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01.12.2012 | Research article | Ausgabe 1/2012 Open Access

BMC Health Services Research 1/2012

The influence of age, gender and socio-economic status on multimorbidity patterns in primary care. first results from the multicare cohort study

BMC Health Services Research > Ausgabe 1/2012
Ingmar Schäfer, Heike Hansen, Gerhard Schön, Susanne Höfels, Attila Altiner, Anne Dahlhaus, Jochen Gensichen, Steffi Riedel-Heller, Siegfried Weyerer, Wolfgang A Blank, Hans-Helmut König, Olaf von dem Knesebeck, Karl Wegscheider, Martin Scherer, Hendrik van den Bussche, Birgitt Wiese
Wichtige Hinweise

Electronic supplementary material

The online version of this article (doi:10.​1186/​1472-6963-12-89) contains supplementary material, which is available to authorized users.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

HvdB, IS, HH, KW, MS and BW conceived and designed the study. BW and GS prepared the data for analysis. IS and GS analysed the data. IS drafted the manuscript. SH, AA, AD, JG, SRH, SW, WB, HHK, and OvdK participated in study design and implementation. All authors read and approved the final manuscript.



Multimorbidity is a phenomenon with high burden and high prevalence in the elderly. Our previous research has shown that multimorbidity can be divided into the multimorbidity patterns of 1) anxiety, depression, somatoform disorders (ADS) and pain, and 2) cardiovascular and metabolic disorders. However, it is not yet known, how these patterns are influenced by patient characteristics. The objective of this paper is to analyze the association of socio-demographic variables, and especially socio-economic status with multimorbidity in general and with each multimorbidity pattern.


The MultiCare Cohort Study is a multicentre, prospective, observational cohort study of 3.189 multimorbid patients aged 65+ randomly selected from 158 GP practices. Data were collected in GP interviews and comprehensive patient interviews. Missing values have been imputed by hot deck imputation based on Gower distance in morbidity and other variables. The association of patient characteristics with the number of chronic conditions is analysed by multilevel mixed-effects linear regression analyses.


Multimorbidity in general is associated with age (+0.07 chronic conditions per year), gender (-0.27 conditions for female), education (-0.26 conditions for medium and -0.29 conditions for high level vs. low level) and income (-0.27 conditions per logarithmic unit). The pattern of cardiovascular and metabolic disorders shows comparable associations with a higher coefficient for gender (-1.29 conditions for female), while multimorbidity within the pattern of ADS and pain correlates with gender (+0.79 conditions for female), but not with age or socioeconomic status.


Our study confirms that the morbidity load of multimorbid patients is associated with age, gender and the socioeconomic status of the patients, but there were no effects of living arrangements and marital status. We could also show that the influence of patient characteristics is dependent on the multimorbidity pattern concerned, i.e. there seem to be at least two types of elderly multimorbid patients. First, there are patients with mainly cardiovascular and metabolic disorders, who are more often male, have an older age and a lower socio-economic status. Second, there are patients mainly with ADS and pain-related morbidity, who are more often female and equally distributed across age and socio-economic groups.

Trial registration

Additional file 1: Table S1. Multimorbidity patterns by gender* - results from tetrachoric factor analyses. (PDF 37 KB)
Additional file 2: Table S2. Intercentre differences in socio-demographic data of patients at baseline (n = 3,189). (PDF 52 KB)
Additional file 3: Table S3. Comparison of study participants and non-responders regarding the chance for study participation: results from multilevel logistic regression analysis allowing for random effects at the study centre and GP practice-within-study centre level. (PDF 79 KB)
Authors’ original file for figure 1
Authors’ original file for figure 2
Authors’ original file for figure 3
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