Over 20 years between 1985 and 2004, there was a substantial decline of 74% in the age-adjusted hazard of first MI among men and women the Whitehall II cohort. Over half of the MI decline could be explained by a combination of favourable time trends in major risk factors, particularly non-HDL cholesterol, HDL cholesterol, SBP, and cigarette smoking. Rising adiposity had an adverse impact on the declining trend in MI, such that had other risk factor trends not occurred, rising BMI may have led to an increase in MI incidence over the follow-up. The MI decline and the risk factor contributions were broadly similar for men and women.
Multiple repeated measurements of risk factors, using consistent techniques for the measurement of the physical factors on each occasion, are a key strength of this study. We linked risk factor trends to coronary events at an individual level, thus avoiding the limitation of ecological analyses predominantly used to study time trends. Further, this is apparently the first analytical study of MI trends in a cohort following both men and women. We used consistent methods to identify MIs throughout the follow-up period to limit confounding of the estimate of the incidence trend by changes in diagnostic criteria. Silent MIs were not included, and the outcome thus corresponds to major CHD events. Risk factor levels were related to MI events up to 5 years ahead, based on the interval between clinic phases, and there is evidence that the benefits of smoking cessation, changes in blood lipids, and blood pressure are realized in this timeframe.18–20
There are several limitations. The analyses were necessarily based on participants who re-attended after baseline and provided complete risk factor data at one phase at least. This could introduce survival and response biases which might overestimate the favourable trends observed, due to a healthy participant effect. However, survivor bias is unlikely to be marked as survival in the cohort is high.9
Including those participants with missing risk factor data, the 20-year decline was smaller: 62% (95% CI 34–78) indicating some response bias. As we could arguably expect similar overestimation of the favourable risk factor trends, the percentage explained by each risk factor may still be comparable. HDL cholesterol values at baseline were derived from serum apolipoprotein-A1 for a subgroup of the participants. The likely impact is underestimation of the variance associated with the baseline HDL measurements but without biasing the estimate of the contribution of HDL to the MI decline. Any measurement imprecision of the risk factors, particularly likely for the questionnaire-derived dietary factors, physical activity, and alcohol consumption, may have led to the underestimation of the contribution to the MI decline. Questions on physical activity at phase 5 were more detailed than those in the earlier phases, giving more opportunity to report activity, which could lead to the underestimation of the physical activity decline and its counterproductive role. The analyses of the risk factor contributions by gender lack precision (CIs for the percentage contributions are wide), particularly for women who experienced few events (48 in total), and should thus be considered exploratory. Diabetes was not considered in this analysis. It is likely that diabetes lies on the causal pathway between several of the risk factors considered here and major CHD risk. Including diabetes in the analysis would therefore be problematic and could lead to the underestimation of the effects of the risk factors.21
The limitation of not considering diabetes is that we are unable to ascertain the extent to which the adverse effect of increasing BMI levels operates through an increase in diabetes (particularly type 2 diabetes) incidence. Effort was made to model carefully the relationship between the risk factors and MI incidence, for example, by inclusion of squared terms in the continuous variables in the Cox regression models, where significant. However, if the relationship between the risk factors and MI incidence is not fully captured in the Cox models, this may have led to the underestimation of the association between the risk factors and the MI risk and in turn the underestimation of the percentage of the decline in MI explained by the risk factors.
Trends in non-HDL cholesterol had the greatest single impact on the decline in MI incidence. The favourable time trend in non-HDL cholesterol may reflect the increasing use of lipid-regulating medication or lifestyle (e.g. diet) or some combination of factors. Statin use rose to 11% of the cohort (25% of those with high LDL cholesterol) by the end of the follow-up in 2004,22
suggesting that lipid-regulating medication may have made an appreciable contribution.
The combined contribution of the risk factors to the MI decline in the present study was similar to that found in a national cohort of men over a similar period (46%), but the individual relative impacts of the risk factors differed between the two cohorts.1
The decline in smoking prevalence had greater impact in the national cohort, possibly explained by the already lower prevalence of smokers at a later baseline in the present study (23% among men in Whitehall II compared with ~40% among men in the national cohort). The trend in and contribution of non-HDL cholesterol was smaller in the national cohort (non-HDL cholesterol fell by 0.4 mmol/L over 12 years in Whitehall II men, compared with 0.35 mmol/L over 20 years in the national cohort23
), possibly reflecting greater take-up of effective lipid-lowering medication in the present study.22
The differences may reflect the higher socioeconomic status in the present London-based cohort. Indeed, in results stratified by employment grade, the risk factor contributions in the lowest grades corresponded more closely to the national cohort findings (data not shown).
In a comparable analysis of US women, 68% of the decline in CHD incidence could be explained by combined trends in smoking, diet (decreased saturated fat, increased fibre content), and post-menopausal hormone use.6
Dietary trends in isolation accounted for the largest part of the decline (52%). The greater contribution of diet in the US investigation is likely to reflect the influence of diet on risk factors such as blood pressure and cholesterol not available in that study, but included as explanatory variables in our analysis. Any protective effect of hormone therapy is doubtful in the light of recent evidence from the Women's Health Initiative.24
Finally, the WHO MONICA Project suggested that cigarette smoking, SBP and total cholesterol together explained approximately 38% of the variation in trends in coronary event rates from the mid-1980s to the mid-1990s in men in 27 different populations.7
The lower total percentage explained may reflect the ecological analysis, using aggregate data to study variations in trends between populations, rather than studying variation over time in individuals within one population as in the present study.
In this cohort of London civil servants, there was a substantial decline in MI over two decades to 2004, more than half of which could be attributed to favourable risk factor trends, highlighting what can be achieved and emphasizing the value of measures to reduce exposure to these risk factors in the population. The risk factor trends were of comparable importance for men and women, suggesting that similar influences have operated to achieve declines in MI incidence, such that similar prevention strategies may be appropriate for both genders. Further research is needed to determine whether the residual unexplained portion of the decline in MI may be explained by early treatment, underestimated contributions of the major risk factors (reflecting imprecision in the analyses), or the influence of other risk factors. The apparent lack of association of the decline in physical activity with the time trend in MI may reflect the methodological limitations associated with quantifying activity levels or the measured decline in the activity levels was insufficient to influence MI incidence.
While the negative contribution of rising mean BMI over recent decades appears to have been outweighed by the favourable trends in other vascular risk factors, continued increases in BMI may further reduce or even reverse the decline in MI incidence. The extent to which the rise in BMI may have influenced the time trend in MI through an increase in the incidence of diabetes cannot be evaluated from this analysis. The association between type 2 diabetes and CHD risk is well established and previous studies suggest that a concurrent rise in incidence of type 2 diabetes has occurred which may be at least in part explained by rising BMI,25
supporting the influence of BMI on the time-trend in CHD operating to some extent through rising diabetes. Sharply rising trends in statin and BP-lowering medication2,23
may contribute to continuing favourable MI incidence trends in the UK and other rich countries but it is unlikely that the healthcare systems in emerging economies will have the necessary resources to provide the level of care needed to compensate for the increasing prevalence of overweight and obesity already taking place. The rising BMI in the UK and in other countries needs therefore urgent attention.