Jobarteh Modou L, McCrory Megan A, Lo Benny, Sun Mingui, Sazonov Edward, Anderson Alex K, Jia Wenyan, Maitland Kathryn, Qiu Jianing, Steiner-Asiedu Matilda, Higgins Janine A, Baranowski Tom, Olupot-Olupot Peter, Frost Gary
Section for Nutrition Research, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK.
Department of Health Sciences, Boston University, Boston, MA, USA.
Curr Dev Nutr. 2020 Feb 7;4(2):nzaa020. doi: 10.1093/cdn/nzaa020. eCollection 2020 Feb.
Malnutrition is a major concern in low- and middle-income countries (LMIC), but the full extent of nutritional deficiencies remains unknown largely due to lack of accurate assessment methods. This study seeks to develop and validate an objective, passive method of estimating food and nutrient intake in households in Ghana and Uganda. Household members (including under-5s and adolescents) are assigned a wearable camera device to capture images of their food intake during waking hours. Using custom software, images captured are then used to estimate an individual's food and nutrient (i.e., protein, fat, carbohydrate, energy, and micronutrients) intake. Passive food image capture and assessment provides an objective measure of food and nutrient intake in real time, minimizing some of the limitations associated with self-reported dietary intake methods. Its use in LMIC could potentially increase the understanding of a population's nutritional status, and the contribution of household food intake to the malnutrition burden. This project is registered at clinicaltrials.gov (NCT03723460).
营养不良是低收入和中等收入国家(LMIC)的一个主要问题,但由于缺乏准确的评估方法,营养缺乏的全部程度在很大程度上仍不为人知。本研究旨在开发并验证一种客观、被动的方法,用于估算加纳和乌干达家庭的食物和营养摄入量。为家庭成员(包括5岁以下儿童和青少年)配备可穿戴式摄像设备,以捕捉他们在清醒时间的食物摄入图像。然后使用定制软件,将所拍摄的图像用于估算个人的食物和营养(即蛋白质、脂肪、碳水化合物、能量和微量营养素)摄入量。被动式食物图像捕捉和评估可实时提供食物和营养摄入量的客观测量结果,最大限度地减少了与自我报告饮食摄入方法相关的一些局限性。在低收入和中等收入国家使用该方法可能会增进对人群营养状况的了解,以及家庭食物摄入对营养不良负担的影响。该项目已在clinicaltrials.gov(NCT03723460)注册。