Affiliation:
1. College of acupuncture and moxibustion and Massage, Guizhou University of Traditional Chinese Medicine
2. Acupuncture and moxibustion Rehabilitation Department of the Second Affiliated Hospital of Guizhou University of Traditional Chinese Medicine
3. Chronic Disease Management Center of Guizhou Provincial Center for Disease Control and Prevention
4. The Second Clinical Medical College of Guizhou University of Traditional Chinese Medicine
Abstract
Abstract
Background
Metabolic syndrome (MS) has become a public health issue of common concern and urgent need to be solved all over the world. Guizhou Province is located in southwestern China, and because of its unique climate conditions, geographic location, dietary habits, and differences in living habits among ethnic groups, there is a unique distribution of risk factors for MS. The study protocol is designed to investigate the prevalence and related influencing factors of MS among adult residents of Guizhou Province, and to construct a non-invasive risk assessment model for the onset of MS on the basis of risk factors. Additionally, the study will explore the dose–response relationship between different obesity indicators and MS.
Methods
This cross-sectional study will employ a comprehensive and multi-modal recruitment approach to recruit adult residents residing in various cities, counties, and township communities in Guizhou Province who understand written Chinese. During the 16-month survey period, at least 6,435 survey participants will be recruited. The questionnaire data will include personal history, disease history, personal lifestyle habits, blood biochemical indicators, and anthropometry. The dietary data questionnaire design will refer to the Chinese Food Composition List. Data will be collected using a project-based, multidimensional, self-management tool. Statistical analysis will use descriptive analysis methods to study the incidence and prevalence of MS. Logistic regression analysis and linear regression analysis will explore the correlation between various factors and MS, and a non-invasive risk assessment model for MS will be constructed through logistic regression analysis. And the dose-response relationship between BMI, other obesity indicators, and MS risk was analyzed by restricted cubic spline (RCS) fitting regression.
Discussion
The study protocol is intended to update the prevalence and related influencing factors of MS in Guizhou Province over the past decade. Unlike previous studies, we will explore the relationship between dietary patterns and metabolic health, which is crucial for future nutritional recommendations. Additionally, we will conduct in-depth research on the dose–response relationship between different obesity indicators and MS. This will not only provide key data for understanding obesity in Guizhou Province, but also will provide scientific support for our other research.
Publisher
Research Square Platform LLC
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