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Many Small Island Developing States (SIDS) are experiencing a nutrition transition, wherein high prevalence of malnutrition co-occurs with growing rates of diet-related non-communicable diseases. Sustainably managed and accessible aquatic foods can serve as a rich and bioavailable source of nutrients, helping communities achieve healthy diets and meet key sustainable development goals (e.g., SDG 1 No Poverty, SDG 2 Zero Hunger, and SDG 14 Life Below Water). However, to properly harness aquatic food systems in nutrition interventions, we must first understand aquatic food’s role in nutrient intake and adequacy. Here, using a nationally representative survey from Kiribati, we quantify the contribution of aquatic foods to nutrient intake and adequacy, and examine the spatial variability in nutrient intake adequacies. We find aquatic foods are the main contributors of most nutrients we examined, providing > 75% of vitamin B12, retinol, and heme iron, > 50% of niacin and total vitamin A, and > 25% of protein, vitamin E, potassium, and total iron consumed. Consumption of aquatic foods contributes to meeting key nutrient adequacies (e.g., niacin) and provides complete adequacy for vitamin B12 and protein. However, despite high aquatic food consumption, we find high levels of nutrient inadequacies (11 of the 17 nutrients with dietary reference intakes). Overall, our study quantifies the nutritional importance of aquatic foods in an emblematic SIDS, emphasizing their vulnerability to declining aquatic resources. We also highlight the need for cross-scale context-specific targeted nutrition interventions, even when aquatic food consumption is high, to enable SIDS to meet key SDGs.
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This content will become publicly available on August 29, 2026
APPLICATION OF AI AND MACHINE LEARNING TO ANALYZE PROTEIN CONTENT IN U.S. COMMERCIAL BABY FOODS
Proteins are essential macronutrients that support the growth, development, and maintenance of tissues in children. Nutrient requirements vary with age, weight, and physiological needs, making age-specific dietary planning critical. Adequate protein intake promotes both physical growth and cognitive development, while diverse sources such as lean meats, dairy, legumes, and nuts help meet varying nutritional needs and encourage lifelong healthy eating habits. This study analyzed a nutritional dataset of 244 baby foods using artificial intelligence (AI) and machine learning to assess protein content, categorizing items into three groups based on protein content: low (0.0–5.9 g/day), moderate (6.0– 10.9 g/day), and high (11.0–15.0 g/day). The majority (n = 202) fell into the low-protein range, followed by 22 in the moderate range and 20 in the high range. Age-specific protein requirements, expressed in grams per kilogram of body weight (g/kg), were assessed for four age groups: 0– 6 months (1.52 g/kg; 12.6–15.8 g/day; 5.5–6.0 kg), 7–9 months (1.20 g/kg; 9.0–10.2 g/day; 7.5–8.5 kg), 10–12 months (1.00 g/kg; 8.5–9.5 g/day; 8.5–9.5 kg), and 1–3 years (1.05 g/kg; 12.6–15.8 g/day; 12.0–15.0 kg). Low-protein foods may be insufficient for infants with reduced breastmilk or formula intake, while high-protein foods often rich in meat, dairy, or fortified products can help meet upper-range requirements. These findings underscore the need for careful alignment of complementary food protein levels with age-specific nutritional guidelines to support optimal growth and development in early childhood.
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- PAR ID:
- 10633937
- Publisher / Repository:
- http://www.scienceijsar.com
- Date Published:
- Journal Name:
- International Journal of Science Academic Research
- ISSN:
- 2582-6425
- Subject(s) / Keyword(s):
- Baby foods Protein content AI machine learning Infants Young children
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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