Prevalence of and factors associated with multimorbidity among 18 101 adults in the South East Asia Community Observatory Health and Demographic Surveillance System in Malaysia: a population-based, cross-sectional study of the MUTUAL consortium.

Prevalence of and factors associated with multimorbidity among 18 101 adults in the South East Asia Community Observatory Health and Demographic Surveillance System in Malaysia: a population-based, cross-sectional study of the MUTUAL consortium.
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与马来西亚的东南亚社区观测和人口监测系统中1811名成年人的多种多发病相关的患病率和因素:一项基于人群的,基于人群的横断面研究。

DOI:
10.1136/bmjopen-2022-068172
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发表时间:
2022-12-23
期刊:
影响因子:
2.9
通讯作者:
--
中科院分区:
医学3区
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在大型健康和人口监测系统(HDSS)量表上评估社区居住的一般成年人群中多发病的患病率和相关因素。基于人口的横断面研究。马来西亚的东南亚社区观测站HDSS站点。在从13431个家庭招募的45246名参与者中,包括18101名年龄在18-97岁之间的合格成年人(平均年龄47岁,55.6%为女性)。主要结果是多发性硬化的患病率。多发病被定义为每个个体同时存在两种或多种慢性疾病。共选择了13种慢性疾病,并进一步分为11种医疗条件,以说明多发病。这些疾病包括心脏病、中风、糖尿病、高血压、慢性肾病、肌肉骨骼疾病、肥胖、哮喘、视力问题、听力问题和身体活动问题。还分析了多发病的风险因素。在研究队列中,28.5%的人患有多发性硬化症。慢性病的个体患病率范围为1.0%至24.7%,其中肌肉骨骼疾病(24.7%)、肥胖(20.7%)和高血压(18.4%)是最常见的慢性病。慢性疾病的数量随年龄线性增加(p<0.001)。在逻辑回归模型中,多发病率与女性有关(调整OR 1.28,95% CI 1.17至1.40,p<0.001),教育水平(小学教育与未受教育相比:调整后OR 0.63,95% CI 0.53至0.74;中学教育:调整后OR 0.60,95% CI 0.51至0.70;高等教育:调整OR 0.65,95% CI 0.54 - 0.80; p<0.001)和就业状况(在职成年人与退休人员比较:校正OR 0.70,95% CI 0.60至0.82,p<0.001),以及年龄(校正OR 1.05,95% CI 1.05至1.05,p<0.001)。目前初级和二级保健中的单一疾病服务应辅之以解决与多种疾病相关的复杂性的战略,同时考虑到已查明的与多种疾病相关的因素。未来的研究需要确定最常见的慢性病及其危险因素,以制定更有效和更有效的多发病预防和治疗策略。
To assess the prevalence and factors associated with multimorbidity in a community-dwelling general adult population on a large Health and Demographic Surveillance System (HDSS) scale. Population-based cross-sectional study. South East Asia Community Observatory HDSS site in Malaysia. Of 45 246 participants recruited from 13 431 households, 18 101 eligible adults aged 18–97 years (mean age 47 years, 55.6% female) were included. The main outcome was prevalence of multimorbidity. Multimorbidity was defined as the coexistence of two or more chronic conditions per individual. A total of 13 chronic diseases were selected and were further classified into 11 medical conditions to account for multimorbidity. The conditions were heart disease, stroke, diabetes mellitus, hypertension, chronic kidney disease, musculoskeletal disorder, obesity, asthma, vision problem, hearing problem and physical mobility problem. Risk factors for multimorbidity were also analysed. Of the study cohort, 28.5% people lived with multimorbidity. The individual prevalence of the chronic conditions ranged from 1.0% to 24.7%, with musculoskeletal disorder (24.7%), obesity (20.7%) and hypertension (18.4%) as the most prevalent chronic conditions. The number of chronic conditions increased linearly with age (p<0.001). In the logistic regression model, multimorbidity is associated with female sex (adjusted OR 1.28, 95% CI 1.17 to 1.40, p<0.001), education levels (primary education compared with no education: adjusted OR 0.63, 95% CI 0.53 to 0.74; secondary education: adjusted OR 0.60, 95% CI 0.51 to 0.70; tertiary education: adjusted OR 0.65, 95% CI 0.54 to 0.80; p<0.001) and employment status (working adults compared with retirees: adjusted OR 0.70, 95% CI 0.60 to 0.82, p<0.001), in addition to age (adjusted OR 1.05, 95% CI 1.05 to 1.05, p<0.001). The current single-disease services in primary and secondary care should be accompanied by strategies to address complexities associated with multimorbidity, taking into account the factors associated with multimorbidity identified. Future research is needed to identify the most commonly occurring clusters of chronic diseases and their risk factors to develop more efficient and effective multimorbidity prevention and treatment strategies.
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