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  1. 8721
    “…Main food sources of intrinsic sugars for both subsamples were milk and dairy products, fruits, vegetables and cereals, while for added sugars, these were milk and dairy products (mainly yogurts), sugars and sweets (mainly sugary cocoa and nougat), bakery products (mainly cookies) and cereals (mainly bread and wheat flour). …”
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    Dietary Intake of Individual (Intrinsic and Added) Sugars and Food Sources from Spanish Children Aged One to <10 Years—Results from the EsNuPI Study †
  2. 8722
    “…The main sources of energy intake (EI) among children were the sweets, sweetened beverages and desserts followed by grains and mixed dishes. …”
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    Food and nutrient intake of school-aged children in Lebanon and their adherence to dietary guidelines and recommendations
  3. 8723
    “…Conclusions: The frequency of family meals is positively associated with improved food consumption patterns (i.e., higher intake of fruits and vegetables and reduced consumption of sweets) in both parents and children. However, the association in children is partially mediated by parents’ diet quality. …”
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    Frequency of family meals and food consumption in families at high risk of type 2 diabetes: the Feel4Diabetes-study
  4. 8724
    “…Other major contributors to total flavonoid intake for all children were 100% fruit juices (11.6%), berries (7.0%), apples (6.2%), oranges (5.8%) and snacks and sweets (4.5%). CONCLUSIONS: Assessing flavonoid intake and its dietary sources in children provides important context when investigating associations between these dietary compounds and diseases which develop over the life cycle. …”
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    Characterizing Flavonoid Intake of Children in the U.S.: Results From What We Eat in America, NHANES 2017–2018
  5. 8725
    “…Adherence to the DASH diet was defined as intake within the ranges of 10 food groups: whole grains, vegetables, fruits, low-fat dairy, red meat, poultry, fish, nuts and legumes, fats and oils, and sweets and added sugar. Incidence of heart failure was ascertained using the Swedish National Patient Register up to 31 December 2019. …”
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    Hypothetical 22-Year Diet Intervention: Adherence to the Dietary Approach to Stop Hypertension (DASH) Diet and Risk of Heart Failure in Swedish Men and Women
  6. 8726
    “…Foods were grouped (vegetables, fruits, grains, meat and meat alternatives, snacks, sweets, and dairy) and summed into a 7-point dietary diversity score (DDS). …”
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    Dietary Diversity Among U.S. Infants and Toddlers: Associations With Caregiver Sociodemographic Characteristics
  7. 8727
    “…In addition, food items were coded into eight groups (i.e., Beverages; Beans, Nuts, & Seeds [BNS]; Dairy; Fats & Sweets; Fruits & Fruit Juices; Grains; Meat Poultry & Fish; and Vegetables). …”
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    Ultra-Processed Foods Have a Lower Glycemic Index and Load Compared to Minimally Processed Foods
  8. 8728
    “…LEfSe analysis identified phylogenetically enriched taxa associated with the intake of sugars and sweets, legumes, mushrooms, eggs, oils and fats, plant fat, carbohydrates, and monounsaturated fatty acids. …”
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    Nutrition-wide association study of microbiome diversity and composition in colorectal cancer patients
  9. 8729
    “…The largest food categories contributing to total energy purchased included mass-produced, packaged breads (8.2% of total energy purchased), chocolate and sweets (5.7%), biscuits and crackers (5.7%) and ice-cream and edible ices (4.3%). …”
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    Socio-economic difference in purchases of ultra-processed foods in Australia: an analysis of a nationally representative household grocery purchasing panel
  10. 8730
    “…Most participants ate about the same amounts of dairy, meats and canned foods/dried goods as pre-pandemic (61.5, 61.7, and 60.2%, respectively), increased their intake of fresh vegetables/fruits and sweets/snacks (43.2 and 54.5%, respectively), and decreased fast-food and take-out/home delivery (53.2 and 43.1%, respectively). …”
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    Dietary changes among pregnant individuals compared to pre-pandemic: A cross-sectional analysis of the Pregnancy during the COVID-19 Pandemic (PdP) study
  11. 8731
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    Using health administrative data to model associations and predict hospital admissions and length of stay for people with eating disorders
  12. 8732
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    Impact of a Prior Cancer Diagnosis on Quality of Care and Survival Following Acute Myocardial Infarction: Retrospective Population-Based Cohort Study in England
  13. 8733
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    Survival Extrapolation Incorporating General Population Mortality Using Excess Hazard and Cure Models: A Tutorial
  14. 8734
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    HeLP-Diabetes: randomised controlled trial protocol
  15. 8735
    por Paige, Ellie, Barrett, Jessica, Pennells, Lisa, Sweeting, Michael, Willeit, Peter, Di Angelantonio, Emanuele, Gudnason, Vilmundur, Nordestgaard, Børge G., Psaty, Bruce M, Goldbourt, Uri, Best, Lyle G, Assmann, Gerd, Salonen, Jukka T, Nietert, Paul J, Verschuren, W. M. Monique, Brunner, Eric J, Kronmal, Richard A, Salomaa, Veikko, Bakker, Stephan J L, Dagenais, Gilles R, Sato, Shinichi, Jansson, Jan-Håkan, Willeit, Johann, Onat, Altan, de la Cámara, Agustin Gómez, Roussel, Ronan, Völzke, Henry, Dankner, Rachel, Tipping, Robert W, Meade, Tom W, Donfrancesco, Chiara, Kuller, Lewis H, Peters, Annette, Gallacher, John, Kromhout, Daan, Iso, Hiroyasu, Knuiman, Matthew, Casiglia, Edoardo, Kavousi, Maryam, Palmieri, Luigi, Sundström, Johan, Davis, Barry R, Njølstad, Inger, Couper, David, Danesh, John, Thompson, Simon G, Wood, Angela
    Publicado 2017
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    Use of Repeated Blood Pressure and Cholesterol Measurements to Improve Cardiovascular Disease Risk Prediction: An Individual-Participant-Data Meta-Analysis
  16. 8736
    “…The different age groups indicated the following as the reasons for excessive body mass: young respondents—low physical activity and consumption of sweets; middle-aged ones—large/irregular meals; aging ones—large/irregular meals and low physical activity (p = 0.0161). …”
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    Analysis of the Influence of Age, BMI, and WHtR on Body Mass Acceptance, Attitudes, and Motivation towards Body Mass Reduction in Overweight and Obese Caucasian Women
  17. 8737
    “…Lifestyle variables measured were vigorous physical activity (VPA, days/week, min/week), moderate physical activity (MPA, days/week, min/week), walking (days/week, min/week), sitting (min/week), meals/day, vegetables/day, fruits/day, seafood/week, dairy products/week, sweets, chips, fast food/week, litres of liquid/day, litres of sugary drinks/day, alcohol/week and cigarettes/day. …”
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    Body Composition, Physical Fitness, Physical Activity and Nutrition in Polish and Spanish Male Students of Sports Sciences: Differences and Correlations
  18. 8738
    “…Regarding the frequency of consumption of food items and meals, kappa statistics were 0.46–0.81 (the lowest: fruit/mixed fruit and vegetable juices; the highest: Energy drinks) in test–retest for children, 0.30–0.54 (fruit/mixed fruit and vegetable juices; breakfast, respectively) in adolescent’s test–retest, 0.27–0.56 (the lowest: Sweets, fruit, dairy products; the highest: Breakfast) in adolescent’s test and parent’s test. …”
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    Reproducibility of a Short-Form, Multicomponent Dietary Questionnaire to Assess Food Frequency Consumption, Nutrition Knowledge, and Lifestyle (SF-FFQ4PolishChildren) in Polish Children and Adolescents
  19. 8739
    “…To assess food habits, the consumption frequency of some food groups including sweets, salty snacks, carbonated beverages, diet soft drinks, soft beer, fresh fruits, dried fruits, fresh juices, vegetables, packed juices, dairy products (milk, yogurt, and cheese), fast foods, tea, sugar along with tea, and coffee was asked using Likert scale ( never, rarely, weekly, and daily). …”
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    Association of sleep duration and snack consumption in children and adolescents: The CASPIAN‐V study
  20. 8740
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    From Smoking-Permitted to Smokefree Prisons: A 3-Year Evaluation of the Changes in Occupational Exposure to Second-Hand Smoke Across a National Prison System
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