AN AGE-PERIOD-COHORT ANALYSIS OF HEALTH STATUS AND HEALTHCARE USE IN CANADA: ARE BABY BOOMERS DIFFERENT FROM OTHER GENERATIONS?
Bibliographic record
Abstract
BACKGROUND: There are concerns for the provision of healthcare services in Canada given the large numbers of ageing baby boomers. However, little is known about how they differ in their health profile and patterns of healthcare use compared to other generations. This thesis describes three studies, based on a longitudinal survey of the population, examining the trajectories of multimorbidity and healthcare use (i.e. conventional care and complementary and alternative medicine (CAM)) across five birth cohorts. METHODS: Using data from the Longitudinal National Population Health Survey (1994-2011), the thesis studies examined 10186 participants belonging to one of the five birth cohorts: pre World War II (born: 1925-1934), World War II (born: 1935-1944), older (born: 1945-1954) and younger (born: 1955-1964) baby boomers, and Generation X (Gen Xers, born: 1965-1974). Hierarchical age-period-cohort analysis was used to examine the contributions of age (life-course), period, and cohort effects in changes in multimorbidity, use of conventional care (i.e. primary care and specialist services users), and CAM use. RESULTS: Each succeeding recent cohort had higher odds of reporting multimorbidity than their predecessors. Furthermore, Gen Xers and younger boomers, particularly those with multimorbidity, were less likely to use primary care than earlier cohorts. The increasing levels of multimorbidity explained the higher specialist use observed in recent cohorts. Likewise, at corresponding ages, more recent cohorts reported greater chiropractic and CAM use than their predecessors. The use of conventional care was positively related to greater CAM use, but did not contribute to changes over time or to cohort differences in CAM use. CONCLUSIONS: There is a need for policies addressing important generational differences in healthcare preferences and the balance between primary and specialty care to ensure integration and coordination of healthcare delivery. The findings also highlight the importance of planning interventions and policies to deal with more recent birth cohorts entering into older age with worse health than previous generations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".