Franco Berrino - Il Codice Europeo contro il cancro e le Istituzioni Sanitarie
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Intervento alla sessione ALLEANZE PER ALIMENTAZIONE E SALUTE del 33° Convegno di Agricoltura Biodinamica del 21 febbraio 2015 presso l'Università Bocconi di Milano. Importantissimo contributo che rende edotti della scarsa responsabilità delle istituzioni verso le direttive anti cancro legate all'alimentazione.
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Franco Berrino - Il Codice Europeo contro il cancro e le Istituzioni Sanitarie
- 1. ECAC European Code Against Cancer Oct 2014
- 2. Stime IARC/ WHO : Europa 2012 3.442.000 nuovi casi di tumore maligno • Mammella 464.000 13,5% • Intestino 447.000 13,0% • Prostata 417.000 12,1% • Polmone 410.000 11,9% • Vescica 151.000 4,4% • Stomaco 140.000 4,1% • Rene 115.000 3,3% • Pancreas 104.000 3,0% • Melanoma 100.000 2,9%
- 3. ECAC: Codice Europeo Contro il Cancro 12 modi per ridurre il vostro rischio di cancro • Tabacco • Peso corporeo • Esercizio fisico • Dieta • Alcol • Sole • Cancerogeni occupazionali • Radon • Allattamento al seno • Ormoni per menopausa • Vaccinazioni • Diagnosi precoce
- 4. ECAC: raccomandazioni nutrizionali • Impegnatevi a mantenere un peso corporeo sano. • Fate quotidianamente esercizio fisico. • Consumate abbondantemente cereali integrali, legumi, verdure e frutta. • Limitate i cibi ricchi di zucchero e grassi. • Evitate le bevande zuccherate. • Evitate le carni conservate. • Limitate le carni rosse. • Limitate i cibi ricchi di sale. • Se consumate bevande alcoliche, di qualunque tipo, limitatene la quantità.
- 5. 0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1 1 2 3 4 5 cancro cuore polmoni altro 0.8 (0.7-0.9) EPIC (Vergnaud AC 2013 Am j Clin Nutr 97:1107) Mortalità inEPIC (Vergnaud AC 2013 Am j Clin Nutr 97:1107) Mortalità in funzione della compliace alle raccomandazioni del WCRF/ECACfunzione della compliace alle raccomandazioni del WCRF/ECAC Ptrend<0.0001 x tutte le cause Mortalità x
- 6. Codice Europeo 1a Traduzione italiana Contro il Cancro (Ministero della Salute) ▪ Consumate abbondantemente cereali integrali, legumi,verdure e frutta. ▪ Limitate i cibi molto calorici (ricchi di zucchero e grassi). ▪ Evitate le bevande zuccherate. ▪ Evitate le carni conservate. ▪ Limitate le carni rosse. ▪ Limitate i cibi ricchi di sale. ▪ Preferire riso, ???????????? legumi, verdure e frutta. . ▪ Limitate i cibi molto calorici (ricchi di zucchero e grassi). ▪ Evitate le bevande zuccherate. ▪ ?????????????????? ▪ Limitate le carni rosse. ▪ Limitate i cibi ricchi di sale. Il codice europeo e le istituzioni
- 7. - Consumate abbondantemente cereali integrali, legumi, verdure e frutta. - Limitate i cibi ricchi di zucchero e grassi. - Evitate le bevande zuccherate. Evitate le carni conservate. Limitate le carni rosse. - Limitate i cibi ricchi di sale.
- 8. EPIC-2005: Rischio relativo di cancro colorettale in funzione del consumo quotidiano di carne: stime calibrate e non calibrate 1 1,4 1,8 2,2 2,6 3 0 50 100 150 200 g/day Hazard Ratio (uncalibrated data) (calibrated data)
- 9. - Consumate abbondantemente cereali integrali, legumi, verdure e frutta. - Limitate i cibi ricchi di zucchero e grassi. - Evitate le bevande zuccherate. - Evitate le carni conservate. - Limitate le carni rosse. - Limitate i cibi ricchi di sale.
- 10. EPIC: rischio di cancro dell’intestino in funzione del consumo di fibre 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1 1,1 10 15 20 25 30 35 40 45 Calibra ta (origina le ) Lim ite inf. Lim ite sup.
- 11. EPIC: rischio di morire secondo il consumo di fibre vegetali. Chuang S et al. Am J Clin Nutr 2012;96:164-174 grammi D. Burkitt
- 12. EPIC: A parità di consumo di verdure la varietà riduce il cancro polmonare 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1° quartile 2° 3° 4° Quartile Tutti Fumatori Ptrend = 0,02 Büchner FL 2010 CEBP 19:2278
- 13. β-carotene e cancro della mammella: studi su questionari e studi basati sulla concentrazione nel plasma Aune D et al. Am J Clin Nutr 2012;96:356-373 ©2012 by American Society for Nutrition
- 14. - Consumate abbondantemente cereali integrali, legumi, verdure e frutta. - Limitate i cibi molto calorici (ricchi di zucchero e grassi). - Evitate le bevande zuccherate. - Evitate le carni conservate. - Limitate le carni rosse. - Limitate i cibi ricchi di sale.
- 16. 0 0,5 1 1,5 2 2,5 1° 2° 3° 4° Quartile premenopausal postmenopausal >55y at diagnosis ORDET (Sieri, Berrino et al. 2011): 356 casi incidenti di cancro mammarioORDET (Sieri, Berrino et al. 2011): 356 casi incidenti di cancro mammario Rischio di cancro mammario in funzione della glicemiaRischio di cancro mammario in funzione della glicemia *P<0.05 Fully adjusted models HR =2.2 (1.3- 3.2) * * * *
- 17. 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 1° (-86) 2° (87-92) 3° (93 98) 4°(99-107) 5° 108+ RR Rischio di recidiva del carcinoma mammario in funzione della concentrazione plasmatica di glucosio Contiero, Berrino 2013 BCRT (INT) Quintili di glicemia 1.6(1.0-2.5) 1.6(1.0-2.5) 1.6(1.1-2.6) 1.8 (1.1-1.9)
- 18. WHO open public consultation on draft sugars guideline (2014) • WHO’s current recommendation, from 2002, is that sugars should make up less than 10% of total energy intake per day. • A reduction to below 5% of total energy would have additional benefits. • 5% is equivalent to 25 g (6 teaspoons) for an adult of normal body mass index (BMI) • Much sugars consumed today are hidden in processed foods not usually seen as sweets
- 19. Dalla risposta del sottosegretario alla salute, Vito De Filippo all’interrogazione parlamentare sui motivi per cui l’Italia si sia mossa “in assoluta solitudine” contro le indicazioni dell’OMS sulla riduzione del consumo di zucchero. • A parere del Ministero della Salute Italiano, le raccomandazioni delle linee guida (OMS) sono eccessivamente restrittive… • Si deve tener conto che lo zucchero costituisce un nutriente essenziale (!) e che, come tutti gli altri, va assunto in quantità adeguate • La riduzione al 5% della quota delle calorie da zuccheri semplici rappresenta un obiettivo del cui beneficio non ci sono evidenze scientifiche.
- 20. Fig 7 Association between free sugars intakes and measures of body fatness in children. Lisa Te Morenga et al. BMJ 2013;346:bmj.e7492 ©2013 by British Medical Journal Publishing Group
- 21. Fig 4 Effect of increasing free sugars on measures of body fatness in adults. Lisa Te Morenga et al. BMJ 2013;346:bmj.e7492 ©2013 by British Medical Journal Publishing Group
- 22. Fig 5 Isoenergetic exchanges of free sugars with other carbohydrates or other macronutrient sources. Lisa Te Morenga et al. BMJ 2013;346:bmj.e7492 ©2013 by British Medical Journal Publishing Group
- 23. Dietary sugars and cardiometabolic risk: meta-analyses of RCT Te Morenga LA 2014 Am J Clin Nutr 100:65 Il consumo di zucchero è associato ad aumento della pressione sanguigna aumento dei livelli di trigliceridi aumento dei livelli di colesterolo Indipendentemente dall’aumento delle calorie totali e dall’aumento di peso
- 24. EPIC-Norfolk : rischio di diventare obesi in funzione della concentrazione di saccarosio nelle urine e di Vitamina C nel plasma Bingham S 2007 CEBP 16:1651 1.8 (1.2-2.8); Ptrend 0.016)
- 25. Cancro del colon nelle coorti di Harvard (Fuchs M 2014 PLoS) Rischio di recidiva in funzione del consumo di soft drink
- 26. Le 3 pubblicità nei villaggi di montagna del Nepal Malboro Coca-Cola Kit-Kat
- 27. Nayapul, NEPAL
- 29. Sindrome metabolica definita dalla presenza di 3 dei seguenti fattori Circonferenza vita > 85 cm (Femmine) > 100 cm (Maschi) Pressione arteriosa > 85 / 130 Glicemia > 100 mg/100mL Trigliceridemia > 150 mg/100mL Colesterolo HDL < 50 mg/100mL Resistenza insulinica, infiammazione cronica, stress ossidativo, stato protrombotico, endotelite
- 30. Malattie associate alla SM Diabete Malattie Cardiovascolari Patologie oculari BPCO Cancro: Sindrome Alzheimer metabolica Psoriasi Osteoartrite, AR Calcolosi colecistica Iperplasia prostatica Steatosi non alcolica→ Cirrosi Fegato Colon Mammella Prostata Endometrio Pancreas Rene
- 31. DIANA-5: METASTASI A DISTANZA IN FUNZIONE DEL NUMERO DI FATTORI DI SINDROME METABOLICA Berrino 2014 BCRT 147:159, basati su 89 metastasi 1.36 (0.8-2.4) 2.43 (1.3-.4.7) RR
- 32. Fattori di rischio nutrizionali per la SM Bevande zuccherate Bevande zero Nettleton 2009 Cibi ad alto Indice Glicemico Bevande alcoliche McAuley J Lip Res 2006 Davies JAMA 2002 Grassi saturi Proteine in eccesso Riccardi Clin Nutr 2004 Tremblay 2007 Acidi grassi trans Sindrome Eccesso di sale Hunter Lipids 2006 metabolica Townsend Clin Sci 2007 Acidi grassi ω-3 Dieta mediterranea Carpentier AJCN 2006 Esposito JAMA 2004 Acidi grassi monoinsaturi Attività fisica Pérez-Jiménez Diabetologia 2001 Barnard 2003
- 33. MeMeMe 2000 persone (55-80 anni) con sindrome metabolica Raccomandazioni alimentari per tutti Prelievo di sangue basale R METFORMINA PLACEBO R R SI (500) NO (500) SI (500) NO (500) sorveglianza per 5 anni (diabete, infarto, ictus, cancro, alzheimer,…) Eventuali esclusioni per insufficienza renale CORSI DI CUCINA ESERCIZIO FISICO
- 34. EPIC: rischio di diventare sovrappeso (per i normopeso) od obesi (per i sovrappeso) in funzione del consumo proteico (Vergnaud 2012) 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 <14% 14-16 16-18 18-20 20-22 >22% normopeso sovrappeso al reclutamento Introito di proteine in percentuale delle calorie totali P < 0.05 Ptrend <0.0001
- 35. Consumo settimanale di alimenti proteici nel 2006 e raccomandazioni ministeriali PORZIONI ALLA SETTIMANA consumate raccomandate Carni fresche 5,7 3-4 Salumi 3,8 1-2 Pesce 2,1 2-3 Uova 2,4 2-4 Legumi 0,8 2-3 Leclercq et al 2009
- 36. Il Codice Europeo per la prevenzione del Cancro
- 37. • Mazzaffarian NEJM 2011
- 38. Fattori alimentari che stimolano la proliferazione cellulare AMPK mTOR FATTORI di CRESCITA GLICEMIA INSULINA INFIAMMAZIONE POLIAMINE RADICALI LIBERI Eccesso calorico Carico glicemico dolcificanti Frutta Carni Latte Integratori antiossidanti
- 40. Aderenza alle raccomandazioni del WCRF e rischio di cancro mammario postmenopausale Hasert 2013 CEBP Vital cohort 0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1 0 1 2 3 4 5+ RR 0.4 (0.2-06) 0.5 (03-08) 0.6 (0.4-0.8) 0.7 (0.5-1.0) Casi/coorte 28/571 166/5025 300/10324 239/8616 125/4405 41/1856
- 41. Diminuzione del rischio di sviluppare un tumore per ogni punto in più di adesione alle raccomandazioni del WCRF/AICR ( 0–6 punti per gli uomini e 0–7 per le donne). Romaguera D et al. Am J Clin Nutr 2012;96:150-163
Editor's Notes
- HRs of death according to total dietary fiber intake. The HRs were estimated by using a Cox proportional hazard model. The solid line indicates HRs, and the dashed lines indicate 95% CIs derived from a restricted cubic spline regression, with knots placed at the medians of each quintile of the distribution of total dietary fiber intake. The reference point for total dietary fiber intake is 25 g/d. Age was used as the primary time variable in the Cox proportional hazard models. Age at death or at censoring date was used as the time variable for the end of the study. The models excluded the first 2 y of follow-up and stratified by age at recruitment, sex, and center and adjusted for education (none or primary school completed, technical or professional school, secondary school, longer education, and not specified), smoking (never; current 1–15, 16–25, or 26 cigarettes/d; former quit ≤10, 11–20, or ≥20 y; current pipe or cigar occasional, current/former missing, or unknown), alcohol consumption (never or former; current ≤6, &gt;6–18, &gt;18–30, &gt;30–60, or &gt;60 g/d; or missing), BMI (in kg/m2: &lt;18.5, 18.5–24.9, 25–29.9, or ≥30), physical activity (based on the Cambridge/Bilthoven Physical Activity Index: inactive, moderately inactive, moderately active, active, or missing), and total energy intake (kcal/d).
- HRs and 95% CIs of total death and cause-specific deaths per 5-g/d increase in fiber intake in men (A) and women (B). The HRs were estimated by using a Cox proportional hazard model. Age was used as the primary time variable in the Cox proportional hazard models. Age at death or at censoring date was used as time variable of end of the study. The models excluded the first 2 y of follow-up and stratified by age at recruitment, sex, and center and adjusted for education (none or primary school completed, technical or professional school, secondary school, longer education, and not specified), smoking (never; current 1–15, 16–25, or 26 cigarettes/d; former quit ≤10, 11–20, or ≥20 y; current pipe or cigar occasional, current/former missing, or unknown), alcohol consumption (never or former; current ≤6, &gt;6–18, &gt;18–30, &gt;30–60, or &gt;60 g/d; or missing), BMI (in kg/m2: &lt;18.5, 18.5–24.9, 25–29.9, or ≥30), physical activity (based on the Cambridge/Bilthoven Physical Activity Index: inactive, moderately inactive, moderately active, active, or missing), total energy intake (kcal/d), other sources of fiber intake, and ever use of menopausal hormone therapy for women. aFurther adjusted for ever use of menopausal hormone therapy. The x axis refers to HRs.
- HRs and 95% CIs of total death and cause-specific deaths per 5-g/d increase in fiber intake in men (A) and women (B). The HRs were estimated by using a Cox proportional hazard model. Age was used as the primary time variable in the Cox proportional hazard models. Age at death or at censoring date was used as time variable of end of the study. The models excluded the first 2 y of follow-up and stratified by age at recruitment, sex, and center and adjusted for education (none or primary school completed, technical or professional school, secondary school, longer education, and not specified), smoking (never; current 1–15, 16–25, or 26 cigarettes/d; former quit ≤10, 11–20, or ≥20 y; current pipe or cigar occasional, current/former missing, or unknown), alcohol consumption (never or former; current ≤6, &gt;6–18, &gt;18–30, &gt;30–60, or &gt;60 g/d; or missing), BMI (in kg/m2: &lt;18.5, 18.5–24.9, 25–29.9, or ≥30), physical activity (based on the Cambridge/Bilthoven Physical Activity Index: inactive, moderately inactive, moderately active, active, or missing), total energy intake (kcal/d), other sources of fiber intake, and ever use of menopausal hormone therapy for women. aFurther adjusted for ever use of menopausal hormone therapy. The x axis refers to HRs.
- HRs and 95% CIs of total death and cause-specific deaths per 5-g/d increase in fiber intake in men (A) and women (B). The HRs were estimated by using a Cox proportional hazard model. Age was used as the primary time variable in the Cox proportional hazard models. Age at death or at censoring date was used as time variable of end of the study. The models excluded the first 2 y of follow-up and stratified by age at recruitment, sex, and center and adjusted for education (none or primary school completed, technical or professional school, secondary school, longer education, and not specified), smoking (never; current 1–15, 16–25, or 26 cigarettes/d; former quit ≤10, 11–20, or ≥20 y; current pipe or cigar occasional, current/former missing, or unknown), alcohol consumption (never or former; current ≤6, &gt;6–18, &gt;18–30, &gt;30–60, or &gt;60 g/d; or missing), BMI (in kg/m2: &lt;18.5, 18.5–24.9, 25–29.9, or ≥30), physical activity (based on the Cambridge/Bilthoven Physical Activity Index: inactive, moderately inactive, moderately active, active, or missing), total energy intake (kcal/d), other sources of fiber intake, and ever use of menopausal hormone therapy for women. aFurther adjusted for ever use of menopausal hormone therapy. The x axis refers to HRs.
- Dietary and blood concentrations of total carotenoids and breast cancer risk (dose-response analysis). Summary estimates were calculated by using a random-effects model.
- Dietary and blood concentrations of β-carotene and breast cancer risk (dose-response analysis). Summary estimates were calculated by using a random-effects model. MONICA, Monitoring of Trends in Cardiovascular Disease; MSP, Mammary Screening Project; VIP, Västerbotten Intervention Project.
- Dietary and blood concentrations of α-carotene and breast cancer risk (dose-response analysis). Summary estimates were calculated by using a random-effects model. MONICA, Monitoring of Trends in Cardiovascular Disease; MSP, Mammary Screening Project; VIP, Västerbotten Intervention Project.
- Blood concentrations of lutein and breast cancer risk (dose-response analysis). Summary estimates were calculated by using a random-effects model. MONICA, Monitoring of Trends in Cardiovascular Disease; MSP, Mammary Screening Project; VIP, Västerbotten Intervention Project.
- Fig 7 Association between free sugars intakes and measures of body fatness in children. Pooled estimates for odd ratios for incident overweight or obesity in children consuming one or more servings of sugar sweetened beverages per day at baseline compared with children who consumed none or very little at baseline. Overall estimate shows higher odds of overweight or obesity at follow-up in those who consumed one or more servings of sugar sweetened beverages at baseline. Data are expressed as odds ratio (95% confidence interval), using generic inverse variance models with random effects
- Fig 3 Effect of reducing intake of free sugars on measures of body fatness in adults. Pooled effects for difference in body weight (kg) shown for studies comparing reduced intakes (lower sugars) with usual or increased intakes (higher sugars). Overall effect shows increased body weight after intervention in the higher sugars groups. Data are expressed as weighted mean difference (95% confidence interval), using generic inverse variance models with random effects
- Fig 4 Effect of increasing free sugars on measures of body fatness in adults. Pooled effects for difference in body weight (kg) shown for studies comparing increased intake (higher sugars) with usual intake (lower sugars). Overall effect shows increased body weight after intervention in the higher sugars groups. Data are expressed as weighted mean difference (95% confidence interval), using generic inverse variance models with random effects
- Fig 5 Isoenergetic exchanges of free sugars with other carbohydrates or other macronutrient sources. Pooled effects for difference in body weight (kg) for studies comparing isoenergetic exchange of free sugars (higher sugars) with other carbohydrates (lower sugars). Data are expressed as weighted mean difference (95% confidence interval), using generic inverse variance models with random effects
- Figure 3. Relative risk of laryngeal cancer for tobacco smoking and alcohol drinking in a study from Southern Europe. Ref, reference category (risk = 1).
- Survival to age 70 and beyond: effect of smoking in male British doctors Here are Richard Doll’s main findings for smoking and death in British doctors. This graph shows the chances of a 35-year-old surviving to age 70 and beyond. [CLICK] Here are the non-smokers. 81% were still alive at age 70; that means that only 19% had died in middle age. [CLICK] Now here are the cigarette smokers. Only 58% were still alive at 70; that means 42% had died in middle age. This difference of 23% (between 81% survival in the non-smokers and 58% survival in the smokers) arose because about a quarter of all the smokers had been killed by tobacco when they were still in middle age (35-69), mainly from diseases such as lung cancer, heart attack and chronic lung disease. [CLICK] Of course, everybody will die sooner or later: it’s just that, on average, the smokers died 10 years sooner. 81% of the smokers were alive at 60, while 81% of the non-smokers were still alive at 70. [CLICK] Likewise, 58% of the smokers were alive at 70, while 59% of the non-smokers were still alive at 80. Of course this 10-year shift is just the average. Some smokers are not killed by tobacco, while many others lose 10, 20, 30 or more good years. And, next, the effects of stopping smoking…
- HRs (95% CIs) for total cancer and specific cancer types associated with a 1-point increment in WCRF/AICR score (range: 0–6 in men, 0–7 in women). Cox regression models were stratified by center, age (1-y increments), and sex and adjusted for energy intake (kcal), level of education (none, primary school, technical/professional school, secondary school, university degree, unknown/missing), duration of smoking in former smokers (&gt;20 y ago, 11–20 y ago, ≤10 y ago, unknown/missing), number of cigarettes per day among smokers (1–15 cigarettes, 16–25 cigarettes, &gt;25 cigarettes, pipe or cigar, unknown/missing), and presence of chronic diseases at baseline (no, yes, missing). Models for women were further adjusted for ever use of contraceptive pills (no, yes, missing), ever use of hormone replacement therapy (no, yes, missing), age at first menarche (&lt;12 y, ≥12 to ≤15 y, &gt;15 y, missing), age at first pregnancy (&lt;21 y, ≥21 to ≤30 y, &gt;30 y, nulliparous), and menopausal status (premenopausal, postmenopausal, perimenopausal, and surgical postmenopausal). UADT, upper aerodigestive tract; WCRF/AICR, World Cancer Research Fund/American Institute for Cancer Research.