Román Ortiz Carmen, Tenías José María, Estarlich Marisa, Ballester Ferran
Research Support Unit, La Mancha Centro General Hospital, Avenida Constitución 3, 13600, Alcázar de San Juan, Spain.
Spanish Consortium for Research on Epidemiology and Public Health, (CIBERESP), Barcelona, Spain.
Int J Biometeorol. 2015 Oct;59(10):1511-22. doi: 10.1007/s00484-014-0945-y. Epub 2014 Dec 13.
This study aims to systematically review epidemiological studies that evaluate the relationship between meteorology and the incidence of hip fracture (HF). After a search in Scopus, PubMed, and Embase, two independent authors assessed the relevance of studies and extracted data for description. From each study, we extracted the geographic and temporal scope, design, study variables (meteorological and related to HF), statistical analysis, and estimated associations. Of a total of 134 works, 20 studies were selected. All use an ecological design but one case-crossover. Most studies have been conducted in northern latitudes. The analysis methodology did not take into account the temporal structure of the data in 10 studies (regression and linear correlations); the rest used Poisson regression (7) and ARIMA model (3). Most studies showed significant positive associations with rainfall, especially in the form of snow: HF relative risk (RR) on days with precipitation vs. days without precipitation that ranged from 1.14 (95 % confidence interval (CI)1.04 to 1.24) to 1.60 (95 % CI 1.06 to 2.41), the temperature, with RR by one degree Celsius decline from 1.012 (95 % CI 1.004 to 1.020) to 1.030 (95 % CI 1.023 to 1.037), and wind (3) RR FC windiest days vs. calm days: 1.32 (95 % CI 1.10 to 1.58) to 1.35 (95 % CI 0.88 to 2.08). This review shows that analytic methods are very heterogeneous and poorly adapted to the temporary nature of the data. Studies confirm a certain seasonality, with more fractures in winter and meaningful relationships with meteorological conditions typical of this season.
本研究旨在系统回顾评估气象学与髋部骨折(HF)发病率之间关系的流行病学研究。在对Scopus、PubMed和Embase进行检索后,两位独立作者评估了研究的相关性并提取数据进行描述。我们从每项研究中提取了地理和时间范围、设计、研究变量(气象学变量及与髋部骨折相关的变量)、统计分析以及估计的关联。在总共134篇文献中,挑选出了20项研究。所有研究均采用生态学设计,但有一项采用病例交叉设计。大多数研究是在北纬地区进行的。10项研究(回归分析和线性相关分析)的分析方法未考虑数据的时间结构;其余研究采用了泊松回归(7项)和自回归积分移动平均模型(ARIMA模型,3项)。大多数研究表明,髋部骨折与降雨尤其是降雪形式存在显著正相关:有降水日与无降水日相比,髋部骨折相对风险(RR)范围为1.14(95%置信区间(CI)1.04至1.24)至1.60(95%CI 1.06至2.41);与温度存在正相关,温度每下降1摄氏度,RR从1.012(95%CI 1.004至1.020)至1.030(95%CI 1.023至1.037);与风也存在正相关(3项研究),最 windy 日与平静日相比,RR为1.32(95%CI 1.10至1.58)至1.35(95%CI 0.88至2.08)。本综述表明,分析方法非常不一致,且不太适合数据的时间特性。研究证实了一定的季节性,冬季骨折更多,且与该季节典型的气象条件存在显著关系。