patterns of healthy behavior and diabetes medical outcome · 2015-08-07 · behavior and diabetes...
TRANSCRIPT
PATTERNS OF HEALTHY BEHAVIOR AND DIABETES
MEDICAL OUTCOMEIsabel Corcos, PhD, MPH 1, Leslie Ray, MPH, MPPA, MA 1,2, Ryan Smith, MPH2, Barbara M.
Stepanski, MPH, Joshua Smith, PhD, MPH 1, Sanaa Abedin, MPH 2, Amelia Kenner-Brininger, MPH, CPH 1 , Maria Pena, MPH2, Kimberley De Vera, BS1.
1County of San Diego Health and Human Services Agency, Public Health Services, Emergency Medical Services
2County of San Diego Health and Human Services Agency, Public Health Services, Community Health Statistics Unit
5th largest county in the U.S. (4,200 sq. mi.)18 cities, 3.1 million residentsMajor tourist destination, 5 climate zones!
SAN DIEGO COUNTY, CALIFORNIA
41 communities (aggregated census tracts)
• Reflect diverse population, lifestyles, urbanicity across county
• Allow consistent analysis of demographic & health data over time
• Excluding military population which is part of a different medical system
TODAY’S PRESENTATION FOCUS
Continues work presented at 2014 ESRI Health GIS conference
Showed that health-related data from a large consumer marketing survey correlated plausibly with diabetes medical outcomes
WHAT WE KNOW ABOUT DIABETESIN SAN DIEGO COUNTY
General spatial trends: • Lower rates in north coastal, north central & north inland areas • Higher rates in the southern, eastern areas• In some communities, rates often too statistically unstable to
calculate
LOOKED TO ALTERNATIVE SOURCES FOR HEALTH-RELATED DATA
Hospitalization
Death
ED Discharge
*Sources: Patient Hospitalization Discharge Database (CA OSHPD), County of San Diego, Health & Human Services Agency, Public Health Services, Epidemiology & Immunization Services Branch. SANDAG, Current Population Estimates, 2012. Emergency Department Discharge Database (CA OSHPD), County of San Diego, Health & Human Services Agency, Public Health Services, Emergency Medical Services. SANDAG, Current Population Estimates, 2012. Death Statistical Master Files (CDPH), County of San Diego, Health & Human Services Agency, Public Health Services, Epidemiology & Immunization Services Branch. SANDAG, Current Population Estimates, 2012.
135.0 143.4
20.7
0
50
100
150
200
Hospitalization Emergency Department(ED) Discharge
Death
San Diego CountyMedical Outcome Rates
per 100,000 population, 2012
Market Potential (2013) data purchased from ESRI • Derived from large, national consumer spending/use survey• Estimates the likely demand for goods & services• Used by business to understand & target consumers
USE OF MARKET POTENTIAL DATA TO PROFILE COMMUNITIES
• Critical factors to course of most chronic diseases
• Available at census tract level
Many questions relate to diet,
exercise, smoking, medication, medical
services use
LIMITATIONS
Based on survey, projected behaviors of adults
Subject to bias/error on part of those surveyed
Variables collected for business purposes, targeting consumers, not for
assessing population health
Relationship with medical outcome is correlative
HOWEVER, WE CAN USE THIS INFORMATION TO
UNDERSTAND WHO’S DOING WHAT AND WHERE,
AND WHO WILL PROBABLY DO IT AGAIN
TODAY’S PRESENTATION FOCUS
Data related to prevalence of diabetes
Spatial patterns of health behaviors
Community health profiles beyond medical outcome rates
VARIABLES CORRELATED WITH DIABETES MEDICAL OUTCOME
Category Variable County %Exercise frequency Spend 6+ hours exercising per week 23.8%
Spend 3-5 hours exercising per week 23.5%Spend 1-2 hours exercising per week 19.5%Spend no time exercising during a typical week 32.6%
Exercise routine Usually follow a regular exercise routine 26.6%Frequently follow a regular exercise routine 33.9%Occasionally follow a regular exercise routine 26.6%Rarely follow a regular exercise routine 12.3%
Exercise location Exercise at club 2+ times per week 16.1%Exercise at other facility (not club) 2+ times/wk 8.1%Exercise at home 2+ times per week 27.9%
Home equipment Own elliptical 3.9%Own stationary bicycle 5.1%Own treadmill 9.1%Own weight lifting equipment 12.6%
Category Variable County %Smoking Smoked cigarettes in last 12 months 16.5%
Smoked 9+ packs of cigarettes in last 7 days 2.8%Method used to stop smoking/12 mo: Cold Turkey 2.7%
Category Variable County %Doctor Visits Visited doctor in last 12 months 73.3%
1-2 times 23.3%3-5 times 20.8%6+ times 29.3%
Health Professional General/Family 38.4%Dentist 35.8%Eye 19.2%Dermatologist 8.3%Internist 7.2%Chiropractor 6.3%Cardiologist 6.1%Physical Therapist 4.6%Ear/Nose/Throat 4.6%Gastroenterologist 3.9%Nurse Practitioner 3.8%Urologist 3.6%Podiatrist 3.0%Allergist 2.1%
PERCENT OF ADULTS IN SAN DIEGO COUNTY WHO BUY/USE
GOODS & SERVICES (OR “DO” BEHAVIOR)
GREEN: SIGNIFICANT NEGATIVE CORRELATION WITH MEDICAL
OUTCOME
RED: SIGNIFICANT POSITIVE CORRELATION WITH MEDICAL OUTCOME
Category Variable County %Food Choices Went to fast food/drive-in restaurant 9+ times/mo 39.7%
Used white bread in last 6 months 38.1%Drank cola (regular) in last 6 months 44.7%Used artificial sweetener in last 6 months 25.9%Try to eat healthy w/nutrition focus 36.6%Rarely check food ingredients before buying 13.3%Frequently check food ingredients before buying 38.5%
Diet Intent Presently controlling diet 35.6%Diet control for blood sugar level 6.6%Diet control for cholesterol level 8.8%Diet control to maintain weight 11.2%Diet control for physical fitness 11.1%Diet control for weight loss 13.3%Used exercise program for diet method 8.4%
Product labeling Buy foods specifically labeled as fat-free 13.0%Buy foods specifically labeled as high protein 6.1%Buy foods specifically labeled as low-calorie 10.6%Buy foods specifically labeled as low-carb 6.0%Buy foods specifically labeled as low-cholesterol 6.8%Buy foods specifically labeled as low-fat 12.3%Buy foods specifically labeled as sugar-free 10.1%
DATA RELATED TO DIABETES PREVALENCE
• Diet control for blood sugar level• Prescription drug use for diabetes
(insulin dependent)• Prescription drug use for diabetes
(non-insulin dependent)
Indicators of diagnosed disease • Positively correlated with diabetes
medical outcomes• Similar to State survey: 7.8% of
San Diego County adults ever diagnosed with diabetes (California Health Interview Survey, 2011)
6.6%
5.1%
9.0%
1.7%
0.4%
2.4%
3.4%
2.6%
4.3%
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
7.0%
8.0%
9.0%
10.0%
County % Community Min (%) Community Max (%)
Diet control for blood sugar level
Used prescription drug for diabetes(insulin dependent)Used prescription drug for diabetes(non-insulin dependent)
Data reflect diagnosed diabetes, and are particularly helpful for communities where rates for medical encounter cannot be calculated
Finds where high values & low values cluster
• Red: hot spot, high values group
• Blue: cold spot, low values group
Intensity of color reflects degree of confidence in results
SPATIAL PATTERNS: HOT SPOT ANALYSIS BY CENSUS TRACT
Hospitalization rates by community shown for reference
SPATIAL PATTERNS: HOT SPOT ANALYSIS OF PREVALENCE-RELATED VARIABLES
Top to bottom:
• Used prescription for insulin dependent diabetes
• Used prescription for non-insulin dependent diabetes
• Diet control for blood sugar
Significant clustering
Pattern consistent across 3 variables
Hot/cold spots correlated with higher/lower rates of all medical outcomes
County mean proportion (%), & the range of values across communities
Diet, exercise & smoking are major players in chronic diseaseCorrelated with diabetes medical outcomesSpatial patterns helpful in understanding these key behaviors
County Minimum (%) Maximum (%)
Try to eat healthy w/nutrition focus 36.6% 29.3% 43.1%
Frequently check food ingredients before buying 38.5% 35.3% 40.8%
Spend 3-5 hours exercising per week 23.5% 18.9% 28.1%
Rarely follow a regular exercise routine 12.3% 8.6% 16.0%
Went to fast food/drive-in restaurant 9+ times/mo 39.7% 28.0% 46.6%
Smoked 9+ packs of cigarettes in last 7 days 2.8% 1.8% 5.4%
BehaviorPercentage of Adults
SPATIAL PATTERNS: HOT SPOT ANALYSIS OF 6 HEALTH BEHAVIOR VARIABLES
SPATIAL PATTERNS: HOT SPOT ANALYSIS BY CENSUS TRACT
Try to eat healthy w/ a nutrition focus
Frequently check ingredients before buying
Spend 3-5h exercisingper week
Went to fast food/drive-in9+ times/mo
Rarely follow regular exercise routine
Smoked 9+ packs of cigarettes last 7 days
Spatial patterns correlate generally with diabetes hospitalization
• Hot spots for high percentage of healthy choices in coastal central and inland valleys
• Cold spots in the south.
• Unhealthy choices show the opposite patterning
Similar to Hot Spot AnalysisIdentifies clusters of, high (HH) low values (LL)
Outliers – areas that differ from others within a specified distance:
HL- high values near low (orange);
LH- low values near high (white)
SPATIAL PATTERNS: CLUSTER & OUTLIER ANALYSIS BY CENSUS TRACT
SPATIAL PATTERNS: CLUSTER & OUTLIER ANALYSIS
Clustering similar to hot spot analysis
Outliers within communities
Many tracts are outliers for multiple variables
Try to eat healthy w/ a nutrition focus
Frequently check ingredients before buying
Spend 3-5h exercisingper week
Went to fast food/drive-in9+ times/mo
Rarely follow regular exercise routine
Smoked 9+ packs of cigarettes last 7 days
Understanding neighborhood differences can assist in supporting healthy choices, or find
areas for targeted outreach
PROFILING HEALTHY COMMUNITIES
Objective:• Identify communities where
more people make very healthy choices
• Identify communities where fewer healthy choices are made
• Identify which behaviors need support or need change
Category Variable County %Exercise frequency Spend 6+ hours exercising per week 23.8%
Spend 3-5 hours exercising per week 23.5%Spend 1-2 hours exercising per week 19.5%Spend no time exercising during a typical week 32.6%
Exercise routine Usually follow a regular exercise routine 26.6%Frequently follow a regular exercise routine 33.9%Occasionally follow a regular exercise routine 26.6%Rarely follow a regular exercise routine 12.3%
Exercise location Exercise at club 2+ times per week 16.1%Exercise at other facility (not club) 2+ times/wk 8.1%Exercise at home 2+ times per week 27.9%
Home equipment Own elliptical 3.9%Own stationary bicycle 5.1%Own treadmill 9.1%Own weight lifting equipment 12.6%
Category Variable County %Smoking Smoked cigarettes in last 12 months 16.5%
Smoked 9+ packs of cigarettes in last 7 days 2.8%Method used to stop smoking/12 mo: Cold Turkey 2.7%
Category Variable County %Doctor Visits Visited doctor in last 12 months 73.3%
1-2 times 23.3%3-5 times 20.8%6+ times 29.3%
Health Professional General/Family 38.4%Dentist 35.8%Eye 19.2%Dermatologist 8.3%Internist 7.2%Chiropractor 6.3%Cardiologist 6.1%Physical Therapist 4.6%Ear/Nose/Throat 4.6%Gastroenterologist 3.9%Nurse Practitioner 3.8%Urologist 3.6%Podiatrist 3.0%Allergist 2.1%
Category Variable County %Food Choices Went to fast food/drive-in restaurant 9+ times/mo 39.7%
Used white bread in last 6 months 38.1%Drank cola (regular) in last 6 months 44.7%Used artificial sweetener in last 6 months 25.9%Try to eat healthy w/nutrition focus 36.6%Rarely check food ingredients before buying 13.3%Frequently check food ingredients before buying 38.5%
Diet Intent Presently controlling diet 35.6%Diet control for blood sugar level 6.6%Diet control for cholesterol level 8.8%Diet control to maintain weight 11.2%Diet control for physical fitness 11.1%Diet control for weight loss 13.3%Used exercise program for diet method 8.4%
Product labeling Buy foods specifically labeled as fat-free 13.0%Buy foods specifically labeled as high protein 6.1%Buy foods specifically labeled as low-calorie 10.6%Buy foods specifically labeled as low-carb 6.0%Buy foods specifically labeled as low-cholesterol 6.8%Buy foods specifically labeled as low-fat 12.3%Buy foods specifically labeled as sugar-free 10.1%
PROFILING HEALTHY COMMUNITIES
Ranked communities in deciles from healthiest to least healthy for each variable
Category Variable County %Exercise frequency Spend 6+ hours exercising per week 23.8%
Spend 3-5 hours exercising per week 23.5%Spend 1-2 hours exercising per week 19.5%Spend no time exercising during a typical week 32.6%
Exercise routine Usually follow a regular exercise routine 26.6%Frequently follow a regular exercise routine 33.9%Occasionally follow a regular exercise routine 26.6%Rarely follow a regular exercise routine 12.3%
Exercise location Exercise at club 2+ times per week 16.1%Exercise at other facility (not club) 2+ times/wk 8.1%Exercise at home 2+ times per week 27.9%
Home equipment Own elliptical 3.9%Own stationary bicycle 5.1%Own treadmill 9.1%Own weight lifting equipment 12.6%
Category Variable County %Smoking Smoked cigarettes in last 12 months 16.5%
Smoked 9+ packs of cigarettes in last 7 days 2.8%Method used to stop smoking/12 mo: Cold Turkey 2.7%
Category Variable County %Doctor Visits Visited doctor in last 12 months 73.3%
1-2 times 23.3%3-5 times 20.8%6+ times 29.3%
Health Professional General/Family 38.4%Dentist 35.8%Eye 19.2%Dermatologist 8.3%Internist 7.2%Chiropractor 6.3%Cardiologist 6.1%Physical Therapist 4.6%Ear/Nose/Throat 4.6%Gastroenterologist 3.9%Nurse Practitioner 3.8%Urologist 3.6%Podiatrist 3.0%Allergist 2.1%
Category Variable County %Food Choices Went to fast food/drive-in restaurant 9+ times/mo 39.7%
Used white bread in last 6 months 38.1%Drank cola (regular) in last 6 months 44.7%Used artificial sweetener in last 6 months 25.9%Try to eat healthy w/nutrition focus 36.6%Rarely check food ingredients before buying 13.3%Frequently check food ingredients before buying 38.5%
Diet Intent Presently controlling diet 35.6%Diet control for blood sugar level 6.6%Diet control for cholesterol level 8.8%Diet control to maintain weight 11.2%Diet control for physical fitness 11.1%Diet control for weight loss 13.3%Used exercise program for diet method 8.4%
Product labeling Buy foods specifically labeled as fat-free 13.0%Buy foods specifically labeled as high protein 6.1%Buy foods specifically labeled as low-calorie 10.6%Buy foods specifically labeled as low-carb 6.0%Buy foods specifically labeled as low-cholesterol 6.8%Buy foods specifically labeled as low-fat 12.3%Buy foods specifically labeled as sugar-free 10.1%
Composite profile for each category
Frequently check
ingredients
Buy low-calorie foods Diet for
physicalfitness
Diet Exercise
Medical services Smoking
Healthy Community Profile
PROFILING HEALTHY COMMUNITIES
Most to Least Healthy Overall profile, by health behavior category, and by medical outcome
Healthy behaviors cluster
Communities with lower medical outcome rates also have more health-oriented adults (correlative)
Outliers are apparent
Jamul (healthy, but more disease
University (less healthy, low disease)
CommunityHealthy
Community Profile
Diet Exercise Medical Services Smoking Death Hospitalization ED Discharge
Poway 1.8 2.5 1.7 1.7 1.3 4.0 1.0 4.0 San Dieguito 1.9 2.3 2.3 2.2 1.0 2.0 3.0 2.0 North San Diego 2.4 2.1 2.9 2.3 3.0 3.0 3.0 Jamul 2.5 3.7 2.0 1.8 2.7 9.0 8.0 Carlsbad 2.6 2.9 2.4 2.8 2.3 2.0 2.0 2.0 Coastal 2.9 2.9 3.5 3.4 1.7 1.0 1.0 2.0 Valley Center 3.0 4.1 2.7 2.8 2.7 3.0 4.0 Del Mar-Mira Mesa 3.1 3.2 2.7 4.3 2.3 1.0 2.0 2.0 Sweetwater 3.2 3.6 2.4 4.3 2.3 1.0 2.0 1.0 Alpine 3.5 4.7 3.6 2.7 3.0 9.0 5.0 3.0 Elliott-Navajo 3.8 3.7 4.0 3.4 4.0 5.0 4.0 5.0 Harbison Crest 3.9 4.1 3.3 2.8 5.3 Peninsula 4.7 4.3 5.6 6.3 2.7 4.0 3.0 Coronado 4.7 4.6 3.2 5.1 6.0 2.0 1.0 Fallbrook 4.8 5.2 4.1 4.6 5.3 4.0 6.0 6.0 Ramona 4.9 5.4 3.9 5.3 5.0 3.0 7.0 5.0 Santee 5.1 5.5 5.0 3.9 6.0 6.0 8.0 6.0 University 5.2 5.3 6.9 7.5 1.3 2.0 1.0 1.0 Kearny Mesa 5.3 4.6 5.8 5.5 5.3 8.0 5.0 7.0 Palomar-Julian 5.5 5.0 6.0 2.9 8.3 5.0 Spring Valley 5.7 6.1 6.3 5.3 5.0 3.0 8.0 8.0 La Mesa 5.7 5.0 6.3 4.9 6.7 9.0 8.0 8.0 San Marcos 5.8 5.8 5.6 5.6 6.0 7.0 4.0 4.0 Oceanside 6.4 6.5 6.2 6.3 6.7 8.0 6.0 6.0 Central San Diego 6.5 5.7 7.3 7.9 5.0 6.0 9.0 9.0 Anza-Borrego Springs 6.5 6.3 6.9 3.8 9.0 7.0 5.0 Escondido 6.7 7.0 6.8 7.4 5.7 7.0 6.0 7.0 Pauma 6.8 6.2 5.6 7.9 7.3 3.0 3.0 Laguna-Pine Valley 6.8 6.5 6.4 5.5 9.0 Lakeside 7.1 6.9 6.7 5.9 8.7 6.0 4.0 5.0 Vista 7.2 7.4 8.0 7.6 5.7 5.0 7.0 8.0 Lemon Grove 7.4 7.6 8.0 7.4 6.7 4.0 9.0 9.0 El Cajon 7.8 7.3 8.0 7.1 8.7 8.0 7.0 6.0 Mountain Empire 7.8 7.3 7.6 6.4 10.0 10.0 6.0 7.0 South Bay 8.2 8.2 9.3 9.8 5.7 9.0 10.0 9.0 Southeastern San Diego 8.2 8.5 9.1 8.9 6.3 7.0 10.0 10.0
Chula Vista 8.5 8.6 9.3 8.9 7.3 10.0 9.0 10.0 Mid-City 8.7 8.1 8.7 9.0 9.0 5.0 8.0 9.0 National City 8.7 8.7 9.7 9.8 6.7 10.0 10.0 10.0
Composite Healthy Behaviors Ranks Medical Outcome
WHAT THIS ADDS TO OUR GOAL OF BUILDING BETTER HEALTH
Census tract-level data for detailed analysis of community
Estimates of diagnosed diabetes prevalence
Verification that correlations have a significant spatial component
Evaluate community health in areas where medical outcome rates are not
calculable
WHAT THIS ADDS TO OUR GOAL OF BUILDING BETTER HEALTH
Ability to monitor trends & forecast challenges to
population health
Enriched evidence base for data-driven decision-making
Insight into collective impact of key health behaviors
For more information please contact
Dr. Isabel CorcosCounty of San Diego, Health & Human Services Agency
Public Health Services, Emergency Medical [email protected]