The Swiss neighbourhood index of socioeconomic position: update and re-validation.

BACKGROUND: The widely used Swiss neighbourhood index of socioeconomic position (Swiss-SEP 1) was based on data from the 2000 national census on rent, household head education and occupation, and crowding. It may now be out of date. METHODS: We created a new index (Swiss-SEP 2) based on the 2012-2015 yearly micro censuses that have replaced the decennial house-to-house census in Switzerland since 2010. We used principal component analysis on neighbourhood-aggregated variables and standardised the index. We also created a hybrid version (Swiss-SEP 3), with updated values for neighbourhoods centred on buildings constructed after the year 2000 and original values for the remaining neighbourhoods. RESULTS: A total of 1.54 million neighbourhoods were included. With all three indices, the mean yearly equivalised household income increased from around 52,000 to 90,000 CHF from the lowest to the highest index decile. Analyses of mortality were based on 33.6 million person-years of follow-up. The age- and sex-adjusted hazard ratios of all-cause mortality comparing areas in the lowest Swiss-SEP decile with areas of the highest decile were 1.39 (95% confidence interval [CI] 1.36-1.41), 1.31 (1.29-1.33) and 1.34 (1.32-1.37) using the old, new and hybrid indices, respectively. DISCUSSION: The Swiss-SEP indices capture area-based SEP at a high resolution and allow the study of SEP when individual-level SEP data are missing or area-level effects are of interest. The hybrid version (Swiss-SEP 3) maintains high spatial resolution while adding information on new neighbourhoods. The index will continue to be useful for Switzerland's epidemiological and public health research.

Spatial Association of Food Sales in Supermarkets with the Mean BMI of Young Men: An Ecological Study.

Supermarket food sales data might serve as a simple indicator of population-level dietary habits that influence the prevalence of excess weight in local environments. To test this possibility, we investigated how variation in store-level food sales composition across Switzerland is associated with the mean Body Mass Index (BMI) of young men (Swiss Army conscripts) living near the stores. We obtained data on annual food sales (2011) for 553 stores from the largest supermarket chain in Switzerland, identified foods commonly regarded as "healthy" or "unhealthy" based on nutrient content, and determined their contribution to each store's total sales (Swiss francs). We found that the sales percentages of both "healthy" and "unhealthy" food types varied by 2- to 3-fold among stores. Their balance ranged from -15.3% to 18.0% of total sales; it was positively associated with area-based socioeconomic position (r = 0.63) and negatively associated with the mean BMI of young men in the area (r = -0.42). Thus, even though we compared supermarkets from a single chain, different shopping behaviors of customers caused stores in privileged areas to sell relatively more healthy food. Knowledge about such patterns could help in designing in-store interventions for healthier nutrition and monitoring their effects over time.

Death at no cost? Persons with no health insurance claims in the last year of life in Switzerland.

BACKGROUND: Lack of health insurance claims (HIC) in the last year of life might indicate suboptimal end-of-life care, but reasons for no HIC are not fully understood because information on causes of death is often missing. We investigated association of no HIC with characteristics of individuals and their place of residence. METHODS: We analysed HIC of persons who died between 2008 and 2010, which were obtained from six providers of mandatory Swiss health insurance. We probabilistically linked these persons to death certificates to get cause of death information and analysed data using sex-stratified, multivariable logistic regression. Supplementary analyses looked at selected subgroups of persons according to the primary cause of death. RESULTS: The study population included 113,277 persons (46% males). Among these persons, 1199 (proportion 0.022, 95% CI: 0.021-0.024) males and 803 (0.013, 95% CI: 0.012-0.014) females had no HIC during the last year of life. We found sociodemographic and health differentials in the lack of HIC at the last year of life among these 2002 persons. The likelihood of having no HIC decreased steeply with older age. Those who died of cancer were more likely to have HIC (adjusted odds ratio for males 0.17, 95% CI: 0.13-0.22; females 0.19, 95% CI: 0.12-0.28) whereas those dying of mental and behavioural disorders (AOR males 1.83, 95% CI:1.42-2.37; females 1.65, 95% CI: 1.27-2.14), and males dying of suicide (AOR 2.15, 95% CI: 1.72-2.69) and accidents (AOR 2.41, 95% CI: 1.96-2.97) were more likely to have none. Single, widowed, and divorced persons also were more likely to have no HIC (AORs in range of 1.29-1.80). There was little or no association between the lack of HIC and characteristics of region of residence. Patterns of no HIC differed across main causes of death. Associations with age and civil status differed in particular for persons who died of cancer, suicide, accidents and assaults, and mental and behavioural disorders. CONCLUSIONS: Particular groups might be more likely to not seek care or not report health insurance costs to insurers. Researchers should be aware of this aspect of health insurance data and account for persons who lack HIC.

Regional Variation of Cost of Care in the Last 12 Months of Life in Switzerland: Small-area Analysis Using Insurance Claims Data.

BACKGROUND: Health care spending increases sharply at the end of life. Little is known about variation of cost of end of life care between regions and the drivers of such variation. We studied small-area patterns of cost of care in the last year of life in Switzerland. METHODS: We used mandatory health insurance claims data of individuals who died between 2008 and 2010 to derive cost of care. We used multilevel regression models to estimate differences in costs across 564 regions of place of residence, nested within 71 hospital service areas. We examined to what extent variation was explained by characteristics of individuals and regions, including measures of health care supply. RESULTS: The study population consisted of 113,277 individuals. The mean cost of care during last year of life was 32.5k (thousand) Swiss Francs per person (SD=33.2k). Cost differed substantially between regions after adjustment for patient age, sex, and cause of death. Variance was reduced by 52%-95% when we added individual and regional characteristics, with a strong effect of language region. Measures of supply of care did not show associations with costs. Remaining between and within hospital service area variations were most pronounced for older females and least for younger individuals. CONCLUSIONS: In Switzerland, small-area analysis revealed variation of cost of care during the last year of life according to linguistic regions and unexplained regional differences for older women. Cultural factors contribute to the delivery and utilization of health care during the last months of life and should be considered by policy makers.