Can Chronic Disease Diagnosis Urge the Patients to Quit Smoking? - Evidence from the China Health and Nutrition Survey

The impact of chronic disease diagnoses on smoking behavior change and maintenance: Evidence from China

INTRODUCTION

Managing chronic diseases and tobacco use is a formidable challenge in low- and middle-income countries (LMICs) with limited health literacy and access to quality healthcare. This study examines the empirical evidence from China, utilizing quasi-experimental approaches to assess the causal effect of chronic disease diagnoses on smoking behavior.

METHODS

Employing the diagnosis of chronic disease in the older cohorts of the population as a natural experiment, this study utilizes recent advancements in difference-in-difference estimation methods (CS-DID) to investigate the effect of a diagnosis on smoking behavior. Self-reported new diagnoses of conditions ascertained chronic disease diagnoses. CS-DID was run using the study sample from the 2011 to 2018 waves of the China Health and Retirement Longitudinal Study, comparing results with traditional two-way fixed effects and event-study models.

RESULTS

The average treatment effect (ATT) of CS-DID is slightly greater than the effects reported using conventional difference-in-difference methods. We found that diagnoses of cancer, heart disease, and stroke reduced smoking rates by 16% (95% CI: -24 - -8), smoking intensity by 0.31 (95% CI: -0.46 - -0.15), and had lasting impacts on smoking cessation behavior (one wave after diagnosis ATT= -0.17; 95% CI: -0.34 - -0.00, two waves after diagnosis ATT= -0.17; 95% CI: -0.37-0.03). A diagnosis of a mild chronic disease, such as hypertension, diabetes, asthma, chronic lung disease, liver disease, or gastric disease, had more negligible and transient effects on smoking behavior.

CONCLUSIONS

Efforts to enhance smoking cessation in middle-aged and elderly patients with chronic diseases are crucial to improving health outcomes. The 'teachable moment' of chronic disease diagnosis should be seized to provide smoking cessation assistance to achieve the goal of healthy ageing.

Risk profiles for smoke behavior in COVID-19: a classification and regression tree analysis approach

BACKGROUND

COVID-19 pandemic emerged worldwide at the end of 2019, causing a severe global public health threat, and smoking is closely related to COVID-19. Previous studies have reported changes in smoking behavior and influencing factors during the COVID-19 period, but none of them explored the main influencing factor and high-risk populations for smoking behavior during this period.

METHODS

We conducted a nationwide survey and obtained 21,916 valid data. Logistic regression was used to examine the relationships between each potential influencing factor (sociodemographic characteristics, perceived social support, depression, anxiety, and self-efficacy) and smoking outcomes. Then, variables related to smoking behavior were included based on the results of the multiple logistic regression, and the classification and regression tree (CART) method was used to determine the high-risk population for increased smoking behavior during COVID-19 and the most profound influencing factors on smoking increase. Finally, we used accuracy to evaluated the performance of the tree.

RESULTS

The strongest predictor of smoking behavior during the COVID-19 period is acceptance degree of passive smoking. The subgroup with a high acceptation degree of passive smoking, have no smokers smoked around, and a length of smoking of ≥ 30 years is identified as the highest smoking risk (34%). The accuracy of classification and regression tree is 87%.

CONCLUSION

The main influencing factor is acceptance degree of passive smoking. More knowledge about the harm of secondhand smoke should be promoted. For high-risk population who smoke, the "mask protection" effect during the COVID-19 pandemic should be fully utilized to encourage smoking cessation.

Social Participation and Persistent Smoking Among Older Chinese With Smoking-Related Morbidity

OBJECTIVES

Chronic diseases are common in midlife and old age and smoking can pose more health and longevity challenges for older people with chronic illnesses. In China where smoking is highly prevalent, older adults are likely to continue smoking even after developing severe chronic diseases. We examined the national prevalence of persistent smoking among older adults. We also investigated the sociodemographic characteristics of persistent smoking among ever-smokers with chronic diseases and its association with social participation (of various types).

METHODS

We used data from a nationally representative sample of older adults aged 45-80 in the China Health and Retirement Longitudinal Study (2011-2018). Multinomial logistic and multilevel logistic models were fitted.

RESULTS

The national prevalence of persistent smoking was around 24% of older men and 3% of older women. Among those with a history of smoking and chronic illness, younger, nonmarried/partnered, nonretired, or less educated individuals are more likely to continue smoking. Social participation is significantly associated with persistent smoking among those with chronic diseases, but the association differs across different forms of activities. Although the most popular but sedentary activities in China (playing Mahjong, chess, or cards) are associated with an elevated risk of persistent smoking, physical social activities (community-organized dancing, fitness, and qigong) are associated with a reduced risk of persistent smoking.

DISCUSSION

Given the enormous burden of persistent smoking on individuals and society, public smoking cessation inventions should address sociocultural factors of persistent smoking and target older adults who participate in specific social activities.

Effects of chronic disease diagnoses on alcohol consumption among elderly individuals: longitudinal evidence from China

OBJECTIVES

This study estimates the effect of chronic disease diagnoses (CDDs) on elderly Chinese individuals' alcohol consumption behaviour.

SUBJECTS AND PARTICIPANTS

Our analysis was applied to a publicly available dataset that covers 5724 individuals aged 50 or above and spans 15 years (2000-2015: six waves) from the China Health and Nutrition Survey.

DESIGN

The outcome variables are elderly individuals' weekly consumption of alcoholic beverages: beer, red wine, Chinese spirits and total alcohol intake. The explanatory variable of primary interest is the number of chronic diseases diagnosed (including hypertension, diabetes, stroke and myocardial infarction). Other covariates concern sample individuals' sociodemographic and health-related characteristics. A Chamberlain-Mundlak correlated random-effect Tobit model is adopted to simultaneously account for the clustering of 'zeros' in the outcome variable and endogeneity issues such as omitted variables and reverse causality.

RESULTS

Our estimation suggests that, on average, an additional chronic disease diagnosed by medical doctors reduced an elderly Chinese individual's weekly consumption of beer, red wine and Chinese spirits, respectively, by 1.49 (95% CI -2.85 to -0.13), 0.93 (95% CI -1.63 to -0.23) and 0.89 (95% CI -1.23 to -0.54) ounces. These effects translate into a reduction of 0.95 (95% CI -1.29 to -0.60) ounces in total weekly alcohol consumption and a reduction of 24% (95% CI -0.35 to -0.14) in the incidence of excessive drinking. Further explorations suggest that elderly Chinese individuals' alcohol consumption is most responsive to diabetes and stroke diagnoses, but the effects vary across different beverages. Moreover, males, rural residents, smokers and those living with non-drinkers respond to CDDs more strongly than their respective counterparts.

CONCLUSION

While CDDs reduced alcohol consumption among elderly Chinese individuals, they failed to stop all heavy drinkers from excessive drinking. Relevant policies and measures are thus needed to urge heavy drinking patients to quit excessive drinking.