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INTRODUCTION: With obesity rates and obesity-related healthcare costs increasing, policy makers must understand the scope of obesity across populations. OBJECTIVE: This study sought to characterize adult obesity using electronic health records (EHRs) available from a statewide clinical data research network, the OneFlorida Clinical Research Consortium, which contains claims and EHR data from over 12 million patients in Florida. The primary aim was to compare EHR-based Florida obesity rates with those rates obtained from the Behavioural Risk Factor Surveillance System (BRFSS). METHODS: Body mass index from OneFlorida patient data (2012-2016) was used to characterize obesity among adults 20-79 years old. Obesity rates from both OneFlorida and BRFSS (2013) were reported by demographics and by county. RESULTS: Among the 1,344,015 adults in OneFlorida with EHR data and who met inclusion criteria, the obesity rate was 37.1%. Women had higher obesity rates compared with men. Obesity rates varied within racial/ethnic groups, with the highest rate among African-Americans (45.7%). Obesity rates from OneFlorida were consistently higher than those found in BRFSS (overall 27.8%). CONCLUSIONS: Utilizing clinical big data available through hospital system and health partner collaborations provides an important view of the extent of obesity. Although these data are available only from healthcare users, they are large in scope, directly measured and are available sooner than commonly used national data sources.
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BACKGROUND: How the longitudinal asthma control status and other socio-demographic factors influence the changes of health-related quality of life (HRQOL) among asthmatic children, especially from low-income families, has not been fully investigated. OBJECTIVES: This study aimed to describe the trajectories of asthma-specific HRQOL over 15 months and examine the effect of asthma control status on HRQOL by taking socio-demographic factors into consideration. METHODS: A total of 229 dyads of asthmatic children and their parents enroled in public insurance programs were recruited for assessing asthma control status and HRQOL over four time points of assessment. Asthma control status was measured using the Asthma Control and Communication Instrument, and asthma-specific HRQOL was assessed using the Patient-Reported Outcomes Measurement Information System's Pediatric Asthma Impact Scale. Latent growth models (LGMs) were applied to examine the trajectory of HRQOL and the factors contributing to the changes of HRQOL. RESULTS: Unconditional LGM revealed that HRQOL was improved over time. Conditional LGM suggested that accounting for asthma control and participants' socio-demographic factors, the variation in the initial level of HRQOL was significant, yet the rate of change was not. Conditional LGM also revealed that poorly controlled asthma status was associated with poor HRQOL at each time point (P's < 0.05). Lower parental education was associated with lower baseline HRQOL (P < 0.05). Hispanic children had a larger increase in HRQOL over time (P < 0.01) than non-Hispanic White children. CONCLUSIONS: Vulnerable socio-demographic characteristics and poorly controlled asthma status affect HRQOL in children. This finding encourages interventions to improve asthma control status and HRQOL in minority children.