To the best of our knowledge, the current study is by far the first of this kind highlighting the seasonal variability in Internet search volumes for quit smoking. Although the number of searches for this topic steadily decreased from 2004 to 2018, with a little fluctuation in the first two years in several countries including the USA, Canada and Australia. While New Zealand, the number of searches for quit smoking steadily decreased from 2004 to 2006 and increased to a peak in 2008, then decreased (again) from 2008 to 2018 (a similar research reported that compared with 2018, the smoking prevalence had been decreased over the last decade ). Consistent with our prior hypothesis, a statistically significant seasonality for these search queries were identified in the representative countries from both the northern and southern hemisphere, with a zenith in winter and late autumn, nadir in summer and late spring.
The current research provided preliminary evidence for the literature on the epidemiology of quit smoking. It indicated that Internet search queries for quit smoking varied significantly by season. There are multiple factors that may contribute to this seasonal phenomenon and the overall decreased search trend for the topic of quit smoking since 2004.
First, Lexington-Fayette Country, Kentucky implemented an ordinance on April 27, 2004 that all public places including bars, restaurants, pool halls, hotels and all other buildings open to the public should follow a smoke-free rules . Some previous studies broadly assessed the effects of the bans of smoking cessation. It is described that the second-hand smoking (SHS) concentration in public venues has experienced a large reduction, ranging from 70 to 97% . This may be a reasonable explanation for the reduced search volumes for the topic of quit smoking, because less people smoke since the implementation of this smoking ban. Second, according to a report from WHO that tobacco use has been a leading cause of preventable illness throughout the world . Besides, the economic burden of smoking related illness is quite substantial, in Canada, annual burden of tobacco smoking estimated to be nearly 21.3 billion dollars . According to some previous studies, compared with those mothers who are not a smoker, the incidence rate of early SIDS (sudden infant death syndrome) among smokers was 0.6 cases per 100,000 person-days higher . A meta-analysis study in another research reported that sperm concentration has reduced by 13%, sperm motility 10% and sperm morphology 3% among smokers . All of these harmful effects caused by smoking may result in infertility. Furthermore, it has been reported that the relationship between depressive illness and smoking is that people who addicted to smoking are more likely to suffer from depression than those who are not a smoker (Breslau, Kilbey, & Andreski, 1993) . Given the dreadful effects to our body health caused by smoking and the enormous economic burden carried by smoking-related illness, most people tend to quit smoking. Since most smokers have the awareness of the importance of stop smoking, less people search this topic on the Internet. Third, for many young smokers, boredom remained a reason for them to smoke at a time . Additionally, in UK, it has been suggested that the young usually treat the mobile phone use and smoking as a symbol of maturity . The rise in mobile phone usage may be responsible for an observed decreasing in smoking among teenagers over the past few years. Nevertheless, the association between the declining usage of cigarette and the rise in mobile phone use has not been studied in other countries . With the rapidly development of our technologies during the past several years, people have more choice to spend their boring time which may be a reason for our results.
Some other factors may contribute to the seasonality of the search volumes of the topic of quit smoking. The observed seasonality may result from the increment of Internet use in winter. However, this presumption has not been corroborated . The association between depression illness and smoking has already been described, the study also reported that admissions for depressive disorders peaked in the springtime and declined during the summer time . Since the patients with depression are more likely to be a smoker, this may explain that people’s interest towards quit smoking reached a trough in the summer months. Besides, people tend to make the decision to quit smoking in New Year’s Eve, which is a widely recognized seasonal phenomenon . Another research showed that cigarette sales presented a strongly seasonal pattern each year, with a peak in the summer months and reach a low in the winter months. This is almost a mirror image of the seasonality pattern for the search volumes of quit smoking, suggesting a strong association between the two phenomena . Additionally, there are robust evidence to show that current smokers and those who used to be a smoker, have a significantly higher risk of developing chronic obstructive pulmonary disease (COPD) . A significant increase of quit smoking willingness was presented when an awareness of COPD was raised . The data showed that a higher search volume related to “COPD” was presented during the winter months, and this may be one of the reasons why the search volumes of quit smoking reached a highest in the winter months and late autumn. Since most of the countries from the southern hemisphere stand near the equator, the seasonal variation in weather may be fewer compared with the countries in the northern hemisphere. This may explain why the seasonal pattern in the southern hemisphere is slightly different with the northern hemisphere, with peak in the late autumn, nadir in the late spring.
Our current research involved statistical data of the USA, the UK, Canada, Ireland, New Zealand and Australia which represent both hemispheres. There are some advantages identified in our study, including the large and exhaustive amount of data involved, the long period of observation and inclusion of representative countries from both hemispheres. Nevertheless, there remains some inherent limitations in our research. Although a massive amount of data contained in Google Trends, and more than 65% of all queries were searched within the Google engine . It only captures the search behavior of a certain groups of people who have access to Internet and those who choose to search by Google rather than other search engines, which could result in selection bias. Besides, Google Trends only provide normalized instead of raw search volumes. The detailed information by which Google generates these data and the algorithms that Google employs to analysis this information remains unclear. So, it would be impossible for us to control other factors that may influence the total number of Internet searches. Since the data available through Google Trends does not include the demographical features and the characteristics of the individuals who entering search queries, it is also impossible to assess the seasonal variation by subgroup analysis.