1
|
Hang D, Du M, Wang L, Wang K, Fang Z, Khandpur N, Rossato SL, Steele EM, Chan AT, Hu FB, Meyerhardt JA, Mozaffarian D, Ogino S, Sun Q, Wong JB, Zhang FF, Song M. Ultra-processed food consumption and mortality among patients with stages I-III colorectal cancer: a prospective cohort study. EClinicalMedicine 2024; 71:102572. [PMID: 38572081 PMCID: PMC10990709 DOI: 10.1016/j.eclinm.2024.102572] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 02/24/2024] [Accepted: 03/13/2024] [Indexed: 04/05/2024] Open
Abstract
Background Ultra-processed foods (UPFs) are emerging as a risk factor for colorectal cancer (CRC), yet how post-diagnostic UPF intake may impact CRC prognosis remains unexplored. Methods Data collected from food frequency questionnaires were used to estimate intakes of total UPFs and UPF subgroups (serving/d) at least 6 months but less than 4 years post-diagnosis among 2498 patients diagnosed with stages I-III CRC within the Nurses' Health Study and Health Professionals Follow-up Study during 1980-2016. Hazard ratios (HR) and 95% confidence intervals (CIs) of all-cause, CRC- and cardiovascular disease (CVD)-specific mortality in association with UPF consumption were estimated using an inverse probability weighted multivariable Cox proportional hazards regression model, adjusted for confounders. Findings The mean (SD) age of patients at diagnosis was 68.5 (9.4) years. A total of 1661 deaths were documented, including 321 from CRC and 335 from CVD. Compared to those in the lowest quintile (median = 3.6 servings/d), patients in the highest quintile (median = 10 servings/d) of post-diagnostic UPF intake had higher CVD mortality (HR = 1.65, 95% CI = 1.13-2.40) but not CRC or all-cause mortality. Among UPF subgroups, higher consumption of fats/condiments/sauces was associated with a higher risk of CVD-specific mortality (highest vs. lowest quintile of intake, HR = 1.96, 95% CI = 1.41-2.73), and higher intake of ice cream/sherbet was associated with an increased risk of CRC-specific mortality (highest vs. lowest quintile, HR = 1.86, 95% CI: 1.33-2.61). No statistically significant association was found between UPF subgroups and overall mortality. Interpretation Higher post-diagnostic intake of total UPFs and fats/condiments/sauces in CRC survivors is associated with higher CVD mortality, and higher ice cream/sherbet intake is linked to higher CRC mortality. Funding US National Institutes of Health and the American Cancer Society.
Collapse
Affiliation(s)
- Dong Hang
- Department of Epidemiology, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Mengxi Du
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
- Clinical and Translational Epidemiology Unit and Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Lu Wang
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
| | - Kai Wang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Zhe Fang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Neha Khandpur
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Division of Human Nutrition and Health, Wageningen University, Netherlands
- Department of Nutrition, School of Public Health, University of São Paulo, São Paulo, Brazil
| | - Sinara Laurini Rossato
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Institute of Geography, Universidade Federal de Uberlândia, Minas Gerais, Brazil
| | - Eurídice Martínez Steele
- Department of Nutrition, School of Public Health, University of São Paulo, São Paulo, Brazil
- Center for Epidemiological Studies in Health and Nutrition (NUPENS), Faculty of Public Health, University of São Paulo, Brazil
| | - Andrew T. Chan
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Clinical and Translational Epidemiology Unit and Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Frank B. Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Jeffrey A. Meyerhardt
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA
| | - Dariush Mozaffarian
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
- Tufts School of Medicine and Division of Cardiology, Tufts Medical Center, Boston, MA, USA
| | - Shuji Ogino
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women’s Hospital, and Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Nutrition, Harvard Medical School, Boston, MA, USA
- Tokyo Medical and Dental University (Institute of Science Tokyo), Tokyo, Japan
| | - Qi Sun
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - John B. Wong
- Division of Clinical Decision Making, Tufts Medical Center, Boston, MA, USA
| | - Fang Fang Zhang
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
| | - Mingyang Song
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Clinical and Translational Epidemiology Unit and Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| |
Collapse
|
2
|
Li J, Ge X, Liu X, Fu C, Miao J, Zhao W, Miao L, Hang D. Serum apolipoproteins and mortality risk: evidence from observational and Mendelian randomization analyses. Am J Clin Nutr 2024; 119:981-989. [PMID: 38211689 DOI: 10.1016/j.ajcnut.2024.01.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 01/02/2024] [Accepted: 01/08/2024] [Indexed: 01/13/2024] Open
Abstract
BACKGROUND Apolipoproteins (APOs) have emerged as significant players in lipid metabolism that affects the risk of chronic disease. However, the impact of circulating APO concentrations on premature death remains undetermined. OBJECTIVES This study aimed to investigate the associations of serum APOs with all-cause, cardiovascular disease (CVD)-related, and cancer-related mortality. METHODS We included 340,737 participants who had serum APO measurements from the UK Biobank. Restricted cubic splines and multivariable Cox regression models were used to assess the associations between APOs and all-cause and cause-specific mortality by computing hazard ratios (HRs) and 95% confidence intervals (CIs). Based on 1-sample Mendelian randomization (MR) design, including 398,457 participants of White ancestry who had genotyping data from the UK Biobank, we performed instrumental variable analysis with 2-stage least squares regression to assess the association between genetically predicted APOs and mortality. RESULTS After adjusting for potential confounders including high-density and low-density lipoprotein particles, we observed nonlinear inverse relationships of APOA1 with all-cause, CVD-related, and cancer-related mortality (P-nonlinear < 0.001). By contrast, positive relationships were observed for APOB and all-cause (P-nonlinear < 0.001), CVD-related (P-linear < 0.001), and cancer-related (P-linear = 0.03) mortality. MR analysis showed consistent results, except that the association between APOB and cancer mortality was null. Furthermore, both observational and MR analyses found an inverse association between APOA1 and lung cancer-related mortality (HR comparing extreme deciles: 0.46; 95% CI: 0.26, 0.80; and HR: 0.78; 95% CI: 0.63, 0.97, respectively). CONCLUSIONS Our findings indicate that circulating APOA1 has potential beneficial effects on all-cause, CVD-related, and lung cancer-related death risk, whereas APOB may confer detrimental effects on all-cause and CVD-related death risk.
Collapse
Affiliation(s)
- Jiacong Li
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Xianxiu Ge
- Medical Center for Digestive Diseases, Second Affiliated Hospital, Nanjing Medical University, Nanjing, China
| | - Xinyi Liu
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Chengqu Fu
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Junyan Miao
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Wei Zhao
- Center of Clinical Laboratory Science, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Nanjing, China.
| | - Lin Miao
- Medical Center for Digestive Diseases, Second Affiliated Hospital, Nanjing Medical University, Nanjing, China.
| | - Dong Hang
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing, China
| |
Collapse
|
3
|
Bonfiglio C, Campanella A, Donghia R, Bianco A, Franco I, Curci R, Bagnato CB, Tatoli R, Giannelli G, Cuccaro F. Development and Internal Validation of a Model for Predicting Overall Survival in Subjects with MAFLD: A Cohort Study. J Clin Med 2024; 13:1181. [PMID: 38398493 PMCID: PMC10889818 DOI: 10.3390/jcm13041181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 02/01/2024] [Accepted: 02/18/2024] [Indexed: 02/25/2024] Open
Abstract
Background & Aims: Fatty liver disease with metabolic dysfunction (MAFLD) is a new concept proposed to replace the previous concept of Non-Alcoholic Hepatic Steatosis (NAFLD). We developed and internally validated a prognostic model to predict the likelihood of death in a cohort of subjects with MAFLD. Methods: Our work involved two steps: the first was the construction of a bootstrapped multivariable Cox model for mortality risk prognosis and the second was its validation. Results: The study cohort included 1506 subjects, of which 907 were used for internal validation. Discriminant measures for the final model were R2D 0.6845 and Harrell's C 0.8422 in the development and R2D 0.6930 and Harrell's C 0.8465 in the validation. We used the nine independent prognostic factors selected by the LASSO Cox procedure and fitted by the bootstrap Cox survival model, and observed β were: Gender 0.356 1.42 (p < 0.008), Age 0.146 (p < 0.001), Glycemia 0.004 (p < 0.002), Total Cholesterol -0.0040 (p < 0.009), Gamma Glutamyl Transpeptidase 0.009 (p < 0.001), SBP 0.009 (p < 0.036), DBP -0.016 (p < 0.041), ALP 0.008 (p < 0.071) and Widowhood 0.550 (p < 0.001). Conclusions: We produced and validated a model to estimate the probability of death in subjects with MAFLD. The instruments we used showed satisfactory predictive capabilities.
Collapse
Affiliation(s)
- Caterina Bonfiglio
- National Institute of Gastroenterology—IRCCS ‘S de Bellis’, 70013 Castellana Grotte, BA, Italy; (A.C.); (R.D.); (A.B.); (I.F.); (R.C.); (C.B.B.); (R.T.); (G.G.)
| | - Angelo Campanella
- National Institute of Gastroenterology—IRCCS ‘S de Bellis’, 70013 Castellana Grotte, BA, Italy; (A.C.); (R.D.); (A.B.); (I.F.); (R.C.); (C.B.B.); (R.T.); (G.G.)
| | - Rossella Donghia
- National Institute of Gastroenterology—IRCCS ‘S de Bellis’, 70013 Castellana Grotte, BA, Italy; (A.C.); (R.D.); (A.B.); (I.F.); (R.C.); (C.B.B.); (R.T.); (G.G.)
| | - Antonella Bianco
- National Institute of Gastroenterology—IRCCS ‘S de Bellis’, 70013 Castellana Grotte, BA, Italy; (A.C.); (R.D.); (A.B.); (I.F.); (R.C.); (C.B.B.); (R.T.); (G.G.)
| | - Isabella Franco
- National Institute of Gastroenterology—IRCCS ‘S de Bellis’, 70013 Castellana Grotte, BA, Italy; (A.C.); (R.D.); (A.B.); (I.F.); (R.C.); (C.B.B.); (R.T.); (G.G.)
| | - Ritanna Curci
- National Institute of Gastroenterology—IRCCS ‘S de Bellis’, 70013 Castellana Grotte, BA, Italy; (A.C.); (R.D.); (A.B.); (I.F.); (R.C.); (C.B.B.); (R.T.); (G.G.)
| | - Claudia Beatrice Bagnato
- National Institute of Gastroenterology—IRCCS ‘S de Bellis’, 70013 Castellana Grotte, BA, Italy; (A.C.); (R.D.); (A.B.); (I.F.); (R.C.); (C.B.B.); (R.T.); (G.G.)
| | - Rossella Tatoli
- National Institute of Gastroenterology—IRCCS ‘S de Bellis’, 70013 Castellana Grotte, BA, Italy; (A.C.); (R.D.); (A.B.); (I.F.); (R.C.); (C.B.B.); (R.T.); (G.G.)
| | - Gianluigi Giannelli
- National Institute of Gastroenterology—IRCCS ‘S de Bellis’, 70013 Castellana Grotte, BA, Italy; (A.C.); (R.D.); (A.B.); (I.F.); (R.C.); (C.B.B.); (R.T.); (G.G.)
| | | |
Collapse
|
4
|
Fernández-Lázaro D, Seco-Calvo J. Nutrition, Nutritional Status and Functionality. Nutrients 2023; 15:nu15081944. [PMID: 37111162 PMCID: PMC10142726 DOI: 10.3390/nu15081944] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 04/17/2023] [Indexed: 04/29/2023] Open
Abstract
A good quality of life means obtaining adequate nutrition and regular physical activity [...].
Collapse
Affiliation(s)
- Diego Fernández-Lázaro
- Department of Cellular Biology, Genetics, Histology and Pharmacology, Faculty of Health Sciences, University of Valladolid, Campus of Soria, 42004 Soria, Spain
- Neurobiology Research Group, Faculty of Medicine, University of Valladolid, 47005 Valladolid, Spain
| | - Jesús Seco-Calvo
- Institute of Biomedicine (IBIOMED), Universidad de León, 24071 León, Spain
- Department of Physiology, University of the Basque Country, 48940 Leioa, Spain
| |
Collapse
|
5
|
Yang M, Miao J, Du L, Wang J, Yang J, Lu J, Fan X, Huang C, Fu Z, Xu Z, Song M, Ma H, Jin G, Hu Z, Hang D, Shen H. Serum calcium concentrations and risk of all-cause and cause-specific mortality: results from two prospective cohorts. J Clin Endocrinol Metab 2023:7046139. [PMID: 36806939 DOI: 10.1210/clinem/dgad078] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 02/01/2023] [Accepted: 02/06/2023] [Indexed: 02/20/2023]
Abstract
CONTEXT Calcium plays a critical role in various physiological activities. However, the association between circulating calcium concentrations and mortality in a general healthy population remains undetermined. OBJECTIVE To examine the association of serum calcium concentrations with all-cause and cause-specific mortality. METHODS Leveraging data from the UK Biobank (n=361 662) and the US National Health and Nutrition Examination Survey (NHANES, n=36 985), we prospectively examined the association of serum calcium concentrations with all-cause and cause-specific mortality using Cox proportional hazard and restricted-cubic spline models. RESULTS During a median follow-up of 12.0 years, UK Biobank documented 18 327 deaths, including 3119 (17.0%) from cardiovascular disease (CVD) and 9599 (52.4%) from cancer. We found a U-shape relationship of albumin-adjusted calcium concentrations with all-cause and CVD mortality. Compared to participants with moderate calcium levels (the third quintile, Q3), those with low and high levels had an increased risk of all-cause (hazard ratio [HR]=1.02 for Q1 vs. Q3; 1.10 for Q5 vs. Q3) and CVD mortality (HR=1.11 for Q1 vs. Q3; 1.25 for Q5 vs. Q3). In contrast, there was a linear positive relationship with cancer mortality (HR=1.09 for Q5 vs. Q1). Similar results for all-cause, CVD, and cancer mortality were observed in US NHANES. CONCLUSIONS Our findings provide novel insights into the association between serum calcium concentrations and mortality in the general healthy population.
Collapse
Affiliation(s)
- Mingjia Yang
- Department of Epidemiology, School of Public Health, Southeast University, Nanjing 210009, China
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Junyan Miao
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Lingbin Du
- Department of Cancer Prevention, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, China
- Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, China
| | - Jiayu Wang
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Jing Yang
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Jiayi Lu
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Xikang Fan
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Changzhi Huang
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Zan Fu
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Zekuan Xu
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Mingyang Song
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Hongxia Ma
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University 211166, Nanjing, China
| | - Guangfu Jin
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University 211166, Nanjing, China
| | - Zhibin Hu
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University 211166, Nanjing, China
| | - Dong Hang
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University 211166, Nanjing, China
| | - Hongbing Shen
- Department of Epidemiology, School of Public Health, Southeast University, Nanjing 210009, China
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University 211166, Nanjing, China
| |
Collapse
|