{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T11:21:45Z","timestamp":1777375305981,"version":"3.51.4"},"reference-count":23,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2017,6,1]],"date-time":"2017-06-01T00:00:00Z","timestamp":1496275200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/100004960","name":"Minnesota Department of Transportation","doi-asserted-by":"publisher","award":["NS-326"],"award-info":[{"award-number":["NS-326"]}],"id":[{"id":"10.13039\/100004960","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Am J Health Promot"],"published-print":{"date-parts":[[2018,3]]},"abstract":"<jats:sec>\n                    <jats:title>Purpose:<\/jats:title>\n                    <jats:p>This study describes the association between frequency of bicycling for active transportation and modifiable cardiometabolic risk factors in the Minneapolis\u2013Saint Paul (MSP) metropolitan area.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design:<\/jats:title>\n                    <jats:p>We conducted an online survey from a convenience sample of likely bicycle commuters.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Setting:<\/jats:title>\n                    <jats:p>Participants were e-mailed invitations including a link to the online survey.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Participants:<\/jats:title>\n                    <jats:p>Participants (n = 1450, 15.6% response rate) were residents of the 7-county MSP metropolitan area aged 20 to 64 years.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Measures:<\/jats:title>\n                    <jats:p>Participants reported frequency of commute and destination cycling from April to September and October to March, prevalent cardiometabolic risk factors, and demographic covariates.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Analysis:<\/jats:title>\n                    <jats:p>We performed logistic regressions for associations between average weekly transportation bicycling and self-reported prevalent obesity, high blood pressure, high cholesterol, low high-density lipoprotein cholesterol, and high triglycerides. We used Poisson regression for the count of cardiometabolic risk factors. All models were adjusted for age, sex, race, smoking, alcohol consumption, and other physical activity, with random intercepts by zip code.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>Self-reported bicycling frequency is associated with significantly lower odds of prevalent obesity, hypertension, and high triglycerides. Three bicycling trips per week is associated with 20% fewer (95% confidence interval: 12%-28%) cardiometabolic risk factors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>Bicycling frequency is inversely associated with cardiometabolic risk factors. These results provide empirical support for the promotion of active transportation as public health policy.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/0890117117710735","type":"journal-article","created":{"date-parts":[[2017,6,1]],"date-time":"2017-06-01T06:33:22Z","timestamp":1496298802000},"page":"631-637","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":18,"title":["Associations Between Bicycling for Transportation and Cardiometabolic Risk Factors Among Minneapolis\u2013Saint Paul Area Commuters: A Cross-Sectional Study in Working-Age Adults"],"prefix":"10.1177","volume":"32","author":[{"given":"Aaron T.","family":"Berger","sequence":"first","affiliation":[{"name":"Division of Epidemiology and Community Health, University of Minnesota, Twin Cities, Minneapolis MN, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinyi (Lisa)","family":"Qian","sequence":"additional","affiliation":[{"name":"Tourism Center, University of Minnesota, Twin Cities, St Paul, MN, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mark A.","family":"Pereira","sequence":"additional","affiliation":[{"name":"Division of Epidemiology and Community Health, University of Minnesota, Twin Cities, Minneapolis MN, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2017,6,1]]},"reference":[{"key":"bibr1-0890117117710735","unstructured":"League of American Bicyclists. 2015 Bicycle Friendly State\n                      SM\n                      ranking. 2015. http:\/\/bikeleague.org\/sites\/default\/files\/2015_state_ranking_chart.pdf. Accessed May 15, 2017."},{"key":"bibr2-0890117117710735","doi-asserted-by":"publisher","DOI":"10.1016\/j.tra.2011.03.001"},{"key":"bibr3-0890117117710735","unstructured":"Musiker R. Minneapolis tops San Francisco, Portland as most bikeable city of 2015. 2015. https:\/\/www.redfin.com\/blog\/2015\/05\/most-bikeable-cities.html. Accessed May 15, 2017."},{"key":"bibr4-0890117117710735","unstructured":"Health Economics Program, Minnesota Department of Health. Chronic conditions in Minnesota: new estimates of prevalence, cost and geographic variation for insured Minnesotans, 2012. 2016. http:\/\/www.health.state.mn.us\/divs\/hpsc\/hep\/publications\/costs\/20160127_chronicconditions.pdf. Accessed May 15, 2017."},{"key":"bibr5-0890117117710735","doi-asserted-by":"publisher","DOI":"10.1038\/oby.2011.169"},{"key":"bibr6-0890117117710735","volume-title":"Epidemiology and Prevention of Cardiovascular Diseases","author":"Labarthe DR","year":"2010","edition":"2"},{"key":"bibr7-0890117117710735","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa012512"},{"key":"bibr8-0890117117710735","doi-asserted-by":"publisher","DOI":"10.1139\/h06-113"},{"key":"bibr9-0890117117710735","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.pu.08.050187.001345"},{"key":"bibr10-0890117117710735","doi-asserted-by":"crossref","unstructured":"Whitfield GP, Paul P, Wendel AM. Active transportation surveillance\u2014United States, 1999-2012. MMWR Surveill Summ. 2015;64(7):1\u201317. http:\/\/www.cdc.gov\/mmwr\/pdf\/ss\/ss6407.pdf. Accessed May 15, 2017.","DOI":"10.15585\/mmwr.ss6407a1"},{"key":"bibr11-0890117117710735","doi-asserted-by":"publisher","DOI":"10.1249\/00003677-199001000-00014"},{"key":"bibr12-0890117117710735","unstructured":"Kahlmeier S, Kelly P, Foster C, Health economic assessment tools (HEAT) for walking and for cycling. Methodology and user guide, 2014 update: economic assessment of transport infrastructure and policies. 2014. http:\/\/www.euro.who.int\/__data\/assets\/pdf_file\/0010\/256168\/ECONOMIC-ASSESSMENT-OF-TRANSPORT-INFRASTRUCTURE-AND-POLICIES.pdf?ua=1. Accessed May 15, 2017."},{"key":"bibr13-0890117117710735","unstructured":"Development of the Health Economic Assessment Tools (HEAT) for walking and cycling. Consensus workshop: background document. Bonn, 1\u20132 October 2013. Copenhagen, Denmark: WHO Regional Office for Europe; 2013. http:\/\/www.euro.who.int\/__data\/assets\/pdf_file\/0005\/248900\/Development-of-the-health-economic-assessment-tools-HEAT-for-walking-and-cycling.pdf. Accessed May 15, 2017."},{"key":"bibr14-0890117117710735","doi-asserted-by":"publisher","DOI":"10.1016\/j.amepre.2012.06.034"},{"key":"bibr15-0890117117710735","doi-asserted-by":"publisher","DOI":"10.1186\/s12966-015-0223-3"},{"key":"bibr16-0890117117710735","doi-asserted-by":"publisher","DOI":"10.1093\/eurheartj\/ehl475"},{"key":"bibr17-0890117117710735","doi-asserted-by":"publisher","DOI":"10.1080\/15568318.2012.725801"},{"key":"bibr18-0890117117710735","unstructured":"Estimate of 10-year risk for coronary heart disease Framingham point scores. National Heart, Lung and Blood Institute. http:\/\/www.nhlbi.nih.gov\/health-pro\/guidelines\/current\/cholesterol-guidelines\/quick-desk-reference-html\/10-year-risk-framingham-table. Published 2001. Accessed May 15, 2017."},{"key":"bibr19-0890117117710735","unstructured":"How Is Metabolic Syndrome Diagnosed? National Heart, Lung and Blood Institute. http:\/\/www.nhlbi.nih.gov\/health\/health-topics\/topics\/ms\/diagnosis. Published 2016. 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