This large cohort study is the first to estimate SBP variability using mixed effects models to reduce regression dilution, and to determine the positive and log-linear age-specific association between SBP variability and risk of CVD, CHD, stroke, heart failure, all-cause mortality, CVD mortality, and non-CVD mortality among Chinese diabetic patients. The effect of SBP variability on the risk of various outcome events remained significant regardless of patient characteristics after adjusting for usual and baseline SBP, suggesting that SBP variability may provide additional valuable information as a potential predictor for the incidence of CVD events and mortality in the diabetic population, irrespective of the absolute SBP readings. There was no threshold for SBP variability, indicating that the lower the SBP variability, the better the outcome. These findings recommend that clinicians should be cautious about the effect of BP fluctuation on the incidence of CVD and all-cause mortality, as well as the focus on an optimal BP target. Moreover, the impact of SBP variability is strengthened in patients at younger age, lower usual SBP, Charlson’s index and number of types of anti-hypertensive drug prescribed. This is suggestive that additional attention may be needed for these specific patients; groups with higher SBP variability.
There is currently no literature investigating the age-specific effects of SBP variability on CVD and mortality amongst diabetic patients. In general, our results demonstrated a direct log-linear or linear association between SBP variability and outcome events, which confirmed the results of previous studies. For instance, a post-trial follow-up study of the landmark trial, named Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) trial, on 9,113 diabetic patients with a medium follow-up of 7.6 years also illustrated the positive log-linear associations that each 5 mmHg increment in SD of SBP was associated with a 13%, 8% and 11% increase in the risk of all-cause mortality, CVD, and myocardial infarction, respectively (15). No significant association for stroke and CVD mortality was obtained (15). Nevertheless, they acknowledged that the small sample size and number of events (668 stroke events and 614 CVD mortality events) may affect the generalizability of the results. A few studies have shown a lack of any significant associations between SBP variability and outcome events (11, 35). In a cohort study on 2,161 diabetic patients in Taiwan, over a 5.5 year follow-up, SBP variability was significant associated with all-cause mortality but not with CVD mortality. This was likely to be explained by the small sample size and small number of events as only 25 CVD mortality events among 2,161 patients were observed (35). Furthermore, the measurement of SBP variability was determined by SBP readings after baseline, which may have resulted in informative censoring or immortal time bias (12, 13). Compared to these studies, we have incorporated a significantly larger number of patients without CVD, longer follow-up periods and much large number of incident outcome events. In this current study, SBP variability was based on measurements performed before baseline, hence the results should be more reliable and better powered to demonstrate the etiological associations between SBP variability and adverse outcomes. It is also worthy to mention that the results in all previous studies did not correct for regression dilution bias, and thus their findings may underestimate the effect of SBP variability. Hence, it is expected that the strength of the association of SBP variability on the risk of event outcomes in this study will be greater.
In this current study the analyses of individual CVD events, identified a stronger impact of SBP variability on stroke compared to CHD and heart failure. Indeed, the previous meta-analysis, which included mostly studies involving patients with severe diseases such as CVD or from the general population, also showed a similar pattern that SBP variability, as with usual blood pressure (30), contributes more to stroke than cardiac events (12). Current findings extended these findings that the effect of SBP variability on CVD event may be driven primarily by stroke in the diabetic population.
The pathophysiological mechanisms underlying the association between SBP variability and risks of CVD and mortality has not been fully clarified. On one hand, augmented BP variability is associated with endothelial dysfunction and chronic inflammation (36–39) which may speed up atherosclerosis, eventually leading to the development of CVD and increased mortality risk (36, 37). The increased variability in BP could also lead to arterial stiffness, which makes one prone to encounter adverse vascular events (40–42). Other possible mechanisms include coronary artery calcification, left ventricular diastolic dysfunction, and glomerulosclerosis, which were all in the direction of negative clinical outcomes (40, 41, 43, 44). In addition, persistent fluctuations in BP could be a reflection of abnormal autonomic regulation from end-organ damage as has been reported in animal models.(37)
A recent post-hoc analysis of the Valsartan Antihypertensive Long-term Use Evaluation trial (VALUE) on 13,803 hypertensive patients over a mean follow-up period of 4.2 years reported that SBP variability was associated with a significantly higher risk of multiple diseases in patients with age < 68 years than in those with age ≥ 68 years (45). On top of this observation, our findings from subgroup analyses showed a trend that not only within the age range from 45 to 85 years that younger people was more susceptible to the adverse influence of SBP variability but also the impact was stronger on lower usual SBP, Charlson’s index and number of types of anti-hypertensive drug prescribed. The reasons may be that these patients were more likely to have higher SBP variability, as shown in Table 1 and literature (46). Therefore, these groups may tolerate more continual fluctuation than others. As a consequence, these patients may be more vulnerable to SBP variability. Meanwhile, patients with these conditions (e.g. younger and low comorbidity) were more likely with fewer vascular risk factors, and thus may be more sensitive to blood pressure variability. On the contrary, other risk factors in patients with higher age and morbidity may overshadow the detrimental effect of SBP variability. A few studies concluded that poor anti-hypertensive medication adherence and usage of different types of anti-hypertensive drugs may cause patients to be more prone to higher SBP variability and CVD risk (47–50). Although drug adherence information was unavailable in this current study, many previous studies have found no significant difference in SBP variability amongst different levels of drug adherence or types of anti-hypertensive medications used (51–53). Therefore, these factors do not explain the links between SBP variability and the incidence of CVD and all-cause mortality (46, 52). Further studies are required to clarify the mechanism of this relationship.
Strengths and Limitations of this study
Our study has several strengths. Firstly, we included a Type 2 Diabetes cohort with a near ten-year follow-up period, which was the largest and longest study and well powered to demonstrate the associations between SBP variability and outcome events in different subgroups. Secondly, we used appropriate statistical analysis methods to correct for regression dilution bias and conducted sensitivity analyses, which allowed us to make a comprehensive evaluation of the relationship between SBP and diverse clinical outcomes. Multiple imputations were used to impute missing data in order to reduce selection bias. Thirdly, relevant baseline covariates, such as patients’ laboratory results, disease attributes, and treatment modalities, were considered to generate reliable results with the aid of HA’s computerised administrative database.
There were also limitations to our study. Firstly, the study design of a retrospective cohort study can only yield a conclusion about association but not causation. However, a low probability of reverse causation was observed as patients with CVD at baseline were excluded in this study, the results were very similar in the sensitivity analysis when we only included patients with a follow-up period of above one year. Secondly, potential confounding factors related to lifestyles, such as physical activity level and dietary intake, were not assessed in this study. Instead, we have examined the individuals’ anthropometric and clinical parameters, including BMI, HbA1c, and lipid profile, which could alternatively reflect the severity of their diseases and their lifestyle habits. Lastly, the association between SBP variability and increased CVD risk was well demonstrated in this study. However, this could possibly be due to the individual differences amongst our study subjects, compared to the general population and the Type 2 diabetic populations from other Chinese regions. Temporal variations and alterations in non-assessed risk factors or interventions might also induce heterogeneity in the association. Therefore, our findings might not be applicable to other settings.