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.

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.

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.

The authors examined the associations of social support with socioeconomic status (SES) and with mortality, as well as how SES differences in social support might account for SES differences in mortality. Analyses were based on 9,333 participants from the British Whitehall II Study cohort, a longitudinal cohort established in 1985 among London-based civil servants who were 35–55 years of age at baseline. SES was assessed using participant's employment grades at baseline. Social support was assessed 3 times in the 24.4-year period during which participants were monitored for death. In men, marital status, and to a lesser extent network score (but not low perceived support or high negative aspects of close relationships), predicted both all-cause and cardiovascular mortality. Measures of social support were not associated with cancer mortality. Men in the lowest SES category had an increased risk of death compared with those in the highest category (for all-cause mortality, hazard ratio = 1.59, 95% confidence interval: 1.21, 2.08; for cardiovascular mortality, hazard ratio = 2.48, 95% confidence interval: 1.55, 3.92). Network score and marital status combined explained 27% (95% confidence interval: 14, 43) and 29% (95% confidence interval: 17, 52) of the associations between SES and all-cause and cardiovascular mortality, respectively. In women, there was no consistent association between social support indicators and mortality. The present study suggests that in men, social isolation is not only an important risk factor for mortality but is also likely to contribute to differences in mortality by SES.

Prospective data on depressive symptoms and blood pressure (BP) are scarce, and the impact of age on this association is poorly understood. The present study examines longitudinal trajectories of depressive episodes and the probability of hypertension associated with these trajectories over time. Participants were 6,889 men and 3,413 women London based civil servants, aged 35–55 years at baseline, followed for 24 years between 1985 and 2009. Depressive episode (defined as scoring 4 or more on the General Health Questionnaire-Depression subscale or using prescribed antidepressant medication) and hypertension (systolic/diastolic blood pressure ≥ 140/90 mm Hg or use of antihypertensive medication) were assessed concurrently at five medical examinations. In the fully adjusted longitudinal logistic regression analyses based on Generalized-Estimating-Equations using age as the time scale, participants in the “increasing depression” group had a 24% (p<0.05) lower risk of hypertension at ages 35–39, compared to those in the “low/transient depression” group. However, there was a faster age-related increase in hypertension in the “increasing depression” group, corresponding to a 7% (p<0.01) greater increase in the odds of hypertension for every each five-year increase in age. A higher risk of hypertension in the first group of participants was not evident before age 55. A similar pattern of association was observed in men and women although it was stronger in men. This study suggests that the risk of hypertension increases with repeated experience of depressive episodes over time and becomes evident in later adulthood.

Background

Father’s occupational position, education and height have all been used to examine the effects of adverse early life socioeconomic circumstances on health, but it remains unknown whether they predict mortality equally well.

Methods

We used pooled data on 18393 men and 7060 women from the Whitehall-II and GAZEL cohorts to examine associations between early life socioeconomic circumstances and all-cause and cause-specific mortality.

Results

During the 20-year follow-up period, 1487 participants died. Education had a monotonic association with all mortality outcomes, the age, sex and cohort adjusted Hazard Ratio (HR) for the lowest versus the highest educational group was 1.45 (95% Confidence Interval (CI): 1.24,1.69) for all-cause mortality. There was evidence of a U-shaped association between height and all-cause, cancer and cardiovascular mortality, robust to adjustment for the other indicators (HR=1.41; 95% CI: 1.03,1.93 for those shorter-than-average and HR=1.36; 95% CI: 0.98,1.88 for those taller-than-average for cardiovascular (CVD) mortality). Greater all-cause and cancer mortality was observed in participants whose father’s occupational position was manual rather than non-manual (HR=1.11; 95% CI: 1.00,1.23 for all-cause mortality), but the risks were attenuated after adjusting for education and height.

Conclusions

The association between early life socioeconomic circumstances and mortality depends on the socioeconomic indicator used and the cause of death examined. Height is not a straightforward measure of early life socioeconomic circumstances as taller people do not have a health advantage for all mortality outcomes.

Aims

Vascular risk factors are associated with cognitive impairment and dementia, although most of the research in this domain focuses on cerebrovascular factors. We examined the relationship between the recently developed Framingham general cardiovascular risk profile and cognitive function and 10-year decline in late midlife.

Methods and results

Study sample comprised of 3486 men and 1341 women, mean age 55 years [standard deviation (SD)=6], from the Whitehall II study, a longitudinal British cohort study. The Framingham General Cardiovascular Risk profile, assessed between 1997 and 1999, included age, sex, HDL cholesterol, total cholesterol, systolic blood pressure, smoking status, and diabetes status. Measures of cognitive function consisted of tests of reasoning (Alice Heim 4-I), memory, phonemic and semantic fluency, and vocabulary (Mill-Hill), assessed three times (1997–1999, 2002–2004, 2007–2009) over 10 years. In cross-sectional age-adjusted models, 10% point increments in cardiovascular risk were associated with poor performance in all cognitive domains in both men and women (all P-values <0.001). In models adjusted for age, ethnicity, marital status, and education, 10% higher cardiovascular risk was associated with greater overall 10-year cognitive decline in men, reasoning in particular (−0.47; 95% CI: −0.81, −0.11).

Conclusion

In middle-aged individuals free of cardiovascular disease, an adverse cardiovascular risk profile is associated with poor cognitive function, and decline in at least one cognitive domain in men.

Objective

To examine the association between adult education and child mortality, and to explore the influence of other socioeconomic markers - caste, household wealth and urbanization - on this association.

Methods

Data were drawn from the 1998–1999 Indian National Family Health Survey from 26 states on 66367 children aged 5 or under. Adult education, head of household and spouse, was categorized into 0, 1–8, and 9 or more years of schooling. Logistic regression was used to estimate associations between measures of education and child mortality in analysis adjusted for other socioeconomic markers. Effect modification by caste, household wealth and urbanization was assessed by fitting an interaction term with education.

Results

Compared to those with no education, 9 or more years of education for the head of household (OR=0.54: 95% CI=0.48–0.62) and the spouse (OR=0.44: 95% CI=0.36–0.54) was associated with lower child mortality in analyses adjusted for age, sex and state of residence. Further adjustments for caste and urbanization attenuated these associations slightly and substantially when adjustments were made for household wealth. Nevertheless, in fully adjusted models, nine or more years of education for the head of household (OR=0.81: 95% CI=0.70–0.93) and the spouse (OR=0.75: 95% CI=0.60–0.94) remained associated with child mortality. There was no effect modification by caste, household wealth and urbanization of the association between adult education and child mortality.

Conclusion

Our results suggest that adult education has a protective association with child mortality in India. Caste, household wealth and urbanization do not modify or completely attenuate this association.

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

Background

Analysis of change in health status using data from two waves can be examined either adjusted or unadjusted for baseline health status. We assess the effect of socioeconomic position (SEP) on cognitive change using both these strategies and discuss the implications of the analyses.

Methods

Data come from 1261 men and 483 women of the Whitehall II cohort study, aged 50-55 years at wave 1. Cognition was assessed at both waves using a test of verbal memory, and two tests of verbal fluency. Analysis of Variance (ANOVA) was used to estimate the effect of SEP on change score and analysis of covariance (ANCOVA) to estimate this effect adjusted for the baseline cognitive score. Then the ANCOVA estimates were corrected for bias due to measurement error (estimated based on 3-month test-retest). Finally, ANCOVA estimates were examined for increasing levels of measurement error.

Results

The results of the ANOVA suggest no effect of SEP on cognitive decline. In contrast, the ANCOVA suggests significantly greater cognitive decline in the lower SEP groups. However, the ANCOVA estimates for the effect of wave 1 cognition show evidence for regression to the mean due to the presence of measurement error. The corrected ANCOVA estimates show no association between SEP and cognitive decline.

Conclusions

We recommend caution when using ANCOVA, or adjustment for baseline, in the analysis of change using two waves of observational data.

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.

The authors examined the associations of hostility measured in adulthood with subsequent BMI assessed at four time points over a 19-year period 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 for hostility. BMI (kg/m2) was assessed at medical examination at 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 the follow-up in both sexes. In women, higher levels of hostility were associated with higher BMI at baseline and this effect remained constant over the follow-up period. In men, hostility levels were also strongly associated with BMI at baseline but results of the interaction term between time and hostility also suggest that this association increased over time, with the highest quartile of hostility gaining an excess of 0.016 kg/m2 (p=0.023) annually over the follow-up period compared to the lowest quartile. The authors conclude that the difference in BMI as function of the hostility levels in men is not stable over time.

Background

Various methodologic approaches have been used to estimate the role of risk factors in explaining the social gradient in coronary heart disease (CHD).

Objective

Our objective was to examine whether there is a discrepancy in results obtained using the relative and absolute approaches.

Methods

Data are from the Whitehall II prospective cohort study on 5,363 men who were 40–62 years old at the start of the 11-year follow-up period.

Results

One or more of the four conventional risk factors examined (smoking, hypertension, high cholesterol, and diabetes) were present for 77% of individuals in the low compared with 68% in the high socioeconomic group. The relative risk for incident CHD in the low socioeconomic group was 1.66 (95% confidence interval = 1.20 to 2.29) compared with the high group. Standardizing the distribution of risk factors in the low- and high-socioeconomic group to the overall study sample reduced relative risk by 16% and absolute risk by 14%. We also computed the population attributable risk (PAR) to indicate the reduction in CHD if the risk factor was completely removed from the population. The PAR associated with having at least one risk factor was 41% (95% confidence interval = 33% to 57%) in the high and 58% (13% to 91%) in the low socioeconomic group.

Conclusions

In situations where the goal is to remove social differences in the distribution of risk factors, conventional risk factors explain a similar proportion of the social gradient in CHD whether using the relative or absolute approaches to change in risk. This is not comparable to population attributable risk calculations, in which the goal is to completely remove the risk factors from the population. Failure to recognize that these methods address different questions seems to be the reason for discrepancies in previous results.

Objectives

Self-rated-health (SRH) is considered a valid measure of health status as it has been shown to predict mortality in several studies. We examine whether SRH predicts mortality equally well in different socioeconomic groups.

Methods

Data (14879 men and 5525 women) are drawn from GAZEL, a prospective cohort study of French public utility workers. Data on SRH and the socioeconomic measures (education, occupational position and income) were taken from the baseline questionnaire (1989), when the average age of individuals was 44.2 years (SD = 3.5). Mortality follow-up was available for a mean of 17.2 years and analysed over the first 10 years and over the entire follow-up period. Associations between SRH and mortality were assessed using Cox regression models using the Relative Index of Inequality (RII) to summarize associations.

Results

The RII for the association between SRH and mortality over the first 10 years was 6.78 (95% confidence interval (CI)=3.33–13.81) in the lowest occupational group and 2.10 (95% CI = 0.97–4.54) in the highest. For income, the RIIs were 8.82 (95% CI=4.70–16.54) for the lowest and 1.80 (95% CI=0.86–3.80) for the highest groups respectively. Findings over the full follow-up period were similar. The association between SRH and mortality was weaker in the high occupation and income groups, both in the short and the long term. The results for education were similar but generally weaker than for the other socioeconomic measures.

Conclusions

The predictive ability of SRH for mortality weakens with increasing socioeconomic advantage among middle-aged individuals. Thus SRH appears not to measure “true” health status in a similar way across socioeconomic categories.

Objectives To estimate 10 year decline in cognitive function from longitudinal data in a middle aged cohort and to examine whether age cohorts can be compared with cross sectional data to infer the effect of age on cognitive decline.

Design Prospective cohort study. At study inception in 1985-8, there were 10 308 participants, representing a recruitment rate of 73%.

Setting Civil service departments in London, United Kingdom.

Participants 5198 men and 2192 women, aged 45-70 at the beginning of cognitive testing in 1997-9.

Main outcome measure Tests of memory, reasoning, vocabulary, and phonemic and semantic fluency, assessed three times over 10 years.

Results All cognitive scores, except vocabulary, declined in all five age categories (age 45-49, 50-54, 55-59, 60-64, and 65-70 at baseline), with evidence of faster decline in older people. In men, the 10 year decline, shown as change/range of test×100, in reasoning was −3.6% (95% confidence interval −4.1% to −3.0%) in those aged 45-49 at baseline and −9.6% (−10.6% to −8.6%) in those aged 65-70. In women, the corresponding decline was −3.6% (−4.6% to −2.7%) and −7.4% (−9.1% to −5.7%). Comparisons of longitudinal and cross sectional effects of age suggest that the latter overestimate decline in women because of cohort differences in education. For example, in women aged 45-49 the longitudinal analysis showed reasoning to have declined by −3.6% (−4.5% to −2.8%) but the cross sectional effects suggested a decline of −11.4% (−14.0% to −8.9%).

Conclusions Cognitive decline is already evident in middle age (age 45-49).