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

Area of Science:

• Gerontology
• Epidemiology
• Public Health

Background:

• Multimorbidity, the coexistence of multiple chronic conditions, is prevalent in aging populations.
• Understanding multimorbidity patterns is crucial for effective healthcare management and resource allocation.
• Previous research has indicated potential variations in disease clustering based on demographics.

Purpose of the Study:

• To identify and characterize distinct multimorbidity patterns in a representative sample of middle-aged and older German adults.
• To investigate potential gender-specific differences within these identified multimorbidity patterns.
• To explore associations between multimorbidity patterns and socio-demographic, behavioral, and lifestyle factors.

Main Methods:

• Latent Class Analysis (LCA) was applied to data from the German Ageing Survey (DEAS) 2017 wave.
• The analysis included 6,554 community-dwelling individuals aged 43-92 years.
• Multimorbidity was defined as the presence of at least two out of 13 specified chronic conditions.

Main Results:

• Over half (53.3%) of the participants exhibited multimorbidity.
• Five distinct multimorbidity patterns were identified: relatively healthy, high morbidity, arthrosis/inflammatory/mental illnesses, hypertension-metabolic illness, and cardiovascular/cancer.
• Women showed a significantly higher relative risk of belonging to the arthrosis/inflammatory/mental illnesses class compared to men.

Conclusions:

• Chronic diseases do not cluster randomly; distinct, clinically meaningful multimorbidity patterns exist.
• Gender differences in multimorbidity patterns were specifically noted in the arthrosis/inflammatory/mental illnesses class.
• The identified patterns are associated with significant variations in socio-demographic, health behavior, and lifestyle factors.