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

Abstract

BackgroundIn 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.MethodsA 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.ResultsThe 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.ConclusionIn 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s40608-016-0092-6) contains supplementary material, which is available to authorized users.

A tall order: Small area mapping and modelling of adult height among Swiss male conscripts

“…The recruitment process of the Swiss Armed Forces has been described in details elsewhere (Bruggisser et al, 2016;Panczak et al, 2016Panczak et al, , 2014, in brief, all men are reviewed for recruitment during the year in which they turn 19. The military assessments include, among others, a standardized measurement of height (rounded to integers) of every conscript (without shoes and in light underwear), including those who get deferred or exempted (Bundesgesetz über die Armee und die Militärverwaltung,510.10,Art.…”

“…3 and Art. 9) (Panczak et al, 2016(Panczak et al, , 2014. Swiss Armed Forces provided a complete set of anonymized conscript records from 1.1.2005 to 31.12.2011 which included date of birth, date of conscription, height, current occupation, postcode of place of residence (further referred to as 'postcode') and stage of conscription (first, regular visit versus reassessment).…”

“…We obtained a dataset of postcode boundaries from the Federal Directorate of Cadastral Surveying ("Release 7-1. Mai 2013", boundaries as per 31st of March 2013) (Panczak et al, 2016(Panczak et al, , 2014.…”

“…Small-area analyses are able to describe clusters and geographic variations of a given outcome (Elliott and Wartenberg, 2004). In the case of height, this might be of particular interest because people with high socioeconomic position usually tend to live near others with high socioeconomic position, irrespective of administrative units such as districts or cantons (Panczak et al, 2016). Such spatially organized socioeconomic and/or demographic effects often continue to be observed after controlling for individual-level factors (Panczak et al, 2012).…”

“…Switzerland serves as an ideal basis for such studies because of its cultural and demographic diversity and historical stability (four official language regions, and significant variation of geographical and socioeconomic environment). Studies of mortality and obesity have already shown the benefits of small-area analyses in Switzerland (Moser et al, 2014;Panczak et al, 2016Panczak et al, , 2012. Moreover, military conscription provides a large, spatially referenced dataset of the anthropometric status of young men at a prescribed age.…”