Pelvic girdle pain - associations between risk factors in early pregnancy and disability or pain intensity in late pregnancy: a prospective cohort study

Abstract

Abstract Background Recent studies have shown high prevalence rates for pelvic girdle pain (PGP) in pregnancy. Some risk factors for developing PGP have been suggested, but the evidence is weak. Furthermore there is almost no data on how findings from clinical examinations are related to subsequent PGP. The main purpose for this study was to study the associations between socio-demographical, psychological and clinical factors measured at inclusion in early pregnancy and disability or pain intensity in gestation week 30. Methods This is a prospective cohort study following women from early to late pregnancy. Eligible women were recruited at their first attendance at the maternity care unit. 268 pregnant women answered questionnaires and underwent clinical examinations in early pregnancy and in gestation week 30. We used scores on disability and pain intensity in gestation week 30 as outcome measures to capture the affliction level of PGP. Multiple linear regression analysis was used to study the associations between potential risk factors measured in early pregnancy and disability or pain intensity in gestation week 30. Results Self-reported pain locations in the pelvis, positive posterior pelvic pain provocation (P4) test and a sum of pain provocation tests in early pregnancy were significantly associated with disability and pain intensity in gestation week 30 in a multivariable statistic model. In addition, distress was significantly associated with disability. The functional active straight leg raise (ASLR) test, fear avoidance beliefs and the number of pain sites were not significantly associated with either disability or pain intensity. Conclusions The results suggest that a clinical examination, including a few tests, performed in early pregnancy may identify women at risk of a more severe PGP late in pregnancy. The identification of clinical risk factors may provide a foundation for development of targeted prevention strategies.