Institute of Health and Wellbeing, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.
British Heart Foundation Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.
BMC Infect Dis. 2022 Mar 30;22(1):273. doi: 10.1186/s12879-022-07132-9.
Infection with SARS-CoV-2 virus (COVID-19) impacts disadvantaged groups most. Lifestyle factors are also associated with adverse COVID-19 outcomes. To inform COVID-19 policy and interventions, we explored effect modification of socioeconomic-status (SES) on associations between lifestyle and COVID-19 outcomes.
Using data from UK-Biobank, a large prospective cohort of 502,536 participants aged 37-73 years recruited between 2006 and 2010, we assigned participants a lifestyle score comprising nine factors. Poisson regression models with penalised splines were used to analyse associations between lifestyle score, deprivation (Townsend), and COVID-19 mortality and severe COVID-19. Associations between each exposure and outcome were examined independently before participants were dichotomised by deprivation to examine exposures jointly. Models were adjusted for sociodemographic/health factors.
Of 343,850 participants (mean age > 60 years) with complete data, 707 (0.21%) died from COVID-19 and 2506 (0.76%) had severe COVID-19. There was evidence of a nonlinear association between lifestyle score and COVID-19 mortality but limited evidence for nonlinearity between lifestyle score and severe COVID-19 and between deprivation and COVID-19 outcomes. Compared with low deprivation, participants in the high deprivation group had higher risk of COVID-19 outcomes across the lifestyle score. There was evidence for an additive interaction between lifestyle score and deprivation. Compared with participants with the healthiest lifestyle score in the low deprivation group, COVID-19 mortality risk ratios (95% CIs) for those with less healthy scores in low versus high deprivation groups were 5.09 (1.39-25.20) and 9.60 (4.70-21.44), respectively. Equivalent figures for severe COVID-19 were 5.17 (2.46-12.01) and 6.02 (4.72-7.71). Alternative SES measures produced similar results.
Unhealthy lifestyles are associated with higher risk of adverse COVID-19, but risks are highest in the most disadvantaged, suggesting an additive influence between SES and lifestyle. COVID-19 policy and interventions should consider both lifestyle and SES. The greatest public health benefit from lifestyle focussed COVID-19 policy and interventions is likely to be seen when greatest support for healthy living is provided to the most disadvantaged groups.
SARS-CoV-2 病毒(COVID-19)感染对弱势群体的影响最大。生活方式因素也与 COVID-19 不良结局有关。为了为 COVID-19 政策和干预措施提供信息,我们探讨了社会经济地位(SES)对生活方式与 COVID-19 结局之间关系的调节作用。
使用来自 UK-Biobank 的数据,这是一项针对 2006 年至 2010 年间招募的 502,536 名 37-73 岁参与者的大型前瞻性队列研究,我们为参与者分配了一个由九个因素组成的生活方式评分。使用带有惩罚样条的泊松回归模型分析了生活方式评分、贫困(汤森德)与 COVID-19 死亡率和严重 COVID-19 之间的关系。在参与者按贫困程度分为两组之前,先独立分析每个暴露因素与结局之间的关系,然后检查联合暴露因素。模型调整了社会人口统计学/健康因素。
在 343,850 名有完整数据的参与者(平均年龄>60 岁)中,有 707 人(0.21%)死于 COVID-19,2506 人(0.76%)患有严重 COVID-19。生活方式评分与 COVID-19 死亡率之间存在非线性关系的证据,但生活方式评分与严重 COVID-19 之间以及贫困程度与 COVID-19 结局之间的非线性关系证据有限。与低贫困程度相比,高贫困程度组的参与者具有更高的 COVID-19 结局风险。生活方式评分和贫困程度之间存在相加交互作用的证据。与低贫困程度组中生活方式评分最健康的参与者相比,低贫困程度组中生活方式评分较差的参与者 COVID-19 死亡率风险比(95%CI)分别为 5.09(1.39-25.20)和 9.60(4.70-21.44),严重 COVID-19 的相应数字分别为 5.17(2.46-12.01)和 6.02(4.72-7.71)。严重 COVID-19 的相应数字分别为 5.17(2.46-12.01)和 6.02(4.72-7.71)。替代 SES 衡量标准得出了类似的结果。
不健康的生活方式与 COVID-19 不良结局的风险增加有关,但在最弱势群体中风险最高,这表明 SES 和生活方式之间存在附加影响。COVID-19 政策和干预措施应同时考虑生活方式和 SES。生活方式为重点的 COVID-19 政策和干预措施最能为最弱势群体提供健康生活的最大支持,从而带来最大的公共卫生效益。