UC San Diego Health Department of Biomedical Informatics, University of California San Diego, San Diego, CA, USA.
Shu Chien-Gene Lay Department of Bioengineering, University of California San Diego, 9500 Gilman Dr, , La Jolla, San Diego, CA, USA.
Biol Sex Differ. 2023 Nov 1;14(1):76. doi: 10.1186/s13293-023-00558-z.
Females have been historically excluded from biomedical research due in part to the documented presumption that results with male subjects will generalize effectively to females. This has been justified in part by the assumption that ovarian rhythms will increase the overall variance of pooled random samples. But not all variance in samples is random. Human biometrics are continuously changing in response to stimuli and biological rhythms; single measurements taken sporadically do not easily support exploration of variance across time scales. Recently we reported that in mice, core body temperature measured longitudinally shows higher variance in males than cycling females, both within and across individuals at multiple time scales.
Here, we explore longitudinal human distal body temperature, measured by a wearable sensor device (Oura Ring), for 6 months in females and males ranging in age from 20 to 79 years. In this study, we did not limit the comparisons to female versus male, but instead we developed a method for categorizing individuals as cyclic or acyclic depending on the presence of a roughly monthly pattern to their nightly temperature. We then compared structure and variance across time scales using multiple standard instruments.
Sex differences exist as expected, but across multiple statistical comparisons and timescales, there was no one group that consistently exceeded the others in variance. When variability was assessed across time, females, whether or not their temperature contained monthly cycles, did not significantly differ from males both on daily and monthly time scales.
These findings contradict the viewpoint that human females are too variable across menstrual cycles to include in biomedical research. Longitudinal temperature of females does not accumulate greater measurement error over time than do males and the majority of unexplained variance is within sex category, not between them.
由于有记录表明，男性研究对象的结果将有效地推广到女性身上，因此女性在历史上一直被排除在生物医学研究之外。部分原因是假设卵巢节律会增加随机样本总体的变异性。但是，样本中的并不是所有变异性都是随机的。人体生物统计学不断对外界刺激和生物节律做出反应；偶尔进行的单次测量不容易支持跨时间尺度的方差探索。最近，我们报告说，在老鼠中，纵向测量的核心体温显示男性的变异性高于周期性雌性，无论是在个体内部还是跨个体，在多个时间尺度上都是如此。
在这里，我们探索了纵向人体远端体温，使用可穿戴传感器设备（Oura Ring）在 20 至 79 岁的女性和男性中进行了 6 个月的测量。在这项研究中，我们并没有将比较仅限于女性与男性，而是根据其夜间体温是否存在大致每月的模式，开发了一种将个体分类为周期性或非周期性的方法。然后，我们使用多种标准工具比较了跨时间尺度的结构和方差。
正如预期的那样，存在性别差异，但在多个统计比较和时间尺度上，没有一个群体的变异性始终超过其他群体。当跨时间评估变异性时，无论其体温是否包含每月周期，女性在每日和每月时间尺度上都与男性没有显著差异。
这些发现与认为女性在月经周期内变化太大而无法纳入生物医学研究的观点相矛盾。女性的纵向体温随时间的推移不会累积更多的测量误差，并且大多数无法解释的变异性在性别类别内，而不是在性别之间。
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