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Introduction Although Switzerland has one of the highest life expectancy in the world, this global indicator may mask significant disparities at a local level. The present study used a spatial cluster detection approach on individual mortality data to investigate the geographic footprint of life expectancy inequalities in the state of Geneva, Switzerland. Methods Individual-level mortality data (n=30,592) were obtained from the Geneva’s mortuary announcements (2003-2017). We measured life expectancy inequalities through Life Expectancy Difference (LED), defined as the difference between the individual’s age at death and their Life Expectancy at Birth. We assessed the spatial dependence of LED across the state of Geneva using spatial autocorrelation statistics (Local Moran’s I). To ensure the robustness of the discovered patterns, we ran the analysis for ten random subsets of 10,000 individuals drawn from the 30,592 deceased. We also repeated the spatial analysis for LED before and after controlling for nationality and neighborhood income.Results LED was not randomly distributed across the state of Geneva. The ten random subsets revealed no significant difference in the geographic footprint of LED and the population characteristics within Local Moran cluster types, suggesting the robustness of the spatial structure obtained. The proportion of women, the proportion of Swiss, and the median neighborhood income were significantly lower for populations within low LED clusters than for populations within high LED clusters. After controlling for nationality and neighborhood income, we observed a slight reduction in the low LED cluster footprints, but we found similar differences in population characteristics between cluster types.Conclusion To the best of our knowledge, this is the first study in Switzerland using spatial cluster detection methods to investigate small area inequalities in life expectancy. We identified a clear geographic footprint of LED, which may support further investigations and guide future public health interventions at the local level.

BackgroundThe COVID-19 pandemic has affected billions of people around the world both directly through the infection itself and indirectly through its economic, social and sanitary impact. Collecting data over time is essential for the understanding of the disease spread, the incidence of COVID19-like symptoms, the level and dynamics of immunity, as well as the long-term impact of the pandemic.ObjectiveThe objective of the study was to set up a longitudinal follow-up of adult participants of serosurveys carried out in the Canton of Geneva, Switzerland, during the COVID-19 pandemic.MethodsSerosurvey participants were invited to create an account on the dedicated digital platform Specchio-COVID19 (https://www.specchio-covid19.ch/). Upon registration, an initial questionnaire assessed socio-demographic and lifestyle characteristics (including housing conditions, physical activity, diet, alcohol and tobacco consumption), anthropometry, general health, and experience related to COVID-19 (symptoms, COVID-19 test results, quarantines, hospitalizations). Weekly, participants were invited to fill in a short questionnaire with updates on self-reported COVID-19-compatible symptoms, SARS-CoV-2 infection testing and vaccination. A more detailed questionnaire about mental health, well-being, risk perception, and changes in working conditions was proposed monthly. Supplementary questionnaires were proposed at regular intervals to assess more in depth the impact of the pandemic on physical and mental health, vaccination adherence, health care consumption and changes in health behaviors. At baseline, serology testing allowed to assess the spread of SARS-CoV-2 infection among the general population and subgroups of workers. Additionally, seropositive participants and a sample of randomly selected participants were invited for serologic testing at regular intervals in order to monitor both the seropersistance of anti-SARS-CoV-2 antibodies and the seroprevalence of anti-SARS-CoV-2 antibodies in the population of the Canton of Geneva.Ethics and disseminationThe study was approved by the Cantonal Research Ethics Commission of Geneva, Switzerland (CCER Project ID 2020-00881). Results will be disseminated in a variety of ways, via the Specchio-COVID19 platform, social media posts, press releases, and through regular scientific dissemination methods (open-access articles, conferences).Article summaryStrengths and limitationsThis is a large study with a diversified recruitment among the general population and mobilized workers. It will contribute to obtain a clearer picture of the impact of the COVID-19 pandemic, for both the general population and targeted subpopulations.A major strength of the study is the combined use of serological testing and questionnaires. While regular serological testing will help us to model evolution of the pandemic, self-reported data on socioeconomic characteristics, COVID-19-compatible symptoms, and general and mental health will allow us to monitor the progression of the COVID-19 pandemic as well as to thoroughly analyze its effects on several dimensions of health.The longitudinal component of the study will provide insight into the extent and duration of immunity, as well as the long-term impact of the pandemic and the sanitary, social and economic measures associated with it.The main limitation is that Specchio-COVID19 is based on self-reports with a risk of information bias. However, considering the pandemic context, participants are generally engaged to participate and to contribute to COVID-19 research. Further, at least half of the sample is based on random selection in the general population.The study is primarily being conducted online, which may limit the generalizability of the findings, especially for the elderly and vulnerable populations, although internet access is extensive in Switzerland. Nonetheless, participants can use paper questionnaires to contribute to the major assessments.

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.

Inadequate sodium and potassium dietary intakes are associated with major, yet preventable, health consequences. Local public health interventions can be facilitated and informed by fine-scale geospatial analyses. In this study, we assess the existence of spatial clustering (i.e., an unusual concentration of individuals with a specific outcome in space) of estimated sodium (Na), potassium (K) intakes, and Na:K ratio in the Bus Santé 1992–2018 annual population-based surveys, including 22,495 participants aged 20–74 years, residing in the canton of Geneva, using the local Moran’s I spatial statistics. We also investigate whether socio-demographic and food environment characteristics are associated with identified spatial clustering, using both global ordinary least squares (OLS) and local geographically weighted regression (GWR) modeling. We identified clear spatial clustering of Na:K ratio, Na, and K intakes. The GWR outperformed the OLS models and revealed spatial variations in the associations between explanatory and outcome variables. Older age, being a woman, higher education, and having a lower access to supermarkets were associated with higher Na:K ratio, while the opposite was seen for having the Swiss nationality. Socio-demographic characteristics explained a major part of the identified clusters. Socio-demographic and food environment characteristics significantly differed between individuals in spatial clusters of high and low Na:K ratio, Na, and K intakes. These findings could guide prioritized place-based interventions tailored to the characteristics of the identified populations.

Background Evidence suggests that the built environment can influence the intensity of physical activity. However, most of the studies do not consider the geographic context of this association. Studies assessing the spatial dependence of physical activity are limited by an aggregated geographic scale or self-reported physical activity. We aimed to assess individual spatial dependence of objectively measured moderate and vigorous physical activity (MVPA) and describe the characteristics of the built environment among spatial clusters of MVPA. Methods Cross-sectional data from the second follow-up of CoLaus|PsyCoLaus (2014-2017), a longitudinal population-based study of the Lausanne area (Switzerland), was used to objectively measure daily MVPA using accelerometers. We ran Local Moran’s I to assess the spatial dependence of MVPA. This method compares the behavior (MVPA) of participants to that of other individuals located in the same neighborhood. It classifies individuals into four categories: high MVPA clusters, low MVPA clusters, low MVPA outliers in high MVPA clusters, and high MVPA outliers in low MVPA clusters. Additionally, the characteristics of the built environment observed in the clusters based on raw MVPA and MVPA adjusted for socioeconomic and demographic factors were described. Results Data from 1,889 participants (median age 63 years, 55% women) were used. The geographic distribution of MVPA and the characteristics of the built environment among clusters were similar for raw and adjusted MVPA. In the adjusted model, we found a low concentration of individuals within spatial clusters of high MVPA (median: 36.9 mins; 3% of the studied population) and low MVPA (median: 10.1 mins; 2% of the studied population). Yet, clear differences were found in both models between clusters regarding the built environment; High MVPA clusters were located in areas with a higher density of parks, recreational, public, and commercial & industrial areas, preferential pedestrian zones, population density, cycling pathways, public transport accessibility and interconnected streets than low MVPA clusters. Conclusions Although with few individuals within clusters, MVPA clusters were identified. The built environment may influence spatial patterns of MVPA independently of socioeconomic and demographic factors. Interventions in the built environment should be considered to promote physically active behaviors in urban areas.

BACKGROUND The etiology of Parkinson's disease (PD) remains unknown. To approach the issue of PD's risk factors from a new perspective, we hypothesized that coupling the geographic distribution of PD with spatial statistics may provide new insights into environmental epidemiology research. The aim of this case-control study was to examine the spatial dependence of PD prevalence in the Canton of Geneva, Switzerland (population = 474,211). METHODS PD cases were identified through Geneva University Hospitals, private neurologists and nursing homes medical records (n = 1115). Controls derived from a population-based study (n = 12,614) and a comprehensive population census dataset (n = 237,771). All individuals were geographically localized based on their place of residence. Spatial Getis-Ord Gi* statistics were used to identify clusters of high versus low disease prevalence. Confounder-adjustment was performed for age, sex, nationality and income. Tukey's honestly significant difference was used to determine whether nitrogen dioxide and particulate matters PM10 concentrations were different within PD hotspots, coldspots or neutral areas. RESULTS Confounder-adjustment greatly reduced greatly the spatial association. Characteristics of the geographic space influenced PD prevalence in 6% of patients. PD hotspots were concentrated in the urban centre. There was a significant difference in mean annual nitrogen dioxide and PM10 levels (+3.6 μg/m3 [p

Coral reefs are suffering a major decline due to the environmental constraints imposed by climate change. Over the last 20 years, three major coral bleaching events occurred in concomitance of anomalous heat waves, provoking a severe loss of coral cover world-wide. Recent works, however, reported of reefs at which recurrent bleaching events resulted in reduced sensitivity to thermal stresses. Adaptation has been suggested to be responsible for this phenomenon. The conservation strategies for preserving the reefs, as they are conceived now, can not cope with global climatic shifts. In this regard, researchers advocated the set-up of a preservation framework to reinforce coral adaptive potential. The main obstacle to this approach is that studies focusing on coral adaptation usually concern a couple of contrasted reefs and their results are therefore hard to generalize at the scale of a reef system. In this work, we ran a seascape genomics analysis to study adaptation of a flagship coral species of the Ryukyu Archipelago (Japan). By associating genotype frequencies with descriptors of historical environmental conditions, we discovered six polymorphisms that might elicit resistance against thermal stress and calculated the probability of presence of these putative adaptive traits across the whole study area. Furthermore, the seascape genomics method allowed us to calculate a connectivity model based on sea surface currents and calibrated on genetic data. These results were used to compute, for every reef of the Ryukyu Archipelago, indexes describing corals adaptive and connective potential. This information can be extremely useful for preservation, since it provides an objective information on how the adaptive potential distributes and disperse across the reef system. Finally, we provide two examples of how this information can be implemented in conservation strategies commonly used such as the establishment of marine protected areas and coral nurseries. Together, the results of our work advocate the value of genetic analyses for empowering preservation efforts dedicated to the protection of coral reef from warming oceans.

Vast, pristine ecosystems and their biodiversity are vanishing globally at frightening speed, but many large tracts of wilderness have not yet been systematically inventoried and important natural populations of threatened species remain poorly characterized. The forest-savanna ecotone of the Eastern Central African Republic (CAR) is one such poorly studied area. Using camera traps, transect walks and collected fecal samples, we provide the first quantitative survey of chimpanzees (Pan troglodytes) in this region previously classified as a highly important chimpanzee conservation unit. In contrast to species distribution models and expert predictions, we did not find any evidence of chimpanzees in the large and remote forest blocks west of the Chinko River despite considerable search effort. Our study thus highlights the limitations of relying solely on remote sensing data to predict the presence or absence of endangered species and illustrates the necessity of extensive field surveys to accurately assess occurrence and density in remote areas. However, we did discover a sizeable and reproducing population of chimpanzees east of the Chinko River. Based on a density of 0.81chimpanzees/km2 in closed canopy forest that we inferred from nest count data, we estimate 910 weaned chimpanzees to inhabit the Chinko Nature Reserve (CNR) and further predict additional 2700 individuals in adjacent, unmanaged hunting zones and reserves. According to microsatellite data, these chimpanzees genetically cluster with P. t. schweinfurthii populations in East Africa. Conservation action and appropriate management plans are urgently needed to protect this important population and to prevent heavily-armed nomadic pastoralists from the Sahel, illegal miners, as well as elephant and meat poachers, from irretrievably destroying the natural vegetation and local biodiversity of the area.

samβada is a genome-environment association software, designed to search for signatures of local adaptation. However, pre- and postprocessing of data can be labour-intensive, preventing wider uptake of the method. We have now developed R.SamBada, an r-package providing a pipeline for landscape genomic analysis based on samβada, spanning from the retrieval of environmental conditions at sampling locations to gene annotation using the Ensembl genome browser. As a result, R.SamBada standardizes the landscape genomics pipeline and eases the search for candidate genes of local adaptation, enhancing reproducibility of landscape genomic studies. The efficiency and power of the pipeline is illustrated using two examples: sheep populations from Morocco with no evident population structure and Lidia cattle from Spain displaying population substructuring. In both cases, R.SamBada enabled rapid identification and interpretation of candidate genes, which are further discussed in the light of local adaptation. The package is available in the r CRAN package repository and on GitHub (github.com/SolangeD/R.SamBada).

An increasing number of studies are using landscape genomics to investigate local adaptation in wild and domestic populations. The implementation of this approach requires the sampling phase to consider the complexity of environmental settings and the burden of logistic constraints. These important aspects are often underestimated in the literature dedicated to sampling strategies.In this study, we computed simulated genomic datasets to run against actual environmental data in order to trial landscape genomics experiments under distinct sampling strategies. These strategies differed by design approach (to enhance environmental and/or geographic representativeness at study sites), number of sampling locations and sample sizes. We then evaluated how these elements affected statistical performances (power and false discoveries) under two antithetical demographic scenarios.Our results highlight the importance of selecting an appropriate sample size, which should be modified based on the demographic characteristics of the studied population. For species with limited dispersal, sample sizes above 200 units are generally sufficient to detect most adaptive signals, while in random mating populations this threshold should be increased to 400 units. Furthermore, we describe a design approach that maximizes both environmental and geographical representativeness of sampling sites and show how it systematically outperforms random or regular sampling schemes. Finally, we show that although having more sampling locations (between 40 and 50 sites) increase statistical power and reduce false discovery rate, similar results can be achieved with a moderate number of sites (20 sites). Overall, this study provides valuable guidelines for optimizing sampling strategies for landscape genomics experiments.

PurposeLocal physical and social environment has a defining influence on individual behaviour 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).MethodsGeo-referenced individual-level data from the population-based cross-sectional Bus Santé study (n = 5,002) 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 neighbourhood income and individual educational attainment; and demographic factors (age and Swiss nationality). The association between adjusted clusters and the proximity to the nearest screening centre was also evaluated.ResultsMammography 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 = 1,033). Adjustment for age and nationality further reduced the number of individuals exhibiting spatially dependent behaviour (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 centre.ConclusionsSES 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 neighbourhood-level determinants could influence mammography adherence and be the object of targeted public health interventions.

ObjectiveTo identify populations and areas presenting higher consumption of sugar-sweetened beverages (SSB) and their overlap with populations and areas presenting higher body mass index (BMI).DesignCross-sectional population-based study.SettingState of Geneva, Switzerland.Participants15,767 non-institutionalized residents aged between 35 and 74 years (20 and 74 since 2011) of the state of Geneva, Switzerland.Main outcome measuresSpatial indices of sugar-sweetened beverage intake frequency and body mass index. Median regression analysis was used to control for characteristics of patients.ResultsThe SSB intake frequency and the BMI were not randomly distributed across the state. Among the 15,423 participants retained for the analyses, 2,034 (13.2%) were within clusters of high SSB intake frequency and 1,651 (10.7%) was within clusters of low SSB intake frequency, 11,738 (76.1%) showed no spatial dependence. We also identified clusters of BMI, 4,014 (26.0%) participants were within clusters of high BMI and 3,591 (23.3%) were within clusters of low BMI, 7,818 (50.7%) showed no spatial dependence. We found that clusters of SSB intake frequency and BMI overlap in specific areas. 1,719 (11.1%) participants were within high SSB intake frequency and high BMI clusters. After adjustment for covariates (education level, gender, age, nationality, and the median income of the area), the identified clusters persisted and were only slightly attenuated.ConclusionA fine-scale spatial approach allows identifying specific populations and areas presenting higher SSB consumption and, for some areas, higher SSB consumption associated with higher BMI. These findings could guide legislators to develop targeted interventions such as prevention campaigns and pave the way for precision public health.What is already known on this topicThe consumption of sugar-sweetened beverages (SSBs) is an important contributory factor of obesity and obesity-related diseases.SSB consumption varies according to socioeconomic status, which could explain the higher prevalence of obesity in specific areas.SSB taxation faces resistance in many countries due to its potential regressive nature.What this study addsThe spatial analysis of individual-level SSB consumption in the state of Geneva provides a clear identification of populations and areas presenting higher SSB consumption and, for some areas, higher SSB consumption along with higher body mass index (BMI).The results demonstrate the persistence of SSB clustering in the geographic space after adjusting for education level, gender, nationality, age, and neighborhood-level median income.The findings provide guidance for future public health interventions to reduce SSB consumption by better targeting vulnerable populations.

INTRODUCTION: Daytime sleepiness is highly prevalent in the general adult population and has been linked to an increased risk of workplace and vehicle accidents, lower professional performance and poorer health. Despite the established relationship between noise and daytime sleepiness, little research has explored the individual-level spatial distribution of noise-related sleep disturbances. We assessed the spatial dependence of daytime sleepiness and tested whether clusters of individuals exhibiting higher daytime sleepiness were characterized by higher nocturnal noise levels than other clusters. DESIGN AND METHODS: Population-based cross-sectional study, in the city of Lausanne, Switzerland. Sleepiness was measured using the Epworth Sleepiness Scale (ESS) for 3697 georeferenced individuals from the CoLaus|PsyCoLaus cohort (period = 2009-2012). We used the sonBASE georeferenced database produced by the Swiss Federal Office for the Environment to characterize nighttime road traffic noise exposure throughout the city. We used the GeoDa software program to calculate the Getis-Ord Gi* statistics for unadjusted and adjusted ESS in order to detect spatial clusters of high and low ESS values. Modeled nighttime noise exposure from road and rail traffic was compared across ESS clusters. RESULTS: Daytime sleepiness was not randomly distributed and showed a significant spatial dependence. The median nighttime traffic noise exposure was significantly different across the three ESS Getis cluster classes (p

In a simulation study of genotypes conducted over 100 generations for more than 1600 butterfly’s individuals, we evaluate how the increase of anthropogenic fragmentation and reduction of habitat size along urbanisation gradients (from 7% to 59% of impervious land cover) influences genetic diversity and population persistence in butterfly species. We show that in areas characterised by a high urbanisation rate (> 56% impervious land cover), a large decrease of both genetic diversity (loss of 60-80% of initial observed heterozygosity) and population size (loss of 70-90% of individuals) is observed over time. This is confirmed by empirical data available for the mobile butterfly species Pieris rapae in a sub-part of the study area. Comparing simulated data for P. rapae with its normal dispersal ability and with a reduced dispersal ability, we also show that a higher dispersal ability can be an advantage to survive in an urban or highly fragmented environment. The results obtained here suggest that it is of high importance to account for population persistence, and confirm that it is crucial to maintain habitat size and connectivity in the context of land-use planning.

Background and Aims: Knowledge on how climate-induced range shifts might affect natural selection is crucial to understand the evolution of species range. Methods: Using historical demographic perspectives gathered from regional-scale phylogeography on the alpine herb Biscutella laevigata, indirect interferences on gene flow and signature of selection based on AFLP genotyping were compared between local populations persisting at the trailing edge and expanding at the leading edge. Key results: Spatial autocorrelation revealed that gene flow was two times more restricted at the trailing edge and genome scans indicated divergent selection in this persisting population. In contrast, no pattern of selection emerged in the expanding population at the leading edge. Conclusions: Historical effects may determine different architecture of genetic variation and selective patterns within local populations, what is arguably important to understand evolutionary processes acting across the species ranges.

Landscape genomics is a rapidly advancing research field that combines population genomics, landscape ecology, and spatial analytical techniques to explicitly quantify the effects of environmental heterogeneity on neutral and adaptive genetic variation and underlying processes. Landscape genomics has tremendous potential for addressing fundamental and applied research questions in various research fields, including ecology, evolution, and conservation biology. However, the unique combination of different scientific disciplines and analytical approaches also constitute a challenge to most researchers wishing to apply landscape genomics. Here, we present an introductory overview of important concepts and methods used in current landscape genomics. For this, we first define the field and explain basic concepts and methods to capture different hypotheses of landscape influences on neutral genetic variation. Next, we highlight established and emerging genomic tools for quantifying adaptive genetic variation in landscape genomic studies. To illustrate the covered topics and to demonstrate the potential of landscape genomics, we provide empirical examples addressing a variety of research question, i.e., the investigation of evolutionary processes driving population differentiation, the landscape genomics of range expanding species, and landscape genomic patterns in organisms of special interest, including species inhabiting aquatic and terrestrial environments. We conclude by outlining remaining challenges and future research avenues in landscape genomics.

Uncovering the genetic basis of adaptation hinges on the ability to detect loci under selection. However, population genomics outlier approaches to detect selected loci may be inappropriate for clinal populations or those with unclear population structure because they require that individuals be clustered into populations. An alternate approach, landscape genomics, uses individual-based approaches to detect loci under selection and reveal potential environmental drivers of selection. We tested four landscape genomics methods on a simulated clinal population to determine their effectiveness at identifying a locus under varying selection strengths along an environmental gradient. We found all methods produced very low type I error rates across all selection strengths, but elevated type II error rates under "weak" selection. We then applied these methods to an AFLP genome scan of an alpine plant, Campanula barbata, and identified five highly supported candidate loci associated with precipitation variables. These loci also showed spatial autocorrelation and cline patterns indicative of selection along a precipitation gradient. Our results suggest that landscape genomics in combination with other spatial analyses provides a powerful approach for identifying loci potentially under selection and explaining spatially complex interactions between species and their environment.

Population genomic analysis can be an important tool in understanding local adaptation. Identification of potential adaptive loci in such analyses is usually based on the survey of a large genomic dataset in combination with environmental variables. Phenotypic data are less commonly incorporated into such studies, although combining a genome scan analysis with a phenotypic trait analysis can greatly improve the insights obtained from each analysis individually. Here, we aimed to identify loci potentially involved in adaptation to climate in 283 Loblolly pine (Pinus taeda) samples from throughout the species’ range in the southeastern United States. We analyzed associations between phenotypic, molecular, and environmental variables from datasets of 3082 single nucleotide polymorphism (SNP) loci and 3 categories of phenotypic traits (gene expression, metabolites, and whole-plant traits). We found only 6 SNP loci that displayed potential signals of local adaptation. Five of the 6 identified SNPs are linked to gene expression traits for lignin development, and 1 is linked with whole-plant traits. We subsequently compared the 6 candidate genes with environmental variables and found a high correlation in only 3 of them (R2 > 0.2). Our study highlights the need for a combination of genotypes, phenotypes, and environmental variables, and for an appropriate sampling scheme and study design, to improve confidence in the identification of potential candidate genes.

Iranian livestock diversity is still largely unexplored, in spite of the interest in the populations historically reared in this country located near the Fertile Crescent, a major livestock domestication centre. In this investigation, the genetic diversity and differentiation of 10 Iranian indigenous fat-tailed sheep breeds were investigated using 18 microsatellite markers. Iranian breeds were found to host a high level of diversity. This conclusion is substantiated by the large number of alleles observed across loci (average 13.83, range 7-22) and by the high within-breed expected heterozygosity (average 0.75, range 0.72-0.76). Iranian sheep have a low level of genetic differentiation, as indicated by the analysis of molecular variance, which allocated a very small proportion (1.67%) of total variation to the between-population component, and by the small fixation index (FST = 0.02). Both Bayesian clustering and principal coordinates analysis revealed the absence of a detectable genetic structure. Also, no isolation by distance was observed through comparison of genetic and geographical distances. In spite of high within-breed variation, signatures of inbreeding were detected by the FIS indices, which were positive in all and statistically significant in three breeds. Possible factors explaining the patterns observed, such as considerable gene flow and inbreeding probably due to anthropogenic activities in the light of population management and conservation programmes, are discussed.

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 neighborhood- and individual-level characteristics. DESIGN Cohort study SETTING Swiss general urban population PARTICIPANTS 6,481 geo-referenced individuals from the CoLaus cohort at baseline (age range 35–74 years, period=2003-2006) and 4,460 at follow-up (period=2009-2012). OUTCOME MEASURES Body weight and height were measured by trained health care professionals with participants standing without shoes in light indoor clothing. BMI was calculated as weight (kg) divided by height squared (m2). 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 neighborhood-level income but not individual-level characteristics. Similar results were observed among participants who developed obesity. CONCLUSIONS To 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 neighborhood-level income. ARTICLE SUMMARY STRENGTHS AND LIMITATIONS OF THE STUDY • As far as we know, this is the first study to report the persistence of spatial clusters of high BMI values over a 5-year period in adults from a general population • The observed east to west pattern of BMI clustering fits known socio-economic and ethno-cultural differences distinguishing these opposite regions of the city of Lausanne, Switzerland • A consequence of the social policy applied by the city is likely to fix populations with modest income in subsidized housing located in specific areas • While recruitment methods of the CoLaus study aimed at collecting information on a representative sample of the general population, adult participants and non-participants to the CoLaus study may differ and participation bias cannot be excluded • We considered several individual-level covariates but data on individual income was missing. We used instead the median income of the including city statistical sector.

Understanding the genetic basis of species adaptation in the context of global change poses one of the greatest challenges of this century. Although we have begun to understand the molecular basis of adaptation in those species for which whole genome sequences are available, the molecular basis of adaptation is still poorly understood for most non-model species. In this paper, we outline major challenges and future research directions for correlating environmental factors with molecular markers to identify adaptive genetic variation, and point to research gaps in the application of landscape genetics to real-world problems arising from global change, such as the ability of organisms to adapt over rapid time scales. High throughput sequencing generates vast quantities of molecular data to address the challenge of studying adaptive genetic variation in non-model species. Here, we suggest that improvements in the sampling design should consider spatial dependence among sampled individuals. Then, we describe available statistical approaches for integrating spatial dependence into landscape analyses of adaptive genetic variation.

Past studies conducted in urban areas analyzed the impact of the presence of green spaces on public health, and highlighted in particular the psychological benefits of interacting with nature. To investigate a supposed relationship between overweight and dense built environment, we focused on the State of Geneva, Switzerland, and calculated the correlation between Body Mass Index (BMI) in a representative sample of 6663 adults and the percentage of natural areas at the locations where these individuals were living. To this end, we used population-based health data from the “Bus Sante” study (Geneva University Hospitals) and multi-scale land cover maps obtained by means of satellite images and LiDAR data classification. We found little correlation between BMI (as a proxy for health) and land cover data and were not able to verify the working hypothesis at local and regional scales. However, an important phenomenon highlighted here is the difference in the results obtained between the city center and the whole State.

Made available in DSpace on 2014-12-03T13:10:41Z (GMT). No. of bitstreams: 0 Previous issue date: 2014-04-17Bitstream added on 2014-12-03T13:23:06Z : No. of bitstreams: 1 WOS000336933100001.pdf: 1869434 bytes, checksum: 328036103331f0bb6f07c771ed0c43d0 (MD5) International Atomic Energy Agency Agricultural Biotechnology Research Institute of Iran-North branch Background: Iran is an area of particular interest for investigating goat diversity. Archaeological remains indicate early goat domestication (about 10 000 years ago) in the Iranian Zagros Mountains as well as in the high Euphrates valley and southeastern Anatolia. In addition, mitochondrial DNA data of domestic goats and wild ancestors (C. aegagrusor bezoar) suggest a pre-domestication management of wild populations in southern Zagros and central Iranian Plateau. In this study genetic diversity was assessed in seven Iranian native goat breeds, namely Markhoz, Najdi, Taleshi, Khalkhali, Naini, native Abadeh and Turki-Ghashghaei. A total of 317 animals were characterized using 14 microsatellite loci. Two Pakistani goat populations, Pahari and Teddy, were genotyped for comparison.Results: Iranian goats possess a remarkable genetic diversity (average expected heterozygosity of 0.671 across loci, 10.7 alleles per locus) mainly accounted for by the within-breed component (G(ST) = 5.9%). Positive and highly significant F-IS values in the Naini, Turki-Ghashghaei, Abadeh and Markhoz breeds indicate some level of inbreeding in these populations. Multivariate analyses cluster Iranian goats into northern, central and western groups, with the western breeds relatively distinct from the others. Pakistani breeds show some relationship with Iranian populations, even if their position is not consistent across analyses. Gene flow was higher within regions (west, north, central) compared to between regions but particularly low between the western and the other two regions, probably due to the isolating topography of the Zagros mountain range. The Turki-Ghashghaei, Najdi and Abadeh breeds are reared in geographic areas where mtDNA provided evidence of early domestication. These breeds are highly variable, located on basal short branches in the neighbor-joining tree, close to the origin of the principal component analysis plot and, although highly admixed, they are quite distinct from those reared on the western side of the Zagros mountain range.Conclusions: These observations call for further investigation of the nuclear DNA diversity of these breeds within a much wider geographic context to confirm or re-discuss the current hypothesis (based on maternal lineage data) of an almost exclusive contribution of the eastern Anatolian bezoar to the domestic goat gene pool. ABRII, North Branch, Rasht 416354115, Iran Karakoram Int Univ, Dept Biol Sci, Gilgit, Pakistan Univ Tehran, Sch Biol, Tehran 141556455, Iran Univ Tehran, Ctr Excellence Phylogeny Living Organisms, Tehran 141556455, Iran Norwegian Univ Sci & Technol, Dept Biol, N-7491 Trondheim, Norway Food & Agr Org United Nat, Anim Prod & Hlth Div, I-00153 Rome, Italy Ecole Polytech Fed Lausanne, Lab Geog Informat Syst, Sch Civil & Environm Engn ENAC, CH-1015 Lausanne, Switzerland Univ Cattolica Sacro Cuore, Ist Zootecn & Biodivers & Ancient DNA BioDNA Res, Piacenza, Italy Univ Estadual Paulista, Dept Apoio, Lab Bioquim & Biol Mol Anim, Aracatuba, Brazil IAEA, Anim Prod & Hlth Sect, A-1400 Vienna, Austria Univ Estadual Paulista, Dept Apoio, Lab Bioquim & Biol Mol Anim, Aracatuba, Brazil International Atomic Energy AgencyD3.10.25

Foreigners in Switzerland: Issues and territorial realities. The article aims to clarify certain ideas on the territorial aspects of xenophobia in Switzerland, at the national, regional and local levels. Statistical data on the structure of the Swiss population since 1950, together with the most recent of the popular polls on Swiss policy towards immigrants, provide valuable geographical insights into the current debate and help identify more clearly the underlying themes of identity, immigration, integration and, more generally, the multicultural societies of today and tomorrow. The statistical tool should not be used, however, without careful consideration being given to the ever-present risks of interpretation and over-simplified schématisation. At a moment when the first data from the ten-year Swiss census are available, it is well to remember that the control of numbers is the key to population policies and may, in addition, contribute to a clarification of the social and political debate., Résumé: cette contribution voudrait fixer quelques idées sur les aspects territoriaux de l'expression xénophobe au plan national, régional et local. Les données statistiques relatives aux structures de la population depuis 1950, mais aussi les scrutins populaires les plus récents sur le thème de la politique suisse des étrangers, apportent un éclairage géographique au débat actuel et contribuent à mieux cerner les thèmes sous-jacents de l'identité, de l'immigration, de l'intégration voire, plus largement encore, des sociétés multiculturelles d'aujourd'hui et de demain. L'éloge de la statistique ne doit cependant pas faire oublier les risques d'interprétation et de schématisation, toujours réels. Au moment où les premiers chiffres du recensement décennal en Suisse sont publiés, on doit rappeler que la maîtrise du nombre est à la clé des politiques de population et peut, par ailleurs, contribuer à clarifier le débat politique et social., Hussy Charles, Crivelli Ruggero, Joost Stéphane, Métral Grégoire. La présence étrangère en Suisse. Enjeux et réalités territoriales. In: Revue de géographie alpine, tome 90, n°3, 2002. pp. 81-98.

BACKGROUND: Body mass index (BMI) may cluster in space among adults and be spatially dependent. Whether BMI clusters among children and how age-specific BMI clusters are related remains unknown. We aimed to identify and compare the spatial dependence of BMI in adults and children in a Swiss general population, taking into account the area's income level. METHODS: Geo-referenced data from the Bus Santé study (adults, n=6663) and Geneva School Health Service (children, n=3601) were used. We implemented global (Moran's I) and local (local indicators of spatial association (LISA)) indices of spatial autocorrelation to investigate the spatial dependence of BMI in adults (35-74 years) and children (6-7 years). Weight and height were measured using standardized procedures. Five spatial autocorrelation classes (LISA clusters) were defined including the high-high BMI class (high BMI participant's BMI value correlated with high BMI-neighbors' mean BMI values). The spatial distributions of clusters were compared between adults and children with and without adjustment for area's income level. RESULTS: In both adults and children, BMI was clearly not distributed at random across the State of Geneva. Both adults' and children's BMIs were associated with the mean BMI of their neighborhood. We found that the clusters of higher BMI in adults and children are located in close, yet different, areas of the state. Significant clusters of high versus low BMIs were clearly identified in both adults and children. Area's income level was associated with children's BMI clusters. CONCLUSIONS: BMI clusters show a specific spatial dependence in adults and children from the general population. Using a fine-scale spatial analytic approach, we identified life course-specific clusters that could guide tailored interventions.

IntroductionSmoking bans were suggested to reduce smoking prevalence and increase quit ratio but their equity impact remains unclear. We aimed to characterise the socioeconomic status (SES)-related inequalities in smoking prevalence and quit ratio before and after the implementation of a public smoking ban.MethodsWe included data from 17 544 participants in the population-based cross-sectional Bus Santé study in Geneva, Switzerland, between 1995 and 2014. We considered educational attainment (primary, secondary and tertiary) as a SES indicator. Outcomes were smoking prevalence (proportion of current smokers) and quit ratio (ex-smokers to ever-smokers ratio). We used segmented linear regression to assess the overall impact of smoking ban on outcome trends. We calculated the relative (RII) and slope (SII, absolute difference) indexes of inequality, quantifying disparities between educational groups in outcomes overall (1995–2014), before and after ban implementation (November 2009).ResultsLeast educated participants displayed higher smoking prevalence (RII=2.04, Pbefore=1.84, Pafter=3.01, Pbefore=0.14, Pafter=0.19, Pbefore=−0.15, Pafter=−0.27, PConclusionsImplementation of a public smoking ban coincided with a short-lived decrease in smoking prevalence and increase in quit ratio but also with a widening in SES inequalities in smoking-related outcomes.

International audience; Since the time of their domestication, goats (Capra hircus) have evolved in a large variety of locally adapted populations in response to different human and environmental pressures. In the present era, many indigenous populations are threatened with extinction due to their substitution by cosmopolitan breeds, while they might represent highly valuable genomic resources. It is thus crucial to characterize the neutral and adaptive genetic diversity of indigenous populations. A fine characterization of whole genome variation in farm animals is now possible by using new sequencing technologies. We sequenced the complete genome at 12× coverage of 44 goats geographically representative of the three phenotypically distinct indigenous populations in Morocco. The study of mitochondrial genomes showed a high diversity exclusively restricted to the haplogroup A. The 44 nuclear genomes showed a very high diversity (24 million variants) associated with low linkage disequilibrium. The overall genetic diversity was weakly structured according to geography and phenotypes. When looking for signals of positive selection in each population we identified many candidate genes, several of which gave insights into the metabolic pathways or biological processes involved in the adaptation to local conditions (e.g., panting in warm/desert conditions). This study highlights the interest of WGS data to characterize livestock genomic diversity. It illustrates the valuable genetic richness present in indigenous populations that have to be sustainably managed and may represent valuable genetic resources for the long-term preservation of the species.