Child maltreatment and cardiovascular disease: quantifying mediation pathways using UK Biobank.
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ABSTRACT:
SUBMITTER: Ho FK
PROVIDER: S-EPMC7291652 | biostudies-literature | 2020 Jun
REPOSITORIES: biostudies-literature
Publications
Child maltreatment and cardiovascular disease: quantifying mediation pathways using UK Biobank.
Ho Frederick K FK Celis-Morales Carlos C Gray Stuart R SR Petermann-Rocha Fanny F Lyall Donald D Mackay Daniel D Sattar Naveed N Minnis Helen H Pell Jill P JP
BMC medicine 20200612 1
<h4>Background</h4>Child maltreatment is associated with cardiovascular disease (CVD), but mediation pathways have not been fully elucidated. The aim of the current study was to determine and quantify the underlying pathways linking child maltreatment and CVD.<h4>Methods</h4>We conducted a retrospective cohort study using the UK Biobank. The number and types of child maltreatment, including abuse and neglect, were recalled by the participants. Lifestyle, biological, physical, and mental health f ...[more]
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Project description:Cardiovascular disease (CVD) is influenced by genetic and environmental factors. Childhood maltreatment is associated with CVD and may modify genetic susceptibility to cardiovascular risk factors. We used genetic and phenotypic data from 100,833 White British UK Biobank participants (57% female; mean age = 55.9 years). We regressed nine cardiovascular risk factors/diseases (alcohol consumption, body mass index [BMI], low-density lipoprotein cholesterol, lifetime smoking behaviour, systolic blood pressure, atrial fibrillation, coronary heart disease, type 2 diabetes, and stroke) on their respective polygenic scores (PGS) and self-reported exposure to childhood maltreatment. Effect modification was tested on the additive and multiplicative scales by including a product term (PGS*maltreatment) in regression models. On the additive scale, childhood maltreatment accentuated the effect of genetic susceptibility to higher BMI (Peffect modification: 0.003). Individuals not exposed to childhood maltreatment had an increase in BMI of 0.12 SD (95% CI: 0.11, 0.13) per SD increase in BMI PGS, compared to 0.17 SD (95% CI: 0.14, 0.19) in those exposed to all types of childhood maltreatment. On the multiplicative scale, similar results were obtained for BMI though these did not withstand to Bonferroni correction. There was little evidence of effect modification by childhood maltreatment in relation to other outcomes, or of sex-specific effect modification. Our study suggests the effects of genetic susceptibility to a higher BMI may be moderately accentuated in individuals exposed to childhood maltreatment. However, gene*environment interactions are likely not a major contributor to the excess CVD burden experienced by childhood maltreatment victims.
| S-EPMC10159177 | biostudies-literature
Project description:BackgroundChild maltreatment is associated with asthma in adults. We examined whether lifetime major depressive disorder (MDD) or lifetime generalised anxiety disorder (GAD) mediate an association between child maltreatment and current asthma among 81 105 British adults in the UK Biobank who completed a mental health survey and had complete data on child maltreatment, GAD, MDD, asthma and relevant covariates but no diagnosis of chronic obstructive pulmonary disease.MethodsChild maltreatment was ascertained based on answers to the five questions in the Childhood Trauma Screener. Two mediators, lifetime MDD and GAD, were assessed based on the Composite International Diagnostic Interview Short Form. Current asthma was defined as physician-diagnosed asthma and wheeze or whistling in the chest in the previous year. Logistic regression was used for the multivariable analysis of child maltreatment and current asthma, and a mediation analysis was conducted to estimate the contributions of lifetime MDD and lifetime GAD to the child maltreatment-current asthma association.ResultsIn a multivariable analysis, any child maltreatment was associated with asthma (adjusted OR 1.22, 95% CI 1.15-1.28; p<0.01). In a mediation analysis adjusted for household income, educational attainment, smoking status, pack-years of smoking and other covariates, lifetime GAD and lifetime MDD explained 21.8% and 32.5%, respectively, of the child maltreatment-current asthma association. Similar results were obtained after excluding current smokers and former smokers with ≥10 pack-years of smoking from the mediation analysis.ConclusionOur findings suggest that GAD and MDD mediate an association between child maltreatment and asthma in adults, independently of smoking.
| S-EPMC9481745 | biostudies-literature
Project description:BackgroundUnderstanding the mental health consequences of child maltreatment at different life stages is important in accurately quantifying the burden of maltreatment. This study investigated the association between child maltreatment and incident mental disorders in middle and older age as well as the potential mediators and moderators.MethodsThis is a retrospective cohort study of 56,082 participants from UK Biobank. Child maltreatment was recalled using the Childhood Trauma Screener. Incident mental disorders, including depressive, anxiety and affective disorders, behavioural syndromes, post-traumatic stress disorder (PTSD), schizophrenia, substance abuse, and dementia, after baseline assessment were ascertained through linkage to primary care records.FindingsThere was a dose-response relationship between child maltreatment and mental disorder. Those who experienced three or more maltreatment types had the highest risk of all mental disorders (HR 1.85, 95% CI: 1.67-2.06) followed by those who experienced two (HR 1.48, 95% CI: 1.35-1.63) and then one (HR 1.26, 95% CI: 1.19-2.35). Child maltreatment was most strongly associated with PTSD (HR 1.59, 95% CI: 1.20-2.10 P=0.001). The excess risk was largely unexplained by the included mediators. The association between child maltreatment and all mental disorders were stronger among participants who binge drank (Pinteraction=0.003) or had few social visits (Pinteraction=0.003).InterpretationThe mental health consequence of child maltreatment could last decades, even among those who had no recorded mental disorders in early adulthood. In the absence of strong mediators, prevention of child maltreatment remains the priority.FundingWellcome Trust Institutional Strategic Support Fund.
| S-EPMC8642708 | biostudies-literature
Project description:Racism drives population health inequities by shaping the unequal distribution of key social determinants of health, such as socioeconomic resources and exposure to stressors. Research on interrelationships among race, socioeconomic resources, stressors, and health has proceeded along two lines that have largely remained separate: one examining differential effects of socioeconomic resources and stressors on health across racialized groups (moderation processes), and the other examining the role of socioeconomic resources and stressors in contributing to racial inequities in health (mediation processes). We conceptually and analytically integrate these areas using race theory and a novel moderated mediation approach to path analysis to formally quantify the extent to which an array of socioeconomic resources and stressors-collectively and individually-mediate racialized health inequities among a sample of older adults from the Health and Retirement Study. Our results yield theoretical contributions by showing how the socioeconomic status-health gradient and stress processes are racialized (24% of associations examined varied by race), substantive contributions by quantifying the extent of moderated mediation of racial inequities (approximately 70%) and the relative importance of various social factors, and methodological contributions by showing how commonly used simple mediation approaches that ignore racialized moderation processes overestimate-by between 5% and 30%-the collective roles of socioeconomic status and stressors in accounting for racial inequities in health.
| S-EPMC10841571 | biostudies-literature
Project description:BackgroundIdentifying people at risk of cardiovascular diseases (CVD) is a cornerstone of preventative cardiology. Risk prediction models currently recommended by clinical guidelines are typically based on a limited number of predictors with sub-optimal performance across all patient groups. Data-driven techniques based on machine learning (ML) might improve the performance of risk predictions by agnostically discovering novel risk predictors and learning the complex interactions between them. We tested (1) whether ML techniques based on a state-of-the-art automated ML framework (AutoPrognosis) could improve CVD risk prediction compared to traditional approaches, and (2) whether considering non-traditional variables could increase the accuracy of CVD risk predictions.Methods and findingsUsing data on 423,604 participants without CVD at baseline in UK Biobank, we developed a ML-based model for predicting CVD risk based on 473 available variables. Our ML-based model was derived using AutoPrognosis, an algorithmic tool that automatically selects and tunes ensembles of ML modeling pipelines (comprising data imputation, feature processing, classification and calibration algorithms). We compared our model with a well-established risk prediction algorithm based on conventional CVD risk factors (Framingham score), a Cox proportional hazards (PH) model based on familiar risk factors (i.e, age, gender, smoking status, systolic blood pressure, history of diabetes, reception of treatments for hypertension and body mass index), and a Cox PH model based on all of the 473 available variables. Predictive performances were assessed using area under the receiver operating characteristic curve (AUC-ROC). Overall, our AutoPrognosis model improved risk prediction (AUC-ROC: 0.774, 95% CI: 0.768-0.780) compared to Framingham score (AUC-ROC: 0.724, 95% CI: 0.720-0.728, p < 0.001), Cox PH model with conventional risk factors (AUC-ROC: 0.734, 95% CI: 0.729-0.739, p < 0.001), and Cox PH model with all UK Biobank variables (AUC-ROC: 0.758, 95% CI: 0.753-0.763, p < 0.001). Out of 4,801 CVD cases recorded within 5 years of baseline, AutoPrognosis was able to correctly predict 368 more cases compared to the Framingham score. Our AutoPrognosis model included predictors that are not usually considered in existing risk prediction models, such as the individuals' usual walking pace and their self-reported overall health rating. Furthermore, our model improved risk prediction in potentially relevant sub-populations, such as in individuals with history of diabetes. We also highlight the relative benefits accrued from including more information into a predictive model (information gain) as compared to the benefits of using more complex models (modeling gain).ConclusionsOur AutoPrognosis model improves the accuracy of CVD risk prediction in the UK Biobank population. This approach performs well in traditionally poorly served patient subgroups. Additionally, AutoPrognosis uncovered novel predictors for CVD disease that may now be tested in prospective studies. We found that the "information gain" achieved by considering more risk factors in the predictive model was significantly higher than the "modeling gain" achieved by adopting complex predictive models.
| S-EPMC6519796 | biostudies-literature
Project description:AimsThe aim of this study was to investigate the cross-sectional associations of modelled residential road traffic noise with cardiovascular disease risk factors [systolic (SBP) and diastolic blood pressure (DBP), C-reactive protein, triglycerides, glycated haemoglobin, and self-reported hypertension] in UK Biobank.Methods and resultsThe UK Biobank recruited 502 651 individuals aged 40-69 years across the UK during 2006-10. Road traffic noise (Lden and Lnight) exposure for 2009 was estimated at baseline address using a simplified version of the Common Noise Assessment Methods model. We used multivariable linear and logistic regression models, adjusting for age, sex, body mass index (BMI), smoking, alcohol intake, area- and individual-level deprivation, season of blood draw, length of time at residence, and nitrogen dioxide (main model), in an analytical sample size of over 370 000 participants. Exposure to road-traffic Lden >65 dB[A], as compared to ≤55 dB[A], was associated with 0.77% [95% confidence interval (CI) 0.60%, 0.95%], 0.49% (95% CI 0.32%, 0.65%), 0.79% (95% CI 0.11%, 1.47%), and 0.12% (95% CI -0.04%, 0.28%) higher SBP, DBP, triglycerides, and glycated haemoglobin, respectively. Removing BMI from the main model yielded significant positive associations with all five markers with elevated percent changes. The associations with SBP or DBP did not appear to be impacted by hypertension medication while a positive association with prevalent self-reported hypertension was seen in the non-medicated group who exposed to a Lden level of 60-65 dB[A] (odds ratio 1.07, 95% CI 1.00, 1.15).ConclusionExposure to road traffic noise >65 dB[A], independent of nitrogen dioxide, was associated with small but adverse changes in blood pressure and cardiovascular biochemistry.
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Project description:BackgroundIndividuals of South Asian ancestry represent 23% of the global population, corresponding to 1.8 billion people, and have substantially higher risk of atherosclerotic cardiovascular disease compared with most other ethnicities. US practice guidelines now recognize South Asian ancestry as an important risk-enhancing factor. The magnitude of enhanced risk within the context of contemporary clinical care, the extent to which it is captured by existing risk estimators, and its potential mechanisms warrant additional study.MethodsWithin the UK Biobank prospective cohort study, 8124 middle-aged participants of South Asian ancestry and 449 349 participants of European ancestry who were free of atherosclerotic cardiovascular disease at the time of enrollment were examined. The relationship of ancestry to risk of incident atherosclerotic cardiovascular disease-defined as myocardial infarction, coronary revascularization, or ischemic stroke-was assessed with Cox proportional hazards regression, along with examination of a broad range of clinical, anthropometric, and lifestyle mediators.ResultsThe mean age at study enrollment was 57 years, and 202 405 (44%) were male. Over a median follow-up of 11 years, 554 of 8124 (6.8%) individuals of South Asian ancestry experienced an atherosclerotic cardiovascular disease event compared with 19 756 of 449 349 (4.4%) individuals of European ancestry, corresponding to an adjusted hazard ratio of 2.03 (95% CI, 1.86-2.22; P<0.001). This higher relative risk was largely consistent across a range of age, sex, and clinical subgroups. Despite the >2-fold higher observed risk, the predicted 10-year risk of cardiovascular disease according to the American Heart Association/American College of Cardiology Pooled Cohort equations and QRISK3 equations was nearly identical for individuals of South Asian and European ancestry. Adjustment for a broad range of clinical, anthropometric, and lifestyle risk factors led to only modest attenuation of the observed hazard ratio to 1.45 (95% CI, 1.28-1.65, P<0.001). Assessment of variance explained by 18 candidate risk factors suggested greater importance of hypertension, diabetes, and central adiposity in South Asian individuals.ConclusionsWithin a large prospective study, South Asian individuals had substantially higher risk of atherosclerotic cardiovascular disease compared with individuals of European ancestry, and this risk was not captured by the Pooled Cohort Equations.
| S-EPMC8355171 | biostudies-literature
Project description:PurposeWe examined (1) if child maltreatment (CM) is associated with lower health-related quality of life (HRQoL) and fewer quality-adjusted life years (QALY) over a 9-year follow-up of midlife women and (2) if adulthood psychosocial mediators could explain these associations.MethodsWomen (n = 342) completed the Childhood Trauma Questionnaire. Longitudinal HRQoL and QALY outcomes measured at five study visits include 36-item Short-Form Health Survey mental component score and physical component score and the Short Form-6 Dimension health index. Aims 1 and 2 were investigated by generalized estimating equations and sequential structural nested mean models, respectively.ResultsTwenty percent reported 2+ CM types. Compared with women without CM, women who experienced 2+ CM types reported 5- and 4-points lower scores in mental component score and physical component score, respectively, and 28 fewer healthy days per year in QALY. Low optimism, sleep problems, and low social support each explained greater than 10% of the relationship between 2+ CM and HRQoL and QALY over time.ConclusionsCM is a life-course social determinant of HRQoL and QALY throughout midlife, particularly in women who experienced 2+ CM types. Several mediators are modifiable and could be targets of interventions to mitigate the negative impact of CM on midlife HRQoL and QALY in women.
| S-EPMC7153694 | biostudies-literature
Project description:Background Therapeutic advances have reduced cardiovascular death rates in people with cardiovascular diseases (CVD). We aimed to define the rates of cardiovascular and noncardiovascular death in people with specified CVDs or accruing cardiovascular multimorbidity. Methods and Results We studied 493 280 UK residents enrolled in the UK Biobank cohort study. The proportion of deaths attributed to cardiovascular, cancer, infection, or other causes were calculated in groups defined by 9 distinct self-reported CVDs at baseline, or by the number of these CVDs at baseline. Poisson regression analyses were then used to define adjusted incidence rate ratios for these causes of death, accounting for sociodemographic factors and comorbidity. Of 27 729 deaths, 20.4% were primarily attributed to CVD, 53.6% to cancer, 5.0% to infection, and 21.0% to other causes. As cardiovascular multimorbidity increased, the proportion of cardiovascular and infection-related deaths was greater, contrasting with cancer and other deaths. Compared with people without CVD, those with 3 or more CVDs experienced adjusted incidence rate ratios of 7.0 (6.2-7.8) for cardiovascular death, 4.4 (3.4-5.6) for infection death, 1.5 (1.4-1.7) for cancer death, and 2.0 (1.7-2.4) for other causes of death. There was substantial heterogeneity in causes of death, both in terms of crude proportions and adjusted incidence rate ratios, among the 9 studied baseline CVDs. Conclusions Noncardiovascular death is common in people with CVD, although its contribution varies widely between people with different CVDs. Holistic and personalized care are likely to be important tools for continuing to improve outcomes in people with CVD.
| S-EPMC8751922 | biostudies-literature
Project description:BackgroundEmerging evidence supports a link between circadian disruption as measured by higher night-to-night variation in sleep duration and increased risk of cardiovascular disease (CVD). It remains unclear whether this association varies by CVD types or may be modified by average sleep duration and genetic risk for CVD.MethodsOur prospective analysis included 86,219 UK Biobank participants who were free from CVD when completing 7 days of accelerometer measurement in 2013-2016. Sleep irregularity was evaluated by the standard deviation (SD) of accelerometer-measured sleep duration over 7 days. Incident major CVD events, defined as fatal or nonfatal myocardial infarction (MI) and stroke, were identified through linkage to Hospital Episode Statistics data until May 31, 2022. Multivariable-adjusted Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% CIs for associations of sleep duration SD with risk for major CVD events overall and for MI and stroke separately.ResultsWe documented 2,310 incident cases of major CVD events (MI: 1,183, stroke: 1,175) over 636,258 person-years of follow-up. After adjusting for sociodemographic factors and family history of CVD, the HR (95% CI) associated with a 1-hour increase in sleep duration SD was 1.19 (1.10, 1.27) for CVD (p-trend<0.0001), 1.23 (1.11, 1.35) for MI (p-trend<0.0001), and 1.17 (1.05, 1.29) for stroke (p-trend=0.003). Additional adjustment for lifestyle factors, co-morbidities and sleep-related factors modestly attenuated these associations. Higher sleep irregularity was associated with higher CVD risk irrespective of genetic risk (p-interaction=0.43), but this association was stronger among individuals with longer average sleep duration >8 hours (p-interaction=0.006).ConclusionsHigher night-to-night variation in accelerometer-measured sleep duration was associated with consistently higher risks for major CVD events. The association did not seem to be modified by genetic risk for CVD and was more pronounced in long sleepers.
| S-EPMC11302714 | biostudies-literature