Obesity clusters
within the Empire Health Foundation Region
Joe Campo, MPH
Healthcare Research Group
Office of Financial Management
Highlights of November 17th, 2011, presentation
Identifying clusters
Obesity is on the rise nationally and locally – with
broad consequence affecting quality of life and
longevity as well as cost to the health care system
as a whole.
High & low obesity clusters
brfss 2003-2010
Using cluster identification software from the
National Cancer Institute, together with Behavioral
Risk Factor Surveillance System (BRFSS) data for
2003 through 2010, three regions were identified
within the Empire Health Foundation (EHF) Region
as having higher than expected obesity rates.
North
Spokane
City
Lincoln/
Stevens
South
Spokane
County
These high obesity clusters include most of Adams
County, portions of Lincoln and Stevens Counties,
and the northern portion of Spokane City.
Adams
An area with lower than expected obesity rates
was also identified; this area comprises most of
the southern portion of Spokane County.
Trends within each of these cluster areas, as well as for the EHF Region as a whole, were
also assessed. For the Adams and Lincoln/Stevens clusters, no significant trends were
identified, although the lines that best fit each of those areas’ obesity rates are moving
upwards. For North Spokane City, there had been a significant upward trend (7% per year)
from 2003 to 2008; however, in 2009 and 2010 the rates in that area are markedly lower.
Surprisingly, within the low obesity cluster, South Spokane County, the rates are increasing
over time at 4% per year. So, too, within the EHF Region as a whole the obesity rates are
also increasing at 3% per year.
Behavioral Risk Factor Surveillance System (2003-2010)
Behavioral Risk Factor Surveillance System (2003-2010)
percent obese within high & low clusters
trends – percent obese from 2003-2010
40
EHF’s
% obese w/
95% ci
35
30
25
South Spokane
County
North Spokane
City
Lincoln/
Stevens
Adams
45
45
45
40
40
40
35
35
45
40
ns
20
30
EHF trend
+ 2.6% per year
30
+ 7.0%
ns
35
35
30
30
25
ns
15
25
25
25
10
20
20
20
5
15
20
+ 4.4%
15
2003 2004 2005 2006 2007 2008 2009 2010
15
2003 2004 2005 2006 2007 2008 2009 2010
15
2003 2004 2005 2006 2007 2008 2009 2010
2003 2004 2005 2006 2007 2008 2009 2010
0
So. Spokane County
No. Spokane City
Obesity clusters within the Empire Health Foundation Region
Adams
Lincoln/Stevens
November 2011
Obesity clusters within the Empire Health Foundation Region
Obesity clusters within the Empire Health Foundation Region
November 2011
November 2011
Hospitalizations – Rates
Age-adjusted inpatient day hospitalization rates, for 2005 to 2009 combined, were analyzed
for conditions known to be associated with obesity. These rates were based upon the
patients’ reported ZIP code of residence, not where the hospital was located.
Rates for diabetes as the primary or secondary diagnosis within each of the high obesity
clusters were higher than the EHF Region’s rate; in the low obesity cluster, they were lower.
For coronary artery disease (CAD), rates within the high obesity Adams and Lincoln/Stevens
clusters were higher than the EHF’s Region's rate; in the low obesity South Spokane County
cluster they were lower. Somewhat surprisingly, the rates in the high obesity North Spokane
City cluster were borderline low compared to the EHF Region. However, the rates in each of
the high obesity clusters were higher than the rate in the low obesity one.
Rates for stroke were markedly high in Lincoln/Stevens clusters. Similarly, rates for
hypertension were markedly high in the Adams cluster.
Washington & Oregon inpatient discharge data (2005-2009)
Washington & Oregon inpatient discharge data (2005-2009)
diabetes (any diagnoses)
coronary artery disease
6000
1800
5500
1600
5000
1400
4500
4000
1200
3500
1000
3000
800
2500
2000
600
So. Spokane County No. Spokane City
Adams
Lincoln/Stevens
So. Spokane County No. Spokane City
age-adjusted patient day rates per 100,000 persons
Obesity clusters within the Empire Health Foundation Region
November 2011
Adams
Obesity clusters within the Empire Health Foundation Region
November 2011
Washington & Oregon inpatient discharge data (2005-2009)
Washington & Oregon inpatient discharge data (2005-2009)
stroke
hypertension
1800
Lincoln/Stevens
age-adjusted patient day rates per 100,000 persons
100
90
1600
80
1400
70
60
1200
50
1000
40
30
800
20
600
10
400
0
So. Spokane County No. Spokane City
Adams
Lincoln/Stevens
So. Spokane County
No. Spokane City
age-adjusted patient day rates per 100,000 persons
Obesity clusters within the Empire Health Foundation Region
November 2011
Obesity clusters within the Empire Health Foundation Region
Adams
Lincoln/Stevens
age-adjusted patient day rates per 100,000 persons
Obesity clusters within the Empire Health Foundation Region
November 2011
November 2011
Hospitalizations – Trends
Trends for these hospitalization rates were also assessed. For diabetes, however, no
significant trends were identified for any of the clusters or the EHF region as a whole; the
rates are essentially remaining flat over time.
Conversely, for CAD, trends were seen in each cluster and for the region as a whole. In all
instances those rates were decreasing, although at varying rates. Within the EHF Region,
CAD rate are decreasing at close to -6% per year. In the South Spokane County, they are
decreasing at a lower rate, approximately -4% per year. The rates are decreasing at -3% per
year within the North Spokane City cluster, -6% per year in Adams, and about -5% per year
in Lincoln/Stevens.
For stroke, the rates within the EHF Region are decreasing at -6% per year. They are
decreasing in Lincoln/Stevens by -21% per year. The rates in North Spokane City , however,
have been increasing by 12% per year starting in 2005.
Hypertension is increasing in South Spokane County – at 10% per year. No trends are seen
elsewhere.
Washington & Oregon inpatient discharge data (2000-2009)
Washington & Oregon inpatient discharge data (2000-2009)
trends – diabetes in primary or secondary
trends – coronary artery disease
South Spokane
County
South Spokane
County
North Spokane
City
10000
10000
10000
8000
8000
Lincoln/
Stevens
Adams
8000
8000
6000
6000
6000
4000
4000
4000
4000
2000
2000
2000
2000
0
0
0
0
Obesity clusters within the Empire Health Foundation Region
3500
3500
3000
3000
3000
2500
2500
2500
2500
2000
2000
2000
1500
1500
1500
1500
1000
1000
1000
1000
500
500
500
0
0
0
2000
500
- 5.6%
- 4.4%
0
November 2011
3500
- 3.2%
- 6.2%
trends – hypertension
Lincoln/
Stevens
Adams
4000
4000
4000
3500
3500
3500
3500
3000
3000
2500
3000
2500
2000
2000
- 6.2%
2500
+12.1%
(2005-09)
1500
1000
North Spokane
City
Lincoln/
Stevens
Adams
100
100
100
100
90
90
90
90
80
80
80
80
70
70
70
70
60
60
60
50
50
50
40
40
40
40
30
30
30
30
20
20
20
20
3000
2500
2000
2000
1500
1500
1000
South Spokane
County
60
50
1000
9.6%
500
500
500
500
10
10
10
10
0
0
0
0
0
0
0
0
Obesity clusters within the Empire Health Foundation Region
- 4.6%
November 2011
Washington & Oregon inpatient discharge data (2000-2009)
North Spokane
City
3000
Obesity clusters within the Empire Health Foundation Region
trends – stroke
4000
1000
3500
Washington & Oregon inpatient discharge data (2000-2009)
South Spokane
County
Lincoln/
Stevens
Adams
10000
6000
1500
North Spokane
City
November 2011
Obesity clusters within the Empire Health Foundation Region
Obesity clusters within the Empire Health Foundation Region
November 2011
November 2011
Hospitalizations – Costs
Excess costs or savings were also estimated for hospitalizations associated with obesity.
These were derived by converting all reported hospitalization charges to “costs” using the
Agency for Healthcare Research and Quality’s (AHRQ) cost-to-charge ratios, estimating the
number of patient days that would be generated in each cluster if the populations living
those clusters had been hospitalized at the same rate they were within the EHF Region,
comparing those “expected” patient days to the actual days generated, multiplying any
differences in days by the EHF Region’s cost per day, dividing that product by the population
in each cluster, and then multiplying the results by 1,000 to generate an estimated excess
cost or saving per 1,000 person within each cluster.
For instance, because the hospitalization rate for diabetes in the South Spokane County
cluster is lower than the rate in the EHF Region, the saving there equals about $35,000 per
1,000 persons per year compared to what it would have cost had they been hospitalized at
the same rate as seen for the region as a whole. In Lincoln/Stevens the excess
hospitalization rates equal an excess cost of $40,000 per 1,000 persons per year for
diabetes.
Washington & Oregon inpatient discharge data (2006-2010)
Washington & Oregon inpatient discharge data (2006-2010)
costs - diabetes (any diagnoses)
Savings
costs - coronary artery disease
Savings
Excess costs
So. Spokane County
So. Spokane County
No. Spokane City
No. Spokane City
Adams
Adams
Lincoln/Stevens
Lincoln/Stevens
-$40,000
-$20,000
$0
$20,000
$40,000
-$25,000
-$15,000
-$5,000
per 1,000 persons
November 2011
Washington & Oregon inpatient discharge data (2006-2010)
$15,000
$25,000
Obesity clusters within the Empire Health Foundation Region
November 2011
Washington & Oregon inpatient discharge data (2006-2010)
costs - stroke
costs - hypertension
Savings
Excess costs
So. Spokane County
So. Spokane County
No. Spokane City
No. Spokane City
Adams
Adams
Lincoln/Stevens
Lincoln/Stevens
-$5,000
$5,000
per 1,000 persons
Obesity clusters within the Empire Health Foundation Region
Savings
Excess costs
$0
$5,000
$10,000
$15,000
$20,000
per 1,000 persons
Obesity clusters within the Empire Health Foundation Region
-$200
Excess costs
$0
$200
$400
$600
$800
$1,000
per 1,000 persons
November 2011
Obesity clusters within the Empire Health Foundation Region
Obesity clusters within the Empire Health Foundation Region
November 2011
November 2011
Characteristics of the population
Various behavioral and demographic characteristics of each cluster area were also assessed.
Included, below, are measures pertaining to exercise, diet, insurance coverage, education,
income and race.
Behavioral Risk Factor Surveillance System (2003-2010)
Behavioral Risk Factor Surveillance System (2005, 2007 & 2009)
no exercise outside of work
less than 5 fruits or vegetables per day
40
84
35
82
80
30
78
25
76
20
74
15
72
10
70
5
68
0
66
So. Spokane County
No. Spokane City
Adams
Obesity clusters within the Empire Health Foundation Region
Lincoln/Stevens
November 2011
So. Spokane County
No. Spokane City
Adams
Lincoln/Stevens
Obesity clusters within the Empire Health Foundation Region
November 2011
Behavioral Risk Factor Surveillance System (2003-2010)
Behavioral Risk Factor Surveillance System (2003-2010)
no health care coverage
education: college or tech school grad
40
60
35
50
30
40
25
20
30
15
20
10
10
5
0
0
So. Spokane County
No. Spokane City
Adams
Obesity clusters within the Empire Health Foundation Region
Lincoln/Stevens
November 2011
So. Spokane County
No. Spokane City
Adams
Lincoln/Stevens
Obesity clusters within the Empire Health Foundation Region
November 2011
Behavioral Risk Factor Surveillance System (2003-2010)
Behavioral Risk Factor Surveillance System (2003-2010)
income above 200% federal poverty level
american indian/alaska native
80
6
70
5
60
4
50
40
3
30
2
20
1
10
0
0
So. Spokane County
No. Spokane City
Obesity clusters within the Empire Health Foundation Region
Adams
Lincoln/Stevens
November 2011
Obesity clusters within the Empire Health Foundation Region
So. Spokane County
No. Spokane City
Obesity clusters within the Empire Health Foundation Region
Adams
Lincoln/Stevens
November 2011
November 2011
Characteristics of the environment
A community’s access to healthy food is one factor to consider in assessing the role
environment plays in promoting or preventing obesity.
The map below is based upon data provided by the CDC showing the percent of health food
retailer in a tract relative to all food retailers in that tract including quickie-marts and fast
food vendors.
Overlaid on the map are selected cities within the EHF Region. Also overlaid on the map are
the high obesity clusters identified through BRFSS.
While no rigorous assessment has been done on the correlation between the obesity
clusters and the regions with poor access to healthy food retailers, a scan of the map
suggests that both Springdale and Ritzville differ from the other cities shown in that they
both are within regions with relatively poor access to healthy food retailers.
healthy food stores as a
percent of all food stores
Colville
by census tract
less than 4%
Springdale
4% to 12%
12% to 20%
20% to 33%
Davenport
Deer Park
Spokane City
Cheney
33% or more
Washington average = 12%
National average = 10%
Ritzville
Othello
Obesity clusters within the Empire Health Foundation Region
November 2011
What the future may hold
Factors that lead to obesity may be traced back to early youth – or younger. In that context,
we examined hospitals birth data, as well as the school-based Healthy Youth Survey data.
For hospital-based births, a concerning
harbinger was seen in assessing macrosomia,
or large-baby births; these newborns may be
at greater risk for adult obesity than normal
weight ones. Surprisingly, the low obesity
South Spokane County had the highest
macrosomia birth rate.
Washington & Oregon inpatient discharge data (2006-2010)
macrosomia (large baby syndrome)
90
80
70
60
50
Healthy Youth Survey data were also
assessed, with clusters being identified for
selected risk-factors and overlaid on the
obesity cluster areas. These overlays suggest
a degree of concordance between risk
factors and the obesity clusters identified.
40
30
20
10
0
So. Spokane County
No. Spokane City
Adams
Lincoln/Stevens
Obesity clusters within the Empire Health Foundation Region
November 2011
Healthy Youth Survey (2006, 2008 & 2010)
Healthy Youth Survey (2006, 2008 & 2010)
obese
drinks two or more sodas per day
20
20
Obese
18
18
16
16
14
14
12
10
8
6
Drinks two or more sodas per day
12
Adams/
Lincoln
School
Districts
4
10
8
Spokane
School
Districts
6
EHF Region
2
0
0
November 2011
EHF Region
4
2
Obesity clusters within the Empire Health Foundation Region
Adams/
Lincoln
School
Districts
Cluster
Obesity clusters within the Empire Health Foundation Region
November 2011
Healthy Youth Survey (2006, 2008 & 2010)
Healthy Youth Survey (2006, 2008 & 2010)
3+ hours of TV viewing per day
physically active less than 5 days/week
40
54
Three or more hours of TV viewing per day
35
Less than five days per week of being physically active
for one hour or more
52
30
50
25
48
20
15
Spokane
School
Districts
Adams
School
Districts
46
EHF Region
44
10
Obesity clusters within the Empire Health Foundation Region
Spokane
School
Districts
5
42
0
40
November 2011
Obesity clusters within the Empire Health Foundation Region
Obesity clusters within the Empire Health Foundation Region
EHF Region
November 2011
November 2011
Additional findings
Behavioral Risk Factor Surveillance System (2003-2010)
Behavioral Risk Factor Surveillance System (2003-2010)
background – large area comparisons
background – county comparisons
45
45
40
40
normal
overweight
obese
normal
35
normal overweight
normal
overweight
normal
overweight
overweight
35
30
30
obese
25
obese
obese
obese
25
20
20
15
15
10
10
5
5
0
0
Nation (2010)
Washington State
Eastern Washington
Obesity clusters within the Empire Health Foundation Region
Empire Health
Foundation Region
November 2011
Adams
Ferry
Lincoln
Pend
Oreille
Spokane
Stevens
Obesity clusters within the Empire Health Foundation Region
November 2011
Washington & Oregon inpatient discharge data (2005-2009)
Washington & Oregon inpatient discharge data (2005-2009)
low-extremity amputations w/ diabetes
diabetes long-term complications
250
Whitman
600
500
200
400
150
300
100
200
50
100
0
0
So. Spokane County
No. Spokane City
Adams
Lincoln/Stevens
So. Spokane County
No. Spokane City
age-adjusted patient day rates per 100,000 persons
Obesity clusters within the Empire Health Foundation Region
November 2011
Adams
Lincoln/Stevens
age-adjusted patient day rates per 100,000 persons
Obesity clusters within the Empire Health Foundation Region
November 2011
Behavioral Risk Factor Surveillance System (2009-2010)
Behavioral Risk Factor Surveillance System (2009-2010)
high adverse childhood experiences
self-assessed health status: fair or poor
60
30
50
25
40
20
30
15
20
10
10
5
0
0
So. Spokane County
No. Spokane City
Obesity clusters within the Empire Health Foundation Region
Adams
Lincoln/Stevens
November 2011
Obesity clusters within the Empire Health Foundation Region
So. Spokane County
No. Spokane City
Obesity clusters within the Empire Health Foundation Region
Adams
Lincoln/Stevens
November 2011
November 2011
Summaries
Behavioral Risk Factor Surveillance System (2003-2010)
summary of obesity rates

There are pronounced geographic variations in obesity rates

Compared to the nation, the EHF obesity rate is lower; compared
to the state, it is higher
Within EHF Region, Adams County has the highest obesity rate;
Spokane and Whitman have the lowest
Only Spokane &Whitman show a trend in their obesity rates:
upwards
Small area clusters may differ, but there is a general concordance
For 2003-2010, three high and one low obesity clusters are seen
Only the low obesity South Spokane area has a trend: upwards
There is also a increasing trend seen in the EHF Region as a
whole






Obesity clusters within the Empire Health Foundation Region
November 2011
Washington & Oregon inpatient discharge data (2006-2010)
summary of hospitalization rates

High diabetes rates for high obesity clusters, low for the low one




Amputations: high in high obesity cluster, low in low
Long-term comp.: high in two high clusters, low in low
Short-term comp: high in No. Spokane, low in So. Spokane
Uncontrolled : high in two high clusters, low in low & No. Spokane
CAD – high in Adams & Lincoln/Stevens, low in S. Spokane & N.
Spokane
 Stroke – high in No. Spokane & Lincoln/Stevens, low in So. Spokane &
Washington & Oregon inpatient discharge data (2006-2010)
Adams
summary
of hospitalization rates
 Hypertension – high in Adams



No trends seen with diabetes hospitalization rates
CAD – trending downwards with regions and each clusters area
(smoking?)
November 2011
Stroke – trending downwards in EHF region and Lincoln/Stevens;
trending upwards in No. Spokane City
For diabetes in general, nearly $40,000 in excess costs per 1,000
persons in Lincoln/Stevens; the opposite in So. Spokane County
For CAD, nearly $20,000 in excess costs per 1,000 persons in
Lincoln/Stevens; the opposite in So. Spokane County
Obesity clusters within the Empire Health Foundation Region



Obesity clusters within the Empire Health Foundation Region
November 2011
Discussion and sources
Obesity clusters within the Empire Health Foundation Region
discussion

Wide variations in obesity rates across the region

High (and low) obesity clusters are identifiable

The health care needs and costs associated with obesity
disproportionately affect the high obesity regions

The trends, in general, do not portend well

Identifying and assessing geographic variations can, however,
help to engage communities in addressing this condition
Obesity clusters within the Empire Health Foundation Region
November 2011
background – sources and methods
data sources
• brfss
• inpatient hospitalizations
• chars & oregon
tools
• head-banging
weighted two-dimensional
median-based smoothing
algorithm
• births and deaths
• zip-code population
ute 16
o
t ate R
S
16
ute16
o
t ateR
S
oute
t ateR
S
• cost-to-charge ratios
• modified retail food
...environment index
• spatial scan statistic
• joinpoint regression
• healthy youth survey
Obesity clusters within the Empire Health Foundation Region
Obesity clusters within the Empire Health Foundation Region
analyzes varying models to test if a
change in trend is statistically
significant.
November 2011
November 2011
Pend
Oreille
Ferry
Stevens
Lincoln
Spokane
Adams
Whitman
Obesity clusters within the Empire Health Foundation Region
November 2011