47 research outputs found

    Alcohol consumption patterns across Europe and adherence to the European guidelines in coronary patients : findings from the ESC-EORP EUROASPIRE V survey

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    Background and aims: Alcohol consumption is an important risk factor for cardiovascular morbidity and mortality worldwide. The highest levels of alcohol consumption are observed in Europe, where alcohol as contributing cause of coronary heart disease (CHD) is also most significant. We aimed to describe alcohol consumption patterns across European regions and adherence to the current guidelines in patients with a recent CHD event. Methods: The ESC-EORP survey (EUROASPIRE V) has been conducted in 2016-2017 at 131 centers in 27 Eu-ropean countries in 7350 patients with a recent CHD. Median alcohol consumption, as well as the proportion of abstainers and excessive drinkers (i.e. >70 g/week for women and >140 for men, as recommended by the European guidelines on cardiovascular prevention), was calculated for each region. To assess adherence to guidelines, proportions of participants who were advised to reduce excessive alcohol consumption and participants who were incorrectly not advised were calculated per region. Results: Mean age was 64 years (SD: 9.5), 75% were male. Abstention rates were 53% in males and 77% in females, whereas excessive drinking was reported by 9% and 5% of them, respectively. Overall, 57% of the participants were advised to reduce alcohol consumption. In the total population, 3% were incorrectly not advised, however, this percentage differed per region (range: 1%-9%). In regions where alcohol consumption was highest, participants were less often advised to reduce their consumption. Conclusion: In this EUROASPIRE V survey, the majority of CHD patients adhere to the current drinking guidelines, but substantial heterogeneity exists between European regions

    Dietary Intake of Total, Animal, and Vegetable Protein and Risk of Type 2 Diabetes in the European Prospective Investigation into Cancer and Nutrition (EPIC)-NL Study

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    OBJECTIVE - Dietary recommendations are focused mainly on relative dietary fat and carbohydrate content in relation to diabetes risk. Meanwhile, high-protein diets may contribute to disturbance of glucose metabolism, but evidence from prospective studies is scarce. We examined the association among dietary total, vegetable, and animal protein intake and diabetes incidence and whether consuming 5 energy % from protein at the expense of 5 energy % from either carbohydrates or fat was associated with diabetes risk. RESEARCH DESIGN AND METHODS - A prospective cohort study was conducted among 38,094 participants of the European Prospective Investigation into Cancer and Nutrition (EPIC)-NL study. Dietary protein intake was measured with a validated food frequency questionnaire. Incident diabetes was verified against medical records. RESULTS - During 10 years of follow-up, 918 incident cases of diabetes were documented. Diabetes risk increased with higher total protein (hazard ratio 2.15 [95% CI 1.77-2.60] highest vs. lowest quartile) and animal protein (2.18 [1.80 -2.63]) intake. Adjustment for confounders did not materially change these results. Further adjustment for adiposity measures attenuated the associations. Vegetable protein was not related to diabetes. Consuming 5 energy % from total or animal protein at the expense of 5 energy % from carbohydrates or fat increased diabetes risk. CONCLUSIONS - Diets high in animal protein are associated with an increased diabetes risk. Our findings also suggest a similar association for total protein itself instead of only animal sources. Consumption of energy from protein at the expense of energy from either carbohydrates or fat may similarly increase diabetes risk. This finding indicates that accounting for protein content in dietary recommendations for diabetes prevention may be useful

    Exposome-Wide Association Study of Body Mass Index Using a Novel Meta-Analytical Approach for Random Forest Models

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    BACKGROUND: Overweight and obesity impose a considerable individual and social burden, and the urban environments might encompass factors that contribute to obesity. Nevertheless, there is a scarcity of research that takes into account the simultaneous interaction of multiple environmental factors. OBJECTIVES: Our objective was to perform an exposome-wide association study of body mass index (BMI) in a multicohort setting of 15 studies. METHODS: Studies were affiliated with the Dutch Geoscience and Health Cohort Consortium (GECCO), had different population sizes (688-141,825), and covered the entire Netherlands. Ten studies contained general population samples, others focused on specific populations including people with diabetes or impaired hearing. BMI was calculated from self-reported or measured height and weight. Associations with 69 residential neighborhood environmental factors (air pollution, noise, temperature, neighborhood socioeconomic and demographic factors, food environment, drivability, and walkability) were explored. Random forest (RF) regression addressed potential nonlinear and nonadditive associations. In the absence of formal methods for multimodel inference for RF, a rank aggregation-based meta-analytic strategy was used to summarize the results across the studies. RESULTS: Six exposures were associated with BMI: five indicating neighborhood economic or social environments (average home values, percentage of high-income residents, average income, livability score, share of single residents) and one indicating the physical activity environment (walkability in formula presented buffer area). Living in high-income neighborhoods and neighborhoods with higher livability scores was associated with lower BMI. Nonlinear associations were observed with neighborhood home values in all studies. Lower neighborhood home values were associated with higher BMI scores but only for values up to formula presented . The directions of associations were less consistent for walkability and share of single residents. DISCUSSION: Rank aggregation made it possible to flexibly combine the results from various studies, although between-study heterogeneity could not be estimated quantitatively based on RF models. Neighborhood social, economic, and physical environments had the strongest associations with BMI. https://doi.org/10.1289/EHP13393.</p

    Alcohol consumption patterns across Europe and adherence to the European guidelines in coronary patients: Findings from the ESC-EORP EUROASPIRE V survey

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    Background and aims: Alcohol consumption is an important risk factor for cardiovascular morbidity and mortality worldwide. The highest levels of alcohol consumption are observed in Europe, where alcohol as contributing cause of coronary heart disease (CHD) is also most significant. We aimed to describe alcohol consumption patterns across European regions and adherence to the current guidelines in patients with a recent CHD event. Methods: The ESC-EORP survey (EUROASPIRE V) has been conducted in 2016–2017 at 131 centers in 27 European countries in 7350 patients with a recent CHD. Median alcohol consumption, as well as the proportion of abstainers and excessive drinkers (i.e. >70 g/week for women and >140 for men, as recommended by the European guidelines on cardiovascular prevention), was calculated for each region. To assess adherence to guidelines, proportions of participants who were advised to reduce excessive alcohol consumption and participants who were incorrectly not advised were calculated per region. Results: Mean age was 64 years (SD: 9.5), 75% were male. Abstention rates were 53% in males and 77% in females, whereas excessive drinking was reported by 9% and 5% of them, respectively. Overall, 57% of the participants were advised to reduce alcohol consumption. In the total population, 3% were incorrectly not advised, however, this percentage differed per region (range: 1%–9%). In regions where alcohol consumption was highest, participants were less often advised to reduce their consumption. Conclusion: In this EUROASPIRE V survey, the majority of CHD patients adhere to the current drinking guidelines, but substantial heterogeneity exists between European regions

    Post-load glucose subgroups and associated metabolic traits in individuals with type 2 diabetes:An IMI-DIRECT study

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    AIM: Subclasses of different glycaemic disturbances could explain the variation in characteristics of individuals with type 2 diabetes (T2D). We aimed to examine the association between subgroups based on their glucose curves during a five-point mixed-meal tolerance test (MMT) and metabolic traits at baseline and glycaemic deterioration in individuals with T2D. METHODS: The study included 787 individuals with newly diagnosed T2D from the Diabetes Research on Patient Stratification (IMI-DIRECT) Study. Latent class trajectory analysis (LCTA) was used to identify distinct glucose curve subgroups during a five-point MMT. Using general linear models, these subgroups were associated with metabolic traits at baseline and after 18 months of follow up, adjusted for potential confounders. RESULTS: At baseline, we identified three glucose curve subgroups, labelled in order of increasing glucose peak levels as subgroup 1-3. Individuals in subgroup 2 and 3 were more likely to have higher levels of HbA1c, triglycerides and BMI at baseline, compared to those in subgroup 1. At 18 months (n = 651), the beta coefficients (95% CI) for change in HbA1c (mmol/mol) increased across subgroups with 0.37 (-0.18-1.92) for subgroup 2 and 1.88 (-0.08-3.85) for subgroup 3, relative to subgroup 1. The same trend was observed for change in levels of triglycerides and fasting glucose. CONCLUSIONS: Different glycaemic profiles with different metabolic traits and different degrees of subsequent glycaemic deterioration can be identified using data from a frequently sampled mixed-meal tolerance test in individuals with T2D. Subgroups with the highest peaks had greater metabolic risk

    Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

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    Funding Information: GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file : Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services. Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

    Pilot data on the association between social jetlag and obesity-related characteristics in Dutch adolescents over one year

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    Objective: Social jetlag, a form of chronic circadian misalignment, has previously been associated with obesity in adults. We aimed to investigate the association between social jetlag and obesity-related characteristics in Dutch adolescents over a 1-year period. Methods: We analysed data of 83 adolescents, who were recruited from a Dutch cohort born between the years 1990 and 1993. At the age of 16 and 17y, we determined anthropometric measurements, body composition, physical activity, hours of television use, and self-reported sleep duration. Using linear regression models, we assessed the association between social jetlag, defined as more than a 1-hour difference between the midpoint of sleep during weekdays and weekend days, and body mass index (BMI), body fat percentage, and waist circumference at baseline and after one year. We corrected the analysis for sex, sleep, physical activity, and hours of television use. Results: At age 16y, we observed that social jetlag was highly prevalent, with only 13% of the adolescents reporting no social jetlag (≤1 h), whereas 29% and 58% reported a social jetlag of >1–2 h and ≥2 h. In a cross-sectional analysis, we observed at age 16y a significant higher BMI in the group with no social jetlag, compared to the group with >1- to 2-hour and ≥2-hour social jetlag after adjustment for sex (−0.81 kg/m2, 95% confidence interval = −3.1 to 1.4; and −2.09 kg/m2, 95% confidence interval = −4.1 to −0.1). This association remained significant after correction for the other possible confounders. No significant associations were observed between social jetlag at age 16y and changes in obesity-related characteristics over one year. Conclusion: Our pilot data showed that social jetlag is highly prevalent in adolescents, with social jetlag associated with a lower BMI; however, in this small group, social jetlag was not associated with changes in obesity-related characteristics over time

    Cardiovascular risk factors and lifestyle behaviours in relation to longevity: a Mendelian randomization study

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    Background: The American Heart Association introduced the Life's Simple 7 initiative to improve cardiovascular health by modifying cardiovascular risk factors and lifestyle behaviours. It is unclear whether these risk factors are causally associated with longevity. Objectives: This study aimed to investigate causal associations of Life's Simple 7 modifiable risk factors, as well as sleep and education, with longevity using the two-sample Mendelian randomization design. Methods: Instrumental variables for the modifiable risk factors were obtained from large-scale genome-wide association studies. Data on longevity beyond the 90th survival percentile were extracted from a genome-wide association meta-analysis with 11,262 cases and 25,483 controls whose age at death or last contact was ≤ the 60th survival percentile. Results: Risk factors associated with a lower odds of longevity included the following: genetic liability to type 2 diabetes (OR 0.88; 95% CI: 0.84;0.92), genetically predicted systolic and diastolic blood pressure (per 1-mmHg increase: 0.96; 0.94;0.97 and 0.95; 0.93;0.97), body mass index (per 1-SD increase: 0.80; 0.74;0.86), low-density lipoprotein cholesterol (per 1-SD increase: 0.75; 0.65;0.86) and smoking initiation (0.75; 0.66;0.85). Genetically increased high-density lipoprotein cholesterol (per 1-SD increase: 1.23; 1.08;1.41) and educational level (per 1-SD increase: 1.64; 1.45;1.86) were associated with a higher odds of longevity. Fasting glucose and other lifestyle factors were not significantly associated with longevity. Conclusion: Most of the Life's Simple 7 modifiable risk factors are causally related to longevity. Prevention strategies should focus on modifying these risk factors and reducing education inequalities to improve cardiovascular health and longevity

    Associations between dimensions of the social environment and cardiometabolic risk factors: Systematic review and meta-analysis

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    Aim: The social environment (SE), including social contacts, norms and support, is an understudied element of the living environment which impacts health. We aim to comprehensively summarize the evidence on the association between the SE and risk factors of cardiometabolic disease (CMD). Methods: We performed a systematic review and meta-analysis based on studies published in PubMed, Scopus and Web of Science Core Collection from inception to 16 February 2021. Studies that used a risk factor of CMD, e.g., HbA1c or blood pressure, as outcome and social environmental factors such as area-level deprivation or social network size as independent variables were included. Titles and abstracts were screened in duplicate. Study quality was assessed using the Newcastle-Ottawa Scale. Data appraisal and extraction were based on the study protocol published in PROSPERO. Data were synthesized through vote counting and meta-analyses. Results: From the 7521 records screened, 168 studies reported 1050 associations were included in this review. Four meta-analyses based on 24 associations suggested that an unfavorable social environment was associated with increased risk of cardiometabolic risk factors, with three of them being statistically significant. For example, individuals that experienced more economic and social disadvantage had a higher “CVD risk scores” (OR = 1.54, 95%CI: 1.35 to 1.84). Of the 458 associations included in the vote counting, 323 (71%) pointed towards unfavorable social environments being associated with higher CMD risk. Conclusion: Higher economic and social disadvantage seem to contribute to unfavorable CMD risk factor profiles, while evidence for other dimensions of the social environment is limited
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