David Drozek, Alexandria DeFabio, Randi Amstadt, Godwin Y Dogbey
{"title":"体重指数变化作为生活方式强化改变计划后生物特征变化的预测因子。","authors":"David Drozek, Alexandria DeFabio, Randi Amstadt, Godwin Y Dogbey","doi":"10.1155/2019/8580632","DOIUrl":null,"url":null,"abstract":"<p><p>The initial benefits of lifestyle modification programs such as reduction in chronic and cardiovascular diseases (CVD) risk factors have been well documented. However, such positive effects may deteriorate over time following relapse into inactivity. Timely detection of weight regain leading to the deterioration of the accrued benefits could trigger early resumption of intensive lifestyle intervention. To date, no known cost-effective, noninvasive approach for monitoring long-term outcomes has yet been established. The purpose of this study was to determine if body mass index (BMI) change predicted changes in other CVD biometric markers during an intensive lifestyle modification program. This study was an observational, retrospective review of records of participants from the Complete Health Improvement Program (CHIP). Biomarker changes of participants in this community-based Intensive Therapeutic Lifestyle Modification Program (ITLMP) offered in Athens, Ohio, a rural Appalachian college town, between April 2011 and June 2017 were reviewed retrospectively. BMI, heart rate (Pulse), systolic blood pressure (SBP), diastolic blood pressure (DBP), and fasting blood levels of total cholesterol (TC), low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides (TG), and glucose (FBS) were monitored before and after program completion. Data were analyzed using a multivariate general linear model. The sample analyzed consisted of 620 participants (mean age of 52.3±13.0 years, 74.5% female). Controlling for age and gender, BMI change significantly predicted 5 out of the 8 biomarker changes measured [Wilk's <i>λ</i> = 0.939, <i>F</i>(8,526) = 4.29, <i>p</i> <.0001]. Specifically, a 1-point BMI decrease was associated with 4.4 units decrease in TC, 3.2 units in LDL, 5.3 units in TG, 2 units in SBP, and 1 unit in DBP (all <i>p</i> values < .05). These results suggest that change in BMI may be a useful predictor of change in other CVD biomarkers' outcomes during and after an ITLMP participation. Tracking BMI, therefore, could serve as a proxy measure for identifying regressing biomarker changes following participation in an ITLMP leading to a timelier reassessment and intervention. Future studies evaluating the value of BMI as a surrogate for highlighting overall cardiovascular health are warranted.</p>","PeriodicalId":7388,"journal":{"name":"Advances in Preventive Medicine","volume":"2019 ","pages":"8580632"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2019/8580632","citationCount":"6","resultStr":"{\"title\":\"Body Mass Index Change as a Predictor of Biometric Changes following an Intensive Lifestyle Modification Program.\",\"authors\":\"David Drozek, Alexandria DeFabio, Randi Amstadt, Godwin Y Dogbey\",\"doi\":\"10.1155/2019/8580632\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The initial benefits of lifestyle modification programs such as reduction in chronic and cardiovascular diseases (CVD) risk factors have been well documented. However, such positive effects may deteriorate over time following relapse into inactivity. Timely detection of weight regain leading to the deterioration of the accrued benefits could trigger early resumption of intensive lifestyle intervention. To date, no known cost-effective, noninvasive approach for monitoring long-term outcomes has yet been established. The purpose of this study was to determine if body mass index (BMI) change predicted changes in other CVD biometric markers during an intensive lifestyle modification program. This study was an observational, retrospective review of records of participants from the Complete Health Improvement Program (CHIP). Biomarker changes of participants in this community-based Intensive Therapeutic Lifestyle Modification Program (ITLMP) offered in Athens, Ohio, a rural Appalachian college town, between April 2011 and June 2017 were reviewed retrospectively. BMI, heart rate (Pulse), systolic blood pressure (SBP), diastolic blood pressure (DBP), and fasting blood levels of total cholesterol (TC), low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides (TG), and glucose (FBS) were monitored before and after program completion. Data were analyzed using a multivariate general linear model. The sample analyzed consisted of 620 participants (mean age of 52.3±13.0 years, 74.5% female). Controlling for age and gender, BMI change significantly predicted 5 out of the 8 biomarker changes measured [Wilk's <i>λ</i> = 0.939, <i>F</i>(8,526) = 4.29, <i>p</i> <.0001]. Specifically, a 1-point BMI decrease was associated with 4.4 units decrease in TC, 3.2 units in LDL, 5.3 units in TG, 2 units in SBP, and 1 unit in DBP (all <i>p</i> values < .05). These results suggest that change in BMI may be a useful predictor of change in other CVD biomarkers' outcomes during and after an ITLMP participation. Tracking BMI, therefore, could serve as a proxy measure for identifying regressing biomarker changes following participation in an ITLMP leading to a timelier reassessment and intervention. 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引用次数: 6
摘要
生活方式改变计划的最初好处,如减少慢性和心血管疾病(CVD)的风险因素,已经得到了充分的证明。然而,随着时间的推移,这种积极的影响可能会随着不运动的复发而恶化。及时发现体重反弹导致累积收益恶化,可以触发早期恢复密集的生活方式干预。迄今为止,还没有一种已知的具有成本效益的、无创的方法来监测长期结果。本研究的目的是确定在密集的生活方式改变计划中,体重指数(BMI)的变化是否能预测其他心血管疾病生物标志物的变化。本研究是对完全健康改善计划(CHIP)参与者记录的观察性、回顾性回顾。在2011年4月至2017年6月期间,回顾性回顾了在阿巴拉契亚乡村大学城俄亥俄州雅典提供的以社区为基础的强化治疗性生活方式改变计划(ITLMP)参与者的生物标志物变化。在项目完成前后监测BMI、心率(Pulse)、收缩压(SBP)、舒张压(DBP)、空腹总胆固醇(TC)、低密度脂蛋白(LDL)、高密度脂蛋白(HDL)、甘油三酯(TG)和葡萄糖(FBS)水平。数据分析采用多元一般线性模型。样本分析包括620名参与者(平均年龄52.3±13.0岁,74.5%为女性)。在控制年龄和性别的情况下,BMI变化显著预测了8项生物标志物变化中的5项[Wilk's λ = 0.939, F(8,526) = 4.29, p < 0.05]。这些结果表明,BMI的变化可能是ITLMP期间和之后其他CVD生物标志物结果变化的有用预测因子。因此,跟踪BMI可以作为一种替代措施,用于识别参与ITLMP后的退化生物标志物变化,从而更及时地重新评估和干预。未来的研究评估BMI作为强调整体心血管健康的替代品的价值是有必要的。
Body Mass Index Change as a Predictor of Biometric Changes following an Intensive Lifestyle Modification Program.
The initial benefits of lifestyle modification programs such as reduction in chronic and cardiovascular diseases (CVD) risk factors have been well documented. However, such positive effects may deteriorate over time following relapse into inactivity. Timely detection of weight regain leading to the deterioration of the accrued benefits could trigger early resumption of intensive lifestyle intervention. To date, no known cost-effective, noninvasive approach for monitoring long-term outcomes has yet been established. The purpose of this study was to determine if body mass index (BMI) change predicted changes in other CVD biometric markers during an intensive lifestyle modification program. This study was an observational, retrospective review of records of participants from the Complete Health Improvement Program (CHIP). Biomarker changes of participants in this community-based Intensive Therapeutic Lifestyle Modification Program (ITLMP) offered in Athens, Ohio, a rural Appalachian college town, between April 2011 and June 2017 were reviewed retrospectively. BMI, heart rate (Pulse), systolic blood pressure (SBP), diastolic blood pressure (DBP), and fasting blood levels of total cholesterol (TC), low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides (TG), and glucose (FBS) were monitored before and after program completion. Data were analyzed using a multivariate general linear model. The sample analyzed consisted of 620 participants (mean age of 52.3±13.0 years, 74.5% female). Controlling for age and gender, BMI change significantly predicted 5 out of the 8 biomarker changes measured [Wilk's λ = 0.939, F(8,526) = 4.29, p <.0001]. Specifically, a 1-point BMI decrease was associated with 4.4 units decrease in TC, 3.2 units in LDL, 5.3 units in TG, 2 units in SBP, and 1 unit in DBP (all p values < .05). These results suggest that change in BMI may be a useful predictor of change in other CVD biomarkers' outcomes during and after an ITLMP participation. Tracking BMI, therefore, could serve as a proxy measure for identifying regressing biomarker changes following participation in an ITLMP leading to a timelier reassessment and intervention. Future studies evaluating the value of BMI as a surrogate for highlighting overall cardiovascular health are warranted.