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Effectiveness of information technology–enabled ‘SMART Eating’ health promotion intervention: A cluster randomized controlled trial

机译:信息技术的有效性使能“智能饮食”健康促进干预:群集随机对照试验

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摘要

BACKGROUND:Unhealthy dietary behaviour-high intake of fat, sugar, and salt, and low intake of fruits and vegetables-is a major risk factor for chronic diseases. There is a lack of evidence-based interventions to promote healthy dietary intake among Indian populations. Therefore, we tested the effectiveness of an information technology-enabled 'SMART Eating' intervention to reduce the intake of fat, sugar and salt, and to increase the intake of fruits and vegetables. METHODS:In Chandigarh, a North Indian city, a cluster randomized controlled trial was implemented in twelve geographical clusters, based on the type of housing (i.e., LIG: Low-income group; MIG; Middle-income group, and HIG: High-income group-a proxy for socio-economic status). Computer-generated randomization was used to allocate clusters to intervention and comparison arms after pairing on the basis of socioeconomic status and geographical distance between clusters. The sample size was 366 families per arm (N = 732). One adult per family was randomly selected as an index case to measure the change in the outcomes. For behaviour change, a multi-channel communication approach was used, which included information technology-short message service (SMS), email, social networking app and 'SMART Eating' website, and interpersonal communication along with distribution of a 'SMART Eating' kit-kitchen calendar, dining table mat, and measuring spoons. The intervention was implemented at the family level over a period of six months. The comparison group received pamphlets on nutrition education. Outcome measurements were made at 0 and 6 months post-intervention at the individual level. Primary outcomes were changes in mean dietary intakes of fat, sugar, salt, and fruit and vegetables. Secondary outcomes included changes in body mass index (BMI), blood pressure, haemoglobin, fasting plasma glucose (FPG), and serum lipids. Mixed-effects linear regression models were used to determine the net change in the outcomes in the intervention group relative to the comparison group. RESULTS:Participants' mean age was 53 years, a majority were women (76%), most were married (90%) and 51% had completed a college degree. All families had mobile phones, and more than 90% of these families had access to Internet through mobile phones. The intervention group had significant net mean changes of -12.5 g/day (p<0.001), -11.4 g/day (p<0.001), -0.5 g/day (p<0.001), and +71.6 g/day (p<0.001) in the intake of fat, sugar, salt, and fruit and vegetables, respectively. Similarly, significant net changes occurred for secondary outcomes: BMI -0.25 kg/m2, diastolic blood pressure -2.77 mm Hg, FPG -5.7 mg/dl, and triglycerides -24.2mg/dl. The intervention had no effect on haemoglobin, systolic blood pressure, low-density lipoprotein cholesterol, or high-density lipoprotein cholesterol. CONCLUSION:The IT-enabled 'SMART Eating' intervention was found to be effective in reducing fat, sugar, and salt intake, and increasing fruit and vegetable consumption among urban adults from diverse socio-economic backgrounds. TRIAL REGISTRATION:Clinical Trial Registry of India CTRI/2016/11/007457.
机译:背景:不健康的饮食行为 - 高摄入脂肪,糖和盐,以及水果和蔬菜的低摄入量 - 是慢性疾病的主要危险因素。缺乏基于证据的干预措施,以促进印度人口中的健康饮食摄入量。因此,我们测试了能够实现信息技术的“智能饮食”干预的有效性,以减少脂肪,糖和盐的摄入,并增加水果和蔬菜的摄入量。方法:在北印度城市Chandigarh,一个基于外壳类型的12个地理集群,在十二个地理集群中实施了一个集群随机对照试验(即LIG:低收入群体; MIG;中等收入小组,和HIG:高 - 收入组 - 社会经济地位的代理)。在基于社会经济地位和集群之间的地理距离,将计算机生成的随机化用于分配与干预和比较臂进行干预和比较臂。样品大小为每只臂366个族(n = 732)。每个家庭的一个成年人被随机选择作为索引案例来衡量结果的变化。对于行为改变,使用了多通道通信方法,其中包括信息技术短信服务(SMS),电子邮件,社交网络应用程序和“智能进食”网站,以及人际关系的交流以及分布“智能饮食”套件-Kitchen日历,餐桌垫和测量勺子。干预在六个月内在家庭级别实施。比较小组接受了关于营养教育的小册子。结果测量在干预后的0和6个月内进行个人水平。主要结果是脂肪,糖,盐和水果和蔬菜的平均膳食摄入量的变化。二次结果包括体重指数(BMI),血压,血红蛋白,空腹血浆葡萄糖(FPG)和血清脂质的变化。混合效应线性回归模型用于确定相对于比较组的干预组的结果的净变化。结果:参与者的平均年龄为53岁,大多数是女性(76%),大多数已婚(90%),51%完成了大学学位。所有家庭都有手机,超过90%的家庭通过手机访问互联网。干预组具有显着的净平均变化-12.5克/天(P <0.001),-11.4克/天(P <0.001),-0.5克/天(P <0.001),+ 71.6克/天(P <0.001)分别在摄入脂肪,糖,盐和水果和蔬菜中。类似地,二次结果发生显着的净变化:BMI -0.25 kg / m2,舒张压-2.77mm Hg,Fpg -5.7mg / dl和甘油三酯-24.2mg / dl。干预对血红蛋白,收缩压,低密度脂蛋白胆固醇或高密度脂蛋白胆固醇没有影响。结论:已发现它启用的“智能饮食”干预措施有效减少脂肪,糖和盐摄入量,从各种社会经济背景中增加城市成年人的水果和蔬菜消费。审判登记:印度临床试验登记处Ctri / 2016/11 / 007457。

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