People living in the same area are more likely to experience similar socioeconomic characteristics, which leads to cluster effect and influences the generalizability of data regarding metabolic syndrome (MetS). However, previous studies did not consider or adjust for the cluster effect of living circumstances. The aim of this study was to determine the prevalence of MetS and associated lifestyle factors in Chinese adults 18 to 80 years of age, using multi-level generalized estimation equation (GEE).The participants came from a large-scale cross-sectional population survey. A total of 28,062 participants underwent all the blood tests. Participants meeting at least 3 of the 5 diagnostic criteria were defined as having MetS. Multi-level GEE was used to evaluate the relationship between MetS and lifestyle covariates to control the cluster effect of living circumstances. Odds ratios (ORs) and their 95% confidence intervals (CIs) were used to assess the strength of each relationship.A total of 65.70% of the participants had at least 1 clinical feature of MetS, and 2926 were diagnosed with MetS (prevalence 14.03%). 32.74%, 18.93%, 10.25%, 3.25%, and 0.53% of the participants had 1, 2, 3, 4, and 5 components, respectively. The prevalence of MetS in men (12.31%) was lower than in women (15.57%). After controlling for the cluster effect of living circumstances, many demographic and lifestyle characteristics were associated with MetS. Overweight (OR = 1.670, 95%CI: 1.600-1.743), obesity (OR = 2.287, 95% CI: 2.136-2.449), current alcohol consumption (OR = 1.053, 95% CI: 1.020-1.086), physical labor (OR=1.070, 95% CI: 1.040-1.101), a high-salt diet (OR=1.040, 95% CI: 1.009-1.071), hyperuricemia (OR=1.264, 95% CI: 1.215-1.316), short sleep duration (OR=1.032, 95% CI: 1.009-1.055), and a family history of cardiovascular disease (OR=1.065, 95% CI: 1.019-1.113), or cerebrovascular disease (OR=1.055, 95% CI: 1.007-1.104) increased the risk of MetS. The risk of MetS increased 6.9% (OR = 1.069, 95% CI: 1.053-1.085) with each 5% increase in body fat percentage.MetS has become a serious public health challenge in China. Many lifestyle factors have been found to be closely associated with MetS, including obesity, a high-salt diet, alcohol consumption, and short sleep duration. Therefore, changes in lifestyle are very important for adults to reduce the prevalence of MetS.

UNASSIGNED: Routine health information systems (RHISs) are crucial to informing decision-making at all levels of the health system. However, the use of RHIS data in low- and middle-income countries (LMICs) is limited due to concerns regarding quality, accuracy, timeliness, completeness and representativeness.
UNASSIGNED: This study systematically reviewed technical, behavioural and organisational/environmental challenges that hinder the use of RHIS data in LMICs and strategies implemented to overcome these challenges.
UNASSIGNED: Four electronic databases were searched for studies describing challenges associated with the use of RHIS data and/or strategies implemented to circumvent these challenges in LMICs. Identified articles were screened against inclusion and exclusion criteria by two independent reviewers.
UNASSIGNED: Sixty studies met the inclusion criteria and were included in this review, 55 of which described challenges in using RHIS data and 20 of which focused on strategies to address these challenges. Identified challenges and strategies were organised by their technical, behavioural and organisational/environmental determinants and by the core steps of the data process. Organisational/environmental challenges were the most commonly reported barriers to data use, while technical challenges were the most commonly addressed with strategies.
UNASSIGNED: Despite the known benefits of RHIS data for health system strengthening, numerous challenges continue to impede their use in practice.
UNASSIGNED: Additional research is needed to identify effective strategies for addressing the determinants of RHIS use, particularly given the disconnect identified between the type of challenge most commonly described in the literature and the type of challenge most commonly targeted for interventions.

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Background: Emerging technologies such as smartphones and wearable sensors have enabled the paradigm shift to new patient-centered healthcare, together with recent mobile health (mHealth) app development. One such promising healthcare app is incision monitoring based on patient-taken incision images. In this review, challenges and potential solution strategies are investigated for surgical site infection (SSI) detection and evaluation using surgical site images taken at home. Methods: Potential image quality issues, feature extraction, and surgical site image analysis challenges are discussed. Recent image analysis and machine learning solutions are reviewed to extract meaningful representations as image markers for incision monitoring. Discussions on opportunities and challenges of applying these methods to derive accurate SSI prediction are provided. Conclusions: Interactive image acquisition as well as customized image analysis and machine learning methods for SSI monitoring will play critical roles in developing sustainable mHealth apps to achieve the expected outcomes of patient-taken incision images for effective out-of-clinic patient-centered healthcare with substantially reduced cost.

This panel study investigates how temperature, humidity, and their interaction affect chronic obstructive pulmonary disease (COPD) patients\' self-reported symptoms. One hundred and six COPD patients from Shanghai, China, were enrolled, and age, smoking status, St. George Respiratory Questionnaire (SGRQ) score, and lung function index were recorded at baseline. The participants were asked to record their indoor temperature, humidity, and symptoms on diary cards between January 2011 and June 2012. Altogether, 82 patients finished the study. There was a significant interactive effect between temperature and humidity (p < 0.0001) on COPD patients. When the indoor humidity was low, moderate, and high, the indoor temperature ORs were 0.969 (95% CI 0.922 to 1.017), 0.977 (0.962 to 0.999), and 0.920 (95% CI 0.908 to 0.933), respectively. Low temperature was a risk factor for COPD patients, and high humidity enhanced its risk on COPD. The indoor temperature should be kept at least on average at 18.2 °C, while the humidity should be less than 70%. This study demonstrates that temperature and humidity were associated with COPD patients\' symptoms, and high humidity would enhance the risk of COPD due to low temperature.