Back pain related to Pregnancy

March 10th, 2015 by Dr. Curtis Hall

Back pain related to pregnancy can be treated drug free with chiropractic.

According to a recent study of 115 patients there was 70% improvement of lower back pain at 1 month, 85% improvement at 3 months and 90% improvement at 6 months.

A summary of the study can be found below.

Baseline numerical rating scale (NRS) and Oswestry questionnaire data were collected. Duration of complaint, number of previous LBP episodes, LBP during a previous pregnancy, and category of pain location were recorded.

The patient’s global impression of change (PGIC) (primary outcome), NRS, and Oswestry data (secondary outcomes) were collected at 1 week, 1 and 3 months after the first treatment. At 6 months and 1 year the PGIC and NRS scores were collected. PGIC responses of ‘better’ or ‘much better’ were categorized as ‘improved’.

The proportion of patients ‘improved’ at each time point was calculated. Chi-squared test compared subgroups with ‘improvement’. Baseline and follow-up NRS and Oswestry scores were compared using the paired t-test. The unpaired t-test compared NRS and Oswestry scores in patients with and without a history of LBP and with and without LBP during a previous pregnancy. Anova compared baseline and follow-up NRS and Oswestry scores by pain location category and category of number of previous LBP episodes. Logistic regression analysis also was also performed.


52% of 115 recruited patients ‘improved’ at 1 week, 70% at 1 month, 85% at 3 months, 90% at 6 months and 88% at 1 year. There were significant reductions in NRS and Oswestry scores (p < 0.0005). Category of previous LBP episodes number at one year (p = 0.02) was related to ,improvement’ when analyzed alone, but was not strongly predictive in logistic regression. Patients with more prior LBP episodes had higher 1 year NRS scores (p = 0.013).


Most pregnant patients undergoing chiropractic treatment reported clinically relevant improvement at all time points. No single variable was strongly predictive of, improvement’ in the logistic regression model.