Abstract
BackgroundPremature mortality is an important population health indicator used to assess health system functioning and to identify areas in need of health system intervention. Predicting the future incidence of premature mortality in the population can facilitate initiatives that promote equitable health policies and effective delivery of public health services. This study protocol proposes the development and validation of the Premature Mortality Risk Prediction Tool (PreMPoRT) that will predict the incidence of premature mortality using large population-based community health surveys and multivariable modeling approaches.MethodsPreMPoRT will be developed and validated using various training, validation, and test data sets generated from the six cycles of the Canadian Community Health Survey (CCHS) linked to the Canadian Vital Statistics Database from 2000 to 2017. Population-level risk factor information on demographic characteristics, health behaviors, area level measures, and other health-related factors will be used to develop PreMPoRT and to predict the incidence of premature mortality, defined as death prior to age 75, over a 5-year period. Sex-specific Weibull accelerated failure time models will be developed using a Canadian provincial derivation cohort consisting of approximately 500,000 individuals, with approximately equal proportion of males and females, and about 12,000 events of premature mortality. External validation will be performed using separate linked files (CCHS cycles 2007–2008, 2009–2010, and 2011–2012) from the development cohort (CCHS cycles 2000–2001, 2003–2004, and 2005–2006) to check the robustness of the prediction model. Measures of overall predictive performance (e.g., Nagelkerke’s R2), calibration (e.g., calibration plots), and discrimination (e.g., Harrell’s concordance statistic) will be assessed, including calibration within defined subgroups of importance to knowledge users and policymakers.DiscussionUsing routinely collected risk factor information, we anticipate that PreMPoRT will produce population-based estimates of premature mortality and will be used to inform population strategies for prevention.
Highlights
Premature mortality is an important population health indicator used to assess health system functioning and to identify areas in need of health system intervention
Premature mortality is an indicator that represents the concept of an unfulfilled life expectancy and is meaningful in the context of public health as premature deaths are largely amenable to targeted policy and programmatic interventions [1, 2]
Premature mortality is an important indicator of population health that has been used to assess health system functioning and to identify areas in need of targeted health system intervention
Summary
Data sources PreMPoRT will use national population-based survey data from the Canadian Community Health Survey (CCHS) linked to the Canadian Vital Statistics Database (CVSD). The external validation will examine the prediction models’ performance in the same source population but using different individuals surveyed over a different time period For both development and validation cohorts, respondents will be excluded if they were under the age of 18 or older than 74 years as of the CCHS interview date. The full Canadian dataset will be used to derive final regression coefficients, in an effort to optimize the sample size and follow-up period with the same predictor variables and form as specified in the derivation model This approach is recommended as differences in regression coefficients between the development and validation dataset are expected to be small and using the full dataset facilitates stability in regression estimates [41]. Arthritis, back problems, high blood pressure, migraines, emphysema, chronic obstructive pulmonary disease, diabetes, heart disease, cancer, intestinal ulcers, stroke, urinary incontinence, bowel disease, mood disorder, or anxiety disorder
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