dose-response relation between physical activity and health: an observational epidemiologic...

Dose-Response Relation betweenPhysical Activity and Health:

An Observational Epidemiologic Perspective

I-Min Lee, MD, ScD

“The paradox of the clinical trial is that it is the best

way to assess whether an intervention works, but is

arguably the worst way to assess who will benefit

from it.”

“It must be recognised explicitly that, in order to

apply the results of the trials to individual patients,

there must be a parallel investment in observational

studies – both quantitative and qualitative.”

Mant; Lancet 1999;353:743-6

Clinical Trials vs. Observational Studies

Research Direction

1950’s to Does PA decrease risk

early 1990’s of chronic diseases?

early 1990’s We know PA decreasesonwards risk of chronic diseases:

- how much?- how intense?- what duration?- etc.“dose-response”

• “Describes the change in effect … caused by

differing levels of exposure to a stressor”; central

to determining safe and hazardous levels for drugs

and pollutants (Wikipedia)

• PubMed search for “dose response” and

“exercise” – studies as far back as 1967, but

mainly related to drug effects; e.g., effect of beta-

blocker on exercise tolerance in angina patients

• In the mid-1980’s, we begin to see the term used

for the study of different doses of PA

• ? Influence of medical/epidemiologic principles

Dose-Response: Definition

“Most of the evidence currently available

seems to be related to the effects

(benefits or risks) of regular physical

activity rather than to the relationship

between dose and response.”

Dose-Response Issues Concerning PA and Health:An Evidence-Based Symposium(Hockley Valley, Canada, 2000)

What Do We Know (2000)?

“Participation in aerobic and muscle-strengthening

physical activities above minimum recommended

amounts provides additional health benefits ...”

It is well-documented that PA of longer duration or

higher intensity is associated with additional risk

decrements but the exact shape of the … curve

remains unclear and may vary depending on the

health outcome of interest and baseline PA level …”

What Do We Know (2007)?

Physical activity and public health: Updated recommendation for adults from ACSM/AHA. Haskell et al, MSSE 2007;39:1423-34

Why the Interest in Dose-Response?

1. Knowledge is useful in clinical and public health setting

2. Dose-response is one criterion used to judge cause-and-effect relation in observational studies (most studies of PA-chronic disease are observational)

3. Dose-response can help us understand the biology underlying physical activity-disease relation

Above average

Average

Below average

Sedentary Moderate Very High

Exercise Workload

Immuno-surveillance

Infection risk

Nieman DC, MSSE 2000;32:S406-S411

Issues to Consider in Studies of Dose-Response

• “Physical activity” is ambiguous; need to specify which measure is of interest (total volume? intensity? duration?)

• Analogy: I want to study the dose-response between “diet” and health (total calories? fat calories? meat intake? etc.)

Definition of Physical Activity

• Most epi studies use questionnaires

• Questionnaire usually tested for reliability (repeatability) and validity (“correctness”)

• But, note that high correlations for validity don’t necessarily mean the absolute values (e.g, comparing questionnaire and doubly-labeled water) agree

Translation of Physical Activity from Epidemiologic Studies

• E.g., Harvard alumni questionnaire: comparing qx estimate and doubly-labeled water, r = 0.67

• Qx estimate of PA = 716 kcal/day

• But, doubly-labeled water estimate of PA (total EE minus RMR) = 802 kcal/day

• Not surprising, since qx estimates walking, stairs, sports/recreation ONLY

• (Doubly-labeled water minus TEE) calculates ALL physical activity (including, e.g., brushing teeth, fixing meals, etc.)

Inter-relations among PA components (1)

• Inter-relations among PA components contribute to complexity of analyses

• Appropriate analyses need to be conducted, to get “right” answer

• E.g., if we see these rates of disease associated with different PA intensities:

no activity 15/10,000 (referent)mod intensity 12/10,000 (p=0.32)vig intensity 5/10,000 (p=0.02)

• What interpretations are possible, and what are the implications?

Inter-relations among PA components (2)

• In randomized trials, consider this in design of the intervention arms

• Not possible in observational studies, so control for this in analyses. The aim is to mimic the controlled environment in a randomized trial.

Choice of Cutpoints (1)

• Continuous measure of PA, or categories?

• Continuous measure:- if non-linear relation, yields little additional info- interpretation less understandable

• Categorical measure:- allows visualization of disease rates in each category

Choice of Cutpoints (2)

• If categorical, how many groups?

• Quantiles (e.g., tertiles, quintiles)

• “Natural” breaks according to research interest

• “Natural” breaks on numerical scale

• Driven by biology

Shape of the Curve (1)

C

A

B

Increasing doses of activity

Incr

easi

ng

rat

es o

f d

isea

se

Shape of the Curve (2)

• Most investigators test for linear trend on log scale

• Note that a straight line on the log scale translates to an exponential curve on the natural scale

• However, for small effects (RR between 0.5 and 1, or 1 and 2), curves on log and natural scales look similar

• Other shapes of the curve are possible (e.g., regression splines)

Hu FB et al, JAMA 2000;283:2961-7

Spline Regression Model(cubic spline, 4 knots)

Shape of the Curve (3)

• Individual studies have their own ways of assessing and categorizing PA

• This makes it difficult to combine data across studies to synthesize info on the shape of the dose-response curve for a particular health outcome

• Investigators have done the best they can for meta-analyses, but may be combining disparate categories

E.g., “quintiles” of PA do not mean the same thing in different studies:

Finnish men(twin study):

Q1: <4.0 MET-hr/wk

Q2: 4.1-9.0

Q3: 9.1-17.4

Q4: 17.5-34.1

Q5: 31.5+

US women(Nurses’ Health Study):

Q1: <2.5 MET-hr/wk

Q2: 2.5-7.2

Q3: 7.3-13.4

Q4: 13.5-23.3

Q5: 23.4+

Men in Q5 expended 60% more energy than women in Q5

Dose-response curves for physical activity and physical fitness in relation to CVD

Williams PT, MSSE 2001;33:754-761

Population under Study

• Physical activity varies according to age, sex, race, etc.

• Thus the range of activity in different populations being studied may vary

• This may have an impact on the dose-response curve observed in any single study

• (Which is why combining data across studies is needed to get a good idea of the complete dose-response curve)

Hypothetical Spectrum of Response

80

85

90

95

100

105

1 2 3 4 5 6 7 8 9 10

Eve

nt

Rat

e

Physical Activity Doses

P, trend <0.001

Sample 1

Sample 2

In Sample 1:

• Less active population (could be older persons, women)

• We likely would choose Group 1 as our reference (a very sluggardly group!)

• We would see nice dose-response

In Sample 2:

• More active population (could be younger persons, men)

• We likely would choose Group 5 as our reference (a pretty active group)

• We would see little dose-response

Dose-Response for Volume of Physical Activity

Dose-Response for Volume

• Probably the simplest measure to analyze

• Any assessment of PA, no matter how simple, gives an idea of the volume of PA even if estimation of the actual energy expended cannot be made

• E.g., “none”, “a little”, “a lot”

Garfinkel et al, Cancer 1988;62:1844-1850

Harvard Alumni Health Study

80

85

90

95

100

105

<500 500-999

1000-1499

1500-1999

200-2499

2500-2999

3000-3499

3500+

Ag

e-S

td D

eath

Rat

e/10

,000

Physical Activity, Kcal/Week

Lee et al, JAMA 1995;273:1179-1184

P, trend <0.001

Mortality Rates by Tertiles of Free-Living Activity Energy Expenditure Health ABC Study

Manini et al, JAMA 2006;296:171-9

302 healthy adults, 70-82 y, followed ~6 y, 55 deaths

Dose-Response for Intensity of Physical Activity

Dose-Response for Intensity

• 2 issues to be concerned about: confounding by volume of PA, and confounding by activities of other intensities

• Analogous to confounding by total caloric intake and confounding by other nutrients in diet studies

• Can borrow methods from diet studies to control for these issues

Standard multivariate model

Health Professionals’ Follow-Up Study

Tanasescu et al, JAMA 2002;288:1994-2000

“Energy decomposition” method

Harvard Alumni Health Study

Energy expended in:

<150 kcal/wk

150-399 kcal/wk

400-750 kcal/wk

750-1499 kcal/wk

1500+ kcal/wk

Vigorous activities

1.00

(ref)

0.88

(0.81-0.96)

0.91

(0.81-1.02)

0.87

(0.76-1.00)

0.86

(0.76-0.96)

Nonvigorous activities

1.00

(ref)

0.98

(0.86-1.11)

1.09

(0.96-1.23)

1.08

(0.96-1.23)

1.05

(0.93-1.18)

P, (vig) – (nonvig)

-- 0.19 0.04 0.02 0.02

Lee et al, JAMA 1995;273:1179-1184

Multivariate RR’s for Mortality:

Notes:

• It is not sufficient to note that the coefficient (RR) for vigorous activities is significant, while that for non-vigorous activities is non-significant

• What is important is: are the coefficients (I.e., [vig] versus [nonvig]) DIFFERENT from each other?

Harvard Alumni Health Study

0.6

0.7

0.8

0.9

1.0

1.1

1.2

<150 150-399 400-749 750-1499 1500

Vig Non-vig

P, trend = 0.32

P, trend = 0.007

Physical Activity, Kcal/Week

Lee et al, JAMA 1995;273:1179-1184

Restriction/Stratification

Women's Health Study

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Does not Walk <1 1-1.5 2+

P, trend <0.001

Walking, Hr/Wk

RR

* o

f C

HD

* multivariate; among women without vigorous activity

Lee et al, JAMA 2001; 285:1447-1454

Harvard Alumni Health Study

Non-vigorous activity, kcal/wk*: Age-Std Mortality Rate (per 10,000)

<500 149

500-999 155

1000-1499 166

1500-1999 132

2000-2499 176

2500-2999 125

3000-3499 200

3500+ 143

P, trend = 0.99

* Among 17,321 men, 1195 performed only non-vigorous activities (380 deaths) Lee et al, JAMA 1995;273:1179-1184

The updated physical activity recommendation (2007 ACSM/AHA) allows for combining moderate and vigorous activities –

What data support this?

WHI Observational Cohort

Manson et al, NEJM 2002;347:716-25

~ 12.5 MET-hr

~ 10 MET-hr

Dose-Response for Duration (Frequency) of Physical Activity

Dose-Response for Duration

• Same issue: we are concerned about confounding by total volume of PA

• Close correlation between volume of energy expended and duration or frequency of PA

• Longer duration, more frequent bouts result in greater energy expended

• To isolate dose-response for duration or frequency, analysis must control for volume of energy expended

Dose-Response for Duration

• This answers the question: For two persons expending the same volume of energy, does the one exercising in long bouts/less frequently benefit more than the one exercising in short bouts/more frequently?

• Almost no data on this from observational studies

• (In randomized clinical trials, by design, investigator can control for total volume of energy expended)

Duration (min) Age-Adjusted RR (95% CI)

No sports/rec 1.00 (ref)

1-15 0.85 (0.55-1.31)

16-30 0.76 (0.57-1.03)

31-45 0.85 (0.58-1.24)

46-60 0.80 (0.59-1.10)

>60 0.78 (0.62-0.98)

p, trend = 0.04

Harvard Alumni Health Study

Lee et al, Circulation 2000;102:981-986

Duration (min) Bivariate RR* (95% CI)

No sports/rec 1.00 (ref)

1-15 0.94 (0.61-1.47)

16-30 0.92 (0.65-1.30)

31-45 1.07 (0.68-1.67)

46-60 1.02 (0.69-1.50)

>60 1.05 (0.73-1.49)

p, trend = 0.68

* adjusted for age and volume of PA

Harvard Alumni Health Study

Summary

• We’ve become more sophisticated in the questions we ask about PA-disease associations, moving from “is there an association?” to “what are the details of the association?”

• Many complex issues arise from the latter question related to dose-response

• Clear that there still are gaps in knowledge to be addressed