Division of Chronic Disease Epidemiology, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.
Division of Epidemiology and Biostatistics, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.
Br J Nutr. 2022 Apr 14;127(7):1037-1049. doi: 10.1017/S0007114521001525. Epub 2021 May 11.
We investigated the associations between dietary patterns and chronic disease mortality in Switzerland using an ecological design and explored their spatial dependence, i.e. the tendency of near locations to present more similar and distant locations to present more different values than randomly expected. Data of the National Nutrition Survey menuCH (n 2057) were used to compute hypothesis- (Alternate Healthy Eating Index (AHEI)) and data-driven dietary patterns. District-level standardised mortality ratios (SMR) were calculated using the Swiss Federal Statistical Office mortality data and linked to dietary data geographically. Quasipoisson regression models were fitted to investigate the associations between dietary patterns and chronic disease mortality; Moran's I statistics were used to explore spatial dependence. Compared with the first, the fifth AHEI quintile (highest diet quality) was associated with district-level SMR of 0·95 (95 % CI 0·93, 0·97) for CVD, 0·91 (95 % CI 0·88, 0·95) for ischaemic heart disease (IHD), 0·97 (95 % CI 0·95, 0·99) for stroke, 0·99 (95 % CI 0·98, 1·00) for all-cancer, 0·98 (95 % CI 0·96, 0·99) for colorectal cancer and 0·93 (95 % CI 0·89, 0·96) for diabetes. The Swiss traditional and Western-like patterns were associated with significantly higher district-level SMR for CVD, IHD, stroke and diabetes (ranging from 1·02 to 1·08) compared with the Prudent pattern. Significant global and local spatial dependence was identified, with similar results across hypothesis- and data-driven dietary patterns. Our study suggests that dietary patterns partly contribute to the explanation of geographic disparities in chronic disease mortality in Switzerland. Further analyses including spatial components in regression models would allow identifying regions where nutritional interventions are particularly needed.
我们采用生态设计研究了瑞士饮食模式与慢性病死亡率之间的关联,并探讨了它们的空间依赖性,即接近的地点呈现更相似的值,而遥远的地点呈现更不同的值,这超过了随机预期。使用国家营养调查菜单 CH(n=2057)的数据来计算假设性的(替代健康饮食指数(AHEI))和数据驱动的饮食模式。使用瑞士联邦统计局的死亡率数据计算区县级标准化死亡率比(SMR),并在地理上与饮食数据相关联。使用拟泊松回归模型来研究饮食模式与慢性病死亡率之间的关联;使用 Moran's I 统计量来探索空间依赖性。与第一五分位数相比,第五五分位数(最高饮食质量)与心血管疾病区县级 SMR 为 0.95(95%CI 0.93,0.97)、缺血性心脏病(IHD)为 0.91(95%CI 0.88,0.95)、中风为 0.97(95%CI 0.95,0.99)、所有癌症为 0.99(95%CI 0.98,1.00)、结直肠癌为 0.98(95%CI 0.96,0.99)、糖尿病为 0.93(95%CI 0.89,0.96)相关。与谨慎模式相比,瑞士传统模式和西式模式与心血管疾病、IHD、中风和糖尿病的区县级 SMR 显著更高(范围为 1.02 至 1.08)。发现了显著的全局和局部空间依赖性,在假设性和数据驱动的饮食模式中都得到了相似的结果。我们的研究表明,饮食模式在一定程度上解释了瑞士慢性病死亡率的地域差异。在回归模型中纳入空间成分的进一步分析可以确定需要营养干预的特定区域。