Automated Author ProfileXiaojing.Guo
Department of Chronic Disease and Aging Health Management, Chinese Center for Disease Control and PreventionInstitute of Basic Medical Sciences,Chinese Academy of Medical Science & School of Basic Medicine,Peking Union Medical College
Xiaojing.Guo
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 2.3 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Objective This study aimed to analyze the trends in blood pressure control rates among hypertensive patients managed under the National Basic Public Health Service from 2012 to 2022 and to explore the factors influencing these rates. The study provides a scientific basis for optimizing resource allocation and policy formulation.Methods TUtilizing data collected by the Chinese Center for Disease Control and Prevention from 16 counties across 8 provinces (autonomous regions), this study employed trajectory models and generalized linear mixed-effects models (GLMMs) to analyze blood pressure control rates and their associated factors.Results Most blood pressure control rates fluctuated between 59% and 72%, divided into three trajectory groups: the Low-Level Decline group (18.75%), all rural, with declining control rates; the Low-Level Increase group (29.17%), mostly rural, with increasing control rates; and the High-Level Maintenance group (52.08%), primarily urban, with control rates maintained above 75%. Individual behavioral protective factors varied significantly across groups, with the best protective indicators in the High-Level Maintenance group. Community physician service levels were high and relatively uniform across all groups. Blood pressure control rates in the Low-Level Decline group were associated with Dietary Diversity Score (DDS) and weight measurements; in the Low-Level Increase group, they were associated with gender and physical activity; and in the High-Level Maintenance group, they were associated with medication adherence and awareness of blood pressure knowledge.Conclusion The quality of community physician services requires further enhancement. It is recommended to strengthen the training of primary healthcare personnel, improve service quality, and intensify health education and lifestyle interventions to improve the management outcomes of hypertension.
Authors
- Danying.Li ;
- Xiaojing.Guo ;
- Xiaolei.Zhu ;
- Xiang.Si ;
- Xiaochang.Zhang ;
- Xia.Wan