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.

Background: It has been suggested that dietary patterns are associated with future risk of depressive symptoms. However, there is a paucity of prospective data that have examined the temporality of this relation.

Objective: We examined whether adherence to a healthy diet, as defined by using the Alternative Healthy Eating Index (AHEI), was prospectively associated with depressive symptoms assessed over a 5-y period.

Design: Analyses were based on 4215 participants in the Whitehall II Study. AHEI scores were computed in 1991–1993 and 2003–2004. Recurrent depressive symptoms were defined as having a Center for Epidemiologic Studies Depression Scale score ≥16 or self-reported use of antidepressants in 2003–2004 and 2008–2009.

Results: After adjustment for potential confounders, the AHEI score was inversely associated with recurrent depressive symptoms in a dose-response fashion in women (P-trend < 0.001; for 1 SD in AHEI score; OR: 0.59; 95% CI: 0.47, 0.75) but not in men. Women who maintained high AHEI scores or improved their scores during the 10-y measurement period had 65% (OR: 0.35%; 95% CI: 0.19%, 0.64%) and 68% (OR: 0.32%; 95% CI: 0.13%, 0.78%) lower odds of subsequent recurrent depressive symptoms than did women who maintained low AHEI scores. Among AHEI components, vegetable, fruit, trans fat, and the ratio of polyunsaturated fat to saturated fat components were associated with recurrent depressive symptoms in women.

Conclusion: In the current study, there was a suggestion that poor diet is a risk factor for future depression in women.

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.

Unfavorable work characteristics, such as low job control and too high or too low job demands, have been suggested to increase the likelihood of physical inactivity during leisure time, but this has not been verified in large-scale studies. The authors combined individual-level data from 14 European cohort studies (baseline years from 1985–1988 to 2006–2008) to examine the association between unfavorable work characteristics and leisure-time physical inactivity in a total of 170,162 employees (50% women; mean age, 43.5 years). Of these employees, 56,735 were reexamined after 2–9 years. In cross-sectional analyses, the odds for physical inactivity were 26% higher (odds ratio = 1.26, 95% confidence interval: 1.15, 1.38) for employees with high-strain jobs (low control/high demands) and 21% higher (odds ratio = 1.21, 95% confidence interval: 1.11, 1.31) for those with passive jobs (low control/low demands) compared with employees in low-strain jobs (high control/low demands). In prospective analyses restricted to physically active participants, the odds of becoming physically inactive during follow-up were 21% and 20% higher for those with high-strain (odds ratio = 1.21, 95% confidence interval: 1.11, 1.32) and passive (odds ratio = 1.20, 95% confidence interval: 1.11, 1.30) jobs at baseline. These data suggest that unfavorable work characteristics may have a spillover effect on leisure-time physical activity.

Lung function predicts mortality; whether it is associated with functional status in the general population remains unclear. This study examined the association of lung function with multiple measures of functioning in early old age. Data are drawn from the Whitehall II study; data on lung function (forced expiratory volume in 1 s, height FEV1), walking speed (2.44 m), cognitive function (memory and reasoning) and self-reported physical and mental functioning (SF-36) were available on 4,443 individuals, aged 50–74 years. In models adjusted for age, 1 standard deviation (SD) higher height-adjusted FEV1 was associated with greater walking speed (beta = 0.16, 95% CI: 0.13, 0.19), memory (beta = 0.09, 95% CI: 0.06, 0.12), reasoning (beta = 0.16, 95% CI: 0.13, 0.19) and self-reported physical functioning (beta = 0.13, 95% CI: 0.10, 0.16). Socio-demographic measures, health behaviours (smoking, alcohol, physical activity, fruit/vegetable consumption), body mass index (BMI) and chronic conditions explained two-thirds of the association with walking speed and self-assessed physical functioning and over 80% of the association with cognitive function. Our results suggest that lung function is a good ‘summary’ measure of overall functioning in early old age.

Objective

To examine the combined effects of depressive symptoms and resting heart rate (RHR) on mortality.

Methods

Data come from 5936 participants, aged 61 ± 6 years, from the Whitehall II study. Depressive symptoms were assessed in 2002–2004 using the center-for-epidemiologic-studies-depression-scale (score ≥ 16). RHR was measured at the same study phase via electrocardiogram. Participants were assigned to 1 of 6 risk-factor-groups based on depression status (yes/no) and RHR categories (<60, 60 – 80, >80 bpm). Mean follow-up for mortality was 5.6 years.

Results

In mutually adjusted Cox regression models, depression (hazard ratio = 1.93 p<0.001) and RHR>80 bpm (hazard ratio = 1.67, p<0.001) were independent predictors of mortality. After adjustment for potential confounding and mediating variables, participants with both depression and high RHR had a 3.0-fold higher (p<0.001) risk of death compared to depression-free participants with RHR ranging from 60 to 80 bpm. This risk is particularly marked in participants with prevalent CHD.

Conclusions

This study provides evidence that the coexistence of depressive symptoms and elevated RHR is associated with substantially increased risk of death compared to those without these two factors. This finding raises the possibility that treatments that improve both depression and RHR might improve survival.

Lung function predicts mortality, whether it is associated with functional status in the general population remains unclear. This study examined the association of lung function with multiple measures of functioning in early old age. Data are drawn from the Whitehall II study; data on lung function (forced expiratory volume in one second, height FEV1), walking speed (over 2.44 m), cognitive function (memory and reasoning), and self-reported physical and mental functioning (SF-36) were available on 4443 individuals, aged 50–74 years. In models adjusted for age, one standard deviation (SD) higher height-adjusted FEV1 was associated with greater walking speed (beta=0.16, 95% CI: 0.13, 0.19), memory (beta=0.09, 95% CI: 0.06, 0.12), reasoning (beta=0.16, 95% CI: 0.13, 0.19), and self-reported physical functioning (beta=0.13, 95% CI: 0.10, 0.16). Socio-demographic measures, health behaviours (smoking, alcohol, physical activity, fruit/vegetable consumption), BMI and chronic conditions explained two-thirds of the association with walking speed and self-assessed physical functioning and over 80% of the association with cognitive function. Our results suggest that lung function is a good “summary” measure of overall functioning in early old age.

Objectives

Cognitive reserve is associated with a lower risk of dementia but the extent to which it shapes cognitive aging trajectories remains unclear. Our objective is to examine the impact of three markers of reserve from different points in the lifecourse on cognitive function and decline in late adulthood.

Methods

Data are from 5234 men and 2220 women, mean age 56 years (standard deviation=6) at baseline, from the Whitehall II cohort study. Memory, reasoning, vocabulary, phonemic and semantic fluency were assessed three times over 10 years. Linear mixed models were used to assess the association between markers of reserve (height, education, and occupation) and cognitive decline, using the 5 cognitive tests and a global cognitive score composed of these tests.

Results

All three reserve measures were associated with baseline cognitive function, with strongest associations with occupation and the weakest with height. All cognitive functions except vocabulary declined over the 10 year follow-up period. On the global cognitive test, there was greater decline in the high occupation group (−0.27; 95% confidence interval (CI): −0.28, −0.26) compared to the intermediate (−0.23; 95% CI: −0.25, −0.22) and low groups (−0.21; 95% CI: −0.24, −0.19); p=0.001. The decline in reserve groups defined by education (p=0.82) and height (p=0.55) was similar.

Interpretation

Cognitive performance over the adult lifecourse was remarkably higher in the high reserve groups. However, rate of cognitive decline did not differ between reserve groups except occupation where there was some evidence of greater decline in the high occupation group.

Objective

To examine the combined effects of depressive symptoms and resting heart rate (RHR) on mortality.

Methods

Data come from 5936 participants, aged 61 ±6 years, from the Whitehall II study. Depressive symptoms were assessed in 2002–2004 using the center-for-epidemiologic-studies-depression-scale (score ≥16). RHR was measured at the same study phase via electrocardiogram. Participants were assigned to 1 of 6 risk-factor-groups based on depression status (yes/no) and RHR categories (<60, 60–80, >80 bpm). Mean follow-up for mortality was 5.6 years.

Results

In mutually adjusted Cox regression models, depression (hazard ratio = 1.93 p<0.001) and RHR>80 bpm (hazard ratio = 1.67, p<0.001) were independent predictors of mortality. After adjustment for potential confounding and mediating variables, participants with both depression and high RHR had a 3.0-fold higher (p<0.001) risk of death compared to depression-free participants with RHR ranging from 60 to 80 bpm. This risk is particularly marked in participants with prevalent CHD.

Conclusions

This study provides evidence that the coexistence of depressive symptoms and elevated RHR is associated with substantially increased risk of death compared to those without these two factors. This finding raises the possibility that treatments that improve both depression and RHR might improve survival.

Aims

To estimate the contribution of risk factor trends to 20-year declines in myocardial infarction (MI) incidence in British men and women.

Methods and results

From 1985 to 2004, 6379 men and 3074 women in the Whitehall II cohort were followed for incident MI and risk factor trends. Over 20 years, the age–sex-adjusted hazard of MI fell by 74% (95% confidence interval 48–87%), corresponding to an average annual decline of 6.5% (3.2–9.7%). Thirty-four per cent (20–76%) of the decline in MI hazard could be statistically explained by declining non-HDL cholesterol levels, followed by increased HDL cholesterol (17%, 10–32%), reduced systolic blood pressure (13%, 7–24%), and reduced cigarette smoking prevalence (6%, 2–14%). Increased fruit and vegetable consumption made a non-significant contribution of 7% (−1–20%). In combination, these five risk factors explained 56% (34–112%). Rising body mass index (BMI) was counterproductive, reducing the scale of the decline by 11% (5–23%) in isolation. The MI decline and the impact of the risk factors appeared similar for men and women.

Conclusion

In men and women, over half of the decline in MI risk could be accounted for by favourable risk factor time trends. The adverse role of BMI emphasizes the importance of addressing the rising population BMI.

Aims

To examine the association of alcohol consumption over 10 years with cognitive performance in different socioeconomic groups.

Design

Prospective cohort study, the French GAZEL study.

Setting

France.

Participants

Employees of France’s national electricity and gas company.

Measurements

Alcohol intake was assessed annually, beginning in 1992, using questions on frequency and quantity of alcoholic beverages consumed in a week; used to define mean consumption and trajectory of alcohol intake over 10 years. Cognitive performance among participants aged ≥55 years (N=4073) was assessed in 2002–2004 using the Digit Symbol Substitution Test (DSST), a measure of psychomotor speed, attention and reasoning. Occupational position at age 35 and education were used as the markers of socioeconomic position.

Findings

All analyses were stratified by socioeconomic position. In the low occupational group, participants consuming a mean of more than 21 drinks per week had 2.1 points lower (95% CI: −3.9, −0.3) DSST score compared to those consuming 4–14 drinks per week. In participants with primary school education, the corresponding difference was 3.6 points (95% CI: −7.1,−0.0). No association between alcohol consumption and cognitive performance was observed in the intermediate and high socioeconomic groups, defined using either occupation or education. Analysis of trajectories of alcohol consumption showed that in the low socioeconomic groups large increase or decrease in alcohol consumption was associated with lower cognitive scores compared to stable consumption.

Conclusions

Our results suggest that high alcohol consumption is associated with poorer cognitive performance only in the low socioeconomic group, possibly due to greater cognitive reserve in the higher socioeconomic groups.

The authors examined the extent to which socioeconomic position, behavior-related factors, cardiovascular risk factors, inflammatory markers, and chronic diseases explain the association between poor lung function and mortality in 4,817 participants (68.9% men) from the Whitehall II Study aged 60.8 years (standard deviation, 5.9), on average. Forced expiratory volume in 1 second (FEV1) was used to measure lung function in 2002–2004. A total of 139 participants died during a mean follow-up period of 6.4 years (standard deviation, 0.8). In a model adjusted for age and sex, being in the lowest tertile of FEV1/height2 was associated with a 1.92-fold (95% confidence interval: 1.35, 2.73) increased risk of mortality compared with being in the top 2 tertiles. Once age, sex, and smoking history were taken into account, the most important explanatory factors for this association were inflammatory markers (21.3% reduction in the FEV1/height2-mortality association), coronary heart disease, stroke, and diabetes (11.7% reduction), and alcohol consumption, diet, physical activity, and body mass index (9.8% reduction). The contribution of socioeconomic position and cardiovascular risk factors was small (≤3.5% reduction). Taken together, these factors explained 32.5% of the association. Multiple pathways link lung function to mortality; these results show inflammatory markers to be particularly important.

Objective

Depression has been widely linked to poor cognition and dementia in the elderly. However, comorbidity at older ages does not allow an assessment of the role of mental health as a risk factor for cognitive outcomes. We examined the association between depressive symptoms, measured 6 times over an 18-year period, and cognitive deficits in late midlife.

Methods

4271 men and women (35–55 years at baseline) from the Whitehall II study were followed up for 18 years during which depressive symptoms were assessed 6 times using the General Health Questionnaire depression subscale. Cognition was assessed at the most recent wave (2002–2004, mean age 61, range 50–74) using six tests: memory, reasoning, vocabulary, 2 tests of verbal fluency and the MMSE (Mini Mental State Examination). Cognitive deficit was defined as MMSE <28 and performance in the worst sex-specific quintile for the other tests.

Results

History of depressive symptoms, once or more in the 6 times assessed, had a weak association with some of the cognitive tests. However, in analysis adjusted for sociodemographic variables, diabetes, coronary heart disease, hypertension, stroke, & anti-depressant use, persistent depressive symptoms (4–6 times) were associated with cognitive deficits on all tests: memory (Odds Ratio (OR)=1.91; 95% Confidence Interval (CI)=1.36–2.67), reasoning (OR=1.60; 95% CI=1.15–2.20), vocabulary (OR=1.75; 95% CI=1.27–2.41), phonemic fluency (OR=1.40; 95% CI=1.00–1.94), semantic fluency (OR=1.68; 95% CI=1.20–2.35), and the MMSE (OR=1.76; 95% CI=1.25–2.50).

Conclusions

Our data show that depressive episodes tend to persist in some individuals and these individuals are at a greater risk of cognitive deficits in late midlife.

Aims

To estimate the contribution of risk factor trends to 20-year declines in myocardial infarction (MI) incidence in British men and women.

Methods and results

From 1985 to 2004, 6379 men and 3074 women in the Whitehall II cohort were followed for incident MI and risk factor trends. Over 20 years, the age–sex-adjusted hazard of MI fell by 74% (95% confidence interval 48–87%), corresponding to an average annual decline of 6.5% (3.2–9.7%). Thirty-four per cent (20–76%) of the decline in MI hazard could be statistically explained by declining non-HDL cholesterol levels, followed by increased HDL cholesterol (17%, 10–32%), reduced systolic blood pressure (13%, 7–24%), and reduced cigarette smoking prevalence (6%, 2–14%). Increased fruit and vegetable consumption made a non-significant contribution of 7% (−1–20%). In combination, these five risk factors explained 56% (34–112%). Rising body mass index (BMI) was counterproductive, reducing the scale of the decline by 11% (5–23%) in isolation. The MI decline and the impact of the risk factors appeared similar for men and women.

Conclusion

In men and women, over half of the decline in MI risk could be accounted for by favourable risk factor time trends. The adverse role of BMI emphasizes the importance of addressing the rising population BMI.

Objective

To examine the association of lipid-lowering drugs, change in diet and physical activity with a decline in low-density lipoprotein (LDL) cholesterol in middle age.

Design

A prospective cohort study.

Setting

The Whitehall II study.

Participants

4469 British civil servants (72% men) aged 39–62 years at baseline.

Main Outcome Measure

Change in LDL-cholesterol concentrations between the baseline (1991–3) and follow-up (2003–4).

Results

Mean LDL-cholesterol decreased from 4.38 to 3.52 mmol/l over a mean follow-up of 11.3 years. In a mutually adjusted model, a decline in LDL-cholesterol was greater among those who were taking lipid-lowering treatment at baseline (−1.14 mmol/l, n=34), or started treatment during the follow-up (−1.77 mmol/l, n=481) compared with untreated individuals (n=3954; p<0.001); among those who improved their diet—especially the ratio of white to red meat consumption and the ratio of polyunsaturated to saturated fatty acids intake—(−0.07 mmol/l, n=717) compared with those with no change in diet (n=3071; p=0.03) and among those who increased physical activity (−0.10 mmol/l, n=601) compared with those with no change in physical activity (n=3312; p=0.005). Based on these estimates, successful implementation of lipid-lowering drug treatment for high-risk participants (n=858) and favourable changes in diet (n=3457) and physical activity (n=2190) among those with non-optimal lifestyles would reduce LDL-cholesterol by 0.90 to 1.07 mmol/l in the total cohort.

Conclusions

Both lipid-lowering pharmacotherapy and favourable changes in lifestyle independently reduced LDL-cholesterol levels in a cohort of middle-aged men and women, supporting the use of multifaceted intervention strategies for prevention.

The authors examined the association of ‘g’ (general intelligence) factor and 5 specific cognitive measures assessed in 1997-1999 with mortality till 2006 (mean follow-up of 8 years) in the middle-aged Whitehall II cohort study. In age- and sex-adjusted analysis, a decrease in one standard-deviation in memory (Hazard Ratio (HR)=1.19, 95% Confidence Interval (CI): 1.02, 1.39) and in AH4-I (HR=1.16, 95%CI: 1.01, 1.35) was found to be associated with higher mortality. The association with ‘g’ factor, phonemic and semantic fluency did not reach significance at p<0.05. No association was found with vocabulary. Out of education, health behaviours and health measures, it was health behaviours that explained the greater part of the association between cognition and mortality, ranging from 21% for memory to 70% for semantic fluency. All the covariates taken together explained only 26% of the association with memory and between 33-90% for the other cognitive measures. This study suggests that ‘g’ type composite measure of cognition might not be enough to understand the associations between cognition and health.

Further analysis of data from two prospective cohorts reveals differences in the extent to which health behaviors attenuate associations between socioeconomic position and mortality outcomes.

Background

Differences in morbidity and mortality between socioeconomic groups constitute one of the most consistent findings of epidemiologic research. However, research on social inequalities in health has yet to provide a comprehensive understanding of the mechanisms underlying this association. In recent analysis, we showed health behaviours, assessed longitudinally over the follow-up, to explain a major proportion of the association of socioeconomic status (SES) with mortality in the British Whitehall II study. However, whether health behaviours are equally important mediators of the SES-mortality association in different cultural settings remains unknown. In the present paper, we examine this issue in Whitehall II and another prospective European cohort, the French GAZEL study.

Methods and Findings

We included 9,771 participants from the Whitehall II study and 17,760 from the GAZEL study. Over the follow-up (mean 19.5 y in Whitehall II and 16.5 y in GAZEL), health behaviours (smoking, alcohol consumption, diet, and physical activity), were assessed longitudinally. Occupation (in the main analysis), education, and income (supplementary analysis) were the markers of SES. The socioeconomic gradient in smoking was greater (p<0.001) in Whitehall II (odds ratio [OR]  = 3.68, 95% confidence interval [CI] 3.11–4.36) than in GAZEL (OR  = 1.33, 95% CI 1.18–1.49); this was also true for unhealthy diet (OR  = 7.42, 95% CI 5.19–10.60 in Whitehall II and OR  = 1.31, 95% CI 1.15–1.49 in GAZEL, p<0.001). Socioeconomic differences in mortality were similar in the two cohorts, a hazard ratio of 1.62 (95% CI 1.28–2.05) in Whitehall II and 1.94 in GAZEL (95% CI 1.58–2.39) for lowest versus highest occupational position. Health behaviours attenuated the association of SES with mortality by 75% (95% CI 44%–149%) in Whitehall II but only by 19% (95% CI 13%–29%) in GAZEL. Analysis using education and income yielded similar results.

Conclusions

Health behaviours were strong predictors of mortality in both cohorts but their association with SES was remarkably different. Thus, health behaviours are likely to be major contributors of socioeconomic differences in health only in contexts with a marked social characterisation of health behaviours.

Please see later in the article for the Editors' Summary

Editors' Summary

Background

The influence of the socioeconomic environment on the health of individuals and populations is well known, giving rise to the so-called social determinants of health. The social determinants of health are the conditions in which people are born, grow, live, work, and age, including the health system. These circumstances are shaped by the distribution of money, power, and resources at global, national, and local levels, which are themselves influenced by policy choices. The social determinants of health are mostly responsible for health inequities—the unfair and avoidable differences in health status seen within and between countries. In addition, health-damaging behaviors are often strongly socially patterned. For example, material constraints, lack of knowledge, and limited opportunities to follow health promoting messages often act as barriers that prevent those from lower socioeconomic groups to adopt a healthy lifestyle. Yet the extent to which health behaviors explain social inequalities in health remains unclear and can range from 12% to 72% according to some studies.

Why Was This Study Done?

In a recently published paper using data from the British Whitehall II cohort, the researchers showed that longitudinal assessment of health behaviors accounted for socioeconomic differences in mortality better than a single baseline assessment as used in most previous studies. (The Whitehall II study started in 1985 to examine the socioeconomic gradient in health among 10,308 London-based civil servants [6,895 men and 3,413 women] aged 35–55).

However, it is not clear whether health behaviors are equally important mediators of the socioeconomic-health association in different cultural settings. In this study, the researchers examine this issue by comparing their recent findings of the Whitehall II study with another European cohort, the French GAZEL study. (The GAZEL study started in 1989 among employees of the French national gas and electricity company totaling 20,625 employees [15,011 men and 5,614 women], aged 35–50.) The Whitehall II study and the GAZEL study have comparable designs in the way both assess socioeconomic status, health behaviors, and mortality and have a similar age range and follow-up period.

What Did the Researchers Do and Find?

The researchers included 9,771 participants from the Whitehall II study and 17,760 from the GAZEL study—mean follow up for Whitehall II was 19.5 years and for GAZEL was 16.5 years. The researchers used occupation as the main marker of socioeconomic status, and education and income as supplementary markers of socioeconomic status. Apart from a few exceptions, the researchers analyzed each cohort separately and used statistical techniques to calculate: the mortality rates per 1000 person-years for each socioeconomic group; the age- and sex-adjusted prevalence rates of smoking, heavy alcohol consumption, unhealthy diet, and physical inactivity, at the first and the last follow-up of the study for each socioeconomic group; and the differences in health behaviors prevalence between lowest and highest occupational position. Then the researchers used a statistical model to deduce the contribution of all health behaviors.

The researchers found that the socioeconomic gradient in smoking, unhealthy diet, and physical inactivity was greater in Whitehall II than in GAZEL. Socioeconomic differences in mortality were similar in the two cohorts, a hazard ratio of 1.62 in Whitehall II and 1.94 in GAZEL for lowest versus highest occupational position. Health behaviors weakened the association between socioeconomic status and mortality by 75% in Whitehall II but only by 19% in GAZEL. The supplementary analysis the researchers conducted using education and income as socioeconomic markers gave similar results.

What Do These Findings Mean?

These results suggest that the social patterning of unhealthy behaviors differs between countries. Although in both cohorts socioeconomic status and health behaviors were strong predictors of mortality, major differences in the social patterning of unhealthy behaviors in the two cohorts meant that the causal chains leading from socioeconomic status to health behaviors to mortality were different. Therefore it may be that health behaviors are likely to only be major contributors of socioeconomic differences in health in contexts with a marked social characterization of those behaviors. In order to identify the common and unique determinants of social inequalities in health in different populations, there needs to be further comparative research on the relative importance of different pathways linking socioeconomic status to health.

Additional Information

Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000419.

WHO provides information on social determinants of health

University College London provides information on the Whitehall study

The GAZEL study is available in an online open access format

The purpose of this study was to investigate whether cognitive function in midlife predicts incident coronary heart disease (CHD), followed up over 6 years. Data on 5292 (28% women, mean age 55) individuals free from CHD at baseline were drawn from the British Whitehall II study. We used Cox regression to model the association between cognition and CHD in analyses adjusted for socio-demographic variables, cardiovascular risk factors and health behaviors. The results show a one standard deviation lower score on the “general” cognitive measure and measures of reasoning and vocabulary to be associated with elevated CHD risk. There was some evidence that these effects differed between high and low socioeconomic status (SES) groups with associations only seen in the low SES group. These results were not explained by threshold effects or by the different SES groups representing different parts of the cognitive test score distribution. Three other possible explanations of these results are discussed: sub clinical vascular disease drives the observed association but no effect is observed in the high SES group due to compensation provided by greater cognitive reserve, cognition is a marker of overall bodily integrity particularly in low-SES groups, and SES is a moderator of the association between cognition and CHD, because it marks a range of other risk factors.

Context

Previous studies may have underestimated the contribution of health behaviors to social inequalities in mortality because health behaviors were assessed only at the baseline of the study.

Objective

To examine the role of health behaviors in the association between socioeconomic position and mortality and compare whether their contribution differs when assessed at only one point in time to that assessed longitudinally through the follow-up.

Main outcome measures

All-cause and cause-specific mortality.

Design, Setting, and Participants

Participants are drawn from the British Whitehall II longitudinal cohort study, established in 1985 on 10,308 London based civil servants, aged 35–55 years. Analyses are based on 9,590 men and women followed for mortality until 2009. Socioeconomic position was derived from civil service employment grade (high, intermediate and low) at baseline. Smoking, alcohol consumption, diet and physical activity were assessed four times over the follow-up.

Results

654 participants died during the follow-up. In analysis adjusted for sex and year of birth, those in the low socioeconomic position had 1.60 times higher risk of death from all causes than those in the high position (a rate difference of 1.94 per 1000 person-years). This association was attenuated by 42% (95% CI, 21%–94%) when health behaviors assessed at baseline were entered into the model and by 72% (95% CI, 42%–154%) when they were entered as time dependent covariates. The corresponding attenuations were 29% (95% CI, 11%–54%) and 45% (95% CI, 24%–79%) for cardiovascular mortality and 61% (95% CI, 16%–425%) and 94% (95% CI, 35%–595%) for non-cancer non-cardiovascular mortality. The difference between the baseline only and repeated assessments of health behaviors was mostly due to an increased explanatory power of diet (from 7% to 17% for all-cause mortality), physical activity (from 5% to 21% for all-cause mortality) and alcohol consumption (from 3% to 12% for all-cause mortality). The role of smoking, the strongest mediator in these analyses, did not change when using baseline or repeat assessments (from 32% to 35% for all-cause mortality).

Conclusions

In a civil service population in London, there was an association between socioeconomic position and mortality that was substantially accounted for by adjustment for health behaviors, particularly when the behaviors were assessed repeatedly.

The authors examined associations of health behaviors over a 17-year period, separately and in combination, with cognition in late midlife in 5123 men and women from the Whitehall II study (United Kingdom). Health behaviors were assessed in early midlife (mean age=44 years, Phase 1, 1985–1988), in midlife (mean age=56 years, Phase 5, 1997–1999) and in late midlife (mean age=61 years, Phase 7, 2002–2004). A score of the number of unhealthy behaviors (smoking, alcohol abstinence, low physical activity, and low fruit and vegetable consumption) was defined as ranging from 0 to 4. Poor (defined as scores in the worst sex-specific quintile) executive function and memory in late midlife (Phase 7) were analyzed as outcomes. Compared to those with no unhealthy behaviors, those with 3–4 unhealthy behaviors at Phase 1 (Odds Ratio (OR)=1.84; 95% Confidence Interval: 1.27,2.65), Phase 5 (OR=2.38; 1.76, 3.22) and Phase 7 (OR=2.76;2.04,3.73) were more likely to have poor executive function. A similar association was observed for memory. Odds of poor executive function and memory were the greater the more times the participant reported unhealthy behaviors over the three phases. This study suggests that both the number of unhealthy behaviors and their duration is associated with subsequent cognitive function in later life.

The authors examined associations of health behaviors over a 17-year period, separately and in combination, with cognition in late midlife in 5,123 men and women from the Whitehall II study (United Kingdom). Health behaviors were assessed in early midlife (mean age = 44 years; phase 1, 1985–1988), in midlife (mean age = 56 years; phase 5, 1997–1999), and in late midlife (mean age = 61 years; phase 7, 2002–2004). A score of the number of unhealthy behaviors (smoking, alcohol abstinence, low physical activity, and low fruit and vegetable consumption) was defined as ranging from 0 to 4. Poor (defined as scores in the worst sex-specific quintile) executive function and memory in late midlife (phase 7) were analyzed as outcomes. Compared with those with no unhealthy behaviors, those with 3–4 unhealthy behaviors at phase 1 (odds ratio (OR) = 1.84, 95% confidence interval (CI): 1.27, 2.65), phase 5 (OR = 2.38, 95% CI: 1.76, 3.22), and phase 7 (OR = 2.76, 95% CI: 2.04, 3.73) were more likely to have poor executive function. A similar association was observed for memory. The odds of poor executive function and memory were the greater the more times the participant reported unhealthy behaviors over the 3 phases. This study suggests that both the number of unhealthy behaviors and their duration are associated with subsequent cognitive function in later life.

Background

Prospective data on the association between common mental disorders and obesity are scarce, and the impact of ageing on this association is poorly understood.

Aims

To examine the association between common mental disorders and obesity (BMI≥30 kg/m2) across the adult life course.

Methods

6832 men and 3348 women aged 35-55 were screened 4 times during a 19-year follow-up (the Whitehall II study). Each screening included measurements of mental disorders (the General Health Questionnaire), weight, and height.

Results

The excess risk of obesity in the presence of mental disorders increased with age (p=0.004). The estimated proportion of obese people was 5.7% at age 40 both in the presence and absence of mental disorders, but the corresponding figures were 34.6% and 27.1% at age 70. The excess risk did not vary by sex or according to ethnic group or socioeconomic position.

Conclusion

The association between common mental disorders and obesity becomes stronger at older ages.

Conflict of interest

No conflict of interest declared (MK, GDB, ASM, HN, SS, AGT, TNA, JV, MGM, MJ)

Background

Prospective data on the association between common mental disorders and obesity are scarce, and the impact of ageing on this association is poorly understood.

Aims

To examine the association between common mental disorders and obesity (body mass index ⩾30 kg/m2) across the adult life course.

Method

The participants, 6820 men and 3346 women, aged 35–55 were screened four times during a 19-year follow-up (the Whitehall II study). Each screening included measurements of mental disorders (the General Health Questionnaire), weight and height.

Results

The excess risk of obesity in the presence of mental disorders increased with age (P = 0.004). The estimated proportion of people who were obese was 5.7% at age 40 both in the presence and absence of mental disorders, but the corresponding figures were 34.6% and 27.1% at age 70. The excess risk did not vary by gender or according to ethnic group or socioeconomic position.

Conclusions

The association between common mental disorders and obesity becomes stronger at older ages.

The extent to which the effect of risk factors on cognitive ageing is dependent on APOE ε4 remains unclear. The objective of this study is to examine whether APOE ε4 allele modifies the association between health behaviors and cognition in late midlife. Data are drawn from 5447 participants of the Whitehall II study, health behaviors were assessed in 1997-1999 (mean age = 55.6, Standard Deviation (SD) = 6.0) and APOE genotype and cognitive function in 2002-2004 (mean age = 60.9, SD = 5.9). Among APOE ε4 non-carriers, current smokers had lower scores on memory (difference in T-score = -2.49, 95%CI: -3.37, -1.60), reasoning (-2.88, 95%CI: -3.74, -2.01), phonemic (-2.66, 95%CI: -3.56, -1.76) and semantic (-2.38, 95%CI: -3.28, -1.47) fluency compared to never smokers. In APOE ε4 carriers, difference between current and never smokers was seen only for reasoning (-1.92, 95%CI: -3.31, -0.51). Interaction terms supported differential effects of smoking as a function of APOE ε4 status for memory (p = 0.01), and phonemic (p = 0.008) and semantic fluency (p = 0.02). Cognitive scores were lower among non-drinkers compared to moderate drinkers, among the sedentary participants and those who ate fruits and vegetable less than 2 times per day irrespective of APOE ε4 status. This study suggests that the APOE ε4 allele modifies the association of smoking but not that of other health behaviors - alcohol consumption, physical activity, fruit and vegetable consumption - with cognitive function in late midlife.

The authors examined the associations of hostility measured in adulthood with subsequent body mass index (BMI; weight (kg)/height (m)2) assessed at 4 time points over a 19-year period (1985–2004) in a United Kingdom cohort study. A total of 6,484 participants (4,494 men and 1,990 women) aged 35–55 years at baseline (1985–1988) completed the Cook-Medley Hostility Scale. BMI was assessed upon medical examination in phases 1 (1985–1988), 3 (1991–1993), 5 (1997–1999), and 7 (2002–2004). Mixed-models analyses of repeated measures showed clear evidence of increasing BMI over follow-up in both sexes. In women, higher levels of hostility were associated with higher BMI at baseline, and this effect remained constant throughout the follow-up period. In men, hostility levels were also strongly associated with BMI at baseline, but results for the interaction between time and hostility also suggested that this association increased over time, with persons in the highest quartile of hostility gaining an excess of 0.016 units (P = 0.023) annually over the follow-up period as compared with persons in the lowest quartile. The authors conclude that the difference in BMI as a function of hostility levels in men is not stable over time.