Prevalence of hypertension among type 2 diabetes mellitus patients in China: a systematic review and meta-analysis

Figures

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  Figure 1.. Flowchart of a systematic review and meta-analysis for the prevalence of hypertension among T2DM patients in China.

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  Figure 2.. Forest plot of the nine studies that assessed the pooled prevalence of hypertension among T2DM patients in China.

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  Figure 3.. Funnel plots showed basic symmetry, indicating that there was no publication bias among the studies. Note: Standard normal deviate (SND) is defined as the sample mean divided by its standard error. Precision is defined as the inverse of the standard error. Regression analysis of precision with SND. The resulting regression equation is SND=a+b×precision. If there is asymmetry, the effect of a small sample test will systematically deviate from that of a large sample test, and the regression line will not pass through the starting point. In addition, p=0.922, which is >0.05, so there was no publication bias. When the x-axis (precision) value is 0, the corresponding y-axis is SND (sample mean divided by its standard error), and the 95% CI can be obtained by calculating the sample mean and standard error.

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  Figure 4.. Egger's test indicated that there was no publication bias among the studies.

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  Figure 5.. Forest plot for the subgroup analysis by region of the country. Note: The software specified that p values were not shown when there were fewer than three study samples.

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  Figure 6.. Forest plot for the subgroup analysis by study setting.

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  Figure 7.. Forest plot for the subgroup analysis by gender of primary study participants.