Estimating lifetime malnourished period and its statistics based on the concept of Markov chain with reward

Flexible transition timing in discrete-time multistate life tables using Markov chains with rewards

Discrete-time multistate life tables are attractive because they are easier to understand and apply in comparison with their continuous-time counterparts. While such models are based on a discrete time grid, it is often useful to calculate derived magnitudes (e.g. state occupation times), under assumptions which posit that transitions take place at other times, such as mid-period. Unfortunately, currently available models allow very few choices about transition timing. We propose the use of Markov chains with rewards as a general way of incorporating information on the timing of transitions into the model. We illustrate the usefulness of rewards-based multistate life tables by estimating working life expectancies using different retirement transition timings. We also demonstrate that for the single-state case, the rewards approach matches traditional life-table methods exactly. Finally, we provide code to replicate all results from the paper plus R and Stata packages for general use of the method proposed.

Lifetime impact of being underweight or overweight/obese during childhood in Vietnam

BACKGROUND

There is limited evidence about lifetime burden of child malnutrition. This study aimed to estimate the lifetime impact of being underweight or overweight/obese during childhood in Vietnam.

METHODS

We developed a life table model in combination with a Markov model for Vietnamese children aged 5-19 years and simulated until they reached 75 years of age or died using published data. The starting year was 2019 and the model estimated number of deaths, years of life lived and quality-adjusted life years (QALY) with an annual discount rate of 3%. We performed scenario, one-way, and probabilistic sensitivity analyses to assess the impact of uncertainties in input parameters.

RESULTS

The model estimated 9.68 million deaths (6.44 million men and 3.24 million women), 622 million years of life lived (317 million men and 305 million women), and 601 million QALYs (308 million men and 293 million women). Scenario analyses showed that the reduction in either underweight or overweight/obesity alone, and reduction in both underweight and overweight/obesity resulted in fewer deaths, more years of life lived and more QALYs gained. In the scenario where everyone was a healthy weight, the model estimated 577,267 fewer deaths (6.0% less), 2 million more years of life lived (0.3% more), and 3 million QALYs gained (0.6% more) over base-case results which represents current situation in Vietnam.

CONCLUSIONS

Our results suggest that addressing underweight and overweight/obesity will contribute to reducing deaths and increasing years of life lived and QALYs. Policies and interventions in alignment with Sustainable Development Goals to address underweight and overweight/obesity are necessary to achieve health for all.