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Background: The government-led community-based Chinese National Integrated Demonstration Areas for the Prevention and Control of Noncommunicable Diseases programme was launched in 2011, but no rigorous impact evaluation has been conducted to date. We aimed to evaluate the causal effects of this programme on behavioural risk factors. Methods: We used data from the latest five waves of the China Chronic Disease and Risk Factor Surveillance. The primary outcome is a behavioural risk score combining current smoking, passive smoking, drinking in last month, regular exercise, body mass index, and waist circumference. We applied the synthetic difference-in-differences method and constructed synthetic controls from the non-demonstration areas with the outcome. The average treatment effects on the treated were estimated for overall effect and by short- (1-2), medium- (3-4), and long-term (6-7 years) effects. Findings: We identified 26 demonstration areas (N = 72,193) and 100 non-demonstration areas (N = 275,397). Participants in the demonstration areas had higher education and income levels and different pre-implementation trends than non-demonstration areas. Using synthetic controls instead of non-demonstration areas reduced these pre-implementation differences. Compared to the synthetic controls, declines were observed in current smoking (-1.78% [-4.51%, 0.96%]), passive smoking (-8.09% [-14.27%, -1.90%]), and drinking in last month (-4.04% [-8.75%, 0.67%]) but not in the other factors. Behavioural risk score declined by 1.05 short-term (95% CI: -1.84, -0.26), 1.15 medium-term (95% CI: -2.08, -0.22), 2.82 long-term (95% CI: -4.79, -0.85), and 1.54 overall (95% CI: -2.51, -0.56). Interpretation: The programme improved behavioural risk scores, primarily through reductions in the prevalence of smoking and drinking, and the effect was long-lasting. Our findings provided empirical evidence for utilizing an integrated prevention and control strategy to fight against NCD in China and other countries facing similar challenges. Funding: The China National Key Research and Development Program (2018YFC1315304 and 2017YFC1310902); National Natural Science Foundation of China (81872721).
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[This corrects the article DOI: 10.2196/45111.].
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BACKGROUND: Rapid advancements in eHealth and mobile health (mHealth) technologies have driven researchers to design and evaluate numerous technology-based interventions to promote smoking cessation. The evolving nature of cessation interventions emphasizes a strong need for knowledge synthesis. OBJECTIVE: This systematic review and meta-analysis aimed to summarize recent evidence from randomized controlled trials regarding the effectiveness of eHealth-based smoking cessation interventions in promoting abstinence and assess nonabstinence outcome indicators, such as cigarette consumption and user satisfaction, via narrative synthesis. METHODS: We searched for studies published in English between 2017 and June 30, 2022, in 4 databases: PubMed (including MEDLINE), PsycINFO, Embase, and Cochrane Library. Two independent reviewers performed study screening, data extraction, and quality assessment based on the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) framework. We pooled comparable studies based on the population, follow-up time, intervention, and control characteristics. Two researchers performed an independent meta-analysis on smoking abstinence using the Sidik-Jonkman random-effects model and log risk ratio (RR) as the effect measurement. For studies not included in the meta-analysis, the outcomes were narratively synthesized. RESULTS: A total of 464 studies were identified through an initial database search after removing duplicates. Following screening and full-text assessments, we deemed 39 studies (n=37,341 participants) eligible for this review. Of these, 28 studies were shortlisted for meta-analysis. According to the meta-analysis, SMS or app text messaging can significantly increase both short-term (3 months) abstinence (log RR=0.50, 95% CI 0.25-0.75; I2=0.72%) and long-term (6 months) abstinence (log RR=0.77, 95% CI 0.49-1.04; I2=8.65%), relative to minimal cessation support. The frequency of texting did not significantly influence treatment outcomes. mHealth apps may significantly increase abstinence in the short term (log RR=0.76, 95% CI 0.09-1.42; I2=88.02%) but not in the long term (log RR=0.15, 95% CI -0.18 to 0.48; I2=80.06%), in contrast to less intensive cessation support. In addition, personalized or interactive interventions showed a moderate increase in cessation for both the short term (log RR=0.62, 95% CI 0.30-0.94; I2=66.50%) and long term (log RR=0.28, 95% CI 0.04-0.53; I2=73.42%). In contrast, studies without any personalized or interactive features had no significant impact. Finally, the treatment effect was similar between trials that used biochemically verified or self-reported abstinence. Among studies reporting outcomes besides abstinence (n=20), a total of 11 studies reported significantly improved nonabstinence outcomes in cigarette consumption (3/14, 21%) or user satisfaction (8/19, 42%). CONCLUSIONS: Our review of 39 randomized controlled trials found that recent eHealth interventions might promote smoking cessation, with mHealth being the dominant approach. Despite their success, the effectiveness of such interventions may diminish with time. The design of more personalized interventions could potentially benefit future studies. TRIAL REGISTRATION: PROSPERO CRD42022347104; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=347104.