Dataset for Urinary incontinence in female weightlifters

OVERVIEW

Title of Dataset: Urinary incontinence in female weightlifters

Reference: doi: 10.1371/journal.pone.0278376. PMID: 36449558; PMCID: PMC9710785.

Author Information

Name: Marianne Huebner
Institution: Michigan State University
Address: East Lansing, MI 48824

Period of data collection: 27 April – 20 May 2022

Geographic region of data collection: Online survey in USA with participants from 29 countries in IWF regions Africa, Asia, Europe, Oceania, PanAmerican

LIST OF FILES
Dataset: wlisi_zenodo.xlsx
Data dictionary: wlisi_meta.xlsx

METHODOLOGICAL INFORMATION

Description of methods used for collection/generation of data: The survey was distributed by the Master Committee of the International Weightlifting Federation (IWF) to the National Master Chairs. They then used email or social media to communicate the study to the women weightlifters. The Survey was available in four languages (English, German, French, Spanish), translated and tested by native speakers. In addition, the survey was advertised in weightlifting interest groups via Facebook and Instagram. The survey was administered online via Qualtrics (Provo, UT, USA).

Methods for processing the data: Data were downloaded from Qualtrics (Provo, UT, USA) to Excel and then pre-processed in the statistical software R v. 4.0.3. (https://www.r-project.org)

Variable formats (numeric, character) were checked and transformed, as appropriate.

Data quality checks:  Exclusion criteria were younger than 30 years  (n=1), missing age (n=1), currently pregnant (n=3). To account for the possibility of male participants missing responses to age of menstruation or prior pregnancies (n=15), were also excluded. Since the focus was on competitive weightlifters, missing response to age of first competition (n=34) or no snatch or clean and jerk in the last 6 months (n=14) were also exclusion criteria. This resulted in an analysis data set of 824 women. Univariate distributions were evaluated numerically and graphically.

DATA-SPECIFIC INFORMATION

Number of variables: 27

Number of cases/rows: 824

Variable List: wlisi_meta.xlsx

Missing data codes: NA