TY - JOUR
T1 - Multimorbidity, ageing and mortality
T2 - Normative data and cohort study in an American population
AU - Rocca, Walter A.
AU - Grossardt, Brandon R.
AU - Boyd, Cynthia M.
AU - Chamberlain, Alanna M.
AU - Bobo, William V.
AU - St Sauver, Jennifer L.
N1 - Funding Information:
Contributors WAR, BRG and JLS were involved in the conception and design of the study. BRG and WAR conducted the data analyses. WAR drafted the manuscript. All authors (WAR, BRG, CMB, AMC, WVB and JLS) contributed to the interpretation of the data and provided critical revisions of the manuscript. All authors (WAR, BRG, CMB, AMC, WVB and JLS) also approved the final version to be published. Funding This study used the resources of the Rochester Epidemiology Project, which is supported by the National Institute on Aging of the National Institutes of Health (grants R01 AG034676 and R01 AG052425). WAR was partly supported by the National Institutes of Health (R21 AG058738, U54 AG044170, U01 AG006786 and P01 AG004875).
Publisher Copyright:
© 2021 BMJ Publishing Group. All rights reserved.
PY - 2021/3/19
Y1 - 2021/3/19
N2 - Objectives To describe the percentile distribution of multimorbidity across age by sex, race and ethnicity, and to demonstrate the utility of multimorbidity percentiles to predict mortality. Design Population-based descriptive study and cohort study. Setting Olmsted County, Minnesota (USA). Participants We used the medical records-linkage system of the Rochester Epidemiology Project (REP; http://www.rochesterproject.org) to identify all residents of Olmsted County, Minnesota who reached one or more birthdays between 1 January 2005 and 31 December 2014 (10 years). Methods For each person, we obtained the count of chronic conditions (out of 20 conditions) present on each birthday by extracting all of the diagnostic codes received in the 5 years before the index birthday from the electronic indexes of the REP. To compare each person's count to peers of same age, the counts were transformed into percentiles of the total population and displayed graphically across age by sex, race and ethnicity. In addition, quintiles 1, 2, 4 and 5 were compared with quintile 3 (reference) to predict the risk of death at 1 year, 5 years and through end of follow-up using time-to-event analyses. Follow-up was passive using the REP. Results We identified 238 010 persons who experienced a total of 1 458 094 birthdays during the study period (median of 6 birthdays per person; IQR 3-10). The percentiles of multimorbidity across age did not vary noticeably by sex, race or ethnicity. In general, there was an increased risk of mortality at 1 and 5 years for quintiles 4 and 5 of multimorbidity. The risk of mortality for quintile 5 was greater for younger age groups and for women. Conclusions The assignment of multimorbidity percentiles to persons in a population may be a simple and intuitive tool to assess relative health status, and to predict short-term mortality, especially in younger persons and in women.
AB - Objectives To describe the percentile distribution of multimorbidity across age by sex, race and ethnicity, and to demonstrate the utility of multimorbidity percentiles to predict mortality. Design Population-based descriptive study and cohort study. Setting Olmsted County, Minnesota (USA). Participants We used the medical records-linkage system of the Rochester Epidemiology Project (REP; http://www.rochesterproject.org) to identify all residents of Olmsted County, Minnesota who reached one or more birthdays between 1 January 2005 and 31 December 2014 (10 years). Methods For each person, we obtained the count of chronic conditions (out of 20 conditions) present on each birthday by extracting all of the diagnostic codes received in the 5 years before the index birthday from the electronic indexes of the REP. To compare each person's count to peers of same age, the counts were transformed into percentiles of the total population and displayed graphically across age by sex, race and ethnicity. In addition, quintiles 1, 2, 4 and 5 were compared with quintile 3 (reference) to predict the risk of death at 1 year, 5 years and through end of follow-up using time-to-event analyses. Follow-up was passive using the REP. Results We identified 238 010 persons who experienced a total of 1 458 094 birthdays during the study period (median of 6 birthdays per person; IQR 3-10). The percentiles of multimorbidity across age did not vary noticeably by sex, race or ethnicity. In general, there was an increased risk of mortality at 1 and 5 years for quintiles 4 and 5 of multimorbidity. The risk of mortality for quintile 5 was greater for younger age groups and for women. Conclusions The assignment of multimorbidity percentiles to persons in a population may be a simple and intuitive tool to assess relative health status, and to predict short-term mortality, especially in younger persons and in women.
KW - epidemiology
KW - general medicine (see internal medicine)
KW - geriatric medicine
KW - statistics & research methods
UR - http://www.scopus.com/inward/record.url?scp=85103070342&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85103070342&partnerID=8YFLogxK
U2 - 10.1136/bmjopen-2020-042633
DO - 10.1136/bmjopen-2020-042633
M3 - Article
C2 - 33741663
AN - SCOPUS:85103070342
SN - 2044-6055
VL - 11
JO - BMJ open
JF - BMJ open
IS - 3
M1 - e042633
ER -