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      Intelligence in youth and health behaviours in middle age

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      a , * , b , a , c , a
      Intelligence
      Elsevier

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          Abstract

          Objective

          We investigated the association between intelligence in youth and a range of health-related behaviours in middle age.

          Method

          Participants were the 5347 men and women who responded to the National Longitudinal Survey of Youth 1979 (NLSY-79) 2012 survey. IQ was recorded with the Armed Forces Qualification Test (AFQT) when participants were aged 15 to 23 years of age. Self-reports on exercise (moderate activity, vigorous activity, and strength training), dietary, smoking, drinking, and oral health behaviours were recorded when participants were in middle age (mean age = 51.7 years). A series of regression analyses tested for an association between IQ in youth and the different health related behaviours in middle age, while adjusting for childhood socio-economic status (SES) and adult SES.

          Results

          Higher IQ in youth was significantly associated with the following behaviours that are beneficial to health: being more likely to be able to do moderate cardiovascular activity (Odds Ratio, 95% CI) (1.72, 1.35 to 2.20, p < .001) and strength training (1.61, 1.37 to 1.90, p < .001); being less likely to have had a sugary drink in the previous week (0.75, 0.71 to 0.80, p < .001); a lower likelihood of drinking alcohol heavily (0.67, 0.61 to 0.74, p < .001); being less likely to smoke (0.60, 0.56 to 0.65, p < .001); being more likely to floss (1.47, 1.35 to 1.59, p < .001); and being more likely to say they “often” read the nutritional information (1.20, 1.09 to 1.31, p < .001) and ingredients (1.24, 1.12 to 1.36, p < .001) on food packaging compared to always reading them. Higher IQ was also linked with dietary behaviours that may or may not be linked with poorer health outcomes (i.e. being more likely to have skipped a meal (1.10, 1.03 to 1.17, p = .005) and snacked between meals (1.37, 1.26 to 1.50, p < .001) in the previous week). An inverted u-shaped association was also found between IQ and the number of meals skipped per week. Higher IQ was also linked with behaviours that are known to be linked with poorer health (i.e. a higher likelihood of drinking alcohol compared to being abstinent from drinking alcohol (1.58, 1.47 to 1.69, p < .001)). A u-shaped association was found between IQ and the amount of alcohol consumed per week and an inverted u-shaped association was found between IQ and the number of cigarettes smoked a day. Across all outcomes, adjusting for childhood SES tended to attenuate the estimated effect size only slightly. Adjusting for adult SES led to more marked attenuation but statistical significance was maintained in most cases.

          Conclusion

          In the present study, a higher IQ in adolescence was associated with a number of healthier behaviours in middle age. In contrast to these results, a few associations were also identified between higher intelligence and behaviours that may or may not be linked with poor health (i.e. skipping meals and snacking between meals) and with behaviours that are known to be linked with poor health (i.e. drinking alcohol and the number of cigarettes smoked). To explore mechanisms of association, future studies could test for a range of health behaviours as potential mediators between IQ and morbidity or mortality in later life.

          Highlights

          • Links between intelligence in youth and mid-life health behaviours were examined.

          • Higher IQ was associated with a range of healthier behaviours in mid-life.

          • There were non-linear associations between IQ and unhealthy behaviours.

          • There was essentially no attenuation after adjusting for childhood SES.

          • Statistical significance was largely maintained after adjusting for adult SES.

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          Most cited references48

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          Low cigarette consumption and risk of coronary heart disease and stroke: meta-analysis of 141 cohort studies in 55 study reports

          Abstract Objective To use the relation between cigarette consumption and cardiovascular disease to quantify the risk of coronary heart disease and stroke for light smoking (one to five cigarettes/day). Design Systematic review and meta-analysis. Data sources Medline 1946 to May 2015, with manual searches of references. Eligibility criteria for selecting studies Prospective cohort studies with at least 50 events, reporting hazard ratios or relative risks (both hereafter referred to as relative risk) compared with never smokers or age specific incidence in relation to risk of coronary heart disease or stroke. Data extraction/synthesis MOOSE guidelines were followed. For each study, the relative risk was estimated for smoking one, five, or 20 cigarettes per day by using regression modelling between risk and cigarette consumption. Relative risks were adjusted for at least age and often additional confounders. The main measure was the excess relative risk for smoking one cigarette per day (RR1_per_day−1) expressed as a proportion of that for smoking 20 cigarettes per day (RR20_per_day−1), expected to be about 5% assuming a linear relation between risk and consumption (as seen with lung cancer). The relative risks for one, five, and 20 cigarettes per day were also pooled across all studies in a random effects meta-analysis. Separate analyses were done for each combination of sex and disorder. Results The meta-analysis included 55 publications containing 141 cohort studies. Among men, the pooled relative risk for coronary heart disease was 1.48 for smoking one cigarette per day and 2.04 for 20 cigarettes per day, using all studies, but 1.74 and 2.27 among studies in which the relative risk had been adjusted for multiple confounders. Among women, the pooled relative risks were 1.57 and 2.84 for one and 20 cigarettes per day (or 2.19 and 3.95 using relative risks adjusted for multiple factors). Men who smoked one cigarette per day had 46% of the excess relative risk for smoking 20 cigarettes per day (53% using relative risks adjusted for multiple factors), and women had 31% of the excess risk (38% using relative risks adjusted for multiple factors). For stroke, the pooled relative risks for men were 1.25 and 1.64 for smoking one or 20 cigarettes per day (1.30 and 1.56 using relative risks adjusted for multiple factors). In women, the pooled relative risks were 1.31 and 2.16 for smoking one or 20 cigarettes per day (1.46 and 2.42 using relative risks adjusted for multiple factors). The excess risk for stroke associated with one cigarette per day (in relation to 20 cigarettes per day) was 41% for men and 34% for women (or 64% and 36% using relative risks adjusted for multiple factors). Relative risks were generally higher among women than men. Conclusions Smoking only about one cigarette per day carries a risk of developing coronary heart disease and stroke much greater than expected: around half that for people who smoke 20 per day. No safe level of smoking exists for cardiovascular disease. Smokers should aim to quit instead of cutting down to significantly reduce their risk of these two common major disorders.
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            Genome-wide association study of cognitive functions and educational attainment in UK Biobank (N=112 151)

            People's differences in cognitive functions are partly heritable and are associated with important life outcomes. Previous genome-wide association (GWA) studies of cognitive functions have found evidence for polygenic effects yet, to date, there are few replicated genetic associations. Here we use data from the UK Biobank sample to investigate the genetic contributions to variation in tests of three cognitive functions and in educational attainment. GWA analyses were performed for verbal–numerical reasoning (N=36 035), memory (N=112 067), reaction time (N=111 483) and for the attainment of a college or a university degree (N=111 114). We report genome-wide significant single-nucleotide polymorphism (SNP)-based associations in 20 genomic regions, and significant gene-based findings in 46 regions. These include findings in the ATXN2, CYP2DG, APBA1 and CADM2 genes. We report replication of these hits in published GWA studies of cognitive function, educational attainment and childhood intelligence. There is also replication, in UK Biobank, of SNP hits reported previously in GWA studies of educational attainment and cognitive function. GCTA-GREML analyses, using common SNPs (minor allele frequency>0.01), indicated significant SNP-based heritabilities of 31% (s.e.m.=1.8%) for verbal–numerical reasoning, 5% (s.e.m.=0.6%) for memory, 11% (s.e.m.=0.6%) for reaction time and 21% (s.e.m.=0.6%) for educational attainment. Polygenic score analyses indicate that up to 5% of the variance in cognitive test scores can be predicted in an independent cohort. The genomic regions identified include several novel loci, some of which have been associated with intracranial volume, neurodegeneration, Alzheimer's disease and schizophrenia.
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              Intelligence Predicts Health and Longevity, but Why?

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                Author and article information

                Contributors
                Journal
                Intelligence
                Intelligence
                Intelligence
                Elsevier
                0160-2896
                1 July 2018
                Jul-Aug 2018
                : 69
                : 71-86
                Affiliations
                [a ]Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, Scotland EH8 9JZ, UK
                [b ]MRC/CSO Social & Public Health Sciences Unit, 200 Renfield Street, University of Glasgow, Glasgow G2 3QB, UK
                [c ]MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton SO16 6YD, UK
                Author notes
                [* ]Corresponding author. s1457166@ 123456sms.ed.ac.uk
                Article
                S0160-2896(17)30267-2
                10.1016/j.intell.2018.04.005
                6075942
                30100645
                ea2c01b7-0c6d-4ff0-a470-47ad0bd26e64
                © 2018 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 8 September 2017
                : 30 March 2018
                : 29 April 2018
                Categories
                Article

                Clinical Psychology & Psychiatry
                Clinical Psychology & Psychiatry

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