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… something that appears simple on the surface, that may be more complicated than one would think. Challenges to the Epidemiology of Aging : The REasons for Geographic And Racial Differences in Stroke Study . George Howard, DrPH UAB School of Public Health Birmingham, AL. Introduction.
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… something that appears simple on the surface, that may be more complicated than one would think Challenges to the Epidemiology of Aging: The REasons for Geographic And Racial Differences in Stroke Study George Howard, DrPH UAB School of Public Health Birmingham, AL
Introduction • Goal: Examine how age influences associations of risk factors with stroke events • Background: • Many studies have a restricted age range and can see “part of the picture” regarding the impact of age • REGARDS has both broad age range, and a large sample size, allowing assessment with age strata of risk factor associations with stroke events • Approach: • There have been 715 strokes over 5.5 years of follow-up • Proportional hazards analysis to evaluate associations with “traditional” (Framingham) stroke risk factors within age strata
Age Distribution and Stroke Events in REGARDS 190 Strokes (1.3%) 283 Strokes (3.2%) 242 Strokes (5.3%)
“Univariate” Hazard Ratio of Incident Stroke for “Traditional” Stroke Risk Factors(after adjustment for age) Hypertension Diabetes Smoking Atrial Fib LVH Heart Dis
“Univariate” & Multivariable Hazard Ratio of Incident Stroke for “Traditional” Stroke Risk Factors(after adjustment, or additional adjustment, for age) Hypertension Diabetes Smoking Atrial Fib LVH Heart Dis
Overall Analysis Conclusions • After adjustment for age, these “traditional” risk factors: • Univariately: • All significantly (p ≤ 0.0002) associated with stroke risk • Univariately, each is associated with a hazard ratio of ≈ 1.5 to 2.0 • Multivariable adjustment had only modest impact on the significance (p ≤ 0.0014) or magnitude of association (HR ≈ 1.4 to 2.0) • But what of the association within age strata?
Univariate Hazard Ratio of Incident Stroke for “Traditional” Stroke Risk FactorsShown for Young (45-64), Middle-Aged (65-74), and Old (75+) Participants Hypertension Diabetes Smoking Atrial Fib LVH Heart Dis
Univariate Hazard Ratio of Incident Stroke for “Traditional” Stroke Risk FactorsShown for Young (45-64), Middle-Aged (65-74), and Old (75+) Participants Hypertension Diabetes Smoking Atrial Fib LVH Heart Dis
Observations • Univariately • Substantial declines in the impact of hypertension, diabetes, smoking and heart disease with age • More modest decline for LVH • Initial decline, then increase, for atrial fibrillation • Hypertension, diabetes, smoking, and LVH all not even significant in the oldest age strata
Univariate Hazard Ratio of Incident Stroke for “Traditional” Stroke Risk FactorsShown for Young (45-64), Middle-Aged (65-74), and Old (75+) Participants Hypertension Diabetes Smoking Atrial Fib LVH Heart Dis
Multivariable Hazard Ratio of Incident Stroke for “Traditional” Stroke Risk FactorsShown for Young (45-64), Middle-Aged (65-74), and Old (75+) Participants Hypertension Diabetes Smoking Atrial Fib LVH Heart Dis
Observations • Univariately • Substantial declines in the impact of hypertension and diabetes with age • More modest (but still substantial) decline for smoking, heart disease and LVH • Initial decline, then increase, for atrial fibrillation • Hypertension, diabetes, smoking, and LVH all not even significant in the oldest age strata • For hypertension, diabetes, atrial fibrillation, LVH and heart disease – multivariable adjustment had: • A substantial mediating impact on risk at young ages • Little impact at older ages • Multivariable adjustment had little impact on smoking
Interpretation? • The small literature on age-related changes agrees … risk factor effects are smaller in the elderly • Should we conclude that risk factors are less important in the elderly? • … what little randomized trial data there is in the elderly shows treatment is beneficial • For example, the Systolic Hypertension in the Elderly Program (SHEP) showed a reduction from 8.2/100 participants to 5.2/100 participants for antihypertensive treatment (RR = 0.64; p = 0.0003) • … but SHEP eligibility started at 60 years • Still, what else could be driving the smaller impact at older ages?
An Alternative Explanation • Suppose the incorrect proportional hazards model is fit, h(t) = g(t)eα(HYPER)rather than h(t) = g(t)eα(HYPER) + β(OTHER) • Well … it depends • If OTHER is not correlated with HYPER … no worries … a confounder must be associated with both the exposure (HYPER) and outcome (STROKE) • However, if OTHER is correlated with HYPER ... • Then OTHER will be confounder if it is associated with stroke risk • The estimate for α will include the effect of HYPER and everything that is correlated with it (in this case OTHER) • But … this should be a constant bias if: • The impact of HYPER and OTHER is constant across age (no AGE-by-OTHER interaction) • Correlation between HYPER and OTHER is constant across age • So are these assumptions true?
Interesting … but what does this have to do with the epidemiology of aging? • Risk factors sometimes tend to be correlated (for example, the metabolic syndrome) • For example, it is expected that hypertensives are more likely to be diabetic (and obese, and dyslipidemic, and …) • Since hypertensive participants are more likely to be diabetic … omitting diabetes from the model will include part of the effect of diabetes • … but what is the association of hypertension and diabetes as a function of age?
Implications? • If diabetes is uniformly associated with stroke over ages, then omitting diabetes from a model assessing hypertension as a risk factor for stroke will: • For young ages, the effect of hypertension will be substantially overestimated … but adjustment for diabetes will substantially attenuate the effect of hypertension • At older ages, the impact of hypertension at older ages will still be overestimated (diabetes still positively correlated!), but to a much smaller effect … but adjustment for diabetes will have a much smaller attenuating effect • Hmmm … that is exactly what we saw in the univariate, then the multivariable, analyses of hypertension? • Omitting hypertension from the estimation of diabetes will have precisely the same effects (again, what we saw) • What about other factors association with hypertension?
Agreement of Risk Factors with Hypertension Smoking Atrial Fib LVH Heart Dis LVH and Heart Disease have marginally higher correlations , and modest declines Smoking and atrial Fib have low correlation, and only minimal declines
… but what does this have to do with the declines of the impact of risk factors with age? • Not only does REGARDS show this declining impact of risk factors with age … but so does nearly every study with data across a broad age range • But if we adjust for the OTHER risk factors, we get the correct estimate for HYPER • But risk factors explain less than half of incident strokes • Even with residual confounding and measurement error … there must be many unknown risk factors • Obviously, one cannot adjust for the unknown risk factors … and they may be having the same impact as the known
Could There Be “Reflections” of OTHER Risk Factors Available? • Consider the “General Health Question” Compared to others your age, how would you rate your health? Excellent Very Good Good Fair Poor Univar Stroke HR 1.00 (ref) 1.01 (0.80 – 1.28) 1.47 (1.17 – 1.84) 2.07 (1.61 – 2.66) 3.00 (2.09 – 4.32) Multi Stroke HR 1.00 (ref) 0.90 (0.71 – 1.15) 1.11 (0.87 – 1.41) 1.38 (1.05 – 1.81) 1.71 (1.15 – 2.55) … well join me on the thin ice … perhaps this is asking “How bad are your latent risk factors?” …but what are the agre-related associations of hypertension and general health?
Association of Hypertension with Self-Perceived General Health Status of Good, Fair or Poor
The “Latent” Risk Factors in the Elderly • Hence, the associations of known and “latent” (or unobserved or unknown) risk factors could also be decreasing in the elderly • Perhaps two forces are likely at work: • Elimination of those with multiple risk factors • Contamination of the control group with higher risk participants • We could also speculate that other forces could be active • Changes in the magnitude of associations with age • Synergies (interactions) between risk factors
Elimination of those with multiple risk factors • Suppose • There are only two risk factors (HYPER and OTHER) • Each is 50% prevalent and there is no correlation • 20% event rate in those without either risk factor • Each with a HR of 2.0 for both 34% 20% 50% 50% • Put simply, it is a lot easier to be a 45 year old with hypertension and the latent factor, than it is to be a 75 year old with both risk factors • As a corollary, at age 75, normotensive participants are more likely to also have OTHER than are hypertensives
Contamination of the control group with higher risk participants • With the exception of cigarette smoking, the prevalence of most risk factors increases with age
Age-Related Changes in the Prevalence of Risk Factors • So … with the exception of cigarette smoking, the prevalence of most risk factors increases with age • But this is happening while the associations between risk factors are decreasing • These prevalences have to be increasing somewhere … and the only other place it can is in the control group • A more difficult question … “Does the prevalence of the latent factor increase with age?” • Again put simply • In the young, the impact of risk factors can be clearly seen • In the old, there is more “noise” in the system, and seeing the impact of any one risk factor is more difficult
Conclusions • In REGARDS (and in practically all other studies with data) risk factors show a declining impact with aging • This could be a true effect … or it could be a bias introduced through: • An age-related change in the correlation between risk factors (particularly with latent factors) • Increasing “noise” making the identification of any singe factor in the elderly more difficult • At some level, it may not make a difference … risk differences of older individuals with/without risk are smaller
Potential Implications? • In study planning, anticipate smaller risk factor effects in the elderly (and larger studies) • Interpret the absence of associations with caution • The lack of an association may not imply that treatment does not reduce risk • It is not clear whether studies in the young are overestimating associations, or studies in the elderly are underestimating effects … but it is clear one of these is true! • Because the declining impact of risk factors may be attributable to biases • A more broad risk factor assessment may be warranted? • Perhaps heightened concern for precision in measurement? • The link to randomized treatment trials is more tenuous