Life course trajectories of alcohol consumption in the United Kingdom using longitudinal data from nine cohort studies.

Background Alcohol consumption patterns change across life and this is not fully captured in cross-sectional series data. Analysis of longitudinal data, with repeat alcohol measures, is necessary to reveal changes within the same individuals as they age. Such data are scarce and few studies are able to capture multiple decades of the life course. Therefore, we examined alcohol consumption trajectories, reporting both average weekly volume and frequency, using data from cohorts with repeated measures that cover different and overlapping periods of life. Methods Data were from nine UK-based prospective cohorts with at least three repeated alcohol consumption measures on individuals (combined sample size of 59,397 with 174,666 alcohol observations), with data spanning from adolescence to very old age (90 years plus). Information on volume and frequency of drinking were harmonised across the cohorts. Predicted volume of alcohol by age was estimated using random effect multilevel models fitted to each cohort. Quadratic and cubic polynomial terms were used to describe non-linear age trajectories. Changes in drinking frequency by age were calculated from observed data within each cohort and then smoothed using locally weighted scatterplot smoothing. Models were fitted for men and women separately. Results We found that, for men, mean consumption rose sharply during adolescence, peaked at around 25 years at 20 units per week, and then declined and plateaued during mid-life, before declining from around 60 years. A similar trajectory was seen for women, but with lower overall consumption (peak of around 7 to 8 units per week). Frequent drinking (daily or most days of the week) became more common during mid to older age, most notably among men, reaching above 50% of men. Conclusions This is the first attempt to synthesise longitudinal data on alcohol consumption from several overlapping cohorts to represent the entire life course and illustrates the importance of recognising that this behaviour is dynamic. The aetiological findings from epidemiological studies using just one exposure measure of alcohol, as is typically done, should be treated with caution. Having a better understanding of how drinking changes with age may help design intervention strategies

Association of apolipoprotein E gene polymorphisms with blood lipids and their interaction with dietary factors

Several candidate genes have been identified in relation to lipid metabolism, and among these, lipoprotein lipase (LPL) and apolipoprotein E (APOE) gene polymorphisms are major sources of genetically determined variation in lipid concentrations. This study investigated the association of two single nucleotide polymorphisms (SNPs) at LPL, seven tagging SNPs at the APOE gene, and a common APOE haplotype (two SNPs) with blood lipids, and examined the interaction of these SNPs with dietary factors. METHODS: The population studied for this investigation included 660 individuals from the Prevention of Cancer by Intervention with Selenium (PRECISE) study who supplied baseline data. The findings of the PRECISE study were further replicated using 1238 individuals from the Caerphilly Prospective cohort (CaPS). Dietary intake was assessed using a validated food-frequency questionnaire (FFQ) in PRECISE and a validated semi-quantitative FFQ in the CaPS. Interaction analyses were performed by including the interaction term in the linear regression model adjusted for age, body mass index, sex and country. RESULTS: There was no association between dietary factors and blood lipids after Bonferroni correction and adjustment for confounding factors in either cohort. In the PRECISE study, after correction for multiple testing, there was a statistically significant association of the APOE haplotype (rs7412 and rs429358; E2, E3, and E4) and APOE tagSNP rs445925 with total cholesterol (P = 4 × 10- 4 and P = 0.003, respectively). Carriers of the E2 allele had lower total cholesterol concentration (5.54 ± 0.97 mmol/L) than those with the E3 (5.98 ± 1.05 mmol/L) (P = 0.001) and E4 (6.09 ± 1.06 mmol/L) (P = 2 × 10- 4) alleles. The association of APOE haplotype (E2, E3, and E4) and APOE SNP rs445925 with total cholesterol (P = 2 × 10- 6 and P = 3 × 10- 4, respectively) was further replicated in the CaPS. Additionally, significant association was found between APOE haplotype and APOE SNP rs445925 with low density lipoprotein cholesterol in CaPS (P = 4 × 10- 4 and P = 0.001, respectively). After Bonferroni correction, none of the cohorts showed a statistically significant SNP-diet interaction on lipid outcomes. CONCLUSION: In summary, our findings from the two cohorts confirm that genetic variations at the APOE locus influence plasma total cholesterol concentrations, however, the gene-diet interactions on lipids require further investigation in larger cohorts

Comparison of the associations of body mass index and measures of central adiposity and fat mass with coronary heart disease, diabetes, and all-cause mortality: a study using data from 4 UK cohorts.

BACKGROUND: Measures of regional adiposity have been proposed as alternatives to the measurement of body mass index (BMI) for identifying persons at risk of future disease. OBJECTIVE: The objective was to compare the magnitudes of association of BMI and alternative measurements of adiposity with coronary heart disease, diabetes, and cardiovascular disease risk factors and all-cause mortality. DESIGN: Data from 4 cohorts of adults [3937 women from the British Women's Heart and Health Study (BWHHS); 2367 and 1950 men from phases 1 and 3, respectively, of the Caerphilly Prospective Study (CaPS); 403 men and women from the Boyd Orr Study; and 789 men and women from the Maidstone-Dewsbury Study] were analyzed. RESULTS: The magnitudes of associations of BMI with incident coronary heart disease and cardiovascular disease risk factors were similar to those with measurements of central adiposity [waist circumference (WC), waist-hip ratio (WHR), or waist-height ratio (WHtR)] and more direct measurements of fat mass (bioimpedance/skinfold thickness). In CaPS (men only), there was no strong evidence of differences in the strengths of association with incident diabetes between BMI, WC, WHR, and WHtR (P for heterogeneity > 0.49 for all). In the BWHHS (women only), there was statistical evidence that WC [hazard ratio (HR): 2.35; 95% CI: 2.03, 2.73] and WHtR (HR: 2.29; 95% CI: 1.98, 2.66) were more strongly associated with diabetes than with BMI (HR: 1.80; 95% CI: 1.59, 2.04) (P for heterogeneity < 0.02 for both). Central adiposity measurements were positively associated with all-cause mortality, as was BMI, but only when those with a BMI (in kg/m(2)) <22.5 were removed from the analyses. CONCLUSION: No strong evidence supports replacing BMI in clinical or public health practice with other adiposity measures