Prevalence of chronic medical conditions in Switzerland: exploring estimates validity by comparing complementary data sources.
BACKGROUND
Prevalence estimates of chronic medical conditions and their multiples (multimorbidity) in the general population are scarce and often rather speculative in Switzerland. Using complementary data sources, we assessed estimates validity of population-based prevalence rates of four common chronic medical conditions with high impact on cardiovascular health (diabetes mellitus, hypertension, dyslipidemia, obesity).


METHODS
We restricted our analyses to patients 15-94 years old living in the German speaking part of Switzerland. Data sources were: Swiss Health Survey (SHS, 2007, n = 13,580); Family Medicine ICPC Research using Electronic Medical Record Database (FIRE, 2010-12, n = 99,441); and hospital discharge statistics (MEDSTAT, 2009-10, n = 883,936). We defined chronic medical conditions based on use of drugs, diagnoses, and measurements.


RESULTS
After a careful harmonization of the definitions, a high degree of concordance, especially regarding the age- and gender-specific distribution patterns, was found for diabetes mellitus (defined as drug use or diagnosis in SHS, drug use or diagnosis or blood glucose measurement in FIRE, and ICD-10 codes E10-14 as secondary diagnosis in MEDSTAT) and for hypertension (defined as drug use alone in SHS and FIRE, and ICD-10 codes I10-15 or I67.4 as secondary diagnosis in MEDSTAT). A lesser degree of concordance was found for dyslipidemia (defined as drug use alone in SHS and FIRE, and ICD-10 code E78 in MEDSTAT), and for obesity (defined as BMI ≥ 30 kg/m(2) derived from self-reported height and weight in SHS, from measured height and weight or diagnosis of obesity in FIRE, and ICD-10 code E66 as secondary diagnosis in MEDSTAT). MEDSTAT performed well for clearly defined diagnoses (diabetes, hypertension), but underrepresented systematically more symptomatic conditions (dyslipidemia, obesity).


CONCLUSIONS
Complementary data sources can provide different prevalence estimates of chronic medical conditions in the general population. However, common age and sex patterns indicate that a careful harmonization of the definition of each chronic medical condition permits a high degree of concordance.
Ueli
U
Zellweger
Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, Zürich CH-8001, Switzerland. matthias.bopp@uzh.ch.
Matthias
M
Bopp
Barbara M
BM
Holzer
Sima
S
Djalali
Vladimir
V
Kaplan
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002908:Chronic Disease / Q000453:epidemiology*; D003625:Data Collection / Q000592:standards*; D003920:Diabetes Mellitus / Q000453:epidemiology; D005260:Female; D006306:Health Surveys; D006801:Humans; D038801:International Classification of Diseases; D008297:Male; D008875:Middle Aged; D009765:Obesity / Q000453:epidemiology; D015995:Prevalence; D015203:Reproducibility of Results; D013557:Switzerland / Q000453:epidemiology