Predictors of Leg Cramps in Primary Care Patients

This dataset examines variables predicting the presence of leg cramps, including age, gender, rurality, BMI, sedentarism, physical activity, chronic cardiometabolic conditions, and medication use. It was created by Jenenne Geske and last updated in February 2026. The specific number of rows and columns is unknown.

Use Cases

• Analyze the relationship between BMI and the presence of leg cramps across different age groups.
• Investigate how chronic cardiometabolic health conditions correlate with leg cramps, controlling for physical activity levels.
• Model the predictive power of sedentarism versus physical activity on leg cramps in rural versus urban populations.
• Examine the association between the use of diuretics or albuterol and the reported presence of leg cramps.

Strengths

• Data includes multiple predictor variables such as age, gender, BMI, and medication use.
• Focuses on a specific clinical question regarding leg cramps in a primary care context.
• Dataset was last updated in February 2026, indicating recent maintenance.

Limitations

• The sample size (number of rows) is unknown, limiting assessment of statistical power.
• Specific column definitions and data types are not provided, complicating analysis.
• Geographic and temporal coverage of the primary care data is unspecified.

Provenance

Source

Harvard Dataverse

Collection Method

Variables compiled to examine predictors of leg cramps in primary care patients.

Freshness

Last updated on 2026-02-12.