JMIR Publications

ABSTRACT

Background:

In some countries, including Japan, the leading country in terms of longevity, a national survey is conducted to investigate healthy life years using a questionnaire for the presence of activity limitations. While life expectancy has been increasing, healthy life years have not kept pace, necessitating an effective health policy to narrow the gap.

Objective:

The aim of the study is to develop a prediction model for healthy life years without activity limitations and deploy the model in a health policy to prolong healthy life years.

Methods:

The Comprehensive Survey of Living Conditions, a cross-sectional national survey of Japan, was conducted by the Japanese Ministry of Health, Labour, and Welfare in 2013, 2016, and 2019. The data from 1,537,773 responders were used for modelling using machine learning. Activity limitations were set as the targets. Age, sex, and 40 types of diseases or injuries were included as features. Healthy life years without activity limitation were calculated by incorporating the predicted prevalence rate of activity limitations in a life table. For the wide utility of the model in individuals, we developed an application tool for the model.

Results:

A total 42 features were included in the feature set. Age had the highest impact on model accuracy, followed by depression or other mental diseases; back pain; bone fracture; other neurological disorders, pain, or paralysis; stroke, cerebral hemorrhage or infarction; arthritis; Parkinson’s disease; dementia; and other injuries or burns. The model exhibited high performance with an area under the curve of 0·85 (95% confidence interval: 0·84–0·85) with exact calibration. The prediction results were consistent with the observed values of healthy life years for both sexes in each year (range of difference between predictive and observed value: −0·89–0·16 in male and 0·61–1·23 in female respondents). We applied the prediction model to a regional health policy to prolong healthy life years by adjusting the representative predictors to a target prevalence rate. Additionally, we presented the health condition without activity limitations (HCAL) index, followed by the application development for individual health promotion.

Conclusions:

The prediction model will enable national or regional governments to establish an effective health promotion policy for risk prevention at the population and individual levels to prolong healthy life years. Further investigation is needed to validate the model’s adaptability to various ethnicities and, in particular, to countries where the population exhibits a short lifespan.