Unhealthy Lifestyle, Genetics and Risk of Cardiovascular Disease and Mortality in 76,958 Individuals from the UK Biobank Cohort Study.
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ABSTRACT:
SUBMITTER: Livingstone KM
PROVIDER: S-EPMC8707428 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe UK Biobank (UKB) has been used widely to examine associations between lifestyle risk factors and mortality outcomes. It is unknown whether the extremely low UKB response rate (5.5%) and lack of representativeness materially affects the magnitude and direction of effect estimates.MethodsWe used poststratification to match the UKB sample to the target population in terms of sociodemographic characteristics and prevalence of lifestyle risk factors (physical inactivity, alcohol intake, smoking, and poor diet). We compared unweighted and poststratified associations between each lifestyle risk factor and a lifestyle index score with all-cause, cardiovascular disease (CVD), and cancer mortality. We also calculated the unweighted to poststratified ratio of HR (RHR) and 95% confidence interval as a marker of effect-size difference.ResultsOf 371,974 UKB participants with no missing data, 302,009 had no history of CVD or cancer, corresponding to 3,298,958 person years of follow-up. Protective associations between alcohol use and CVD mortality observed in the unweighted UKB were substantially altered after poststratification, for example, from a hazard ratio (HR) of 0.63 (0.45-0.87) unweighted to 0.99 (0.65-1.50) poststratified for drinking ≥5 times/week versus never drinking. The magnitude of the poststratified all-cause mortality hazard ratio comparing least healthy with healthiest tertile of lifestyle risk factor index was 9% higher (95% confidence interval: 4%, 14%) than the unweighted estimates.ConclusionsLack of representativeness may distort the associations of alcohol with CVD mortality, and may underestimate health hazards among those with cumulatively the least healthy lifestyles.
| S-EPMC7850587 | biostudies-literature
Project description:BackgroundEvidence is limited regarding the association between lifestyles and cardiovascular disease (CVD), and the extent to which healthy lifestyles could offset the genetic risk of CVD in females with breast cancer (BC).MethodsFemales diagnosed as BC, who were free of CVD at baseline, from UK Biobank were included. Five modifiable lifestyle factors were considered to calculate the healthy lifestyle score, namely body mass index (BMI), smoking, alcohol drinking, dietary habits, and physical activity. The polygenetic risk score (PRS) was derived for coronary heart disease (CHD), ischemic stroke (IS), and heart failure (HF).ResultsIn 13,348 female BC survivors, there were 986 CVD events (736 CHD, 165 IS, and 353 HF) over a median of 8.01 years of follow-up. Participants with 4-5 healthy lifestyle components were associated with a decreased risk of incident CVD (HR: 0.50; 95%CI: 0.37, 0.66), CHD (HR: 0.49; 95%CI: 0.35, 0.69), IS (HR: 0.35; 95%CI: 0.19, 0.65), and HF (HR: 0.59; 95%CI: 0.36, 0.97), compared with those with 0-1 lifestyle components. Evidence for the genetic-lifestyle interaction was observed for CHD (p = 0.034) and HF (p = 0.044). Among participants at high genetic risk, a healthy lifestyle was associated with a lower risk of CHD (HR: 0.37; 95%CI: 0.24, 0.56), IS (HR: 0.37; 95%CI: 0.15, 0.93) and HF (HR: 0.39; 95%CI: 0.21, 0.73).ConclusionsOur findings suggest that BC survivors with a high genetic risk could benefit more from adherence to a healthy lifestyle in reducing CVD risk.
| S-EPMC9965301 | biostudies-literature
Project description:BackgroundPrevious studies primarily targeted the ability of polygenic risk scores (PRSs) to predict a specific disease, and only a few studies have investigated the association between genetic risk scores and cardiovascular (CV) mortality. We assessed PRSs for coronary artery disease (CAD) and type 2 diabetes (T2DM) as the predictive factors for CV mortality, independent of traditional risk factors, and further investigated the additive effect between lifestyle behavior and PRS on CV mortality.MethodsWe used genetic and phenotypic data from UK Biobank participants aged 40-69 years at baseline, collected with standardized procedures. Genome-wide PRSs were constructed using >6 million genetic variants. Cox proportional hazard models were used to analyze the relationship between PRS and CV mortality with stratification by age, sex, disease status, and lifestyle behavior.ResultsOf 377,909 UK Biobank participants having European ancestry, 3,210 (0.8%) died due to CV disease during a median follow-up of 8.9 years. CV mortality risk was significantly associated with CAD PRS [low vs. very high genetic risk groups, CAD PRS hazard ratio (HR) 2.61 (2.02-3.36)] and T2DM PRS [HR 2.08 (1.58-2.73)], respectively. These relationships remained significant even after an adjustment for a comprehensive range of demographic and clinical factors. In the very high genetic risk group, adherence to an unfavorable lifestyle was further associated with a substantially increased risk of CV mortality [favorable vs. unfavorable lifestyle with very high genetic risk for CAD PRS, HR 8.31 (5.12-13.49); T2DM PRS, HR 5.84 (3.39-10.04)]. Across all genetic risk groups, 32.1% of CV mortality was attributable to lifestyle behavior [population attributable fraction (PAF) 32.1% (95% CI 28.8-35.3%)] and 14.1% was attributable to smoking [PAF 14.1% (95% CI 12.4-15.7%)]. There was no evidence of significant interaction between PRSs and age, sex, or lifestyle behavior in predicting the risk of CV mortality.ConclusionPRSs for CAD or T2DM and lifestyle behaviors are the independent predictive factors for future CV mortality in the white, middle-aged population. PRS-based risk assessment could be useful to identify the individuals who need intensive behavioral or therapeutic interventions to reduce the risk of CV mortality.
| S-EPMC9428483 | biostudies-literature
Project description:ImportanceAccelerated aging makes adults more vulnerable to chronic diseases and death. Whether childhood adversity is associated with accelerated aging processes, and to what extent lifestyle mediates the association, remain unknown.ObjectiveTo examine the associations of childhood adversity with a phenotypic aging measure and the role of unhealthy lifestyle in mediating these associations.Design, setting, and participantsA retrospective cohort analysis was conducted using data from adult participants in the UK Biobank baseline survey (2006-2010) and online mental health survey (2016). Data analysis was performed from September 1, 2021, to February 28, 2022.ExposuresChildhood adversity, including physical neglect, emotional neglect, sexual abuse, physical abuse, and emotional abuse, was assessed retrospectively through the online mental health survey (2016).Main outcomes and measuresA phenotypic aging measure, phenotypic age acceleration, was calculated, with higher values indicating accelerated aging. Body mass index, smoking status, alcohol consumption, physical activity, and diet were combined to construct an unhealthy lifestyle score (range, 0-5, with higher scores denoting a more unhealthy lifestyle).ResultsA total of 127 495 participants aged 40 to 69 years (mean [SD] chronological age at baseline, 56.4 [7.7] years; 70 979 women [55.7%]; 123 987 White participants [97.2%]) were included. Each individual type of childhood adversity and cumulative childhood adversity score were associated with phenotypic age acceleration. For instance, compared with participants who did not experience childhood adversity, those who experienced 4 (β = 0.296, 95% CI, 0.130-0.462) or 5 (β = 0.833; 95% CI, 0.537-1.129) childhood adversities had higher phenotypic age acceleration in fully adjusted models. The formal mediation analysis revealed that unhealthy lifestyle partially mediated the associations of childhood adversity with phenotypic age acceleration by 11.8% to 42.1%.Conclusions and relevanceIn this retrospective cohort study, childhood adversity was significantly associated with acceleration of aging and, more importantly, unhealthy lifestyle partially mediated these associations. These findings reveal a pathway from childhood adversity to health in middle and early older adulthood through lifestyle and underscore the potential of more psychological strategies beyond lifestyle interventions to promote healthy aging.
| S-EPMC9449787 | biostudies-literature
Project description:The association of overweight/obesity and metabolically unhealthy (MU) with the risk of developing Barrett's esophagus (BE) remains uncertain. We evaluated whether MU and overweight/obesity are associated with increased BE incidence and whether they have a synergistic impact on BE development. We analyzed the body mass index (BMI) and metabolic indicators at baseline of 402,510 individuals from the UK Biobank with no history of BE. Overweight/obesity and MU were defined as BMI ≥ 25.0 kg/m2 and presence of ≥ 1 MU indicators, respectively. Accordingly, the participants were categorized into four groups: (1) metabolically healthy non-overweight/obesity (MHNO), (2) metabolically unhealthy non-overweight/obesity (MUNO), (3) metabolically healthy overweight/obesity (MHO), and (4) metabolically unhealthy overweight/obesity (MUO). During a median follow-up of 13.5 years, 6195 (1.5%) individuals were newly diagnosed with BE. Among them, 39,281 (9.8%), 92,000 (22.9%), 25,297 (6.3%), and 245,932 (61.1%) individuals were classified as MHNO, MUNO, MHO, and MUO, respectively. In Cox regression analyses, both MU and overweight/obesity were independently associated with BE incidence. Moreover, BE incidence was significantly higher in the MUNO, MHO, and MUO groups, compared to the MHNO group. MU and overweight/obesity are independent risk factors for BE and have a synergistic effect on BE development.
| S-EPMC11364852 | biostudies-literature
Project description:Most studies of severe/fatal COVID-19 risk have used routine/hospitalisation data without detailed pre-morbid characterisation. Using the community-based UK Biobank cohort, we investigate risk factors for COVID-19 mortality in comparison with non-COVID-19 mortality. We investigated demographic, social (education, income, housing, employment), lifestyle (smoking, drinking, body mass index), biological (lipids, cystatin C, vitamin D), medical (comorbidities, medications) and environmental (air pollution) data from UK Biobank (N = 473,550) in relation to 459 COVID-19 and 2626 non-COVID-19 deaths to 21 September 2020. We used univariate, multivariable and penalised regression models. Age (OR = 2.76 [2.18-3.49] per S.D. [8.1 years], p = 2.6 × 10-17), male sex (OR = 1.47 [1.26-1.73], p = 1.3 × 10-6) and Black versus White ethnicity (OR = 1.21 [1.12-1.29], p = 3.0 × 10-7) were independently associated with and jointly explanatory of (area under receiver operating characteristic curve, AUC = 0.79) increased risk of COVID-19 mortality. In multivariable regression, alongside demographic covariates, being a healthcare worker, current smoker, having cardiovascular disease, hypertension, diabetes, autoimmune disease, and oral steroid use at enrolment were independently associated with COVID-19 mortality. Penalised regression models selected income, cardiovascular disease, hypertension, diabetes, cystatin C, and oral steroid use as jointly contributing to COVID-19 mortality risk; Black ethnicity, hypertension and oral steroid use contributed to COVID-19 but not non-COVID-19 mortality. Age, male sex and Black ethnicity, as well as comorbidities and oral steroid use at enrolment were associated with increased risk of COVID-19 death. Our results suggest that previously reported associations of COVID-19 mortality with body mass index, low vitamin D, air pollutants, renin-angiotensin-aldosterone system inhibitors may be explained by the aforementioned factors.
| S-EPMC7882869 | biostudies-literature
Project description:BackgroundFew studies have examined associations between genetic risk for type 2 diabetes (T2D), lifestyle, clinical risk factors, and cardiovascular disease (CVD). We aimed to investigate the association of and potential interactions among genetic risk for T2D, lifestyle behavior, and metabolic risk factors with CVD.MethodsA total of 345,217 unrelated participants of white British descent were included in analyses. Genetic risk for T2D was estimated as a genome-wide polygenic risk score constructed from > 6 million genetic variants. A favorable lifestyle was defined in terms of four modifiable lifestyle components, and metabolic health status was determined according to the presence of metabolic syndrome components.ResultsDuring a median follow-up of 8.9 years, 21,865 CVD cases (6.3%) were identified. Compared with the low genetic risk group, participants at high genetic risk for T2D had higher rates of overall CVD events, CVD subtypes (coronary artery disease, peripheral artery disease, heart failure, and atrial fibrillation/flutter), and CVD mortality. Individuals at very high genetic risk for T2D had a 35% higher risk of CVD than those with low genetic risk (HR 1.35 [95% CI 1.19 to 1.53]). A significant gradient of increased CVD risk was observed across genetic risk, lifestyle, and metabolic health status (P for trend > 0.001). Those with favorable lifestyle and metabolically healthy status had significantly reduced risk of CVD events regardless of T2D genetic risk. This risk reduction was more apparent in young participants (≤ 50 years).ConclusionsGenetic risk for T2D was associated with increased risks of overall CVD, various CVD subtypes, and fatal CVD. Engaging in a healthy lifestyle and maintaining metabolic health may reduce subsequent risk of CVD regardless of genetic risk for T2D.
| S-EPMC9284808 | biostudies-literature
Project description:BackgroundBoth genetic and lifestyle factors contribute to the development of asthma, but whether unfavourable lifestyle is associated with similar increases in risk of developing asthma among individuals with varying genetic risk levels remains unknown.MethodsA healthy lifestyle score was constructed using body mass index, smoking status, physical activities and dietary pattern to further categorise into ideal, intermediate and poor groups. Genetic risk of asthma was also categorised as three groups based on the tertiles of polygenic risk score established using 212 reported and verified single-nucleotide polymorphisms of European ancestry in the UK Biobank study. We examined the risk of incident asthma related with each lifestyle level in each genetic risk group by Cox regression models.ResultsFinally, 327 124 participants without baseline asthma were included, and 157 320 (48.1%) were male. During follow-up, 6238 participants (1.9%) developed asthma. Compared to ideal lifestyle in a low genetic risk group, poor lifestyle was associated with a hazard ratio of up to 3.87 (95% CI, 2.98-5.02) for developing asthma in a high genetic risk group. There was interaction between genetic risk and lifestyle, and the population-attributable fraction of lifestyle and genetic risk were 30.2% and 30.0% respectively.ConclusionIn this large contemporary population, lifestyle and genetic factors jointly play critical roles in the development of asthma, and the effect values of lifestyle on incident adult-onset asthma were greater than that of genetic risk. Our findings highlighted the necessity of a comprehensive intervention for the prevention of asthma despite the genetic risk.
| S-EPMC10086697 | biostudies-literature
Project description:BackgroundContested evidence suggests that obesity confers no risk to health in people who have a healthy lifestyle, particularly if there are no metabolic complications of obesity. The aim was to examine the association between adherence to lifestyle recommendations and the absence of metabolic complications on the incident or fatal cardiovascular disease and all-cause mortality across different categories of body mass index (BMI).MethodsThis contemporary prospective cohort study included 339,902 adults without cardiovascular disease at baseline, recruited between 2006 and 2010 from the UK Biobank and followed until 2018-2020. The main exposures were four healthy lifestyle behaviours: never smoker, alcohol intake ≤ 112g/ week, 150 min moderate physical activity or 75 min vigorous activity/week, ≥ 5 servings of fruit or vegetables/day, and we assessed these overall and across the BMI groups. Metabolic complications of excess adiposity were hypertension, diabetes and hyperlipidaemia, and we examined whether obesity was associated with increased risk in the absence of these complications. The outcomes were all-cause mortality, death from, and incident cardiovascular disease (CVD).ResultsIndividuals who met four lifestyle recommendations but had excess weight had higher all-cause mortality; for BMI 30-34.9 kg/m2, the hazard ratio (HR) was 1.42 (95% confidence interval 1.20 to 1.68), and for BMI ≥ 35 kg/m2, HR was 2.17 (95% CI 1.71 to 2.76). The risk was lower, but still increased for people with no metabolic complications; for all-cause mortality, BMI 30-34.9 kg/m2 had an HR of 1.09 (95% CI 0.99 to 1.21), and BMI ≥ 35 kg/m2 had an HR of 1.44 (95% CI 1.19 to 1.74) for all-cause mortality. Similar patterns were found for incident and fatal CVD.ConclusionsMeeting healthy lifestyle recommendations, or the absence of metabolic complications of obesity offsets some, but not all, of the risk of subsequent CVD, and premature mortality in people with overweight or obesity. Offering support to achieve and maintain a healthy weight and to adopt healthy behaviours are likely to be important components in effective preventative healthcare.
| S-EPMC8845299 | biostudies-literature
Project description:BackgroundAlthough associations between chronic obstructive pulmonary disease (COPD) or ischaemic heart disease (IHD) and lifestyle factors or air pollution factors (referred as LAFs below) are well-established, it is unclear the influences of LAFs on the trajectory of IHD and COPD multimorbidity (referred as ICM below). Therefore, this study investigated the influences of LAFs on the trajectory of ICM from healthy to IHD or COPD, to ICM, and to all-cause death.MethodsA cohort of 339,213 participants from the UK Biobank aged 37-73 who were free of IHD and COPD were included. A multi-state model was used to analyse the influences of high-risk factors including current smoking or quitting due to illness or physician's advice, current excessive alcohol drinking, physical inactivity, unhealthy body shape, and excessive air pollution with particulates matter with an aerodynamic diameter ≤2.5 μm (PM2.5) on ICM trajectory.ResultsDuring a median follow-up of 13.74 years, 46,398 participants developed IHD or COPD (referred as IOC below), 3949 developed ICM, and 35,691 died from any cause. All five high-risk factors played crucial but different roles in these transitions. The hazard ratios (95 % confidence intervals) per one-factor increase were 1.29 (1.27-1.3), 1.38 (1.33-1.44), and 1.69 (1.56-1.84) for transitions from baseline to IOC, from IOC to ICM, and from baseline to ICM and 1.19 (1.17-1.21), 1.18 (1.15-1.21), and 1.12 (1.05-1.19) for mortality risk from baseline to all-cause death, from IOC to all-cause death, and from ICM to all-cause death, respectively.ConclusionsOur study revealed that LAFs have a stronger impact on morbidity outcomes than on morbidity outcomes. These findings provide evidence to develop strategies for managing the trajectory of ICM.
| S-EPMC11337018 | biostudies-literature