The association of the Mediterranean diet (MD) with mortality among people with a history of cardiovascular disease (CVD) has not been systematically examined. Hereby, our objective was to investigate the association of MD with all-cause and cardiovascular mortality in people with a history of CVD. We searched five electronic databases including Embase, PubMed, Scopus, Web of Science, and Cochrane Central Register of Controlled Trials to screen eligible studies published before 31 August 2020. A random-effect model was used to examine the association of a 2-unit increment in MD score with the risk of all-cause and cardiovascular mortality. We conducted sensitivity and subgroup analyses and examined potential publication bias by Egger’s and Begg’s tests. Seven cohort studies (eight datasets) with a total of 37,879 participants who had a history of CVD were eligible for the main analysis. The pooled hazard ratios were 0.85 (95% CIs: 0.78–0.93; n = 8) for all-cause mortality and 0.91 (95% CIs; 0.82–1.01; n = 4) for cardiovascular mortality for each 2-unit increment in a score of adherence to MD. Subgroup analyses for all-cause mortality showed that the association appeared relatively stronger in Mediterranean areas (HR = 0.76 [0.69–0.83]) than non-Mediterranean areas (HR = 0.95 [0.93–0.98]) and in studies with a shorter duration (HR = 0.75 [0.66–0.84] for <7 years vs. HR = 0.94 [0.91–0.98] for ≥7 years). No evidence of publication bias was observed. The present meta-analysis of prospective cohort studies provided evidence that adherence to MD improved survival in people with a history of CVD.

Background: There are an increasing number of mobile apps that provide dietary guidance to support a healthy lifestyle and disease management. However, the characteristics of these nutrition-related apps are not well analyzed. Objective: This study aimed to evaluate the functionality and quality of nutrition-related apps in China. Methods: Mobile apps providing dietary guidance were screened in the Chinese iOS and Android app stores in November 2017, using stepwise searching criteria. The first screening consisted of extracting information from the app descriptions. Apps that (1) were free, (2) contain information on diet and nutrition, and (3) were last updated after January 1, 2016, were downloaded for further analysis. Nutritional functionalities were determined according to the Chinese Dietary Guidelines framework. Market-related functionalities were developed from previous studies and tailored to downloaded apps. The quality of apps was assessed with the user version of the Mobile App Rating Scale (uMARS). Results: Out of 628 dietary guidance apps screened, 44 were nutrition-related. Of these, guidance was provided on diet exclusively (11/44, 25%), fitness (17/44, 39%), disease management (11/44, 25%), or maternal health (5/44, 11%). Nutritional functionalities included nutritional information inquiry (40/44, 91%), nutrition education (35/44, 80%), food record (34/44, 77%), diet analysis (34/44, 77%), and personalized recipes (21/44, 48%). Dietary analysis and suggestions mainly focused on energy intake (33/44, 75%) and less on other factors such as dietary structure (10/44, 23%). Social communication functionalities were available in 42 apps (96%), user incentives were supported in 26 apps (59%), and intelligent recognition technology was available in 8 apps (18%). The median score for the quality of the 44 apps, as determined on a 5-point uMARS scale, was 3.6 (interquartile range 0.7). Conclusions: Most nutrition-related apps are developed for health management rather than for dietary guidance exclusively. Although basic principles of energy balance are used, their nutritional functionality was relatively limited and not individualized. More efforts should be made to develop nutrition-related apps with evidence-based nutritional knowledge, comprehensive and personalized dietary guidance, and innovative technology.

Background: High salt consumption has contributed to the rise of noncommunicable diseases around the world. The application of mobile health (mHealth) technologies has witnessed rapid growth in recent years. However, evidence to support mHealth interventions to confront the challenge of salt reduction has not yet been critically reviewed. Objective: The aim of this study was to identify, characterize, and evaluate mHealth interventions aimed at salt reduction across the world. Methods: A systematic search of studies in English or Chinese language published from January 1, 1992 to July 31, 2017 was conducted using 4 English databases (PubMed, MEDLINE, Global Health, and Cochrane) and 3 Chinese databases (Wanfang, China Science and Technology Journal, and China National Knowledge of Infrastructure). All studies directly using mobile technologies in health care with a primary or secondary objective of reducing dietary salt consumption were included. Results: A total of 1609 articles were found using the search strategy, with 11 full articles (8 English and 3 Chinese) being included for data extraction, including 11 interventional studies. Overall, few high-quality interventions were identified. Most interventions were limited by small study population sample sizes, lack of control groups, and short follow-up times, all of which were obstacles in generating long-term scalable approaches. Most interventions employed short message service as a platform for mHealth interventions, whereas some innovative mHealth technologies were also explored. Most interventions had a primary focus of improving awareness of dietary salt consumption. The outcome variables used to measure intervention effectiveness included 24-hour urinary sodium excretion, spot urine sampling, dietary records, and indirect behavior or knowledge indicators targeting salt consumption. Although most interventions displayed positive outcome results, none of them provided reliable evidence to evaluate the effectiveness of salt reduction. Conclusions: Salt reduction in mHealth initiatives remains relatively unexplored; however, studies that did intervene on salt-reduction show the potential of mHealth as an effective intervention method. We provide 3 recommendations for future mHealth interventions in salt reduction—(1) increased use of new, innovative, and interactive mHealth technologies; (2) development of mHealth interventions with primary prevention measures and goals of salt reduction; and (3) large-scale, rigorously designed, and object-targeted clinical trials of mHealth interventions with appropriate quantitative outcome variables, in particular 24-hour urine sodium.

Limited evidence investigated the combined influence of early-adulthood weight change and later physical activity on the risk of cardiovascular (CVD) and all-cause mortality. The aim of this study is to explore the associations of early-adulthood weight change and later physical activity with CVD and all-cause mortality. This is a cohort study of 23,193 US adults aged 40 to 85 years from the National Health and Nutrition Examination Survey (NHANES) 1999 to 2014. Cox proportional hazards regression was used to calculate hazard ratios (HRs) with 95% confidence intervals (CIs) of CVD and all-cause mortality associated with early-adulthood weight change and later physical activity. During a median follow-up of 9.2 years, there were 533 and 2734 cases of CVD and all-cause deaths. Compared with being physically inactive, the HRs of the CVD mortality of being physically active were 0.44 (0.26 to 0.73), 0.58 (0.19 to 1.82), 0.38 (0.17 to 0.86) and 0.46 (0.21 to 1.02) among individuals with stable normal, stable obese, non-obese to obese and maximum overweight early-adulthood weight change patterns. Using stable normal patterns that were physically active later as the reference, other early-adulthood weight change patterns did not show a significantly higher risk of CVD mortality when participants were physically active in later life; later physically inactive participants had a significantly increased risk of CVD mortality, with HRs of 2.17 (1.30 to 3.63), 5.32 (2.51 to 11.28), 2.59 (1.29 to 5.18) and 2.63 (1.32 to 5.26) in the stable normal, stable obese, non-obese to obese and maximum overweight groups, respectively. Similar results can be seen in the analyses for all-cause mortality. Our findings suggest that inadequate physical activity worsens the negative impact of unhealthy early-adulthood weight change patterns, which is worthy of being noted in the improvement of public health.

In estimating the average treatment effect in observational studies, the influence of confounders should be appropriately addressed. To this end, the propensity score is widely used. If the propensity scores are known for all the subjects, bias due to confounders can be adjusted by using the inverse probability weighting (IPW) by the propensity score. Since the propensity score is unknown in general, it is usually estimated by the parametric logistic regression model with unknown parameters estimated by solving the score equation under the strongly ignorable treatment assignment (SITA) assumption. Violation of the SITA assumption and/or misspecification of the propensity score model can cause serious bias in estimating the average treatment effect (ATE). To relax the SITA assumption, the IPW estimator based on the outcome‐dependent propensity score has been successfully introduced. However, it still depends on the correctly specified parametric model and its identification. In this paper, we propose a simple sensitivity analysis method for unmeasured confounders. In the standard practice, the estimating equation is used to estimate the unknown parameters in the parametric propensity score model. Our idea is to make inferences on the (ATE) by removing restrictive parametric model assumptions while still utilizing the estimating equation. Using estimating equations as constraints, which the true propensity scores asymptotically satisfy, we construct the worst‐case bounds for the ATE with linear programming. Differently from the existing sensitivity analysis methods, we construct the worst‐case bounds with minimal assumptions. We illustrate our proposal by simulation studies and a real‐world example.

BACKGROUND There are an increasing number of mobile applications that provide dietary guidance in supporting healthy lifestyle and disease management. However, the characteristics of these nutrition-related apps are not well analyzed. OBJECTIVE This study aimed to evaluate the functionality and quality of nutrition-related apps in China. METHODS Mobile apps providing dietary guidance were screened in Chinese iOS and android app stores using stepwise searching criteria in November 2017. Primary review was conducted by extracting information from the description of apps. Free apps that contain all the information of diet and nutrition, with the last update after 1st Jan 2016 were downloaded for further analysis on the nutritional functionality features based on the framework of Chinese Dietary Guidelines and on the market related features as well. The user version of the Mobile Application Rating Scale (uMARS) was used to assess the quality of apps. RESULTS Among the 44 downloaded nutrition-related apps screened from 628 apps with dietary guidance content, only 11(25%) were aimed exclusively for dietary guidance, the others were aimed for fitness guidance (17, 39%), disease management (11, 25%) and maternal health (5, 11%) respectively. The nutritional functionalities of the 44 apps included nutritional information enquiry (40, 91%), nutrition education (35, 80%), food record (34, 77%), diet analysis (34, 77%), and personalized recipes (21, 48%). Twelve out of 44 apps contained all of the above five nutrition related functionalities. The diet analysis and suggestions were mainly focused on energy (33/44, 75%), less on other factors like dietary structure (10/44, 23%). About 96% (42/44) of the apps provided social communication functionality and 59% (26/44) of the apps supported user incentives. Eight out of 44 apps (18%) also applied intelligent recognition technology. Using 5-point uMARS as scales of quality, the median scores of the 44 apps was 3.6 (IQR = 0.7). CONCLUSIONS Most nutrition-related apps are developed in the service of health management other than for dietary guidance exclusively. Although basic energy balance theory was generally applied, the nutritional functionality of the nutrition-related apps is relatively limited and not individualized. More efforts should be taken to integrate with the scientific nutritional knowledge and innovative technology in developing an app followed with complete and personalized dietary guidance.