Chen Hung-Hui, Lee Ching-Fang, Huang Jian-Pei, Hsiung Yvonne, Chi Li-Kang
School of Nursing, College of Medicine, National Taiwan University, Taipei, Taiwan.
Department of Nursing, National Taiwan University Hospital, Taipei, Taiwan.
J Nurs Scholarsh. 2023 Jan;55(1):304-318. doi: 10.1111/jnu.12813. Epub 2022 Sep 19.
To explore the effectiveness of a nurse-led mobile health (mHealth) intervention to prevent excessive gestational weight gain (GWG) in overweight and obese women.
A randomized controlled trial with an experimental study design. Ninety-two pregnant women with body mass index (BMI) ≥25 kg/m at less than 17 weeks gestation were recruited from two prenatal clinics in northern Taiwan from January to June 2020. The experimental group used the MyHealthyWeight (MHW) app and a wearable activity tracker (WAT), and the controls received standard antenatal treatments with no mHealth-based elements. Two hospital follow-up visits were scheduled at 24-26 weeks in the second trimester and 34-36 weeks in the third trimester. A generalized estimating equation (GEE) was used to examine the trajectories and the effectiveness of mHealth on GWG.
No difference in GWG was found between the intervention and control groups at baseline (p > 0.05). The GWG trajectory in the entire cohort of women with obesity exhibited a quadratic pattern (ß = 1.8, 95% confidence interval [CI] = 1.27-2.32), and intervention participants' weekly GWG was gained significantly lower than their controls in the second trimester (p < 0.05). Throughout the pregnancy, the mHealth intervention group had a significantly lower proportion of individuals who exceeded their GWG in both total (21.6% vs. 32.6%) and weekly weight gain (first trimester = 58.7% vs. 65.2%; second trimester = 45% vs. 67.4%; third trimester = 48.6% vs. 55.1%). In particular, among obese women in the third trimester, those in the intervention group gained less gestational weight than their controls. The adjusted body weight difference was 5.44 kg (p = 0.023), signifying the total GWG difference (3.30 vs. 8.74 kg) between the means of the two groups. The GEE model indicated that obese women who were aged 35 years, had prepregnancy exercise habits, perceived self-efficacy of diet, and more physical activity tended to have low GWG (p < 0.05).
The nurse-led mHealth-based intervention shows promising results in significantly preventing excessive GWG among high-BMI women. More effectiveness was found among the obese subgroup.
The mHealth-based intervention would be successfully implemented by nurses to help high-BMI women maintain their optimal body weight and promote healthy behavioral changes, particularly in diet and physical activity during pregnancy.
探讨由护士主导的移动健康(mHealth)干预措施对预防超重和肥胖孕妇孕期体重过度增加(GWG)的有效性。
采用实验性研究设计的随机对照试验。2020年1月至6月,从台湾北部的两家产前诊所招募了92名妊娠小于17周、体重指数(BMI)≥25 kg/m²的孕妇。实验组使用“MyHealthyWeight(MHW)”应用程序和可穿戴活动追踪器(WAT),对照组接受不包含基于mHealth元素的标准产前治疗。安排在孕中期的24 - 26周和孕晚期的34 - 36周进行两次医院随访。使用广义估计方程(GEE)来检验mHealth对GWG的轨迹和有效性。
干预组和对照组在基线时的GWG无差异(p > 0.05)。肥胖女性整个队列的GWG轨迹呈二次曲线模式(β = 1.8,95%置信区间[CI] = 1.27 - 2.32),干预组参与者在孕中期的每周GWG显著低于对照组(p < 0.05)。在整个孕期,mHealth干预组在总体(21.6%对32.6%)和每周体重增加方面(孕早期 = 58.7%对65.2%;孕中期 = 45%对67.4%;孕晚期 = 48.6%对55.1%)超过GWG的个体比例显著更低。特别是在孕晚期的肥胖女性中,干预组的孕期体重增加少于对照组。调整后的体重差异为5.44 kg(p = 0.023),表明两组均值之间的总GWG差异(3.30对8.74 kg)。GEE模型表明,年龄35岁、孕前有运动习惯、饮食自我效能感高且体力活动更多的肥胖女性往往GWG较低(p < 0.05)。
由护士主导的基于mHealth的干预措施在显著预防高BMI女性过度GWG方面显示出有前景的结果。在肥胖亚组中发现了更高的有效性。
基于mHealth的干预措施将由护士成功实施,以帮助高BMI女性维持最佳体重,并促进健康行为改变,特别是在孕期的饮食和体力活动方面。