Risk factors associated with chronic low back pain: an analysis of Turkey health survey data

Abstract

Background: Turkey, a developing country has low back disorders as the most common symptom among adults with 33% prevalence in 2014. The patient’s self reports are important to determine the condition as chronic low back pain (CLBP) is a symptom rather than the disease. However, there is a scarcity of knowledge about self-reported CLBP among adults from developing countries. Methods: A community-based cross-sectional population survey study conducted by face-to-face interviews. To identify socio-demographic factors, health, behavior, and comorbidities associated with (CLBP). 6729 adults (≥15 years) with self-reported CLBP and 12400 non-CLBP adults who participated 2014 Turkey Health Survey (THS) were included. Data on smoking, alcohol consumption, physical activity, healthy eating behavior, muscle strengthening activities, and kinesitherapist and psychotherapist visits were collected. Socio-demographic characteristics, comorbidities, and health of CLBP and non-CLBP adults were compared using logistic regression analysis. Results: Age, gender, marital status, occupational status and health insurance were associated with a higher likelihood to report CLBP (p<0.001). The likelihood of diabetes and hypertension was higher in patients with CLBP (p<0.001). Visiting a psychotherapist, smoking and healthy eating were associated with a higher likelihood of CLBP (p<0.001) whereas, alcohol consumption, physical activity, muscle strengthening activities and visiting kinesiotherapist were associated with a lower likelihood of CLBP (p<0.001). Conclusions: Reduced smoking and alcohol consumption, healthy eating, increased physical activity, kinesitherapy and psychotherapy can be employed to manage CLBP.

The mediating role of depressive symptoms among Turkish population related to gender and low back pain: evidence from a national health survey

“…The association between the outcome and independent variables was analyzed employing binary logistic regression. All the variables included in our analyses as our independent variables were selected based on their importance in literature [ 12 , 46 ]. All variables with a p -value of < 0.1 were selected for inclusion in multivariable models [ 47 ].…”