A long format data set from a longitudinal study of low back pain (LBP) on midwestern manufacturing workers.
LBPA data frame on the following variables:
| Variable | Description | Class |
sid: | The subject identification variable for individuals. | Factor |
Baseline.date: | The date of baseline visit or enrollment of individuals into the study. | Date |
Date: | The calendar time of follow-up visit. | Date |
time_to_row: | The number of days between the current follow-up visit and the baseline date. | Integer |
case.lbp: | A status indicator for individuals possessing any LBP (0 for no and 1 for yes). | Integer |
case.med: | A status indicator determining whether indviduals are taking medication for LBP (0 for no and 1 for yes). | Integer |
case.sc: | A status indicator to determine whether individuals are seeking care for LBP (0 for no and 1 for yes). | Integer |
case.ls: | A status indicator to determine whether individuals have lost time from work due to LBP (0 for no and 1 for yes). | Integer |
gender: | The gender of the individual (either M for Male or F for Female). | Factor |
age: | The age of the individual at baseline visit in years. | Numeric |
weight: | The weight of individuals in lbs. | Integer |
height: | The height of individuals in inches. | Integer |
raceth: | A categorical variable to determine the race/ethnicity of individuals (0 = White; 1 = Hispanic/Latino; 2 = Black; 3 = Asian; 4 = Native Hawaiian or Pacific Islander; 5 = Native American or Native Alaskan; 6 = Other/declined). | Factor |
smoking: | A smoking indicator variable (0 = Smoked less than 100 cigarettes in life; 1 = smoked in the past, but no longer, 2 = currently smoke). | Factor |
comptenure: | A categorical variable to determine length of time at the current company (0 = less than 3 months; 1 = 3 months to 1 year; 2 = 1 year to 3 years; 3 = 3 years to 5 years; 4 = 5 years to 10 years; 5 = 10 or more years). | Factor |
jobtenure: | A categorical variable to determine length of time in their current job 0 = less than 3 months; 1 = 3 months to 1 year; 2 = 1 year to 3 years; 3 = 3 years to 5 years; 4 = 5 years to 10 years; 5 = 10 or more years. | Factor |
control.order: | A categorical variable to determine how much control individuals have over the order in which they complete tasks (0 = "Very Much", 1 = "Much", 2="Moderate Amounts", 3="A Little", 4="Very Little"). | Factor |
control.pace: | A categorical variable to determine how much control individuals have over the pace in which they complete tasks (0 = "Very Much", 1 = "Much", 2="Moderate Amounts", 3="A Little", 4="Very Little"). | Factor |
control.breaks: | A categorical variable to determine the amount of control individuals have in taking breaks between completing tasks (0 = "Very Much", 1 = "Much", 2="Moderate Amounts", 3="A Little", 4="Very Little"). | Factor |
supervisor.support: | A categorical variable determining how much support individuals feel they receive from their supervisor (0="Almost Always", 1="Some of the Time", 2="Hardly Ever"). | Factor |
coworker.support: | A categorical variable determining how much support individuals feel they receive from their coworkers (0="Almost Always", 1="Some of the Time", 2="Hardly Ever"). | Factor |
job.satisfied: | A categorical variable to determine whether individuals feel satisfied with their current job (0="Very Satisfied", 1="Somewhat Satisfied", 2="A Little Satisfied", 3="Not at all Satisfied"). | Factor |
bmi: | The calculated body mass index (BMI) of individuals based on height and weight. | Numeric |
Data set construction was done through the consolidation of various source files pulled from the original database. The final data frame contains follow-up information for selected individuals. The case definitions assessed over time were case.lbp, case.med, case.sc, and case.lt. Column time_to_row is constructed using the Baseline.date and Date columns to calculate the number of days between observations (denoted by rows). All other columns are constant with respect to time. Categorical variables were recorded through self-assessment on the part of the subject. The age and weight variables were able to be physically measured to then be used in calculation of bmi.
Garg, Arun, Kurt Hegmann, J. Moore, Jay Kapellusch, Matthew Thiese, Sruthi Boda, Parag Bhoyar, Donald Bloswick, Andrew Merryweather, Richard Sesek, Gwen Deckow-Schaefer, James Foster, Eric Wood, Xiaoming Sheng, and Richard Holubkov (2013). Study protocol title: A prospective cohort study of low back pain. BMC Musculoskeletal Disorders 14(84), 84.
Ingulli, Charles. (2020). A Survey of Statistical Methods for Investigating Risk of Low Back Pain in a Cohort of Manufacturing Workers. (85696). [Master's Thesis, American University]