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      Risk of developing multimorbidity across all ages in an historical cohort study: differences by sex and ethnicity


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          To study the incidence of de novo multimorbidity across all ages in a geographically defined population with an emphasis on sex and ethnic differences.


          Historical cohort study.


          All persons residing in Olmsted County, Minnesota, USA on 1 January 2000 who had granted permission for their records to be used for research (n=123 716).


          We used the Rochester Epidemiology Project medical records-linkage system to identify all of the county residents. We identified and removed from the cohort all persons who had developed multimorbidity before 1 January 2000 (baseline date), and we followed the cohort over 14 years (1 January 2000 through 31 December 2013).

          Main outcome measures

          Incident multimorbidity was defined as the development of the second of 2 conditions (dyads) from among the 20 chronic conditions selected by the US Department of Health and Human Services. We also studied the incidence of the third of 3 conditions (triads) from among the 20 chronic conditions.


          The incidence of multimorbidity increased steeply with older age; however, the number of people with incident multimorbidity was substantially greater in people younger than 65 years compared to people age 65 years or older (28 378 vs 6214). The overall risk was similar in men and women; however, the combinations of conditions (dyads and triads) differed extensively by age and by sex. Compared to Whites, the incidence of multimorbidity was higher in Blacks and lower in Asians.


          The risk of developing de novo multimorbidity increases steeply with older age, varies by ethnicity and is similar in men and women overall. However, as expected, the combinations of conditions vary extensively by age and sex. These data represent an important first step toward identifying the causes and the consequences of multimorbidity.

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          Most cited references22

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          History of the Rochester Epidemiology Project: half a century of medical records linkage in a US population.

          The Rochester Epidemiology Project (REP) has maintained a comprehensive medical records linkage system for nearly half a century for almost all persons residing in Olmsted County, Minnesota. Herein, we provide a brief history of the REP before and after 1966, the year in which the REP was officially established. The key protagonists before 1966 were Henry Plummer, Mabel Root, and Joseph Berkson, who developed a medical records linkage system at Mayo Clinic. In 1966, Leonard Kurland established collaborative agreements with other local health care providers (hospitals, physician groups, and clinics [primarily Olmsted Medical Center]) to develop a medical records linkage system that covered the entire population of Olmsted County, and he obtained funding from the National Institutes of Health to support the new system. In 1997, L. Joseph Melton III addressed emerging concerns about the confidentiality of medical record information by introducing a broad patient research authorization as per Minnesota state law. We describe how the key protagonists of the REP have responded to challenges posed by evolving medical knowledge, information technology, and public expectation and policy. In addition, we provide a general description of the system; discuss issues of data quality, reliability, and validity; describe the research team structure; provide information about funding; and compare the REP with other medical information systems. The REP can serve as a model for the development of similar research infrastructures in the United States and worldwide. Copyright © 2012 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.
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            Generalizability of epidemiological findings and public health decisions: an illustration from the Rochester Epidemiology Project.

            To illustrate the problem of generalizability of epidemiological findings derived from a single population using data from the Rochester Epidemiology Project and from the US Census. We compared the characteristics of the Olmsted County, Minnesota, population with the characteristics of populations residing in the state of Minnesota, the Upper Midwest, and the entire United States. Age, sex, and ethnic characteristics of Olmsted County were similar to those of the state of Minnesota and the Upper Midwest from 1970 to 2000. However, Olmsted County was less ethnically diverse than the entire US population (90.3% vs 75.1% white), more highly educated (91.1% vs 80.4% high school graduates), and wealthier ($51,316 vs $41,994 median household income; 2000 US Census data). Age- and sex-specific mortality rates were similar for Olmsted County, the state of Minnesota, and the entire United States. We provide an example of analyses and comparisons that may guide the generalization of epidemiological findings from a single population to other populations or to the entire United States. Copyright © 2012 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.
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              Use of a medical records linkage system to enumerate a dynamic population over time: the Rochester epidemiology project.

              The Rochester Epidemiology Project (REP) is a unique research infrastructure in which the medical records of virtually all persons residing in Olmsted County, Minnesota, for over 40 years have been linked and archived. In the present article, the authors describe how the REP links medical records from multiple health care institutions to specific individuals and how residency is confirmed over time. Additionally, the authors provide evidence for the validity of the REP Census enumeration. Between 1966 and 2008, 1,145,856 medical records were linked to 486,564 individuals in the REP. The REP Census was found to be valid when compared with a list of residents obtained from random digit dialing, a list of residents of nursing homes and senior citizen complexes, a commercial list of residents, and a manual review of records. In addition, the REP Census counts were comparable to those of 4 decennial US censuses (e.g., it included 104.1% of 1970 and 102.7% of 2000 census counts). The duration for which each person was captured in the system varied greatly by age and calendar year; however, the duration was typically substantial. Comprehensive medical records linkage systems like the REP can be used to maintain a continuously updated census and to provide an optimal sampling framework for epidemiologic studies.

                Author and article information

                BMJ Open
                BMJ Open
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                3 February 2015
                : 5
                : 2
                : e006413
                [1 ]Division of Epidemiology, Department of Health Sciences Research, College of Medicine, Mayo Clinic , Rochester, Minnesota, USA
                [2 ]The Robert D and Patricia E Kern Center for the Science of Health Care Delivery, College of Medicine, Mayo Clinic , Rochester, Minnesota, USA
                [3 ]Division of Geriatric Medicine and Gerontology, Department of Medicine, School of Medicine, Johns Hopkins University , Baltimore, Maryland, USA
                [4 ]Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, College of Medicine, Mayo Clinic , Rochester, Minnesota, USA
                [5 ]Department of Psychiatry and Psychology, College of Medicine, Mayo Clinic , Rochester, Minnesota, USA
                [6 ]Division of Cardiovascular Diseases, Department of Internal Medicine, College of Medicine, Mayo Clinic , Rochester, Minnesota, USA
                [7 ]Department of Research, Olmsted Medical Center , Rochester, Minnesota, USA
                [8 ]Department of Neurology, College of Medicine, Mayo Clinic , Rochester, Minnesota, USA
                Author notes
                [Correspondence to ] Dr Walter A Rocca; rocca@ 123456mayo.edu
                Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions

                This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

                : 19 August 2014
                : 19 December 2014
                : 8 January 2015

                epidemiology,general medicine (see internal medicine),geriatric medicine,preventive medicine,primary care


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