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1.
Nutrients ; 13(8)2021 Aug 15.
Article in English | MEDLINE | ID: mdl-34444959

ABSTRACT

The rapid rise in prevalence of overweight/obesity, as well as high prevalence of type 2 diabetes and other nutrition-related noncommunicable diseases, has led the Food Safety and Standards Authority of India (FSSAI) to propose a front-of-package labeling (FOPL) regulation. An effective FOPL system applies a nutrient profile model that identifies foods high in sugar, sodium, and saturated fat that would receive a warning label for consumers to effectively discern between more and less healthy foods. Previous Nutrition Alchemy data collected by the food industry (n = 1306 products) estimated that approximately 96% of foods in India would have at least one warning label based on the FSSAI proposed FOPL. This near universal coverage of warning labels may be inaccurate and misleading. To address this, the current study compared two nutrient profile models, the WHO South-East Asia Region Organization (SEARO) and the Chilean Warning Octagon (CWO) Phase 3, applied to food products available in the Indian market from 2015-2020, collected through Mintel Global New Products Database (n = 10,501 products). Results suggest that 68% of foods and beverages would have at least one ' high-in' level warning label. This study highlights the need to include a more comprehensive sample of food products for assessing the value of warning labels.


Subject(s)
Food Analysis/statistics & numerical data , Food Industry/legislation & jurisprudence , Food Labeling/legislation & jurisprudence , Food/statistics & numerical data , Nutrition Policy/legislation & jurisprudence , Chile , Consumer Behavior , Databases, Factual , Asia, Eastern , Humans , India , Nutritive Value , World Health Organization
2.
Am J Prev Med ; 54(3): 403-412, 2018 03.
Article in English | MEDLINE | ID: mdl-29455757

ABSTRACT

INTRODUCTION: The Special Supplemental Nutrition Program for Women, Infants and Children (WIC) required major revisions to food packages in 2009; effects on nationwide low-income household purchases remain unexamined. METHODS: This study examines associations between WIC revisions and nutritional profiles of packaged food purchases from 2008 to 2014 among 4,537 low-income households with preschoolers in the U.S. (WIC participating versus nonparticipating) utilizing Nielsen Homescan Consumer Panel data. Overall nutrients purchased (e.g., calories, sugar, fat), amounts of select food groups with nutritional attributes that are encouraged (e.g., whole grains, fruits and vegetables) or discouraged (e.g., sugar-sweetened beverages, candy) consistent with dietary guidance, composition of purchases by degree of processing (less, moderate, or high), and convenience (requires preparation, ready to heat, or ready to eat) were measured. Data analysis was performed in 2016. Longitudinal random-effects model adjusted outcomes controlling for household composition, education, race/ethnicity of the head of the household, county quarterly unemployment rates, and seasonality are presented. RESULTS: Among WIC households, significant decreases in purchases of calories (-11%), sodium (-12%), total fat (-10%), and sugar (-15%) occurred, alongside decreases in purchases of refined grains, grain-based desserts, higher-fat milks, and sugar-sweetened beverages, and increases in purchases of fruits/vegetables with no added sugar/fats/salt. Income-eligible nonparticipating households had similar, but less pronounced, reductions. Changes were gradual and increased over time. CONCLUSIONS: WIC food package revisions appear associated with improved nutritional profiles of food purchases among WIC participating households compared with low-income nonparticipating households. These package revisions may encourage WIC families to make healthier choices among their overall packaged food purchases.


Subject(s)
Consumer Behavior/statistics & numerical data , Food Assistance , Food Supply/statistics & numerical data , Poverty/statistics & numerical data , Adolescent , Adult , Child , Child, Preschool , Energy Intake , Family Characteristics , Female , Humans , Infant , Longitudinal Studies , Male , Middle Aged , Nutritive Value , Young Adult
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