Prevalence and Predictors of Leg Cramps in the Third Trimester of Pregnancy: A Cross-Sectional Study.

IF 2.5 4区 医学 Q2 OBSTETRICS & GYNECOLOGY
International Journal of Women's Health Pub Date : 2024-08-12 eCollection Date: 2024-01-01 DOI:10.2147/IJWH.S465872
Ala'a Abandeh, Amer Sindiani, Mohammad S Nazzal, Nihad A Almasri, Afnan Megdadi, Linzette Morris, Eman Alshdaifat, Saddam F Kanaan
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引用次数: 0

Abstract

Objective: This study aimed to estimate the prevalence and determine predictors of leg cramps among pregnant women in their third trimester.

Methods: A sample of pregnant women in their third trimester who routinely visited local clinics in Jordan was recruited. Participants completed a socio-demographic and clinical characteristics questionnaire, the numeric pain rating scale (NPRS) for leg cramp pain intensity, the Arabic version of the Pregnant Physical Activity Questionnaire (PPAQ), the Nordic Musculoskeletal Questionnaire (NMQ), Short Form Health Survey (SF-12), Pittsburgh Sleep Quality Index (PSQI), and Hospital Anxiety and Depression Scale (HADS). In addition, magnesium (Mg) and calcium (Ca) serum levels were examined. Logistic regression analyses were used to identify predictors of leg cramps occurrence. A linear regression model was used to investigate predictors of leg cramps pain intensity among pregnant women who reported leg cramps.

Results: Two hundred and five (n=205) pregnant women completed the study. The estimated prevalence of leg cramps was 58%. Logistic regression results showed that not receiving assistance with housework (OR 0.46, p=0.025), progress in the number of gestational weeks (OR 1.10, p=0.021), the number of previous pregnancies (OR 1.21, p=0.049), having leg swelling (OR 2.28, p=0.019), and having gastrointestinal (GIT) problems (OR 2.12, P=0.046) were associated with a higher odds of leg cramps occurrence. In the subsample with pregnant women with leg cramps, linear regression results showed that pregnant women with high school education versus elementary school (β=0.70, p=0.012), number of working hours (β=0.11, p=0.010), using vitamins supplements (β=-1.70, p=0.043), having diabetes after pregnancy (β=1.05, p=0.036), having sciatica (β=0.58, p=0.028), having hip pain (β =-.33, p=0.029), and higher PSQI total score (β=0.09, p=0.020) were the significant predictors of leg cramp pain intensity.

Conclusion: Many health-related conditions, as well as work and home-related work characteristics, may be considered risk factors for the occurrence of leg cramps and increased leg cramps pain intensity in pregnancy.

怀孕三个月腿抽筋的发生率和预测因素:一项横断面研究。
研究目的本研究旨在估计怀孕三个月的孕妇腿部抽筋的发生率,并确定预测因素:抽样调查了经常到约旦当地诊所就诊的怀孕三个月的孕妇。参与者填写了社会人口学和临床特征问卷、腿抽筋疼痛强度数字疼痛评级量表(NPRS)、阿拉伯语版孕妇体力活动问卷(PPAQ)、北欧肌肉骨骼问卷(NMQ)、简表健康调查(SF-12)、匹兹堡睡眠质量指数(PSQI)和医院焦虑抑郁量表(HADS)。此外,还检查了血清中的镁(Mg)和钙(Ca)水平。逻辑回归分析用于确定腿抽筋发生的预测因素。在报告腿抽筋的孕妇中,使用线性回归模型研究腿抽筋疼痛强度的预测因素:共有 255 名(n=205)孕妇完成了研究。估计腿部抽筋的发生率为 58%。逻辑回归结果显示,未接受家务协助(OR 0.46,P=0.025)、孕周数增加(OR 1.10,P=0.021)、前次怀孕次数(OR 1.21,P=0.049)、腿部肿胀(OR 2.28,P=0.019)和胃肠道(GIT)问题(OR 2.12,P=0.046)与腿部抽筋发生几率较高有关。在腿抽筋孕妇的子样本中,线性回归结果显示,受过高中教育的孕妇比受过小学教育的孕妇(β=0.70,P=0.012)、工作时间长的孕妇(β=0.11,P=0.010)、使用维生素补充剂的孕妇(β=-1.70,p=0.043)、妊娠后患糖尿病(β=1.05,p=0.036)、坐骨神经痛(β=0.58,p=0.028)、臀部疼痛(β=-.33,p=0.029)、较高的 PSQI 总分(β=0.09,p=0.020)是腿抽筋疼痛强度的显著预测因素:结论:许多与健康相关的情况以及与工作和家庭相关的工作特征,都可能被认为是孕期发生腿抽筋和增加腿抽筋疼痛强度的风险因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Journal of Women's Health
International Journal of Women's Health OBSTETRICS & GYNECOLOGY-
CiteScore
3.70
自引率
0.00%
发文量
194
审稿时长
16 weeks
期刊介绍: International Journal of Women''s Health is an international, peer-reviewed, open access, online journal. Publishing original research, reports, editorials, reviews and commentaries on all aspects of women''s healthcare including gynecology, obstetrics, and breast cancer. Subject areas include: Chronic conditions including cancers of various organs specific and not specific to women Migraine, headaches, arthritis, osteoporosis Endocrine and autoimmune syndromes - asthma, multiple sclerosis, lupus, diabetes Sexual and reproductive health including fertility patterns and emerging technologies to address infertility Infectious disease with chronic sequelae including HIV/AIDS, HPV, PID, and other STDs Psychological and psychosocial conditions - depression across the life span, substance abuse, domestic violence Health maintenance among aging females - factors affecting the quality of life including physical, social and mental issues Avenues for health promotion and disease prevention across the life span Male vs female incidence comparisons for conditions that affect both genders.
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