Predicting Smoking Prevalence in Japan Using Search Volumes in an Internet Search Engine: Infodemiology Study

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 prefecture, obtained from national surveys. The predictor variables were the search volumes on Yahoo! Japan Search. We collected the search volumes for queries related to terms from the thesaurus of 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 volume, the values for the April 1 to March 31 fiscal year (FY) 1 year prior to the survey (ie, FY 2015 and FY 2018) were used. Partial correlation coefficients, adjusted for data year, were calculated between smoking prevalence and search volume, and a regression analysis using a 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. The best model was selected with the Akaike information criterion corrected (AICC) for small sample size and the 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 The partial correlation coefficients for men showed that 9 search queries had significant correlations with smoking prevalence, including cigarette (r=–0.417, P<.001), cigar in kanji (r=–0.412, P<.001), and cigar in katakana (r=-0.399, P<.001). For women, five search queries had significant correlations, including vape (r=0.335, P=.001), quitting smoking (r=0.288, P=.005), and cigar (r=0.286, P=.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 in the 47 prefectures for the total sample was 23.492% (95% CI 21.617%-25.367%), showing an increasing trend, with an average of 29.024% (95% CI 27.218%-30.830%) for men and 8.793% (95% CI 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 and sex in Japan. 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.

Changes in lifestyle-related behaviour during the COVID-19 pandemic in Japan: a questionnaire survey for examinees who underwent an annual health check-up

“…64,66 With regard to smoking habits, the prevalence of smoking in Japan has consistently decreased from 2001 to 2019; however, estimates for 2020 indicated flattening and increasing trends among men (29.0%) and women (8.8%), respectively. 67 Based on the answers to question 5, approximately 20.0% of men and 8.0% of women were smokers. Therefore, the prevalence of smoking among the current participants, both men and women, was lower than the estimated 2020 results.…”

“…[74][75][76][77][78][79] The results of this current study complement these previous findings. [67][68][69][70][71][72][73][74][75][76][77][78][79] Possible explanations for an increase in smoking frequency rather than a decrease included responding to pandemic-induced stress by increasing smoking frequency, 75 no restrictions against smoking while teleworking 74 or being bored due to self-isolation. 77,80 In terms of mental health, the COVID-19 pandemic caused a negative effect on people's mental health and emotions, such as depression, post-traumatic stress disorder, substance use disorder, confusion and anger.…”

“…Therefore, the prevalence of smoking among the current participants, both men and women, was lower than the estimated 2020 results. 67 Since the examinees who underwent check-ups at the ASMC were relatively young (the mean age was 47.8 years) and worked in large companies, they may have a high literacy rate and be concerned regarding their health. This may offer a partial explanation to the divergence in numbers.…”

“… 74 – 79 The results of this current study complement these previous findings. 67 – 79 Possible explanations for an increase in smoking frequency rather than a decrease included responding to pandemic-induced stress by increasing smoking frequency, 75 no restrictions against smoking while teleworking 74 or being bored due to self-isolation. 77 , 80 …”