Evaluating methods to define place of residence in Canadian administrative data and the impact on observed associations with all-cause mortality in type 2 diabetes
Bibliographic record
Abstract
An individual’s location of residence may impact health, however, health services and outcomes research generally use a single point in time to define where an individual resides. While this estimate of residence becomes inaccurate when the study subject moves, the impact on observed associations is not known. This study quantifies the impact of different methods to define residence (rural, urban, metropolitan) on the association with all-cause mortality. A diabetes cohort of new metformin users was identified from administrative data in Alberta, Canada between 2008 and 2019. An individual’s residence (rural/urban/metropolitan) was defined from postal codes using 4 different methods: residence defined at 1-year before first metformin (this served as the reference model), comparison 1- stable residence for 3 years before first metformin, comparison 2– residence as time-varying (during the outcome observation window), and comparison 3 - nested case control (residence closest to the index date after identifying cases and controls). Multivariable Cox proportional hazard and logistic regression models were constructed to examine the association between residence definitions and all-cause mortality. We identified 157,146 new metformin users (mean age of 55 years and 57% male) and 8,444 (5%) deaths occurred during the mean follow up of 4.7 (SD 2.3) years. There were few instances of moving after first metformin; 2.6% of individuals moved to a smaller centre (metropolitan to urban or rural, or urban to rural) and 3.1% moved to a larger centre (rural to urban or metropolitan, or urban to metropolitan). The association between rural residence and all-cause mortality was consistent (aHR:1.18; 95%CI:1.12–1.24), regardless of the method used to define residence. The method used to define residence in a population of adults newly treated with metformin for type 2 diabetes has minimal impact on measures of all-cause mortality, possibly due to infrequent migration. The observed association between residence and mortality is compelling but requires further investigation and more robust analysis. There is growing evidence describing the impact of where an individual lives on their health. However, most of these studies identify place of residence at a single point in time and do not consider when a person moves. This could result in misclassification, which could over- or underestimate the influence of residence on health outcomes. In this study, residence was defined with 4 different methods: at 1-year before starting metformin for type 2 diabetes; stable residence for 3-years before starting metformin; accounting for changes in residence after being newly treated with metformin for type 2 diabetes; and near the end of the study at death or the end of follow up. The results of this study describe that individuals rarely move after treatment initiation with metformin for type 2 diabetes and that living in a rural area has a higher risk of death from any cause, further investigation into the latter is required. Individuals rarely move after treatment initiation with metformin for type 2 diabetes. In population-based cohort studies of adults with type 2 diabetes, classifying place of residence at baseline, 1-year prior to the index date is reasonable. The increased mortality of rural residents requires further investigation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.083 | 0.330 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".