Elsevier

Mayo Clinic Proceedings

Volume 89, Issue 10, October 2014, Pages 1336-1349
Mayo Clinic Proceedings

Original article
Prevalence of Multimorbidity in a Geographically Defined American Population: Patterns by Age, Sex, and Race/Ethnicity

https://doi.org/10.1016/j.mayocp.2014.07.010Get rights and content

Abstract

Objective

To describe the prevalence of multimorbidity involving 20 selected chronic conditions in a geographically defined US population, emphasizing age, sex, and racial/ethnic differences.

Patients and Methods

Using the Rochester Epidemiology Project records linkage system, we identified all residents of Olmsted County, Minnesota, on April 1, 2010, and electronically extracted the International Classification of Diseases, Ninth Revision codes associated with all health care visits made between April 1, 2005, and March 31, 2010 (5-year capture frame). Using these codes, we defined the 20 common chronic conditions recommended by the US Department of Health and Human Services. We counted only persons who received at least 2 codes for a given condition separated by more than 30 days, and we calculated the age-, sex-, and race/ethnicity-specific prevalence of multimorbidity.

Results

Of the 138,858 study participants, 52.4% were women (n=72,732) and 38.9% had 1 or more conditions (n=54,012), 22.6% had 2 or more conditions (n=31,444), and 4.9% had 5 or more conditions (n=6853). The prevalence of multimorbidity (≥2 conditions) increased steeply with older age and reached 77.3% at 65 years and older. However, the absolute number of people affected by multimorbidity was higher in those younger than 65 years. Although the prevalence of multimorbidity was similar in men and women overall, the most common dyads and triads of conditions varied by sex. Compared with white persons, the prevalence of multimorbidity was slightly higher in black persons and slightly lower in Asian persons.

Conclusion

Multimorbidity is common in the general population; it increases steeply with older age, has different patterns in men and women, and varies by race/ethnicity.

Section snippets

Study Population

Most medical care in Olmsted County, Minnesota, has been provided historically and is currently provided by a few health care institutions: Olmsted Medical Center and its affiliated hospital, Mayo Clinic and its two affiliated hospitals, Rochester Family Medicine Clinic, and a few smaller care facilities. The health care records from these institutions are linked together through the REP records linkage system.12, 13, 14 Persons are considered residents of Olmsted County at the time of each

Description of the Olmsted County Population

Overall, the REP infrastructure identified 142,992 Olmsted County residents on April 1, 2010, compared with 144,248 individuals counted by the US Census on the same day.23 Of 142,992 residents, 138,858 provided Minnesota research authorization for medical record research (97.1%) and were included in the analyses. Figure 1 and Supplemental Table 2 (available online at http://www.mayoclinicproceedings.org) show the age- and sex-specific prevalence of each of the 20 conditions considered

Principal Findings

In this study, multimorbidity was common, increased steeply with older age, and was similar in men and women overall. However, more men than women had 5 or more conditions. Despite the traditional focus on multimorbidity in the older adult population,5, 8, 9, 10, 11 the absolute number of persons affected by multimorbidity was higher in persons younger than 65 years than in those 65 years or older. Multimorbidity was also higher in blacks than in white persons and in white than in Asian

Conclusion

We described the prevalence of 20 chronic conditions across all age groups, in men and women separately, and across race/ethnic groups in the Olmsted County population. Multimorbidity is common in the general population; it increases steeply with age, has different patterns in men and women, and varies by race/ethnicity. These findings have implications for clinical practice and for etiologic research. On the one hand, the findings may inform the transition from single diagnosis-based

Acknowledgments

We thank Ms Carol J. Greenlee for her assistance in typing and formatting the manuscript.

The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

References (41)

  • F. Wang et al.

    Epidemiology of multimorbidity

    Lancet

    (2012)
  • B. Guthrie et al.

    Epidemiology of multimorbidity: author's reply

    Lancet

    (2012)
  • V.L. Roger et al.

    Coronary disease surveillance in Olmsted County objectives and methodology

    J Clin Epidemiol

    (2002)
  • C.M. Boyd et al.

    Clinical practice guidelines and quality of care for older patients with multiple comorbid diseases: implications for pay for performance

    JAMA

    (2005)
  • L.D. Hughes et al.

    Guidelines for people not for diseases: the challenges of applying UK clinical guidelines to people with multimorbidity

    Age Ageing

    (2013)
  • R.A. Goodman et al.

    Defining and measuring chronic conditions: imperatives for research, policy, program, and practice

    Prev Chronic Dis

    (2013)
  • Multiple Chronic Conditions: A Strategic Framework: Optimum Health and Quality of Life for Individuals With Multiple Chronic Conditions

    (December 2010)
  • M.E. Salive

    Multimorbidity in older adults

    Epidemiol Rev

    (2013)
  • A.K. Parekh et al.

    Managing multiple chronic conditions: a strategic framework for improving health outcomes and quality of life

    Public Health Rep

    (2011)
  • R.B. Wallace et al.

    The dimensions of multiple chronic conditions: where do we go from here? a commentary on the Special Issue of Preventing Chronic Disease

    Prev Chronic Dis

    (2013)
  • Cited by (177)

    View all citing articles on Scopus

    For editorial comment, see page 1321

    Grant Support: This study was made possible by the Rochester Epidemiology Project (grant number R01-AG034676; Principal Investigators: Walter A. Rocca, MD, MPH, and Barbara P. Yawn, MD, MSc). This study was also supported by the Paul Beeson Career Development Award Program (National Institute on Aging K23 AG032910), the John A. Hartford Foundation, Atlantic Philanthropies, the Starr Foundation, and an anonymous donor (all to C.M.B.).

    View full text