1. Constructing a childhood BMI registry: Tracking an Epidemic
Doug Hirano, MPH, 1 and Valentina Hernandez, 2
Asian Pacific Community in Action, Phoenix, AZ
Mountain Park Health Center, AZ

2. Setting
Mountain Park Health Center – FQHC with 5 clinics in metropolitan Phoenix area
Main clinic in South Phoenix serves 10,000 low-income Pediatrics Department patients annually
90% are Hispanic, 4% African American, 4% White

3. Origins of the Registry
Student intern first conducted chart review in 2003 to establish baseline BMIs in Pediatrics Department
Community childhood obesity coalition developed in South Phoenix in 2005
Funding provided in 2007 by the Arizona Department of Health Services supported the initiation of ongoing BMI data entry and analysis

4. Eligibility & Data Parameters
Internal clinic task force developed parameters of BMI registry
Eligibility for inclusion: well child visit, ages 4 – 19 years
Data fields: address, date of birth, gender, race/ethnicity, height, weight, BMI and percentile, diagnosis of selected conditions (diabetes, hypertension, dyslipidemia)

5. Methods
Data Entry Specialist queries the patient management system for the names and chart numbers of children ages 4 – 19 years seen for a well child visit
Charts are pulled from Medical Records and data recorded on spreadsheet
Data are then exported to MS Access for analysis

6. Data Utilization – Assessment Mountain Park Health Center, 2007 – 2008 BMI percentile ranking by age

7. Data Utilization - Trends Mountain Park Health Center, 2003 and 2007 Obesity Rates by Age

8. Data Utilization - Planning

9. Value of BMI Data
Documents problem for resource acquisition (e.g., grants), for catalyzing community efforts (e.g., coalitions) and for advocacy (e.g., policy and environmental changes)
Establishes a baseline with which to track changes over time and to evaluate program/policy efforts
Constitutes an estimate of community-level BMI rates

10. Limitations
Clinic-based data are not necessarily representative of the wider community
BMI among children and adolescents is a moving target that is a function of individual growth rates and lifestyle behaviors such as diet and physical activity

11. Summary
BMI registry is a relatively simple process that has many benefits; may become even easier with advent of EHR
Key resource: data entry
Behavioral risk factor data would nicely augment BMI data
Through geo-mapping, has the potential to become a powerful tool to better understand the epidemic

12. For Further Information
Doug Hirano, MPH Executive Director Asian Pacific Community in Action 6741 N. 7th Street Phoenix, AZ (602)