Statistical analysis
Descriptive statistics were used to summarize the demographic
data, psychosocial and physical characteristics and the distribution
of MSDs and RULA scores of various body regions of participants. A
logistic regression was performed to predict low back pain from
ergonomic, psychosocial and individual factors. This model was
adjusted for age, sex, body mass index (BMI) and underlying
disease as possible confounders. The final model was chosen based
on having the lowest value of Akaike Information Criterion (AIC)
(Cetin and Erar, 2002). R software version 2.11.1 was used for all
analyses, and statistical significance was set at
Statistical analysisDescriptive statistics were used to summarize the demographicdata, psychosocial and physical characteristics and the distributionof MSDs and RULA scores of various body regions of participants. Alogistic regression was performed to predict low back pain fromergonomic, psychosocial and individual factors. This model wasadjusted for age, sex, body mass index (BMI) and underlyingdisease as possible confounders. The final model was chosen basedon having the lowest value of Akaike Information Criterion (AIC)(Cetin and Erar, 2002). R software version 2.11.1 was used for allanalyses, and statistical significance was set at <0.05.
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