Arterial hypertension has a high prevalence in the general population and is a major risk factor for cardiovascular diseases (CVD).1,2 Hypertension-mediated organ damage (HMOD), i.e., stroke, left ventricular hypertrophy (LVH), abnormal ankle-brachial index (ABI), and chronic kidney disease (CKD), substantially increases the risk of hypertension-related comorbidities (HRC), including overt CVD, such as coronary artery disease (CAD), heart failure, atrial fibrillation, stroke, peripheral vascular disease (PVD), and CKD or its progression as well as mortality, even in well-controlled hypertension.3–6 Indeed, large observational studies have demonstrated independent associations between hypertension and each of these outcomes. Additionally, controlled clinical trials of antihypertensive drugs have shown impressive reductions in cardiovascular events.7,8

The American Heart Association (AHA) has developed a metric, termed Life's Simple 7 (LS7), for defining and promoting ideal cardiovascular health metrics (CVHM).9 The LS7 includes four modifiable health behaviors (body mass index [BMI]<25kg/m2, physical activity, a healthy diet and nonsmoking) and three modifiable biological factors (untreated total cholesterol<200mg/dL, untreated blood pressure<120/80mmHg and untreated fasting blood glucose<100mg/dL). Achievement of the ideal in these metrics has been associated with improved CVD-free survival and a reduction in healthcare costs.10–12

A priori, the burden of cardiovascular disease risk factors is high among individuals with hypertension. Although hypertensive patients share many risk factors included in the LS7, the relationship between having an ideal risk factor profile in the LS7 plus other community risk factors and HMOD and HRC has not been thoroughly assessed. Thus, considering the increased morbidity and mortality as well as high healthcare costs associated with hypertension, identifying and treating these modifiable health behaviors and health factors could decrease hypertension-related life-threatening complications.

We hypothesized that a poorer cardiovascular health status is related to a higher risk of HMOD and HRC. Thus, we aimed to assess in a population-based cohort of hypertensive patients from an urban primary care center the association between the individual and combined factors that comprise the LS7, determined at baseline, and the presence of HMOD-HRC, recorded at the beginning of the study and during the two years of follow-up. Finally, we also assessed the relationship between ideal CVH plus other community risk factors, such as poverty, alcohol consumption, marital status and educational attainment,13–15 and adverse hypertensive patient outcomes.

A total of 243 hypertensive patients were enrolled in this observational study, of whom 233 were prevalent hypertensive patients and 10 were incident hypertensive subjects. Table 1 shows baseline socio-demographic and clinical characteristics as well as CVHM and community risk factors in the whole study sample and stratified by gender. Overall, the mean age of the participants was 68.5±13 years and most had a low educational level and low family income, and were married or cohabiting. As expected, a family history of CVD and hypertension had a high prevalence as well as preexisting CVD. Given the study participation criteria, a high proportion of the entire cohort received ACEI/ARA II medication for blood pressure control.

Women, who comprised 54% of the study sample, had a higher waist-to-height ratio, BMI, and HDL-cholesterol level. Conversely, diastolic blood pressure and fasting glucose were significantly lower in the females than males. In addition, males had a higher family income, were more often married, had more nocturnal work and a higher alcohol consumption. Finally, CVD was more prevalent in male subjects.

Baseline characteristics according to the Life's Simple 7 factors

The distribution of poor, intermediate and ideal LS7 component scores by gender is presented in Fig. 1. Smoking and blood glucose were the most common ideal health components in both genders, whereas an ideal BMI and healthy dietary pattern were the least common. Due to the study design, no patient had an ideal blood pressure level. Only three patients presented 5 ideal CVHM scores. Lastly, women had numerically higher ideal scores than men in all components except for ideal physical activity that was significantly higher in men (P<0.001).

Fig. 1.

Prevalence of the 7 cardiovascular health metrics by sex. Abbreviations: BMI, body mass index.

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Baseline socio-demographic and clinical characteristics according to the different LS7 component scores are shown in Tables S2 and S3. As compared to current smokers, participants who never smoked were older and had lower triglyceride levels. Compared with inactive patients, individuals with an ideal physical activity were more likely to be male and had a lower BMI and waist-to-height ratio. As compared to individuals with a BMI≥30kg/m2, subjects with a BMI<25kg/m2 had higher HDL-cholesterol levels and a lower prevalence of diabetes as well as lower HbA1c and hs-CRP levels. Interestingly, a significant correlation between hs-CRP and BMI was also observed in the whole population (r=0.282; P=0.0001). Compared to individuals with a poor diet, patients with an ideal diet were older and had a lower diastolic pressure (Table S2). As compared to individuals with poor fasting glucose levels, patients with ideal glucose levels were younger, had a higher educational level and a lower prevalence of CVD and LVH, showed lower triglyceride levels and had a lower albuminuria/creatinine ratio and HbA1c levels as well as higher levels of total-, LDL- and HDL-cholesterol, and were treated with fewer lipid-lowering drugs. Compared to individuals with intermediate or poor cholesterol levels, participants with ideal cholesterol levels were younger and had a lower prevalence of CVD and lower triglyceride levels. Finally, compared to individuals with poor blood pressure, subjects with intermediate blood pressure control had a lower systolic blood pressure (Table S3).

End-organ damage and outcome follow-up

Table 3 displays HMOD-HRC at baseline and during the two-year follow-up. In the current study, we recorded a total of 264 cases of HMOD-HRC in 243 patients, of which 225 were collected in the initial assessment and 39 occurred during the follow-up. The overall crude HMOD-HRC incidence rate was 7.1 per 100-person-years (95% CI 4.1–10.1) in the entire population. In particular, patients experienced the following HMOD-HRC at follow-up: 11 atherosclerotic events (CAD and stroke), 8 CKD or progression, 4 heart failure, 11 atrial fibrillations and 5 de novo LVH. Overall, a total of 58 patients had more than one HMOD-HRC. Additionally, we recorded 9 deaths: 6 attributed to CVD, 2 due to cancer and 1 due to infectious complication. Lastly, 64 patients had any-cause hospitalization at follow-up.

Table 3.

Hypertension-mediated organ damage and hypertension-related comorbidities at baseline and during follow-up.a

	Baseline	Follow-up	Global
Ischemic heart disease, (n)	14.2 (32)	10.3 (4)	13.6 (36)
Stroke (n)	6.7 (15)	18 (7)	8.3 (22)
Peripheral vascular diseaseb (n)	7.1 (16)	–	6.1 (16)
Atrial Fibrillation (n)	22.2 (50)	28.2 (11)	23.1 (61)
Left ventricular hypertrophy (n)	23.6 (53)	12.8 (5)	22 (58)
Heart failure (n)	8 (18)	10.3 (4)	8.3 (22)
CKD (n)	18.2 (41)	20.5 (8)	18.6 (49)
Total	225	39	264

Abbreviations: CKD, chronic kidney disease.

Data are provided as percentage, and in parentheses the total number.

a

Hypertension-mediated organ damage, includes stroke, left ventricular hypertrophy, abnormal ankle-brachial index and CKD; Hypertension-related comorbidities includes stroke, coronary artery disease, heart failure, atrial fibrillation, peripheral vascular disease and CKD or its progression

b

Peripheral vascular disease was defined as intermittent claudication, amputation or revascularization of legs or ankle-brachial index≤0.9.

Table 4 shows comparisons between patients with and without HMOD-HRC. As expected, patients with HMOD-HRC were older, had a longer history of hypertension and a higher proportion had diabetes, as well as a lower GFR and higher albuminuria/creatinine ratio and HbA1c levels. Likewise, they received a higher proportion of lipid-lowering medication because they had a worse lipid profile before inclusion in the study. Consequently, total- and LDL-cholesterol levels were significantly lower in the HMOD-HRC group at baseline assessment. A higher proportion of ideal CVHM scores was observed in patients without HMOD-HRC. Finally, patients with HMOD-HRC had a greater proportion of any-cause hospitalization and all deaths occurred in those with HMOD-HRC.

Table 4.

Characteristics of patients with and without hypertension-mediated organ damage and hypertension-related comorbidities.

Characteristicsc	No HMOD-HRC	HMOD-HRC	P value
	(n=121)	(n=122)
Age (years)	63.5±12.3	73.7±11.7	<0.001
Duration of hypertension (months)	133±82.9	179.7±127	0.001
Body mass index (kg/m2)	30.7±5.7	30.4±4.1	0.627
Waist-to-height ratio	0.63±0.09	0.64±0.07	0.225
Systolic blood pressure (mmHg)	133.2±15.7	137.4±18.4	0.058
Diastolic blood pressure (mmHg)	81.5±8.9	78.4±10.1	0.010
Fasting glucose (mg/dL)	105±37.6	114.8±35.4	0.038
Total cholesterol (mg/dL)	198.8±33.7	175.3±38.1	<0.001
HDL cholesterol (mg/dL)	52±13.5	49.3±14.2	0.131
LDL cholesterol (mg/dL)	117.7±33.1	94.8±33.3	<0.001
Log triglycerides (mg/dL)	2.1±0.2	2.1±0.2	0.329
Diabetes (%)	28.9	54.1	<0.001
Family history of CVDa(%)	55.4	64.8	0.135
Family history of hypertension (%)	81	78.7	0.655
Family history of diabetes (%)	51.2	60.7	0.139
Family history of cancer (%)	63.6	57.4	0.318
Education level (%)			0.093
Primary school or below	65.3	77.9
Middle school	26.4	17.2
High school or university	8.3	4.9
Marital status (%)			0.352
Married or cohabiting	60.3	62.3
Single or religious	7.4	3.3
Divorced or widowed	32.2	34.4
Alcohol consumption (%)			0.250
Low	77.7	74.6
Moderate	15.7	22.1
High	6.6	3.3
Low incomeb(%)	83.5	83.6	0.892
Nocturnal work (%)	5.8	6.6	0.803
eGFR (ml/min/1.73m2)	84.8±15.2	71.9±24.8	<0.001
Log albuminuria/creatinine (mg/g)	1±0.6	1.5±0.7	0.001
HbA1C (%)	5.9±0.9	6.3±1.1	0.004
Log C-reactive protein (mg/dL)	0.3±0.5	0.4±0.4	0.318
ABI	1.2±0.1	1.1±0.2	0.001
Antihypertensive medication (%)
ACEI/ARA II	91.7	93.4	0.624
Calcium antagonists	16.5	43.4	<0.001
Beta-blockers	8.3	31.4	<0.001
Vasodilators	0.8	7.4	0.010
Diuretics	50.4	51.2	0.898
Lipid-lowering medication (%)	41.3	68.9	<0.001
Left ventricular hypertrophy (%)	–	43.4	<0.001
CVDa(%)	–	83.6	<0.001
CKD (%)	–	33.6	<0.001
Hospitalization (%)	14.9	37.7	<0.001
Death (%)	–	7.4	0.002
Cardiovascular health metrics (%)			0.048
0–1	38	44.3
2	28.9	32
3	16.5	18.9
4–5	16.5	4.9

Abbreviations: ABI, ankle-brachial index; ACEI/ARA II, angiotensin-converting enzyme inhibitors or angiotensin receptor antagonists; CKD, chronic kidney disease; CVD, cardiovascular disease; eGFR, estimated glomerular filtration rate. HMOD-HRC, hypertension-mediated organ damage and/or hypertension-related comorbidities.

a

CVD, cardiovascular disease, including myocardial infarction, heart failure, cardiac arrhythmia, stroke, and peripheral vascular disease.

b

Low income: <25,000 €/y.

c

Mean (SD) unless otherwise stated.

Fig. 2A displays a significantly lower prevalence of HMOD plus HRC as the number of ideal CVHM scores increased. Similarly, the prevalence of death and any-cause hospitalization (Fig. 2B), and the composite endpoint that included mortality, all-cause hospitalization and HMOD-HRC were also lower as the number of ideal CVHM scores increased (Fig. 2C).

Fig. 2.

Prevalence of HMOD plus HRC (A), death or any-cause hospitalization (B) and HMOD or HRC, death or all-cause hospitalization (C) according to the number of ideal CVHM. Data are provided as percentage and 95% confidence interval. Abbreviations: CVHM, cardiovascular health metrics. HMOD, hypertension-mediated organ damage; HRC, hypertension-related comorbidities.

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In an age- and sex-adjusted logistic regression analysis, individual CVHM components were not associated with either the presence of HMOD-HRC or the composite endpoint (HMOD-HRC, death or any-cause hospitalization) (Table S4). However, in a fully multivariate logistic regression adjusted for confounders (Table 5), the risk of HMOD-HRC significantly increased as the number of ideal CVHM scores decreased, using subjects with 4 to 5 ideal CVHM scores as the reference (Model 1). Similarly, when the composite endpoint used as dependent variable was death, hospitalization or HMOD-HRC, again subjects with lower CVHM scores had significantly higher odds of the composite endpoint (Model 2).

Table 5.

Multivariate logistic regression for associations between number of ideal cardiovascular health metrics and hypertension-mediated organ damage or hypertension-related comorbidities and mortality and all-cause hospitalization.

	OR	95% CI	P value
Model 1
Ideal cardiovascular health metrics
4–5	1 (Reference)
2–3	3.38	1.03–11.14	0.045
0–1	4.04	1.26–1294	0.019
Model 2
Ideal cardiovascular health metrics
4–5	1 (Reference)
2–3	3.17	1.05–9.51	0.040
0–1	3.43	1.19–9.92	0.023

Adjusted for: Age, sex, duration of hypertension, ankle-brachial index, family history of cardiovascular disease, low income, education level, marital status, alcohol consumption, HbA1c, hs-PCR and hypertensive medication. Model 1, dependent variable used was: hypertension-mediated organ damage (HMOD) or hypertension-related comorbidities (HRC). Model 2, dependent variable used was: HMOD or HRC or death or all-cause hospitalization. (Hosmer–Lemeshow test: Model 1, P=0.114; Model 2, P=0.227).

The main findings of this prospective study are: (1) an overall very low prevalence of ideal CVHM scores was seen in hypertensive patients from an urban population. This finding was mainly driven by unhealthy behaviors, and was similar between men and women; (2) patients with a greater number of ideal CVHM scores had in general a more favorable state of biological and metabolic factors and a graded and reduced risk for adverse outcomes, including HMOD-HRC, mortality and any-cause hospitalizations; and (3) the presence of poorer cumulative ideal CVHM scores (0–1) was associated with unfavorable outcomes in this particular population. These findings suggest that an optimal CVH status could help to reduce the risk of HMOD-HRC. This is one of just a few studies to evaluate thoroughly the association between a combination of healthy lifestyle factors and modifiable biological factors plus other community-risk factors and HMOD-HRC in the setting of hypertensive patients from an urban population.

In 2010, the AHA defined the concept of ideal CVHM, since when an increasing number of studies in the general population have suggested that adherence to various healthy lifestyle factors and biological factors is related to better clinical outcomes.21–28 However, an important number of reports in different populations have found that the prevalence of ideal CVHM was extremely low (<3%).29–35 Consistent with previous studies, we also found that the prevalence of ideal CVHM was very low in hypertensive patients from an urban population. Our patients were classified into groups with 0–1, 2–3 and ≥4 ideal CVHM scores as very few participants had extreme values, either the lower (0) or upper (5) ends of the range. This allowed for a reasonable number of participants in each risk group. No patients presented 6 or 7 ideal CVHM factors and only three patients had 5 ideal CVHM. In fact, given the study design no patient presented an ideal level of blood pressure. This suggests that behavior changes required for compliance with the ideal CVHM are difficult targets to achieve, especially in an aging population. Indeed, our study comprised a mostly elderly population with a high prevalence of other well-known vascular risk factors such as BMI>30kg/m2 (50.2%), diabetes (41.6%) or the presence of CKD (16%), which could have contributed to the scarcity of healthy factors and healthy behaviors in our patients. Thus, recommendations for the general population, included in CVHM, might not apply to an elderly hypertensive population with a high burden of unhealthy behaviors and lifestyles, like in the current study.

Hypertension has a high prevalence in the general population (∼50%) and comprises an important risk factor for HMOD-HRC,36 which in turn leads to unfavorable outcomes. Additionally, many hypertension-related risk factors are included in the LS7. It is expected, therefore, that a poor cardiovascular health status, evaluated through the measurement system of the AHA, which combines 4 health behaviors and 3 vascular risk factors, could contribute to the life-threatening complications of this disease. In fact, the positive assessment of these seven estimates has been associated with a decrease in the risk of CVD and a lower rate of global and cardiovascular mortality in multiple observational studies.10,12,33,37 Individuals with 5–7 ideal CVHM have a much lower rate of cardiovascular entities and cardiovascular mortality, as well as all-cause mortality than those with 0–1 ideal CVHM. Conversely, those with a lower number of ideal CVHM have an increased risk of hypertension-mediated comorbidities and any-cause mortality.38 In the current study, we assessed the relationship between behavior factors plus health factors and HMOD-HRC and unfavorable outcomes in hypertensive patients, mostly aging, in whom multiple well-known vascular risk factors coexist. It is plausible to think, thus, that these patients were less likely to possess beneficial CVH components and consequently possess fewer ideal CVHM, leading to an increased risk of HMOD-HRC and poorer outcomes. In this line, our patients with more healthy LS7 components were more likely to be younger and had a higher number of ideal healthy behaviors and biological factors than those with fewer ideal CVHM. As a result, we observed a lower prevalence of HMOD plus HRC as well as a lesser mortality and any-cause hospitalization as the number of CVHM increased gradually.

Interestingly, hs-CRP levels declined with the increase in the number of CVHM. Additionally, hs-CRP levels were negatively associated with the number of CVHM in our hypertensive population. This is consistent with previous reports.39,40 Hs-CRP may play an important role in the incidence and progression of hypertension, and hs-CRP levels increase if other comorbidities are present in hypertensive patients, such obesity or metabolic syndrome.41,42

Individual ideal CVHM were not associated with the study endpoints. Consistent with our findings, previous reports also found no association with ideal BMI, healthy diet score, desirable cholesterol levels or HbA1c levels, especially when other comorbidities are present.25,43–45 This suggests that ideal CVH components can act collaboratively rather than individually, mainly in patients with multiple comorbidities, including those with hypertension. In other words, the excess risk of HMOD-HRC among hypertensive patients may be explained by the clustering of other cardiovascular risk factors associated with hypertension. Of note, we found that patients with a lower cumulative ideal CVHM score (0–1) had a higher risk for HMOD-HRC. In particular, the risk for HMOD-HRC increased 3–4 times in those patients with ≤3 CVH components compared with individuals with 4–5 ideal CVHM after adjusting for potential confounding factors such as age, sex, duration of hypertension, parental history of CVD, poverty, alcohol consumption, marital status, educational levels, ABI, hs-CRP, HbA1c and hypertensive medication. Likewise, meeting a lower number of cardiovascular health metrics also appeared to be associated with a higher risk for the composite endpoint that included HMOD-HRC, death or all-cause hospitalization. In consonance with our findings, many observational studies provide strong evidence to support the beneficial effects of cumulative ideal CVHM on CVD incidence and mortality in the general population and in patients with other cardiovascular comorbidities, including hypertension.25,27,33,45–47 With this background, preventative efforts to reduce HMOD-HRC should implement strategies promoting a more holistic approach, focusing on a combination of cardiovascular risk factors to achieve optimal vascular health, which may yield greater benefits than would be expected by targeting individual CVH components independently.

Data from the current study were not available to assess whether changes in cardiovascular health actually reduce HMOD-HRC risk, as documented.48 Previous reports have demonstrated in both diabetic and nondiabetic patients that intensive multifactorial interventions aimed at reducing cardiovascular risk factors (achieving lower blood pressure, lipid treatment goals, ACEI use and aspirin use) were associated with a substantially lower incidence of nephropathy, progression of retinopathy and progression of neuropathy as well as a lower CVD rate and all-cause mortality.49,50 Whether these goals could be achieved in hypertensive patients is, at the moment, uncertain and further large prospective observational studies are needed to elucidate this concern.

The findings from the present study should be interpreted within the context of known and potential limitations. Results of our study may not be generalized to other populations with a different context, age, race and lifestyle culture. Our patients were mostly old, had several comorbidities and came from an urban population, which may also have led to selection bias. Indeed, populations in rural areas are unique compared with those in metropolitan areas. Additionally, due to the self-reported nature of the data collected, social desirability bias was also likely. This could also underestimate the impact of CVHM on outcome. Likewise, we studied a relatively small sample of hypertensive patients and perhaps future studies with a larger sample size are needed in this particular population. Finally, the data from this study cannot elucidate whether changes in health measures can actually reduce HMOD-HRC and mortality.

Despite these limitations, our study also has some strengths. We performed an observational study and collection of baseline data was broad and complete using a standardized questionnaire. There were no missing data in the current study. In addition, we followed strictly not only the recommendations of the 7 AHA ideal metrics as previously reported, but also recorded other community risk factors such as family income, nocturnal work, education level or alcohol consumption, which could have a negative influence on CVHM.

The results from the current study using the AHA metrics demonstrate that these measurements are useful for assessing unfavorable outcomes in a high-risk population (hypertensive individuals) to suggest prevention efforts. Consequently, the systematic assessment of healthy behaviors and modifiable biological factors in this particular population could serve as an enhanced tool for clinical practice to counsel patients about those risk factors and to address with community-based hypertension prevention programs. Clinical and public health efforts should be aimed at fomenting the ideal CVHM to further improve prevention of CVD and mortality in hypertensive populations. In this way, early detection of hypertension and adequate blood pressure treatment, control of obesity and overweight, providing ideal diet and advising physical activity, stopping smoking and using modern therapeutic strategies to manage diabetes and dyslipidemia can minimize HMOD-HRC, mainly in elderly hypertensive patients.

In conclusion, our findings show a low prevalence of ideal CVHM in hypertensive patients from an urban population who have a high burden of well-known cardiovascular risk factors. An inverse relationship between CVHM scores and outcomes (HMOD-HRC, death or hospitalizations) was observed. Therefore, intervention studies aimed to increase this score may improve prognosis among community-based hypertensive patients.

This study was supported in part by the Spanish Ministry of Economy and Innovation (grant PI17/02043 and grant ICI21/00042) from the Instituto de Salud Carlos III co-funded by the Fondo Europeo de Desarrollo Regional-FEDER (REDinREN, RD16/0009/0006, RD16/0009/0031 and RICORS, RD21/0005/0012).

The authors declare no conflict of interest.