A Nationwide Physical Activity Intervention for 654,500 Adults in Singapore: Cost-Utility Analysis
Bibliographic record
Abstract
Background: Increasing physical inactivity is a primary risk factor for diabetes and hypertension, contributing to rising health care expenditure and productivity losses. As Singapore's aging population grows, there is an increased disease burden on Singapore's health systems. Large-scale physical activity interventions could potentially reduce the disease burden but face challenges with the uncertainty of long-term health impact and high implementation costs, hindering their adoption. Objective: We examined the cost-effectiveness of the Singapore National Steps Challenge (NSC), an annual nationwide mobile health (mHealth) intervention to increase physical activity, from both the health care provider perspective, which only considers the direct costs, and the societal perspective, which considers both the direct and indirect costs. Methods: We used a Markov model to assess the long-term impact of increased physical activity from the NSC on adults aged 17 years and older. A Monte Carlo simulation with 1000 samples was conducted to compare two situations: the NSC conducted yearly for 10 years against a no-intervention situation with no NSC. The model projected inpatient and outpatient costs and mortality arising from diabetes and hypertension, as well as their complications. Health outcomes were expressed in terms of the quality-adjusted life-years (QALYs) gained. All future costs and QALYs were discounted at 3% per annum. Sensitivity analyses were done to test the robustness of our model results. Results: We estimated that conducting the NSC yearly for 10 years with a mean cohort size of 654,500 participants was projected to prevent 6200 diabetes cases (95% credible interval 3700 to 9100), 10,500 hypertension cases (95% credible interval 6550 to 15,200), and 4930 deaths (95% credible interval 3260 to 6930). This led to a reduction in health care costs of SGD (Singapore dollar) 448 million (95% credible interval SGD 132 million to SGD 1.09 billion; SGD 1=US $0.73 for the year 2019). There would be 78,800 (95% credible interval 55,700 to 102,000) QALYs gained. Using a willingness-to-pay threshold of SGD 10,000 per QALY gained, the NSC would be cost-saving. When indirect costs were included, the NSC was estimated to reduce societal costs by SGD 1.41 billion (95% credible interval SGD 353 million to SGD 3.80 billion). The model was most sensitive to changes in the inpatient cost of treatment for diabetes complications, time horizon, and program compliance. Conclusions: In this modeling study, increasing physical activity by conducting a yearly nationwide physical activity intervention was cost-saving, preventing diabetes and hypertension and reducing mortality from these diseases. Our results provide important information for decision-making in countries that may consider introducing similar large-scale physical activity programs.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".