{"doi":"10.1111/ijpo.13037","title":"<scp>Ultra‐processed</scp>food consumption and<scp>BMI‐Z</scp>among children at risk for obesity from<scp>low‐income</scp>households","abstract":"OBJECTIVE: To evaluate the association between baseline ultra-processed food consumption in early childhood and child BMI Z-score over 36 months. METHODS: We conducted a prospective cohort analysis as a secondary data analysis of the Growing Right Onto Wellness randomised trial. Dietary intake was measured via 24-h diet recalls. The primary outcome was child BMI-Z, measured at baseline and at 3-, 9-, 12-, 24- and 36-month timepoints. Child BMI-Z was modelled using a longitudinal mixed-effects model, adjusting for covariates and stratifying by age. RESULTS: Among 595 children, median (Q1-Q3) baseline age was 4.3 (3.6-5.0) years, 52.3% of the children were female, 65.4% had normal weight, 33.8% were overweight, 0.8% were obese and 91.3% of parents identified as Hispanic. Model-based estimates suggest that, compared with low ultra-processed consumption (300 kcals/day), high ultra-processed intake (1300 kcals/day) was associated with a 1.2 higher BMI-Z at 36 months for 3-year-olds (95% CI = 0.5, 1.9; p < 0.001) and a 0.6 higher BMI-Z for 4-year-olds (95% CI = 0.2, 1.0; p = 0.007). The difference was not statistically significant for 5-year-olds or overall. CONCLUSIONS: In 3- and 4-year-old children, but not in 5-year-old children, high ultra-processed food intake at baseline was significantly associated with higher BMI-Z at 36-month follow-up, adjusting for total daily kcals. This suggests that it might not be only the total number of calories in a child's daily intake that influences child weight status, but also the number of calories from ultra-processed foods.","journal":"Pediatric Obesity","year":2023,"id":339600,"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":16,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9113,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":865808,"name":"Nadia Markie Sneed","orcid":"0000-0001-9973-6672","position":1,"is_corresponding":false},{"id":396885,"name":"Evan C. Sommer","orcid":"0000-0003-4546-205X","position":2,"is_corresponding":false},{"id":544160,"name":"Kimberly P. Truesdale","orcid":"0000-0002-6697-8322","position":3,"is_corresponding":false},{"id":455170,"name":"Donna Matheson","orcid":"0000-0001-6279-6786","position":4,"is_corresponding":false},{"id":865809,"name":"Tracy Noerper","orcid":"0000-0002-6595-4257","position":5,"is_corresponding":false},{"id":396887,"name":"Lauren R. Samuels","orcid":"0000-0002-7273-5626","position":6,"is_corresponding":false},{"id":382525,"name":"Shari L. Barkin","orcid":"0000-0003-1585-3818","position":7,"is_corresponding":false},{"id":396884,"name":"William J. Heerman","orcid":"0000-0002-9706-6860","position":0,"is_corresponding":true}],"reference_count":39,"raw_metadata":null,"created_at":"2026-07-19T01:10:49.535464Z","pmid":"37070567","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":[]}