Diabetic population mortality and cardiovascular risk attributable to hypertension: A decade follow-up from the Tehran Lipid and Glucose Study

Abstract

To determine the extent to which burden of cardiovascular disease (CVD) outcomes among diabetic population is attributable to hypertension. Nine-year follow-up data were secured for 7068 participants aged ≥ 20 years old, free from CVD at baseline. Cox proportional hazards regression was implemented to estimate hazard ratios (HRs) of hypertension. Population-attributable hazard fraction (PAHF) was used to assess proportion of diabetic population hazard of CVD events and mortality attributable to hypertension. In the whole population, irrespective of diabetes or hypertension status, incidence rate (95% CI) of CVD, coronary heart disease (CHD), as well as CVD and all-cause mortality per 1000 person-year were 8.3 (7.6–9.0), 7.1 (6.5–7.8), 1.8 (1.5–2.1) and 3.9 (3.5–4.5), respectively. Among diabetes participants, hypertension was a risk factor for CHD (HR = 1.63, 95% CI 1.15–2.03), CVD (HR = 1.74, 95% CI 1.50–2.41), CVD mortality (HR = 1.65, 95% CI 0.87–3.12) and all-cause mortality (HR = 1.53, 95% CI 0.97–2.42). HRs, however, were not statistically significant for all-cause or CVD mortality. PAHFs (%) of hypertension was 27.5 (95% CI 8.3–42.6) for CHD, 29.6 (95% CI 10.6–44.4) for CVD, 27.9 (95% CI − 17.2 to 55.7) for CVD mortality and 22.6 (95% CI − 5.9 to 43.4) for all-cause mortality. Our study shows that there is an excess risk of CVD in hypertensive patients with diabetes related to inadequate control of blood pressure.

Key Words::

• Cardiovascular disease
• diabetes
• hypertension
• mortality
• population-attributable hazard fraction

Introduction

Previous studies designed to estimate the impact of type 2 diabetes (hereafter diabetes) on cardiovascular diseases (CVD), coronary heart disease (CHD) or mortality (1) have reported the population-attributable risk to vary from 6% to 18% (2,3). We have previously quantified the contribution of diabetes to the burden of CVD, CHD and all-cause mortality among the participants of the Tehran Lipid and Glucose Study (TLGS). We observed that 22%, 21% and 24% of the incident cases of CVD, CHD and all-cause mortality, respectively, would have potentially been avoided had diabetes been eliminated from the population (3). Diabetes frequently coincides with hypertension. This coincidence adds considerably to the diabetes-related overall morbidity and mortality (4). Hypertension is a major contributor to cardiovascular morbidity and mortality in diabetes (5). Patients with both hypertension and diabetes have been shown to be approximately four times as likely to develop CVD as non-diabetic non-hypertensive individuals (6).

Few studies have focused on exploring the extent to which excess risk of CVD and mortality in diabetic individuals is attributable to hypertension (7). We therefore sought to quantify the burden of CVD and all-cause mortality attributable to hypertension among diabetes participants.

Methods and patients

Study population

Detailed descriptions of the TLGS have been reported elsewhere (8); in brief, the TLGS is a large-scale, long-term, community-based prospective study performed on a representative sample of residents of district No. 13 of Tehran, capital of Iran. Age and sex distributions of the population in the district were representative of the overall population of Tehran at the time of the baseline examination. A total of 15,005 residents aged ≥ 3 years were invited by telephone to participate in the TLGS, which has two major components: a cross-sectional prevalence study of non-communicable disease and associated risk factors, implemented between March 1999 and December 2001, and a prospective follow-up study. Data collection is ongoing, designed to continue for at least 20 years, at 3-year intervals. Participants were categorized into the cohort (n = 9375) and intervention groups (n = 5630), the latter to be educated for implementation of lifestyle modifications. For the current study, of those aged ≥ 20 years (n = 10,368), we selected those who participated in the follow-up study until 20 March 2009 (n = 8201). After exclusions (figures may overlap: 524 prevalent CVD, insufficient for ascertaining diabetes: 989 or hypertension: 225), 7068 (3930 women) participants remained eligible, contributing to a 63,626 person-year follow up. At the time of this study, the median follow up time was 9.3 years.

Clinical and laboratory measurements

A trained interviewer collected information using a pretested questionnaire. The information obtained included demographic data, family history of premature CVD, past medical history of CVD and smoking status. Weight was measured, with individuals minimally clothed without shoes, using digital scales (Seca 707: range 0.1–150 kg) and recorded to the nearest 100 g. Height was measured in a standing position without shoes, using tape meter while shoulders were in a normal alignment. Waist circumference (WC) was measured at the umbilical level and that of the hip at the maximum level over light clothing, using an unstretched tape meter, without any pressure to body surface and measurements were recorded to the nearest 0.1 cm (9). After a 15-min rest in the sitting position, two measurements of blood pressure were taken, on the right arm, using a standardized mercury sphygmomanometer (calibrated by the Iranian Institute of Standards and Industrial Researches); the mean of the two measurements was considered the participant's blood pressure.

A blood sample was drawn between 07:00 and 09:00 h from all study participants, after 12–14 h overnight fasting. All the blood analyses were undertaken at the TLGS research laboratory on the day of blood collection. Plasma glucose was measured using an enzymatic colorimetric method with glucose oxidase. Fasting plasma glucose (FPG) measurement was performed for all participants, and the standard 2-h post-challenge plasma glucose (2h-PCPG) test for those not on glucose-lowering drugs. Total cholesterol (TC) was assayed, using the enzymatic colorimetric method with cholesterol esterase and cholesterol oxidase. High-density lipoprotein cholesterol (HDL-C) was measured after precipitation of the apolipoprotein B containing lipoproteins with phosphotungistic acid. Triglycerides (TGs) were assayed using enzymatic colorimetric assay with glycerol phosphate oxidase. Analyses were performed using Pars Azmon kits (Pars Azmon Inc., Tehran, Iran) and a Selectra 2 auto-analyzer (Vital Scientific, Spankeren, Netherlands). All samples were analyzed when internal quality control met the acceptable criteria. The intra and inter-assay coefficients of variation were both < 2.2% for plasma glucose, and 0.5% and 2% for TC, respectively (8).

Outcome measurements

Details of cardiovascular outcomes have been published elsewhere (10). In this ongoing study, every TLGS participant is followed up for any medical event during the previous year, by telephone. They are questioned by a trained nurse regarding any medical conditions or whether a related event have occurred, a trained physician collects complementary data during a home visit and/or a visit to the respective hospital to collect data from the participants medical files. In the case of mortality, data are collected from the hospital or the death certificate by an authorized local physician. Collected data are evaluated by an outcome committee consisting of a principal investigator, an internist, an endocrinologist, a cardiologist, an epidemiologist and the physician who collects the outcome data. Other experts are invited for evaluation of non-communicable disorders, as needed. A specific outcome for each event is assigned according to International Statistical Classification of Diseases and Related Health Problems criteria, 10th Revision, and American Heart Association classification for cardiovascular events (8,11,12). CHD includes cases of definite myocardial infarction (MI) diagnosed by electrocardiogram (ECG) and biomarkers, probable MI (positive ECG findings plus cardiac symptoms or signs and biomarkers showing negative or equivocal results), unstable angina pectoris (new cardiac symptoms or changing symptom patterns and positive ECG findings with normal biomarkers), angiographically proven CHD and CHD death. CVD is specified as a composite measure of any CHD events, stroke or cerebrovascular death.

Definition of terms

Current smoker was defined as a person who smokes cigarettes daily or occasionally. A previous history of CVD reflected any prior diagnosis of CVD by a physician. The family history of CVD was obtained by asking participants whether any member in their immediate family (first-degree relatives) had experienced a fatal or non-fatal MI, stroke or sudden cardiac arrest. The event was considered premature if it occurred before the age of 55 years in male relatives and before 65 in female relatives (13). In accordance with the definition provided by American Diabetes Association, participants were classified as having diabetes at the baseline if they met at least one of these criteria: FPG ≥ 7 mmol/l, or 2h-PCPG ≥ 11.1 mmol/l or taking anti-diabetic medication. The diagnosis of hypertension was made in participants who self-reported anti-hypertensive drug usage or in those with the average of the two diastolic blood pressure measurements ≥ 90 mmHg or with average of the two systolic blood pressure measurements was ≥ 140 mmHg (14). In contrast to previous studies (7), we intentionally used the same criteria for definition of hypertension among individuals with and without diabetes to avoid a priori presumption regarding impact of hypertension on endpoints among individuals with and without diabetes. Otherwise, we might have already rejected the null hypothesis of the study that hazard ratio_(diabetes) = hazard ratio_{(no diabetes)}, before testing it.

Statistics analysis

Findings on covariate variables are expressed as means (SD) or percentages for continuously distributed and categorical variables, respectively. We tested for difference between hypertensive and normotensive individuals using the t-test and χ² for continuously and categorically distributed variable, respectively. Incidence rates were compared with log-rank test.

In the analysis of outcomes (CVD, CHD, and all-cause and CVD mortality), hypertension was assessed using Cox proportional hazard regression model. Survival time was the time from start of the follow-up period to the date of the first incident CVD event or death (failure). The censoring time of an individual was the time from entry into the study to loss to follow-up or the end of the study (20 March 2009), whichever happened first. Censored observation meant the individuals refused to participate further in the study (were lost to follow-up), died (from non-CVD causes), when death was not the study outcome (competing risk) or continued until 20 March 2009 when the study was ended (administrative censoring). Nested models incorporating hypertension included sequentially more covariates including age, sex, smoking, family history of premature CVD, waist circumference, triglycerides, total and HDL-cholesterol, and FPG. We also examined if direction or magnitude of the association of hypertension with different endpoints were modified by sex, age or lifestyle modification intervention measure. As such, the interaction term for sex × hypertension, age× hypertension and intervention× hypertension were introduced into regression models. The significance interactions were examined by likelihood ratio test. Recently, Chen et al. (15) and Samuelsen & Eide (16) have proposed a definition for population-attributable fraction (PAF) for cohort studies with time-to-event, i.e. Population-attributable Hazard Fraction (PAHF). The PAHF is defined based on the effect of the hypothetical risk factor modification to the low-risk level; it is estimated at the instantaneous time point t:

where p is proportion exposed at time t and HR(t) = h2(t)/h1(t) denotes instantaneous hazard ratio at time t (15,16). This measure describes the approximate proportion of events that could be avoided by the risk factor modification in a short time interval [t, t+Δt], where t→0. We used the proportion exposed at baseline, p = p(0) as suggested (16,17). As such, the formula corresponds to the traditional PAF (18) formula, as it was presented in the literature by Levin (19).

Wald tests of the linear hypotheses concerning the Cox regression models coefficients (paired homogeneity test) were performed to test the null hypotheses that the hazard ratios (effect size) for diabetes were equal to those for hypertension.

We set the statistical significance level at a two-tailed type I error of 0.05. All statistical analyses were performed using STATA version 11 (STATA, College Station, Texas USA) and SAS 9.2 (SAS Institute Inc., Cary, NC, USA).

Medical ethics

We certify that all applicable institutional and governmental regulations concerning the ethical use of human volunteers were followed during this research. Informed written consent was obtained from all participants and the Ethical Committee of Research Institute for Endocrine Sciences approved this study.

Results

Among 770 participants with diabetes, 411 (53%) had hypertension at baseline, whereas among 6298 participants without diabetes 1317 (21%) had hypertension at baseline. Compared with normotensive diabetic individuals at baseline, hypertensive diabetic individuals were older, heavier, had higher levels of systolic and diastolic blood pressure, waist circumference, 2h-PCPG, and total and HDL-cholesterol (Table I).

Table I. Baseline characteristics of individuals at baseline.

Variables at baseline	No diabetes mellitus			Diabetes mellitus
	Without hypertension (n = 4981)	With hypertension (n = 1317)	p	Without hypertension (n = 359)	With hypertension (n = 411)	p
Age (years)	38.42	51.28	< 0.001	51.70	57.54	< 0.001
Male	2182 (0.44)	502 (0.38)	< 0.001	165 (0.46)	144 (0.35)	0.002
Family history of premature CVD	389 (0.08)	151 (0.11)	< 0.001	37 (0.10)	49 (0.12)	0.487
Current smoking	730 (0.15)	95 (0.07)	< 0.001	51 (0.14)	25 (0.06)	< 0.001
Intervention	1868 (0.38)	508 (0.39)	0.476	149 (0.42)	167 (0.41)	0.708
Systolic blood pressure (mmHg)	112.18	138.51	< 0.001	119.82	148.56	< 0.001
Diastolic blood pressure (mmHg)	74.11	88.72	< 0.001	76.50	88.84	< 0.001
Weight (kg)	69.43	73.57	< 0.001	73.05	74.98	0.039
Waist (cm)	85.55	93.60	< 0.001	94.57	98.67	< 0.001
Height (cm)	163.22	159.98	< 0.001	160.98	158.45	< 0.001
Fasting plasma glucose (mmol/l)	4.93	5.16	< 0.001	9.15	8.98	< 0.001
PCPG (mmol/l)	5.70	6.60	< 0.001	14.71	15.58	< 0.001
Triglycerides (mmol/l)	0.39	0.65	< 0.001	0.88	0.92	0.764
Total cholesterol (mmol/l)	5.22	5.83	< 0.001	5.87	6.28	< 0.001
HDL-cholesterol (mmol/l)	1.10	1.11	0.290	1.03	1.08	0.006

Categorically distributed variables are reported as frequency (percentage) and continuously distributed variables as mean (SD). CVD, cardiovascular disease; HDL, high-density lipoprotein; PCPG, 2-h post-challenge plasma glucose.

Incidence rates (95% CI) of CVD, CHD, and CVD and all-cause mortality per 1000 person-years were 8.3 (7.6–9.0), 7.1 (6.5–7.8), 1.8 (1.5–2.1) and 3.9 (3.5–4.5), respectively. The corresponding figures were 30.6 (26.6–35.3), 26.7 (23.0–31.0), 7.9 (6.0–10.3) and 14.7 (12.1–17.9) among individuals with diabetes, and 5.8 (5.2–6.4), 4.9 (4.4–5.6), 1.1 (0.8–1.4) and 2.7 (2.3–3.1) among individuals without diabetes.

As presented in Table II, hypertensive patients with diabetes were significantly more likely to experience different outcomes compared with normotensive patients with diabetes (p-values < 0.001).

Table II. Incidence rates (per 1000 person-year) of different endpoints among individuals with diabetes mellitus who had no history of previous cardiovascular disease.

Outcome	Normotensive	Hypertensive	p-value
Coronary heart disease	18.2 (04.0–23.7)	34.5 (28.7–41.4)	< 0.001
Cardiovascular disease	20.3 (15.8–26.0)	40.3 (34.0–47.8)	< 0.001
Cardiovascular mortality	5.0 (3.0–8.1)	10.5 (7.6–14.4)	0.009
All-cause mortality	10.3 (7.3–14.5)	18.6 (14.7–23.6)	0.004

Among individuals without diabetes at baseline, increased risk of incident CHD, CVD and CVD and all-cause mortality resisted all adjustments. Among patients with diabetes at baseline, hypertension was associated with an increased risk of CHD and CVD, but not CVD mortality or all-cause mortality. Wide confidence intervals indicated that study sample might have not had enough power to detect the mortality risk associated with hypertension among diabetic participants. The fraction of diabetic population hazards of different endpoints attributable to hypertension ranged from 23% to 30%; the corresponding figures for non-diabetic population were from 24% to 45%.

Multivariate regression models of the proportional hazard survival analysis confirmed that hypertension was a risk factor for CHD (HR = 1.81, 95% CI 1.46–2.23), CVD (HR = 1.92, 95% CI 1.57–2.33), CVD mortality (HR = 2.36, 95% CI 2.53–3.33) and all-cause mortality (HR = 1.86, 95% CI 1.40–2.46), independent of diabetes. Similarly diabetes was a risk factor for CHD (HR = 1.79, 95% CI 1.37–2.33), CVD (HR = 1.75, 95% CI 1.37–2.24), CVD mortality (HR = 2.57, 95% CI 1.57–4.21) and all-cause mortality (HR = 1.99, 95% CI 1.39–2.85) independent of hypertension. A paired homogeneity test revealed that the magnitude of excess hazards of CHD, CVD, CVD mortality and all-cause mortality due to diabetes were not different from those of hypertension (p-values > 0.5). PAHFs of diabetes for CHD (PAHF 17.9, 95% CI 9.4–25.6), CVD (PAHF 17.6, 95% CI 9.4–25.0), CVD mortality (PAHF 30.3, 95% CI 14.7–43.1) and all-cause mortality (PAHF 21.4, 95% CI 10.3–31.0) were all much lower than PAHFs of hypertension for CHD (PAHF 25.8, 95% CI 16.1–34.4), CVD (PAHF 28.9, 95% CI 19.8–36.8), CVD mortality (PAHF 39.1, 95% CI 18.7–54.3) and all-cause mortality (PAHF 27.7, 95% CI 14.8–38.7). This could have possibly been attributable to the lower prevalence of diabetes (12.4%) than hypertension (25.5%) in the TLGS population.

As Table III presents, PAHFs of hypertension for CVD and CHD among participants with diabetes were all statistically significant and consistently greater than the corresponding PAHFs among participants without diabetes. The opposite was true for death from all causes or from CVD; PAHFs were smaller among participants with diabetes than among participants without diabetes.

Table III. Age-adjusted hazard ratio for hypertension as a risk factor for cardiovascular disease and mortality and population-attributable hazard fraction.

	No diabetes mellitus				Diabetes mellitus
	HR (95% CI)	p-value	PAHF (95% CI)	p-value	HR (95% CI)	p-value	PAHF (95% CI)	p-value
Coronary heart disease
Model 1	2.01 (1.56–2.60)	< 0.001	25.6 (15.6–34.4)	< 0.001	1.75 (1.25–2.43)	= 0.001	29.0 (11.1–43.6)	= 0.003
Model 2	1.85 (1.43–2.41)	< 0.001	23.3 (12.8–32.6)	< 0.001	1.74 (1.24–2.44)	= 0.001	29.2 (10.3–43.8)	= 0.004
Model 3	1.88 (1.45–2.45)	< 0.001	23.9 (13.3–33.2)	< 0.001	1.58 (1.12–2.34)	= 0.009	26.2 (6.6–41.6)	= 0.011
Model 4	1.90 (1.46–2.47)	< 0.001	24.1 (13.5–33.4)	< 0.001	1.63 (1.15–2.03)	= 0.006	27.5 (8.3–42.6)	= 0.007
Cardiovascular disease
Model 1	2.10 (1.66–2.66)	< 0.001	28.1 (18.7–36.3)	< 0.001	1.81 (1.32–2.47)	< 0.001	31.3 (14.4–44.8)	= 0.001
Model 2	1.95 (1.53–2.49)	< 0.001	25.9 (16.1–34.6)	< 0.001	1.83 (1.33–2.53)	< 0.001	32.0 (14.3–45.9)	= 0.001
Model 3	1.99 (1.56–2.53)	< 0.001	26.5 (16.6–35.1)	< 0.001	1.67 (1.20–2.31)	= 0.002	28.0 (8.8–43.2)	= 0.007
Model 4	1.99 (1.56–2.54)	< 0.001	26.6 (16.7–3.53)	< 0.001	1.74 (1.50–2.41)	= 0.001	29.6 (10.6–44.4)	= 0.004
Cardiovascular mortality
Model 1	2.69 (1.54–4.68)	< 0.001	39.7 (17.0–56.1)	= 0.002	1.67 (0.91–3.20)	= 0.097	28.3 (–12.1–54.2)	= 0.144
Model 2	3.10 (1.7–5.59)	< 0.001	43.3 (20.4–59.6)	= 0.001	1.73 (0.92–1.22)	= 0.087	29.8 (–13.3–56.5)	= 0.147
Model 3	3.12 (1.73–5.65)	< 0.001	26.4 (16.6–35.1)	< 0.001	1.59 (0.84–3.00)	= 0.156	26.2 (–20.1–54.6)	= 0.222
Model 4	3.33 (1.83–6.04)	< 0.001	44.9 (24.3–61.0)	< 0.001	1.65 (0.87–3.12)	= 0.128	27.9 (–17.2–55.7)	= 0.187
All-cause mortality
Model 1	1.69 (1.21–2.67)	< 0.001	22.8 (7.8–35.4)	= 0.004	1.29 (0.84–1.98)	= 0.248	14.9 (–15.2–37.2)	= 0.296
Model 2	2.04 (1.43–2.92)	< 0.001	28.5 (14.1–40.4)	< 0.001	1.41 (0.90–2.21)	= 0.132	19.0 (–9.9–40.3)	= 0.176
Model 3	2.08 (1.45–2.98)	< 0.001	28.9 (14.3–41.0)	< 0.001	1.42 (0.90–2.25)	= 0.130	19.2 (–10.3–40.7)	= 0.179
Model 4	2.13 (1.48–3.06)	< 0.001	29.6 (15.0–41.7)	< 0.001	1.53 (0.97–2.42)	= 0.070	22.6 (–5.9–43.4)	= 0.109

HR, hazard ratio; PAHF, population-attributable hazard fraction. where p(t) is the proportion exposed to hypertension at time t. We used proportion exposed at baseline, p = p(0). Model 1 was adjusted for age and sex. Model 2 was adjusted for age, sex, smoking, family history of premature cardiovascular disease and waist circumference. Model 3 was adjusted for age, sex, smoking, family history of premature cardiovascular disease and waist circumference, triglycerides, high-density lipoprotein and total cholesterol. Model 4 was adjusted for age, sex, smoking, family history of premature cardiovascular disease and waist circumference, triglycerides, high-density lipoprotein and total cholesterol and fasting plasma glucose.

The effects of hypertension on different endpoints were not modified by the effects of age or sex (p-values for the likelihood ratio χ² test > 0.2). Lifestyle modification intervention measures neither contributed to the risk of CVD, CHD, or all-cause or CVD mortality nor modified the effects of hypertension or diabetes on endpoints (p-values for the likelihood ratio χ² test > 0.2).

Discussion

We observed that hypertension is a major contributor to the hazard of CVD and mortality among participants of the TLGS who had diabetes. Nearly 57% of patients with diabetes were involved with hypertension at baseline. We demonstrated that a substantial fraction of hazards of CVD (CHD) in a population with diabetes could be attributable to hypertension (PAHF˜25%). However, PAHFs of relatively similar magnitude for mortality (from all-cause or CVD) did not achieve statistical significance.

Among participants of the Framingham original and offspring cohorts, diabetes has been observed to be associated with an increased risk of CVD and mortality, with much of the excess risk being attributable to coexistent hypertension (7).

Reports from clinical trials published over the past few decades provided clear evidences that broad-based treatment of established CVD risk factors among patients with diabetes who already have clinical CVD can improve the event-free survival rate (20). However, data regarding the primary prevention of CVD among patients with diabetes are relatively scares. This is a critical issue, since patients with diabetes are more than twice as likely to develop CVD, CHD and all-cause mortality as the general population (3). Increasing evidences, accrued in the past decades, indicate that by lowering plasma glucose levels there might not be as much beneficial effect on the macrovascular complications of diabetes as on microvascular complications (21). Furthermore, diabetes also worsens the course and aggravates the early and late outcomes in acute coronary syndromes; regardless of the severity of clinical presentation, patients who have diabetes and coronary events experience increased rates of MI and death. Yet, patients with diabetes have an adverse long-term prognosis after MI, including increased rates of reinfarction, congestive heart failure and death (22–26). In developed countries, 80% of patients with diabetes will develop and possibly die of CVD; enormous societal costs are imposed, and patients with diabetes’ longer and healthier lives are hampered (27,28). The traditional therapeutic approaches emphasize glycemic control, which limits microvascular disease but has not generally been agreed upon to have established benefit in macrovascular disease (22). In the light of recent advances in the treatment of diabetes, the American Diabetes Association has made a scientific statement that “if implemented soon after the diagnosis of diabetes, lowering hemoglobin A1C (HbA_1C) to below or around 7% is associated with long-term reduction in macrovascular disease” (29). However, intensive glycemic control does not seem to reduce all-cause mortality in patients with diabetes. Data available from randomized clinical trials continues to be insufficient to prove or refute a relative risk reduction for cardiovascular mortality or morbidity. Moreover, intensive glycemic control increases the relative risk of severe hypoglycemia by 30% (30). The optimum mechanism, speed and extent of HbA_1c reduction might be different in differing populations (31). Therefore, controlling other CVD risk factors that accompany the vast majority of patients with diabetes, such as hypertension, as an attempt to reduce CVD events are attracting attention (32–34).

By contrast with the management of hyperglycemia, several studies have found that aggressive management of hypertension decreases the risk of macrovascular disease and death in persons with diabetes (35). Treatment of hypertension among patients with diabetes has been shown to reduce CVD by 69%, all-cause mortality by 55% and CVD mortality by 76%. Reductions in mortality and CVD were significantly larger among the participants with diabetes than among the those without diabetes (36). Our study has provided a basis for future studies to investigate the degree to which mortality and morbidity among patients with diabetes could be avoided by elimination of hypertension.

PAHFs of hypertension for all-cause or CVD mortality in the current analysis did not reach statistical significance. While lack of statistical power is an explanation, some other potential explanation may deserve mentioning. The proportion of death constituted by CVD in developing countries is not as large as in developed countries (37). The most important cause of mortality in patients with diabetes in developing countries continues to be infections and microvascular complications of diabetes (38); conversely, in the developed world, diabetic microvascular complications are uncommon as causes of death in patients with diabetes (39).

The TLGS is partly an intervention study to improve lifestyle (8,40). We have shown previously that the rate of smoking cessation, attending leisure-time physical activity, losing at least 5% weight, as well as mean blood pressure measures and glycemia could be improved with lifestyle modification interventions (41). In the current study, lifestyle-modification interventions were not observed to modify the effects of hypertension or diabetes on any of the endpoints under the investigation. Whether the same lifestyle modification counseling can confer different degrees of benefits to different subgroups of participants is appealing in that it can pave the way for focused or targeted approaches. In an ancillary analysis (data not shown), we estimated the multivariate-adjusted hazard ratio for CVD of lifestyle modification intervention separately for participants with hypertension/without diabetes in comparison with those with diabetes/without hypertension. We observed that having diabetes/without hypertension vs having hypertension/without diabetes did not modify the effectiveness of the lifestyle modification counseling. However, in a subgroup of participants older than 40 years of age, we observed that although the lifestyle modification intervention did not reduce the CVD risk among participants with hypertension/without diabetes (HR = 1.04, 95% CI 0.79–1.35; p = 0.800), it did reduce the CVD risk among participants with diabetes/ without hypertension (HR = 0.63, 95% CI 0.38–1.05; p = 0.076). Inasmuch as the TLGS has not been specifically designed to find the effectiveness of the intervention measures among subgroups, we might have not had sufficient statistical power to capture the statistical significance of the difference observed (likelihood ratio ÷^{2 =} 0.42, p for interaction = 0.515). On the other hand, subgroup analyses are always subjected to multiplicity of inference and inflation of quixotic bias (the type I error) (42–44). Thus far, we have not observed any evidence supporting the notion that lifestyle modification interventions are more likely to reduce CVD risk (or mortality) among patients with diabetes than among patients with hypertension (40).

The strengths of the present study lie in its prospective nature, use of a large community-based cohort of men and women, accurate and valid data on risk factors at baseline, and continuous surveillance of mortality and CVD events based on standard criteria. The PAHFs reported herein represent the fraction of CVD hazard or mortality in a population with diabetes that is attributable to the causal effects of hypertension. It can help communicate such a risk to public health professionals, administrators, policy-makers and the lay public (45–48). Some limitations to our study merit mentioning. First, our sample size might have not had sufficient statistical power to capture risk among patients with diabetes. Furthermore, the small number of incident events precluded stratification of analyses by age. Second, the diagnosis of hypertension was based on a mean of two readings at the same baseline visit. Although this is often the case in screening studies, it might have inflated the prevalence rate of hypertension. Third, being the best method available in Iran, careful telephone interview or ascertainment of hospital medical records might have been less accurate than a register-based follow-up, and could provide a risk estimate less precise, since some participants who became lost to follow-up might have developed an event or died. As such, we might have underestimated the incidence rates. Finally, the population studied was of Persian ancestry; our results, thus, could not be readily extrapolated to other populations.

Conclusion

Our study indicated that a considerable fraction of excess risk of CVD and mortality in patients with diabetes is attributable to inadequate control of blood pressure.

Competing interests

The authors declare that they have no competing interests.