857, p < 0.001) across all districts in India. A similar pattern of correlation was found for PCs. Within-district and within-PC variation are the primary source of variation for child malnutrition in India. Our results suggest the importance of considering heterogeneity within districts and PCs when planning and administering child nutrition policies.

Spatial epidemiology of gestational age and birth weight in Switzerland: census-based linkage study

BackgroundGestational age and birth weight are strong predictors of infant morbidity and mortality. Understanding spatial variation can inform policies to reduce health inequalities. We examined small-area variation in gestational age and birth weight in Switzerland.MethodsAll singleton live births recorded in the Swiss Live Birth Register 2011 to 2014 were eligible. We deterministically linked the Live Birth Register with census and survey data to create data sets including neonatal and pregnancy-related variables, parental characteristics and geographical variables. We produced maps of 705 areas and fitted linear mixed-effect models to assess to what extent spatial variation was explained by these variables.ResultsWe analysed all 315 177 eligible live births. Area-level averages of gestational age varied between 272 and 279 days, and between 3138 and 3467 g for birth weight. The fully adjusted models explained 31% and 87% of spatial variation of gestational age and birth weight, respectively. Language region accounted for most of the explained variation (23% in gestational age and 62% in birth weight), with shorter gestational age (−0.6 days and −0.9 days) and lower birth weight (−1.1% and −1.8%) in French-speaking and Italian-speaking areas, respectively, compared with German-speaking areas. Other variables explaining variation were, for gestational age, the level of urbanisation (10%) and parental nationality (3%). For birth weight, they were gestational age (27%), parental nationality (27%), civil status (10%) and altitude (10%). In a random sample of 81 968 live births with data on parental education, levels of education were only weakly associated with gestational age (−0.9 days for compulsory vs tertiary maternal education) or birth weight (−0.7% for compulsory vs tertiary maternal education).ConclusionsIn Switzerland, small area variation in birth weight is largely explained, and variation in gestational age partially explained, by geocultural, sociodemographic and pregnancy factors.