{"doi":"10.1371/journal.pone.0231572","title":"A comparison of different practical indices for assessing carbohydrate quality among carbohydrate-rich processed products in the US","abstract":"Healthier carbohydrate (carb)-rich foods are essential for health, but practical, validated indices for their identification are not established. We compared four pragmatic metrics, based on, per 10g of carb:(a) ≥1g fiber (10:1 carb:fiber), (b) ≥1g fiber and <1g free sugars (10:1:1 carb:fiber:free sugars), (c) ≥1g fiber and <2g free sugars (10:1:2 carb:fiber:free sugars); and (d) ≥1g fiber and, per each 1 g of fiber, <2g free sugars (10:1 carb:fiber, 1:2 fiber:free sugars; or 10:1|1:2). Using 2013-2016 National Health and Nutrition Examination Survey /Food and Nutrient Database for Dietary Studies, we assessed, overall and for 12 food categories, whether each metric discriminated carb-rich products higher or lower (per 100g) in calories, total fat, saturated fat, protein, sugar, fiber, sodium, potassium, magnesium, folate, and 8 vitamins/minerals. Among 2,208 carb-rich products, more met 10:1 (23.2%) and 10:1|1:2 (21.3%), followed by 10:1:2 (19.2%) and 10:1:1 (16.4%) ratios, with variation by product sub-categories. The 10:1 and 10:1|1:2 ratios similarly identified products with lower calories, fat, free sugars, and sodium; and higher protein, fiber, potassium, magnesium, iron, vitamin B6, vitamin E, zinc and iron. The 10:1:2 and 10:1:1 ratios identified products with even larger differences in calories and free sugars, but smaller differences in other nutrients above and lower folate, thiamine, riboflavin, and niacin; the latter findings were attenuated after excluding breakfast cereals (~9% of products). These novel findings inform dietary guidance for consumers, policy, and industry to identify and promote the development of the healthier carb-rich foods.","journal":"PLoS ONE","year":2020,"id":93292,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":40,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9453,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":22757,"name":"Colin D. Rehm","orcid":"0000-0002-7644-0040","position":1,"is_corresponding":false},{"id":397702,"name":"Peilin Shi","orcid":"0000-0002-8540-798X","position":2,"is_corresponding":false},{"id":465891,"name":"Nicola M. McKeown","orcid":"0000-0002-1437-7533","position":3,"is_corresponding":false},{"id":22683,"name":"Dariush Mozaffarian","orcid":"0000-0001-7958-9492","position":4,"is_corresponding":false},{"id":243249,"name":"Renata Micha","orcid":"0000-0002-3983-1632","position":5,"is_corresponding":false},{"id":465890,"name":"Junxiu Liu","orcid":"0000-0003-3303-0217","position":0,"is_corresponding":true}],"reference_count":21,"raw_metadata":null,"created_at":"2026-07-18T22:30:54.208860Z","pmid":"32437371","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}