JMIR Publications

ABSTRACT

Background:

Tobacco smoking is an important public health issue and a core indicator of public health policy worldwide. However, global pandemics and natural disasters have prevented surveys from being conducted.

Objective:

The purpose of this study was to predict smoking prevalence by prefecture and sex in Japan using Internet search trends.

Methods:

This study used the infodemiology approach. The outcome variable was smoking prevalence by prefectures obtained from official records. The predictor variable was the search volumes on Yahoo! JAPAN Search. We collected the search volumes of search queries, which were related terms from thesaurus in the Japanese medical article database “Ichu-shi.” Predictor variables were converted to per capita values and standardized as Z-scores. For smoking prevalence, the values for 2016 and 2019 were used, and for search volumes, the values for the fiscal year (FY) one year prior to the survey (that is, FY 2015 and FY 2018) were used. Partial correlation coefficients, adjusted for data year, were observed between smoking prevalence and search volumes, and regression analysis using generalized linear mixed model with random effects was conducted for each prefecture. Several models were tested, including a model that included all search queries, a variable reduction method, and one that excluded cigarette product names, and the best model was selected by the corrected Akaike’s Information criterion (AICC) and Bayesian Information criterion (BIC). We compared the predicted and actual smoking prevalence in 2016 and 2019 based on the best model and predicted the smoking prevalence in 2022.

Results:

No significant correlation coefficients were found for the total sample. For men, nine search queries had significant correlations with smoking prevalence, such as cigarette (シガレット); r=-0.417, p<0.001, cigar (葉巻); r=-0.412, p<0.001, cigar (シガー); r=-0.399, p<0.001. For women, five search queries had significant correlations, such as vape; r=0.335, p=0.001, no smoking (禁煙); r=0.288, p=0.005 cigar (シガー); r=0.286, p=0.006. The models with all search queries were the best models for both AICC and BIC scores. Scatter plots of actual and estimated smoking prevalence in 2016 and 2019 confirmed a relatively high degree of agreement. The average estimated smoking prevalence in 2022 of the 47 prefectures for the total sample was 23.492 (21.617–25.367), showing an increasing trend, with and average of 29.024 (27.218–30.830) for men and 8.793 (7.531–10.054) for women.

Conclusions:

This study suggests that the search volume of tobacco-related queries in Internet search engines can predict smoking prevalence by prefecture. These findings will enable the development of low-cost, timely, and crisis-resistant health indicators that will enable the evaluation of health measures and contribute to improved public health.