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Identification of Hypertension Predictors and Application to Hypertension Prediction in an Urban Han Chinese Population: A Longitudinal Study, 2005-2010.

Zhang W, Wang L, Chen Y, Tang F, Xue F, Zhang C - Prev Chronic Dis (2015)

Bottom Line: After a 5-year follow-up, the cohort of participants had an area under receiver operating characteristic curve (area under the curve [AUC]) with an odds ratio (OR) of 0.755 (95% confidence interval [CI], 0.746-0.763) for men and an OR of 0.801 (95% CI, 0.792-0.810) for women.After tenfold cross validation, the AUC was still high, with 0.755 (95% CI, 0.746-0.763) for men and 0.800 (95% CI, 0.791-0.810) for women.An HSP-based 5-year risk matrix provided a convenient tool for risk appraisal.

View Article: PubMed Central - PubMed

Affiliation: Department of Biostatistics, School of Public Health, Shandong University, Jinan, China.

ABSTRACT

Introduction: Research suggests that targeting high-risk, nonhypertensive patients for preventive intervention may delay the onset of hypertension. We aimed to develop a biomarker-based risk prediction model for assessing hypertension risk in an urban Han Chinese population.

Methods: We analyzed data from 26,496 people with hypertension to extract factors from 11 check-up biomarkers. Then, depending on a 5-year follow-up cohort, a Cox model for predicting hypertension development was built by using extracted factors as predictors. Finally, we created a hypertension synthetic predictor (HSP) by weighting each factor with its risk for hypertension to develop a risk assessment matrix.

Results: After factor analysis, 5 risk factors were extracted from data for both men and women. After a 5-year follow-up, the cohort of participants had an area under receiver operating characteristic curve (area under the curve [AUC]) with an odds ratio (OR) of 0.755 (95% confidence interval [CI], 0.746-0.763) for men and an OR of 0.801 (95% CI, 0.792-0.810) for women. After tenfold cross validation, the AUC was still high, with 0.755 (95% CI, 0.746-0.763) for men and 0.800 (95% CI, 0.791-0.810) for women. An HSP-based 5-year risk matrix provided a convenient tool for risk appraisal.

Conclusion: Hypertension could be explained by 5 factors in a population sample of Chinese urban Han. The HSP may be useful in predicting hypertension.

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Related in: MedlinePlus

Prevalence of hypertension, by age, at baseline, in an urban Han population, China, 2005–2010.Age, yHypertension Prevalence, %MenWomen1817.912.081910.2302015.444.92218.60.692212.021.782312.462.652412.542.912512.461.272611.472.292712.912.22813.092.442912.453.093015.512.23114.293.053216.943.043315.52.933417.293.173520.713.743621.733.73717.624.383824.194.663925.434.064027.936.994127.777.324228.438.984330.29.794430.4610.734533.5513.024635.3413.724735.1314.554839.2118.884935.9118.225037.4521.625140.9724.395241.4626.115340.8527.835443.4332.165543.2732.585643.2433.785744.4141.925849.6442.965946.7245.536048.845.956148.3444.266253.546.58635554.626453.3154.976555.6853.956658.9158.796758.5953.86864.6253.096962.3560.387064.9462.967164.9968.257263.9562.417371.9968.167471.1270.617571.3569.837671.9769.687779.467.87874.4275.427970.6273.868072.468.638164.8975.618270.6871.748377.2758.068470.5981.82856068.42
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Figure 1: Prevalence of hypertension, by age, at baseline, in an urban Han population, China, 2005–2010.Age, yHypertension Prevalence, %MenWomen1817.912.081910.2302015.444.92218.60.692212.021.782312.462.652412.542.912512.461.272611.472.292712.912.22813.092.442912.453.093015.512.23114.293.053216.943.043315.52.933417.293.173520.713.743621.733.73717.624.383824.194.663925.434.064027.936.994127.777.324228.438.984330.29.794430.4610.734533.5513.024635.3413.724735.1314.554839.2118.884935.9118.225037.4521.625140.9724.395241.4626.115340.8527.835443.4332.165543.2732.585643.2433.785744.4141.925849.6442.965946.7245.536048.845.956148.3444.266253.546.58635554.626453.3154.976555.6853.956658.9158.796758.5953.86864.6253.096962.3560.387064.9462.967164.9968.257263.9562.417371.9968.167471.1270.617571.3569.837671.9769.687779.467.87874.4275.427970.6273.868072.468.638164.8975.618270.6871.748377.2758.068470.5981.82856068.42

Mentions: In our study, 26,496 of 95,785 participants had hypertension at baseline, a prevalence of 27.7% (32.6% for men and 19.5% for women). Although hypertension prevalence increased with age in both men and women (Figure 1), it was higher in men than women before age 60 and was similar after age 60. Of the 3,793 participants (2,894 men and 899 women) who did not have hypertension at baseline but had hypertension at the end of year 5, the cumulative incidence was 21.7% (3,793 of 17,471). We calculated the distribution of age and 11 biomarkers among participants with and without baseline hypertension (Table 1), and all variables differed significantly for participants with and without baseline hypertension. Results of the analysis were used to create a correlation matrix for the 11 biomarkers (Appendix A).


Identification of Hypertension Predictors and Application to Hypertension Prediction in an Urban Han Chinese Population: A Longitudinal Study, 2005-2010.

Zhang W, Wang L, Chen Y, Tang F, Xue F, Zhang C - Prev Chronic Dis (2015)

Prevalence of hypertension, by age, at baseline, in an urban Han population, China, 2005–2010.Age, yHypertension Prevalence, %MenWomen1817.912.081910.2302015.444.92218.60.692212.021.782312.462.652412.542.912512.461.272611.472.292712.912.22813.092.442912.453.093015.512.23114.293.053216.943.043315.52.933417.293.173520.713.743621.733.73717.624.383824.194.663925.434.064027.936.994127.777.324228.438.984330.29.794430.4610.734533.5513.024635.3413.724735.1314.554839.2118.884935.9118.225037.4521.625140.9724.395241.4626.115340.8527.835443.4332.165543.2732.585643.2433.785744.4141.925849.6442.965946.7245.536048.845.956148.3444.266253.546.58635554.626453.3154.976555.6853.956658.9158.796758.5953.86864.6253.096962.3560.387064.9462.967164.9968.257263.9562.417371.9968.167471.1270.617571.3569.837671.9769.687779.467.87874.4275.427970.6273.868072.468.638164.8975.618270.6871.748377.2758.068470.5981.82856068.42
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4663898&req=5

Figure 1: Prevalence of hypertension, by age, at baseline, in an urban Han population, China, 2005–2010.Age, yHypertension Prevalence, %MenWomen1817.912.081910.2302015.444.92218.60.692212.021.782312.462.652412.542.912512.461.272611.472.292712.912.22813.092.442912.453.093015.512.23114.293.053216.943.043315.52.933417.293.173520.713.743621.733.73717.624.383824.194.663925.434.064027.936.994127.777.324228.438.984330.29.794430.4610.734533.5513.024635.3413.724735.1314.554839.2118.884935.9118.225037.4521.625140.9724.395241.4626.115340.8527.835443.4332.165543.2732.585643.2433.785744.4141.925849.6442.965946.7245.536048.845.956148.3444.266253.546.58635554.626453.3154.976555.6853.956658.9158.796758.5953.86864.6253.096962.3560.387064.9462.967164.9968.257263.9562.417371.9968.167471.1270.617571.3569.837671.9769.687779.467.87874.4275.427970.6273.868072.468.638164.8975.618270.6871.748377.2758.068470.5981.82856068.42
Mentions: In our study, 26,496 of 95,785 participants had hypertension at baseline, a prevalence of 27.7% (32.6% for men and 19.5% for women). Although hypertension prevalence increased with age in both men and women (Figure 1), it was higher in men than women before age 60 and was similar after age 60. Of the 3,793 participants (2,894 men and 899 women) who did not have hypertension at baseline but had hypertension at the end of year 5, the cumulative incidence was 21.7% (3,793 of 17,471). We calculated the distribution of age and 11 biomarkers among participants with and without baseline hypertension (Table 1), and all variables differed significantly for participants with and without baseline hypertension. Results of the analysis were used to create a correlation matrix for the 11 biomarkers (Appendix A).

Bottom Line: After a 5-year follow-up, the cohort of participants had an area under receiver operating characteristic curve (area under the curve [AUC]) with an odds ratio (OR) of 0.755 (95% confidence interval [CI], 0.746-0.763) for men and an OR of 0.801 (95% CI, 0.792-0.810) for women.After tenfold cross validation, the AUC was still high, with 0.755 (95% CI, 0.746-0.763) for men and 0.800 (95% CI, 0.791-0.810) for women.An HSP-based 5-year risk matrix provided a convenient tool for risk appraisal.

View Article: PubMed Central - PubMed

Affiliation: Department of Biostatistics, School of Public Health, Shandong University, Jinan, China.

ABSTRACT

Introduction: Research suggests that targeting high-risk, nonhypertensive patients for preventive intervention may delay the onset of hypertension. We aimed to develop a biomarker-based risk prediction model for assessing hypertension risk in an urban Han Chinese population.

Methods: We analyzed data from 26,496 people with hypertension to extract factors from 11 check-up biomarkers. Then, depending on a 5-year follow-up cohort, a Cox model for predicting hypertension development was built by using extracted factors as predictors. Finally, we created a hypertension synthetic predictor (HSP) by weighting each factor with its risk for hypertension to develop a risk assessment matrix.

Results: After factor analysis, 5 risk factors were extracted from data for both men and women. After a 5-year follow-up, the cohort of participants had an area under receiver operating characteristic curve (area under the curve [AUC]) with an odds ratio (OR) of 0.755 (95% confidence interval [CI], 0.746-0.763) for men and an OR of 0.801 (95% CI, 0.792-0.810) for women. After tenfold cross validation, the AUC was still high, with 0.755 (95% CI, 0.746-0.763) for men and 0.800 (95% CI, 0.791-0.810) for women. An HSP-based 5-year risk matrix provided a convenient tool for risk appraisal.

Conclusion: Hypertension could be explained by 5 factors in a population sample of Chinese urban Han. The HSP may be useful in predicting hypertension.

Show MeSH
Related in: MedlinePlus