International Journal of Health Geographics最新文献

{"title":"The geospatial and conceptual configuration of the natural environment impacts the association with health outcomes and behavior in children and adolescents.","authors":"Carina Nigg,&nbsp;Claudia Niessner,&nbsp;Alexander Burchartz,&nbsp;Alexander Woll,&nbsp;Jasper Schipperijn","doi":"10.1186/s12942-022-00309-0","DOIUrl":"https://doi.org/10.1186/s12942-022-00309-0","url":null,"abstract":"<p><strong>Background: </strong>Studies investigating associations between natural environments and health outcomes or health behaviors in children and adolescents yielded heterogenous results to date. This may be the result of different geospatial configurations of the natural environment and confounding characteristics of the study population. Thus, we investigated how the relationship between the natural environment and mental health, muscular fitness, and physical activity varies depending on the geospatial configuration of nature and children's and adolescents' characteristics.</p><p><strong>Methods: </strong>Data were derived from the German Motorik-Modul (MoMo) cohort study (2018-2020) that investigates physical activity, muscular fitness, and health parameters in a national sample of children and adolescents (N = 2843) between four and 17 years (M_age = 10.46 ± 3.49 years; 48.3% girls). Mental health was assessed via questionnaire, muscular fitness via standing long jump, and physical activity with 7-day accelerometer measurement. Using geographic information systems, land cover, and land use data, three different nature definitions were applied. Both circular buffers (100-1000 m) and street-network buffers (1000-5000 m) were created for each of the nature definitions. Associations were explored with linear regression models, and interaction analysis was used to investigate how those relationships vary by gender, age, and socio-economic status.</p><p><strong>Results: </strong>The relationship between the three outcomes and the natural environment varied considerably depending on the nature definition, buffer size, and buffer type, as well as socio-demographic characteristics. Specifically, when comparing youth with a high socio-economic status to those with a medium socio-economic status, smaller circular buffer distances were related to less physical activity, but larger street-network buffer distances were related to greater mental health problems. Distinct relationships also occurred for youth with low socio-economic status in those relationships, with the pattern being less clear.</p><p><strong>Conclusions: </strong>For future health research studies that investigate the role of the natural environment, we argue for the development of an a-priori model that integrates both geospatial considerations (nature definition, buffer type, and buffer size) and conceptual considerations (health outcome/behavior, sample characteristics) based on potentially underlying mechanisms that link the natural environment and the health outcome or behavior under investigation to theoretically underpin the geospatial configuration of the natural environment.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":" ","pages":"9"},"PeriodicalIF":4.9,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9366780/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40619080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Regional variation in lifestyle patterns and BMI in young children: the GECKO Drenthe cohort.","authors":"Rikstje Wiersma,&nbsp;Richard H Rijnks,&nbsp;Gianni Bocca,&nbsp;H Marike Boezen,&nbsp;Esther Hartman,&nbsp;Eva Corpeleijn","doi":"10.1186/s12942-022-00302-7","DOIUrl":"https://doi.org/10.1186/s12942-022-00302-7","url":null,"abstract":"<p><strong>Background: </strong>A better understanding of lifestyle behaviours of children < 7 years and the relation with childhood overweight is needed. The aim of our prospective study was to examine how lifestyle patterns in young children are associated with the development of childhood overweight. As ecological models suggest focusing on not only the child as an individual, but also their environment, we also considered the role of socio-economic status (SES) and spatial clustering of lifestyle and body mass index (BMI).</p><p><strong>Methods: </strong>In 1792 children (aged 3-6 years) participating in the GECKO Drenthe cohort, diet, screen time, outdoor play and sleep were assessed by questionnaires and moderate-to-vigorous physical activity and sedentary time by accelerometry (Actigraph GT3X). At 10-11 years, height and weight were measured to calculate age- and sex-specific standardized BMI z-scores (zBMI). Lifestyle patterns were identified using principal component analysis. To assess spatial clustering for the lifestyle patterns and zBMI, we calculated the Global Moran's I statistic. Linear- and logistic regression models, taking into account SES, were performed to examine the association between the lifestyle patterns and the development of overweight. For the spatial analyses, we added spatial terms for the determinants, the outcome, and the error term.</p><p><strong>Results: </strong>Three lifestyle patterns were identified: (1) 'high activity', (2) 'low screen time, high sleep and healthy diet', and (3) 'high outdoor play'. No associations were observed between the 'high activity' or 'high outdoor play' patterns at young age with the development of childhood overweight (all p > 0.05). In contrast, children who adhered to the 'low screen time, high sleep and healthy diet' pattern had lower odds to become overweight and a lower zBMI at 10-11 years (odds ratio [95% CI] = 0.766 [0.65; 0.90]). These findings remained similar after taking SES into account. Regarding the spatial analyses, we found spatial clustering of zBMI, but no spatial clustering of the lifestyle patterns.</p><p><strong>Conclusions: </strong>Low screen time, high sleep duration and a healthy diet cluster into a pattern that seems favourable in the prevention of childhood overweight, independent of individual SES. The spatial analyses suggest that there are likely other neighbourhood factors that contribute to the spatial clustering of childhood overweight.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":" ","pages":"7"},"PeriodicalIF":4.9,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9250228/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40464411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Associations between neighborhood characteristics and dating violence: does spatial scale matter?","authors":"Paul Rodrigues,&nbsp;Martine Hébert,&nbsp;Mathieu Philibert","doi":"10.1186/s12942-022-00306-3","DOIUrl":"https://doi.org/10.1186/s12942-022-00306-3","url":null,"abstract":"<p><strong>Background: </strong>Dating violence (DV) is a public health problem that could have serious repercussions for the health and well-being of a large number of adolescents. Several neighborhood characteristics could influence these behaviors, but knowledge on such influences is still limited. This study aims at (1) evaluating the associations between neighborhood characteristics and DV, and (2) assessing how spatial scale influences the estimations of the latter associations.</p><p><strong>Methods: </strong>The Québec Health Survey of High School Students (2016-2017) was used to describe DV. Neighborhoods were operationalized with polygon-based network buffers of varying sizes (ranging from 250 to 1000 m). Multiple data sources were used to describe neighborhood characteristics: crime rate, alcohol outlet density (on-premises and off-premises), walkability, greenness, green spaces density, and youth organizations density. Gendered-stratified logistic regressions were used for assessing the association between neighborhood characteristics and DV.</p><p><strong>Results: </strong>For boys, off-premises alcohol outlet density (500 m) is associated with an increase in perpetrating psychological DV. Crime rate (500 m) is positively associated with physical or sexual DV perpetration, and crime rate (250 m) is positively associated with physical or sexual DV victimization. Greenness (1000 m) has a protective effect on psychological DV victimization. For girls, walkability (500 m to 1000 m) is associated with a decrease in perpetrating and experiencing psychological DV, and walkability (250 m) is negatively associated with physical or sexual DV victimization.</p><p><strong>Conclusions: </strong>Several neighborhood characteristics are likely to influence DV, and their effects depend on the form of DV, gender, and spatial scale. Public policies should develop neighborhood-level interventions by improving neighborhood living conditions.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":" ","pages":"6"},"PeriodicalIF":4.9,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9210619/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40104641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deviations from typical paths: a novel approach to working with GPS data in the behavioral sciences.","authors":"Karen E Nielsen,&nbsp;Shannon T Mejía,&nbsp;Richard Gonzalez","doi":"10.1186/s12942-022-00305-4","DOIUrl":"https://doi.org/10.1186/s12942-022-00305-4","url":null,"abstract":"<p><strong>Background: </strong>Behavioral science researchers are increasingly collecting detailed location data such as second-by-second GPS tracking on participants due to increased ease and affordability. While intraindividual variability has been discussed in the travel literature for decades, traditional methods designed for studying individual differences in central tendencies limit the extent to which novel questions about variability in lived experiences can be answered. Thus, new methods of quantifying behavior that focus on intraindividual variability are needed to address the context in which the behavior occurs and the location tracking data from which behavior is derived.</p><p><strong>Methods: </strong>We propose deviations from typical paths as a data processing technique to separate individual-level typical travel behavior from a location tracking data set in order to highlight atypical travel behavior as an outcome measure.</p><p><strong>Results: </strong>A simulated data example shows how the method works to produce deviation measures from a location dataset. Analysis of these deviations offers additional insights compared to traditional measures of maximum daily distance from home.</p><p><strong>Conclusions: </strong>This process can be integrated into larger research questions to explore predictors of atypical behavior and potential mechanisms of behavior change.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":" ","pages":"5"},"PeriodicalIF":4.9,"publicationDate":"2022-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9206293/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39986887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A machine learning approach to small area estimation: predicting the health, housing and well-being of the population of Netherlands","authors":"Markus Viljanen, L. Meijerink, L. Zwakhals, J. van de Kassteele","doi":"10.1186/s12942-022-00304-5","DOIUrl":"https://doi.org/10.1186/s12942-022-00304-5","url":null,"abstract":"","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48376797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction: Validation of desk‑based audits using Google Street View® to monitor the obesogenic potential of neighbourhoods in a pediatric sample: a pilot study in the QUALITY cohort","authors":"Jean-Baptiste Roberge, Gisèle Contreras, L. Kakinami, A. Van Hulst, M. Henderson, T. Barnett","doi":"10.1186/s12942-022-00303-6","DOIUrl":"https://doi.org/10.1186/s12942-022-00303-6","url":null,"abstract":"","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2022-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42974822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Validation of desk-based audits using Google Street View® to monitor the obesogenic potential of neighbourhoods in a pediatric sample: a pilot study in the QUALITY cohort","authors":"Jean-Baptiste Roberge, Gisèle Contreras, L. Kakinami, A. Van Hulst, M. Henderson, T. Barnett","doi":"10.1186/s12942-022-00301-8","DOIUrl":"https://doi.org/10.1186/s12942-022-00301-8","url":null,"abstract":"","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2022-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46424912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Light at night and risk of breast cancer: a systematic review and dose-response meta-analysis.","authors":"Teresa Urbano,&nbsp;Marco Vinceti,&nbsp;Lauren A Wise,&nbsp;Tommaso Filippini","doi":"10.1186/s12942-021-00297-7","DOIUrl":"https://doi.org/10.1186/s12942-021-00297-7","url":null,"abstract":"<p><p>Breast cancer is the most common malignancy in women and the second leading cause of cancer death overall. Besides genetic, reproductive, and hormonal factors involved in disease onset and progression, greater attention has focused recently on the etiologic role of environmental factors, including exposure to artificial lighting such as light-at-night (LAN). We investigated the extent to which LAN, including outdoor and indoor exposure, affects breast cancer risk. We performed a systematic review of epidemiological evidence on the association between LAN exposure and breast cancer risk, using a dose-response meta-analysis to examine the shape of the relation. We retrieved 17 eligible studies through September 13, 2021, including ten cohort and seven case-control studies. In the analysis comparing highest versus lowest LAN exposure, we found a positive association between exposure and disease risk (risk ratio [RR] 1.11, 95% confidence interval-CI 1.07-1.15), with comparable associations in case-control studies (RR 1.14, 95% CI 0.98-1.34) and cohort studies (RR 1.10, 95% CI 1.06-1.15). In stratified analyses, risk was similar for outdoor and indoor LAN exposure, while slightly stronger risks were observed for premenopausal women (premenopausal: RR 1.16, 95% CI 1.04-1.28; postmenopausal: 1.07, 95% CI 1.02-1.13) and for women with estrogen receptor (ER) positive breast cancer (ER + : RR 1.09, 95% CI 1.02-1.17; ER-: RR 1.07, 95% CI 0.92-1.23). The dose-response meta-analysis, performed only in studies investigating outdoor LAN using comparable exposure assessment, showed a linear relation up to 40 nW/cm²/sr after which the curve flattened, especially among premenopausal women. This first assessment of the dose-response relation between LAN and breast cancer supports a positive association in selected subgroups, particularly in premenopausal women.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":" ","pages":"44"},"PeriodicalIF":4.9,"publicationDate":"2021-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8520294/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39523212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to: Development of a Web GIS for small-scale detection and analysis of COVID-19 (SARS-CoV-2) cases based on volunteered geographic information for the city of Cologne, Germany, in July/August 2020.","authors":"Fabian Schmidt,&nbsp;Arne Dröge-Rothaar,&nbsp;Andreas Rienow","doi":"10.1186/s12942-021-00295-9","DOIUrl":"https://doi.org/10.1186/s12942-021-00295-9","url":null,"abstract":"","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":" ","pages":"43"},"PeriodicalIF":4.9,"publicationDate":"2021-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8480272/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39471268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Differences in depressive symptoms by rurality in Japan: a cross-sectional multilevel study using different aggregation units of municipalities and neighborhoods (JAGES).","authors":"Mariko Kanamori,&nbsp;Masamichi Hanazato,&nbsp;Daisuke Takagi,&nbsp;Katsunori Kondo,&nbsp;Toshiyuki Ojima,&nbsp;Airi Amemiya,&nbsp;Naoki Kondo","doi":"10.1186/s12942-021-00296-8","DOIUrl":"https://doi.org/10.1186/s12942-021-00296-8","url":null,"abstract":"<p><strong>Background: </strong>Rurality can reflect many aspects of the community, including community characteristics that may be associated with mental health. In this study, we focused on geographical units to address multiple layers of a rural environment. By evaluating rurality at both the municipality and neighborhood (i.e., a smaller unit within a municipality) levels in Japan, we aimed to elucidate the relationship between depression and rurality. To explore the mechanisms linking rurality and depression, we examined how the association between rurality and depression can be explained by community social capital according to geographical units.</p><p><strong>Methods: </strong>We used cross-sectional data from the 2016 wave of the Japan Gerontological Evaluation Study involving 144,822 respondents aged 65 years or older residing in 937 neighborhoods across 39 municipalities. The population density quintile for municipality-level rurality and the quintile for the time required to reach densely inhabited districts for neighborhood-level rurality were used. We calculated the prevalence ratios of depressive symptoms by gender using a three-level (individual, neighborhood, and municipality) Poisson regression. Community social capital was assessed using three components: civic participation, social cohesion, and reciprocity.</p><p><strong>Results: </strong>The prevalence of depressive symptoms was higher in municipalities with lower population density than those with the highest population density; the ratios were 1.22 (95% confidence intervals: 1.15, 1.30) for men and 1.22 (1.13, 1.31) for women. In contrast, when evaluating rurality at the neighborhood level, the prevalence of depressive symptoms was 0.9 times lower for men in rural areas; no such association was observed for women. In rural municipalities, community civic participation was associated with an increased risk of depressive symptoms. In rural neighborhoods, community social cohesion and reciprocity were linked to a lower risk of depressive symptoms.</p><p><strong>Conclusions: </strong>The association between rurality and depression varied according to geographical unit. In rural municipalities, the risk of depression may be higher for both men and women, and the presence of an environment conducive to civic participation may contribute to a higher risk of depression, as observed in this study. The risk of depression in men may be lower in rural neighborhoods in Japan, which may be related to high social cohesion and reciprocity.</p>","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":" ","pages":"42"},"PeriodicalIF":4.9,"publicationDate":"2021-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8474726/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39452735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}