METHODS: Here, we employ the Global Weather Type Classification, Version 2, to determine the combined impact of temperature and humidity on PA in a sample of insufficiently active young adults. We conducted secondary analyses of data from a single-group behavioral intervention trial that varied the number of digital messages sent daily. Young adults (n = 81) wore Fitbit Versa smartwatches for a 6-month period sometime between April 2019 and July 2020, and location was tracked using a custom smartphone application.
RESULTS: Mixed linear models indicated that, across 8179 person-days, PA was significantly lower on days with humid conditions and significantly higher on warm dry days, though the latter relationship was no longer significant when controlling for timing in relation to the COVID-19 pandemic declaration. Demographic factors did not affect the relationship between weather and PA.
CONCLUSIONS: Results are a first step in providing additional guidance for encouraging PA in insufficiently active individuals given forecasted daily weather conditions. Future work should examine seasonal variability in the weather type-PA relationship without the influence of a world-altering event influencing results.
方法:这里,我们采用全球天气类型分类,版本2,以确定温度和湿度对PA的综合影响在不充分活跃的年轻人的样品。我们对单组行为干预试验的数据进行了二次分析,该试验改变了每天发送的数字消息的数量。年轻人(n=81)在2019年4月至2020年7月之间的某个时候佩戴FitbitVersa智能手表6个月,并使用自定义智能手机应用程序跟踪位置。
结果:混合线性模型表明,8179人日,PA在潮湿条件下的日子明显较低,在温暖干燥的日子明显较高,尽管在控制与COVID-19大流行宣布相关的时间时,后一种关系不再显著。人口统计因素不影响天气与PA之间的关系。
结论:结果是为在预测的每日天气条件下不充分活跃的个体中鼓励PA提供额外指导的第一步。未来的工作应该检查天气类型-PA关系的季节性变化,而不会受到影响结果的改变世界的事件的影响。