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Exercise and outcomes. Hirsch, Diehr 11-18-2005 (9 AM). Compact Results. Adjusting for Age in Regression Only Does not match Table 5, which is age-specific Big exercise effects unadjusted Much smaller differences after adjustment

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exercise and outcomes

Exercise and outcomes

Hirsch, Diehr

11-18-2005 (9 AM)

compact results
Compact Results
  • Adjusting for Age in Regression Only
  • Does not match Table 5, which is age-specific
  • Big exercise effects unadjusted
  • Much smaller differences after adjustment
  • But some quintiles have significantly fewer “years” than quintile 5
    • The confidence interval doesn’t overlap with the CI for quintile 5
  • Propensity score approach suggests that the covariates we used do achieve balance.
regression model
Regression Model
  • Not in causal pathway?
    • gend01 age00 lage agesex lagesex white grade01
    • smoke alcoh aspirin
    • diabada maxcom maxint maxsten copdbl shtbrt chdblmod emphysem chfbase cbd cancer prknsn06 renal arth01
    • crp fib44 alb44 depscr05 cis42 benzod06
    • minimental digcor
    • evggfp timewlk iadl adl
  • Possibly in causal pathway? biorea21 biores21 bmi
    • choladj hdl44 ldladj lipid06
    • hyper aai suppul16
  • Re-try propensity score model without some of these suspect variables?
but here is the bad news
But here is the bad news
  • I calculated a propensity score from the variables in the regression (59 variables incl 42 in model and 17 not in)
  • I created quintiles of the propensity score
  • I looked within each quintile to see whether log kcal was correlated with the covariates.
vars in propensity score
Vars in propensity score
  • Regression variables: gend01 age00 lage agesex lagesex white grade01 iadl adl timewlk biorea21 biores21 bmi choladj hdl44 ldladj lipid06 hyper smoke diabada alcoh aspirin maxcom maxint maxsten aai copdbl shtbrt chdblmod chfbase cbd diag01 prknsn06 renal arth01 crp fib44 alb44 depscr05 score30 digcor ih000 suppul16 cis42 benzod06 emphysem
  • Other Variables (obtained from screening all variables: not used in regression model, to keep sample size up): hip13 insul12 wbld23 brtsht07 domgrip benzod06 cancer arth01 aai cis42 chstpn cpvd anar1a06 avzmdia iadl hip13 insul12 married fvc18 live03 netscr03 extart07 time17 suppul16 trblsl08 ues waist13 wgt5008 white wbld23 wakeup08
balance lkcal corr with
Balance: lkcal corr with:
  • In Propensity quintile 1, more exercise correlated with lower fibrinogen, lower wbc, lower waist circumference, lower weight (4/59 vars: a problem? Type of bias?)
  • 2: less hypertension
  • 3: higher digital symbol score, higher grip strength, married, living with spouse (vs alone, etc.)
  • 4: more alcohol, more aspirin, more chd, lower suppine pulse rate, lower wbc, higher grip strength
  • 5: higher ankle/arm ratio, lower chest pain, less trouble sleeping
  • 20/59*5 = 3% of all corrs sdfz
  • Balance is amazingly good
balance if hypertension weight cholesterol not in model
Balance if hypertension, weight, cholesterol not in model
  • In Propensity quintile 1, more exercise is associated with fewer IADL difficulties, lower cholesterol, lower BMI, lower LDL, lower fibrinogen, higher evggfp, smaller hips, smaller waist
  • 2: lower bmi, less alcohol, smaller hips, smaller waist
  • 3: lower bmi, higher albumin, smaller hip, more grip strength, more married, higher fvc, lives with spouse, smaller waist
  • 4: lower bmi, higher hdl, higher alcohol, less stenosis, higher fibrinogen, smaller hips, lower wbc, less peripherovascular disease, smaller waist
  • 5: No blacks, no people with 1 iadl at baseline, lower digital symbol score, less trouble falling asleep
  • Balance is much worse without those variables. If bmi and hip size and hdl matter, the groups are not comparable.
age specific results

Age-specific results

Use single age group

Use age-specific quintiles

But Age is adjusted for in regression

(I’m not sure that we want to adjust for age twice)

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