对代谢综合征强化生活方式改变计划的变量反应进行探索性分析。

IF 2 Q2 MEDICINE, GENERAL & INTERNAL BMC primary care Pub Date : 2024-10-01 DOI:10.1186/s12875-024-02608-w
Scott B Maitland, Paula Brauer, David M Mutch, Dawna Royall, Doug Klein, Angelo Tremblay, Caroline Rheaume, Khursheed Jeejeebhoy
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引用次数: 0

摘要

背景:多年来,人们已经认识到对生活方式干预的反应存在很大差异,研究人员也开始从个体反应的固有差异中找出误差来源。这项针对代谢综合征(MetS)的强化生活方式干预(饮食和运动)的二次分析旨在确定根据连续代谢综合征评分(Gurka/MetS)的变化来衡量的治疗反应分组的研究完成者之间可能存在的重要差异:方法: 根据 Gurka/MetS 评分的变化,将一项为期 12 个月的初级保健研究中的所有研究完成者分为五组。与之前的研究结果一致,z-score 0.4 的变化定义为临床相关变化。研究人员采用重复测量方差分析法对12个月内心血管疾病风险和MetS的各项临床指标进行了研究,以寻找五个组别在不同时期的反应差异:在 176 名参与者中,50%(n = 88)的得分保持稳定,10%(n = 18)的得分仅在前 3 个月有相关变化,随后恢复到基线水平,20%(n = 35)在整个研究过程中实现了有意义的变化,11%(n = 20)在 3-12 个月内出现延迟反应,9%(n = 15)的得分出现恶化。在干预过程中,各组之间存在显著的差异(P 结论:在干预过程中,各组之间存在显著的差异(P 结论:在干预过程中,各组之间存在显著的差异(P 结论):需要努力确定导致生活方式干预反应差异的关键因素,这些因素可用于指导针对这一常见疾病的强化生活方式干预的治疗决策:试验注册:ClinicalTrials.gov Identifier:试验注册:ClinicalTrials.gov Identifier:NCT01616563;首次注册日期:2012年6月12日。
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Exploratory analysis of the variable response to an intensive lifestyle change program for metabolic syndrome.

Background: Substantial variability in response to lifestyle interventions has been recognized for many years, and researchers have begun to disentangle sources of error from inherent differences in individual responsiveness. The objective of this secondary analysis of an intensive lifestyle intervention (diet and exercise) for metabolic syndrome (MetS) was to identify potentially important differences among study completers grouped by treatment response as measured by change in a continuous metabolic syndrome score (Gurka/MetS).

Methods: All study completers from a 12-month primary care study were categorized into one of five groups according to change in the Gurka/MetS score. A change of 0.4 in z-score defined clinically relevant change in line with results of previous studies. Repeated measures analysis of variance was used to examine cardiovascular disease risk and individual clinical indicators of MetS over 12 months, looking for differences in response over time by the five groups.

Results: Of 176 participants, 50% (n = 88) had stable scores, 10% (n = 18) had relevant change scores in the first 3 months only and reverted toward baseline, 20% (n = 35) achieved meaningful change over the whole study, 11% (n = 20) had a delayed response at 3-12 months, and 9% (n = 15) demonstrated worsening scores. Significant differential patterns were noted for groups over the duration of the intervention (p < .001). Improvement in diet quality and fitness scores were similar across all groups. Other available variables were tested and did not account for the differences.

Conclusion: Work is needed to identify key factors that account for differences in responses to lifestyle interventions that can be used to guide treatment decisions for intensive lifestyle interventions for this common condition.

Trial registration: ClinicalTrials.gov Identifier: NCT01616563; first registered June 12, 2012.

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