Abstract：
BACKGROUND: Gender influences cardiovascular disease (CVD) through norms, social relations, roles and behaviours. This study identified gender-specific aspects of socialisation associated with CVD.
METHODS: A longitudinal study was conducted, involving 9936 (5,231 women and 4705 men) initially healthy, community-dwelling Australians aged 70 years or more from the ASPirin in Reducing Events in the Elderly (ASPREE) study and ASPREE Longitudinal Study of Older Persons, with a median follow-up time of 6.4 years. Variable categorisation, variable selection (using machine learning (ML) models; Elastic Net and extreme gradient boosting) and Cox-regression were employed separately by binary gender to identity socialisation factors (n=25 considered) associated with CVD.
RESULTS: Different socialisation factors were identified using the ML models. In the Cox model, for both genders, being married/partnered was associated with a reduced risk of CVD (men: HR 0.76, 95% CI 0.60 to 0.96; women: HR 0.67, 95% CI 0.58 to 0.95). For men, having 3-8 relatives they felt close to and could call on for help (HR 0.76, 95% CI 0.58 to 0.99; reference <3 relatives), having 3-8 relatives they felt at ease talking with about private matters (HR 0.70, 95% CI 0.55 to 0.90; reference <3 relatives) or playing games such as chess or cards (HR 0.82, 95% CI 0.67 to 1.00) was associated with reduced risk of CVD. For women, living with others (HR 0.71, 95% CI 0.55 to 0.91) or having ≥3 friends they felt at ease talking with about private matters (HR 0.74, 95% CI 0.58 to 0.95; reference <3 friends) was associated with a lower risk of CVD.
CONCLUSIONS: This study demonstrates the need to prioritise gender-specific social factors to improve cardiovascular health in older adults.
METHODS: A longitudinal study was conducted, involving 9936 (5,231 women and 4705 men) initially healthy, community-dwelling Australians aged 70 years or more from the ASPirin in Reducing Events in the Elderly (ASPREE) study and ASPREE Longitudinal Study of Older Persons, with a median follow-up time of 6.4 years. Variable categorisation, variable selection (using machine learning (ML) models; Elastic Net and extreme gradient boosting) and Cox-regression were employed separately by binary gender to identity socialisation factors (n=25 considered) associated with CVD.
RESULTS: Different socialisation factors were identified using the ML models. In the Cox model, for both genders, being married/partnered was associated with a reduced risk of CVD (men: HR 0.76, 95% CI 0.60 to 0.96; women: HR 0.67, 95% CI 0.58 to 0.95). For men, having 3-8 relatives they felt close to and could call on for help (HR 0.76, 95% CI 0.58 to 0.99; reference <3 relatives), having 3-8 relatives they felt at ease talking with about private matters (HR 0.70, 95% CI 0.55 to 0.90; reference <3 relatives) or playing games such as chess or cards (HR 0.82, 95% CI 0.67 to 1.00) was associated with reduced risk of CVD. For women, living with others (HR 0.71, 95% CI 0.55 to 0.91) or having ≥3 friends they felt at ease talking with about private matters (HR 0.74, 95% CI 0.58 to 0.95; reference <3 friends) was associated with a lower risk of CVD.
CONCLUSIONS: This study demonstrates the need to prioritise gender-specific social factors to improve cardiovascular health in older adults.
摘要：
背景：性别通过规范影响心血管疾病（CVD），社会关系,角色和行为。这项研究确定了与CVD相关的社会化的性别特异性方面。
方法：进行了一项纵向研究，涉及9936（5,231名女性和4705名男性）最初健康，来自ASPirin减少老年人事件（ASPREE）研究和ASPREE老年人纵向研究的70岁或以上的社区居住澳大利亚人，中位随访时间为6.4年。变量分类，变量选择(使用机器学习(ML)模型;ElasticNet和极端梯度提升)和Cox回归分别采用与CVD相关的二元性别-身份社会化因素(考虑n=25).
结果：使用ML模型确定了不同的社会化因素。在Cox模型中,对于男女来说，结婚/伴侣与CVD风险降低相关(男性:HR0.76,95%CI0.60~0.96;女性:HR0.67,95%CI0.58~0.95).对于男人来说,有3-8个亲戚，他们觉得很亲近，可以寻求帮助（HR0.76，95％CI0.58至0.99；参考<3个亲戚），有3-8名亲属可以轻松地谈论私人事务(HR0.70,95%CI0.55至0.90;参考<3名亲属)或玩棋牌等游戏(HR0.82,95%CI0.67至1.00)与CVD风险降低相关。对女人来说,与他人生活在一起(HR0.71,95%CI0.55~0.91)或有≥3个朋友他们认为可以轻松地谈论私事(HR0.74,95%CI0.58~0.95;参考<3个朋友)与较低的CVD风险相关.
结论：这项研究表明，需要优先考虑性别特定的社会因素，以改善老年人的心血管健康。
方法：进行了一项纵向研究，涉及9936（5,231名女性和4705名男性）最初健康，来自ASPirin减少老年人事件（ASPREE）研究和ASPREE老年人纵向研究的70岁或以上的社区居住澳大利亚人，中位随访时间为6.4年。变量分类，变量选择(使用机器学习(ML)模型;ElasticNet和极端梯度提升)和Cox回归分别采用与CVD相关的二元性别-身份社会化因素(考虑n=25).
结果：使用ML模型确定了不同的社会化因素。在Cox模型中,对于男女来说，结婚/伴侣与CVD风险降低相关(男性:HR0.76,95%CI0.60~0.96;女性:HR0.67,95%CI0.58~0.95).对于男人来说,有3-8个亲戚，他们觉得很亲近，可以寻求帮助（HR0.76，95％CI0.58至0.99；参考<3个亲戚），有3-8名亲属可以轻松地谈论私人事务(HR0.70,95%CI0.55至0.90;参考<3名亲属)或玩棋牌等游戏(HR0.82,95%CI0.67至1.00)与CVD风险降低相关。对女人来说,与他人生活在一起(HR0.71,95%CI0.55~0.91)或有≥3个朋友他们认为可以轻松地谈论私事(HR0.74,95%CI0.58~0.95;参考<3个朋友)与较低的CVD风险相关.
结论：这项研究表明，需要优先考虑性别特定的社会因素，以改善老年人的心血管健康。
