Multimorbidity patterns in the German general population aged 40 years and over

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Erscheinungsjahr:
2023
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  • Aim The aim of this study was to identify and describe multimorbidity patterns among middle-aged and older community-dwelling individuals in Germany. Moreover, we aimed to determine potential gender differences in multimorbidity patterns. Methods We analysed data from the most recent (sixth) wave (2017) of the large nationally representative German Ageing Survey (DEAS). Altogether n=6,554 individuals participated, mean age was 62.0 (ranging from 43 to 92 years). Latent Class Analysis was performed to identify multimorbidity patterns, based on 13 chronic conditions and diseases. Multimorbidity was defined as the presence of at least two chronic conditions. Results Altogether, 53.3% of individuals were multimorbid. We identified and clinically described five multimorbidity patterns: the relatively healthy class (45.1%), the high morbidity class (10.8%), the arthrosis/inflammatory/mental illnesses class (20.6%), the hypertension-metabolic illness class (21.7%), and the cardiovascular/cancer class (1.7%). Our analysis revealed that women compared to men have higher relative risk (IRR=1.61, 95% CI 1.25-2.06) of being in the arthrosis/inflammatory/mental illnesses class, compared to the relatively healthy class. Furthermore, we found that, depending on which multimorbidity pattern individuals belong to, they differ greatly in terms of socio-demographic factors, health behaviour, and lifestyle factors. Conclusions We showed that the many chronic diseases cluster in a non-random way. Five clinically meaningful multimorbidity patterns were identified. Gender differences were apparent only in one class, namely in the arthrosis/inflammatory/mental illnesses class.
  • AIM: The aim of this study was to identify and describe multimorbidity patterns among middle-aged and older community-dwelling individuals in Germany. Moreover, we aimed to determine potential gender differences in multimorbidity patterns.

    METHODS: We analysed data from the most recent (sixth) wave (2017) of the large nationally representative German Ageing Survey (DEAS). Altogether n = 6,554 individuals participated, mean age was 62.0 (ranging from 43 to 92 years). Latent Class Analysis was performed to identify multimorbidity patterns, based on 13 chronic conditions and diseases. Multimorbidity was defined as the presence of at least two chronic conditions.

    RESULTS: Altogether, 53.3% of individuals were multimorbid. We identified and clinically described five multimorbidity patterns: the relatively healthy class (45.1%), the high morbidity class (10.8%), the arthrosis/inflammatory/mental illnesses class (20.6%), the hypertension-metabolic illness class (21.7%), and the cardiovascular/cancer class (1.7%). Our analysis revealed that women compared to men have higher relative risk (IRR = 1.61, 95% CI 1.25-2.06) of being in the arthrosis/inflammatory/mental illnesses class, compared to the relatively healthy class. Furthermore, we found that, depending on which multimorbidity pattern individuals belong to, they differ greatly in terms of socio-demographic factors, health behaviour, and lifestyle factors.

    CONCLUSIONS: We showed that the many chronic diseases cluster in a non-random way. Five clinically meaningful multimorbidity patterns were identified. Gender differences were apparent only in one class, namely in the arthrosis/inflammatory/mental illnesses class.

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  • info:eu-repo/semantics/closedAccess
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Forschungsinformationssystem des UKE

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oai:pure.atira.dk:publications/ef8d9043-de6c-4c84-8de9-4883372e86c5