Life expectancy gains from dietary modifications: a comparative modeling study in 7 countries.

BACKGROUND: Eating healthier is associated with a range of favorable health outcomes. Our previous model estimated the impact of dietary changes on life expectancy gains but did not consider height, weight, or physical activity. OBJECTIVES: We aimed to estimate the increase in life expectancy resulting from the transition from typical national dietary patterns to longevity-optimizing dietary changes, more feasible dietary modifications, and optimized vegan dietary changes in China, France, Germany, Iran, Norway, the United Kingdom, and the United States. METHODS: Our modeling study used data from meta-analyses presenting dose-response relationships between intake of 15 food groups and mortality. Background mortality data were from the Global Burden of Disease Study. We used national food intake data and adjusted for height, weight, and physical activity level. RESULTS: For 40-y-olds, estimated life expectancy gains ranged from 6.2 y (with uncertainty interval [UI]: 5.7, 7.5 y) for Chinese females to 9.7 y (UI: 8.1, 11.3 y) for United States males following sustained changes from typical country-specific dietary patterns to longevity-optimized dietary changes, and from 5.2 y (UI: 4.0, 6.5 y) for Chinese females to 8.7 y (UI: 7.1, 10.3 y) for United States males following changes to optimized vegan dietary changes. CONCLUSIONS: A sustained change from country-specific typical dietary pattern patterns to longevity-optimized dietary changes, more feasible dietary changes, or optimized vegan dietary changes are all projected to result in substantial life expectancy gains across ages and countries. These changes included more whole grains, legumes, and nuts and less red/processed meats and sugars and sugar-sweetened beverages. The largest gains from dietary changes would be in the United States.

Nuts and seeds - a scoping review for Nordic Nutrition Recommendations 2023.

Background: Nuts and seeds have been part of diets in most of the world for millenniums, and they have also been consumed in the Nordic and Baltic countries for centuries. Consumption of nuts and seeds is linked with various health outcomes. Therefore, when updating the Nordic Nutrition Recommendations (NNR), summarizing the best evidence on key health outcomes from the consumption of nuts and seeds is essential. Objectives: This study aims to evaluate the updated evidence on the consumption of nuts and seeds and health outcomes regarded relevant for the Nordic and Baltic countries, as well as their dose-response relationship presented in updated systematic reviews and meta-analyses. Method: The scoping review is built on a de novo systematic review and an umbrella review published in 2022 on the consumption of nuts and seeds and its various health outcomes, including cardiovascular disease and diabetes. Results: Intake of nuts and seeds is associated with a lower risk of cardiovascular diseases, with evidence assessed as probable. This conclusion is mirrored by evidence from trials on biomarkers for chronic diseases. An intake of a serving of nuts of 28-30 g/day compared to not eating nuts is estimated to translate into approximately 20% relative reduction in the risks of cardiovascular disease and premature deaths. For cancers, consumption of a serving of nuts is inversely associated with cancer mortality. However, for type 2 diabetes, there are mixed and inconclusive results. Additionally, there are inverse associations between nut consumption and respiratory and infectious disease mortality. Allergies for nuts are seen among 1-2% of the population. Conclusion: Overall, the current evidence supports dietary recommendations to increase nut consumption to a serving of nuts and seeds per day for people without allergies to these foods.

Prediction of death rates for cardiovascular diseases and cancers.

Background: To estimate cardiovascular and cancer death rates by regions and time periods. Design: Novel statistical methods were used to analyze clinical surveillance data. Methods: A multicenter, population-based medical survey was performed. Annual recorded deaths from cardiovascular diseases were analyzed for all 195 countries of the world. It is challenging to model such data; few mathematical models can be applied because cardiovascular disease and cancer data are generally not normally distributed. Results: A novel approach to assessing the biosystem reliability is introduced and has been found to be particularly suitable for analyzing multiregion environmental and healthcare systems. While traditional methods for analyzing temporal observations of multiregion processes do not deal with dimensionality efficiently, our methodology has been shown to be able to cope with this challenge. Conclusions: Our novel methodology can be applied to public health and clinical survey data.

Life expectancy can increase by up to 10 years following sustained shifts towards healthier diets in the United Kingdom.

Adherence to healthy dietary patterns can prevent the development of non-communicable diseases and affect life expectancy. Here, using a prospective population-based cohort data from the UK Biobank, we show that sustained dietary change from unhealthy dietary patterns to the Eatwell Guide dietary recommendations is associated with 8.9 and 8.6 years gain in life expectancy for 40-year-old males and females, respectively. In the same population, sustained dietary change from unhealthy to longevity-associated dietary patterns is associated with 10.8 and 10.4 years gain in life expectancy in males and females, respectively. The largest gains are obtained from consuming more whole grains, nuts and fruits and less sugar-sweetened beverages and processed meats. Understanding the contribution of sustained dietary changes to life expectancy can provide guidance for the development of health policies.

Dementia death rates prediction.

BACKGROUND: Prevalence of dementia illness, causing certain morbidity and mortality globally, places burden on global public health. This study primary goal was to assess future risks of dying from severe dementia, given specific return period, within selected group of regions or nations. METHODS: Traditional statistical approaches do not have benefits of effectively handling large regional dimensionality, along with nonlinear cross-correlations between various regional observations. In order to produce reliable long-term projections of excessive dementia death rate risks, this study advocates novel bio-system reliability technique, that being particularly suited for multi-regional environmental, biological, and health systems. DATA: Raw clinical data has been used as an input to the suggested population-based, bio-statistical technique using data from medical surveys and several centers. RESULTS: Novel spatiotemporal health system reliability methodology has been developed and applied to dementia death rates raw clinical data. Suggested methodology shown to be capable of dealing efficiently with spatiotemporal clinical observations of multi-regional nature. Accurate disease risks multi-regional spatiotemporal prediction being done, relevant confidence intervals have been presented as well. CONCLUSIONS: Based on available clinical survey dataset, the proposed approach may be applied in a variety of clinical public health applications. Confidence bands, given for predicted dementia-associated death rate levels with return periods of interest, have been reasonably narrow, indicating practical values of advocated prognostics.

Floating wind turbines structural details fatigue life assessment.

Fatigue damage prediction is essential for safety of contemporary offshore energy industrial projects, like offshore wind turbines, that are to be designed for sufficiently long operational period of time, with minimal operational disruptions. Offshore structures being designed to withstand environmental loadings due to winds and waves. Due to accumulated fatigue damage, offshore wind floating turbines may develop material cracks in their critical locations sooner than expected. Dataset needed for an accurate assessment of fatigue damage may be produced by either extensive numerical modeling, or direct measurements. However, in reality, temporal length of the underlying dataset being typically too short to provide an accurate calculation of direct fatigue damage and fatigue life. Hence, the objective of this work is to contribute to the development of novel fatigue assessment methods, making better use of limited underlying dataset. In this study, in-situ environmental conditions were incorporated to assess offshore FWT tower base stresses; then structural cumulative fatigue damage has been assessed. Novel deconvolution extrapolation method has been introduced in this study, and it was shown to be able to accurately predict long-term fatigue damage. The latter technique was validated, using artificially reduced dataset, and resulted in fatigue damage that was shown to be close to the damage, calculated from the full original underlying dataset. Recommended method has been shown to utilize available dataset much more efficiently, compared to direct fatigue estimation. Accurate fatigue assessment of offshore wind turbine structural characteristics is essential for structural reliability, design, and operational safety.

Gaidai-Xing reliability method validation for 10-MW floating wind turbines.

In contrast to well-known bivariate statistical approach, which is known to properly forecast extreme response levels for two-dimensional systems, the research validates innovative structural reliability method, which is particularly appropriate for multi-dimensional structural responses. The disadvantage of dealing with large system dimensionality and cross-correlation across multiple dimensions is not a benefit of traditional dependability approaches that deal with time series. Since offshore constructions are built to handle extremely high wind and wave loads, understanding these severe stresses is essential, e.g. wind turbines should be built and operated with the least amount of inconvenience. In the first scenario, the blade root flapwise bending moment is examined, whereas in the second, the tower bottom fore-aft bending moment is examined. The FAST simulation program was utilized to generate the empirical bending moments for this investigation with the load instances activated at under-rated, rated, and above-rated speeds. The novel reliability approach, in contrast to conventional reliability methods, does not call for the study of a multi-dimensional reliability function in the case of numerical simulation. As demonstrated in this work, it is now possible to assess multi-degree-of-freedom nonlinear system failure probability, in the case when only limited system measurements are available.

Characterisation of extreme load responses of a 10-MW floating semi-submersible type wind turbine.

The global average size of offshore wind turbines has increased steadily from 1.5 MW to 6 MW from 2000 to 2020. With this backdrop, the research community has recently looked at huge 10-15 MW class floating offshore wind turbines (FOWTs). The larger rotor, nacelle structure and tower have more significant structural flexibility. The larger structural flexibility, controller dynamics, aerodynamics, hydrodynamics, and various environmental conditions result in complex structural responses. The structural load effects of a very large FOWT could be more severe than that of the lower MW classes. Accurate quantification of the extreme dynamic responses of FOWT systems is essential in the design of the Ultimate Limit State (ULS) due to the fully-coupled interaction between the FOWT system and environmental conditions. Motivated by this, extreme responses of the 10 MW semi-submersible type FOWT are investigated using the average conditional exceedance rate (ACER) and Gumbel methods. Three operating conditions representing below-rated (U = 8 m/s), rated (U = 12 m/s) and above-rated (U = 16 m/s) regions were considered. The aim is to guide future research on large FOWTs by indicating the expected ULS loads.

Improving extreme offshore wind speed prediction by using deconvolution.

This study proposes an innovative method for predicting extreme values in offshore engineering. This includes and is not limited to environmental loads due to offshore wind and waves and related structural reliability issues. Traditional extreme value predictions are frequently constructed using certain statistical distribution functional classes. The proposed method differs from this as it does not assume any extrapolation-specific functional class and is based on the data set's intrinsic qualities. To demonstrate the method's effectiveness, two wind speed data sets were analysed and the forecast accuracy of the suggested technique has been compared to the Naess-Gaidai extrapolation method. The original batch of data consisted of simulated wind speeds. The second data related to wind speed was recorded at an offshore Norwegian meteorological station.

Consumption of Nuts and Seeds and Health Outcomes Including Cardiovascular Disease, Diabetes and Metabolic Disease, Cancer, and Mortality: An Umbrella Review.

Consumption of nuts and seeds is associated with a range of health outcomes. Summarizing the best evidence on essential health outcomes from the consumption of nuts is essential to provide optimal recommendations. Our objective is to comprehensively assess health outcome associations related to the consumption of nuts and seeds, using a culinary definition including tree nuts and peanuts (registered in PROSPERO: CRD42021258300). Health outcomes of interest include cardiovascular disease, cancer, diabetes, obesity, respiratory disease, mortality, and their disease biomarkers. We present associations for high compared with low consumption, per serving, and dose-response relations. MEDLINE, Embase, Cochrane, and Epistemonikos were searched and screened for systematic reviews and meta-analyses. Evidence was extracted from 89 articles on the consumption of nuts and relevant health outcomes, including 23 articles with meta-analysis on disease and mortality, 66 articles on biomarkers for disease, and 9 articles on allergy/adverse outcomes. Intake of nuts was associated with reduced risk of cardiovascular diseases and related risk factors, with moderate quality of evidence. An intake of 28 g/d nuts compared with not eating nuts was associated with a 21% RR reduction of cardiovascular disease (including coronary heart disease incidence and mortality, atrial fibrillation, and stroke mortality), an 11% risk reduction of cancer deaths, and 22% reduction in all-cause mortality. Nut consumption was also inversely associated with mortality from respiratory diseases, infectious diseases, and diabetes; however, associations between nut consumption and diabetes incidence were mixed. Meta-analyses of trials on biomarkers for disease generally mirrored meta-analyses from observational studies on cardiovascular disease, cancers, and diabetes. Allergy and related adverse reactions to nuts were observed in 1-2% of adult populations, with substantial heterogeneity between studies. Overall, the current evidence supports dietary recommendations to consume a handful of nuts and seeds per day for people without allergies to these foods.