En zie ook onder preventie
7 augustus 2024: Bron: The Lancet
Wanneer de Amerikaanse bevolking 30 procent minder bewerkt vlees en minder rood vlees zou gaan eten dan zou dat binnen een tijdbestek van 10 jaar ook tot 30 procent minder gevallen van diabetes type 2, hart- en vaatziekten, darmkanker en overlijden aan alle oorzaken geven.
Dat stellen onderzoekers van de universiteit van Edinburgh die aan de hand van de gegevens van 8665 volwassenen een simulatieonderzoek deden naar het eten van bewerkt vlees en onbewerkt rood vlees in hun voedingspatroon en die werden vergeleken en gesimuleerd wat dat voor effect zou hebben op de totale bevolking van 240 miljoen volwassen Amerikanen gerekend over tien jaar follow-up.
Uit het studierapport:
- De onderzoekers schatten dat een vermindering van 30 procent in de inname van bewerkt vlees alleen al zou kunnen resulteren in 352.900; 92.500; en 53.300 minder gevallen van diabetes type 2, hart- en vaatziekten en darmkanker, respectievelijk, en 16.700 minder sterfgevallen door alle oorzaken gedurende een periode van tien jaar.
- Alleen al een vermindering van de inname van onbewerkt rood vlees met 30 procent zou kunnen leiden tot 732.600; 291.500; en 32.200 minder gevallen van diabetes type 2, hart- en vaatziekten en darmkanker, respectievelijk, en 46.100 minder sterfgevallen door alle oorzaken.
- Een vermindering van 30 procent in de inname van zowel bewerkt vlees als onbewerkt rood vlees zou kunnen resulteren in 1.073.400; 382.400; en 84.400 minder gevallen van diabetes type 2, hart- en vaatziekten en darmkanker, respectievelijk, en 62.200 minder sterfgevallen door alle oorzaken gedurende een periode van tien jaar.
En in deze grafiek uit het studieverslag gekopieerd. En in de referentielijst.
Table 1Input parameters
| Justification | Reference | |
|---|---|---|
| Baseline risk of type 2 diabetes | Provided age-specific risk prediction with three US cohorts: Coronary Artery Risk Development in Young Adults (participants aged 18–40 years), Atherosclerosis Risk in Communities (participants aged 45–64 years), and the Cardiovascular Health Study (participants aged 65 years or older). We used the simple model as all required variables were available in NHANES. AUROCs ranged from 0·72 (95% CI 0·69–0·76) for participants aged 25–30 years to 0·79 (0·76–0·83) for participants aged 35–40 years. | Alva et al |
| Baseline risk of cardiovascular disease | Provided sex-specific risk prediction with two US cohorts: the Framingham Heart Study and the Framingham Offspring Study. C statistic, analogous to AUROC, ranged from 0·763 (95% CI 0·746–0·780) in men to 0·793 (0·772–0·814) in women. All required variables were available in NHANES. | D'Agostino et al |
| Baseline risk of colorectal cancer | Provided sex-specific risk prediction with one US cohort: the Multi-Ethnic Cohort Study. C statistic was 0·681 (95% CI 0·669–0·694) in men and 0·679 (0·665–0·692) in women. All required variables, except family history of colorectal cancer, were available in NHANES. | Wells et al |
| Association between processed meat and unprocessed red meat intake and type 2 diabetes | Meta-analysis that provided dose–response curves separately for processed meat and unprocessed red meat from 25 cohort studies; 17 were included in the estimate for processed meat and unprocessed red meat. Each additional 100 g per day of red meat was associated with a relative risk of 1·31 (95% CI 1·19–1·45) of type 2 diabetes. Each additional 50 g per day of processed meat was associated with a relative risk of 1·46 (1·26–1·69) of type 2 diabetes. These estimates were similar to those from Gu et al, who combined three US cohorts (ie, Nurses' Health Study, Nurses' Health Study II, and Health Professionals Follow-up Study); every one serving per day increment in red meat was associated with a hazard ratio of 1·28 (1·24–1·31) increased risk of type 2 diabetes. Every one serving per day increment of processed red meat was associated with a hazard ratio of 1·46 (1·40–1·53) increased risk of type 2 diabetes. The estimates were also similar to a meta-analysis by Shi et al of 18 effect estimates from 16 studies, which found that each 50 g per day increment of processed red meat was associated with a hazard ratio of 1·44 (1·40–1·53) increased risk of type 2 diabetes. | Yang et al; Gu et al; Shi et al |
| Association between processed meat and unprocessed red meat intake and cardiovascular disease | Combined estimate from six US cohorts: Atherosclerosis Risk in Communities, Coronary Artery Risk Development in Young Adults, Cardiovascular Health Study, Framingham Heart Study, Framingham Offspring Study, and Multi-Ethnic Study of Atherosclerosis. For processed meat intake, hazard ratio for increased risk of cardiovascular disease for two vs zero servings per week was 1·07 (95% CI 1·04–1·11). For unprocessed red meat, hazard ratio for increased risk of cardiovascular disease for two vs zero servings per week was 1·03 (1·01–1·06). One serving was assumed to be equivalent to 30 g of processed meat in our micro-Simulation of the Health Impacts of Food Transformations. These estimates were similar to the meta-analysis by Shi et al of 17 effect estimates from 14 studies, which found that each 50 g per day increment of processed red meat was associated with a hazard ratio of 1·26 (1·18–1·35) increased risk of cardiovascular disease. | Zhong et al; Shi et al |
| Association between processed meat and unprocessed red meat intake and colorectal cancer | Meta-analysis that provided dose–response relative risk estimates for processed meat and red meat. Pooled relative risk for 50 g per day of processed meat intake was 1·22 (95% CI 1·12–1·33) on the basis of eight cohort studies, whereas pooled relative risk for 100 g per day of red meat was 1·16 (1·05–1·29) on the basis of nine cohort studies. These findings were consistent with Bouvard et al, who found that each 50 g per day increment of processed meat increased the risk of colorectal cancer by a relative risk of 1·18 (1·10–1·28). | Zhao et al; International Agency for Research on Cancer |
| Mortality among people with type 2 diabetes | Registry-based study of the Swedish National Diabetes Register that provided age-specific hazard ratios of all-cause mortality among people with type 2 diabetes. As this study was based outside the USA, we used hazard ratios from the simple model that were unadjusted for country of origin and education. | Tancredi et al |
| Mortality among people with cardiovascular disease | Age-adjusted and sex-adjusted all-cause mortality hazard ratios for people with a history of stroke and myocardial infarction from the Emerging Risk Factors collaboration. Mortality hazard ratio for people with a history of stroke was 2·1 (95% CI 2·0–2·2) and for people with a history of myocardial infarction was 2·0 (1·9–2·2). We used a sampling distribution based on the mean of these hazard ratios. | Di Angelantonio et al |
| Mortality among people with colorectal cancer | Fixed age-specific and sex-specific mortality probabilities based on colorectal cancer mortality statistics from the USA in 2017 and estimates of the prevalence of colorectal cancer in corresponding age and sex groups from the 2017–18 NHANES. | Siegel et al |
AUROC=area under the receiver-operating curve. NHANES=US National Health and Nutrition Examination Survey.
En zie ook deze grafiek uitgesplitst naar de vier genoemde ziektebeelden:
Figure 3Absolute percentages of prevented occurrences of each disease by annual household income, age, sex, and ethnicity after a 10-year 30% reduction in processed meat intake
Het volledige studierapport is gratis in te zien. Hier het abstract van de studie gepubliceerd in The Lancet Planetary Earth:
Estimated effects of reductions in processed meat consumption and unprocessed red meat consumption on occurrences of type 2 diabetes, cardiovascular disease, colorectal cancer, and mortality in the USA: a microsimulation study
Summary
Background
High consumption of processed meat and unprocessed red meat is associated with increased risk of multiple chronic diseases, although there is substantial uncertainty regarding the relationship for unprocessed red meat. We developed a microsimulation model to estimate how reductions in processed meat and unprocessed red meat consumption could affect rates of type 2 diabetes, cardiovascular disease, colorectal cancer, and mortality in the US adult population.
Methods
We used data from two versions of the US National Health and Nutrition Examination Survey, one conducted during 2015–16 and one conducted during 2017–18, to create a simulated US population. The starting cohort was restricted to respondents aged 18 years or older who were not pregnant and had 2 days of dietary-recall data. First, we used previously developed risk models to estimate the baseline disease risk of an individual. For type 2 diabetes we used a logistic-regression model and for cardiovascular disease and colorectal cancer we used Cox proportional-hazard models. We then multiplied baseline risk by relative risk associated with individual processed meat and unprocessed red meat consumption. Prevented occurrences of type 2 diabetes, cardiovascular disease, colorectal cancer, and mortality were computed by taking the difference between the incidence in the baseline and intervention scenarios. All stages were repeated for ten iterations to correspond to a 10-year time span. Scenarios were reductions of 5%, 10%, 30%, 50%, 75%, and 100% in grams consumed of processed meat, unprocessed red meat, or both. Each scenario was repeated 50 times for uncertainty analysis.
Findings
The total number of individual respondents included in the simulated population was 8665, representing 242 021 876 US adults. 4493 (51·9%) of 8665 individuals were female and 4172 (48·1%) were male; mean age was 49·54 years (SD 18·38). At baseline, weighted mean daily consumption of processed meat was 29·1 g, with a 30% reduction being 8·7 g per day, and of unprocessed red meat was 46·7 g, with a 30% reduction being 14·0 g per day. We estimated that a 30% reduction in processed meat intake alone could lead to 352 900 (95% uncertainty interval 345 500–359 900) fewer occurrences of type 2 diabetes, 92 500 (85 600–99 900) fewer occurrences of cardiovascular disease, 53 300 (51 400–55 000) fewer occurrences of colorectal cancer, and 16 700 (15 300–17 700) fewer all-cause deaths during the 10-year period. A 30% reduction in unprocessed red meat intake alone could lead to 732 600 (725 700–740 400) fewer occurrences of type 2 diabetes, 291 500 (283 900–298 800) fewer occurrences of cardiovascular disease, 32 200 (31 500–32 700) fewer occurrences of colorectal cancer, and 46 100 (45 300–47 200) fewer all-cause deaths during the 10-year period. A 30% reduction in both processed meat and unprocessed red meat intake could lead to 1 073 400 (1 060 100–1 084 700) fewer occurrences of type 2 diabetes, 382 400 (372 100–391 000) fewer occurrences of cardiovascular disease, 84 400 (82 100–86 200) fewer occurrences of colorectal cancer, and 62 200 (60 600–64 400) fewer all-cause deaths during the 10-year period.
Interpretation
Reductions in processed meat consumption could reduce the burden of some chronic diseases in the USA. However, more research is needed to increase certainty in the estimated effects of reducing unprocessed red meat consumption.
Funding
The Wellcome Trust.
Contributors
LST and LMJ acquired funding. JK and LMJ accessed and verified the underlying data and wrote the original draft of the paper. JK developed the simulation model and cleaned the underlying data, with inputs from PA and LMJ. PA and LST reviewed and edited the paper. All authors conceptualised the study, had full access to all the data in the study, and had final responsibility for the decision to submit for publication.
Data sharing
All code to run the micro-Simulation of the Health Impacts of Food Transformations is available at https://github.com/jsfken/mSHIFT. De-identified US National Health and Nutrition Examination Survey data are available at https://wwwn.cdc.gov/nchs/nhanes/Default.aspx.
Declaration of interests
We declare no competing interests.
Acknowledgments
This study was funded by the Wellcome Trust (grant 216042/Z/19/Z). We thank Victor Zhong for useful discussions and providing relevant data and Brian Wells for providing details of the colorectal cancer risk equations. We also thank Andrew Freedman, Jennifer Marratt, Thomas Imperiale, Jane Driver, Michael Goodman, Mohammed Ali, Edward Gregg, Sarah Frank, Anna Grummon, Benjamin Allaire, and Anthony Wood for useful discussions.
Supplementary Material
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Supplementary appendix
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Published: July 2024
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