OP100 The impact of smoking on cognitive decline associated with ageing: a cross-country comparison between England and China

Background Healthy ageing represents a major societal challenge for both the UK and China, with both countries facing a marked growth in ageing populations, but less clear is the role of modifiable risk factors such as lifestyle behaviours that could have cultural and regional influences. We aimed to investigate the impact of smoking on the age-related cognitive decline over 8 years follow-up period in a cross-country comparison of England and China. Methods The data employed were from the English Longitudinal Study of Ageing (ELSA) (n=6,768) spanning over 8 years from wave 5 (20010/11) to wave 9 (2018/19), and the Chinese Health and Retirement Longitudinal Study (CHARLS) (n= 10,253) waves 1 (2011) to 4 (2018). We assessed the change in memory using immediate and delayed 10-word recall tests (max score 20) over 4 waves at every two-year follow-up within each of the two cohorts. Smoking was measured at baseline with a self-completion questionnaire. The covariates considered were age, sex, marital status, education, wealth, urbanicity, hypertension, heart problems, diabetes, depressive symptoms, and alcohol consumption. The association between smoking and cognitive decline was examined independently within each study by employing a coordinated analysis using linear mixed models and a similar set of covariates within each analytical sample. Results In England, the baseline memory was (beta (ß) =8.52, standard errors (SE)=0.20), p=0.001, while the rate of memory change was estimated with a linear slope of ß =-0.13, SE=0.03, p=0.001 per year. In China, the baseline memory was ß =7.01, SE=0.23, p=0.001 and the linear slope of memory change over time was ß =-0.39, SE=0.05, p=0.001 per year. We found a steeper memory decline for English participants who were smokers with ß =-0.04, SE=0.02), p=0.044 yearly change in memory scores compared to non-smokers independent of all covariates. A slower decline in memory was also observed for Chinese smokers ß =-0.4, SE=0.2, p=0.018 independent of all covariates. No associations were found between baseline smoking and baseline memory performance (intercept) within each study. Conclusion The overall results imply a clear and consistent detrimental effect of smoking on the rate of memory decline over almost a decade in both England and China. Public health strategies for preventing cognitive decline should target smoking cessation and support individuals in adopting healthier lifestyles worldwide

Age adjusted and multivariable logistic regression of risk factors for any hospital admissions (compared to none), ≥7 hospital admissions (compared to <7 admissions) and >20 days of hospital stay (compared to ≤20 days) from 1999–2009 in 23,740 men and women aged 40–79 years 1993–1997.

Age adjusted and multivariable logistic regression of risk factors for any hospital admissions (compared to none), ≥7 hospital admissions (compared to 20 days of hospital stay (compared to ≤20 days) from 1999–2009 in 23,740 men and women aged 40–79 years 1993–1997.</p

Alcohol consumption and future hospital usage: The EPIC-Norfolk prospective population study

<div><p>Background</p><p>Heavy drinkers of alcohol are reported to use hospitals more than non-drinkers, but it is unclear whether light-to-moderate drinkers use hospitals more than non-drinkers.</p><p>Objective</p><p>We examined the relationship between alcohol consumption in 10,883 men and 12,857 women aged 40–79 years in the general population and subsequent admissions to hospital and time spent in hospital.</p><p>Methods</p><p>Participants from the EPIC-Norfolk prospective population-based study were followed for ten years (1999–2009) using record linkage.</p><p>Results</p><p>Compared to current non-drinkers, men who reported any alcohol drinking had a lower risk of spending more than twenty days in hospital multivariable adjusted OR 0.80 (95%CI 0.68–0.94) after adjusting for age, smoking status, education, social class, body mass index and prevalent diseases. Women who were current drinkers were less likely to have any hospital admissions multivariable adjusted OR 0.84 (95%CI 0.74–0.95), seven or more admissions OR 0.77 (95% CI 0.66–0.88) or more than twenty hospital days OR 0.70 (95%CI 0.62–0.80). However, compared to lifelong abstainers, men who were former drinkers had higher risk of any hospital admissions multivariable adjusted OR 2.22 (95%CI 1.51–3.28) and women former drinkers had higher risk of seven or more admissions OR 1.30 (95%CI 1.01–1.67).</p><p>Conclusion</p><p>Current alcohol consumption was associated with lower risk of future hospital usage compared with non-drinkers in this middle aged and older population. In men, this association may in part be due to whether former drinkers are included in the non-drinker reference group but in women, the association was consistent irrespective of the choice of reference group. In addition, there were few participants in this cohort with very high current alcohol intake. The measurement of past drinking, the separation of non-drinkers into former drinkers and lifelong abstainers and the choice of reference group are all influential in interpreting the risk of alcohol consumption on future hospitalisation.</p></div

Descriptive characteristics by alcohol category for women in the EPIC-Norfolk cohort 1993–1997 and hospital admission 1999–2009.

Descriptive characteristics by alcohol category for women in the EPIC-Norfolk cohort 1993–1997 and hospital admission 1999–2009.</p

The percentage of Human Intelligence Tasks (HITs) correctly classified by the majority (>50%) of key workers (KW’s), with range of percentage of correct “votes” for each image category in brackets.

<p>(0.05c = study design 1—no previous experience; 0.05c_500_90% = study design 2—moderate experience)</p><p>The percentage of Human Intelligence Tasks (HITs) correctly classified by the majority (>50%) of key workers (KW’s), with range of percentage of correct “votes” for each image category in brackets.</p

Baseline characteristics of KW participation by study design for trials 1 and 2.

<p>(0.03c = study design 1; 0.05c = study design 2; 0.03c_500_90% = study design 3; 0.03c_5000_99% = study design 4).</p

The percentage of HITs correctly classified by the majority (>50%) of KW’s, with range of percentage of correct “votes” for each image category in brackets.

<p>The percentage of HITs correctly classified by the majority (>50%) of KW’s, with range of percentage of correct “votes” for each image category in brackets.</p

The proportion correctly identified by severity of abnormality as well as the sensitivity, specificity and area under the ROC curve (AUC) for each study design in trials 1 and 2 by classification difficulty.

<p>(0.03c = study design 1; 0.05c = study design 2; 0.03c_500_90% = study design 3; 0.03c_5000_99% = study design 4).</p

The AUC and associated 95%CI for trial 1 (0.03c) as a function of the number of KW gradings per image.

<p>The AUC increases as the number of KW gradings increases with a peak at 16 individual gradings per image. A similar curve was obtained for all study designs in both trials, although a variation was seen in the optimal number of KWs needed to achieve a peak ROC.</p

The sensitivity, specificity and area under the ROC curve (AUC) for each study design in trials 1 and 2.

<p>(0.05c = study design 1—no previous experience; 0.05c_500_90% = study design 2—moderate experience)</p><p>The sensitivity, specificity and area under the ROC curve (AUC) for each study design in trials 1 and 2.</p