健康与参与洛兰-法尔斯特健康研究:一项队列研究

T. Holmager, G. Napolitano, Neda Esmai­lzadeh Bruun-Rasmu­ssen, R. Jepsen, Søren Lophaven, Elsebeth Lynge
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摘要

洛兰-法尔斯特是丹麦死亡率最高的地区。然而,一项基于人群的健康调查的临床测量结果显示,该地区的疾病患病率指标与丹麦其他地区相似。这项研究旨在解开这一悖论。Lolland-Falster健康研究(LOFUS)于2016-2020年进行。从邀请之日起至2023年2月1日,我们对53,000名受邀者的死亡率进行了随访。采用对数二项回归,按性别、年龄、城市、居住群体、家庭组成和经济状况等亚组计算不参加与参加LOFUS的相对风险(RR)。使用泊松回归,计算了非参与者与参与者的全因死亡率以及癌症、心血管疾病、呼吸系统疾病、外因和其他疾病的死亡率在亚组之间和亚组内的死亡率比(MRR)。三分之一(36%)被邀请参加联卢特派团的人参加了会议。亚组之间的参与程度差异不大;其中最大的是公共供养者与自食自力者的RR为1.37 (95% CI 1.35至1.40)。然而,非参与者的死亡率高于参与者(MRR 3.08, 95% CI 2.82至3.37)。这种模式在所有亚组中都是一致的,并且在全因死亡率和特定原因死亡率中都发现了这种模式。我们观察到的这种矛盾可以部分归因于子群体之间的参与差异。然而,由于调查数据缺乏人口代表性,我们的研究表明,通过非参与者的超额死亡率来衡量的组内选择比组间选择重要得多。因此,在使用加权卫生调查数据确定卫生干预措施的优先次序时应谨慎。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Health and participation in the Lolland-Falster Health Study: a cohort study
Lolland-Falster is the area of Denmark with highest mortality. However, clinical measurements from a population-based health survey showed prevalence of disease indicators similar to those in the rest of Denmark. The study aimed to disentangle this paradox.The Lolland-Falster Health Study (LOFUS) took place in 2016–2020. We followed the 53 000 invited persons up for mortality from invitation date to 1 February 2023. Log-binomial regression was used to calculate relative risk (RR) of non-participation versus participation in LOFUS by subgroups of sex, age, municipality, residency group, household composition and economic status. Using Poisson regression, mortality rate ratio (MRR) was calculated between subgroups and within subgroups for non-participants versus participants for all-cause mortality and mortality from cancer, cardiovascular diseases, respiratory diseases, external causes and other diseases.One-third (36%) of persons invited to LOFUS participated. Only modest differences were seen in participation across subgroups; the largest being an RR of 1.37 (95% CI 1.35 to 1.40) for publicly supported versus self-supported persons. However, non-participants had higher mortality than participants (MRR 3.08, 95% CI 2.82 to 3.37). This pattern was consistent across all subgroups and was found for both all-cause and cause-specific mortality.The paradox we observed could partly be attributed to participation differences between subgroups. However, for the lack of population representativeness of the survey data, our study indicated within-group selection, measured by excess mortality of non-participants, to be much more important than between-group selection. One should therefore be cautious in using even weighted health survey data for prioritising health interventions.
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