Districts Of Shanghai Research Articles

The site-city interaction effect uncertainty on structural responses and its application to fragility analysis of buildings in Shanghai CBD

Seismic fragility analysis is a crucial tool for assessing the seismic performance of buildings. In areas with dense clusters of tall buildings, the significant site-city interaction (SCI) effect alters wave propagation mechanisms, influencing the seismic fragility of structures. However, a significant increase in computational workload results from the need for detailed modeling of sites and building clusters for the SCI analysis. To address this challenge, this work first investigates the minimum number of earthquake waves required to characterize SCI-induced response changes. The Central Business District of Shanghai is analyzed. A table for the recommended minimum number for a given accuracy requirement and prediction reliability is provided. Moreover, a seismic fragility analysis method considering the SCI effect is proposed for low-rise buildings. The case study indicates that, buildings with similar height will exhibit various fragility changes after considering SCI. For the complete damage state, the mean intensity value of the fragility curve can be 14.4 % smaller than that without SCI. In addition, this approach provides significant computational workload reduction. For the case study, the computational workload of the proposed method is roughly 1/50 of that using traditional IDA method.

Decreased prevalence of alcohol use and related sociodemographic factors in an urban district of Shanghai, China: Evidence from three cross-sectional surveys (2010–2021)

BackgroundAlcohol use contributes considerably to the global impact of disease. However, limited research has been conducted recently to explore the changes in the prevalence of alcohol use, especially in urban Shanghai, China. ObjectivesTo estimate the prevalence changes of alcohol use and explore related sociodemographic factors among urban residents of Xuhui district, Shanghai, China. MethodsUsing a multistage probability proportionate-to-size sampling method, three waves of household investigations via a structured questionnaire were conducted in Xuhui district, Shanghai, China, between 2010 and 2021. Data were collected by face-to-face interviews among residents aged 15 or older who responded to the 2010, 2015, and 2021 Health Status and Health Service Utilization Survey. Age and sex standardized prevalence of alcohol use was calculated, and the linear trend was tested using logistic regression models. Multilevel mixed-effects logistic regression models with robust covariance matrix estimators were used to estimate related factors of alcohol use. ResultsA total of 24 552 participants aged 15–109 years were included. The standardized overall prevalence of current regular alcohol use statistically declined from 8.8 % in 2010 to 5.5 % in 2021. This decreasing trend was statistically significant, especially among men aged 30–59 and ≥ 75 years old. However, the prevalence of overall alcohol use, regardless of frequency, increased from 19.6 % in 2015 to 24.0 % in 2021. Multivariate regression analysis showed that men had a significantly higher likelihood of regular alcohol use than women. Also, age was positively related to regular alcohol use, while education level was negatively related to this behavior. ConclusionsAlcohol use was still common, although a significant decreasing trend in the prevalence of regular alcohol use was observed overall, in this study population. The findings call for strengthened health education and alcohol control in the context of the harmful effects of alcohol use at any level.

A dataset of remote sensing images from high-precision optical satellites for urban three-dimensional reconstruction in Xuhui District of Shanghai

A dataset of remote sensing images from high-precision optical satellites for urban three-dimensional reconstruction in Xuhui District of Shanghai

Unidimensional or multidimensional? Revisiting the psychometrics of PHQ-9 and EPDS using bifactor model and item response theory in 2939 Chinese perinatal women

BackgroundPerinatal depression often goes undetected and untreated in low- and middle-income countries like China. Reliable screening tools can improve this situation. The Patient Health Questionnaire-9 (PHQ-9) and the Edinburgh Postnatal Depression Scale (EPDS), two widely used tools, often exhibit inconsistent factor structures, leading to debates regarding their unidimensionality versus multidimensionality and casting doubts on their psychometric properties. MethodsOur study aimed to assess the utility of PHQ-9 and EPDS in Chinese perinatal women and to address the debate by employing the bifactor model and item response theory (IRT). We enrolled 2939 perinatal women from a maternity and infant health hospital serving all 16 districts of Shanghai. The bifactor model was used to examine the factor structure of PHQ-9 and EPDS, while IRT analysis evaluated the psychometric properties. ResultsThe indices derived from the bifactor model indicated that both PHQ-9 and EPDS should be used as unidimensional measurements. All items in PHQ-9 and EPDS showed adequate discriminative ability and difficulty, but certain items require further refinement. PHQ-9 demonstrated better measurement precision at high levels of latent depression than EPDS. LimitationsThese findings might not generalize to perinatal women in impoverished areas. The absence of clinical diagnoses limited the exploration of sensitivity and specificity. ConclusionsPHQ-9 and EPDS are effective tools for detecting depression in Chinese perinatal women and should be used as unidimensional tools. Our study expands upon existing psychometric findings related to PHQ-9 and EPDS, offering valuable insights for their application in research and clinical settings.

The control rate of hypertension across months of year and hours of day in a large real-world database.

We investigated the control rate of hypertension across months of year and hours of day in a real-world database. The study participants were hypertensive patients from 142 community health centers across 16 districts in Shanghai, China, who measured their blood pressure with an automatic office blood pressure measurement platform between 2018 and 2023. The 343,400 hypertensive patients included 53.7% of women, and had average age of 70.2 (±8.1) years (range 50-90 years). For months of year, the control rate of hypertension was lowest in February and highest in August (51.9% vs 71.8%). For hours of day, the control rate of hypertension was lowest at 7:00 AM and highest at 12:00 PM (52.1% vs 76.0%). When the months of year and hour of day were considered together, the control rate was lowest at 7 AM in February (42.1%), and highest at 12 PM in July (86.8%). In 8516 patients who had uncontrolled blood pressure in the early morning and had their blood pressure also measured around noon, 45.7% had masked uncontrolled morning hypertension, with higher rates in spring and summer, and in women, those aged 50-69 years, and non-diabetic patients. The control rate of hypertension varies greatly across months of year and hours of day, suggesting that the evaluation of blood pressure control has to take into full consideration the measurement time in terms of months and hours.

Smartwatch Measures of Outdoor Exposure and Myopia in Children

Time spent outdoors has been proven effective in preventing myopia, but little is known about the association of outdoor exposure patterns with myopia. To examine the association of outdoor exposure patterns with myopic shift in children. This 1-year prospective cohort study from December 2017 to December 2018 was a secondary analysis of a cluster-randomized trial (Shanghai Time Outside to Reduce Myopia [STORM]). STORM was a school-based intervention study, recruiting 16 schools from 8 districts in Shanghai, from October 2016 to December 2018. Children without myopia at baseline who consistently wore a smartwatch for a minimum of 6 hours daily, sustained for at least 90 days, and who had complete information were included. Data analysis was performed from December 2017 to December 2018. The outdoor exposure pattern was defined as the episode of time outdoors and instant sunlight intensity over a continuous period. Myopic shift was defined as the absolute change in refraction between the initial spherical equivalence and the follow-up spherical equivalence. This study included 2976 students (mean [SD] age, 7.2 [0.6] years; 1525 girls [51.2%]). The mean (SD) daily time outdoors was 90 (28) minutes, and the mean (SD) sunlight intensity was 2345 (486) lux. Of the 12 outdoor exposure patterns, the major outdoor exposure patterns were time outdoors with at least 15 minutes, accounting for 74.9% of minutes (33 677 584 of 45 016 800 minutes). Only patterns with at least 15 minutes accompanied with no less than 2000 lux were associated with less myopic shift in refraction (for ≥15 minutes and 2000 to 3999 lux, -0.007 diopter [D] [95% CI, -0.011 to -0.002 D]; for ≥15 minutes and ≥4000 lux, -0.006 D [95% CI, -0.010 to -0.002 D]). The isotemporal substitution of patterns with at least 15 minutes and 2000 lux for other outdoor exposure patterns was positively associated with less myopic shift. In this 1-year prospective cohort study of children with smartwatches, continuous outdoor exposure with at least 15 minutes accompanied with no less than 2000 lux sunlight intensity was associated with less myopic shift. These findings suggest that future outdoor interventions should focus not only on the overall time outdoors but also on the effective outdoor exposure patterns, as a means to effectively prevent myopia in children.

Association of Beverage Consumption during Pregnancy with Adverse Maternal and Offspring Outcomes.

As the global consumption of sugary and non-sugar sweetened beverages continues to rise, there is growing concern about their health impacts, particularly among pregnant women and their offspring. This study aimed to investigate the consumption patterns of various beverages among pregnant women in Shanghai and their potential health impacts on both mothers and offspring. We applied a multi-stage random sampling method to select participants from 16 districts in Shanghai. Each district was categorised into five zones. Two towns were randomly selected from each zone, and from each town, 30 pregnant women were randomly selected. Data were collected through face-to-face questionnaires. Follow-up data on births within a year after the survey were also obtained. The consumption rates of total beverages (TB), sugar-sweetened beverages (SSB), and non-sugar sweetened beverages (NSS) were 73.2%, 72.8%, and 13.5%, respectively. Logistic regression analysis showed that compared to non-consumers, pregnant women consuming TB three times or less per week had a 38.4% increased risk of gestational diabetes mellitus (GDM) (OR = 1.384; 95% CI: 1.129-1.696) and a 64.2% increased risk of gestational hypertension (GH) (OR = 1.642; 95% CI: 1.129-2.389). Those consuming TB four or more times per week faced a 154.3% higher risk of GDM (OR = 2.543; 95% CI: 2.064-3.314) and a 169.3% increased risk of GH (OR = 2.693; 95% CI: 1.773-4.091). Similar results were observed in the analysis of SSB. Regarding offspring health, compared to non-consumers, TB consumption four or more times per week was associated with a substantial increase in the risk of macrosomia (OR = 2.143; 95% CI: 1.304-3.522) and large for gestational age (LGA) (OR = 1.695; 95% CI: 1.219-2.356). In the analysis of NSS, with a significantly increased risk of macrosomia (OR = 6.581; 95% CI:2.796-13.824) and LGA (OR = 7.554; 95% CI: 3.372-16.921). The high level of beverage consumption among pregnant women in Shanghai needs attention. Excessive consumption of beverages increases the risk of GDM and GH, while excessive consumption of NSS possibly has a greater impact on offspring macrosomia and LGA.

Survey on the satisfaction of community elderly care service and its optimization strategies: A case study of S district in Shanghai

Survey on the satisfaction of community elderly care service and its optimization strategies: A case study of S district in Shanghai

How washing behaviors influence GHG emissions in textile use phase: a PLS-SEM analysis of household washing behaviors in Shanghai

PurposeThis paper explores what factors influence household textile washing behaviour and how these factors relate to greenhouse gas emissions during the textile use stage.Design/methodology/approachA questionnaire survey related to textile summer washing and care behavior was conducted among households in 16 administrative districts of Shanghai. This study used the modified Consumer Lifestyle Approach framework of the washing and care ecosystem. The research hypotheses were established by selecting related factors from four aspects: household demographic characteristics, economy and consumption characteristics, washing machines and detergents characteristics.FindingsFirst, we have demonstrated how some course factors do not significantly affect greenhouse emissions. None of the demographics, detergent-related activities, economy and consumption constructs significantly affect greenhouse emissions. Second, we have identified that washing machine and related activities has a direct positive effect on GHG emissions. The washing machine is not only the de facto carrier of all washing activities but also the core of washing activities. Washing machine is crucial in reducing greenhouse emissions and adjusting consumer behaviors.Originality/valueThis paper conducts a study related to the washing and care behavior of households in Shanghai. The paper examines the factors influencing household washing behavior and the relationship between these factors and greenhouse gas emissions during the textile use phase.

Understanding the Role of Technology Anxiety in the Adoption of Digital Health Technologies (DHTs) by Older Adults with Chronic Diseases in Shanghai: An Extension of the Unified Theory of Acceptance and Use of Technology (UTAUT) Model.

The unprecedented rapid growth of digital health has brought new opportunities to the health field. However, elderly patients with chronic diseases, as an important potential beneficiary group, are affected by the digital divide, leading to unsatisfactory usage of digital health technologies (DHTs). Our study focused on the factors influencing the adoption of DHTs among this vulnerable group. To extend the UTAUT theory, technology anxiety and several demographic predictors were included to address the age characteristics of the respondents. An on-site survey was conducted in general, district, and community hospitals in Shanghai (n = 309). Facilitating conditions negatively influenced technology anxiety. Technology anxiety hindered behavioural intention. Social influence had a significant but negative impact on behavioural intention. Education, whether older adults have had experience with DHTs and previous smartphone usage experiences were significantly associated with technology anxiety. The findings provide valuable information for multiple stakeholders, including family members of elderly users, product designers, and policymakers. Ameliorating facilitating conditions, improving devices' usage experience, encouraging attempts and focusing on groups with lower educational levels can help to reduce technology anxiety and promote DHT acceptance and use in older age groups.

The impact of social interventions on COVID-19 spreading based on multilayer commuter networks

From March to June 2022, Shanghai was struck by a new coronavirus variant, Omicron, resulting in the infected cases of at least 600,000 people. Despite implementing a strict containment policy of city-wide silence (i.e., residents were not allowed to go out unless necessary), the outbreak cannot be effectively prevented within a short period of time. A significant academic and practical question is: how could we prevent and control outbreak of COVID-19 in large, densely populated cities like Shanghai? It is necessary to develop a rational epidemic spreading model for large cities, in order to accurately predict the trend of disease and quantitatively assess the impact of non-pharmaceutical interventions. In this paper, a multilayer commuter metapopulation network model is constructed to capture commuting flows and the size of epidemic outbreak during commuting between districts. The model accurately predicts epidemic spreading in each district of Shanghai. Assuming strict city-wide lockdowns, with each district locked down and limited inter-district commuting as social zones, simulations demonstrate significant suppression of outbreaks due to social-level interventions. For example, a 1-fold increase in PCR (Polymerase Chain Reaction) testing efficiency reduces the size of epidemic outbreak by approximately 70%. Larger districts require stricter controls to prevent exponential growth. Lockdowns effectively prevent epidemic outbreak at low disease rates but less so at high rates. Liberalized policies lead to varied outbreak trends, with economically developed regions peaking earlier due to higher population densities. This study provides a comprehensive framework for quantitatively evaluating the impact of social and regional controls on urban epidemics.

Carbon neutrality transformation pathway in ecoregions: An empirical study of Chongming District, Shanghai, China

In the context of global efforts to address climate change, research into regional carbon neutrality strategies has become especially critical. For developing countries and regions, it is essential to scientifically and rationally assessing the paths for small-scale regional transformations under carbon neutrality imperatives to effectively implement low-carbon transition measures. This study utilizes Chongming District in Shanghai of China as a case to establish a framework for forecasting carbon emission and sink from a multi-dimensional natural-social perspective. This facilitates the simulation and optimization of pathways for carbon neutrality transformation. The results indicate: (1) From 2000 to 2020, the total regional carbon emission exhibited a rising trend, while the total carbon sink initially declined then increased, indicating potential enhancement zone with significant potential and space for carbon neutrality development. (2) Enhanced management of ecological spaces and land use planning result in notable increases in carbon sink. Strategic measures such as emission and consumption reductions, alongside energy transitions, effectively controlled carbon emission growth and facilitated comprehensive decarbonization. (3) By combining ecological priority with enhanced control and balanced development with enhanced control, the region can achieve carbon neutrality. This showcases the effective role of policy regulation in facilitating high-quality carbon–neutral transformations. (4)Effective ecosystem management along with robust reduction and transition strategies enable county-level carbon–neutral transformations, offering a model and methodological support for other developing regions facing the twin challenges of economic growth and environmental sustainability.

Iodine Status of Infants and Toddlers under 2 Years of Age and Its Association with Feeding Behaviors and Maternal Iodine Status in Shanghai: A Quantile Regression Analysis.

It is crucial to provide adequate iodine nutrition to infants and toddlers for proper thyroid function and subsequent brain development. Infants are particularly vulnerable to iodine deficiency during the transition from a milk-based diet (breast milk and/or infant formula) to solid food. This study examines the current iodine levels of children during their first two years of life and investigates the association between these levels and feeding behaviors and the iodine status of their mothers in Shanghai, a city located in eastern China. A hospital-based cohort study was conducted to enroll mother-child pairs, where the child is aged 6-23 months, who visited community health service centers in the 16 districts of Shanghai, China. Data on socio-demographic factors and feeding behavior data were collected from the participants. The urinary iodine concentration (UIC) in both the young children and their mothers were analyzed. A total of 2282 mother-child pairs were included in this analysis. The median (p25-p75) UIC for lactating women, weaning women, and children were 121.3 μg/L (68.1-206.4 μg/L), 123.4 μg/L (58.4-227.2 μg/L), and 152.1 μg/L (75.8-268.3 μg/L), respectively. The UIC in children was found to be higher than that in their mothers (p < 0.001). Children who consumed less than 500 mL per day of formula milk in the last week had lower UICs compared with those who consumed 500 mL per day or more (p = 0.026). Furthermore, the children's UIC was positively correlated with the maternal UIC (rs = 0.285, p < 0.001). Multiple quantile regression analysis revealed a statistically significant positive association between maternal UIC and children's UIC between the 0.1 and 0.9 quantiles (all p < 0.001). We found that the iodine status of infants and toddlers, as well as of mothers, was sufficient. However, a large minority of children and mothers may be at risk of iodine deficiency. Furthermore, no associations between children's UIC and feeding behaviors were observed. Moreover, there was a positive correlation between the UIC of young children and their mothers.

A study on the spatial differences between the tourism network attention and tourism flow in Shanghai, China

The tourism network attention as a reflection of tourism demand is closely related to the tourism flow, the differences between the two has become an important criterion for judging the efficiency of destination tourism demand conversion, as well as a manifestation of the balance and coordination of destination tourism industry. Against the background of insufficient release of tourism demand in China, research on the development differences between tourism network attention and tourism flow can provide a basis for demand-side management and high-quality development. Based on the theory of spatial mismatch, this research analyzes the spatial development difference between the tourism network attention and the tourism flow in Shanghai from 2012 to 2021 using methods such as center of gravity model, spatial mismatch index, and two-dimensional combination matrix. The results show: (1) According to the analysis of the center of gravity model, there was a shift of the center of gravity of tourism network attention with the direction of "south-north", while the tourism flow shifted "west-east"; the center of gravity between tourism network attention and tourism flow began to diverge from 2012 to 2016, gradually converged from 2016 to 2019, and then gradually deviated again after 2020. (2) According to the spatial mismatch index, the spatial mismatch types between tourism network attention and tourism flow in various Districts of Shanghai are mainly negative and low mismatch, with high mismatch areas mainly distributed in the eastern and southwestern parts of Shanghai. (3) Combining the two-dimensional combination matrix, it can be observed that the spatial development difference between tourism network attention and tourism flow in Shanghai show a characteristic of "enlarging-shrinking-enlarging". From 2012 to 2016, the spatial development difference between tourism network attention and tourism flow in Shanghai continuously expanded; from 2017 to 2019, the spatial development difference continuously shrank; and from 2020 to 2021, the spatial differences expanded again. (4) The analysis results of the panel data model show that the development of tourism resources and the level of tourism services have a positive promoting effect on the evolution of spatial mismatch, while the social basic development environment has a negative effect. The research results not only meet the needs of evaluating the high-quality development of the tourism industry in the current economic restructuring, providing direction for the high-quality development of the regional tourism industry, but also enrich the research content of network attention as a tourism element participating in the evaluation of tourism industry development quality, and deepen the relationship research between network attention and tourism flow.

Assessment of radiotherapy and diagnosis resources allocation in Shanghai, China

ObjectiveTo evaluate the equity of medical resources in radiotherapy and diagnosis in Shanghai, China, based on population, geography, and economic factors. MethodsData on medical resources including institutions, equipment, and staff in radiotherapy/diagnosis were collected from all 16 districts of Shanghai, China in 2022. Separate data were collected for institutions and devices in CT. The Gini coefficient (G) and Lorenz curves were used to assess fairness based on population and geography, while the Theil index (T) was employed to evaluate health equity based on economic factors. Health resource agglomeration degree (HRAD) and population agglomeration degree (PAD) were utilized to analyze the equity and accessibility of medical resources considering both population and geography. ResultsIn 2022, Shanghai had a total of 992 institutions, 4,925 devices, and 10,282 personnel in radiotherapy and diagnosis. Additionally, there were 381 institutions conducting CT examinations and 776 CT machines in Shanghai. The Gini coefficients for institutions, devices, and personnel in radiotherapy and diagnosis based on population ranged from 0.2 to 0.4, while for CT, the Gini coefficients for institutions and devices ranged from 0.2 to 0.4. When considering geography, all Gini coefficients were greater than 0.5. The results of the Theil index indicated that inequities in distribution may be influenced by economic factors. The HRAD and PAD revealed disparities in the accessibility of institutions, devices, and personnel in radiotherapy/diagnosis and CT in Shanghai. ConclusionsInequities in the distribution of institutions, equipment, and personnel for radiotherapy/diagnosis and CT were observed in Shanghai in 2022, both geographically and economically. There is a critical need to enhance the allocation of resources for radiological equipment and personnel and to establish a scientifically robust urban resource planning framework.

Urban traffic-parking system dynamics model with macroscopic properties: a comparative study between Shanghai and Zurich

Analyzing the dynamics of parking traffic can better represent the real dynamic states of road networks, thereby allowing for a deeper analysis of the parking system’s impact. This paper comparatively investigates the impact of parking policies on two traffic networks with different infrastructure, socio-economic, and policy characteristics. Parking space, average parking duration, and parking fee policies were analyzed as a function of cruising distances and cruising time with indirect effects on traffic emissions. Empirically, the system dynamics model application is tested and validated with the macroscopic data from two central business districts (CBDs) in Shanghai (Xujiahui area) and Zurich (Bahnhofstrasse area). Results showed Bahnhofstrasse CBD is more sensitive against the policy shifts with relatively higher elasticity and indicated greater responsiveness in aggregating traffic emissions when compared with Xujiahui CBD. The findings of this study may provide an overall framework to empirically assess the performance of different traffic conditions and strategies on urban parking systems.

Effects of Social Support on Medication Adherence Among Patients with Schizophrenia: Serial Multiple Mediation Model.

This study aims to explore the serial mediating effect of stigma and depression on the association between social support and medication adherence. A cross-sectional survey was undertaken in the Changning District of Shanghai using a five-part questionnaire from August to December 2023. A convenient sampling method was employed, and 35 patients with schizophrenia were invited from each of the 9 streets in Changning District to participate in the survey, resulting in a total of 305 valid questionnaires collected. The questionnaire measured social support, stigma, depression, medication adherence, and demographic characteristics. Data analysis involved descriptive statistics, independent samples t-tests, ANOVA, Pearson correlation analysis, and the bootstrap method. There was a direct and significantly positive association between social support and medication adherence (β = 0.69, p < 0.001). Moreover, increased levels of stigma (β = - 0.45, p = 0.013) and depression (β = - 0.09, p = 0.017) were both associated with a decline in medication adherence. Bootstrapping analysis revealed that the association between social support and medication adherence operated indirectly through stigma (β = 0.11, 95% CI: 0.03, 0.18). Additionally, social support was indirectly associated with medication adherence through depression (β = 0.15, 95% CI: 0.04, 0.30). Further analysis indicated that social support had an indirect association with medication adherence through both stigma and depression (β = 0.04, 95% CI: 0.01, 0.07). Stigma and depression serially mediate the association between social support and medication adherence among patients with schizophrenia. This serial multiple mediation model underscores the importance of integrating social support interventions with psychological interventions aimed at reducing stigma and depression, thereby effectively enhancing medication adherence in patients with schizophrenia.

A hybrid ensemble optimized BiGRU method for short-term photovoltaic generation forecasting

In the context of prominent energy crisis, photovoltaic power (PV) generation has received increasing attention, then accurate PV generation forecasting is crucial for ensuring the smooth operation of power stations. However, existing research is insufficient in comprehensively analyzing the impact of PV generation volatility. To fill the gaps and enhance the prediction accuracy, this paper proposes a new hybrid forecasting method. We first introduce the Locally Weighted Scatterplot Smoothing (LOWESS) method to process the data and enhance the data stability, and use Pearson correlation coefficient (PCC) and Random Forests (RF) for feature selection to improve the quality of input data. Then we use Attention mechanism and Convolutional Neural Network (CNN) layer to optimize Bi-directional Gate Recurrent Unit (BiGRU) model and form a new hybrid model. Finally, based on the Bagging algorithm, we use ensemble learning to further optimize the hybrid BiGRU model to enhance the depth and performance. The proposed method is validated through case analysis results from two different locations, Xuhui District in Shanghai, China and the DKASC area in Alice Springs, Australia. The results demonstrate that, compared with other models, the developed method exhibits exceptional prediction performance and effectively enhances the accuracy of PV generation forecasting. Keywords: photovoltaic power generation; Locally Weighted Scatterplot Smoothing; feature selection; ensemble learning; Bi-directional Gate Recurrent Unit.

The Minhang Pediatric Biobank cohort study: protocol overview and baseline characteristics

BackgroundLittle has been done to establish biobanks for studying the environment and lifestyle risk factors for diseases among the school-age children. The Minhang Pediatric Biobank (MPB) cohort study aims to identify factors associated with health and diseases of school-aged children living in the urban or suburban area of Shanghai.MethodsThis population-based cohort study was started in all sub-districts/towns of Minhang district of Shanghai in 2014. First-grade students in elementary school were enrolled during the time of their routine physical examinations, with self-administered questionnaires completed by their primary caregivers. Additional information was extracted from multiple health information systems. Urine and saliva samples were collected during the baseline survey and follow-up visits.ResultsAt the end of 2014 academic year, a total number of 8412 children and their parents were recruited, including 4339 boys and 4073 girls. All the participants completed the baseline survey and physical examination, and 7128 urine and 2767 saliva samples were collected. The five most prevalent childhood diseases in this population were dental caries, bronchitis, pneumonia, asthma and overweight/obese.ConclusionsThe MPB cohort has been successfully established, serving as a useful platform for future research relating to the genetic, environmental and lifestyle risk factors for childhood diseases.

Longitudinal Dynamics of Immune Response in Occupational Populations Post COVID-19 Infection in the Changning District of Shanghai, China.

Monitoring the long-term changes in antibody and cellular immunity following Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection is crucial for understanding immune mechanisms that prevent reinfection. In March 2023, we recruited 167 participants from the Changning District, Shanghai, China. A subset of 66 participants that were infected between November 2022 and January 2023 was selected for longitudinal follow-up. The study aimed to investigate the dynamics of the immune response, including neutralizing antibodies (NAbs), anti-spike (S)-immunoglobulin G (IgG), anti-S-IgM, and lymphocyte profiles, by analyzing peripheral blood samples collected three to seven months post infection. A gradual decrease in NAbs and IgG levels were observed from three to seven months post infection. No significant differences in NAbs and IgG titers were found across various demographics, including age, sex, occupation, and symptomatic presentation, across five follow-up assessments. Additionally, a strong correlation between NAbs and IgG levels was identified. Lymphocyte profiles showed a slight change at five months but had returned to baseline levels by seven months post infection. Notably, healthcare workers exhibited lower B-cell levels compared to police officers. Our study demonstrated that the immune response to SARS-CoV-2 infection persisted for at least seven months. Similar patterns in the dynamics of antibody responses and cellular immunity were observed throughout this period.