Moderate alcohol consumption as risk factor for adverse brain outcomes and cognitive decline: longitudinal cohort study. Study design and participants. Five hundred and fifty people were randomly selected for the current Whitehall II imaging substudy (2. Whitehall II cohort study. The Whitehall II study was established in 1. University College London, with the aim of investigating the relation between socioeconomic status, stress, and cardiovascular health. It recruited 1. 0 3. Sociodemographic, health, and lifestyle variables (including alcohol use) were measured over a follow- up period of about 3. High Energy Fat Burner - Vegan Diet For Weight Loss Meal Plan Pdf High Energy Fat Burner Weight Loss Supplements During Pregnancy Weight Loss Clinic Johnson City Tn. Stair stringer calculator free download. Samsung PC Studio 7.2.24.9 41,850 downloads: Nero 9 Free 9.4.12.3d 33,427 downloads. Net, Free downloads of Stair Calculator. Advance your online legal research with Westlaw, the most preferred service year after year. Start your Free Trial today. For prevention and management of diabetes complications in children and adolescents, please refer to Section 12 “Children and Adolescents.” Atherosclerotic. ![]() The 3638323 to 1605548 a 1450464 of 14434154 in 1270284 on 508384 that 503295 is 492114 said 487849 with 423779 at 408185. The Best Practice Advocacy Centre delivers educational and continuing professional development programmes to medical practitioners and other health professional. To make the sample as representative as possible of the cohort at baseline, we drew a random list of 1. Whitehall II phase 1. Participants were sampled from high, intermediate, and low socioeconomic groups. Alcohol variables collected in each phase included units drunk a week, frequency of drinking a week over the previous year, and results of the CAGE screening questionnaire. We used weekly consumption in this analysis as there is less likelihood of a ceiling effect in comparison with drinking frequency. We calculated average alcohol use across the study as mean consumption a week averaged across all study phases. Participants were deemed “abstinent” if they consumed less than 1 unit of alcohol a week. Social class was determined according to occupation at phase 3 (highest class=1, lowest=4).
Drugs (number of psychotropic drugs reported as taken) and lifetime history of major depressive disorder (assessed by structured clinical interview for DSM IV) were assessed at the time of the scan. Information about personality traits was determined by questionnaire at phase 1 and included trait impulsivity (question: “Are you hot- headed?”). Cognitive function was assessed longitudinally at phases 3, 5, 7, 9, and 1. Short term memory recall (2. Cross sectional cognitive performance was measured at the time of the scan with the Montreal cognitive assessment (Mo. CA, education adjusted), trail making test (TMT- A and B), Rey- Osterrieth complex figure (RCF) test (copy, immediate, delay, recognition), Hopkins verbal learning test (HVLT- R; immediate, delay), Boston naming test (BNT), and digit span and digit substitution test (DSST). Full scale IQ (FSIQ) was estimated at the time of the scan with the test of premorbid functioning- UK version (TOPF- UK), with adjustment for sex and education. Participants were included in the imaging substudy if they were safe to undergo MRI and able to give informed consent. Exclusions were due to incomplete or poor quality imaging data or gross structural abnormality (such as a brain cyst), incomplete data on alcohol use (> 2 study phases data missing), and missing sociodemographic, health, or cognitive data (fig 2. We used T1- weighted and diffusion tensor (DTI) 3. T MRI sequences for these analyses. Full technical details are in the appendix. In brief, we initially examined associations between alcohol use and grey matter using voxel based morphometry, an objective method to compare grey matter density between individuals in each voxel (smallest distinguishable image volume) of the structural image. For each participant for subsequent analyses we additionally extracted hippocampal volumes (adjusted for total intracranial volume) using an automated segmentation/registration tool. Automated segmentation of the amygdala was less reliable in this sample so we did not use extracted volumes in this analysis. Three clinicians independently defined hippocampal atrophy according to visual rating (Scheltens score. Diffusion tensor images indicate the directional preference of water diffusion in neural tissue and allow inferences about the structural integrity of white matter tracts. In healthy myelinated fibres diffusion is restricted perpendicular to the longitudinal axis of the fibre—that is, it is anisotropic. We carried out voxel- wise statistical analysis of diffusion tensor data (fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD)) using tract based spatial statistics (TBSS). Outcomes. Primary outcomes were continuous measures of grey matter density in the voxel based morphometry analysis and white matter integrity in the tract based spatial statistics analysis (fractional anisotropy, mean, radial, and axial diffusivity). Visual ratings of hippocampal atrophy were dichotomised into atrophy versus no atrophy based on 0/1 on the (4 point) Scheltens scale to reflect clinical use (“abnormal” versus “normal”). Hippocampal volume (%intracranial volume) was used as a continuous variable in a multiple linear regression analysis. As cognitive outcomes we used decline in short term memory, semantic and lexical fluency, and cross sectional performance on Montreal cognitive assessment, trail making test, Rey- Osterrieth complex figure test, Hopkins verbal learning test, Boston naming test, digit span, and digit substitution test. Statistical analysis. All analyses were done with R,3. To assess representativeness of included participants we examined differences between included and excluded participants using t tests of means (continuous variables) or . According to variable type, we used means (standard deviations), medians (interquartile ranges), or numbers (percentages) to summarise sociodemographic and clinical measures for included participants who were split by safe versus unsafe average alcohol use averaged over all phases, on the basis of UK contemporary (pre- 2. Significant differences between safe and unsafe drinkers in continuous variables were tested with t tests of means (normally distributed) or Wilcoxon rank sum tests (non- normally distributed), and in binary categorical variables (and mini- mental state examination, Montreal cognitive assessment, and Framingham stroke risk score, which have lower and upper bounds) with Fisher’s exact test of proportions. In view of small group numbers (< 5) for social class, we performed a simulation test to estimate group differences. Weekly consumption of alcohol (units and grams) was described with means, standard deviations, medians, and interquartile ranges. We examined alcohol trends over time using mixed effects modelling, with time from study baseline (phase 1) as the independent variable and alcohol consumption (units/week) as the dependent variable. This method accounts for missing data and correlation of repeated measures (in this case alcohol use). We calculated intercepts (baseline consumption) and slopes (trends over study) for each participant. The ability of other variables to predict longitudinal trends of alcohol consumption was tested by inclusion of the following in the mixed effects model: age, sex, education, premorbid IQ, social class, Framingham risk score (a composite measure including smoking, cardiovascular disease or diabetes, cardiovascular drugs), exercise frequency, club attendance, voluntary work, visits with friends and family, lifetime history of major depressive disorder on the structured clinical interview for DSM IV (SCID) (yes- 2/no- 1), and current psychotropic drugs (yes- 2/no- 1). We included mean alcohol consumption (units/week) across all study phases as an independent variable in voxel based morphometry (grey matter density as dependent variable) and tract based spatial statistics analyses (FA/MD/RD/AD as dependent variable). Voxel- wise, we applied a generalised linear model (GLM) using permutation based non- parametric testing (randomise),3. TFCE). We used two post hoc tests to confirm the associations between alcohol consumption and hippocampal size after the voxel based morphometry analysis. Firstly, we used logistic regression to calculate odds ratios for left and right hippocampal atrophy versus no atrophy (visual atrophy ratings based on a cut off of 0/1 on the Scheltens scale),3. The latter was categorised as abstinent (< 1 unit, reference group), 1 to < 7 units, 1.
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