Modified WCRF/AICR Score and All-Cause, Digestive System, Cardiovascular, Cancer and Other-Cause-Related Mortality: A Competing Risk Analysis of Two Cohort Studies Conducted in Southern Italy
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data Collection
2.2. Exposure Assessment
2.3. Tracing Procedures and Outcome Assessment
2.4. Statistical Analysis
3. Results
3.1. Modified WCRF/AICR Score Components
3.2. The Cohort
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- WHO. Strategizing National Health in the 21st Century: A Handbook Chapter 12 Intersectoral Planning Foe Health and Health Equity. 2016. Available online: https://apps.who.int/iris/bitstream/handle/10665/250221/9789241549745-chapter12-eng.pdf?sequence=3&isAllowed=y (accessed on 30 October 2020).
- Adams, S.H.; Anthony, J.C.; Carvajal, R.; Chae, L.; Khoo, C.S.H.; Latulippe, M.E.; Matusheski, N.V.; McClung, H.L.; Rozga, M.; Schmid, C.H.; et al. Perspective: Guiding Principles for the Implementation of Personalized Nutrition Approaches That Benefit Health and Function. Adv. Nutr. 2019, 11, 25–34. [Google Scholar] [CrossRef] [PubMed]
- Griffiths, J.C.; De Vries, J.; McBurney, M.I.; Wopereis, S.; Serttas, S.; Marsman, D.S. Measuring health promotion: Translating science into policy. Eur. J. Nutr. 2020, 59, 11–23. [Google Scholar] [CrossRef] [PubMed]
- Kołodziej, H.; Lopuszańska, M.; Bielicki, T.; Jankowska, E.A. Social inequality in premature mortality among Polish urban adults during economic transition. Am. J. Hum. Biol. 2007, 19, 878–885. [Google Scholar] [CrossRef] [PubMed]
- Fresán, U.; Martínez-González, M.A.; Sabaté, J.; Bes-Rastrollo, M. Global sustainability (health, environment and monetary costs) of three dietary patterns: Results from a Spanish cohort (the SUN project). BMJ Open 2019, 9, e021541. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Wilkinson, M.D.; Dumontier, M.; Aalbersberg, I.J.; Appleton, G.; Axton, M.; Baak, A.; Blomberg, N.; Boiten, J.W.; da Silva Santos, L.B.; Bourne, P.E.; et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data 2016, 3, 160018. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- El Bilali, H. Research on agro-food sustainability transitions: Where are food security and nutrition? Food Secur. 2019, 11, 559–577. [Google Scholar] [CrossRef] [Green Version]
- Willett, W.; Rockström, J.; Loken, B.; Springmann, M.; Lang, T.; Vermeulen, S.; Garnett, T.; Tilman, D.; DeClerck, F.; Wood, A.; et al. Food in the Anthropocene: The EAT-Lancet Commission on healthy diets from sustainable food systems. Lancet 2019, 393, 447–492. [Google Scholar] [CrossRef]
- Diet, Nutrition, Physical Activity and Cancer: A Global Perspective. Continuous Update Project Expert Report. Available online: https://www.wcrf.org/dietandcancer/resources-and-toolkit (accessed on 30 October 2020).
- Grafetstätter, M.; Pletsch-Borba, L.; Sookthai, D.; Karavasiloglou, N.; Johnson, T.; Katzke, V.A.; Hoffmeister, M.; Bugert, P.; Kaaks, R.; Kühn, T. Thrombomodulin and Thrombopoietin, Two Biomarkers of Hemostasis, Are Positively Associated with Adherence to the World Cancer Research Fund/American Institute for Cancer Research Recommendations for Cancer Prevention in a Population-Based Cross-Sectional Study. Nutrients 2019, 11, 2067. [Google Scholar] [CrossRef] [Green Version]
- Hashemian, M.; Farvid, M.S.; Poustchi, H.; Murphy, G.; Etemadi, A.; Hekmatdoost, A.; Kamangar, F.; Sheikh, M.; Pourshams, A.; Sepanlou, S.G.; et al. The application of six dietary scores to a Middle Eastern population: A comparative analysis of mortality in a prospective study. Eur. J. Epidemiol. 2019, 34, 371–382. [Google Scholar] [CrossRef] [PubMed]
- Quagliariello, V.; D’Aiuto, G.; Iaffaioli, R.V.; Berretta, M.; Buccolo, S.; Iovine, M.; Paccone, A.; Cerrone, F.; Bonanno, S.; Nunnari, G.; et al. Reasons why COVID-19 survivors should follow dietary World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) recommendations: From hyper-inflammation to cardiac dysfunctions. Eur. Rev. Med. Pharm. Sci. 2021, 25, 3898–3907. [Google Scholar] [CrossRef]
- Becaria Coquet, J.; Caballero, V.R.; Camisasso, M.C.; González, M.F.; Niclis, C.; Román, M.D.; Muñoz, S.E.; Leone, C.M.; Procino, F.; Osella, A.R.; et al. Diet Quality, Obesity and Breast Cancer Risk: An Epidemiologic Study in Córdoba, Argentina. Nutr. Cancer 2020, 72, 1026–1035. [Google Scholar] [CrossRef] [PubMed]
- Castelló, A.; Martín, M.; Ruiz, A.; Casas, A.M.; Baena-Cañada, J.M.; Lope, V.; Antolín, S.; Sánchez, P.; Ramos, M.; Antón, A.; et al. Lower Breast Cancer Risk among Women following the World Cancer Research Fund and American Institute for Cancer Research Lifestyle Recommendations: EpiGEICAM Case-Control Study. PLoS ONE 2015, 10, e0126096. [Google Scholar] [CrossRef] [PubMed]
- Romaguera, D.; Vergnaud, A.-C.; Peeters, P.H.; Van Gils, C.H.; Chan, D.S.; Ferrari, P.; Romieu, I.; Jenab, M.; Slimani, N.; Clavel-Chapelon, F.; et al. Is concordance with World Cancer Research Fund/American Institute for Cancer Research guidelines for cancer prevention related to subsequent risk of cancer? Results from the EPIC study. Am. J. Clin. Nutr. 2012, 96, 150–163. [Google Scholar] [CrossRef] [PubMed]
- Shams-White, M.M.; Brockton, N.T.; Mitrou, P.; Romaguera, D.; Brown, S.; Bender, A.; Kahle, L.L.; Reedy, J. Operationalizing the 2018 World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) Cancer Prevention Recommendations: A Standardized Scoring System. Nutrients 2019, 11, 1572. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Inoue-Choi, M.; Robien, K.; Lazovich, D. Adherence to the WCRF/AICR guidelines for cancer prevention is associated with lower mortality among older female cancer survivors. Cancer Epidemiol. Biomark. Prev. 2013, 22, 792–802. [Google Scholar] [CrossRef] [Green Version]
- Solans, M.; Chan, D.S.M.; Mitrou, P.; Norat, T.; Romaguera, D. A systematic review and meta-analysis of the 2007 WCRF/AICR score in relation to cancer-related health outcomes. Ann. Oncol. 2020, 31, 352–368. [Google Scholar] [CrossRef] [Green Version]
- Tollosa, D.N.; Tavener, M.; Hure, A.; James, E.L. Adherence to multiple health behaviours in cancer survivors: A systematic review and meta-analysis. J. Cancer Surviv. 2019, 13, 327–343. [Google Scholar] [CrossRef]
- Bonaccio, M.; Di Castelnuovo, A.; Costanzo, S.; De Curtis, A.; Persichillo, M.; Cerletti, C.; Donati, M.B.; de Gaetano, G.; Iacoviello, L. Association of a traditional Mediterranean diet and non-Mediterranean dietary scores with all-cause and cause-specific mortality: Prospective findings from the Moli-sani Study. Eur. J. Nutr. 2021, 60, 729–746. [Google Scholar] [CrossRef]
- Koller, M.T.; Raatz, H.; Steyerberg, E.W.; Wolbers, M. Competing risks and the clinical community: Irrelevance or ignorance? Stat. Med. 2012, 31, 1089–1097. [Google Scholar] [CrossRef] [Green Version]
- Lau, B.; Cole, S.R.; Gange, S.J. Competing risk regression models for epidemiologic data. Am. J. Epidemiol. 2009, 170, 244–256. [Google Scholar] [CrossRef]
- Austin, P.C.; Lee, D.S.; Fine, J.P. Introduction to the Analysis of Survival Data in the Presence of Competing Risks. Circulation 2016, 133, 601–609. [Google Scholar] [CrossRef] [PubMed]
- Serra-Majem, L.; Tomaino, L.; Dernini, S.; Berry, E.M.; Lairon, D.; Ngo de la Cruz, J.; Bach-Faig, A.; Donini, L.M.; Medina, F.X.; Belahsen, R.; et al. Updating the Mediterranean Diet Pyramid towards Sustainability: Focus on Environmental Concerns. Int. J. Env. Res. Public Health 2020, 17, 8758. [Google Scholar] [CrossRef] [PubMed]
- Campanella, A.; Misciagna, G.; Mirizzi, A.; Caruso, M.G.; Bonfiglio, C.; Aballay, L.R.; Vas de Arruda Silveira, L.; Bianco, A.; Franco, I.; Sorino, P.; et al. The effect of the Mediterranean Diet on lifespan. A treatment-effect survival analysis of a population-based prospective cohort study in Southern Italy. Int. J. Epidemiol. 2021, 50, 245–255. [Google Scholar] [CrossRef]
- Veronese, N.; Notarnicola, M.; Cisternino, A.M.; Inguaggiato, R.; Guerra, V.; Reddavide, R.; Donghia, R.; Rotolo, O.; Zinzi, I.; Leandro, G.; et al. Trends in adherence to the Mediterranean diet in South Italy: A cross sectional study. Nutr. Metab. Cardiovasc. Dis. NMCD 2020, 30, 410–417. [Google Scholar] [CrossRef] [PubMed]
- Bonfiglio, C.; Leone, C.M.; Silveira, L.V.A.; Guerra, R.; Misciagna, G.; Caruso, M.G.; Bruno, I.; Buongiorno, C.; Campanella, A.; Guerra, V.M.B.; et al. Remnant cholesterol as a risk factor for cardiovascular, cancer or other causes mortality: A competing risks analysis. Nutr. Metab. Cardiovasc. Dis. NMCD 2020, 30, 2093–2102. [Google Scholar] [CrossRef]
- World Health Organization Update Project Report. Food, Nutrition, Physical Activity and the Prevention of Breast Cancer. Available online: https://www.wcrf.org/sites/default/files/breast-cancer-2010-report.pdf (accessed on 10 October 2020).
- World Helath Organization. Project: Diet, Nutrition, Physical Activity and Breast Cancer. 2017. Available online: https://www.wcrf.org/sites/default/files/breast-cancer-2017-report.pdf (accessed on 10 October 2020).
- World Health Organization. Food, Nutrition, Physical Activity and the prevention of Cancer: A Global Perspective. Available online: https://discovery.ucl.ac.uk/id/eprint/4841/1/4841.pdf (accessed on 10 October 2020).
- Cozzolongo, R.; Osella, A.R.; Elba, S.; Petruzzi, J.; Buongiorno, G.; Giannuzzi, V.; Leone, G.; Bonfiglio, C.; Lanzilotta, E.; Manghisi, O.G.; et al. Epidemiology of HCV infection in the general population: A survey in a southern Italian town. Am. J. Gastroenterol. 2009, 104, 2740–2746. [Google Scholar] [CrossRef]
- Osella, A.R.; Misciagna, G.; Guerra, V.M.; Chiloiro, M.; Cuppone, R.; Cavallini, A.; Di Leo, A. Hepatitis C virus (HCV) infection and liver-related mortality: A population-based cohort study in southern Italy. The Association for the Study of Liver Disease in Puglia. Int. J. Epidemiol. 2000, 29, 922–927. [Google Scholar] [CrossRef] [PubMed]
- Attili, A.F.; Capocaccia, R.; Carulli, N.; Festi, D.; Roda, E.; Barbara, L.; Capocaccia, L.; Menotti, A.; Okolicsanyi, L.; Ricci, G.; et al. Factors associated with gallstone disease in the MICOL experience. Multicenter Italian Study on Epidemiology of Cholelithiasis. Hepatology 1997, 26, 809–818. [Google Scholar] [CrossRef]
- International Standard Classification of Education (ISCED-97). Available online: https://ec.europa.eu/eurostat/cache/metadata/Annexes/educ_uoe_h_esms_an2.htm (accessed on 17 August 2020).
- International Standard Classification of Occupations, International Labour Office. Available online: https://www.ilo.org/wcmsp5/groups/public/---dgreports/---dcomm/---publ/documents/publication/wcms_172572.pdf (accessed on 22 January 2020).
- Sever, P. New hypertension guidelines from the National Institute for Health and Clinical Excellence and the British Hypertension Society. J. Renin Angiotensin Aldosterone Syst. 2006, 7, 61–63. [Google Scholar] [CrossRef]
- Kaaks, R.; Riboli, E. Validation and calibration of dietary intake measurements in the EPIC project: Methodological considerations. European Prospective Investigation into Cancer and Nutrition. Int. J. Epidemiol. 1997, 26 (Suppl. 1), S15–S25. [Google Scholar] [CrossRef] [Green Version]
- Riboli, E.; Hunt, K.J.; Slimani, N.; Ferrari, P.; Norat, T.; Fahey, M.; Charrondière, U.R.; Hémon, B.; Casagrande, C.; Vignat, J.; et al. European Prospective Investigation into Cancer and Nutrition (EPIC): Study populations and data collection. Public Health Nutr. 2002, 5, 1113–1124. [Google Scholar] [CrossRef] [PubMed]
- Slimani, N.; Deharveng, G.; Unwin, I.; Southgate, D.A.T.; Vignat, J.; Skeie, G.; Salvini, S.; Parpinel, M.; Møller, A.; Ireland, J.; et al. The EPIC nutrient database project (ENDB): A first attempt to standardize nutrient databases across the 10 European countries participating in the EPIC study. Eur. J. Clin. Nutr. 2007, 61, 1037–1056. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- WHO. International Classification of Diseases—Tenth Edition. Available online: https://icd.who.int/browse10/2010/en (accessed on 20 October 2020).
- Cox, D.R. Regression Models and Life-Tables. J. R. Stat. Soc. Ser. B 1972, 34, 187–220. [Google Scholar] [CrossRef]
- Fine, J.P.; Gray, R.J. A Proportional Hazards Model for the Subdistribution of a Competing Risk. J. Am. Stat. Assoc. 1999, 94, 496–509. [Google Scholar] [CrossRef]
- Coviello, V.; Boggess, M. Cumulative incidence estimation in the presence of competing risks. Stata J. 2004, 4, 103–112. [Google Scholar] [CrossRef] [Green Version]
- Gerber, M.; Hoffman, R. The Mediterranean diet: Health, science and society. Br. J. Nutr. 2015, 113 (Suppl. 2), S4–S10. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Lacatusu, C.M.; Grigorescu, E.D.; Floria, M.; Onofriescu, A.; Mihai, B.M. The Mediterranean Diet: From an Environment-Driven Food Culture to an Emerging Medical Prescription. Int. J. Environ. Res. Public Health 2019, 16, 942. [Google Scholar] [CrossRef] [Green Version]
- Bonaccio, M.; Di Castelnuovo, A.; Bonanni, A.; Costanzo, S.; De Lucia, F.; Persichillo, M.; Zito, F.; Donati, M.B.; De Gaetano, G.; Iacoviello, L. Decline of the Mediterranean diet at a time of economic crisis. Results from the Moli-sani study. Nutr. Metab. Cardiovasc. Dis. 2014, 24, 853–860. [Google Scholar] [CrossRef]
- Soltani, S.; Jayedi, A.; Shab-Bidar, S.; Becerra-Tomas, N.; Salas-Salvado, J. Adherence to the Mediterranean Diet in Relation to All-Cause Mortality: A Systematic Review and Dose-Response Meta-Analysis of Prospective Cohort Studies. Adv. Nutr. 2019, 10, 1029–1039. [Google Scholar] [CrossRef]
- Sofi, F.; Abbate, R.; Gensini, G.F.; Casini, A. Accruing evidence on benefits of adherence to the Mediterranean diet on health: An updated systematic review and meta-analysis. Am. J. Clin. Nutr. 2010, 92, 1189–1196. [Google Scholar] [CrossRef] [Green Version]
- Graffouillère, L.; Deschasaux, M.; Mariotti, F.; Neufcourt, L.; Shivappa, N.; Hébert, J.R.; Wirth, M.D.; Latino-Martel, P.; Hercberg, S.; Galan, P.; et al. Prospective association between the Dietary Inflammatory Index and mortality: Modulation by antioxidant supplementation in the SU.VI.MAX randomized controlled trial. Am. J. Clin. Nutr. 2016, 103, 878–885. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Hodge, A.M.; Bassett, J.K.; Dugué, P.A.; Shivappa, N.; Hébert, J.R.; Milne, R.L.; English, D.R.; Giles, G.G. Dietary inflammatory index or Mediterranean diet score as risk factors for total and cardiovascular mortality. Nutr. Metab. Cardiovasc. Dis. NMCD 2018, 28, 461–469. [Google Scholar] [CrossRef]
- Grosso, G.; Marventano, S.; Yang, J.; Micek, A.; Pajak, A.; Scalfi, L.; Galvano, F.; Kales, S.N. A comprehensive meta-analysis on evidence of Mediterranean diet and cardiovascular disease: Are individual components equal? Crit. Rev. Food Sci. Nutr. 2017, 57, 3218–3232. [Google Scholar] [CrossRef] [PubMed]
- The Institute for Health Metrics and Evaluation (IHME). Available online: http://www.healthdata.org/data-visualization/gbd-compare (accessed on 10 May 2020).
- WHO. Diet, Nutrition and Prevention of Chronic Diseases. Available online: https://apps.who.int/iris/bitstream/handle/10665/42665/WHO TRS 916.pdf (accessed on 10 October 2020).
- Kong, L.C.; Holmes, B.A.; Cotillard, A.; Habi-Rachedi, F.; Brazeilles, R.; Gougis, S.; Gausserès, N.; Cani, P.D.; Fellahi, S.; Bastard, J.P.; et al. Dietary patterns differently associate with inflammation and gut microbiota in overweight and obese subjects. PLoS ONE 2014, 9, e109434. [Google Scholar] [CrossRef]
- Wang, D.D.; Li, Y.; Bhupathiraju, S.N.; Rosner, B.A.; Sun, Q.; Giovannucci, E.L.; Rimm, E.B.; Manson, J.E.; Willett, W.C.; Stampfer, M.J.; et al. Fruit and Vegetable Intake and Mortality: Results from 2 Prospective Cohort Studies of US Men and Women and a Meta-Analysis of 26 Cohort Studies. Circulation 2021, 143, 1642–1654. [Google Scholar] [CrossRef]
- Leenders, M.; Boshuizen, H.C.; Ferrari, P.; Siersema, P.D.; Overvad, K.; Tjønneland, A.; Olsen, A.; Boutron-Ruault, M.C.; Dossus, L.; Dartois, L.; et al. Fruit and vegetable intake and cause-specific mortality in the EPIC study. Eur. J. Epidemiol. 2014, 29, 639–652. [Google Scholar] [CrossRef] [Green Version]
- Van Zutphen, M.; Boshuizen, H.C.; Kenkhuis, M.F.; Wesselink, E.; Geijsen, A.; de Wilt, J.H.W.; van Halteren, H.K.; Spillenaar Bilgen, E.J.; Keulen, E.T.P.; Janssen-Heijnen, M.L.G.; et al. Lifestyle after colorectal cancer diagnosis in relation to recurrence and all-cause mortality. Am. J. Clin. Nutr. 2021. [Google Scholar] [CrossRef]
- Winkels, R.M.; Heine-Bröring, R.C.; van Zutphen, M.; van Harten-Gerritsen, S.; Kok, D.E.; van Duijnhoven, F.J.; Kampman, E. The COLON study: Colorectal cancer: Longitudinal, Observational study on Nutritional and lifestyle factors that may influence colorectal tumour recurrence, survival and quality of life. BMC Cancer 2014, 14, 374. [Google Scholar] [CrossRef] [Green Version]
- Huang, L.; Chen, L.; Gui, Z.-X.; Liu, S.; Wei, Z.-J.; Xu, A.M. Preventable lifestyle and eating habits associated with gastric adenocarcinoma: A case-control study. J. Cancer 2020, 11, 1231–1239. [Google Scholar] [CrossRef] [Green Version]
- Barber, T.M.; Kabisch, S.; Pfeiffer, A.F.H.; Weickert, M.O. The Health Benefits of Dietary Fibre. Nutrients 2020, 12, 3209. [Google Scholar] [CrossRef]
- Burkitt, D.P.; Trowell, H.C. Dietary fibre and western diseases. Ir. Med. J. 1977, 70, 272–277. [Google Scholar] [PubMed]
- Stephen, A.M.; Champ, M.M.; Cloran, S.J.; Fleith, M.; van Lieshout, L.; Mejborn, H.; Burley, V.J. Dietary fibre in Europe: Current state of knowledge on definitions, sources, recommendations, intakes and relationships to health. Nutr. Res. Rev. 2017, 30, 149–190. [Google Scholar] [CrossRef] [PubMed]
- The InterAct Consortium. Dietary fibre and incidence of type 2 diabetes in eight European countries: The EPIC-InterAct Study and a meta-analysis of prospective studies. Diabetologia 2015, 58, 1394–1408. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Park, Y.; Subar, A.F.; Hollenbeck, A.; Schatzkin, A. Dietary fiber intake and mortality in the NIH-AARP diet and health study. Arch. Intern. Med. 2011, 171, 1061–1068. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Slavin, J. Fiber and prebiotics: Mechanisms and health benefits. Nutrients 2013, 5, 1417–1435. [Google Scholar] [CrossRef] [Green Version]
- Dahl, W.J.; Agro, N.C.; Eliasson, Å.M.; Mialki, K.L.; Olivera, J.D.; Rusch, C.T.; Young, C.N. Health Benefits of Fiber Fermentation. J. Am. Coll. Nutr. 2017, 36, 127–136. [Google Scholar] [CrossRef] [PubMed]
- Rauber, F.; Steele, E.M.; Louzada, M.; Millett, C.; Monteiro, C.A.; Levy, R.B. Ultra-processed food consumption and indicators of obesity in the United Kingdom population (2008–2016). PLoS ONE 2020, 15, e0232676. [Google Scholar] [CrossRef] [PubMed]
- Hemler, E.C.; Hu, F.B. Plant-Based Diets for Personal, Population, and Planetary Health. Adv. Nutr. 2019, 10, S275–S283. [Google Scholar] [CrossRef]
- Fresán, U.; Martínez-Gonzalez, M.A.; Sabaté, J.; Bes-Rastrollo, M. The Mediterranean diet, an environmentally friendly option: Evidence from the Seguimiento Universidad de Navarra (SUN) cohort. Public Health Nutr. 2018, 21, 1573–1582. [Google Scholar] [CrossRef] [Green Version]
- Fresán, U.; Martínez-González, M.A.; Segovia-Siapco, G.; Sabaté, J.; Bes-Rastrollo, M. A three-dimensional dietary index (nutritional quality, environment and price) and reduced mortality: The “Seguimiento Universidad de Navarra” cohort. Prev. Med. 2020, 137, 106124. [Google Scholar] [CrossRef] [PubMed]
- Abbasalizad Farhangi, M.; Ataie-Jafari, A.; Najafi, M.; Sarami Foroushani, G.; Mohajeri Tehrani, M.R.; Jahangiry, L. Gender Differences in Major Dietary Patterns and Their Relationship with Cardio-Metabolic Risk Factors in a Year before Coronary Artery Bypass Grafting (CABG) Surgery Period. Arch. Iran. Med. 2016, 19, 470–479. [Google Scholar] [PubMed]
- Lin, L.Y.; Hsu, C.Y.; Lee, H.A.; Tinkov, A.A.; Skalny, A.V.; Wang, W.H.; Chao, J.C. Gender difference in the association of dietary patterns and metabolic parameters with obesity in young and middle-aged adults with dyslipidemia and abnormal fasting plasma glucose in Taiwan. Nutr. J. 2019, 18, 75. [Google Scholar] [CrossRef] [PubMed]
- Gough, B.; Conner, M.T. Barriers to healthy eating amongst men: A qualitative analysis. Soc. Sci Med. 2006, 62, 387–395. [Google Scholar] [CrossRef] [PubMed]
- Rothman, K.J. Causes. Am. J. Epidemiol. 1976, 104, 587–592. [Google Scholar] [CrossRef]
- Courtenay, W.H. Constructions of masculinity and their influence on men’s well-being: A theory of gender and health. Soc. Sci. Med. 2000, 50, 1385–1401. [Google Scholar] [CrossRef]
- Roos, G.; Prättälä, R.; Koski, K. Men, masculinity and food: Interviews with Finnish carpenters and engineers. Appetite 2001, 37, 47–56. [Google Scholar] [CrossRef] [Green Version]
- Kołodziej, H.; Lopuszańska, M.; Jankowska, E.A. Decrease in sex difference in premature mortality during system transformation in Poland. J. Biosoc. Sci. 2008, 40, 297–312. [Google Scholar] [CrossRef] [PubMed]
- Zhao, M.; Veeranki, S.P.; Magnussen, C.G.; Xi, B. Recommended physical activity and all cause and cause specific mortality in US adults: Prospective cohort study. BMJ 2020, 370, m2031. [Google Scholar] [CrossRef] [PubMed]
Scoring Criteria of Modified WCRF/AICR Score | % of Participants with Maximum Component Scores | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Components | Age Class (Years) | Sex | |||||||||
0 # | 0.5 ǂ | 1 § | <40 n = 1322 | 41–49 n = 1024 | 50–59 n = 996 | 60–69 n = 792 | ≥70 n = 732 | Female n = 2352 | Male n = 2514 | Total n = 4866 | |
Energy dense foods (kcal/100g) | >175 | 125–175 | ≤125 | 30.83 | 27.14 | 28.84 | 23.63 | 18.61 | 33.16 | 20.64 | 26.70 |
Fast food intake (g/day) | >42 | 18–42 | <18 | 1.25 | 1.61 | 5.61 | 14.30 | 20.69 | 7.70 | 6.76 | 7.21 |
Sugary drinks intake (g/day) | >250 | ≤250 | 0 | 6.78 | 14.53 | 24.73 | 36.53 | 44.44 | 23.04 | 21.93 | 22.47 |
Fruits and Vegetables (g) | <200 | 200–400 | ≥400 | 63.20 | 71.44 | 71.16 | 73.18 | 74.72 | 69.77 | 69.93 | 69.85 |
Cereals. Whole grain bread and Legumes (g) | <24 | 24–64 | ≥64 | 27.21 | 19.88 | 20.57 | 12.64 | 10.83 | 20.66 | 18.54 | 19.56 |
White bread. pasta and rice (g/day) | ≥144 | 91–144 | <91 | 39.68 | 43.69 | 54.92 | 57.60 | 58.75 | 59.86 | 39.58 | 49.38 |
* Red (R) and processed meat (P) | R+P ≥ 500 or P ≥ 50 | R+P < 500 and P 3–50 | R+P < 500 and P < 3 | 13.50 | 18.26 | 24.41 | 37.55 | 47.22 | 29.21 | 22.24 | 25.61 |
** Cold meat (g/day) | >22 | 7–22 | ≤7 | 14.97 | 19.98 | 31.79 | 48.02 | 59.03 | 35.25 | 27.68 | 31.34 |
Alcohol intake (g/day) | ≥20 | 10–20 | ≤10 | 73.01 | 62.97 | 54.23 | 53.64 | 60.56 | 80.23 | 45.11 | 62.08 |
Sodium (g/day) | ≥3 | 2.4–3 | <2.4 | 62.68 | 71.36 | 79.97 | 84.36 | 88.34 | 79.17 | 71.04 | 74.98 |
*** BMI (kg/m2) | <18.5 and ≥30 | 25–30 | 18.5–24.9 | 52.80 | 36.73 | 23.33 | 16.86 | 18.33 | 39.33 | 26.09 | 32.49 |
All ¥ | Modified WCRF/AICR Score Categories | ||||
---|---|---|---|---|---|
0–11 | ≤5 | 5.5–7 | >7 | p-Value | |
n *** | 4866 | 771 | 2949 | 1146 | |
Age at Enrollment (years) * | 51.46 (15.81) | 48.90 (14.19) | 50.92 (15.73) | 54.56 (16.57) | <0.001 |
Age (categorical. years) *** | <0.001 | ||||
<40 | 1356 (27.9) | 227 (29.4) | 869 (29.5) | 260 (22.7) | |
40–49 | 991 (20.4) | 199 (25.8) | 592 (20.1) | 200 (17.5) | |
50–59 | 1016 (20.9) | 176 (22.8) | 608 (20.6) | 232 (20.2) | |
60–69 | 784 (16.1) | 96 (12.5) | 475 (16.1) | 213 (18.6) | |
≥70 | 719 (14.8) | 73 (9.5) | 405 (13.7) | 241 (21.0) | |
Sex *** | <0.001 | ||||
Female | 2352 (48.3) | 147 (19.1) | 1369 (46.4) | 836 (72.9) | |
Male | 2514 (51.7) | 624 (80.9) | 1580 (53.6) | 310 (27.1) | |
Marital Status *** | <0.001 | ||||
Single | 764 (15.7) | 114 (14.8) | 479 (16.2) | 171 (14.9) | |
Married/Coupled | 3673 (75.5) | 609 (79.0) | 2231 (75.7) | 833 (72.7) | |
Separated/Divorced | 117 (2.4) | 19 (2.5) | 68 (2.3) | 30 (2.6) | |
Widower | 312 (6.4) | 29 (3.8) | 171 (5.8) | 112 (9.8) | |
Education *** | 0.044 | ||||
Primary School | 1332 (27.4) | 186 (24.1) | 807 (27.4) | 339 (29.6) | |
Secondary School | 1487 (30.6) | 264 (34.2) | 893 (30.3) | 330 (28.8) | |
High School | 1385 (28.5) | 224 (29.1) | 833 (28.2) | 328 (28.6) | |
Graduated | 493 (10.1) | 70 (9.1) | 321 (10.9) | 102 (8.9) | |
Illiterate | 169 (3.5) | 27 (3.5) | 95 (3.2) | 47 (4.1) | |
Job *** | <0.001 | ||||
Managers and Professionals | 287 (5.9) | 63 (8.2) | 176 (6.0) | 48 (4.2) | |
Craft, Agricultural and Sales Workers | 1279 (26.3) | 227 (29.4) | 765 (25.9) | 287 (25.0) | |
Elementary Occupations | 1038 (21.3) | 199 (25.8) | 671 (22.8) | 168 (14.7) | |
Housewife | 634 (13.0) | 55 (7.1) | 361 (12.2) | 218 (19.0) | |
Pensioneers | 1372 (28.2) | 196 (25.4) | 815 (27.6) | 361 (31.5) | |
Jobless | 254 (5.2) | 31 (4.0) | 160 (5.4) | 63 (5.5) | |
No Information | 2 (<1) | 0 (0.0) | 1 (<1) | 1 (0.1) | |
DBP (mmHg) * | 124.10 (17.81) | 123.58 (16.70) | 123.69 (17.98) | 125.52 (18.06) | 0.010 |
SBP (mmHg) * | 76.76 (9.74) | 77.50 (10.15) | 76.38 (9.74) | 77.24 (9.41) | 0.003 |
Weight (kg) * | 73.06 (14.97) | 82.12 (15.18) | 73.57 (14.63) | 65.63 (11.62) | <0.001 |
BMI (kg/m2) * | 27.51 (5.15) | 29.55 (5.16) | 27.65 (5.23) | 25.77 (4.29) | <0.001 |
Kcal days | 2182.34 (825.13) | 2843.35 (998.83) | 2200.11 (720.08) | 1689.64 (588.49) | <0.001 |
Triglycerides (mmol/L) * | 1.38 (0.98) | 1.54 (1.13) | 1.39 (0.99) | 1.23 (0.81) | <0.001 |
Total Cholesterol (mmol/L) * | 5.10 (1.01) | 5.18 (1.00) | 5.08 (1.00) | 5.09 (1.06) | 0.064 |
HDL (mmol/L) * | 1.33 (0.35) | 1.26 (0.32) | 1.33 (0.36) | 1.41 (0.36) | <0.001 |
LDL (mmol/L) * | 3.14 (0.87) | 3.22 (0.84) | 3.13 (0.86) | 3.13 (0.92) | 0.038 |
Glucose (mmol/L) * | 5.87 (1.40) | 6.02 (1.26) | 5.85 (1.32) | 5.83 (1.65) | 0.005 |
GPT (μkat/L) * | 0.28 (0.22) | 0.32 (0.22) | 0.28 (0.21) | 0.26 (0.25) | <0.001 |
GGT (μkat/L) * | 0.25 (0.25) | 0.31 (0.30) | 0.25 (0.24) | 0.22 (0.24) | <0.001 |
Smoke *** | <0.001 | ||||
Never/Former | 4029 (82.8) | 603 (78.2) | 2425 (82.2) | 1001 (87.3) | |
Current | 837 (17.2) | 168 (21.8) | 524 (17.8) | 145 (12.7) | |
Observation time ** | 14.86 (14.20. 15.10) | 14.89 (14.50. 15.20) | 14.86 (14.20. 15.14) | 14.80 (14.17. 14.97) | <0.001 |
Age at Death (years) ** | 65.74 (53.51. 77.17) | 62.38 (53.31. 72.97) | 64.47 (52.91. 76.68) | 70.06 (55.90. 81.11) | <0.001 |
Status *** | 0.008 | ||||
Alive and/or Censored | 4132 (84.9) | 675 (87.5) | 2512 (85.2) | 945 (82.5) | |
Dead | 734 (15.1) | 96 (12.5) | 437 (14.8) | 201 (17.5) | |
Cause of Death *** | 0.11 | ||||
Alive and/or Censored | 4132 (84.9) | 675 (87.5) | 2512 (85.2) | 945 (82.5) | |
DSD-related mortality | 131 (2.7) | 20 (2.6) | 76 (2.6) | 35 (3.1) | |
CVD-related mortality | 210 (4.3) | 25 (3.2) | 126 (4.3) | 59 (5.1) | |
CR-related mortality | 128 (2.6) | 21 (2.7) | 77 (2.6) | 30 (2.6) | |
Other-Cause mortality | 265 (5.4) | 30 (3.9) | 158 (5.4) | 77 (6.7) | |
Diabetes *** | 0.43 | ||||
No | 4542 (93.3) | 718 (93.1) | 2763 (93.7) | 1061 (92.6) | |
Yes | 324 (6.7) | 53 (6.9) | 186 (6.3) | 85 (7.4) | |
Dyslipidemia *** | 0.011 | ||||
No | 4059 (83.4) | 619 (80.3) | 2460 (83.4) | 980 (85.5) | |
Yes | 807 (16.6) | 152 (19.7) | 489 (16.6) | 166 (14.5) | |
Hypertension *** | 0.91 | ||||
No | 3662 (75.3) | 581 (75.4) | 2224 (75.4) | 857 (74.8) | |
Yes | 1204 (24.7) | 190 (24.6) | 725 (24.6) | 289 (25.2) |
mWCRF/AICR Score Categories | mWCRF/AICR (Continuos) | |||||
---|---|---|---|---|---|---|
5.5–7 | >7 | |||||
HR | 95% CI | HR | 95% CI | HR | 95% CI | |
All-Cause mortality | ||||||
Whole Sample | 0.94 | 0.74; 1.19 | 0.75 | 0.57; 1.00 | 0.92 * | 0.86; 0.97 |
Female | 1.39 | 0.77; 2.51 | 1.38 | 0.75; 2.52 | 0.95 | 0.86; 1.05 |
Male | 0.86 | 0.65; 1.13 | 0.56 * | 0.39; 0.82 | 0.91 * | 0.84; 0.98 |
SHR | 95% CI | SHR | 95% CI | SHR | 95% CI | |
DSD-related mortality | ||||||
Whole Sample | 0.82 | 0.50; 1.36 | 0.72 | 0.38; 1.37 | 0.98 | 0.86; 1.13 |
Female | 1.59 | 0.35; 7.09 | 2.62 | 0.62; 11.00 | 1.20 | 0.92; 1.58 |
Male | 0.79 | 0.46; 1.36 | 0.38 * | 0.15; 0.97 | 0.94 | 0.80; 1.10 |
CVD-related mortality | ||||||
Whole Sample | 1.17 | 0.72; 1.90 | 1.19 | 0.69; 2.07 | 0.99 | 0.88; 1.12 |
Female | 3.66 | 0.55; 24.3 | 4.14 | 0.61; 28.29 | 1.07 | 0.93; 1.24 |
Male | 1.10 | 0.65; 1.86 | 1.01 | 0.51; 1.98 | 0.90 | 0.75; 1.08 |
Cancer-related mortality | ||||||
Whole Sample | 0.76 | 0.46; 1.25 | 0.64 | 0.36; 1.14 | 0.89 | 0.78; 1.01 |
Female | 2.36 | 0.52; 10.75 | 1.91 | 0.42; 8.68 | 0.93 | 0.76; 1.13 |
Male | 0.54 * | 0.30; 0.95 | 0.43 * | 0.19; 0.97 | 0.83 * | 0.70; 0.99 |
Other-Cause mortality | ||||||
Whole Sample | 1.11 | 0.72; 1.72 | 0.87 | 0.52; 1.44 | 0.90 * | 0.82; 0.99 |
Female | 0.54 | 0.27; 1.08 | 0.43 * | 0.21; 0.88 | 0.85 * | 0.73; 0.99 |
Male | 1.39 | 0.81; 2.39 | 1.12 | 0.58; 2.15 | 0.95 | 0.84; 1.08 |
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Mirizzi, A.; Aballay, L.R.; Misciagna, G.; Caruso, M.G.; Bonfiglio, C.; Sorino, P.; Bianco, A.; Campanella, A.; Franco, I.; Curci, R.; et al. Modified WCRF/AICR Score and All-Cause, Digestive System, Cardiovascular, Cancer and Other-Cause-Related Mortality: A Competing Risk Analysis of Two Cohort Studies Conducted in Southern Italy. Nutrients 2021, 13, 4002. https://doi.org/10.3390/nu13114002
Mirizzi A, Aballay LR, Misciagna G, Caruso MG, Bonfiglio C, Sorino P, Bianco A, Campanella A, Franco I, Curci R, et al. Modified WCRF/AICR Score and All-Cause, Digestive System, Cardiovascular, Cancer and Other-Cause-Related Mortality: A Competing Risk Analysis of Two Cohort Studies Conducted in Southern Italy. Nutrients. 2021; 13(11):4002. https://doi.org/10.3390/nu13114002
Chicago/Turabian StyleMirizzi, Antonella, Laura R. Aballay, Giovanni Misciagna, Maria G. Caruso, Caterina Bonfiglio, Paolo Sorino, Antonella Bianco, Angelo Campanella, Isabella Franco, Ritanna Curci, and et al. 2021. "Modified WCRF/AICR Score and All-Cause, Digestive System, Cardiovascular, Cancer and Other-Cause-Related Mortality: A Competing Risk Analysis of Two Cohort Studies Conducted in Southern Italy" Nutrients 13, no. 11: 4002. https://doi.org/10.3390/nu13114002