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Objectives: The Healthy Kids Community Challenge is a large-scale, centrally-coordinated, community-based intervention in Ontario, Canada that promotes healthy behaviours towards improving healthy weights among children. With the goal of exploring tools available to evaluators, we leveraged electronic medical records from primary care physicians to assess child weights prior to launch of the Healthy Kids Community Challenge. This study compares the baseline (i.e. pre-intervention) prevalence of overweight and obesity in children 1–12 years of age living within and outside Healthy Kids Community Challenge communities. Design: Cross-sectional analysis of a primary care patient cohort. Setting: Electronic Medical Record Administrative data Linked Database (EMRALD) in Ontario, Canada. Participants: A cohort of 19 920 Ontario children who are rostered to an EMRALD physician. Children were 1–12 years of age at a primary care visit with recorded measured height and weight, between January 1, 2014 and December 31, 2015. Outcome measure: Overweight and obesity as determined by age- and sex-standardized body mass index using World Health Organization’s Growth Standards. Results: In Healthy Kids Community Challenge communities, 25.6% (95% CI 24.6–26.6%) of children had zBMI above normal (i.e. >1) compared to 26.7% (95% CI 25.9–27.5%) for children living outside of Healthy Kids Community Challenge communities. Conclusions: Despite some differences in sociodemographic characteristics, zBMI of children aged 1–12 years were similar inside and outside of Healthy Kids Community Challenge community boundaries prior to program launch. [ABSTRACT FROM AUTHOR]

Background: Food insecurity is associated with a wide array of negative health outcomes and higher health care costs but there has been no population-based study of the association of food insecurity and mortality in high-income countries. Methods: We use cross-sectional population surveys linked to encoded health administrative data. The sample is 90,368 adults, living in Ontario and respondents in the Canadian Community Health Survey (CCHS). The outcome of interest is all-cause mortality at any time after the interview and within four years of the interview. The primary variable of interest is food insecurity status, with individuals classed as “food secure”, “marginally food insecure”, “moderately food insecure”, or “severely food insecure”. We use logistic regression models to determine the association of mortality with food insecurity status, adjusting for other social determinants of health. Results: Using a full set of covariates, in comparison to food secure individuals, the odds of death at any point after the interview are 1.28 (CI = 1.08, 1.52) for marginally food insecure individuals, 1.49 (CI = 1.29, 1.73) for moderately food insecure individuals, and 2.60 (CI = 2.17, 3.12) for severely food insecure individuals. When mortality within four years of the interview is considered, the odds are, respectively, 1.19 (CI = 0.95, 1.50), 1.65 (CI = 1.37, 1.98), and 2.31 (CI = 1.81, 2.93). Interpretation: These findings demonstrate that food insecurity is associated with higher mortality rates and these higher rates are especially large for the most severe food insecurity category. Efforts to reduce food insecurity should be incorporated into broader public health initiatives to reduce mortality. [ABSTRACT FROM AUTHOR]

Importance: RSV is a common illness among young children that causes significant morbidity and health care costs. Objective: Routinely collected health administrative data can be used to track disease incidence, explore risk factors and conduct health services research. Due to potential for misclassification bias, the accuracy of data-elements should be validated prior to use. The objectives of this study were to validate an algorithm to accurately identify pediatric cases of hospitalized respiratory syncytial virus (RSV) from within Ontario’s health administrative data, estimate annual incidence of hospitalization due to RSV and report the prevalence of major risk factors within hospitalized patients. Study Design and Setting: A retrospective chart review was performed to establish a reference-standard cohort of children from the Ottawa region admitted to the Children’s Hospital of Eastern Ontario (CHEO) for RSV-related disease in 2010 and 2011. Chart review data was linked to Ontario’s administrative data and used to evaluate the diagnostic accuracy of algorithms of RSV-related ICD-10 codes within provincial hospitalization and emergency department databases. Age- and sex-standardized incidence was calculated over time, with trends in incidence assessed using Poisson regression. Results: From a total of 1411 admissions, chart review identified 327 children hospitalized for laboratory confirmed RSV-related disease. Following linkage to administrative data and restriction to first admissions, there were 289 RSV patients in the reference-standard cohort. The best algorithm, based on hospitalization data, resulted in sensitivity 97.9% (95%CI: 95.5–99.2%), specificity 99.6% (95%CI: 98.2–99.8%), PPV 96.9% (95%CI: 94.2–98.6%), NPV 99.4% (95%CI: 99.4–99.9%). Incidence of hospitalized RSV in Ontario from 2005–2012 was 10.2 per 1000 children under 1 year and 4.8 per 1000 children aged 1 to 3 years. During the surveillance period, there was no identifiable increasing or decreasing linear trend in the incidence of hospitalized RSV, hospital length of stay and PICU admission rates. Among the Ontario RSV cohort, 16.3% had one or more major risk factors, with a decreasing trend observed over time. Conclusion: Children hospitalized for RSV-related disease can be accurately identified within population-based health administrative data. RSV is a major public health concern and incidence has not changed over time, suggesting a lack of progress in prevention. [ABSTRACT FROM AUTHOR]