The Increasing Cost of Obesity:
Th IImpactt off Ph
The
Physical
i lA
Activity
ti it and
d Obesity
Ob it
on Medical Expenditures 1998-2006
Jeroen van Meijgaard – UCLA School of Public Health
Academy Health
June 2010
BACKGROUND
 Obesity has been associated with morbidity and higher
medical expenditures
p
 Lack of physical activity has also been associated with
morbidity (and mortality), independent of obesity; and
thus likely with medical expenditures
 Physical activity and obesity are correlated in the
population, yet few studies analyze independent impact
on medical expenditures
 Some evidence that the impact of obesity on mortality
has lessened over time
Use nationally representative study over 9 years to evaluate
independent impact of physical activity and obesity on medical
expenditures and changes over time
DATA – NHIS LINKED WITH MEPS
 Medical Expenditures Panel Survey (MEPS) is a subsample of individuals in the National Health Interview
Survey (NHIS)
 MEPS is conducted 1-2 years after NHIS
 NHIS has self reported weight and height (BMI), leisure
time physical activity
activity, other health behaviors,
behaviors as well as
health conditions and socio-economic variables
 MEPS collects direct personal medical expenditures for
each individual, regardless of source of payment, for
a ous types of
o expenditures
e pe d tu es
various
 NHIS data collection has been consistent since 1997
DATA – SAMPLE CHARACTERISTICS
1997-2005 NHIS data at baseline linked with 1 year
expenditure data from 1998-2006 MEPS
N=40,886:
N
40 886 (18
(18-64:
64 32
32,803;
803 65+
65+: 8
8,803)
803)
Mean expenditures: $3,951 ($, 2003)
No expenditures:
p
13.3%
Female: 57.4%
BMI:
• 18.5-24.9:
18 5 24 9: 38.0%
38 0%
• 25.0-29.9: 35.4%
• 30.0-34.9: 15.7%
• 35.0-39.9: 5.6%
• 40.0+:
3.2%
 Physical Activity:
• None:
40.5%
• 0.1-15.9 METhrs/wk: 30.5%
• 16.0+ METhrs/wk: 28.9%





METHODS
 Use GLM to estimate mean expenditures conditional on
variables
i bl off iinterest:
E ( Expenditures) 
exp W W   P P   WPWxP   Y Y   WY YxW   A A   O1O1   O 2 O2   AO 2 AxO2 






Analysis
y
is stratified by
y Gender and Age
g ((<65;; ≥65))
Separate Age indicator for 5-year age groups (A)
Indicator for Period ((Y):
) 1998-2002 vs 2003-2006
Incorporate interaction for BMI (W) and PA (P)
Incorporate interaction for Period (Y) and BMI (W)
Other regressors include cancer status at baseline, usual
care indicators and activityy limits
RESULTS – IMPACT OF PA AND BMI ON EXPENDITURES
Normal Weight
Overweight
g
Obese I
Obese II
Obese III
Age < 65
Age ≥ 65
Male
Female
Male
Female
$ 2,341
$ 3,158
$ 7,013
$ 7,285
+ $ 225
+ $ 138 + $ 284
– $ 187
+ $ 994
+ $ 708 + $ 2,205 + $ 1,421
+ $ 813
+ $ 848 + $ 2,640
,
+ $ 1,543
,
+ $ 791
+ $ 885 + $ 3,608
+ $ 650
Sedentary
$ 2,752
Somewhat Active – $ 111
Very Active
– $ 92
$ 3,545
– $ 189
– $ 186
$ 7,653
$ 7,948
– $ 613
– $ 379
+ $ 628 – $ 1,207
Note:
N
t P
P-value
l < 5% shown
h
iin b
bold
ld – P-values
P l
and
d confidence
fid
iintervals
t
l were
obtained using simulation methods
RESULTS – CHANGE OVER TIME
Normal Weight
Overweight
g
Obese I
Obese II
Obese III
Age < 65
Male
Female
+1.6% +17.2%
+13.4% +29.2%
+12.9% +26.6%
+12.2%
+4.0%
+14.9% +49.6%
Age ≥ 65
Male
Female
+25.0% +42.9%
– 6.2%
– 8.6%
+13.6% +14.3%
–1.7% +92.0%
+12.0%
+2.4%
BMI≥25
vs. [18.5-24.9]
[18.5 24.9]
BMI≥30
vs. [25.0-29.9]
[25.0 29.9]
+13.5%
+11.6%
11.6%
–
–
–
–
+9.7%
+16.4%
16.4%
+27.2%
+10.0%
10.0%
–
–
–
–
+28.5%
+37.2%
37.2%
Note: P-value < 5% shown in bold – P-values and confidence intervals were
obtained using simulation methods
DISCUSSION
 Substantial impact of overweight and obesity on medical
expenditures
p
 Impact of BMI on expenditures is changing over time
• More rapid increase of expenditures among obese
• Among elderly, shift of minimum to overweight
 Minimal impact of physical activity on medical
expenditures, but not clear why it does not track impact
on morbidity and mortality
• Possibly due to injury related expenditures
• Is higher level of PA associated with higher
propensity to seek preventive care and other services
• Maybe PA differentially impacts acute versus chronic
conditions