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The current and projected burden of multimorbidity: a cross-sectional study in a Southern Europe population

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Abstract

In a context of increasing ageing of the population, it is crucial to better understand multimorbidity and its consequences. This study measured the prevalence of multimorbidity in a Southern Europe population and projected its evolution based on expected demographic changes. It also analysed its associated consequences on self-reported health status, functional capacity, and healthcare use. Our sample included all people aged 25–79 years (6679 men and 8517 women) who participated in the fifth Portuguese National Health Interview Survey, conducted in 2014. Multimorbidity was measured by the presence of at least two self-reported chronic conditions. Multivariable regressions were used to assess the association of multimorbidity with health status, functional capacity, and healthcare use. The projected evolution of multimorbidity was based on official demographic projections. 43.9% of the Portuguese population self-reported the multimorbidity, which was more frequent among older people, women, and low-educated people. We found an association of multimorbidity with poorer health status (OR 3.32, 95%CI 2.60–4.24) and with limited functional capacity (OR 4.44, 95%CI 3.85–5.11). Multimorbidity was also associated with higher healthcare resource use, namely a 26% increased likelihood of hospitalization in the previous 12 months per additional comorbidity. We projected a 13.1% growth in the prevalence of multimorbidity until the year 2050. Multimorbidity affects a substantial share of the population and is expected to grow in the near future related to population ageing. The co-occurrence of chronic health conditions increases sharply with age and is associated with worse health status, reduced functional capacity, and increased healthcare use.

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Authors and Affiliations

Authors

Corresponding author

Correspondence to P. A. Laires.

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Conflict of interest

Pedro Laires is a Novartis employee. The current project was, however, developed during his postdoctoral internship at Nova University and was totally unrelated to any Novartis product or Grant.

Additional information

Responsible editor: Matthias Kliegel.

Appendices

Appendix 1

See Table 2.

Table 2 Relationship between the observed and expected prevalence of co-occurring pairs of chronic health conditions. (Color table online)

Appendix 2

See Tables 3 and 4.

Table 3 Logistic regression model used to assess the association of self-reported health status, functional impairment, and healthcare use with multimorbidity
Table 4 Generalized linear model with a gamma distribution used to assess the adjusted number of chronic conditions

Appendix 3: Absolute numbers and percentage of sample and due projected population’s distribution according to number of chronic health conditions

NR disorders

Sample

Population

Percentage (%)

0

5441

2,764,162

35.8

1

2568

1,269,005

16.9

2

1985

947,338

13.1

3

1625

733,925

10.7

4

1326

549,397

8.7

5

931

402,049

6.1

6

652

270,974

4.3

7

350

129,241

2.3

8

188

76,082

1.2

9

80

24,235

0.5

> = 10

50

17,118

0.3

Total

15,196

7183,526

 
  1. Absolute numbers reflect the distribution of the sample (i.e. not adjusted to the study design), while the percentages are projected to the population after using the survey weights

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Laires, P.A., Perelman, J. The current and projected burden of multimorbidity: a cross-sectional study in a Southern Europe population. Eur J Ageing 16, 181–192 (2019). https://doi.org/10.1007/s10433-018-0485-0

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