Poltavskiy Eduard, Spence J David, Kim Jeehyoung, Bang Heejung
Graduate Group in Epidemiology, University of California, Davis, CA, USA.
Stroke Prevention & Atherosclerosis Research Centre, Robarts Research Institute, Western University, London, Ontario, Canada.
Online J Public Health Inform. 2016 Sep 15;8(2):e186. doi: 10.5210/ojphi.v8i2.6643. eCollection 2016.
In the modern era, with high-throughput technology and large data size, associational studies are actively being generated. Some have statistical and clinical validity and utility, or at least have biologically plausible relationships, while others may not. Recently, the potential effect of birth month on lifetime disease risks has been studied in a phenome-wide model. We evaluated the associations between birth month and 5 cardiovascular disease-related outcomes in an independent registry of 8,346 patients from Ontario, Canada in 1977-2014. We used descriptive statistics and logistic regression, along with model-fit and discrimination statistics. Hypertension and coronary heart disease (of primary interest) were most prevalent in those who were born in January and April, respectively, as observed in the previous study. Other outcomes showed weak or opposite associations. Ancillary analyses (based on raw blood pressures and subgroup analyses by sex) demonstrated inconsistent patterns and high randomness. Our study was based on a high risk population and could not provide scientific explanations. As scientific values and clinical implications can be different, readers are encouraged to read the original and our papers together for more objective interpretations of the potential impact of birth month on individual and public health as well as toward cumulative/total evidence in general.
在现代,随着高通量技术和大数据规模的发展,关联性研究正在积极开展。一些研究具有统计学和临床有效性及实用性,或者至少具有生物学上合理的关系,而其他一些研究可能并非如此。最近,在全表型模型中研究了出生月份对终生疾病风险的潜在影响。我们在1977 - 2014年加拿大安大略省8346名患者的独立登记处评估了出生月份与5种心血管疾病相关结局之间的关联。我们使用了描述性统计和逻辑回归,以及模型拟合和判别统计。如先前研究中所观察到的,高血压和冠心病(主要关注对象)分别在1月和4月出生的人群中最为普遍。其他结局显示出微弱或相反的关联。辅助分析(基于原始血压和按性别进行的亚组分析)显示出不一致的模式和高度的随机性。我们的研究基于高危人群,无法提供科学解释。由于科学价值和临床意义可能不同,鼓励读者同时阅读原文和我们的论文,以便更客观地解释出生月份对个体和公众健康的潜在影响以及总体上的累积/全部证据。