Dalla Lana School of Public Health, University of Toronto, 155 College Street, Toronto, Ontario, M5T 3 M7, Canada.
Institute for Clinical Evaluative Sciences, Room G-106, 2075 Bayview Avenue, Toronto, Ontario, M4N 3 M5, Canada.
Popul Health Metr. 2019 Jul 31;17(1):9. doi: 10.1186/s12963-019-0193-9.
Premature mortality is a meaningful indicator of both population health and health system performance, which varies by geography in Ontario. We used the Local Health Integration Network (LHIN) sub-regions to conduct a spatial analysis of premature mortality, adjusting for key population-level demographic and behavioural characteristics.
We used linked vital statistics data to identify 163,920 adult premature deaths (deaths between ages 18 and 74) registered in Ontario between 2011 and 2015. We compared premature mortality rates, population demographics, and prevalence of health-relevant behaviours across 76 LHIN sub-regions. We used Bayesian hierarchical spatial models to quantify the contribution of these population characteristics to geographic disparities in premature mortality.
LHIN sub-region premature mortality rates ranged from 1.7 to 6.6 deaths per 1000 per year in males and 1.2 to 4.8 deaths per 1000 per year in females. Regions with higher premature mortality had fewer immigrants and higher prevalence of material deprivation, excess body weight, inadequate fruit and vegetable consumption, sedentary behaviour, and ever-smoked status. Adjusting for all variables eliminated close to 90% of geographic variation in premature mortality, but did not fully explain the spatial pattern of premature mortality in Ontario.
We conducted the first spatial analysis of mortality in Ontario, revealing large geographic variations. We demonstrate that well-known risk factors explain most of the observed variation in premature mortality. The result emphasizes the importance of population health efforts to reduce the burden of well-known risk factors to reduce variation in premature mortality.
过早死亡率是衡量人口健康和卫生系统绩效的一个有意义的指标，在安大略省因地理位置而异。我们使用地方卫生整合网络（LHIN）子区域对过早死亡率进行空间分析，调整了关键的人口水平人口统计学和行为特征。
我们使用链接的生命统计数据来确定 2011 年至 2015 年间在安大略省登记的 163920 名成年人过早死亡（18 至 74 岁之间死亡）。我们比较了 76 个 LHIN 子区域的过早死亡率、人口统计学和与健康相关行为的流行率。我们使用贝叶斯层次空间模型来量化这些人口特征对过早死亡率地理差异的贡献。
LHIN 子区域男性过早死亡率范围为每年每 1000 人 1.7 至 6.6 人，女性为每年每 1000 人 1.2 至 4.8 人。过早死亡率较高的地区移民较少，物质匮乏程度较高，超重、水果和蔬菜摄入不足、久坐行为和吸烟史较常见。调整所有变量消除了近 90%的过早死亡率的地理差异，但并未完全解释安大略省过早死亡率的空间模式。
我们对安大略省的死亡率进行了首次空间分析，揭示了较大的地理差异。我们证明，众所周知的风险因素解释了过早死亡率观察到的大部分变化。这一结果强调了人口健康工作的重要性，以减少众所周知的风险因素的负担，从而减少过早死亡率的差异。
