The Effect Water-exercise on Low Back Pain and Sick Leave, Among Healthy Pregnant Women

Overview

To investigate the possible effect of an unsupervised water-exercise program, on the intensity of low back pain and the number of days spent on sick leave, among healthy pregnant women Our hypothesis is, that 45 minutes of water exercise twice a week for a period of 12 weeks during pregnancy, will reduce the intensity of low back pain and the days spent on sick leave.

Low back pain occurs frequently during pregnancy. Studies show prevalence from 50 to 70% of all pregnant women indicating a general problem. Low back pain increases with gestational age and has been shown to be an important contributing factor to sick leave during pregnancy. Low back pain also has a negative impact on the ability to perform daily chores. It is therefore important to focus on how to prevent or reduce low back pain in pregnant women. Some studies suggest that exercise decreases the pain intensity of low back pain during pregnancy. However, most women reduce the intensity of exercise and time spent exercising during pregnancy, and many women do not exercise, despite both national and international recommendation advising pregnant women to be physically active at a moderate intensity level for at least 30 minutes per day. The reason for this reduction in physical exercise level can be attributed to the growing body, pregnancy complications or a sense of insecurity while exercising. Exercise such as swimming and exercising in water have been shown to be increasingly used during pregnancy, because pregnant women feel comfortable and safe performing exercises in water. Two randomized intervention studies found that water-exercise during pregnancy can diminish low back pain and reduce the number of days spent on sick leave. In both studies, the intervention was supervised in groups and took place during the day at a scheduled time. These results indicate that supervised water-exercise may have a beneficial effect on healthy pregnant women. In Denmark, an unsupervised water exercise program for healthy pregnant women, AquaMama, was implemented in public swimming pools in 2011. However, there is no evidence on the effect of unsupervised water exercise programs on the intensity of low back pain and the number of days spent on sick leave. We therefore developed an unsupervised individual water exercise program on the basis of AquaMama supplemented with supportive components to be tested in a randomized controlled trial. Recruitment Pregnant women are recruited from the Department of Obstetrics, Rigshospitalet, Copenhagen, Denmark. The women are selected on the basis of their due date to time the water exercise intervention from the 20th to 32nd weeks of gestation. The women eligible for participation are invited to participate by a mailed invitation send by post with an enclosed description of the project. After one week the women are contacted by telephone or email and invited to an interview, a physical examination of the pelvic and to fill out a baseline questionnaire. Intervention * One introduction session * Unsupervised water-exercises, of a duration of 45 min, twice a week for 12 weeks * A weekly supportive email Statistical analysis plan General statistical considerations: The primary data analysis will be performed based on the intention-to-treat principle. Baseline data (parity, previous low back pain) for the two groups will by compared: For quantitative data a t-test will be applied if the data are sufficiently normal, otherwise the Kruskal-Wallis test will be applied. Categorical data will be compared by the Fisher or chi-square test, the latter being applied if the condition of the expected values being larger than 5 is fulfilled. A t-test will be applied to compare the mean of the primary outcome in the two groups. Similarly secondary outcomes will be compared using t-tests. For the secondary outcomes, the p-values will be adjusted for multiple testing using the Benjamini-Hochberg correction method. If the data are not sufficiently normally distributed, a transformation will be applied if possible. To explore the impact of parity and previous low back pain score on the outcomes, additional linear regression analyses of the outcomes will be performed In case of influential observations (probably only relevant for number of days on sick leave), robust regression techniques will be applied. Per- protocol analysis will be performed of the pregnant women who perform ≥ 75% of all training sessions. The significance level will set at 0.05. Sample size assessment: Sample size calculation was based on the following conditions: * 2 points reduction on a numerical pain scale of 0-10, for the patient experiencing a reduction in pain as clinically important. * The Average highest pain at baseline is 5.8 and SD = 3 (3; 35). -A total of 70% of all pregnant women who experience low back pain. * We assume that the effect of the intervention is 2.0 points if all participants complete the full program. * It is estimated that 50% of participants follow the program for at least 75% of the sessions (high participation, 19-24 sessions) while 35% follow 50-75% (moderate participation, 12 -18 sessions) and 15% follow less than half of the program (low participation). We estimate that the effect of high participation in the training course is a reduction of 2 points, the effect of moderate participation in the training course is a reduction of 1 point, while low participation does not result in a reduction. This gives an overall reduction in the intervention group of 1.35 points (0.50 \* 2 + 0.35 \* 1 + 0.15 \* 0 = 1.35). A difference in pain level of 1.35 (SD = 3.0) will be available with a power of 90% and a significance level of 5% (two-sided) with 150 participants in each group. Strategy in case of missing outcomes For outcomes with less than 5 percent missing data, complete case analyses will be reported. If the percentage of missing data exceeds 5, a sensitivity analysis based on worst-best and best-worst imputation will be applied (in the experimental arm imputing the worst / best outcomes observed in the control arm to the missing outcomes and vice versa for the control arm). In case these analyses give rise to the same conclusion as the complete case analyses, the latter will be reported. Otherwise data will be assumed Missing At Random (MAR) and analyses will be performed using Maximum-Likelihood or Inverse Probability Weighting.

Conditions

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Eligibility

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Outcomes