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Cardiovascular disease: application of a composite risk index from the Telehealth System in a district community
Y B Yip1, Thomas K S Wong, Joanne W Y Chung
1Telehealth Team, School of Nursing, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, Hong Kong. hsvyip@inet.polyu.edu.hk
Insights
A new Cardiovascular Disease Risk Index (CVDRI) effectively identifies high-risk individuals in communities. Higher CVDRI scores significantly increase the likelihood of developing cardiovascular disease (CVD), highlighting the need for targeted interventions.
Area of Science:
- Public Health
- Epidemiology
- Cardiovascular Medicine
Background:
- Cardiovascular disease (CVD) poses a significant public health challenge.
- Effective risk stratification is crucial for community-based health interventions.
Purpose of the Study:
- To develop and validate a composite Cardiovascular Disease Risk Index (CVDRI) using Telehealth System data.
- To assess the association between the number of CVD risk factors and CVD prevalence in a community setting.
Main Methods:
- Utilized data from 1,570 residents in Hong Kong's Tsing Yi community.
- Developed a quantitative CVDRI (0-6 score) incorporating systolic/diastolic blood pressure, diabetes, BMI, smoking, and age.
- Employed multivariate logistic regression to calculate odds ratios for CVD prevalence.
Main Results:
- Individuals with CVDRI scores of 1, 2, and 3+ had 1.7, 5.3, and 10 times higher odds of CVD, respectively, compared to a score of 0.
- High blood pressure was the most influential CVDRI component, followed by diabetes and high BMI.
- The CVDRI effectively identified individuals at increased risk for cardiovascular disease.
Conclusions:
- A CVDRI derived from Telehealth data is a practical tool for identifying community members at risk of CVD.
- Simultaneous management of multiple risk factors in high-risk groups can enhance CVD morbidity and mortality reduction through nurse-led interventions.
Abstract:
Assessing a combination of cardiovascular disease (CVD)-risk factors may be a practical tool for risk assessment and for finding the high-risk group among local community members. This study examines the association between the number of CVD-risk factors, regardless of any specific combination with the CVD ambit, using data from 1,570 residents in Tsing Yi community (Hong Kong) who registered with the Telehealth System. A quantitative composite CVD Risk Index (CVDRI) with scores ranging from 0 to 6 included rankings for high systolic and diastolic blood pressure, presence of diabetes, body mass index (BMI), smoking, and age. Multivariate logistic regression was used to estimate odds ratios for the prevalence of CVD. Those with a CVDRI of 1, 2, or 3 and above were 1.7 [95% confidence interval (CI) = 1.34-3.99], 5.3 (95% CI = 3.60-7.90), and 10 times (95% CI = 6.41-15.50) more likely to have CVD, respectively, than those with a risk index of 0. Among the CVDRI components, high blood pressure had the greatest influence on CVD risk, followed by presence of diabetes and high BMI. In conclusion, a CVDRI based on existing health data from a Telehealth System was developed and used to identify local community members at risk of CVD. Nurse intervention may achieve greater reduction of CVD morbidity and mortality if multiple risk factors for the high-risk group are addressed at the same time.
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