School of public health, University of Montreal, Montreal, Quebec, Canada.
Research center of the IUSMM, CIUSSS de l'Est de l'île de Montréal, Montreal, Quebec, Canada.
Brain Behav. 2024 Nov;14(11):e70126. doi: 10.1002/brb3.70126.
Producing relevant knowledge on the prevalence of mood disorders (MDs) requires a clear identification of people living with the condition. Analyzing this multifaceted disease from the perspective of health administrative data and population-based surveys could contribute to document inconsistencies between these data sources and highlight the strengths and limitations of each methodological approaches.
The aim of this study was to estimate the prevalence of MD disease, assess concordance of MD patterns in population-based surveys versus health administrative data, and investigate statistical differences in characteristics between individuals presenting the disease in each data sources.
This study used the Care Trajectories-Enriched Data (TorSaDE) cohort. The TorSaDE cohort is built by merging five waves of the Canadian Community Health Survey (CCHS) with health administrative data of the province of Quebec, Canada. The sample includes individuals who participated in at least one round of CCHS and for whom evidence of use of health services in the year of CCHS completion and the year before were present in health administrative data. The cohort was split into four groups based on the presence and absence of MD in self-reported versus health administrative data. Groups' characteristics were compared using chi-square tests and ANOVA.
The study cohort was composed of 96,079 individuals, of which 10,418 (10.8%) had MD, regardless of the data sources. Self-reported prevalence of MD was 6.03%, while the prevalence from health administrative data was about 7.79%. Estimates showed a low level of concordance between the two measures, as only 27.4% of people presenting this medical condition were identified in both data sources. Furthermore, individuals identified with MD only in survey data had poorer socioeconomic outcomes but better health outcomes than those from the concordant group (i.e., identified in both data sources). In addition, people presenting MD in health administrative data only had better socioeconomic and health outcomes than those who reported MD diagnosis only in survey data.
Findings suggest that each measure capture different specific subpopulations. Estimates obtained from each source should thus be contextualized and interpreted with caution.
生成关于心境障碍（MD）患病率的相关知识需要明确识别患有该疾病的人群。从卫生行政数据和基于人群的调查角度分析这种多方面的疾病，可以有助于记录这些数据源之间的不一致，并突出每种方法的优势和局限性。
本研究旨在估计 MD 疾病的患病率，评估基于人群的调查与卫生行政数据中 MD 模式的一致性，并调查在每种数据源中呈现疾病的个体之间的特征差异。
本研究使用了丰富数据的关怀轨迹研究（TorSaDE）队列。TorSaDE 队列是通过将加拿大社区健康调查（CCHS）的五个波次与加拿大魁北克省的卫生行政数据合并构建而成。该样本包括至少参加过一轮 CCHS 调查，且在 CCHS 完成年度和前一年度的卫生行政数据中存在使用卫生服务证据的个体。该队列根据自我报告和卫生行政数据中 MD 的存在与否，分为四组。使用卡方检验和方差分析比较各组的特征。
研究队列由 96079 名个体组成，其中 10418 名（10.8%）无论数据来源如何都患有 MD。自我报告的 MD 患病率为 6.03%，而卫生行政数据中的患病率约为 7.79%。估计结果表明，这两种测量方法之间的一致性水平较低，因为只有 27.4%的患有该疾病的个体在两种数据源中都被识别出来。此外，仅在调查数据中被识别出 MD 的个体具有较差的社会经济结局，但健康结局优于来自一致性组（即同时在两种数据源中被识别出的个体）。此外，仅在卫生行政数据中报告 MD 的个体的社会经济和健康结局优于仅在调查数据中报告 MD 诊断的个体。
研究结果表明，每种测量方法都捕捉到了不同的特定亚人群。因此，应谨慎地将从每个来源获得的估计值置于背景下并进行解释。
