Smoking behavior prevalence in one's personal social network and peer's popularity: A population-based study of middle-aged adults in Japan

Cohabitation with a smoker and efficacy of cessation programmes: the mediating role of the theory of planned behaviour

OBJECTIVE

The present research sought to examine whether cohabitation with a smoker undermines smoking cessation among people engaged in a cessation programme and whether the components of the Theory of Planned Behaviour (TPB) act as mediating mechanisms.

DESIGN

A prospective longitudinal study with online questionnaires was conducted among smokers living in Switzerland who enrolled in a 6-months smoking cessation programme.

MAIN OUTCOME MEASURES

Cohabitation with a smoker and the TPB constructs were assessed 10 days after the start of the programme (T1; N = 820). Smoking abstinence was measured at T1, and at 3-months (T2; N = 624) and 6-months follow-ups (T3; N = 354).

RESULTS

Results showed that living with a smoker decreased the odds that smokers remained abstinent throughout the cessation programme. Furthermore, we found that cohabitation was negatively associated with subjective norm. Afterwards, subjective norm predicted intention to maintain smoking cessation, which, in turn, predicted smoking abstinence. Such mediation effects persisted at each time point.

CONCLUSION

The present research provided evidence that living with other smokers at home can lead to greater risks of relapsing among people engaged in a cessation programme. We discussed the role of smoking-related norms in the efficacy of cessation interventions.

Supplemental data for this article is available online at https://doi.org/10.1080/08870446.2022.2041638 .

General health literacy, COVID-19-related health literacy, and protective behaviors: evidence from a population-based study in Japan

Introduction

Health literacy (HL) can be regarded as a key element of non-pharmaceutical interventions used in emergency responses. The present study aimed to determine the associations of combinations of general HL and COVID-19-related HL with COVID-19 protective behaviors and healthy lifestyle behaviors.

Methods

A questionnaire survey was conducted from December 2020 to January 2021 among residents in Japanese metropolitan areas. Valid responses were received from 1,443 residents. The levels of HL were categorized into four groups: low level in both HLs (reference), high level in general HL only, high level in COVID-19-related HL only, and high level in both HLs. The total scores of eight COVID-19 protective behaviors were dichotomized into low and high adherence. Healthy lifestyle behaviors included healthy and balanced diet, adequate sleep, and regular exercise. Poisson regression analyses were conducted to examine the associations between the HL groups and high adherence to COVID-19 protective behaviors.

Results

High level in COVID-19-related HL only was associated with high adherence to COVID-19 protective behaviors [prevalence ratio (PR), 1.25; 95% confidence interval (CI), 1.09-1.45], while high level in general HL only was associated with healthy and balanced diet (PR, 1.49; 95% CI, 1.04-2.13), adequate sleep (PR, 1.46; 95% CI, 1.02-2.10), and regular exercise (PR, 2.00; 95% CI, 1.29-3.13). High level in both HLs showed the highest prevalence of high adherence to COVID-19 protective behaviors and healthy lifestyle behaviors.

Conclusion

These findings indicate that COVID-19-related HL and general HL can both be considered to enhance protective behaviors.

Economic, cognitive, and social paths of education to health-related behaviors: evidence from a population-based study in Japan

BACKGROUND

There is substantial evidence on the association between lower education and unhealthy behaviors. However, the mechanism underlying this association remains unclear. This study aimed to examine whether income, health literacy, and social support mediate the association between education and health-related behaviors.

METHODS

A questionnaire survey was conducted in metropolitan areas in Japan from 2010 to 2011 among residents aged 25-50 years. Data from 3663 participants were used in this study. Health literacy was measured using the Communicative and Critical Health Literacy scale. Health-related behaviors were current smoking, poor dietary habits, hazardous drinking, and lack of exercise. Poisson regression analyses with robust variance estimators were conducted to examine the associations between education and these health-related behaviors. Multiple mediation analyses were conducted to estimate the magnitudes of the mediating effects of income, health literacy, and social support on these associations.

RESULTS

Less educated participants had higher risks of all unhealthy behaviors. Income mediated the associations of education with smoking (6.4%) and exercise (20.0%). Health literacy mediated the associations of education with dietary habits (15.4%) and exercise (16.1%). Social support mediated the associations of education with dietary habits (6.4%) and exercise (7.6%). The education-drinking association was mediated by income in the opposite direction (-10.0%). The proportions of the total effects mediated by income, health literacy, and social support were 9.8% for smoking, 24.0% for dietary habits, -3.0% for drinking, and 43.7% for exercise.

CONCLUSIONS

These findings may provide clues for designing effective interventions to reduce educational inequalities in health-related behaviors.

Organising knowledge to prevent global health crises: a comparative analysis of pandemic preparedness indicators

Preparing for the possibility of a global pandemic presents a transnational organisational challenge: to assemble and coordinate knowledge over institutionally diverse countries with high fidelity. The COVID-19 pandemic has laid these problems bare. This article examines the construction of the three main cross-national indicators of pandemic preparedness: a database with self-reported data by governments, external evaluations organised by the WHO and a global ranking known as the Global Health Security Index. Each of these presents a different model of collecting evidence and organising knowledge: the collation of self-reports by national authorities; the coordination of evaluation by an epistemic community authorised by an intergovernmental organisation and on the basis of a strict template; and the cobbling together of different sources into a common indicator by a transnational multi-stakeholder initiative. We posit that these models represent different ways of creating knowledge to inform policy choices, and each has different forms of potential bias. In turn, this shapes how policymakers understand what is ‘best practice’ and appropriate policy in pandemic preparedness.

Best Practices for Modeling Egocentric Social Network Data and Health Outcomes

OBJECTIVE/AIM

We describe best practices for modeling egocentric networks and health outcomes using a five-step guide.

BACKGROUND

Social network analysis (SNA) is common in social science fields and has more recently been used to study health-related topics including obesity, violence, substance use, health organizational behavior, and healthcare utilization. SNA, alone or in conjunction with spatial analysis, can be used to uniquely evaluate the impact of the physical or built environment on health. The environment can shape the presence, quality, and function of social relationships with spatial and network processes interacting to affect health outcomes. While there are some common measures frequently used in modeling the impact of social networks on health outcomes, there is no standard approach to social network modeling in health research, which impacts rigor and reproducibility.

METHODS

We provide an overview of social network concepts and terminology focused on egocentric network data. Egocentric, or personal networks, take the perspective of an individual who identifies their own connections (alters) and also the relationships between alters.

RESULTS

We describe best practices for modeling egocentric networks and health outcomes according to the following five-step guide: (1) model selection, (2) social network exposure variable and selection considerations, (3) covariate selection related to sociodemographic and health characteristics, (4) covariate selection related to social network characteristics, and (5) analytic considerations. We also present an example of SNA.

CONCLUSIONS

SNA provides a powerful repertoire of techniques to examine how relationships impact attitudes, experiences, and behaviors-and subsequently health.

Realfooders Influencers on Instagram: From Followers to Consumers

(1) Background: Realfooders have positioned themselves in social networks such as Instagram by posting photographs of recipes, advises, habits and nutritional behaviours which are advertised as reliable nutritional patterns and by their self-promotion as highly trained people in the field of nutrition which sometimes jeopardises the health of digital citizenry. (2) Methods: In this article, we develop a quantitative study for analysing the influence of selected Realfooders on 2,866,980 followers on Instagram, taking into account channel variables (gender, location, interests and motivations), followers’ variables (engagement, interaction and consumption) and some variables related to the message of 54 posts about breakfast. (3) Results: Selected Realfooders concentrate their followers in Spain, mostly women between 18 and 24 and between 35 and 44 years old who link their interests on food to the cult of the body and recreational areas. On the other hand, the content generated by Realfooders has been increasing its impact using advertising and marketing techniques for awaking consumer’s interest. (4) Conclusions: Educational and social agents are facing the challenge of low health literacy in young population. Therefore, it is necessary to design and implement strategies for developing critical thinking that allow them to assess the content generated by Realfooders and identify which recommendations can be harmful or beneficial to their health.