Centre for Mental Health Research, the Research School of Population Health, the Australian National University, Australia.
The Australian Geospatial Health Lab, Health Research Institute, The University of Canberra, Australia.
J Alzheimers Dis. 2021;84(2):621-632. doi: 10.3233/JAD-210208.
Dementia is a major global health challenge and the impact of built and social environments' characteristics on dementia risk have not yet been fully evaluated.
To investigate associations between built and social environmental characteristics and diagnosed dementia cases and estimated dementia risk.
We recruited 25,511 patients aged 65 and older from family physicians' practices. We calculated a dementia risk score based on risk and protective factors for patients not diagnosed with dementia. Our exposure variables were estimated for each statistical area level 1: social fragmentation, nitrogen dioxide, public open spaces, walkability, socio-economic status, and the length of main roads. We performed a multilevel mixed effect linear regression analysis to allow for the hierarchical nature of the data.
We found that a one standard deviation (1-SD) increase in NO2 and walkability score was associated with 10% higher odds of any versus no dementia (95% CI: 1%, 21% for NO2 and 0%, 22% for walkability score). For estimated future risk of dementia, a 1-SD increase in social fragmentation and NO2 was associated with a 1% increase in dementia risk (95% CI: 0, 1%). 1-SD increases in public open space and socioeconomic status were associated with 3% (95% CI: 0.95, 0.98) and 1% decreases (95% CI: 0.98, 0.99) in dementia risk, respectively. There was spatial heterogeneity in the pattern of diagnosed dementia and the estimated future risk of dementia.
Associations of neighborhood NO2 level, walkability, public open space, and social fragmentation with diagnosed dementia cases and estimated future risk of dementia were statistically significant, indicating the potential to reduce the risk through changes in built and social environments.
痴呆症是一个全球性的重大健康挑战，建筑和社会环境特征对痴呆症风险的影响尚未得到充分评估。
研究建筑和社会环境特征与诊断痴呆病例和估计痴呆风险之间的关系。
我们从家庭医生诊所招募了 25511 名 65 岁及以上的患者。我们根据未诊断为痴呆症的患者的风险和保护因素计算了痴呆风险评分。我们的暴露变量是针对每个统计区域一级（社会碎片化、二氧化氮、公共开放空间、可步行性、社会经济地位和主要道路长度）进行估计的。我们进行了多层次混合效应线性回归分析，以允许数据的层次性质。
我们发现，二氧化氮和可步行性评分每增加一个标准差（1-SD），任何痴呆症的可能性就会增加 10%（95%置信区间：1%，21%为二氧化氮和 0%，22%为可步行性评分）。对于估计的未来痴呆风险，社会碎片化和二氧化氮每增加 1-SD，痴呆风险就会增加 1%（95%置信区间：0，1%）。公共开放空间和社会经济地位每增加 1-SD，痴呆风险分别降低 3%（95%置信区间：0.95，0.98）和 1%（95%置信区间：0.98，0.99）。诊断痴呆病例和估计未来痴呆风险的模式存在空间异质性。
邻里二氧化氮水平、可步行性、公共开放空间和社会碎片化与诊断痴呆病例和估计未来痴呆风险之间存在统计学上的显著关联，表明通过改变建筑和社会环境有降低风险的潜力。
