Objective:To survey the status of illness and consultation within two weeks among residents in a community in Chengdu.Methods:A multi-stage stratified random sampling was used to carry out a questionnaire survey among the residents in a community in Chengdu during March to April 2019. The disease status, disease severity and consultation within two weeks were surveyed, and influencing factors of two-week illness were analyzed with logistic regression.Results:Among 2 714 participants, 715 had illness (900 times) within two weeks, with a two-week prevalence rate of 26.3%. The main symptoms were dizziness (6.4%, 58/900), cough (6.2%, 56/900), lumbago and leg pain (4.9%, 44/900), palpitations (3.3%, 30/900) and headache (3.1%, 28/900). The three most common diseases were hypertension (38.3%, 345/900), diabetes (19.3%, 174/900) and common cold (6.4%, 58/900). In this survey, the rate of two-week in bed was 20.6‰(56/2 714), and the rate of two-week off work was 4.8‰(13/2 714). Age, gender, education level and work status were the influencing factors of the illness in two weeks ( P<0.05). The choice of medical institution was also different among residents. Conclusion:The survey suggest that primary care should focus on the key groups of residents in the community such as elderly, women, low education level, retirement and unemployed; and it is necessary to strengthen the primary care institutions and two-way referral system of health care.

Depression's high recurrence rate and severe consequences pose significant challenges to public health.To address this issue effectively,this review explores the innovative application of wearable devices in monitoring and intervening in depression,surpassing the limitations of traditional subjective assessments and patient self-reports.The paper systematically analyzes recent studies utilizing wearable devices to monitor physiological and behavioral indicators of depression,categorizing them by different technological types and evaluating their practical effectiveness in early diagnosis and intervention.The findings indicate that wearable devices can continuously monitor physiological indicators and behavioral patterns related to depression,potentially enabling early detection of depressive episodes and supporting timely interventions.Despite challenges such as data privacy and user acceptance,wearable technology holds immense potential in enhancing clinical outcomes in depression treatment.

Objective:To explore the association of different obesity measurement indexes on serum C-reactive protein (CRP) in Chinese adult women.Methods:The data were obtained from baseline and follow-up surveys of the urban Breast Cancer Screening Program in Shuangliu District, Chengdu. A total of 441 adult women were included in the study. A questionnaire survey, physical examination, and laboratory testing were conducted on the subjects. Multivariate logistic regression model, two-level mixed effects logistic regression model, and restricted cubic spline method were used to investigate the linear and nonlinear correlation between different obesity measurement indexes and serum CRP in adult women.Results:For every 1 unit increase in BMI, waist circumference (WC), and adiposity, the risk of elevated serum CRP or exacerbation of chronic low-grade inflammation in adult women increased by 16.5%, 5.0%, and 11.1% ( P<0.05), respectively. Both BMI and adiposity were nonlinear correlated with serum CRP. Using BMI=24.0 kg/m 2 as the reference point, serum CRP level increased with the increase of BMI when BMI >24.0 kg/m 2. Using adiposity=30% as the reference point, serum CRP level increased with the increase of adiposity when adiposity >30%. Conclusions:Overall, obesity reflected by BMI had the strongest association with serum CRP in adult women, followed by body fat content reflected by adiposity, and central obesity reflected by WC had the weakest association with CRP. Adult women with BMI >24.0 kg/m 2 or adiposity >30% are at high risk for obesity-related inflammatory manifestations.