EPIUnit-Instituto de Saúde Pública, Universidade do Porto, Rua das Taipas, 135-139, 4050-600, Porto, Portugal.
Escola Superior de Saúde de Santa Maria, Porto, Portugal.
Rheumatol Int. 2018 May;38(5):905-915. doi: 10.1007/s00296-018-3990-8. Epub 2018 Feb 8.
The aim of this study was to quantify the population impact of rheumatic and musculoskeletal diseases (RMDs) with other non-communicable diseases (NCDs), using two complementary strategies: standard multivariate models based on global burden of disease (GBD)-defined groups vs. empirical mutually exclusive patterns of NCDs. We used cross-sectional data from the Portuguese Fourth National Health Survey (n = 23,752). Six GBD-defined groups were included: RMDs, chronic obstructive pulmonary disease or asthma, cancer, depression, diabetes or renal failure, and stroke or myocardial infarction. The empirical approach comprised the patterns "low disease probability", "cardiometabolic conditions", "respiratory conditions" and "RMDs and depression". As recommended by the outcome measures in rheumatology (OMERACT) initiative, health outcomes included life impact, pathophysiological manifestations, and resource use indicators. Population attributable fractions (PAF) were computed for each outcome and bootstrap confidence intervals (95% CI) were estimated. Among GBD-defined groups, RMDs had the highest impact across all the adverse health outcomes, from frequent healthcare utilization (PAF 7.8%, 95% CI 6.2-9.3) to negative self-rated health (PAF 18.1%, 95% CI 15.4-20.6). In the empirical approach, patterns "cardiometabolic conditions" and "RMDs and depression" had similar PAF estimates across all adverse health outcomes, but "RMDs and depression" showed significantly higher impact on chronic pain (PAF 8.9%, 95% CI 7.6-10.3) than the remaining multimorbidity patterns. RMDs revealed the greatest population impact across all adverse health outcomes tested, using both approaches. Empirical patterns are particularly interesting to evaluate the impact of RMDs in the context of their co-occurrence with other NCDs.
本研究旨在通过两种互补策略来量化风湿和肌肉骨骼疾病（RMDs）与其他非传染性疾病（NCDs）的人群影响：基于全球疾病负担（GBD）定义的疾病组的标准多变量模型与 NCD 的经验性互斥模式。我们使用葡萄牙第四次国家健康调查的横断面数据（n=23752）。纳入了六个 GBD 定义的疾病组：RMDs、慢性阻塞性肺疾病或哮喘、癌症、抑郁症、糖尿病或肾衰竭，以及中风或心肌梗死。经验性方法包括“低疾病概率”、“心血管代谢状况”、“呼吸道状况”和“RMD 和抑郁症”模式。按照风湿病结局测量倡议（OMERACT）的建议，健康结果包括生活影响、病理生理表现和资源利用指标。计算了每种结局的人群归因分数（PAF），并估计了自举置信区间（95%CI）。在 GBD 定义的疾病组中，RMDs 在所有不良健康结局中具有最高的影响，从频繁的医疗保健利用（PAF 7.8%，95%CI 6.2-9.3）到负面的自我评估健康（PAF 18.1%，95%CI 15.4-20.6）。在经验性方法中，“心血管代谢状况”和“RMD 和抑郁症”模式在所有不良健康结局中的 PAF 估计值相似，但“RMD 和抑郁症”模式在慢性疼痛方面的影响显著高于其他多种疾病模式（PAF 8.9%，95%CI 7.6-10.3）。两种方法都表明，RMDs 在所有测试的不良健康结局中具有最大的人群影响。经验性模式在评估 RMDs 与其与其他 NCDs 同时发生的情况下的影响时特别有趣。
