In addition to biological sex, gender, defined as the sociocultural dimension of being a woman or a man, plays a central role in health. However, there are so far few approaches to quantify gender in a retrospective manner in existing study datasets. We therefore aimed to develop a methodology that can be retrospectively applied to assess gender in existing cohorts. We used baseline data from the Berlin Aging Study II (BASE-II), obtained in 2009–2014 from 1869 participants aged 60 years and older. We identified 13 gender-related variables and used them to construct a gender score by using primary component and logistic regression analyses. Of these, nine variables contributed to a gender score: chronic stress, marital status, risk-taking behaviour, personality attributes: agreeableness, neuroticism, extraversion, loneliness, conscientiousness, and level of education. Females and males differed significantly in the distribution of the gender score, but a significant overlap was also found. Thus, we were able to develop a gender score in a retrospective manner from already collected data that characterized participants in addition to biological sex. This approach will allow researchers to introduce the notion of gender retrospectively into a large number of studies.

中文翻译：

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柏林老龄化研究 II 中的性别评分发展：回顾性方法

除了生理性别之外，性别（定义为女性或男性的社会文化维度）在健康方面发挥着核心作用。然而，迄今为止，在现有研究数据集中以回顾性方式量化性别的方法很少。因此，我们旨在开发一种可以回顾性应用于评估现有队列中的性别的方法。我们使用了柏林老龄化研究 II (BASE-II) 的基线数据，该研究于 2009-2014 年从 1869 名 60 岁及以上的参与者中获得。我们确定了 13 个与性别相关的变量，并使用它们通过主要成分和逻辑回归分析构建了性别评分。其中，九个变量对性别评分有贡献：慢性压力、婚姻状况、冒险行为、性格属性：随和、神经质、外向、孤独、尽责、和教育水平。女性和男性在性别得分的分布上存在显着差异，但也发现了显着的重叠。因此，我们能够从已经收集的数据中以回顾性的方式制定性别评分，这些数据除了生理性别之外还表征了参与者。这种方法将使研究人员能够在大量研究中回顾性地引入性别的概念。