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All-cause mortality and multimorbidity in older adults: The role of social support and loneliness

机译:老年人的全因死亡率和多重多达率:社会支持和孤独的作用

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Abstract Objectives To determine whether the effect of multimorbidity on time to mortality is modified by level of social support and loneliness in a representative sample of 2113 participants aged 60+. Methods Vital status was ascertained through national registers or by asking participants' relatives. Baseline variables included number of illnesses, self-perceived social support (Oslo social support scale) and loneliness (UCLA loneliness scale). Kaplan-Meier survival curves were used to estimate the time to death by multimorbidity, social support and loneliness. Adjusted cox proportional hazards regression models were conducted to explore interactions between multimorbidity and social support and loneliness. Results Multimorbidity was associated with low probability of survival, whereas high loneliness and low social support were not related with time to death. Only the interaction multimorbidity?social support was significant. Participants with low social support and 2 chronic diseases, compared with none, presented lower probability of survival (HR=2.43, 95%CI=1.14–5.18, p Discussion These findings indicate that having a supportive social environment increases the survival of people with physical illnesses, especially those with one or two. For those with more than two illnesses, survival remains unchanged regardless of the level of social support and other protective factors should be explored in future research. Geriatric health professionals are encouraged to evaluate social relationships and stimulate support given by relatives, friends or neighbors. Highlights ? Multimorbidity decreased survival in a representative sample of older adults. ? High social support buffered the negative effect of multimorbidity on survival. ? Loneliness did not affect survival, nor did it moderate the effect of multimorbidity.
机译:摘要目的,以确定多元化时间对死亡率的效果是通过2113岁以上的2113名参与者的代表性样本的社会支持和孤独水平来修改。方法通过国家寄存器或要求参与者的亲属确定重要地位。基线变量包括疾病的数量,自我认识的社会支持(奥斯陆社会支持规模)和孤独(UCLA孤独量表)。 Kaplan-Meier生存曲线用于通过多重,社会支持和孤独估算死亡时间。进行了调整的COX比例危害回归模型,以探索多重和社会支持与孤独之间的相互作用。结果多药物与生存率低有关,而高孤独和低社会支持与死亡的时间无关。只有相互作用的多重货物?社会支持很重要。社会支持和2个慢性病的参与者,与无,较低的生存概率较低(HR = 2.43,95%CI = 1.14-5.18,P讨论表明,具有支持性的社会环境增加了物理的人的生存疾病,尤其是那些有一两个人的疾病。对于那些有两种疾病的人,无论社会支持程度和其他保护因素都应该在未来的研究中探讨的那些仍然保持不变。鼓励老年卫生专业人员评估社会关系并刺激支持由亲戚,朋友或邻居给予。亮点?多元化剂在老年人的代表性样本中减少了生存率。?高社会支持缓冲了多重药物对生存率的负面影响。?寂寞不影响生存,也不适中多重的影响。

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