Karen Tu

Infant feeding practices within a large electronic medical record database

BackgroundThe emerging adoption of the electronic medical record (EMR) in primary care enables clinicians and researchers to efficiently examine epidemiological trends in child health, including infant feeding practices.MethodsWe completed a population-based retrospective cohort study of 8815 singleton infants born at term in Ontario, Canada, April 2002 to March 2013. Newborn records were linked to the Electronic Medical Record Administrative data Linked Database (EMRALD™), which uses patient-level information from participating family practice EMRs across Ontario. We assessed exclusive breastfeeding patterns using an automated electronic search algorithm, with manual review of EMRs when the latter was not possible. We examined the rate of breastfeeding at visits corresponding to 2, 4 and 6xa0months of age, as well as sociodemographic factors associated with exclusive breastfeeding.ResultsOf the 8815 newborns, 1044 (11.8%) lacked breastfeeding information in their EMR. Rates of exclusive breastfeeding were 39.5% at 2xa0months, 32.4% at 4xa0months and 25.1% at 6xa0months. At age 6xa0months, exclusive breastfeeding rates were highest among mothers aged ≥40 vs. < 20xa0years (rate ratio [RR] 2.45, 95% confidence interval [CI] 1.62–3.68), urban vs. rural residence (RR 1.35, 95% CI 1.22–1.50), and highest vs. lowest income quintile (RR 1.18, 95% CI 1.02–1.36). Overall, immigrants had similar rates of exclusive breastfeeding as non-immigrants; yet, by age 6xa0months, among those residing in the lowest income quintile, immigrants were more likely to exclusively breastfeed than their non-immigrant counterparts (RR 1.43, 95% CI 1.12–1.83).ConclusionsWe efficiently determined rates and factors associated with exclusive breastfeeding using data from a large EMR database.

Differences in growth of Canadian children compared to the WHO 2006 Child Growth Standards

BACKGROUNDnTo evaluate if there are departures from the WHO Child Growth Standards (WHO-CGS) in postnatal growth of healthy Canadian children in Ontario up to age 2 years, including by infant feeding and ethnicity.nnnMETHODSnWe included data on 9964 healthy, singleton children born in Ontario, Canada. Smoothed weight, length and body mass index (BMI) percentile curves were generated using quantile regression for the Canadian cohort from birth to age 2 years. Differences in percentile values were calculated comparing Canadian children vs. the WHO-CGS.nnnRESULTSnCanadian children under age 2 years were longer than the WHO-CGS at the 10th (0.8 cm), 50th (1.3 cm) and 90th (1.9 cm) percentiles. Canadian children incrementally surpassed the WHO-CGS in weight after age 6 months, and in BMI after 9 months. By age 2 years, the 50th percentile weight of Canadian males was 823 g (95% confidence interval (CI) 680, 965) higher than the WHO-CGS 50th percentile. Weight differences were seen regardless of feeding practice, and were greatest among children of mothers born in Canada and Europe/Western nations, and least for those of East Asian/Pacific or South Asian heritage. Among Canadian breastfed males, 18% (95% CI 16, 19) of newborns and 26% (95% CI 20, 33) toddlers aged 2 years were classified by WHO-CGS as weighing >90th percentile - much higher than the expected rate of 10%. Similarities were seen for differences in BMI.nnnCONCLUSIONSnHealthy Canadian infants/toddlers are longer and heavier than the WHO-CGS norms. Explanations for these discrepancies require further elucidation.

Temporal trends in multiple sclerosis prevalence and incidence in a large population

Objective We sought to better understand the reasons for increasing prevalence of multiple sclerosis (MS) by studying prevalence in relation to incidence, mortality rates, sex ratio, and geographic distribution of cases. Methods We identified MS cases from 1996 to 2013 in Ontario, Canada, by applying a validated algorithm to health administrative data. We calculated age- and sex-standardized prevalence and incidence rates for the province and by census division. Incidence and prevalence sex ratios for women to men were computed. Results The prevalence of MS increased by 69% from 1.57 (95% confidence interval [CI]: 1.54–1.59) per 1,000 in 1996 (n = 12,155) to 2.65 (95% CI: 2.62–2.68) in 2013 (n = 28,192). Incidence remained relatively stable except for a spike in 2010, followed by a subsequent decline in 2011–2013, particularly among young people and men. Mortality decreased by 33% from 26.7 (95% CI: 23.5–30.3) per 1,000 to 18.0 (95% CI: 16.4–19.8) per 1,000. The incidence sex ratio was stable from 1996 to 2009, then declined in 2010, with partial rebound by 2013. MS prevalence and incidence showed no consistent association with latitude. Conclusion In this large, population-based MS cohort, we found stable incidence and increasing prevalence of MS; the latter largely reflected declining mortality. A spike in incidence in 2010 among younger patients and men at a time of widespread media coverage of MS suggests that these groups may be vulnerable to delayed diagnosis. We did not find a latitudinal gradient; however, most Ontarians live between the 42nd and 46th parallels, reducing our ability to detect an effect of latitude.

Long-term exposure to air pollution and the incidence of multiple sclerosis: A population-based cohort study

Background: Evidence of the adverse neurological effects of exposure to ambient air pollution is emerging, but little is known about its effect on the development of multiple sclerosis (MS), the most common autoimmune disease of the central nervous system. Objectives: To investigate the associations between MS incidence and long‐term exposures to fine particles (PM2.5), nitrogen dioxide (NO2), and ozone (O3) Methods: We conducted a population‐based cohort study to investigate the associations between long‐term exposures to PM2.5, NO2, and O3 and the incidence of MS. Our study population included all Canadian‐born residents aged 20–40 years who lived in the province of Ontario, Canada from 2001 to 2013. Incident MS was ascertained from a validated registry. We assigned estimates of annual concentrations of these pollutants to the residential postal codes of subjects for each year during the 13 years of follow‐up. We estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for each pollutant separately using random‐effects Cox proportional hazards models. We conducted various sensitivity analyses, such as lagging exposure up to 5 years and adjusting for access to neurological care, annual average temperature, and population density. Results: Between 2001 and 2013, we identified 6203 incident cases of MS. The adjusted HR of incident MS was 0.96 (95% CI: 0.86–1.07) for PM2.5, 0.91(95% CI: 0.81–1.02) for NO2, and 1.09 (95% CI: 0.98–1.23) for O3. These results were robust to various sensitivity analyses conducted. Conclusions: In this large population‐based cohort, we did not observe significant associations between MS incidence and long‐term exposures to PM2.5, NO2, and O3 in adults in Ontario, 2001–2013. HighlightsNo associations of MS incidence with PM2.5 and NO2 were observed.There was a tendency for increasing MS incidence in relation to O3.Females exhibited a higher risk of developing MS in association with O3 than males.

Long term outcomes of cluster randomized trial to improve cardiovascular health at population level: The Cardiovascular Health Awareness Program (CHAP)

Study question The Cardiovascular Health Awareness Program (CHAP) cardiovascular risk reduction program consisted of sessions run by local volunteers in local pharmacies during which cardiovascular risk was assessed, healthy lifestyle and preventive care was promoted, and the participants were oriented to local resources to support changes in modifiable risk factors. A clustered randomized trial implemented in September 2006 across 39 communities targeting community-dwelling individuals 65 years and older showed a significant reduction in hospitalization one year after its implementation (rate ratio of 91 [95% confidence interval (CI): 86%-97%]). This study explores the impact of CHAP in the first five years. Methods Using health administrative data housed at the Institute for Clinical Evaluative Sciences, we established a closed cohort consisting of all individuals eligible in these communities at the study onset whom we followed over time. We assessed hospitalizations and survival using a negative binomial model for count data and Cox regression to assess time to first event, accounting for the clustered design. The primary outcome was the rate of cardiovascular-related hospitalizations defined as congestive heart failure, stroke or acute myocardial infarction. Results Most estimates pointed to an advantage for the intervention arm, but only all-cause mortality reached statistical significance (hazard ratio [95% CI] = 0.955 [0.914–0.999]). The hospitalization cardiovascular-related hospitalization rate ratio was (0.958, 95% CI: 0.898–1.022) in favour of the intervention communities, translating to an estimated 408 averted hospitalizations over the five-year period. There was no evidence of the effect of time from start of intervention. Conclusions The consistent direction of the outcomes in favour of the intervention arms suggests that CHAP likely had a meaningful impact on reducing cardiovascular-related morbidity and mortality. Given the low cost of the intervention, further development of CHAP should be pursued.

Rotavirus vaccine coverage and factors associated with uptake using linked data: Ontario, Canada

Background In August 2011, Ontario, Canada introduced a rotavirus immunization program using Rotarix™ vaccine. No assessments of rotavirus vaccine coverage have been previously conducted in Ontario. Methods We assessed vaccine coverage (series initiation and completion) and factors associated with uptake using the Electronic Medical Record Administrative data Linked Database (EMRALD), a collection of family physician electronic medical records (EMR) linked to health administrative data. Series initiation (1 dose) and series completion (2 doses) before and after the program’s introduction were calculated. To identify factors associated with series initiation and completion, adjusted odds ratios (aOR) and 95% confidence intervals (95%CI) were calculated using logistic regression. Results A total of 12,525 children were included. Series completion increased each year of the program (73%, 79% and 84%, respectively). Factors associated with series initiation included high continuity of care (aOR = 2.15; 95%CI, 1.61–2.87), maternal influenza vaccination (aOR = 1.55; 95%CI,1.24–1.93), maternal immmigration to Canada in the last five years (aOR = 1.47; 95% CI, 1.05–2.04), and having no siblings (aOR = 1.62; 95%CI,1.30–2.03). Relative to the first program year, infants were more likely to initiate the series in the second year (aOR = 1.71; 95% CI 1.39–2.10) and third year (aOR = 2.02; 95% CI 1.56–2.61) of the program. Infants receiving care from physicians with large practices were less likely to initiate the series (aOR 0.91; 95%CI, 0.88–0.94, per 100 patients rostered) and less likely to complete the series (aOR 0.94; 95%CI, 0.91–0.97, per 100 patients rostered). Additional associations were identified for series completion. Conclusions Family physician delivery achieved moderately high coverage in the program’s first three years. This assessment demonstrates the usefulness of EMR data for evaluating vaccine coverage. Important insights into factors associated with initiation or completion (i.e. high continuity of care, smaller roster sizes, rural practice location) suggest areas for research and potential program supports.

Completeness and accuracy of anthropometric measurements in electronic medical records for children attending primary care

Background Electronic medical records (EMRs) from primary care may be a feasible source of height and weight data. However, the use of EMRs in research has been impeded by lack of standardisation of EMRs systems, data access and concerns about the quality of the data. Objectives The study objectives were to determine the data completeness and accuracy of child heights and weights collected in primary care EMRs, and to identify factors associated with these data quality attributes. Methods A cross-sectional study examining height and weight data for children <19 years from EMRs through the Electronic Medical Record Administrative data Linked Database (EMRALD), a network of family practices across the province of Ontario. Body mass index z-scores were calculated using the World Health Organization Growth Standards and Reference. Results A total of 54,964 children were identified from EMRALD. Overall, 93% had at least one complete set of growth measurements to calculate a body mass index (BMI) z-score. 66.2% of all primary care visits had complete BMI z-score data. After stratifying by visit type 89.9% of well-child visits and 33.9% of sick visits had complete BMI z-score data; incomplete BMI z-score was mainly due to missing height measurements. Only 2.7% of BMI z-score data were excluded due to implausible values. Conclusions Data completeness at well-child visits and overall data accuracy were greater than 90%. EMRs may be a valid source of data to provide estimates of obesity in children who attend primary care.

Effects of ambient air pollution on incident Parkinson’s disease in Ontario, 2001 to 2013: a population-based cohort study

BackgroundnDespite recent studies linking air pollution to neurodegenerative illness, evidence relating air pollution and Parkinsons disease (PD) remains scarce. We conducted a population-based cohort study in Ontario, Canada, to determine the association between air pollution and incident PD.nnnMethodsnUsing health administrative databases, we identified all adults aged 55-85u2009years, free of PD, and who lived in Ontario on 1 April 2001 (∼2.2 million). Individuals were followed up until 31 March 2013. We derived long-term average exposures to fine particulate matter (particles ≤2.5u2009µm in diameter, or PM2.5), nitrogen dioxide (NO2) and ozone from satellite-based estimates, land-use regression models and optimal interpolation methods, respectively. Using 2-year lags in exposures, we linked these estimates to individuals annual postal codes from 1994 (7 years before cohort inception). We applied spatial random-effects Cox proportional hazards models, adjusting for individual- and area-level characteristics. We also performed sensitivity analyses, such as considering longer lags in exposures and stratifying by selected characteristics.nnnResultsnDuring the study period, we identified 38xa0745 newly diagnosed cases of PD. Each interquartile increment (3.8u2009µg/m3) of PM2.5 was associated with a 4% increase in incident PD (95% confidence interval, 1.01-1.08) after adjusting for various covariates. We also found positive associations for NO2 and ozone [hazard ratios (HRs) ranged from 1.03 to 1.04]. The associations for all exposures were unaltered with various sensitivity analyses except for considering longer lags, which somewhat attenuated the estimates, particularly for NO2 and ozone.nnnConclusionsnExposure to air pollution, especially PM2.5, was found to be related to incident PD.

Identifying diabetes cases from administrative data: a population-based validation study

BackgroundHealth care data allow for the study and surveillance of chronic diseases such as diabetes. The objective of this study was to identify and validate optimal algorithms for diabetes cases within health care administrative databases for different research purposes, populations, and data sources.MethodsWe linked health care administrative databases from Ontario, Canada to a reference standard of primary care electronic medical records (EMRs). We then identified and calculated the performance characteristics of multiple adult diabetes case definitions, using combinations of data sources and time windows.ResultsThe best algorithm to identify diabetes cases was the presence at any time of one hospitalization or physician claim for diabetes AND either one prescription for an anti-diabetic medication or one physician claim with a diabetes-specific fee code [sensitivity 84.2%, specificity 99.2%, positive predictive value (PPV) 92.5%]. Use of physician claims alone performed almost as well: three physician claims for diabetes within one year was highly specific (sensitivity 79.9%, specificity 99.1%, PPV 91.4%) and one physician claim at any time was highly sensitive (sensitivity 93.6%, specificity 91.9%, PPV 58.5%).ConclusionsThis study identifies validated algorithms to capture diabetes cases within health care administrative databases for a range of purposes, populations and data availability. These findings are useful to study trends and outcomes of diabetes using routinely-collected health care data.

Trends in the prevalence and incidence of psoriasis and psoriatic arthritis in Ontario, Canada: A population-based study

To estimate the prevalence and incidence of psoriasis and psoriatic arthritis (PsA) over time in Ontario, Canada.