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gender_index [2020/08/20 10:07] laura [Data selection] |
gender_index [2020/08/20 14:33] trynke |
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====== Gender index ====== | ====== Gender index ====== | ||
- | Adult [[start|Lifelines]] participants completed [[1A|baseline]] questions on a broad range of topics, enabling researchers from the [[https://www.rug.nl/staff/a.v.ballering/research|University Medical Center Groningen]] to calculate a gender index. | + | Adult [[start|Lifelines]] participants completed [[1A|baseline]] questions on a broad range of topics, enabling researchers from the [[https://www.rug.nl/staff/a.v.ballering/research|University Medical Center Groningen]] to calculate a gender index. This index is a continuum, ranging from 0% (masculinity) to 100% (femininity). A gender index of 50% indicates androgyny, where equal levels of feminine and masculine characteristics are present ([[sections]]: [[demographics]] ([[sex & gender]]) and [[secondary & linked variables]]). |
- | The gender index can be requested in the Lifelines catalogue or by mail (data@lifelines.nl). When this data has been used in your research, you will have to include a reference to the reference paper listed below. | + | The gender index can be requested in the Lifelines catalogue or by mail (data@lifelines.nl). When this data has been used in your research, you will have to include a reference to the following paper: |
- | + | * [[https://doi.org/10.1016/j.socscimed.2020.112968|Ballering A.V., Bonvanie I.J., olde Hartman T.C., Monden R., Rosmalen J.G.M. (2020) Gender and sex independently associate with common somatic symptoms and lifetime prevalence of chronic disease. Social Science & Medicine]]. | |
- | ===== Reference paper ===== | + | |
- | [[https://doi.org/10.1016/j.socscimed.2020.112968|Ballering A.V., Bonvanie I.J., olde Hartman T.C., Monden R., Rosmalen J.G.M. (2020) Gender and sex independently associate with common somatic symptoms and lifetime prevalence of chronic disease. Social Science & Medicine.]] \\ | + | |
===== Data selection ===== | ===== Data selection ===== | ||
- | Participants had to meet several participants in order to be included in the calculation: | + | Participants had to meet several criteria in order to be included in the calculation: |
- | * Participants have completed the adult baseline questionnaire | + | * Participants have completed the adult [[1A|baseline]] questionnaires |
- | * Participants have their DNA analyzed in GWAS | + | * Participants have their DNA analyzed in [[GWAS|GWAS]] |
* Participants had no suspected intersex condition or non-conform gender identity | * Participants had no suspected intersex condition or non-conform gender identity | ||
This selection resulted in the inclusion of N=13,321 adult Lifelines participants in a subsample, which was used to calculate the gender index.\\ | This selection resulted in the inclusion of N=13,321 adult Lifelines participants in a subsample, which was used to calculate the gender index.\\ | ||
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All psychological and social variables are included in the model to construct the gender index, as far as these meet both of the following criteria: | All psychological and social variables are included in the model to construct the gender index, as far as these meet both of the following criteria: | ||
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===== Calculation derivative variable ===== | ===== Calculation derivative variable ===== | ||
- | To construct the gender index, selected variables were entered into an elastic net regularized generalized linear model with sex as dichotomous outcome. The participants were randomly assigned to a trainingset (80%) and a testing set (20%). Where the trainingset was used to estimate coefficients and the testing set was used to calculate the model's predictive accuracy. | + | To construct the gender index, 245 (dummy) variables, derived from the 153 selected variables were entered into an elastic net regularized generalized linear model, with sex as a dichotomous outcome. The participants were randomly assigned to a trainingset (80%) and a testset (20%). The trainingset was used to estimate regression coefficients, whereas the testing set was used to calculate the developed model’s predictive accuracy. Ultimately, an alpha = 1.0 was found to be the optimal regularization parameter, equaling a LASSO logistic regression. Of the initial 245 potentially sex-related variables, 92 were excluded from the model and 153 (dummy) variables remained representing 85 unique variables. The model’s AUC was 92%. |
- | Estimates of the coefficients (AUC 92%) obtained through the aforementioned regression ultimately formed the basis of the compisite gender idex that was applied to each adult Lifelines participant.\\ | + | The estimates of the coefficients obtained through the aforementioned regression formed the basis of the composite gender index that was applied to each adult Lifelines participant. \\ |
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**Derivative variable**\\ | **Derivative variable**\\ | ||
- | The resulting variable from this analysis is the gender index. This variable is a continuum, ranging from 0% to 100%, and represents the probability of individual being a woman (higher gender index = more feminine characteristics). Androgyny is indicated by an index of 50%, where equal levels of feminine and masculine characteristics are present.\\ | + | The resulting variable from this analysis is the gender index. This variable is a continuum, ranging from 0% (masculinity) to 100% (femininity). A gender index of 50% indicates androgyny, where equal levels of feminine and masculine characteristics are present.\\ |
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- | ===== Papers using the Lifelines gender index ===== | ||
- | * Ballering A.V., Bonvanie I.J., olde Hartman T.C., Monden R., Rosmalen J.G.M. (2020) Gender and sex independently associate with common somatic symptoms and lifetime prevalence of chronic disease. Social Science & Medicine. | ||
- | * ... |