Postgraduate Program in Health Sciences, Faculty of Medicine, Federal University of Goiás, Goiânia, 74605-050, Brazil.
Duke Global Health Institute, Duke University, Durham, NC, USA.
Sci Rep. 2022 Jul 8;12(1):11643. doi: 10.1038/s41598-022-15723-4.
Multimorbidity is highly prevalent in older adults and can lead to hospitalisation. We investigate the prevalence, associated factors, and multimorbidity pattern associated to hospitalisation, readmission, and length of stay in the population aged 50 years and older. We analysed baseline data (2015-2016) from the ELSI-Brazil cohort, a representative sample of non-institutionalised Brazilians aged ≥ 50 years. In total, 8807 individuals aged ≥ 50 years were included. Poisson regression with robust variance adjusted for confounders was used to verify the associations with hospitalisation. Multiple linear regression was used to analyse the associations with readmission and length of stay. Network analysis was conducted using 19 morbidities and the outcome variables. In 8807 participants, the prevalence of hospitalisation was 10.0% (95% CI 9.1, 11), mean readmissions was 1.55 ± 1.191, and mean length of stay was 6.43 ± 10.46 days. Hospitalisation was positively associated with male gender, not living with a partner, not having ingested alcoholic beverages in the last month, and multimorbidity. For hospital readmission, only multimorbidity ≥ 3 chronic conditions showed a statistically significant association. Regarding the length of stay, the risk was positive for males and negative for living in rural areas. Five disease groups connected to hospitalisation, readmission and length of stay were identified. To conclude, sociodemographic variables, such as gender, age group, and living in urban areas, and multimorbidity increased the risk of hospitalisation, mean number of readmissions, and mean length of stay. Through network analysis, we identified the groups of diseases that increased the risk of hospitalisation, readmissions, and length of stay.
多发病在老年人中非常普遍,可能导致住院。我们研究了≥50 岁人群中发病率、相关因素以及与住院、再入院和住院时间相关的多发病模式。我们分析了 ELSI-Brazil 队列的基线数据(2015-2016 年),该队列是≥50 岁非住院巴西人的代表性样本。共纳入 8807 名≥50 岁的个体。使用调整混杂因素的稳健方差的泊松回归来验证与住院的相关性。使用多元线性回归分析与再入院和住院时间的相关性。使用 19 种疾病和结局变量进行网络分析。在 8807 名参与者中,住院率为 10.0%(95%CI 9.1,11),平均再入院率为 1.55±1.191,平均住院时间为 6.43±10.46 天。住院与男性、与伴侣同住、最近一个月未饮酒以及多发病显著相关。对于住院再入院,仅≥3 种慢性疾病与住院再入院显著相关。关于住院时间,男性的风险呈阳性,而农村地区的风险呈阴性。确定了与住院、再入院和住院时间相关的五个疾病组。总之,社会人口学变量,如性别、年龄组和居住在城市地区,以及多发病增加了住院、再入院和平均住院时间的风险。通过网络分析,我们确定了增加住院、再入院和住院时间风险的疾病组。
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