Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, Ministry of Education Key Lab of Environment and Health, and State Key Laboratory of Environment Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Lancet Healthy Longev. 2023 Dec;4(12):e693-e702. doi: 10.1016/S2666-7568(23)00211-8.
Modifiable risk factor estimates are sparse for early-onset dementia incidence. This study aimed to estimate and compare the risk factor profiles of early-onset dementia and late-onset dementia, and to explore the complex relationships between socioeconomic status, lifestyles, and early-onset dementia risk.
In this prospective cohort study, we used data from the UK Biobank for analysis of early-onset dementia and late-onset dementia. For early-onset dementia analyses, data were collected on those aged younger than 60 years without prevalent dementia at baseline. For late-onset dementia analyses, data were collected on those aged 65 years or older at the end of follow-up. Participants with missing information on socioeconomic factors were excluded. Two models were used to test associations between early-onset dementia incidence and socioeconomic status. The first model tested associations between socioeconomic status and early-onset and late-onset dementia incidence, adjusting for covariates. Participant socioeconomic status was defined using education level, income, and employment status via latent class analysis. The second model additionally included a healthy lifestyle score, which was constructed using data on smoking, alcohol consumption, physical activity, and the Healthy Diet Index. Incident early-onset dementia was defined as a dementia case diagnosed before 65 years of age. Multivariable-adjusted Cox proportional hazard regression models were used to estimate the hazard ratio (HR) for risk of dementia. We used multivariable-adjusted Cox proportional-hazard regression models to estimate the HR for risk of both early-onset dementia and late-onset dementia.
Between 2007 and 2010, 257 345 individuals were included in the analysis of early-onset dementia, and 294 133 older individuals were included in the analysis of late-onset dementia. During a mean follow-up of 11·9-12·5 years, 502 early-onset dementia cases and 5768 late-onset dementia cases were documented. Risk factor profiles were typically dissimilar between early-onset dementia and late-onset dementia. For instance, the age and sex adjusted HR for low socioeconomic status (vs high) was 4·40 (95% CI 3·43-5·65) for early-onset dementia and 1·90 (1·74-2·07) for late-onset dementia, yielding a ratio of HRs of 2·32 (1·78-3·02). After adjusting for various risk factors, participants with low socioeconomic status (vs high) had increased risk for early-onset dementia (3·38, 2·61-4·37), and overall lifestyle mediated 3·2% (1·8-5·7) of the association. Individuals with both low socioeconomic status and unhealthy lifestyles had a higher risk of early-onset dementia (5·40, 3·66-7·97). No significant interaction was observed between lifestyle and socioeconomic status. The association between socioeconomic status and early-onset dementia seemed to be more pronounced in individuals with type 2 diabetes (HR 11·21, 95% CI 2·70-46·57).
Early-onset dementia and late-onset dementia might have different risk factor profiles; although risk factors were similar, the magnitude of associations between risk factors and dementia incidence was greater for early-onset dementia. Only a small proportion of the socioeconomic inequity in dementia risk was mediated by healthy lifestyles, which indicates that measures other than healthy lifestyle promotion to improve social determinants of health are warranted.
The National Key Research and Development Program of China, the National Natural Science Foundation of China, the Hubei Province Science Fund for Distinguished Young Scholars, and the Fundamental Research Funds for the Central Universities.
对于早发性痴呆症的发病率,可改变的风险因素估计值很少。本研究旨在估计和比较早发性痴呆症和迟发性痴呆症的风险因素特征,并探讨社会经济地位、生活方式与早发性痴呆症风险之间的复杂关系。
在这项前瞻性队列研究中,我们使用英国生物银行的数据来分析早发性痴呆症和迟发性痴呆症。对于早发性痴呆症分析,数据收集了基线时年龄小于 60 岁且无明显痴呆的人群。对于迟发性痴呆症分析,数据收集了随访结束时年龄在 65 岁及以上的人群。对社会经济因素缺失信息的参与者进行了排除。采用两种模型来检验早发性痴呆症发病率与社会经济地位之间的关联。第一种模型检验了社会经济地位与早发性和迟发性痴呆症发病率之间的关联,调整了协变量。参与者的社会经济地位通过潜在类别分析,使用教育水平、收入和就业状况来定义。第二种模型还包括了一个健康生活方式评分,该评分是根据吸烟、饮酒、身体活动和健康饮食指数的数据构建的。早发性痴呆症的定义是在 65 岁之前诊断出的痴呆病例。多变量调整的 Cox 比例风险回归模型用于估计痴呆风险的危险比(HR)。我们使用多变量调整的 Cox 比例风险回归模型来估计早发性痴呆症和迟发性痴呆症的风险 HR。
2007 年至 2010 年间,共有 257345 人纳入早发性痴呆症分析,294133 名年龄较大的人纳入迟发性痴呆症分析。在平均 11.9-12.5 年的随访期间,记录了 502 例早发性痴呆症病例和 5768 例迟发性痴呆症病例。早发性痴呆症和迟发性痴呆症的风险因素特征通常不同。例如,低社会经济地位(vs 高)的年龄和性别调整 HR 为早发性痴呆症 4.40(95%CI 3.43-5.65),迟发性痴呆症 1.90(1.74-2.07),得出 HR 比值为 2.32(1.78-3.02)。在调整了各种风险因素后,低社会经济地位(vs 高)的参与者早发性痴呆症风险增加(3.38,2.61-4.37),整体生活方式对该关联的中介作用为 3.2%(1.8-5.7)。低社会经济地位和不健康生活方式并存的个体早发性痴呆症风险更高(5.40,3.66-7.97)。生活方式和社会经济地位之间没有观察到显著的相互作用。在患有 2 型糖尿病的个体中,社会经济地位与早发性痴呆症之间的关联似乎更为明显(HR 11.21,95%CI 2.70-46.57)。
早发性痴呆症和迟发性痴呆症可能具有不同的风险因素特征;尽管风险因素相似,但风险因素与痴呆症发病率之间的关联程度在早发性痴呆症中更大。健康生活方式仅能解释痴呆症风险中社会经济不平等的一小部分,这表明需要采取其他措施来改善健康的社会决定因素,而不仅仅是促进健康的生活方式。
早发性痴呆症和迟发性痴呆症的风险因素特征可能不同;尽管风险因素相似,但早发性痴呆症与痴呆症发病率之间的关联程度更大。健康生活方式只能部分解释痴呆风险中的社会经济不平等,这表明需要采取其他措施来改善健康的社会决定因素,而不仅仅是促进健康的生活方式。
国家重点研发计划、国家自然科学基金、湖北省自然科学基金杰出青年基金、中央高校基本科研业务费专项资金。