A comparison of the spatial dependence of body mass index among adults and children in a Swiss general population

Comparison of spatial approaches to assess the effect of residing in a 20-minute neighbourhood on body mass index

Beliefs that neighbourhood environments influence body mass index (BMI) assume people residing proximally have similar outcomes. However, spatial relationships are rarely examined. We considered spatial autocorrelation when estimating associations between neighbourhood environments and BMI in two Australian cities. Using cross-sectional data from 1329 participants (Melbourne = 637, Adelaide = 692), spatial autocorrelation in BMI was examined for different spatial weights definitions. Spatial and ordinary least squares regression were compared to assess how accounting for spatial autocorrelation influenced model findings. Geocoded household addresses were used to generate matrices based on distances between addresses. We found low positive spatial autocorrelation in BMI; magnitudes differed by matrix choice, highlighting the need for careful consideration of appropriate spatial weighting. Results indicated statistical evidence of spatial autocorrelation in Adelaide but not Melbourne. Model findings were comparable, with no residual spatial autocorrelation after adjustment for confounders. Future neighbourhoods and BMI research should examine spatial autocorrelation, accounting for this where necessary.

Body height in adult women and men in a cross-sectional population-based survey in Geneva: temporal trends, association with general health status and height loss after age 50

OBJECTIVE

On the one hand, trends in average height in adulthood mirror changes in living standard and health status of a population and its subgroups; on the other hand, height in general, as well as the loss of height in older age in particular, are associated in different ways with outcomes for health. For these aspects, there is hardly any information for Switzerland based on representative and measured body height data.

DESIGN

Repeated cross-sectional survey study.

SETTING

Fully anonymised data from the representative population-based Geneva Bus Santé Study between 2005 and 2017 were analysed.

METHODS

Data from N=8686 study participants were used in the trend analysis. Height was measured and sociodemographic information and self-rated health was collected via questionnaires. Follow-up (mean: 7.1 years) measurements from N=2112 participants were available to assess height loss after age 50.

RESULTS

Women were, on average, 166.2 cm (SD 6.5) tall and men 179.2 cm (SD 6.5). Among men and women, higher socioeconomic status was associated with taller average height. The flattening of the increase in height from the 1970s birth years appears to begin earlier in the subgroup with the highest education level. The tallest average height was measured for men and women from Central and Northern Europe, the shortest for South America and Asia. The likelihood that participants rated their health as 'very good' increased with greater body height. The follow-up data show that men lost -0.11 cm per follow-up year (95% CI -0.12 to -0.10), women -0.17 cm (95% CI -0.18 to 0.15).

CONCLUSIONS

The association of height and health status is currently understudied. Monitoring changes in average body height may indicate disparities in different subgroups of populations. Based on our study and a growing literature, we think that the multifaceted role of body height should be better considered in clinical practice.

Neighborhood disadvantage moderates the effect of a mobile health intervention on adolescent depression

This study leverages data from a pilot randomized controlled trial to investigate whether the effectiveness of a text-delivered mHealth intervention targeting adolescent depression and anxiety differs according to residential- and activity space-based measures of exposure to community-level socioeconomic disadvantage. For depression, we find that intervention efficacy is significantly stronger for youth residing in more disadvantaged neighborhoods, even after controlling for individual level socioeconomic status, as well as marginal moderating effects of activity space-based neighborhood disadvantage on treatment efficacy. We do not find evidence of treatment efficacy moderation by neighborhood disadvantage regarding anxiety. While the generalizability of our findings is restricted to this sample and for this intervention, this research serves as a motivating example and initial evidence for how mHealth intervention efficacy can vary by characteristics of the environment, in particular community-level disadvantage. Future clinical research should investigate whether the effectiveness of mHealth interventions may be enhanced by personalization based on an individual's contextual environmental exposures.

Geographic footprints of life expectancy inequalities in the state of Geneva, Switzerland

Though Switzerland has one of the highest life expectancies in the world, this global indicator may mask significant disparities at a local level. The present study used a spatial cluster detection approach based on individual death records to investigate the geographical footprint of life expectancy inequalities in the state of Geneva, Switzerland. Individual-level mortality data (n = 22,751) were obtained from Geneva’s official death notices (2009–2016). We measured life expectancy inequalities using the years of potential life lost or gained (YPLLG) metric, defined as the difference between an individual’s age at death and their life expectancy at birth. We assessed the spatial dependence of YPLLG across the state of Geneva using spatial autocorrelation statistics (Local Moran’s I). To ensure the robustness of the patterns discovered, we ran the analyses for ten random subsets of 10,000 individuals taken from the 22,751 deceased. We also repeated the spatial analysis for YPLLG before and after controlling for individual-level and neighborhood-level covariates. The results showed that YPLLG was not randomly distributed across the state of Geneva. The ten random subsets revealed no significant difference with the geographic footprint of YPLLG and the population characteristics within Local Moran cluster types, suggesting robustness for the observed spatial structure. The proportion of women, the proportion of Swiss, the neighborhood median income, and the neighborhood median age were all significantly lower for populations in low YPLLG clusters when compared to populations in high YPLLG clusters. After controlling for individual-level and neighborhood-level covariates, we observed a reduction of 43% and 39% in the size of low and high YPLLG clusters, respectively. To our knowledge, this is the first study in Switzerland using spatial cluster detection methods to investigate inequalities in life expectancy at a local scale and based on individual data. We identified clear geographic footprints of YPLLG, which may support further investigations and guide future public health interventions at the local level.

Vegetarian, pescatarian and flexitarian diets: sociodemographic determinants and association with cardiovascular risk factors in a Swiss urban population

Prevalence and trends of different vegetarian diets remain unknown, with estimates varying depending on the source. Evidence suggests that vegetarian diets are associated with a more favourable cardiovascular risk profile. The present study aimed to assess the prevalence and trends of different types of vegetarian diets in a population-based representative sample, sociodemographic characteristics of participants following such diets and the association of these diets with cardiovascular risk factors. Using repeated cross-sectional population-based surveys conducted in Geneva, Switzerland, 10 797 individuals participated in the study between 2005 and 2017. Participants were classified as vegetarians, pescatarians, flexitarians or omnivores using an FFQ. Sociodemographic and cardiovascular risk factors were evaluated through questionnaires, anthropometric measurements and blood tests. Findings show prevalence of vegetarians increased from 0·5 to 1·2 %, pescatarians from 0·3 to 1·1 % and flexitarians remained stable at 15·6 % of the population over the study period. Compared with omnivores, vegetarians were more likely to be young (OR 2·38; 95 % CI 1·01, 5·6), have higher education (OR 1·59; 95 % CI 1·01, 2·49) and lower income (OR 1·83; 95 % CI 1·04, 3·21); pescatarians and flexitarians were more likely to be women (pescatarian: OR 1·81; 95 % CI 1·10, 3·00; vegetarian: OR 1·57; 95 % CI 1·41, 1·75) and flexitarians were also more likely to have a lower income (OR 1·31; 95 % CI 1·13, 1·53). Participants who adhered to any diet excluding/reducing meat intake had lower BMI, total cholesterol and hypertension compared with omnivores. The present study shows an increase in the prevalence of vegetarians over a 13-year period and suggests that the different vegetarian diets assessed are associated with a better cardiovascular risk profile.

Overlapping spatial clusters of sugar-sweetened beverage intake and body mass index in Geneva state, Switzerland

Background

Obesity and obesity-related diseases represent a major public health concern. Recently, studies have substantiated the role of sugar-sweetened beverages (SSBs) consumption in the development of these diseases. The fine identification of populations and areas in need for public health intervention remains challenging. This study investigates the existence of spatial clustering of SSB intake frequency (SSB-IF) and body mass index (BMI), and their potential spatial overlap in a population of adults of the state of Geneva using a fine-scale geospatial approach.

Methods

We used data on self-reported SSB-IF and measured BMI from residents aged between 20 and 74 years of the state of Geneva (Switzerland) that participated in the Bus Santé cross-sectional population-based study (n = 15,423). Getis-Ord Gi spatial indices were used to identify spatial clusters of SSB-IF and BMI in unadjusted models and models adjusted for individual covariates (education level, gender, age, nationality, and neighborhood-level median income).

Results

We identified a significant spatial clustering of BMI and SSB-IF. 13.2% (n = 2034) of the participants were within clusters of higher SSB-IF and 10.7% (n = 1651) were within clusters of lower SSB-IF. We identified overlapping clusters of SSB-IF and BMI in specific areas where 11.1% (n = 1719) of the participants resided. After adjustment, the identified clusters persisted and were only slightly attenuated indicating that additional neighborhood-level determinants influence the spatial distribution of SSB-IF and BMI.

Conclusions

Our fine-scale spatial approach allowed to identify specific populations and areas presenting higher SSB-IF and highlighted the existence of an overlap between populations and areas of higher SSB-IF associated with higher BMI. These findings could guide policymakers to develop locally tailored interventions such as targeted prevention campaigns and pave the way for precision public health delivery.

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.

Spatial distribution of mammography adherence in a Swiss urban population and its association with socioeconomic status

Purpose

Local physical and social environment has a defining influence on individual behavior and health‐related outcomes. However, it remains undetermined if its impact is independent of individual socioeconomic status. In this study, we evaluated the spatial distribution of mammography adherence in the state of Geneva (Switzerland) using individual‐level data and assessed its independence from socioeconomic status (SES).

Methods

Georeferenced individual‐level data from the population‐based cross‐sectional Bus Santé study (n = 5002) were used to calculate local indicators of spatial association (LISA) and investigate the spatial dependence of mammography adherence. Spatial clusters are reported without adjustment; adjusted for neighborhood income and individual educational attainment; and demographic factors (age and Swiss nationality). The association between adjusted clusters and the proximity to the nearest screening center was also evaluated.

Results

Mammography adherence was not randomly distributed throughout Geneva with clusters geographically coinciding with known SES distributions. After adjustment for SES indicators, clusters were reduced to 56.2% of their original size (n = 1033). Adjustment for age and nationality further reduced the number of individuals exhibiting spatially dependent behavior (36.5% of the initial size). The identified SES‐independent hot spots and cold spots of mammography adherence were not explained by proximity to the nearest screening center.

Conclusions

SES and demographic factors play an important role in shaping the spatial distribution of mammography adherence. However, the spatial clusters persisted after confounder adjustment indicating that additional neighborhood‐level determinants could influence mammography adherence and be the object of targeted public health interventions.

Finding big shots: small-area mapping and spatial modelling of obesity among Swiss male conscripts

BACKGROUND

In Switzerland, as in other developed countries, the prevalence of overweight and obesity has increased substantially since the early 1990s. Most of the analyses so far have been based on sporadic surveys or self-reported data and did not offer potential for small-area analyses. The goal of this study was to investigate spatial variation and determinants of obesity among young Swiss men using recent conscription data.

METHODS

A complete, anonymized dataset of conscription records for the 2010-2012 period were provided by Swiss Armed Forces. We used a series of Bayesian hierarchical logistic regression models to investigate the spatial pattern of obesity across 3,187 postcodes, varying them by type of random effects (spatially unstructured and structured), level of adjustment by individual (age and professional status) and area-based [urbanicity and index of socio-economic position (SEP)] characteristics.

RESULTS

The analysed dataset consisted of 100,919 conscripts, out of which 5,892 (5.8 %) were obese. Crude obesity prevalence increased with age among conscripts of lower individual and area-based SEP and varied greatly over postcodes. Best model's estimates of adjusted odds ratios of obesity on postcode level ranged from 0.61 to 1.93 and showed a strong spatial pattern of obesity risk across the country. Odds ratios above 1 concentrated in central and north Switzerland. Smaller pockets of elevated obesity risk also emerged around cities of Geneva, Fribourg and Lausanne. Lower estimates were observed in North-East and East as well as south of the Alps. Importantly, small regional outliers were observed and patterning did not follow administrative boundaries. Similarly as with crude obesity prevalence, the best fitting model confirmed increasing risk of obesity with age and among conscripts of lower professional status. The risk decreased with higher area-based SEP and, to a lesser degree - in rural areas.

CONCLUSION

In Switzerland, there is a substantial spatial variation in obesity risk among young Swiss men. Small-area estimates of obesity risk derived from conscripts records contribute to its understanding and could be used to design further studies and interventions.

Persistent spatial clusters of high body mass index in a Swiss urban population as revealed by the 5-year GeoCoLaus longitudinal study

OBJECTIVE

Body mass index (BMI) may cluster in space among adults and be spatially dependent. Whether and how BMI clusters evolve over time in a population is currently unknown. We aimed to determine the spatial dependence of BMI and its 5-year evolution in a Swiss general adult urban population, taking into account the neighbourhood-level and individual-level characteristics.

DESIGN

Cohort study.

SETTING

Swiss general urban population.

PARTICIPANTS

6481 georeferenced individuals from the CoLaus cohort at baseline (age range 35-74 years, period=2003-2006) and 4460 at follow-up (period=2009-2012).

OUTCOME MEASURES

Body weight and height were measured by trained healthcare professionals with participants standing without shoes in light indoor clothing. BMI was calculated as weight (kg) divided by height squared (m(2)). Participants were geocoded using their postal address (geographic coordinates of the place of residence). Getis-Ord Gi statistic was used to measure the spatial dependence of BMI values at baseline and its evolution at follow-up.

RESULTS

BMI was not randomly distributed across the city. At baseline and at follow-up, significant clusters of high versus low BMIs were identified and remained stable during the two periods. These clusters were meaningfully attenuated after adjustment for neighbourhood-level income but not individual-level characteristics. Similar results were observed among participants who showed a significant weight gain.

CONCLUSIONS

To the best of our knowledge, this is the first study to report longitudinal changes in BMI clusters in adults from a general population. Spatial clusters of high BMI persisted over a 5-year period and were mainly influenced by neighbourhood-level income.