Department of Community Health Science, Cumming School of Medicine, University of Calgary, 3280 Hospital Drive NW, HRIC Building, Room 3C58, Calgary, AB, T2N 4Z6, Canada.
McCaig Bone and Joint Health Institute, University of Calgary, Calgary, Canada.
BMC Public Health. 2020 Oct 15;20(1):1551. doi: 10.1186/s12889-020-09599-0.
Knowledge of geospatial pattern in comorbidities prevalence is critical to an understanding of the local health needs among people with osteoarthritis (OA). It provides valuable information for targeting optimal OA treatment and management at the local level. However, there is, at present, limited evidence about the geospatial pattern of comorbidity prevalence in Alberta, Canada.
Five administrative health datasets were linked to identify OA cases and comorbidities using validated case definitions. We explored the geospatial pattern in comorbidity prevalence at two standard geographic areas levels defined by the Alberta Health Services: descriptive analysis at rural-urban continuum level; spatial analysis (global Moran's I, hot spot analysis, cluster and outlier analysis) at the local geographic area (LGA) level. We compared area-level indicators in comorbidities hotspots to those in the rest of Alberta (non-hotspots).
Among 359,638 OA cases in 2013, approximately 60% of people resided in Metro and Urban areas, compared to 2% in Rural Remote areas. All comorbidity groups exhibited statistically significant spatial autocorrelation (hypertension: Moran's I index 0.24, z score 4.61). Comorbidity hotspots, except depression, were located primarily in Rural and Rural Remote areas. Depression was more prevalent in Metro (Edmonton-Abbottsfield: 194 cases per 1000 population, 95%CI 192-195) and Urban LGAs (Lethbridge-North: 169, 95%CI 168-171) compared to Rural areas (Fox Creek: 65, 95%CI 63-68). Comorbidities hotspots included a higher percentage of First Nations or Inuit people. People with OA living in hotspots had lower socioeconomic status and less access to care compared to non-hotspots.
The findings highlight notable rural-urban disparities in comorbidities prevalence among people with OA in Alberta, Canada. Our study provides valuable evidence for policy and decision makers to design programs that ensure patients with OA receive optimal health management tailored to their local needs and a reduction in current OA health disparities.
了解共病患病率的地理空间模式对于理解骨关节炎（OA）患者的当地健康需求至关重要。它为在当地层面上针对最佳 OA 治疗和管理提供了有价值的信息。然而，目前，有关加拿大艾伯塔省共病患病率的地理空间模式的证据有限。
使用经过验证的病例定义，将五个行政健康数据集进行链接，以确定 OA 病例和共病。我们在由艾伯塔省卫生服务局定义的两个标准地理区域水平上探索了共病患病率的地理空间模式：农村-城市连续体水平的描述性分析；局部地理区域（LGA）水平的空间分析（全局 Moran's I、热点分析、聚类和异常值分析）。我们比较了热点地区和艾伯塔省其他地区（非热点地区）的区域水平指标。
在 2013 年的 359638 例 OA 病例中，约有 60%的人居住在大都市和城市地区，而只有 2%的人居住在农村偏远地区。所有共病组均表现出统计学上显著的空间自相关（高血压：Moran's I 指数 0.24，z 分数 4.61）。除了抑郁症之外，共病热点主要位于农村和农村偏远地区。抑郁症在大都市（埃德蒙顿-阿博茨菲尔德：每 1000 人中有 194 例，95%CI 192-195）和城市 LGA（莱斯布里奇-北：169，95%CI 168-171）中更为普遍，而不是农村地区（福克斯克里克：65，95%CI 63-68）。共病热点包括更高比例的第一民族或因纽特人。与非热点地区相比，居住在热点地区的 OA 患者社会经济地位较低，获得医疗保健的机会也较少。
这些发现突出了加拿大艾伯塔省 OA 患者共病患病率的显著城乡差异。我们的研究为政策制定者和决策者提供了有价值的证据，以制定计划，确保 OA 患者接受针对其当地需求的最佳健康管理，并减少当前 OA 健康差距。
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