Objective: To analyze the association between insufficient sleep and score of depressive symptoms among junior and senior high school students, so as to provide a scientific reference for targeted early intervention measures of adolescents depressive symptoms. Methods: From September to November 2023, a stratified cluster random sampling method was used to select 96 080 junior and senior high school students from 409 schools in 113 districts and counties in Shaanxi Province. A questionnaire survey was conducted using the 2023 Shaanxi Provincial Common Student Diseases and Health Influencing Factors Survey Form, and their height and weight were measured. Propensity score (PS) matched (1∶1) analysis was used to match participants with insufficient sleep to those sufficient sleep students. Through the gradual correction of the confounders, three multilevel linear models were established to analyze the association between insufficient sleep and depressive symptoms score, and subgroup analysis was conducted afterward. Results: A total of 70 135 (73.00%) students had insufficient sleep. After PS matching, 25 894 pairs were matched. Before PS matching, after adjusting for gender, educational stage, region, adolescent characteristics, boarding status, smoking, alcohol consumption, outdoor activities and body mass index grouping, linear regression analysis results showed that compared with students who got adequate sleep, students who lacked sleep had an increase of 1.39 scores ( B=1.39, 95%CI =1.28-1.51) in depressive symptoms; after PS matching, students with insufficient sleep got an increase of 1.32 scores ( B=1.32, 95%CI =1.17- 1.45 ) in depressive symptoms score compared with those who had adequate sleep (both P <0.05). Conclusions The insufficient sleep is associated with the increase of the depressive symptoms score of junior and senior high school students. It is recommended that junior and senior high school students should keep a good sleeping habit, so as to reduce the prevalence of depressive symptoms.

Objective:To investigate the relationship between triglyceride glucose index (TyG) and body inflammation.Methods:The data were obtained from a baseline survey in population in Xi'an in natural population cohort study in northwest China established in 2018-2019. Based on TG and FPG, TyG/TyG-BMI was constructed to reflect insulin resistance (IR) in the body, and systemic immune-inflammation index (SII) reflecting inflammation in the body was constructed using neutrophil, lymphocyte, and platelet counts. A logistic regression model was used to explore the relationship between the TyG and the SII.Results:A total of 11 491 subjects were included in the analysis. After adjusting for covariates, each unit increase in the TyG increased the risk of high SII by 21% ( OR=1.21, 95% CI:1.12-1.30). The risk of high SII in the group with the TyG in Q4 was 1.34 times higher than that in the group Q1 ( OR=1.34, 95% CI:1.18-1.52). Both sensitivity analysis and subgroup analysis further confirmed the stability of the association between the TyG and the SII. In the population with a BMI ranging from 18.5 to 23.9 kg/m 2, for every unit increase in the TyG as a continuous variable, the risk for high SII increased by 31% ( OR=1.31, 95% CI:1.18-1.45). As a categorical variable, the risk for high SII in the Q4 group was 1.52 times higher than that in the Q1 group ( OR=1.52, 95% CI:1.27-1.83). In a population with BMIs ranging from 24.0 to 27.9 kg/m 2, for every unit increase in the TyG as a continuous variable, the risk for high SII increased by 20% ( OR=1.20, 95% CI:1.07-1.35), and there was no significant difference when it was a categorical variable. Conclusions:The increase in IR is closely related to the development of inflammation in the body, and BMI may regulate their relationship. Early prevention of elevated IR levels before overweight or obesity may have a positive effect on the control of inflammation in the body.

Cohort study is one of the important research methods in analytical epidemiology because of its clear time sequence relationship, which is better than other observational studies in demonstrating causal association. However, screening diagnosis or other methods are often used to exclude the individuals with outcome events during the enrollment process of the subjects in cohort studies. The accuracy of screening diagnosis and the effectiveness of exclusion will affect the accuracy of the baseline status assessment of the subjects included in the study, which may lead to the causal time sequence reversal of exposure-outcome in the estimation of causal effect. Landmark analysis can be used to control reverse causality by excluding subjects with potentially unknown expose-outcome timing. In this paper, we describe the basic principles and analytical steps of landmark analysis, and use data from the Chinese Longitudinal Healthy Longevity Survey to explore the relationship between physical activity and frailty, and introduce the specific application of landmark analysis for the purpose of facilitating its application and inferring causal effects more accurately in cohort studies.

With completing a baseline survey of a large natural population cohort, conducting regular follow-up has become a key factor in further improving the quality of cohort construction and ensuring its sustainable development. Typical cohort follow-up methods include repeat surveys, routine monitoring, and community-oriented surveillance. However, in practical applications, there are often issues such as high costs, difficulty, and high error rates. Telephone follow-up is an important supplementary method to the methods mentioned above, as it has the characteristics of low cost, fast response, and high quality. However, the with difficult organization, quality control is challenging, response rates are low, and management levels vary widely, which limits its widespread use in large-scale population cohort studies. Given the above problems, this study draws on customer relationship management based on the actual needs of the China Northwest Cohort follow-up. It relies on the REDCap electronic data collection platform to build a telephone follow-up management and quality control system. Targeted solutions are provided for key issues in telephone follow-up implementation, including organizational structure, project management, data collection, and process quality control, to improve the quality control level of telephone follow-up comprehensively and thereby enhance the quality and efficiency of follow-up. We hope to provide standardized follow-up programs and efficient quality control tools for newly established and existing cohort studies.

【Objective】 To conduct a case-control study on precocious puberty as an example to introduce the establishment and design of the electronic Data capture and management platform using Research Electronic data Capture (REDCap) system and support the development of clinical research. 【Methods】 Based on the clinical REDCap system, the case-control research project of precocious puberty was created, the case report forms were designed, the user rights were set, and the data quality control rules were formulated. 【Results】 We established the electronic data capture and management platform for our research, which had 15 case report forms, to collect the data of the participants, including sociodemographic information, time for rest and activities, diet, exposure to environmental internal-secretion interfering-substances, physical examination and biochemical indicators. We conducted project management by setting up features such as user permissions and workgroups, and added data quality verification rules to control data quality. The data could be exported in various file formats for analysis and sharing. 【Conclusion】 The application of REDCap to establish the data capture and management platform of precocious puberty case-control study has promoted the efficient implementation of clinical research, which can be further popularized and applied to clinical researches in other fields.

【Objective】 To estimate the prevalence, associated factors and patterns of multimorbidity of non-communicable diseases among adults in Shaanxi Province so as to provide evidence for the prevention and control of non-communicable diseases. 【Methods】 We used the data of adults aged 18 years and older collected in the baseline survey of Shaanxi Project in the Regional Ethnic Cohort Study in Northwest China. Multinomial logistic regression was used to explore the associated factors for multimorbidity. Exploratory factor analysis was used to extract patterns of multimorbidity. 【Results】 The prevalence of multimorbidity was 10.7% among the 44 442 participants. Age increase, being males, urban residence, and being overweight or obesity were positively associated with multimorbidity. Compared with women, men had a higher risk of multimorbidity. The OR and 95% CI was 1.25 (1.12-1.39). The risk of multimorbidity increased with age among adults. Compared with participants aged 18.0-34.9 years, the ORs and 95% CIs of those aged 35.0-44.9, 45.0-54.9, 55.0-64.9, and ≥65.0 years were 4.73 (3.47-6.46), 15.61 (11.60-21.00), 41.39 (30.76-55.70) and 90.04 (66.58-121.77), respectively. The primary multimorbidity patterns among adults in Shaanxi were cardiovascular-metabolic multimorbidity (5.4%), viscero-articular multimorbidity (1.0%), and respiratory multimorbidity (0.3%). 【Conclusion】 More than one in ten adults in Shaanxi Province had multimorbidity, and the predominant pattern of multimorbidity was cardiovascular-metabolic multimorbidity. The prevention and control of non-communicable diseases should be reinforced in middle-aged and older people, males, people living in the urban, and overweight or obese people. More attention should be paid to the prevention and control of cardiovascular-metabolic diseases.

Objective:This study explored the association between antenatal calcium supplementation in the childbearing aged women and risk of small for gestational age infant (SGA) among singleton in Shaanxi province,China.Methods:Multi-stage random cluster sampling method was employed to collect information about pregnant women, who were pregnant and had definite outcomes, and their infants, from 30 districts (counties) in 2010 to 2013. Information was collected by face-to-face questionnaire survey. Generalized linear mixed models were employed after adjusting covariates. Dependent variable was whether single-birth neonate was SGA, and independent variable was calcium supplementation of childbearing aged women in different pregnant periods.Results:A total of 28 357 childbearing aged women was recruited in this study. The age of these women was (28.08±4.74) years old, of which, 79.28% were rural residents and 60.90% had calcium supplementation intake. There was a number of 12 810 female in singleton neonates. The neonatal birth weight and gestational age were (3.27±0.16) kg and (277.44±8.80) day, respectively. The prevalence of SGA was 11.35% in total, and 10.48% in mothers with maternal calcium supplementation and 12.70% in mothers without maternal calcium supplementation in whole antenatal period. There were statistically significant differences seen in antenatal calcium supplementation within the subgroups of maternal age (whether the mother was an advanced maternal woman), residential area, maternal occupation, maternal parity, maternal education level, and household incomes ( P<0.05). After adjusting these covariates, the risk of SGA among childbearing aged women with antenatal calcium supplementation showed 16% decreased risk ( OR=0.84, 95% CI: 0.77-0.92). Further analysis of the different antenatal periods showed that calcium supplementation during the second and third trimester had a statistically significant difference in reducing the risk of neonatal SGA ( P<0.05). Besides, subgroup analysis showed that there was a statistically significant difference between the perinatal calcium supplementation and the single-born neonates with SGA Significance ( P<0.05) in non-advanced women, those who had a low education level and moderate household economic status groups. Conclusion:The risk reduction of SGA among singleton neonates is related to calcium supplementation during antenatal period in Shaanxi province.

In medical research, the quality of data is the key to success. Thus, data quality control becomes an important part of ensuring the research's high quality. REDCap system is an emerging data acquisition system in medical research, which is gradually applied in research at home and abroad. It is a hot issue to realize double data entry and data quality control in using the REDCap system, which researchers are concerned about when this system is supposed to apply. This article will systematically introduce how to use the REDCap system for double data entry and quality control from the aspects of research project creation, data collection tool design, double data entry, data checking and exporting.

【Objective】 To describe the BMI growth trajectories from birth to 24 months and examine the effects of fully breastfeeding time and breastfeeding duration on the BMI growth trajectories. 【Methods】 We conducted a follow-up study of a cohort of 1 388 eligible births. Height and weight were measured at birth, every 3 months to 12 months, and every 6 months to 24 months. Detailed demographic, feeding, activity and diseases data were also collected prospectively. Latent growth mixture modeling was conducted to model the BMI growth trajectories from birth to 24 months. Mixed-effects logistic regression analyses were made to examine the impacts of breastfeeding on this outcome. 【Results】 We identified six BMI trajectory patterns in the 1 285 infants analyzed and labeled them as follows: "normative growth" (26.6%), "normal-accelerating growth" (8.7%), "normal-decelerating growth" (11.7%), "lower-persistent growth" (6.6%), "rapid growth" (26.8%), and "rapid-accelerating growth" (19.5%). Mixed-effects logistic regression analyses revealed that fully breastfeeding ≥ 3 months could significantly decrease the risk of "rapid growth" (OR=0.71, 95% CI 0.51-0.98) and "rapid-accelerating growth" (OR=0.53, 95% CI 0.37-0.75). After adjustment for confounding factors, the relationship remained significant (OR=0.61, 95% CI 0.41-0.89; OR=0.46, 95% CI 0.31-0.68). Weaning before 6 months could significantly increase the risk of "rapid growth" (OR=1.76, 95% CI 1.19-2.61) and "rapid-accelerating growth" (OR=2.08, 95% CI 1.38-3.14). These associations persisted after adjustment for confounding factors (OR=1.69, 95% CI 1.08-2.71; OR=1.88, 95% CI 1.18-2.99). 【Conclusion】 In rural Western China, the main BMI growth trajectory patterns include "normative growth" , "rapid growth" , and "rapid-accelerating growth" . Prolonging breastfeeding may reduce excess weight gain during infancy.

Cohort study is one of the basic methods used in epidemiological research. With the development of the etiological analysis of complex diseases such as cardiovascular diseases, large natural population-based cohort study has become a popular topic in medical research. In the process of cohort development, one of the important issues is to ensure the efficiency and safety on data collection. As a database management system, with open source, free clinical research data collection and high quality, REDCap can widely be applied in large population-based cohort studies. This article summarizes the baseline survey and follow-up procedures on cohort studies and introduces a REDCap-system-based solution for data collection and management. Contents on the establishment of data working groups, data collection, cohort follow-up methods and field application are also discussed in this paper, in order to improve the efficiency of data collection and management in cohort study to help the development of cohort study in China.