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      Associations between types and sources of dietary carbohydrates and cardiovascular disease risk: a prospective cohort study of UK Biobank participants

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          Abstract

          Background

          Recent studies have reported that the associations between dietary carbohydrates and cardiovascular disease (CVD) may depend on the quality, rather than the quantity, of carbohydrates consumed. This study aimed to assess the associations between types and sources of dietary carbohydrates and CVD incidence. A secondary aim was to examine the associations of carbohydrate intakes with triglycerides within lipoprotein subclasses.

          Methods

          A total of 110,497 UK Biobank participants with ≥ two (maximum five) 24-h dietary assessments who were free from CVD and diabetes at baseline were included. Multivariable-adjusted Cox regressions were used to estimate risks of incident total CVD (4188 cases), ischaemic heart disease (IHD; 3138) and stroke (1124) by carbohydrate intakes over a median follow-up time of 9.4 years, and the effect of modelled dietary substitutions. The associations of carbohydrate intakes with plasma triglycerides within lipoprotein subclasses as measured by nuclear magnetic resonance (NMR) spectroscopy were examined in 26,095 participants with baseline NMR spectroscopy measurements.

          Results

          Total carbohydrate intake was not associated with CVD outcomes. Free sugar intake was positively associated with total CVD (HR; 95% CI per 5% of energy, 1.07;1.03–1.10), IHD (1.06;1.02–1.10), and stroke (1.10;1.04–1.17). Fibre intake was inversely associated with total CVD (HR; 95% CI per 5 g/d, 0.96;0.93–0.99). Modelled isoenergetic substitution of 5% of energy from refined grain starch with wholegrain starch was inversely associated with total CVD (0.94;0.91–0.98) and IHD (0.94;0.90–0.98), and substitution of free sugars with non-free sugars was inversely associated with total CVD (0.95;0.92–0.98) and stroke (0.91;0.86–0.97). Free sugar intake was positively associated with triglycerides within all lipoproteins.

          Conclusions

          Higher free sugar intake was associated with higher CVD incidence and higher triglyceride concentrations within all lipoproteins. Higher fibre intake and replacement of refined grain starch and free sugars with wholegrain starch and non-free sugars, respectively, may be protective for incident CVD.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12916-022-02712-7.

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          Most cited references77

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age

            Cathie Sudlow and colleagues describe the UK Biobank, a large population-based prospective study, established to allow investigation of the genetic and non-genetic determinants of the diseases of middle and old age.
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              Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

              Summary Background Rigorous analysis of levels and trends in exposure to leading risk factors and quantification of their effect on human health are important to identify where public health is making progress and in which cases current efforts are inadequate. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a standardised and comprehensive assessment of the magnitude of risk factor exposure, relative risk, and attributable burden of disease. Methods GBD 2019 estimated attributable mortality, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 87 risk factors and combinations of risk factors, at the global level, regionally, and for 204 countries and territories. GBD uses a hierarchical list of risk factors so that specific risk factors (eg, sodium intake), and related aggregates (eg, diet quality), are both evaluated. This method has six analytical steps. (1) We included 560 risk–outcome pairs that met criteria for convincing or probable evidence on the basis of research studies. 12 risk–outcome pairs included in GBD 2017 no longer met inclusion criteria and 47 risk–outcome pairs for risks already included in GBD 2017 were added based on new evidence. (2) Relative risks were estimated as a function of exposure based on published systematic reviews, 81 systematic reviews done for GBD 2019, and meta-regression. (3) Levels of exposure in each age-sex-location-year included in the study were estimated based on all available data sources using spatiotemporal Gaussian process regression, DisMod-MR 2.1, a Bayesian meta-regression method, or alternative methods. (4) We determined, from published trials or cohort studies, the level of exposure associated with minimum risk, called the theoretical minimum risk exposure level. (5) Attributable deaths, YLLs, YLDs, and DALYs were computed by multiplying population attributable fractions (PAFs) by the relevant outcome quantity for each age-sex-location-year. (6) PAFs and attributable burden for combinations of risk factors were estimated taking into account mediation of different risk factors through other risk factors. Across all six analytical steps, 30 652 distinct data sources were used in the analysis. Uncertainty in each step of the analysis was propagated into the final estimates of attributable burden. Exposure levels for dichotomous, polytomous, and continuous risk factors were summarised with use of the summary exposure value to facilitate comparisons over time, across location, and across risks. Because the entire time series from 1990 to 2019 has been re-estimated with use of consistent data and methods, these results supersede previously published GBD estimates of attributable burden. Findings The largest declines in risk exposure from 2010 to 2019 were among a set of risks that are strongly linked to social and economic development, including household air pollution; unsafe water, sanitation, and handwashing; and child growth failure. Global declines also occurred for tobacco smoking and lead exposure. The largest increases in risk exposure were for ambient particulate matter pollution, drug use, high fasting plasma glucose, and high body-mass index. In 2019, the leading Level 2 risk factor globally for attributable deaths was high systolic blood pressure, which accounted for 10·8 million (95% uncertainty interval [UI] 9·51–12·1) deaths (19·2% [16·9–21·3] of all deaths in 2019), followed by tobacco (smoked, second-hand, and chewing), which accounted for 8·71 million (8·12–9·31) deaths (15·4% [14·6–16·2] of all deaths in 2019). The leading Level 2 risk factor for attributable DALYs globally in 2019 was child and maternal malnutrition, which largely affects health in the youngest age groups and accounted for 295 million (253–350) DALYs (11·6% [10·3–13·1] of all global DALYs that year). The risk factor burden varied considerably in 2019 between age groups and locations. Among children aged 0–9 years, the three leading detailed risk factors for attributable DALYs were all related to malnutrition. Iron deficiency was the leading risk factor for those aged 10–24 years, alcohol use for those aged 25–49 years, and high systolic blood pressure for those aged 50–74 years and 75 years and older. Interpretation Overall, the record for reducing exposure to harmful risks over the past three decades is poor. Success with reducing smoking and lead exposure through regulatory policy might point the way for a stronger role for public policy on other risks in addition to continued efforts to provide information on risk factor harm to the general public. Funding Bill & Melinda Gates Foundation.
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                Author and article information

                Contributors
                rebecca.kelly@ndph.ox.ac.uk
                tammy.tong@ndph.ox.ac.uk
                cody.watling@ndph.ox.ac.uk
                andrew.reynolds@otago.ac.nz
                carmen.piernas-sanchez@phc.ox.ac.uk
                js@clin.au.dk
                keren.papier@ndph.ox.ac.uk
                jennifer.carter@ndph.ox.ac.uk
                tim.key@ndph.ox.ac.uk
                aurora.perez-cornago@ndph.ox.ac.uk
                Journal
                BMC Med
                BMC Med
                BMC Medicine
                BioMed Central (London )
                1741-7015
                14 February 2023
                14 February 2023
                2023
                : 21
                : 34
                Affiliations
                [1 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Cancer Epidemiology Unit, Nuffield Department of Population Health, , University of Oxford, ; Richard Doll Building, Roosevelt Drive, Oxford, OX3 7LF UK
                [2 ]GRID grid.29980.3a, ISNI 0000 0004 1936 7830, Department of Medicine, , University of Otago, ; Dunedin, 9016 New Zealand
                [3 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Nuffield Department of Primary Care Health Sciences, , University of Oxford, ; Oxford, OX3 7LF UK
                [4 ]GRID grid.154185.c, ISNI 0000 0004 0512 597X, Department of Clinical Epidemiology, Department of Clinical Medicine, , Aarhus University and Aarhus University Hospital, ; Olof Palmes Allé 43-45, 8200 Aarhus N, Denmark
                [5 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Clinical Trial Service Unit and Epidemiological Studies Unit, , University of Oxford, ; Oxford, OX3 7LF UK
                Author information
                http://orcid.org/0000-0001-7409-8520
                Article
                2712
                10.1186/s12916-022-02712-7
                9926727
                36782209
                2d13b52b-98ed-49b7-a6dd-08f85b4c9a43
                © The Author(s) 2023

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 8 September 2022
                : 14 December 2022
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100014748, Clarendon Fund;
                Funded by: Nuffield Department of Population Health Intermediate Fellowship
                Funded by: Nuffield Department of Population Health Doctor of Philosophy student scholarship
                Funded by: FundRef http://dx.doi.org/10.13039/501100001516, National Heart Foundation of New Zealand;
                Funded by: FundRef http://dx.doi.org/10.13039/501100000265, Medical Research Council;
                Award ID: MR/M012190/1
                Award ID: CTSU A310
                Award Recipient :
                Funded by: National Institute for Health Research (NIHR) Applied Research Collaboration (ARC)
                Funded by: FundRef http://dx.doi.org/10.13039/100010269, Wellcome Trust;
                Award ID: 205212/Z/16/Z
                Award ID: 205212/Z/16/Z
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000289, Cancer Research UK;
                Award ID: C570/A16491
                Award ID: C8221/A19170
                Award Recipient :
                Funded by: Cancer Research UK
                Award ID: A29186
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000274, British Heart Foundation;
                Award ID: CH/1996001/9454
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100013373, NIHR Oxford Biomedical Research Centre;
                Funded by: Cancer Research UK
                Award ID: C8221/A19170
                Award Recipient :
                Funded by: Cancer Research UK
                Award ID: C60192/A28516
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000321, World Cancer Research Fund;
                Award ID: 2019/1953
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2023

                Medicine
                coronary heart disease,stroke,nutritional epidemiology,primary prevention,carbohydrates
                Medicine
                coronary heart disease, stroke, nutritional epidemiology, primary prevention, carbohydrates

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