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Prevalence and clustering of chronic diseases in Tuscany (Central Italy): evidence from a large administrative data warehouse.

医学 社会经济地位 多发病率 人口 糖尿病 横断面研究 疾病 人口学 风险因素 慢性病 流行病学 儿科 环境卫生 内科学 病理 社会学 内分泌学
作者
Francesco Profili,Gavino Maciocco,Benedetta Bellini,Matilde Razzanelli,Paolo Francesconi
出处
期刊:PubMed [National Institutes of Health]
卷期号:44 (5-6): 385-393 被引量:4
标识
DOI:10.19191/ep20.5-6.p385.014
摘要

BACKGROUND: chronic diseases and multimorbidity are on the rise and have a great impact on health and services. OBJECTIVES: to assess the prevalence and patterns of chronic diseases. DESIGN: cross-sectional population-based study on administrative data. SETTING AND PARTICIPANTS: the study includes 3,234,276 Tuscany (Central Italy) inhabitants aged over 15, observed as at 01.01.2019. MAIN OUTCOME MEASURES: subjects were classified as affected or not affected by one of the 17 chronic diseases considered, according to administrative data algorithms. Population prevalence was estimated overall and stratified by gender, age range, and socioeconomic level. A factor analysis was performed in order to evaluate multimorbidity. RESULTS: in Tuscany, 444.8 per 1,000 inhabitants aged over 15 have a chronic disease. The prevalence is 463.5 per 1,000 among females and 424.5 per 1,000 among males, but the two age-adjusted prevalences are equal. The prevalence of chronic patients increases with the level of socioeconomic disadvantage. The most frequent disease is hypertension (308.7 per 1,000), followed by dyslipidaemia (251 per 1,000) and diabetes (75.7 per 1,000). Inflammatory rheumatic diseases and neurological diseases are more prevalent among females than males. The prevalence identified among males almost doubles in comparison to females for all other diseases, in particular for circulatory system diseases. Chronic patients suffer from at least two pathologies in 53.2% of cases. On average, males have more diseases than females. The cardiovascular factor (circulatory system diseases and related) and the neurological factor (neurological diseases and mental disorders) emerged from the factor analysis. CONCLUSIONS: this study quantifies the burden of chronic diseases in the population, which is useful information in epidemiology, in clinical practice, and in services management.

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