{"doi":"10.1111/1753-0407.13555","title":"The association between multiple trajectories of macronutrient intake and the risk of new‐onset diabetes in Chinese adults","abstract":"<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>The association between macronutrient intake and diabetes is unclear. We used data from the China Health and Nutrition Survey to explore the association between macronutrient intake trajectories and diabetes risk in this study.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>We included 6755 participants who did not have diabetes at baseline and participated in at least three surveys. The energy supply ratio of carbohydrate, protein, and fat was further calculated from dietary data; different macronutrient trajectories were determined using multitrajectory models; and multiple Cox regression models were used to evaluate the association between these trajectories and diabetes.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>We found three multitrajectories: decreased low carbohydrate‐increased moderate protein‐increased high fat (DLC‐IMP‐IHF), decreased high carbohydrate‐moderate protein‐increased low fat (DHC‐MP‐ILF), and balanced‐macronutrients (BM). Compared to the BM trajectory, DHC‐MP‐ILF trajectories were significantly associated with increased risk of diabetes (hazard ratio [HR]: 3.228, 95% confidence interval [CI]: 1.571–6.632), whereas no association between DLC‐IMP‐IHF trajectories and diabetes was found in our study (HR: 0.699, 95% CI: 0.351–1.392).</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>The downward trend of high carbohydrate and the increasing trend of low fat increased the risk of diabetes in Chinese adults.</jats:p><jats:p><jats:boxed-text content-type=\"graphic\" position=\"anchor\"><jats:graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mimetype=\"image/png\" position=\"anchor\" specific-use=\"enlarged-web-image\" xlink:href=\"graphic/jdb13555-gra-0001-m.png\"><jats:alt-text>image</jats:alt-text></jats:graphic></jats:boxed-text></jats:p></jats:sec>","journal":"Journal of Diabetes","year":2024,"id":650313,"datarank":0.26876392038420827,"base_score":1.791759469228055,"endowment":1.791759469228055,"self_citation_contribution":0.26876392038420827,"citation_network_contribution":0.0,"self_endowment_contribution":0.26876392038420827,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":5,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1695584,"name":"Guo Ruirui","orcid":null,"position":1,"is_corresponding":false},{"id":13127,"name":"Xiaotong Li","orcid":"0000-0003-1644-6835","position":2,"is_corresponding":false},{"id":1566248,"name":"Fengdan Wang","orcid":null,"position":3,"is_corresponding":false},{"id":1695585,"name":"Zibo Wu","orcid":null,"position":4,"is_corresponding":false},{"id":418652,"name":"Yan Liu","orcid":"0000-0002-8581-2571","position":5,"is_corresponding":false},{"id":993382,"name":"Yibo Dong","orcid":"0000-0002-5264-1382","position":6,"is_corresponding":false},{"id":582684,"name":"Bo Li","orcid":"0000-0001-8782-2485","position":7,"is_corresponding":false},{"id":1695583,"name":"Sizhe Wang","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"The association between multiple trajectories of macronutrient intake and the risk of new‐onset diabetes in Chinese adults","abstract":"<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>The association between macronutrient intake and diabetes is unclear. We used data from the China Health and Nutrition Survey to explore the association between macronutrient intake trajectories and diabetes risk in this study.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>We included 6755 participants who did not have diabetes at baseline and participated in at least three surveys. The energy supply ratio of carbohydrate, protein, and fat was further calculated from dietary data; different macronutrient trajectories were determined using multitrajectory models; and multiple Cox regression models were used to evaluate the association between these trajectories and diabetes.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>We found three multitrajectories: decreased low carbohydrate‐increased moderate protein‐increased high fat (DLC‐IMP‐IHF), decreased high carbohydrate‐moderate protein‐increased low fat (DHC‐MP‐ILF), and balanced‐macronutrients (BM). Compared to the BM trajectory, DHC‐MP‐ILF trajectories were significantly associated with increased risk of diabetes (hazard ratio [HR]: 3.228, 95% confidence interval [CI]: 1.571–6.632), whereas no association between DLC‐IMP‐IHF trajectories and diabetes was found in our study (HR: 0.699, 95% CI: 0.351–1.392).</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>The downward trend of high carbohydrate and the increasing trend of low fat increased the risk of diabetes in Chinese adults.</jats:p><jats:p><jats:boxed-text content-type=\"graphic\" position=\"anchor\"><jats:graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" mimetype=\"image/png\" position=\"anchor\" specific-use=\"enlarged-web-image\" xlink:href=\"graphic/jdb13555-gra-0001-m.png\"><jats:alt-text>image</jats:alt-text></jats:graphic></jats:boxed-text></jats:p></jats:sec>","is_dataset_classified":null,"base_score":1.791759469228055,"endowment":1.791759469228055,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"38721664","pmcid":"PMC11079633","openalex_id":"https://openalex.org/W4396773863","authors":[],"funders":[{"funder_name":"National Natural Science Foundation of China","grant_id":"81973129","title":null}],"total_grants":1,"fwci":2.051,"citation_percentile":0.86266051,"influential_citations":0,"citation_trend":[{"year":2024,"count":2},{"year":2025,"count":2},{"year":2026,"count":1}],"oa_status":"gold","license":"cc-by","oa_locations":[{"url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/1753-0407.13555","host_type":"journal"},{"url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/1753-0407.13555","host_type":"publisher"},{"url":"https://onlinelibrary.wiley.com/doi/pdf/10.1111/1753-0407.13555","host_type":"publisher"},{"url":"https://doi.org/10.1111/1753-0407.13555","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/38721664","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11079633","host_type":"repository"},{"url":"https://doaj.org/article/54ca1811c0fc44a98d113d23296a5d49","host_type":"repository"},{"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11079633/pdf/JDB-16-e13555.pdf","host_type":"repository"},{"url":"https://europepmc.org/articles/PMC11079633","host_type":"Europe_PMC"},{"url":"https://europepmc.org/articles/PMC11079633?pdf=render","host_type":"Europe_PMC"}],"fields_of_study":["Nutritional Studies and Diet","Diet and metabolism studies","Food composition and properties","Humans","Female","Male","China","Middle Aged","Adult","Nutrients","Dietary Carbohydrates","Risk Factors","Nutrition Surveys","Dietary Fats","Diabetes Mellitus","Energy Intake","Dietary Proteins","Diet","East Asian People"],"mesh_terms":["Nutrients","East Asian People","Adult","Energy Intake","China","Diabetes Mellitus","Diet","Dietary Carbohydrates","Dietary Fats","Dietary Proteins","Female","Humans","Male","Middle Aged","Nutrition Surveys","Risk Factors"],"keywords":["Medicine","Diabetes mellitus","Internal medicine","Association (psychology)","Endocrinology","Prospective study","Macronutrient","Multitrajectories","New‐onset Diabetes"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-10T05:15:41.979399Z","pmid":null,"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":[]}