Michael Lebenbaum

Prevalence of Prediabetes and Undiagnosed Diabetes in Canada (2007–2011) According to Fasting Plasma Glucose and HbA1c Screening Criteria

OBJECTIVE To provide the first population-based estimates of prediabetes and undiagnosed type 2 diabetes prevalence in Canada. RESEARCH DESIGN AND METHODS We combined two fasting subsamples of the Canadian Health Measures Survey, which were restricted to nonpregnant adults ≥20 years of age (N = 3,494). Undiagnosed diabetes was defined as not having self-reported type 2 diabetes but having blood glucose measures that met Canadian guidelines (i.e., fasting plasma glucose [FPG] level of ≥7.0 mmol/L or hemoglobin A1c [HbA1c] level of ≥6.5% [≥48 mmol/mol]). Prediabetes was defined as an FPG level of ≥6.1 and <7.0 mmol/L or an HbA1c level of ≥6.0% and <6.5% (≥42 and <48 mmol/mol). All estimates were weighted using survey sampling weights. CIs were calculated with the bootstrap method. RESULTS According to FPG levels, the prevalence of undiagnosed type 2 diabetes in Canadian adults was 1.13% (95% CI 0.79, 1.62), contributing to ∼20% of total type 2 diabetes prevalence (5.62 [95% CI 4.52, 6.95]). Compared with FPG levels, the undiagnosed prevalence was greater using HbA1c level as a criterion (3.09% [95% CI 1.97, 4.81]), ∼41% of the total number of cases of diabetes (7.55 [95% CI 5.98, 9.49]). The HbA1c-only criterion resulted in a threefold increase in prediabetes prevalence overall and a sixfold increase among females (FPG 2.22%, HbA1c 13.31%). Screening based on FPG only identified older undiagnosed case patients, with a mean age of 58.7 years (95% CI 59.9, 63.4). Similarly, using HbA1c identified younger individuals with prediabetes, with reduced BMI and waist circumference compared with FPG levels. CONCLUSIONS In this first study of a nationally representative sample with biospecimen measures, we found that the prevalence of undiagnosed type 2 diabetes and prediabetes was significantly higher using HbA1c levels compared with FPG levels. Further evaluation is needed to fully assess the impact of using the HbA1c criterion.

Neighborhood walkability: differential associations with self-reported transport walking and leisure-time physical activity in Canadian towns and cities of all sizes.

OBJECTIVE To estimate associations between walkability and physical activity during transportation and leisure in a national-level population. METHODS Walkability was measured by Walk Score® (2012-2014) and physical activity by the Canadian Community Health Survey (2007-2012) for urban participants who worked or attended school. Multiple linear regression was done on the total study population, four age subgroups (12-17, 18-29, 30-64, 65+) and three population center subgroups (1000-29,999, 30,000-99,999, 100,000+). RESULTS 151,318 respondents were examined. Comparing highest to lowest Walk Score® quintiles, covariate-adjusted energy expenditure on transport walking [95% confidence interval] was 0.17 [0.15, 0.18] kcal/kg/day higher in the total study population, and significantly higher in all age and population center subgroups. Leisure physical activity was lower in the age 18-29 subgroup (-0.28 [-0.43, -0.12]) and population centers 100,000+ subgroup (-0.10 [-0.18, -0.03]), but higher in the population centers 1000-29,999 subgroup (0.30 [0.12, 0.48]). Total physical activity was higher in the following subgroups: age 30-64 (0.19 [0.12, 0.26]), population centers 100,000+ (0.12 [0.04, 0.19]) and population centers 1000-29,999 (0.40 [0.20, 0.59]). CONCLUSIONS Walkability is associated with transport walking in all age groups and towns and cities of all sizes. Walkabilitys inverse associations with leisure physical activity among young adults and in large population centers may offset energy expenditure gains, while positive associations with leisure physical activity in small centers may add to energy expenditure.

The Prevalence of Undiagnosed and Prediabetes Diabetes in Canada (2007–2011) According to Fasting Plasma Glucose and HbA1c Screening Criteria

OBJECTIVE To provide the first population-based estimates of prediabetes and undiagnosed type 2 diabetes prevalence in Canada. RESEARCH DESIGN AND METHODS We combined two fasting subsamples of the Canadian Health Measures Survey, which were restricted to nonpregnant adults ≥20 years of age (N = 3,494). Undiagnosed diabetes was defined as not having self-reported type 2 diabetes but having blood glucose measures that met Canadian guidelines (i.e., fasting plasma glucose [FPG] level of ≥7.0 mmol/L or hemoglobin A1c [HbA1c] level of ≥6.5% [≥48 mmol/mol]). Prediabetes was defined as an FPG level of ≥6.1 and <7.0 mmol/L or an HbA1c level of ≥6.0% and <6.5% (≥42 and <48 mmol/mol). All estimates were weighted using survey sampling weights. CIs were calculated with the bootstrap method. RESULTS According to FPG levels, the prevalence of undiagnosed type 2 diabetes in Canadian adults was 1.13% (95% CI 0.79, 1.62), contributing to ∼20% of total type 2 diabetes prevalence (5.62 [95% CI 4.52, 6.95]). Compared with FPG levels, the undiagnosed prevalence was greater using HbA1c level as a criterion (3.09% [95% CI 1.97, 4.81]), ∼41% of the total number of cases of diabetes (7.55 [95% CI 5.98, 9.49]). The HbA1c-only criterion resulted in a threefold increase in prediabetes prevalence overall and a sixfold increase among females (FPG 2.22%, HbA1c 13.31%). Screening based on FPG only identified older undiagnosed case patients, with a mean age of 58.7 years (95% CI 59.9, 63.4). Similarly, using HbA1c identified younger individuals with prediabetes, with reduced BMI and waist circumference compared with FPG levels. CONCLUSIONS In this first study of a nationally representative sample with biospecimen measures, we found that the prevalence of undiagnosed type 2 diabetes and prediabetes was significantly higher using HbA1c levels compared with FPG levels. Further evaluation is needed to fully assess the impact of using the HbA1c criterion.

Cardiovascular Disease Population Risk Tool (CVDPoRT): predictive algorithm for assessing CVD risk in the community setting. A study protocol

Introduction Recent publications have called for substantial improvements in the design, conduct, analysis and reporting of prediction models. Publication of study protocols, with prespecification of key aspects of the analysis plan, can help to improve transparency, increase quality and protect against increased type I error. Valid population-based risk algorithms are essential for population health planning and policy decision-making. The purpose of this study is to develop, evaluate and apply cardiovascular disease (CVD) risk algorithms for the population setting. Methods and analysis The Ontario sample of the Canadian Community Health Survey (2001, 2003, 2005; 77 251 respondents) will be used to assess risk factors focusing on health behaviours (physical activity, diet, smoking and alcohol use). Incident CVD outcomes will be assessed through linkage to administrative healthcare databases (619 886 person-years of follow-up until 31 December 2011). Sociodemographic factors (age, sex, immigrant status, education) and mediating factors such as presence of diabetes and hypertension will be included as predictors. Algorithms will be developed using competing risks survival analysis. The analysis plan adheres to published recommendations for the development of valid prediction models to limit the risk of overfitting and improve the quality of predictions. Key considerations are fully prespecifying the predictor variables; appropriate handling of missing data; use of flexible functions for continuous predictors; and avoiding data-driven variable selection procedures. The 2007 and 2009 surveys (approximately 50 000 respondents) will be used for validation. Calibration will be assessed overall and in predefined subgroups of importance to clinicians and policymakers. Ethics and dissemination This study has been approved by the Ottawa Health Science Network Research Ethics Board. The findings will be disseminated through professional and scientific conferences, and in peer-reviewed journals. The algorithm will be accessible electronically for population and individual uses. Trial registration number ClinicalTrials.gov NCT02267447.

Ethnic Differences in Mental Illness Severity: A Population-Based Study of Chinese and South Asian Patients in Ontario, Canada.

OBJECTIVE Little is known about the sociocultural determinants of mental illness at hospital presentation. Our objective was to examine ethnic differences in illness severity at hospital admission among Chinese, South Asian, and the general population living in Ontario, Canada. METHODS We conducted a large, population-based, cross-sectional study of psychiatric inpatients aged from 19 to 105 years who were discharged between 2006 and 2014. A total of 133,588 patients were classified as Chinese (n = 2,582), South Asian (n = 2,452), or the reference group (n = 128,554) using a validated surnames algorithm (specificity: 99.7%). Diagnoses were based on DSM-IV criteria. We examined the association between ethnicity and 4 measures of disease severity: involuntary admissions, aggressive behaviors, and the number and frequency of positive symptoms (ie, hallucinations, command hallucinations, delusions, and abnormal thought process) (Positive Symptoms Scale, Resident Assessment Instrument-Mental Health [RAI-MH]). RESULTS After adjusting for sociodemographic characteristics, immigration status, and discharge diagnosis, Chinese patients had greater odds of involuntary admissions (odds ratio [OR] = 1.79; 95% CI, 1.64-1.95) and exhibiting severe aggressive behaviors (OR = 1.36; 95% CI, 1.23-1.51) and ≥ 3 positive symptoms (OR = 1.39; 95% CI, 1.24-1.56) compared to the general population. South Asian ethnicity was also an independent predictor of most illness severity measures. The association between Chinese ethnicity and illness severity was consistent across sex, diagnostic and immigrant categories, and first-episode hospitalization. CONCLUSIONS Chinese and South Asian ethnicities are independent predictors of illness severity at hospital presentation. Understanding the role of patient, family, and health system factors in determining the threshold for hospitalization is an important future step in informing culturally specific care for these large and growing populations worldwide.

Risk distribution and its influence on the population targets for diabetes prevention.

OBJECTIVE To quantify the influence of type 2 diabetes risk distribution on prevention benefit and apply a method to optimally identify population targets. METHODS We used data from the 2011 Canadian Community Health Survey (N=45,040) and the validated Diabetes Population Risk Tool to calculate 10-year diabetes risk. We calculated the Gini coefficient as a measure of risk dispersion. Intervention benefit was estimated using absolute risk reduction (ARR), number-needed-to-treat (NNT), and number of cases prevented. RESULTS There is a wide variation of diabetes risk in Canada (Gini=0.48) and with an inverse relation to risk (r=-0.99). Risk dispersion is lower among individuals meeting an empirically derived risk cut-off (Gini=0.18). Targeting prevention based on a risk cut-off (10-year risk ≥ 16.5%) resulted in a greater number of cases prevented (340 thousand), higher ARR (7.7%) and lower NNT (13) compared to targeting individuals based on risk factor targets. CONCLUSIONS This study provides empirical evidence to demonstrate that risk variability is an important consideration for estimating the prevention benefit. Prioritizing target populations using an empirically derived cut-off based on a multivariate risk score will result in greater benefit and efficiency compared to risk factor targets.

Availability, Location, and Format of Nutrition Information in Fast-food Chain Restaurants in Ontario, Canada

PURPOSE To assess the availability, location, and format of nutrition information in fast-food chain restaurants in Ontario. METHODS Nutrition information in restaurants was assessed using an adapted version of the Nutrition Environment Measures Study for Restaurants (NEMS-R). Two raters independently visited 50 restaurants, 5 outlets of each of the top-10 fast-food chain restaurants in Canada. The locations of the restaurants were randomly selected within the Waterloo, Wellington, and Peel regions in Ontario, Canada. Descriptive results are presented for the proportion of restaurants presenting nutrition information by location (e.g., brochure), format (e.g., use of symbols), and then by type of restaurant (e.g., quick take-away, full-service). RESULTS Overall, 96.0% (n = 48) of the restaurants had at least some nutrition information available in the restaurant. However, no restaurant listed calorie information for all items on menu boards or menus, and only 14.0% (n = 7) of the restaurants posted calorie information and 26.0% (n = 13) of restaurants posted other nutrients (e.g., total fat) for at least some items on menus boards or menus. CONCLUSIONS The majority of the fast-food chain restaurants included in our study provided at least some nutrition information in restaurants; however, very few restaurants made nutrition information readily available for consumers on menu boards and menus.

Development and validation of a population based risk algorithm for obesity: The Obesity Population Risk Tool (OPoRT)

Background Given the dramatic rise in the prevalence of obesity, greater focus on prevention is necessary. We sought to develop and validate a population risk tool for obesity to inform prevention efforts. Methods We developed the Obesity Population Risk Tool (OPoRT) using the longitudinal National Population Health Survey and sex-specific Generalized Estimating Equations to predict the 10-year risk of obesity among adults 18 and older. The model was validated using a bootstrap approach accounting for the survey design. Model performance was measured by the Brier statistic, discrimination was measured by the C-statistic, and calibration was assessed using the Hosmer-Lemeshow Goodness of Fit Chi Square (HL χ2). Results Predictive factors included baseline body mass index, age, time and their interactions, smoking status, living arrangements, education, alcohol consumption, physical activity, and ethnicity. OPoRT showed good performance for males and females (Brier 0.118 and 0.095, respectively), excellent discrimination (C statistic ≥ 0.89) and achieved calibration (HL χ2 <20). Conclusion OPoRT is a valid and reliable algorithm that can be applied to routinely collected survey data to estimate the risk of obesity and identify groups at increased risk of obesity. These results can guide prevention efforts aimed at reducing the population burden of obesity.

Prevalence and predictors of involuntary psychiatric hospital admissions in Ontario, Canada: a population-based linked administrative database study

Background Involuntary admissions to psychiatric hospitals are common; however, research examining the trends in prevalence over time and predictors is limited. Aims To examine trends in prevalence and risk factors for involuntary admissions in Ontario, Canada. Method We conducted an analysis of all mental health bed admissions from 2009 to 2013 and assessed the association between patient sociodemographics, service utilisation, pathway to care and severity characteristics for involuntary admissions using a modified Poisson regression. Results We found a high and increasing prevalence of involuntary admissions (70.7% in 2009, 77.1% in 2013, 74.1% overall). Individuals with police contact in the prior week (risk ratio (RR) = 1.20) and immigrants both experienced greater likelihood of being involuntarily admitted, regardless of control for other characteristics (RR = 1.07) (both P < 0.0001). Conclusions We identified numerous modifiable and non-modifiable risk factors for involuntary admissions. The prevalence of involuntary admissions was high, linearly increasing over time. Declaration of interest The authors have completed the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported. This study was conducted using funding entirely from public sources. P.K. has received operational support via an Ontario Ministry of Health and Long-Term Care (MOHLTC) Health Services Research Fund Capacity Award to support this project. The Institute for Clinical Evaluative Sciences (ICES) is funded by the Ontario MOHLTC. The study results and conclusions are those of the authors, and should not be attributed to any of the funding agencies or sponsoring agencies. No endorsement by ICES or the Ontario MOHLTC is intended or should be inferred. All decisions regarding study design, publication, and data analysis were made independent of the funding agencies.

The direct healthcare costs associated with psychological distress and major depression: A population-based cohort study in Ontario, Canada

The objective of our study was to estimate direct healthcare costs incurred by a population-based sample of people with psychological distress or depression. We used the 2002 Canadian Community Health Survey on Mental Health and Well Being and categorized individuals as having psychological distress using the Kessler-6, major depressive disorder (MDD) using DSM-IV criteria and a comparison group of participants without MDD or psychological distress. Costs in 2013 USD were estimated by linking individuals to health administrative databases and following them until March 31, 2013. Our sample consisted of 9,965 individuals, of whom 651 and 409 had psychological distress and MDD, respectively. Although the age-and-sex adjusted per-capita costs were similarly high among the psychologically distressed (