[Application of the cigarette purchase tasks in achieving China' s tobacco control goals].

OBJECTIVE: To assess cigarette demand among Chinese smokers through a cigarette purchase task (CPT) and to evaluate cigarette prices under different hypothetical scenarios in order to meet the goals of smoking prevalence reduction in China. METHODS: In the study, 447 participants completed a hypothetical CPT at baseline assessments of a trial, thus, cigarette demand curves were individually fitted for each participant using an exponentiated version of the exponential demand model. Typically, five demand indices were derived, intensity (consumption when free), breakpoint (first price at which consumption is suppressed to 0), maximum output (Omax), maximum price (Pmax, price at which Omax occurred), and elasticity (the ratio of the change in quantity demanded to the change in price). A one-way analysis of variance was used to explore the correlations between the cigarette purchase task indices and socio-demographic and smoking characteristics. The one-way decay model was employed to simulate the smoking cessation rates and determine optimal cigarette prices in a series of scenarios for achieving 20% smoking prevalence. RESULTS: The price elasticity drawn from CPT was 0.54, indicating that a 10% price increase could reduce smoking by 5.4% in the participated smokers. Smokers with higher income were less sensitive to cigarette prices (elasticity=-2.31, P=0.028). Cigarette purchase task indices varied significantly among the smokers with different prices of commonly used cigarettes, tobacco dependence, and smoking volume. The smokers who consumed cigarettes of higher prices reported higher breakpoint, Omax and Pmax, but lower intensity (P=0.001). The smokers who were moderately or highly nicotine dependent reported higher intensity, breakpoint, Omax and Pmax, and they had lower intensity (P=0.001). The smokers who had a higher volume of cigarettes reported higher intensity and Omax, and lower intensity (P < 0.001). To achieve the goal of reducing smoking prevalence to 20% in mainland China, we estimated the desired increase on smoking cessation rate and prices accordingly in a series of scenarios, considering the gender variance and reduced smoking initiation. In scenario (a), to achieve a smoking prevalence goal of 20%, it would be necessary for 24.81% of the current smokers to quit smoking when there were no new smokers. Our fitting model yielded a corresponding value of 59.64 yuan (95%CI 53.13-67.24). Given the assumption in scenario (b) that only males quitted smoking, the desired cessation rates would be 25.82%, with a higher corresponding price of 62.15 yuan (95%CI 55.40-70.06) to induce desired cessation rates. In the proposed scenario (c) where 40 percent of the reduction in smoking prevalence came from reduced smoking initiation, and females and males equally quitted smoking due to increased cigarette prices, the price of a pack of cigarettes would be at least 37.36 yuan (95%CI 32.32-42.69) (equals to $ 5.20) per pack to achieve the cessation rate of 14.89 percent. In scenario (d) where only males quitted smoking due to increased cigarette prices considering the reduced smoking initiation, the respective smoking cessation rates should be 15.49% with the desired prices of 38.60 yuan (95%CI 33.53-44.02). After adjusting for education levels and income levels in scenario (c), the price of cigarettes would be at least 37.37 yuan/pack (equals to $ 5.20) (95%CI 30.73-44.94) and 37.84 yuan/pack (equals to $ 5.26) (95%CI 31.94-44.53), respectively. CONCLUSION: Cigarette purchase task indices are significantly associated with income levels and prices of commonly used cigarettes, levels of tobacco dependence, and smoking volume, which is inspiring in studying price factors that influence smoking behavior. It is suggested that higher cigarette prices, surpassing the current actual market level, is imperative in mainland China. Stronger policy stra-tegies should be taken to increase tobacco taxes and retail cigarette prices to achieve the Healthy China 2030 goal of reducing smoking prevalence to 20%.

Development and psychometric assessment of Health Action Process Approach (HAPA) in terms of smoking cessation among Chinese smokers.

The Health Action Process Approach (HAPA) is a two-stage (pre-intentional and post-intentional) behavioral change model that distinguishes between motivation and volition in behavior change process. This study aims to develop HAPA-based assessments for smoking cessation among current smokers. The HAPA-based measures were developed and the draft measures included nine constructs, namely, risk perception in smoking-induced cancer, risk perception in smoking-induced systemic disease, positive outcome expectancy, negative outcome expectancy, self-efficacy in quitting smoking, self-efficacy in maintaining, self-efficacy in re-initiating, quitting planning and coping planning in smoking cessation, with a total of 26 items. A cross-sectional survey was conducted in China in 2022. Principal Component Analysis was used for Exploratory Factor Analysis (EFA). Cronbach's α coefficient was calculated to evaluate the internal consistency. Variables such as severity of smoking addiction were selected to evaluate the correlation between the HAPA scale and these variables. Of the 928 participants, 76.4% (709/928) were male and the median age was 35 years. Five factors were extracted by EFA. The factor loadings of each item were all greater than 0.60, and the cumulative variance contribution rate was 90.15%. The Cronbach's α coefficient of each HAPA-based subscales was 0.929-0.986. The HAPA-based measurements are comprehensive, reliable and valid in the assessment of smokers' smoking cessation cognition, which can be used to guide the design and implementation of intervention and the development of theory.

Psychiatric symptoms and intentions to quit smoking: How regularity and volume of cigarette consumption moderate the relationship.

INTRODUCTION: Smoking prevalence is disproportionately higher in those with psychiatric symptoms. Smokers with psychiatric symptoms are less likely to have an intention to quit smoking and attain eventual smoking abstinence. This study presents the relationship between depressive/anxiety symptoms and the intention to quit smoking and related influencing factors. METHODS: A cross-sectional study recruited 931 current smoking individuals covering two provinces in China in July 2022. The online survey comprised questions concerning sociodemographic characteristics, smoking conditions and psychiatric symptoms. Chi-squared analyses and moderation analyses were applied. RESULTS: The proportion of smokers who had the intention to quit smoking within six months was 46.1%. In comparison with subjects without depressive/anxiety symptoms, individuals who had both psychiatric symptoms were less likely to have the intention to quit smoking (39.3% vs 49.8%, χ2=9.130, p=0.028). As for the moderating model of depression, the interaction term of depressive symptoms and smoking regularly was significant (ß=0.554, t=3.260, p=0.001). For those who were occasional smokers, depressive symptoms significantly lowered their quitting intentions. The regularity of smoking similarly moderated the effect of anxiety symptoms on quitting intentions. When the number of cigarettes used weekly served as the moderator, the interaction of this number and depressive symptoms was significant, as well as for anxiety (p<0.001), indicating that the volume of cigarette consumption moderated the relationship between depressive/anxiety symptoms and intention to quit smoking. CONCLUSIONS: Psychiatric symptoms were significant factors in reducing the willingness of smokers to quit smoking, and the effects were moderated by smokers' cigarette consumption conditions. Interventions are urged to enhance quitting intentions of these vulnerable smokers.

The relationship between unhealthy lifestyle patterns and depressive symptoms among residents in Beijing, China: A community-based cross-sectional study.

Introduction: Depression is a prevalent mental disorder that has an irreversible impact on people's health status. Unhealthy lifestyles are modifiable and influence mental health significantly. The purpose of this study was to explore the impact of different unhealthy lifestyles and their patterns on depressive symptoms. Methods: The data for this study were obtained from the 2017 Community Diagnostic survey in Daxing District, Beijing. It was a cross-sectional study that included 6,252 samples. The Patient Health Questionnaire version 9 was used to measure depressive symptoms, and the self-administered questionaires were used to investigate five unhealthy lifestyles, including sleep deprivation, the inadequate intake of fruits and vegetables, physical inactivity, smoking, and excessive alcohol consumption. Respondents were assigned 1 point for each of their unhealthy lifestyles, and their overall unhealthy lifestyle scores were calculated. The total scores of unhealthy lifestyles ranged from 0 to 5. Descriptive analyses and Firth's logistic regression model were used to analyze the relationship between unhealthy lifestyle and depression symptoms. Results: It was found that 12.1% of the participants had depressive symptoms. The respondents whose unhealthy lifestyle scores were 2 (OR1.45, 95%CI:1.01 to 2.12), 3 (OR2.29, 95%CI:1.57 to 3.42), 4 (OR 3.04, 95%CI:1.96 to 4.76), or 5 (OR4.08, 95%CI:2.09 to 7.78) were more likely to experience depressive symptoms in comparison with those whose unhealthy lifestyle scores were 0, and the OR increased with the unhealthy lifestyle scores. When the participants had 3 or more unhealthy lifestyles at the same time, different combination patterns of unhealthy lifestyles showed a different effect on depression. The OR was 3.01 (95%CI:1.45 to 5.95) for the combination of sleep deprivation-insufficient intake of fruit and vegetables-excessive alcohol consumption, and was 2.89 (95%CI:1.52 to 5.25) for the combination of sleep deprivation-insufficient intake of fruit and vegetables-physical inactivity-excessive alcohol consumption. Discussion: The co-existence of multiple unhealthy behavioral lifestyles are associated with depressive symptoms. Among the five unhealthy lifestyles, sleep deprivation and the inadequate intake of fruits and vegetables may have a greater impact on depression.

Effects of E-health-based interventions on glycemic control for patients with type 2 diabetes: a Bayesian network meta-analysis.

The high disease burden of type 2 diabetes seriously affects the quality of life of patients, and with the deep integration of the Internet and healthcare, the application of electronic tools and information technology to has become a trend for disease management. The aim of this study was to evaluate the effectiveness of different forms and durations of E-health interventions in achieving glycemic control in type 2 diabetes patients. PubMed, Embase, Cochrane, and Clinical Trials.gov were searched for randomized controlled trials reporting different forms of E-health intervention for glycemic control in type 2 diabetes patients, including comprehensive measures (CM), smartphone applications (SA), phone calls (PC), short message service (SMS), websites (W), wearable devices (WD), and usual care. The inclusion criteria were as follows: (1) adults (age≥18) with type 2 diabetes mellitus; (2) intervention period ≥1 month; (3) outcome HbA1c (%); and (4) randomized control of E-health based approaches. Cochrane tools were used to assess the risk of bias. R 4.1.2 was used to conduct the Bayesian network meta-analysis. A total of 88 studies with 13,972 type 2 diabetes patients were included. Compared to the usual care group, the SMS-based intervention was superior in reducing HbA1c levels (mean difference (MD)-0.56, 95% confidence interval (CI): -0.82 to -0.31), followed by SA (MD-0.45, 95% CI: -0.61 to -0.30), CM (MD-0.41, 95% CI: -0.57 to -0.25), W (MD-0.39, 95% CI: -0.60 to -0.18) and PC (MD-0.32, 95% CI: -0.50 to -0.14) (p < 0.05). Subgroup analysis revealed that intervention durations of ≤6 months were most effective. All type of E-health based approaches can improve glycemic control in patients with type 2 diabetes. SMS is a high-frequency, low-barrier technology that achieves the best effect in lowering HbA1c, with ≤6 months being the optimal intervention duration. Systematic review registration: https://www.crd.york.ac.uk/prospero, identifier CRD42022299896.

China's innovation and research contribution to combating neglected diseases: a secondary analysis of China's public research data.

BACKGROUND: Many emerging and developing economies, such as China, have played the important roles in combating global neglected diseases (NDs). This study aims to explore China's public landscape of research projects and funding of NDs and to provide empirical evidence on promoting China's participation in addressing global health priorities that disproportionately affect developing countries. METHODS: We systematically sourced China's public funding information from the National Natural Science Foundation of China and provincial science and technology agency websites up to August 16, 2019. Following the G-FINDER R&D scope, we screened projects of NDs for analysis. National-funded projects were reviewed on an annual basis for exploring the trends and distribution of funding flows. Information on provincial-funded projects was compared with national projects by disease, research type, and geographical distribution. RESULTS: A total of 1266 projects were included for analysis and categorized by year, funding source, recipient, disease, research type, region, and province. China's national public funding for ND research reached a historical peak of USD 16.22 million in 2018. But the proportion of ND research to all public-funded projects was less than 0.5%, and over half of the ND projects were allocated to "the big three," i.e., tuberculosis, HIV/AIDS, and malaria. About 58% of national and provincial ND projects focus on basic research. Economically developed regions and municipalities play dominant roles in leading national ND research, such as Beijing, Shanghai, and Guangdong. Provincial ND projects are primarily driven by endemic regions. CONCLUSIONS: As a new emerging high-tech innovator, China has gradually increased public input to ND-related innovation and research. But there is still a large funding gap among NDs that requires China's increased support and participation. National development plans and cooperative health needs should be taken into account for China's participation in promoting global research and development (R&D) for combating NDs.

The Incidence of Falls and Related Factors among Chinese Elderly Community Residents in Six Provinces.

This cross-sectional study classified the factors related to falls among residents ≥ 60 years old in China in order to provide evidence for the prevention of falls in the elderly. A total of 2994 participants were enrolled, and the correlations between social demography, physical health, self-health management awareness, family support, and fall risk were analyzed. Factors influencing falls were classified by location, cause, and the activity during falls. Suffering from osteoarthropathy (OR = 1.761, 95% CI: 1.234-2.513, p < 0.05), depression or anxiety (OR = 1.896, 95% CI: 1.331-2.700, p < 0.001), household size > 2 (OR = 1.806, 95% CI: 1.042-3.130, p < 0.05), and poor self-assessed health (OR = 1.478, 95% CI: 1.107-1.972, p < 0.01) were risk factors. Higher participation in community health programs (OR = 0.522, 95% CI: 0.298-0.912, p < 0.05) and spousal support (OR = 0.909, 95% CI: 0.841-0.981, p < 0.05) were protective factors. Falls were divided into the following categories: stairs/hallway (vision, attention problems), bath/toilet (vision, attention problems, slipping), indoor housework (dizziness, leg weakness), and outdoor activities (attention, surface problems). While acknowledging that the personal physical and mental health of the elderly may lead to falls, community support, accelerated transformation of housing, and the construction of barrier-free environments play an important role in reducing the risk of falls.

Protection motivation theory and smoking quitting intention: findings based on structural equation modelling and mediation analysis.

OBJECTIVE: Although many smoking cessation strategies have been implemented, only a few strategies at the population level are grounded in theory. Even in those interventions based on specific theories, most studies have focused only on the outcome. The main objective of this study was to demonstrate the utility of protection motivation theory (PMT) in explaining smoking quitting behaviour among adults, with the goal of providing valuable evidence for further intervention strategies. METHOD: This was a cross-sectional study. Participants were randomly selected on the street from 26 provinces in mainland China. Data were collected via face-to-face interviews. Cronbach's alpha coefficient and the interclass correlation coefficient (ICC) were used to assess the reliability of the individual PMT constructs. We applied structural equation modelling (SEM) to test how well the PMT constructs predicted intention. A bootstrap test was performed to test the potential mediators. RESULTS: The Cronbach's alpha coefficients of all the subscales ranged from 0.71 to 0.74. Greater intentions were significantly associated with higher threat appraisal (Coef. = 0.18, P < 0.01) and coping appraisal (Coef. = 0.24, P < 0.01). Threat appraisal was significantly associated with higher perceived severity and vulnerability but inversely associated with extrinsic rewards and intrinsic rewards. Coping appraisal was significantly associated with higher self-efficacy and response efficacy but inversely associated with response cost. The R2 of quitting intention was 0.12, which means that 12% of quitting intention was predicted by PMT constructs. For threat appraisal, approximately 19.8% of the effects on lower threat appraisal were mediated by higher extrinsic rewards. For coping appraisal, approximately 42.8% of the effects on higher coping appraisal were mediated by higher response efficacy. CONCLUSION: This study finds that PMT is a sound theoretical framework for predicting smoking quitting intention among adults. Coping appraisal has a stronger effect than threat appraisal for predicting quitting intention. Mediation analyses confirmed that extrinsic rewards and response efficacy mediated the relationship between PMT constructs and quitting intention. Our findings are essential for understanding quitting behaviour among adults and support more effective smoking cessation activities.

The characteristics and patterns of e-cigarette use and its association with cigarette cessation intention in a Chinese smoking population: A mediation analysis.

INTRODUCTION: The use of e-cigarettes has become more common in China, but the research on e-cigarettes in China, while growing, is still limited. This study examined the characteristics and patterns of e-cigarette use, and analyzed the possible mediators between cigarette cessation intention and e-cigarette use in a Chinese smoking population. METHODS: This was a cross-sectional study conducted in mainland China. By convenience sampling method, the participants were recruited from 85 major commercial streets of several large cities in China. The study interviewers completed face-to-face interviews and uploaded the completed questionnaires into the online survey platform. The participants were contacted for clarification if any problems were detected. Logistic regression yielded adjusted odds ratios (ORs) for ever use of e-cigarettes. We further conducted a mediation analysis to estimate the effect of possible mediators. RESULTS: From July to August 2020, a total of 738 smokers were invited to participate in this study; 613 smokers were identified as eligible and 609 smokers were included in this analysis. Of them, 24 (3.94%) participants were currently using e-cigarettes, and 165 (27.09%) participants have ever used e-cigarettes. The participants with younger age were more likely to have ever used e-cigarettes, ranging from 37.5% in the 18-29 years age group to 6.5% in the 60-69 years age group. After controlling for demographic characteristics and nicotine dependence, the ever use of e-cigarettes was significantly associated with younger age, higher education level, higher monthly income, previous smoking cessation attempts and quitting intention. With the mediation analysis, the education level is confirmed as a mediating factor, and approximately 42.86% of the effects were mediated through the channel of higher socioeconomic status. CONCLUSIONS: This is the first study to examine the possible mediators between cigarette cessation intention and e-cigarette use in a Chinese smoking population. The findings revealed that high socioeconomic status, particularly higher education level, was a major mediating factor.

Tobacco dependence affects determinants related to quitting intention and behaviour.

This study uses protection motivation theory (PMT) to examine the quitting intentions and behaviours of smokers who have varying levels of nicotine dependence. Our goals are to identify the psychological factors that influence smoking cessation and to provide valuable evidence to promote theory-guided interventions. This is a cross-sectional study that was conducted from July to August 2020. Participants were randomly selected on the streets of 26 provinces on mainland China. Data were collected via face-to-face interviews. Our analysis was conducted in three steps. First, we employed descriptive statistics to present the overall characteristics of our sample. Second, we analysed the association between PMT constructs and quitting intentions stratified by nicotine dependence. Third, we tested how quitting intentions were associated with quitting behaviours in each subgroup using logistic regression models. For intention, almost all the PMT constructs were significantly associated with quitting intention in the low-dependence group. For the moderate- and high-dependence groups, only perceived vulnerability (coefficient = 0.35, P = 0.04) was positively associated with quitting intention. For behaviour, we found a stronger association between quitting intention and behaviour in the low-dependence group (Coef. = 1.67, P = 0.00) than for the other groups. We found a significant association between e-cigarette use and quitting behaviour only in the low-dependence group (Coef. = 1.34, P = 0.00). Coefficients for the moderate- and high-dependence groups were not statistically significant. Smokers at various levels of nicotine dependence have different psychological factors that influence their intentions to stop smoking. Quitting intention was more significantly associated with quitting behaviour for the low nicotine-dependence group than for the other groups. More convincing research is necessary to determine how e-cigarette use affects quitting behaviour in the long term.