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1. Computational Framework for Sequential Diet Recommendation: Integrating Linear Optimization and Clinical Domain Knowledge

   Arefeen, Asiful; Jaribi, Niloo; Mortazavi, Bobak J.; Ghasemzadeh, Hassan (January 2022, 2022 IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE))

   With rapid growth in unhealthy diet behaviors, implementing strategies that improve healthy eating is becoming increasingly important. One approach to improving diet behavior is to continuously monitor dietary intake (e.g., calorie intake) and provide educational, motivational, and dietary recommendation feedback. Although technologies based on wearable sensors, mobile applications, and light-weight cameras exist to gather diet-related information such as food type and eating time, there remains a gap in research on how to use such information to close the loop and provide feedback to the user to improve healthy diet. We address this knowledge gap by introducing a diet behavior change framework that generates real-time diet recommendations based on a user’s food intake and considering user’s deviation from the suggested diet routine. We formulate the problem of optimal diet recommendation as a sequential decision making problem and design a greedy algorithm that provides diet recommendations such that the amount of change in user’s dietary habits is minimized while ensuring that the user’s diet goal is achieved within a given time-frame. This novel approach is inspired by the Social Cognitive Theory, which emphasizes behavioral monitoring and small incremental goals as being important to behavior change. Our optimization algorithm integrates data from a user’s past dietary intake as well as the USDA nutrition dataset to identify optimal diet changes. We demonstrate the feasibility of our optimization algorithms for diet behavior change using real-data collected in two study cohorts with a combined N=10 healthy participants who recorded their diet for up to 21 days. 

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2. Crotalus viridis. Diet.

   Roden, E.; Carlin, B.; Service, J.; Nowak, E. M.; Pasch, B. (January 2020, Herpetological review)
3. Crotalus viridis. Diet.

   Roden, E.; Carlin, B.; Service, J.; Nowak, E. M.; Pasch, B. (April 2020, Herpetological review)
4. Large-scale diet tracking data reveal disparate associations between food environment and diet

   https://doi.org/10.1038/s41467-021-27522-y  

   Althoff, Tim; Nilforoshan, Hamed; Hua, Jenna; Leskovec, Jure (December 2022, Nature Communications)

   Abstract An unhealthy diet is a major risk factor for chronic diseases including cardiovascular disease, type 2 diabetes, and cancer 1–4 . Limited access to healthy food options may contribute to unhealthy diets 5,6 . Studying diets is challenging, typically restricted to small sample sizes, single locations, and non-uniform design across studies, and has led to mixed results on the impact of the food environment 7–23 . Here we leverage smartphones to track diet health, operationalized through the self-reported consumption of fresh fruits and vegetables, fast food and soda, as well as body-mass index status in a country-wide observational study of 1,164,926 U.S. participants (MyFitnessPal app users) and 2.3 billion food entries to study the independent contributions of fast food and grocery store access, income and education to diet health outcomes. This study constitutes the largest nationwide study examining the relationship between the food environment and diet to date. We find that higher access to grocery stores, lower access to fast food, higher income and college education are independently associated with higher consumption of fresh fruits and vegetables, lower consumption of fast food and soda, and lower likelihood of being affected by overweight and obesity. However, these associations vary significantly across zip codes with predominantly Black, Hispanic or white populations. For instance, high grocery store access has a significantly larger association with higher fruit and vegetable consumption in zip codes with predominantly Hispanic populations (7.4% difference) and Black populations (10.2% difference) in contrast to zip codes with predominantly white populations (1.7% difference). Policy targeted at improving food access, income and education may increase healthy eating, but intervention allocation may need to be optimized for specific subpopulations and locations. 

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5. High fat diet increases diet-induced thermogenesis in cold exposure and at thermoneutrality

   Spencer, T; Robbins, A; Tom, C; Cosman, M; Moursi, C; Devlin, MJ (January 2018, American journal of physical anthropology)

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