Neighborhood linking social capital as a predictor of lung cancer: A Swedish national cohort study |
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| Affiliation: | 1. Department of Sports Sociology and Health Sciences, Faculty of Sociology, Kyoto Sangyo University, Motoyama, Kamigamo, Kita-ku, Kyoto, 603-8555, Japan;2. Center for Community-Based Health Research and Education, Organization for the Promotion of Project Research, Shimane University, 89-1 Enya-cho, Izumo, Shimane, 693-8501, Japan;3. Center for Primary Health Care Research, Lund University, Clinical Research Centre (CRC), Building 28, Floor 11, Jan Waldenströms gata 35, Skåne University Hospital, SE-205 02, Malmö, Sweden;4. Department of Family Medicine and Department of Community Health and of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1077, New York, NY, 10029, USA;1. Moffitt Cancer Center, Department of Health Outcomes and Behavior, 4115 E. Fowler Ave., Tampa, FL 33617, United States;2. Moffitt Cancer Center, Center for Immunization and Infection Research in Cancer, 12902 USF Magnolia Drive, Tampa, FL 33612, United States;3. Moffitt Cancer Center, Department of Cancer Epidemiology, 12902 USF Magnolia Drive, Tampa, FL 33612, United States;4. Moffitt Cancer Center, Department of Biostatistics and Bioinformatics, 12902 USF Magnolia Drive, Tampa, FL 33612, United States;5. University of South Florida, Department of Family Medicine, 13330 USF Laurel Drive, Tampa, FL 33612, United States;6. University of South Florida, Department of Epidemiology & Biostatistics, 13201 Bruce B Downs Blvd, Tampa, FL 33612, United States;8. University of Florida, Department of Medicine, 1600 SW Archer Rd., Gainesville, FL 32608, United States;9. University of Florida Health, Department of Health Outcomes and Biomedical Informatics, 2004 Mowry Road, Ste 2245, Gainesville, FL 32610, United States;10. University of Florida Health, Cancer Population Sciences, 2004 Mowry Road, Ste 2245, Gainesville, FL 32610, United States;1. Institute of Medical Epidemiology, Biostatistics and Informatics, Medical Faculty, Martin-Luther-University Halle-Wittenberg, Germany;2. Section of Cancer Information, International Agency for Research on Cancer, 150 cours Albert Thomas, 69372 Lyon Cedex 08, France;3. Department of Medicine, University of Zimbabwe School of Medicine, Harare, Zimbabwe;4. Department of Pathology, Maputo Central Hospital, Maputo, Mozambique;5. CTSU, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7FL, United Kingdom;6. African Cancer Registry Network, 267 Banbury Road, Oxford OX2 7HT, United Kingdom;1. Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, United States;2. Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences Durham, NC, United States;3. Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, United States;4. Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, United States;5. Biospecimen Processing Center, University of North Carolina, Chapel Hill, NC, United States;6. Division of Oncology and Center for Childhood Cancer Research, Children’s Hospital of Philadelphia, Philadelphia, PA, United States;7. Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, PA, United States;8. Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States;9. Showers Center for Childhood Cancer and Blood Disorder, Akron Children’s Hospital, Akron, OH, United States;10. Department of Biostatistics, Colleges of Medicine and Public Health & Health Professions, University of Florida, Children’s Oncology Group Statistics & Data Center, Gainesville, FL, United States;11. Department of Otolaryngology, Washington University School of Medicine, St Louis, MO, 63110;1. Centre for Big Data Research in Health, University of New South Wales Sydney, NSW, Australia;2. Centre for Primary Health Care and Equity, University of New South Wales Sydney, NSW, Australia;3. School of Medicine, University of Wollongong, NSW, Australia;4. National Drug and Alcohol Research Centre, University of New South Wales Sydney, NSW, Australia;5. Faculty of Medicine and Health, University of Sydney, NSW, Australia;6. Cancer Voices NSW, NSW, Australia;1. Univ. Bordeaux, Gironde General Cancer Registry, 33000, Bordeaux, France;2. Inserm, Bordeaux Population Health, Research Center U1219, Team Epicene, 33000, Bordeaux, France;3. Univ. Bordeaux, ISPED, 33000, Bordeaux, France;4. Medical Information Service, Public Health Department, Bordeaux University Hospital, 33000, Bordeaux, France;5. Gironde Screening Coordination Structure, 33700, Mérignac, France;6. Department of Medical Oncology, Institut Bergonié, 33000, Bordeaux, France;7. Clinical Investigation Center and Clinical Epidemiology, Inserm CIC1401, Institut Bergonié, 33000, Bordeaux, France;1. Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, The Capital Region, Nordre Fasanvej 57, 2000, Frederiksberg, Denmark;2. Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, Bethesda, MD, 20892-9778, USA;3. Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, University of Copenhagen, Blegdamsvej 3B, 2200, Copenhagen, Denmark |
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| Abstract: | BackgroundThe aim of this nationwide follow-up study was to examine whether neighborhood linking social capital is associated with lung cancer, including incident and mortality cases, after adjustment for individual- and familial-level factors.MethodsThis follow-up study comprised 2,123,707 men and 2,046,174 women aged 25 years or older in Sweden. The follow-up period started on January 1, 2002 and proceeded until first incident of lung cancer, mortality of lung cancer, death from any other cause, emigration or the end of the study period on December 31, 2010. Multilevel logistic regression models (individual-level factors at the first level and neighborhood-level factors at the second level) were used to calculate odds ratios (ORs) with 95% confidence intervals (95% CIs).ResultsWe identified 16,561 lung cancer cases (8422 men and 8139 women) during the follow-up period. Higher ORs of lung cancer, including incident and mortality cases, were observed in individuals who lived in neighborhoods with low social capital (men: OR = 1.37, 95% CI = 1.27–1.47; women: OR = 1.32, 95% CI = 1.23–1.42) than in those living in neighborhoods with high social capital, after adjustment for potential confounding factors.ConclusionThe results of this large national cohort study suggest that neighborhood linking social capital has important independent effects on lung cancer, including incident and mortality cases. These findings indicate that decision-makers must consider the effect of neighborhood-level factors as well as individual- and familial-level factors. |
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| Keywords: | Social capital Lung cancer Follow-up study Multilevel analysis |
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