Obesity Stigma and Health Behavior: An Experimental Approach
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 330
- 试验地点
- 2
- 主要终点
- Change in sleep onset latency
研究概览
简要总结
The study will use a between-subjects design in a sample of individuals with BMI greater than or equal to 28 from the Los Angeles community (N=330). Participants will be randomly assigned to a weight stigma vs. control manipulation. Changes to the following health behaviors will be subsequently measured in their everyday lives: 3-day diet as captured by ecological momentary assessment (EMA) food diaries, objectively measured eating of obesogenic foods, objectively measured physical activity captured by 24-hour actigraphy, and sleep, captured objectively by overnight actigraphy and subjectively self-reported sleep measures. The investigators hypothesize that weight stigma causes decrements in health behaviors (e.g., sleep, eating, and physical activity) in everyday life.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Basic Science
- 盲法
- Single (Participant)
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •English-speaking
- •BMI greater than or equal to 28
排除标准
- •Major mental disorder including eating disorder, mood disorder, schizophrenia, PTSD
- •Recent (<1 year) diagnosis of major physical conditions that limit physical movement
- •Recent (<1 year) diagnosis of sleep disorder
- •Allergy to any of the foods in the food buffet
结局指标
主要结局
Change in sleep onset latency
时间窗: Change in sleep onset latency will be assessed by measuring sleep onset latency for three days before the intervention as part of the baseline, and three days after the intervention.
Change in sleep onset latency will be assessed using an Actiwatch-2 (Philips Respironics). Data will be captured in 30-second epochs and validated. Actiware 6.0.9 software algorithms will be used to estimate sleep parameters with the following sleep/wake algorithm: D = A-2\*(1/25) + A1\*(1/5) + A\*(1) + A + 1\*(1/5) + A + 2\*(1/25), where AX = accelerometer activity for that minute. Sleep onset is operationalized as after 10 consecutive minutes of D ≤ 40 (as D \> 40 indicates participants are awake).
Change in physical activity
时间窗: Change in physical activity will be assessed by measuring physical activity for 72 hours before the intervention as part of the baseline, and 72 hours after the intervention.
Physical activity, quantified as Metabolic Equivalent of Task (MET) units, will be assessed using ActivPAL4 actigraphs.
Hyperpalatable food intake
时间窗: Hyperpalatable food intake will be measured directly after the intervention.
Hyperpalatable food intake will initially be measured in grams and then converted into kilocalories. The food will consist of the following items: chocolate chip cookies, M\&Ms, potato chips, and Sprite. These foods were chosen because processed foods, added sugars, refined grains, starchy vegetables, and sugar sweetened beverages are foods to avoid according to the 2019 American Diabetes Association Nutrition Consensus Report and are high in carbohydrates and glycemic index.
Change in self-reported dietary intake
时间窗: Change in self-reported dietary intake will be assessed by measuring self-reported dietary intake 72 hours before the intervention as part of the baseline, and 72 hours after the intervention.
Dietary intake data for food recalls will be collected and analyzed using the Automated Self-Administered 24-hour (ASA24) Dietary Assessment Tool developed by the National Cancer Institute, Bethesda, MD. The primary eating outcome for the food diaries will be kilocalories.
Change in sleep duration
时间窗: Change in sleep duration will be assessed by measuring sleep duration for three days before the intervention as part of the baseline, and three days after the intervention.
Change in sleep duration will be assessed using an Actiwatch-2 (Philips Respironics). Data will be captured in 30-second epochs and validated. Actiware 6.0.9 software algorithms will be used to estimate sleep parameters with the following sleep/wake algorithm: D = A-2\*(1/25) + A1\*(1/5) + A\*(1) + A + 1\*(1/5) + A + 2\*(1/25), where AX = accelerometer activity for that minute.
Change in sleep efficiency
时间窗: Change in sleep efficiency will be assessed by measuring sleep efficiency for three days before the intervention as part of the baseline, and three days after the intervention.
Change in sleep efficiency will be assessed using an Actiwatch-2 (Philips Respironics). Data will be captured in 30-second epochs and validated. Actiware 6.0.9 software algorithms will be used to estimate sleep parameters with the following sleep/wake algorithm: D = A-2\*(1/25) + A1\*(1/5) + A\*(1) + A + 1\*(1/5) + A + 2\*(1/25), where AX = accelerometer activity for that minute.
Change in self-reported sleep quality
时间窗: Change in self-reported sleep quality will be assessed by measuring self-reported sleep quality during the mornings of the first 72 hour baseline period before the intervention, and in the mornings of the 72 hour period after the intervention.
Participants will complete a questionnaire assessing self-reported measures of the past night's sleep quality, bedtime, number of minutes it took to fall asleep, number of minutes awake during the night, and the present morning's wake time using the consensus sleep diary (Carney et al., 2012). Data from the sleep diary will not be scored numerically, but instead will be used to supplement scoring of the behavioral actigraphy data. Sleep and wake times will be used to set rest intervals, which are needed to capture accurate sleep intervals. Subjective sleep quality will be used as a fourth dependent sleep variable.
次要结局
未报告次要终点
研究者
A. Janet Tomiyama
Associate Professor
University of California, Los Angeles