81
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Linking of Primary Care Records to Census Data to Study the Association between Socioeconomic Status and Cancer Incidence in Southern Europe: A Nation-Wide Ecological Study

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Area-based measures of economic deprivation are seldom applied to large medical records databases to establish population-scale associations between deprivation and disease.

          Objective

          To study the association between deprivation and incidence of common cancer types in a Southern European region.

          Methods

          Retrospective ecological study using the SIDIAP (Information System for the Development of Research in Primary Care) database of longitudinal electronic medical records for a representative population of Catalonia (Spain) and the MEDEA index based on urban socioeconomic indicators in the Spanish census. Study outcomes were incident cervical, breast, colorectal, prostate, and lung cancer in 2009–2012. The completeness of SIDIAP cancer recording was evaluated through linkage of a geographic data subset to a hospital cancer registry. Associations between MEDEA quintiles and cancer incidence was evaluated using zero-inflated Poisson regression adjusted for sex, age, smoking, alcoholism, obesity, hypertension, and diabetes.

          Results

          SIDIAP sensitivity was 63% to 92% for the five cancers studied. There was direct association between deprivation and lung, colorectal, and cervical cancer: incidence rate ratios (IRR) 1.82 [1.64–2.01], IRR 1.60 [1.34–1.90], IRR 1.22 [1.07–1.38], respectively, comparing the most deprived to most affluent areas. In wealthy areas, prostate and breast cancers were more common: IRR 0.92 [0.80–1.00], IRR 0.91 [0.78–1.06]. Adjustment for confounders attenuated the association with lung cancer risk (fully adjusted IRR 1.16 [1.08–1.25]), reversed the direction of the association with colorectal cancer (IRR 0.90 [0.84–0.95]), and did not modify the associations with cervical (IRR 1.27 [1.11–1.45]), prostate (0.74 [0.69–0.80]), and breast (0.76 [0.71–0.81]) cancer.

          Conclusions

          Deprivation is associated differently with the occurrence of various cancer types. These results provide evidence that MEDEA is a useful, area-based deprivation index for analyses of the SIDIAP database. This information will be useful to improve screening programs, cancer prevention and management strategies, to reach patients more effectively, particularly in deprived urban areas.

          Related collections

          Most cited references24

          • Record: found
          • Abstract: found
          • Article: not found

          Socioeconomic differences in alcohol-attributable mortality compared with all-cause mortality: a systematic review and meta-analysis.

          Factors underlying socioeconomic inequalities in mortality are not well understood. This study contributes to our understanding of potential pathways to result in socioeconomic inequalities, by examining alcohol consumption as one potential explanation via comparing socioeconomic inequalities in alcohol-attributable mortality and all-cause mortality. Web of Science, MEDLINE, PsycINFO and ETOH were searched systematically from their inception to second week of February 2013 for articles reporting alcohol-attributable mortality by socioeconomic status, operationalized by using information on education, occupation, employment status or income. The sex-specific ratios of relative risks (RRRs) of alcohol-attributable mortality to all-cause mortality were pooled for different operationalizations of socioeconomic status using inverse-variance weighted random effects models. These RRRs were then combined to a single estimate. We identified 15 unique papers suitable for a meta-analysis; capturing about 133 million people, 3 741 334 deaths from all causes and 167 652 alcohol-attributable deaths. The overall RRRs amounted to RRR = 1.78 (95% confidence interval (CI) 1.43 to 2.22) and RRR = 1.66 (95% CI 1.20 to 2.31), for women and men, respectively. In other words: lower socioeconomic status leads to 1.5-2-fold higher mortality for alcohol-attributable causes compared with all causes. Alcohol was identified as a factor underlying higher mortality risks in more disadvantaged populations. All alcohol-attributable mortality is in principle avoidable, and future alcohol policies must take into consideration any differential effect on socioeconomic groups. © The Author 2014; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Comparison of the information provided by electronic health records data and a population health survey to estimate prevalence of selected health conditions and multimorbidity

            Background Health surveys (HS) are a well-established methodology for measuring the health status of a population. The relative merit of using information based on HS versus electronic health records (EHR) to measure multimorbidity has not been established. Our study had two objectives: 1) to measure and compare the prevalence and distribution of multimorbidity in HS and EHR data, and 2) to test specific hypotheses about potential differences between HS and EHR reporting of diseases with a symptoms-based diagnosis and those requiring diagnostic testing. Methods Cross-sectional study using data from a periodic HS conducted by the Catalan government and from EHR covering 80% of the Catalan population aged 15 years and older. We determined the prevalence of 27 selected health conditions in both data sources, calculated the prevalence and distribution of multimorbidity (defined as the presence of ≥2 of the selected conditions), and determined multimorbidity patterns. We tested two hypotheses: a) health conditions requiring diagnostic tests for their diagnosis and management would be more prevalent in the EHR; and b) symptoms-based health problems would be more prevalent in the HS data. Results We analysed 15,926 HS interviews and 1,597,258 EHRs. The profile of the EHR sample was 52% women, average age 47 years (standard deviation: 18.8), and 68% having at least one of the selected health conditions, the 3 most prevalent being hypertension (20%), depression or anxiety (16%) and mental disorders (15%). Multimorbidity was higher in HS than in EHR data (60% vs. 43%, respectively, for ages 15-75+, P <0.001, and 91% vs. 83% in participants aged ≥65 years, P <0.001). The most prevalent multimorbidity cluster was cardiovascular. Circulation disorders (other than varicose veins), chronic allergies, neck pain, haemorrhoids, migraine or frequent headaches and chronic constipation were more prevalent in the HS. Most symptomatic conditions (71%) had a higher prevalence in the HS, while less than a third of conditions requiring diagnostic tests were more prevalent in EHR. Conclusions Prevalence of multimorbidity varies depending on age and the source of information. The prevalence of self-reported multimorbidity was significantly higher in HS data among younger patients; prevalence was similar in both data sources for elderly patients. Self-report appears to be more sensitive to identifying symptoms-based conditions. A comprehensive approach to the study of multimorbidity should take into account the patient perspective.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              The association of sexual behaviors with socioeconomic status, family structure, and race/ethnicity among US adolescents.

              This study assessed the relation of socioeconomic status (SES), family structure, and race/ethnicity to adolescent sexual behaviors that are key determinants of pregnancy and sexually transmitted diseases (STDs). The 1992 Youth Risk Behavior Survey/Supplement to the National Health Interview Survey provided family data from household adults and behavioral data from adolescents. Among male and female adolescents, greater parental education, living in a 2-parent family, and White race were independently associated with never having had sexual intercourse. Parental education did not show a linear association with other behaviors. Household income was not linearly related to any sexual behavior. Adjustment for SES and family structure had a limited effect on the association between race/ethnicity and sexual behaviors. Differences in adolescent sexual behavior by race and SES were not large enough to fully explain differences in rates of pregnancy and STD infection. This suggests that other factors, including access to health services and community prevalence of STDs, may be important mediating variables between SES and STD transmission and pregnancy among adolescents.
                Bookmark

                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                20 October 2014
                : 9
                : 10
                : e109706
                Affiliations
                [1 ]Research Unit, Family Medicine, Girona, Spain, and Jordi Gol Institute for Primary Care Research (IDIAP Jordi Gol), Catalunya, Spain
                [2 ]Translab Research Group, Department of Medical Sciences, School of Medicine, University of Girona, Catalunya, Spain
                [3 ]Jordi Gol Institute for Primary Care Research (IDIAP Jordi Gol), Catalunya, Spain
                [4 ]Cancer Prevention Unit and Cancer Registry, Department of Epidemiology and Evaluation, Hospital del Mar, Barcelona, Catalunya, Spain
                [5 ]Primary Care Services, Girona, Spain, and Catalan Institute of Health (ICS), Catalunya, Spain
                [6 ]Primary Care Information System, Catalan Institute of Health (ICS), Catalunya, Spain
                [7 ]Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, United Kingdom
                Federico II University of Naples, Italy
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: MGG DPA. Performed the experiments: MGG JME. Analyzed the data: MGG JME MB MC JB. Contributed reagents/materials/analysis tools: MGG JME MB MC JB. Contributed to the writing of the manuscript: MGG DPA. Interpretation of data: MGG DPA JME RR LMB EH BB. Revision: MGG DPA JME RR LMB EH BB MB. Final approval: MGG DPA JME RR LMB EH BB MB MC JB.

                Article
                PONE-D-14-18648
                10.1371/journal.pone.0109706
                4203762
                25329578
                e5e192dd-186d-45d6-b22f-e678613a754c
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 29 April 2014
                : 5 September 2014
                Page count
                Pages: 7
                Funding
                The authors have no support or funding to report.
                Categories
                Research Article
                Medicine and Health Sciences
                Epidemiology
                Cancer Epidemiology
                Epidemiological Methods and Statistics
                Social Epidemiology
                Custom metadata
                The authors confirm that all data underlying the findings are fully available without restriction. All relevant data are within the paper and its supporting information files.

                Uncategorized
                Uncategorized

                Comments

                Comment on this article