Public Health Procedures,Alone,Will Not Prevent Child Obesity

Beets MW , Brazendale K , Weaver RG , et al. Rethinking behavioral approaches to compliment biological advances to understand the etiology, prevention, and treatment of childhood obesity. Child Obes, 2019; 15:353–358.

Baranowski T , Motil KJ , Moreno JP . Behavioral research agenda in a multietiological approach to child obesity prevention. Child Obes, 2019; 15:223–226.

Baranowski T , Motil KJ , Moreno JP . Multi-etiological perspective on child obesity prevention. Curr Nutr Rep, 2019; 8:1–10.

Moreno JP , Crowley SJ , Alfano CA , et al. Potential circadian and circannual rhythm contributions to the obesity epidemic in elementary school age children. Int J Behav Nutr Phys Act, 2019; 16:25.

Baranowski T , Lytle L . Should the IDEFICS outcomes have been expected?. Obes Rev, 2015; 16 Suppl 2:162–172.

Ludwig DS , Ebbeling CB . The carbohydrate-insulin model of obesity: Beyond “Calories In, Calories Out”. JAMA Intern Med, 2018; 178:1098–1103.

Hall KD , Guyenet SJ , Leibel RL . The carbohydrate-insulin model of obesity is difficult to reconcile with current evidence. JAMA Intern Med, 2018; 178:1103–1105.

Archer E , Lavie CJ , Hill JO . The contributions of ‘diet’, ‘genes’, and physical activity to the etiology of obesity: Contrary evidence and consilience. Prog Cardiovasc Dis, 2018; 61:89–102.

Beets MW , Brazendale K , Weaver RG . The need for synergy between biological and behavioral approaches to address accelerated weight gain during the summer in children. Int J Behav Nutr Phys Act, 2019; 16:39.

Foster GD , Linder B , Baranowski T , et al. A school-based intervention for diabetes risk reduction. N Engl J Med, 2010; 363:443–453.

De Henauw S , Huybrechts I , De Bourdeaudhuij I , et al. Effects of a community-oriented obesity prevention programme on indicators of body fatness in preschool and primary school children. Main results from the IDEFICS study. Obes Rev, 2015; 16 Suppl 2:16–29.

Langeheine M , Pohlabeln H , Lauria F , et al. Attrition in the European child cohort IDEFICS/I.Family: Exploring associations between attrition and body mass index. Front Pediatr, 2018; 6:212.

Chen TA , Baranowski T , Moreno JP , et al. Obesity status trajectory groups among elementary school children. BMC Public Health, 2016; 16:526.

Roberts S , Pilard L , Chen J , et al. Efficacy of population-wide diabetes and obesity prevention programs: An overview of systematic reviews on proximal, intermediate, and distal outcomes and a meta-analysis of impact on BMI. Obes Rev, 2019 [Epub ahead of print]. DOI: 10.1111/obr.12821

Sacks G , Robinson E , Cameron AJ . Issues in measuring the healthiness of food environments and interpreting relationships with diet, obesity and related health outcomes. Curr Obes Rep, 2019; 8:98–111.

Lee BY , Bartsch SM , Mui Y , et al. A systems approach to obesity. Nutr Rev, 2017; 75:94–106.

Khalil HK . Nonlinear Systems. 3rd ed. Englewood Cliffs, NJ: Prentice-Hall, 2002.

Beltran A , Dadabhoy H , Chen TA , et al. Adapting the eButton to the abilities of children for diet assessment. In: Spink A , Riedel G , Zhou L , Teekens L , Albatal R , Gurrin C (eds), Measuring Behavior 2016—10th International Conference on Methods and Techniques in Behavioral Research. Dublin, Ireland, 2016, pp. 72–81.

Beltran A , Dadabhoy H , Ryan C , et al. Dietary assessment with a wearable camera among children: Feasibility and intercoder reliability. J Acad Nutr Diet, 2018; 118:2144–2153.

Raber M , Patterson M , Jia W , et al. Utility of eButton images for identifying food preparation behaviors and meal-related tasks in adolescents. Nutr J, 2018; 17:32.

Jia W , Li Y , Qu R , et al. Automatic food detection in egocentric images using artificial intelligence technology. Public Health Nutr, 2019; 22:1168–1179.

Farooq M , Doulah A , Parton J , et al. Validation of sensor-based food intake detection by multicamera video observation in an unconstrained environment. Nutrients, 2019; 11:609.

He Y , Xu C , Khanna N , et al. Food image analysis: Segmentation, identification and weight estimation. Proc IEEE Int Conf Multimed Expo, 2013; 2013:1–10.

Beltran A , Dadabhoy H , Ryan C , et al. Reliability and validity of food portion size estimation from images using manual flexible digital virtual meshes. Public Health Nutr, 2019; 22:1153–1159.

Fontana JM , Higgins JA , Schuckers SC , et al. Energy intake estimation from counts of chews and swallows. Appetite, 2015; 85:14–21.

Spruijt-Metz D , Wen CKF , Bell BM , et al. Advances and controversies in diet and physical activity measurement in youth. Am J Prev Med, 2018; 55:e81–e91.

Baranowski T , Masse LC , Ragan B , et al. How many days was that? We're still not sure, but we're asking the question better!. Med Sci Sports Exerc, 2008; 40:S544–S549.

Baranowski T , de Moor C . How many days was that? Intra-individual variability and physical activity assessment. Res Q Exerc Sport, 2000; 71:S74–S78.

Narciso J , Silva AJ , Rodrigues V , et al. Behavioral, contextual and biological factors associated with obesity during adolescence: A systematic review. PLoS One, 2019; 14:e0214941.

Hartmann-Boyce J , Johns DJ , Jebb SA , et al. Effect of behavioural techniques and delivery mode on effectiveness of weight management: Systematic review, meta-analysis and meta-regression. Obes Rev, 2014; 15:598–609.

Bull ER , McCleary N , Li X , et al. Interventions to promote healthy eating, physical activity and smoking in low-income groups: A systematic review with meta-analysis of behavior change techniques and delivery/context. Int J Behav Med, 2018; 25:605–616.

Geller K , Lippke S , Nigg CR . Future directions of multiple behavior change research. J Behav Med, 2017; 40:194–202.

Radtke T , Scholz U , Keller R , et al. Smoking is ok as long as I eat healthily: Compensatory health beliefs and their role for intentions and smoking within the Health Action Process Approach. Psychol Health, 2012; 27 Suppl 2:91–107.