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Association of dietary nutrients with blood lipids and blood pressure in 18 countries: a cross-sectional analysis from the PURE study
Andrew Mente, Mahshid Dehghan, Sumathy Rangarajan, Matthew McQueen, Gilles R. Dagenais, Andreas Wielgosz, Scott A. Lear, Wei Li, Hui Chen, Yi Sun, Yang Wang, Rafael Díaz, Álvaro Avezum, Patricio López‐Jaramillo, Pamela Serón, Rajesh Kumar, Rajeev Gupta, Viswanathan Mohan, Sumathi Swaminathan, Raman Kutty, Katarzyna Zatońska, Romaina Iqbal, Rita Yusuf, Noushin Mohammadifard, Rasha Khatib, Nafiza Mat Nasir, Noor Hassim Ismail, Aytekin Oğuz, Annika Rosengren, Afzalhussein Yusufali, Edelweiss Wentzel‐Viljoen, Thandi Puoane, Jephat Chifamba, Koon Teo, Sonia S. Anand, Salim Yusuf, Clara K Chow, Martin O’Donnell, Darryl P. Leong, Andrew Smyth, Philip Joseph, Anwar T. Merchant, Sheikh Mohammed Shariful Islam, M Zhang, Weiwei Hu, Chinthanie Ramasundarahettige, Gary Wong, Shrikant I. Bangdiwala, Leanne Dyal, Amparo Casanova, Gary F. Lewis, Antonio Aliberti, Abdul Rehman Arshad, Álvaro Reyes, Ahmed Zaki, Basil S. Lewis, B Zhang, D Agapay, Danielle M. Hari, E Milazzo, E Ramezani, F Hussain, Fathimath Shifaly, G McAlpine, I. Patrick Kay, J Lindeman, Julija Rimac, John G. Swallow, L Heldman, Maha Mushtaha, Mark Trottier, M Riggi, N Aoucheva, N Kandy, Pam Mackie, Siu Lim Chin, S Ramacham, Sadequa Shahrook, Sylvie Trottier, T Tongana, W Elsheikh, Y. Iyengar, M. McQueen, Kellie Hall, J. Keys, X Wang, J Keneth, Anitha Devanath, Andrés Orlandini, B Linetsky, S Toscanelli, Germana Casaccia, JM Maini Cuneo, Omar Rahman, AK Azad, Khondkar Ayaz Rabbani, HM Cherry, Adnan Mannan, I Hassan, AT Talukdar, RB Tooheen, MU Khan, Mariz Sintaha, Tarzia Choudhury, Md Rabiul Haque, S Parvin, GB Oliveira, CS Marcílio, Antônio José Cordeiro Mattos, Jane DeJesus, Paul Poirier, Ginette Turbide, D. Auger, A LeBlanc De Bluts, MC Proulx, Marie‐Pierre Cayer, Nadine Bonneville, Danijela Gašević, E Corber, Veronica de Jong, I Vukmirovich, George Fodor, Andrew Pipe, A Shane, Fernando Laņas, S Martinez, A Valdebenito, María José Oliveros, Xingyu Wang, Wenhua Zhao, Xuan Jia, Bo Hu, Jian Bo, Zhao Xiuwen, Tao Chen, Qing Deng, Cheng Xiaoru, He Xinye, Li Jian, Juan Li, Xu Liu, Ren Bing, Wang Wei, Yi Zhai, Zhu Manlu, Fanghong Lu, Jianfang Wu, Yindong Li, Yan Hou, Liangqing Zhang, Baoxia Guo, Shiying Zhang, Bian Rongwen, Tian Xiuzhen, Dong Li, Di Chen, Wu Jianguo, Xiao Yize, Tianlu Liu, Peng Zhang, Changlin Dong, Ning Li, Xiaolan Ma, Yang Yuqing, Lei Rensheng, Fu Minfan, Jing He, Yü Liu, Xiaojie Xing, Qiang Zhou, Paul Anthony Camacho, R Garcia, LJA Jurado, Diego Gómez-Arbeláez, JF Arguello, R Dueñas, S Silva, LP Pradilla, F Ramírez, DI Molina, Carlos Cure-Cure, Suhey Pérez, E Hernandez, E. Arcos, S Fernandez, Claudia Narváez, J Paez, A Sotomayor, Henry García, G. Sánchez, T David, Prem Mony, Mário Vaz, A V Bharathi, K Shankar AV Kurpad, KG Jayachitra, Narinder Kumar, Mohan Deepa, K Parthiban, M Anitha, S Hemavathy, T Rahulashankiruthiyayan, K Sridevi, RB Panwar, Indu Mohan, Priyanka Rastogi, S. Rastogi, R. Bhargava, JS Thakur, Binod Kumar Patro, P. V. M. Lakshmi, R Mahajan, P Chaudary, V. Raman Kutty, K. Vijayakumar, G Rajasree, AR Renjini, A Deepu, B. Sandhya, Stephen Asha, HS Soumya, Roya Kelishadi, Ahmad Bahonar, Hadi Heidari, Khalid Yusoff, K S Ng, A Devi, NM Nasir, MM Yasin, Maizatullifah Miskan, EA Rahman, MKM Arsad, Farnaza Ariffin, SA Razak, FA Majid, NA Bakar, MY Yacob, N Zainon, Ruhaya Salleh, MKA Ramli, NA Halim, SR Norlizan, NM Ghazali, MN Arshad, R Razali, Syed Hassan Ali, HR Othman, CWJCW Hafar, A Pit, Norlaila Danuri, F Basir, SNA Zahari, Hafez Mohammad Ammar Abdullah, MA Arippin, NA Zakaria, MJ Hasni, MT Azmi, MI Zaleha, KY Hazdi, AR Rizam, W Sazman, A Azman, Umaiyeh Khammash, A Khatib, Rita Giacaman, Asad Afridi, Rehman Khawaja, Auriba Raza, Khawar Kazmi, Antonio Dans, HU Co, JT Sanchez, L Pudol, C Zamora-Pudol, LAM Palileo-Villanueva, MR Aquino, C Abaquin, SL Pudol, ML Cabral, Witold Zatoński, Andrzej Szuba, Rafał Ilow, M Ferus, Bożena Regulska−Ilow, Dorota Różańska, Maria Wołyniec, Khalid F. AlHabib, Ahmad Hersi, Tarek Kashour, Hussam AlFaleh, Mostafa Q. Alshamiri, HB Altaradi, Omar Alnobani, A Bafart, Nour Alkamel, Mohammed K. Ali, Mahera Abdulrahman, Reza Nouri, A. Kruger, H H Voster, Aletta E. Schutte, FC Eloff, H de Ridder, H Moss, J Potgieter, A.V. Diez Roux, Megan Watson, G de Wet, Antonel Olckers, Johann C. Jerling, Marlien Pieters, Trynke Hoekstra, Ehimario Igumbor, Lungiswa Tsolekile, David Sanders, Pooveshni Naidoo, N Steyn, Nasheeta Peer, Bongani M. Mayosi, Brian Rayner, Estelle V. Lambert, Naomi Levitt, Tracy Kolbe‐Alexander, Lucas Ntyintyane, G. Hughes, Rina Swart, Jean Fourie, Moïse Muzigaba, S Xapa, N Gobile, K Ndayi, B Jwili, K Ndibaza, Bonaventure Amandi Egbujie, Kristina Bengtsson Boström, A Gustavsson, Mattias Andréasson, M Snällman, L Wirdemann, Karen Yeates, Jessica Sleeth, Kajiru Kilonzo, Neşe İmeryüz, Yüksel Altuntaş, Ahmet Temizhan, KBT Calik, AAK Akalin, OT Caklili, MV Keskinler, AN Erbakan, AM Yusufali, Wael Almahmeed, H Swidan, EA Darwish, ARA Hashemi, Najib Al‐Khaja, J. Muscat-Baron, SH Ahmed, TM Mamdouh, WM Darwish, MHS Abdelmotagali, SA Omer Awed, GA Movahedi, H Al Shaibani, RIM Gharabou, DF Youssef, AZS Nawati, ZAR Abu Salah, RFE Abdalla, SM Al Shuwaihi, MA Al Omairi, OD Cadigal, R.S. Alejandrino, Lenon Gwaunza, G Terera, Carol Mahachi, Pretty Murambiwa, T Machiweni, RF Mapanga
Bibliographic record
VenueThe Lancet Diabetes & Endocrinology · 2017
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsSimon Fraser UniversityUniversity of OttawaInstitut universitaire de cardiologie et de pneumologie de QuébecHamilton Health SciencesImpactMcMaster UniversityUniversité LavalPopulation Health Research Institute
FundersHeart and Stroke Foundation of Canada
KeywordsMedicineCholesterolPolyunsaturated fatty acidNutrientSaturated fatPolyunsaturated fatBlood pressureBlood lipidsInternal medicineSaturated fatty acidApolipoprotein BFood scienceEndocrinologyEnvironmental healthPhysiologyFatty acidBiologyBiochemistry
Abstract
No abstract in any covered source. Its absence is recorded, not treated as a negative.
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
models agreeAgreement compares identical category sets and study designs across arms.
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.056
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
Opus teacher head0.024
GPT teacher head0.298
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".
Quick stats
Citations269
Published2017
Admission routes2
Has abstractno