Gareth Hagger-Johnson

Fuel of the self-starter: how mood relates to proactive goal regulation.

The authors consider how multiple dimensions of affect relate to individual proactivity. They conceptualized proactivity within a goal-regulatory framework that encompasses 4 elements: envisioning, planning, enacting, and reflecting. In a study of call center agents (N = 225), evidence supported the distinctiveness of the 4 elements of proactive goal regulation. Findings further indicated that high-activated positive mood was positively associated with all elements of proactive goal regulation, and low-activated negative mood was positively associated with envisioning proactivity. These findings were further supported in a longitudinal investigation of career-related proactivity amongst medical students (N = 250). The role of affective experience in proactivity is more nuanced than previously assumed.

Association Between Questionnaire- and Accelerometer-Assessed Physical Activity: The Role of Sociodemographic Factors

The correlation between objective and self-reported measures of physical activity varies between studies. We examined this association and whether it differed by demographic factors or socioeconomic status (SES). Data were from 3,975 Whitehall II (United Kingdom, 2012–2013) participants aged 60–83 years, who completed a physical activity questionnaire and wore an accelerometer on their wrist for 9 days. There was a moderate correlation between questionnaire- and accelerometer-assessed physical activity (Spearmans r = 0.33, 95% confidence interval: 0.30, 0.36). The correlations were higher in high-SES groups than in low-SES groups (P s = 0.02), as defined by education (r = 0.38 vs. r = 0.30) or occupational position (r = 0.37 vs. r = 0.29), but did not differ by age, sex, or marital status. Of the self-reported physical activity, 68.3% came from mild activities, 25% from moderate activities, and only 6.7% from vigorous activities, but their correlations with accelerometer-assessed total physical activity were comparable (range of r s, 0.21–0.25). Self-reported physical activity from more energetic activities was more strongly associated with accelerometer data (for sports, r = 0.22; for gardening, r = 0.16; for housework, r = 0.09). High-SES persons reported more energetic activities, producing stronger accelerometer associations in these groups. Future studies should identify the aspects of physical activity that are most critical for health; this involves better understanding of the instruments being used.

Impact of Smoking on Cognitive Decline in Early Old Age: The Whitehall II Cohort Study

CONTEXT Smoking is a possible risk factor for dementia, although its impact may have been underestimated in elderly populations because of the shorter life span of smokers. OBJECTIVE To examine the association between smoking history and cognitive decline in the transition from midlife to old age. DESIGN Cohort study. SETTING The Whitehall II study. The first cognitive assessment was in 1997 to 1999, repeated over 2002 to 2004 and 2007 to 2009. PARTICIPANTS Data are from 5099 men and 2137 women in the Whitehall II study, mean age 56 years (range, 44-69 years) at the first cognitive assessment. MAIN OUTCOME MEASURES The cognitive test battery was composed of tests of memory, vocabulary, executive function (composed of 1 reasoning and 2 fluency tests), and a global cognitive score summarizing performance across all 5 tests. Smoking status was assessed over the entire study period. Linear mixed models were used to assess the association between smoking history and 10-year cognitive decline, expressed as z scores. RESULTS In men, 10-year cognitive decline in all tests except vocabulary among never smokers ranged from a quarter to a third of the baseline standard deviation. Faster cognitive decline was observed among current smokers compared with never smokers in men (mean difference in 10-year decline in global cognition=-0.09 [95% CI, -0.15 to -0.03] and executive function=-0.11 [95% CI, -0.17 to -0.05]). Recent ex-smokers had greater decline in executive function (-0.08 [95% CI, -0.14 to -0.02]), while the decline in long-term ex-smokers was similar to that among never smokers. In analyses that additionally took dropout and death into account, these differences were 1.2 to 1.5 times larger. In women, cognitive decline did not vary as a function of smoking status. CONCLUSIONS Compared with never smokers, middle-aged male smokers experienced faster cognitive decline in global cognition and executive function. In ex-smokers with at least a 10-year cessation, there were no adverse effects on cognitive decline.

Influence of individual and combined healthy behaviours on successful aging.

Background: Increases in life expectancy make it important to remain healthy for as long as possible. Our objective was to examine the extent to which healthy behaviours in midlife, separately and in combination, predict successful aging. Methods: We used a prospective cohort design involving 5100 men and women aged 42–63 years. Participants were free of cancer, coronary artery disease and stroke when their health behaviours were assessed in 1991–1994 as part of the Whitehall II study. We defined healthy behaviours as never smoking, moderate alcohol consumption, physical activity (≥ 2.5 h/wk moderate physical activity or ≥ 1 h/wk vigorous physical activity), and eating fruits and vegetables daily. We defined successful aging, measured over a median 16.3-year follow-up, as good cognitive, physical, respiratory and cardiovascular functioning, in addition to the absence of disability, mental health problems and chronic disease (coronary artery disease, stroke, cancer and diabetes). Results: At the end of follow-up, 549 participants had died and 953 qualified as aging successfully. Compared with participants who engaged in no healthy behaviours, participants engaging in all 4 healthy behaviours had 3.3 times greater odds of successful aging (95% confidence interval [CI] 2.1–5.1). The association with successful aging was linear, with the odds ratio (OR) per increment of healthy behaviour being 1.3 (95% CI 1.2–1.4; population-attributable risk for 1–4 v. 0 healthy behaviours 47%). When missing data were considered in the analysis, the results were similar to those of our main analysis. Interpretation: Although individual healthy behaviours are moderately associated with successful aging, their combined impact is substantial. We did not investigate the mechanisms underlying these associations, but we saw clear evidence of the importance of healthy behaviours for successful aging.

Obesity phenotypes in midlife and cognition in early old age The Whitehall II cohort study

Objective: To examine the association of body mass index (BMI) and metabolic status with cognitive function and decline. Methods: A total of 6,401 adults (71.2% men), aged 39–63 years in 1991–1993, provided data on BMI (normal weight 18.5–24.9 kg/m2, overweight 25–29.9 kg/m2; and obese ≥30 kg/m2) and metabolic status (abnormality defined as 2 or more of 1) triglycerides ≥1.69 mmol/L or lipid-lowering drugs, 2) systolic blood pressure ≥130 mm Hg, diastolic blood pressure ≥85 mm Hg, or antihypertensive drugs, 3) glucose ≥5.6 mmol/L or medications for diabetes, and 4) high-density lipoprotein cholesterol <1.04 mmol/L for men and <1.29 mmol/L for women). Four cognitive tests (memory, reasoning, semantic, and phonemic fluency) were administered in 1997–1999, 2002–2004, and 2007–2009, standardized to z scores, and averaged to yield a global score. Results: Of the participants, 31.0% had metabolic abnormalities, 52.7% were normal weight, 38.2% were overweight, and 9.1% were obese. Among the obese, the global cognitive score at baseline (p = 0.82) and decline (p = 0.19) over 10 years was similar in the metabolically normal and abnormal groups. In the metabolically normal group, the 10-year decline in the global cognitive score was similar (p for trend = 0.36) in the normal weight (−0.40; 95% confidence interval [CI] −0.42 to −0.38), overweight (−0.42; 95% CI −0.45 to −0.39), and obese (−0.42; 95% CI −0.50 to −0.34) groups. However, in the metabolically abnormal group, the decline on the global score was faster among obese (−0.49; 95% CI −0.55 to −0.42) than among normal weight individuals (−0.42; 95% CI −0.50 to −0.34), (p = 0.03). Conclusions: In these analyses the fastest cognitive decline was observed in those with both obesity and metabolic abnormality.

Chronic inflammation as a determinant of future aging phenotypes

Background: The importance of chronic inflammation as a determinant of aging phenotypes may have been underestimated in previous studies that used a single measurement of inflammatory markers. We assessed inflammatory markers twice over a 5-year exposure period to examine the association between chronic inflammation and future aging phenotypes in a large population of men and women. Methods: We obtained data for 3044 middle-aged adults (28.2% women) who were participating in the Whitehall II study and had no history of stroke, myocardial infarction or cancer at our study’s baseline (1997–1999). Interleukin-6 was measured at baseline and 5 years earlier. Cause-specific mortality, chronic disease and functioning were ascertained from hospital data, register linkage and clinical examinations. We used these data to create 4 aging phenotypes at the 10-year follow-up (2007–2009): successful aging (free of major chronic disease and with optimal physical, mental and cognitive functioning), incident fatal or nonfatal cardiovascular disease, death from noncardiovascular causes and normal aging (all other participants). Results: Of the 3044 participants, 721 (23.7%) met the criteria for successful aging at the 10-year follow-up, 321 (10.6%) had cardiovascular disease events, 147 (4.8%) died from noncardiovascular causes, and the remaining 1855 (60.9%) were included in the normal aging phenotype. After adjustment for potential confounders, having a high interleukin-6 level (> 2.0 ng/L) twice over the 5-year exposure period nearly halved the odds of successful aging at the 10-year follow-up (odds ratio [OR] 0.53, 95% confidence interval [CI] 0.38–0.74) and increased the risk of future cardiovascular events (OR 1.64, 95% CI 1.15–2.33) and noncardiovascular death (OR 2.43, 95% CI 1.58–3.80). Interpretation: Chronic inflammation, as ascertained by repeat measurements, was associated with a range of unhealthy aging phenotypes and a decreased likelihood of successful aging. Our results suggest that assessing long-term chronic inflammation by repeat measurement of interleukin-6 has the potential to guide clinical practice.

Sexual orientation identity in relation to smoking history and alcohol use at age 18/19: cross-sectional associations from the Longitudinal Study of Young People in England (LSYPE)

Objectives Information about the health behaviours of minority groups is essential for addressing health inequalities. We evaluated the association among lesbian, gay or bisexual (LGB) sexual orientation identity and smoking and alcohol use in young people in England. Design Data drawn from wave 6 of the Longitudinal Study of Young People in England (LSYPE). Setting Self-completion questionnaires during home visits, face-to-face interviews and web-based questionnaires. Participants Data from 7698 participants (3762 men) with information on sexual orientation identity and health behaviours at age 18/19. Outcome measures Cigarette smoking history, alcohol drinking frequency and risky single occasion drinking (RSOD). Results LGB identity was reported by 3.1% of participants (55 gay, 33 lesbian, 35 bisexual male, 111 bisexual female), 3.5% when adjusting for the survey design. Adjusting for a range of covariates, identification as lesbian/gay was found to be associated with smoking (OR=2.23, 95% CI 1.42 to 3.51), alcohol drinking >2 days/week (OR=1.99, 95% CI 1.25 to 3.17) and RSOD (OR=1.80, 95% CI 1.13 to 2.86) more than weekly. Bisexual identity was associated with smoking history (OR=1.84, 95% CI 1.30 to 2.61) but not alcohol drinking >2 days/week (OR=1.20, 95% CI 0.79 to 1.81) or RSOD (OR=1.04, 95% CI 0.71 to 2.86). Conclusions In a sample of more than 7600 young people aged 18/19 years in England, lesbian/gay identity is associated with cigarette smoking, drinking alcohol frequency and RSOD. Bisexual identity is associated with smoking but not RSOD or frequent alcohol drinking.

Combined impact of smoking and heavy alcohol use on cognitive decline in early old age: Whitehall II prospective cohort study

BACKGROUND Identifying modifiable risk factors for cognitive decline may inform prevention of dementia. AIMS To examine the combined impact of cigarette smoking and heavy alcohol consumption on cognitive decline from midlife. METHOD Prospective cohort study (Whitehall II cohort) with three clinical examinations in 1997/99, 2002/04 and 2007/09. Participants were 6473 adults (72% men), mean age 55.76 years (s.d. = 6.02) in 1997/99. Four cognitive tests, assessed three times over 10 years, combined into a global z-score (mean 0, s.d. = 1). RESULTS Age-related decline in the global cognitive score was faster in individuals who were smoking heavy drinkers than in non-smoking moderate alcohol drinkers (reference group). The interaction term (P = 0.04) suggested that the combined effects of smoking and alcohol consumption were greater than their individual effects. Adjusting for age, gender, education and chronic diseases, 10-year decline in global cognition was -0.42 z-scores (95% CI -0.45 to -0.39) for the reference group. In individuals who were heavy alcohol drinkers who also smoked the decline was -0.57 z-scores (95% CI -0.67 to -0.48); 36% faster than the reference group. CONCLUSIONS Individuals who were smokers who drank alcohol heavily had a 36% faster cognitive decline, equivalent to an age-effect of 2 extra years over 10-year follow-up, compared with individuals who were non-smoking moderate drinkers.

Neuroticism and cardiovascular disease mortality: socioeconomic status modifies the risk in women (UK Health and Lifestyle Survey).

Objective The association between personality traits and mortality might differ as a function of socioeconomic status (SES). Our aim was to evaluate the all-cause, cardiovascular disease (CVD), and cancer mortality risk associated with neuroticism or extraversion and their interactions with SES in a representative sample of the UK adult population. Methods A total of 5450 participants (2505 men) from the Health and Lifestyle Survey completed the Eysenck Personality Inventory at baseline and were monitored for vital status over 25 years. SES was defined as a latent variable comprising occupational social class, educational attainment, and income. Results A significant neuroticism-by-SES-by-sex interaction (p = .04) for CVD mortality revealed a neuroticism-by-SES interaction specific to women. Compared to women with average SES, those with both high neuroticism and low SES were at an increased risk for CVD mortality (hazard ratio = 2.02, 95% confidence interval = 1.45–2.80), whereas those with high neuroticism and high SES combined were at a decreased risk for CVD mortality (hazard ratio = 0.61, 95% confidence interval = 0.38–0.97, p for interaction = 0.003). The interaction term was not explained by health behaviors (10% attenuation) and physiological variables (11% attenuation). This interaction was not observed for all-cause and cancer mortality risks or among men for CVD mortality. Conclusions High neuroticism is a risk factor for cardiovascular mortality in women with low SES, whereas in women with higher SES, it is protective. Further research is needed to replicate this finding and identify the mechanisms behind the modifying effect of SES on neuroticism. Abbreviations HALS = Health and Lifestyle Survey CVD = cardiovascular disease EPI = Eysenck Personality Inventory SES = socioeconomic status SD = standard deviation BMI = body mass index FEV1 = forced expiratory volume in 1 second MLR = maximum likelihood with robust standard errors HR = hazard ratio

Pathways from childhood intelligence and socioeconomic status to late-life cardiovascular disease risk.

OBJECTIVE C-reactive protein (CRP) is an acute-phase marker of systemic inflammation and considered an established risk marker for cardiovascular disease (CVD) in old age. Previous studies have suggested that low childhood intelligence, lower socioeconomic status (SES) in childhood or in later life, unhealthy behaviors, poor wellbeing, and high body mass index (BMI) are associated with inflammation. Life course models that simultaneously incorporate all these risk factors can explain how CVD risks accumulate over time, from childhood to old age. METHODS Using the data from 1,091 Scottish adults (Lothian Birth Cohort Study, 1936), a path model was constructed to predict CRP at age 70 from concurrent health behaviors, self-perceived quality of life, and BMI and adulthood SES as mediating variables, and from parental SES and childhood intelligence as distal risk factors. RESULTS A well-fitting path model (CFI = .92, SRMR = .05) demonstrated significant indirect effects from childhood intelligence and parental social class to inflammation via BMI, health behaviors and quality of life (all ps < .05). Low childhood intelligence, unhealthy behaviors, and higher BMI were also direct predictors of CRP. CONCLUSIONS The life course model illustrated how CVD risks may accumulate over time, beginning in childhood and being both direct and transmitted indirectly via low adult SES, unhealthy behaviors, impaired quality of life, and high BMI. Knowledge on the childhood risk factors and their pathways to poor health can be used to identify high-risk individuals for more intensive and tailored behavior change interventions, and to develop effective public health policies.