Are There Height-Dependent Differences in Subclinical Vascular Disease in Hypertensive Patients?



The aim of the study was to determine whether there are differences in subclinical vascular disease (SVD) in hypertensive patients in relation to height. A total of 922 hypertensive, newly diagnosed, treatment-naive patients were included. Physical examination was conducted, with renal function, electrocardiography, and retinography. Patients were distributed according to quartiles of height and sex. Multivariate analysis adjusted for age, sex, and body mass index showed an association between height above the mean and fasting glucose (odds ratio [OR], 1.04; 95% confidence interval [CI], 1.02–1.06), high-density lipoprotein cholesterol (OR, 0.96; CI, 0.92–0.99), triglycerides (OR, 1.07; CI, 1.01–1.15), and left ventricular hypertrophy (LVH) (OR, 1.57; CI, 1.10–2.24). The authors found an inverse association between arteriole-to-venule ratio and height above the mean (OR, 0.97; CI, 0.94–0.99). There are differences in the SVD of hypertensive patients in relation to height. Tall stature is associated with LVH while short stature is associated with increased microvascular involvement. Detection of SVD in hypertensive patients should consider the height.

Height attained in adulthood is a phenotypic expression of genetic load that is influenced by various environmental and socioeconomic variables in the perinatal period and during the growth period.[1] In the general population, a number of epidemiological studies have shown increased total and cardiovascular (CV) mortality in patients of smaller stature compared with their reference population.[2-11] A recent meta-analysis concluded that people with short stature have higher total and CV mortality and a 50% greater chance of developing ischemic heart disease,[12] although there are studies that have found no association between final adult height and total or CV mortality.[11, 13-15] Several mechanisms have been suggested to explain this fact: (1) vascular damage caused by perinatal exposure to poor nutrition or environmental pollutants such as tobacco, (2) socioeconomic deprivation leading to lower quality food and a higher prevalence of toxic habits, and (3) genetic conditioning.[16] Differences have been reported regarding height and type of CV disease. The inverse relationship seems clearer in the case of ischemic heart disease than in stroke[9, 12, 17] although some studies show different results.[11, 15] It seems that patients with greater adult height have higher blood pressure (BP),[18] although this aspect is subject to debate.[16] No association is reported between height and subclinical vascular disease (SVD) in hypertensive patients. The main objective of this study was to determine in newly diagnosed treatment-naive patients whether the prevalence of various types of SVD varies according to adult height.

Patients and Method

Study Population

The Spanish investigation Assessment of BP Self-Monitoring in the Diagnosis of Isolated Clinical Hypertension (VAMPAHICA) study has been described previously.[19] In brief, it was a multicenter prospective study involving 14 primary care centers in the Healthcare Region of Girona (Catalonia). All patients in this study had a recent diagnosis of hypertension, were treatment-naïve, and were recruited from 2003 to 2006.

Study Design

Patients who met the following criteria were included: age 15 to 75 years; hypertension, defined as the average of two BP readings, separated by 2 minutes, taken over 3 different days, with results of ≥140 mm Hg and/or ≥90 mm Hg; recent diagnosis and never treated for hypertension; and provided correct self-BP measurement (SBPM). Exclusion criteria were the following: obvious inability, in the healthcare professional's opinion, to perform SBPM; diabetes mellitus; secondary hypertension; previous CV disease; kidney failure (serum creatinine >2 mg/dL); liver failure; alcoholism or severe psychiatric disease; endocrine or severe haematological disease; or other severe diseases or limitations (eg, the inability to travel to the doctor's office, estimated survival time limited), which, in the physician's opinion, were reason for exclusion. All patients signed the consent form at the time they were informed of their inclusion in the diagnostic study, and the study protocols were approved by the independent ethics committee at the Health Care Institute.

Determination of Clinic BP

Hypertension was diagnosed based on measurements taken by the nurses. After sitting down for 5 minutes, 2 measurements were taken at an interval of 2 minutes. This was performed on 3 different days (6 measurements in total). If the difference between the readings on the same day was >5 mm Hg, a third measurement was taken to obtain the mean. Clinic BP (CBP) value was assessed as the mean of all the readings taken. All the measurements were performed using OMRON 705 CP and OMRON 705 IT monitors (HEM 759 E2 and HEM 759 E, Tokyo, Japan) under the standard conditions that are recommended by international organizations,[20] with an armband adapted to the circumference of each patient's arm.

SBPM Procedure

Each participant was instructed by an expert nurse of the steps required to obtain adequate readings, confirming twice that the process was carried out correctly in their presence. All the measurements were performed using OMRON 705 CP and OMRON 705 IT monitors (HEM 759 E2 and HEM 759 E). It was conducted with an armband adapted to the circumference of each patient's arm. Patients were given written instructions. During 3 working days, 2 readings were performed in the morning before breakfast and 2 more at night before dinner. In both cases, the readings were performed at an interval of 2 minutes and after sitting down for 5 minutes. Patients wrote down the readings in a form they were given for this purpose. In order to check the reliability of the data they also provided the readings obtained through the monitor. The first day's readings were discarded for calculations.

Data Collection

A case report form specially designed for the study was used. The variables included in this study were age, sex, height, weight, body mass index, tobacco consumption, systolic and diastolic CBP, systolic and diastolic SBPM, total cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides, fasting blood glucose, left ventricular hypertrophy (LVH), urinary albumin excretion rate (UAER), glomerular filtration rate (GFR) according to Modification of Diet in Renal Disease formula,[21] advanced lesions of fundus oculi (FO), and arteriole-to-venule ratio (AVR). The latter was in a subgroup of 166 patients selected on the basis of image quality, based primarily on the brightness of the fundus evaluated by an investigator who was unaware of patients' clinical data.

Initial Study

At the start of the study (2003–2006) and at 1 year, the medical charts of all hypertensive participants were reviewed. All included patients underwent a physical examination, fasting blood and urine analysis, standard 12-lead electrocardiography, and retinography. A morning urine sample was analyzed for the detection of UAER. If positive, the presence of leukocytes, red blood cells, or nitrites was ruled out using a reactive strip. Once the cause of the anomaly had been examined and treated, an early morning urine test to determine the albumin/creatinine ratio was repeated 15 days later. Two of 3 consecutive test results were required to be positive in order to make the diagnosis of high UAER. Smokers were defined as patients who had consumed tobacco in the last 6 months. Any of the following alterations were considered SVD: LVH by electrocardiographic (ECG) criteria (Cornell criteria, modified by Dalfo and colleagues,[22] or Sokolow-Lyon criteria) or presence of high UAER defined using the European Society of Hypertension for normal values.[20] Advanced FO lesions, such as soft exudates or hard exudates and hemorrhages were also included.


Two retinographies centered at the macula, one per eye, were taken using a retinograph equipped with a nonmydriatic digital camera (CANON CR6-45NM, Camera EOS D30). All these images were evaluated by an experienced physician unaware of the patient's details (only advanced lesions of ocular fundus). In 166 patients, the images were processed by the SIRIUS[23] application in order to obtain the AVR automatically. To this end, the SIRIUS AVR monitoring service described previously was used.24 A baseline AVR from a reference image can be computed semiautomatically or automatically. To this end, the vessel segments were detected and measured in several circumferences concentric to the optic disc.

The AVR measurement can be computed as the ratio between the means or medians of arteriolar and venular vessel widths. In this study, for each eye, the AVR values were computed automatically using the median. The baseline AVR values were obtained as the average of the two eye measurements.

Data Analysis

First, we did an exhaustive descriptive analysis of the baseline values for all the variables. The difference between the means (in quantitative variables) and the proportions (in qualitative variables) of the variables of interest was performed using the Scheffe test (comparison of means) and chi-square tests (comparison of proportions). In the latter case, when the expected cell count was <5, we applied the Fisher exact test. We then estimated the association between several clinical features and vascular problems as well as the AVR and that the height was greater than the median of the height of the individuals of the same sex by means of generalized linear models (GLMs). When the response variable (either clinical features or vascular problems) was continuous, we used GLMs with Gaussian link (ie, linear model) and when the response variable was dichotomous (occurrence or not of the response), we used GLMs with binomial link (ie, logistic regression).


Baseline Characteristics of Patients

The study recruited 922 patients (45.2 women) with a mean age of 59.8 years (standard deviation, 10.0). Table 1 shows the characteristics of the patients included in the study. A total of 21.6% of patients had LVH, 7.8% had advanced FO lesions, 4.9% had a GFR <60 mL/min/1.73 m2, and 2.4% had a high UAER. The subgroup used to study the AVR showed higher systolic and diastolic CBP than the cohort (154.0 mm Hg vs 150.3 mm Hg [P<.0005] and 91.0 mm Hg vs 88.7 mm Hg [P<.005], respectively). There were significant differences in systolic and diastolic SBPM (141.3 mm Hg vs 137.6 mm Hg [P<.002] and 85.1 mm Hg vs 83.3 mm Hg [P<.05], respectively). No differences between the two groups were found in any of the other variables in Table 1.

Table 1. Baseline Characteristics of Patients
  1. Abbreviations: CBP, clinic blood pressure; FO, fundus oculi; GFR, glomerular filtration rate by Modification of Diet in Renal Disease equation; HDL, high-density lipoprotein; LVH, left ventricular hypertrophy; SBPM, self–blood pressure measurement; SD, standard deviation: UAER, urinary albumin excretion rate (>21 mg/g in men, >32 mg/g in women).

Men, No. (%)505 (54.7)
Women, No. (%)417 (45.2)
Age (SD), y59.8 (10.0)
CBP, mean (SD), mm Hg
Systolic150.3 (12.7)
Diastolic88.7 (9.1)
SBPM, mean (SD), mm Hg
Systolic137.6 (13.7)
Diastolic83.3 (9.3)
Tobacco, No. (%)173 (18.7)
Fasting glucose, mean (SD), mg/dL89.5 (12.3)
Total cholesterol, mean (SD), mg/dL212.5 (35.7)
HDL cholesterol, mean (SD), mg/dL60.01 (23.8)
Triglycerides, mean (SD), mg/dL124.5 (79.9)
High UAER, No. (%)22 (2.4)
LVH, No. (%)199 (21.6)
Advanced FO lesions, No. (%)72 (7.8)
GFR <60 mL/min/1.73 m2, No. (%)45 (4.9)

Stratification by Sex and Height

Table 2 shows patient variables stratified by sex and height quartiles. For both sexes, there was a gradient in height quartiles based on the age of patients, so that older patients were in the lowest height quartile (Q) while younger patients were in the taller quartile. There were differences in the prevalence of LVH (LVH prevalence higher in Q1 and Q4 and lower in Q2 and Q3), high UAER (higher prevalence in middle quartiles), and advanced ocular fundus lesions (most prevalent in Q1 and Q4 height quartiles and lower prevalence in Q3) based on the size quartile in both men and women. In women, additional differences were observed in tobacco consumption (greater consumption in the higher height quartiles), total cholesterol, and GFR <60 mL/min/1.73 m2 (higher prevalence of renal impairment in the lower height quartiles).

Table 2. Clinical Characteristics of Patients Stratified by Sex and Height Quartiles, Adjusted for Weight
 Q1Q2Q3Q4P Value
Age (SD), y66.1 (8.6)64.8 (9.0)60.2 (12.1)54.7 (11.9)<.05
CBP, mm Hg (SD)
Systolic151.5 (8.4)153.6 (12.9)149.1 (11.1)150.6 (13.7)NS
Diastolic87.6 (11.2)90.1 (9.09)89.4 (8.02)89.8 (9.4)NS
SBPM, mm Hg (SD)
Systolic138.8 (10.3)142.0 (13.3)136.7 (11.6)139.7 (13.8)<.05
Diastolic80.0 (11.9)90.1 (9.4)84.4 (8.6)86.1 (9.5)NS
Tobacco, No. (%)29 (22.8)28 (22.2)36 (28.6)34 (27.20)NS
Fasting glucose (SD), mg/dL90.2 (16.5)87.9 (11.4)91.3 (10.1)91.7 (13.8)NS
Total cholesterol (SD), mg/dL212.5 (23.3)210.4 (36.0)209.0 (33.3)210.9 (35.0)NS
HDL cholesterol (SD), mg/dL55.5 (10.0)57.6 (11.3)53.7 (13.7)53.6 (11.7)NS
High UAER, No. (%)3 (2.4)6 (4.8)4 (3.1)3 (2.4)<.05
LVH, No. (%)33 (26.0)20 (15.9)23 (18.2)31 (24.6)<.05
Advanced FO lesions, No. (%)9 (7.2)7 (5.5)3 (2.4)9 (7.1)<.05
GFR <60 mL/min/1.73 m2, No. (%)11 (8.6)1 (0.8)5 (4.0)6 (4.7)NS
 Q1Q2Q3Q4P Value
  1. Abbreviations: CBP, clinic blood pressure; FO, fundus oculi; GFR, glomerular filtration rate according to Modification of Diet in Renal Disease equation; HDL, high-density lipoprotein; LVH, left ventricular hypertrophy; NS, not significant; SBPM, self–blood pressure monitoring; SD, standard deviation; UAER, urinary albumin excretion rate >22 mg/g in men and >32 mg/g in women. Men (cm): quartile 1 (Q1): 153–164; quartile 2 (Q2):165–169; quartile 3 (Q3):170–173: quartile 4 (Q4):174–194; women (cm): Q1: 142–152; Q2:153–156; Q3: 157–160; Q4:161–177. Chi-square test was used for qualitative variables with expected results <5 (continuity correction) and Scheffe test for continuous variables.

Age (SD), y63.6 (11.5)57.1 (10.2)55.5 (7.8)55.6 (8.6)<.05
CBP, mm Hg
Systolic148.6 (12.9)147.9 (13.3)151.2 (9.9)149.5 (10.0)NS
Diastolic87.1 (9.7)86.4 (8.1)90.3 (8.6)88.9 (6.4)NS
SBPM, mm Hg
Systolic136.7 (14.7)134.1 (14.4)138.2 (12.0)133.7 (3.7)NS
Diastolic80.5 (9.1)79.3 (8.7)82.3 (7.9)82.6 (5.8)NS
Tobacco, No. (%)11 (10.5)7 (6.7)15 (14.4)13 (12.5)<.05
Fasting glucose (SD), mg/dL86.0 (11.9)89.9 (11.4)89.8 (15.9)89.1 (9.1)NS
Total cholesterol (SD), mg/dL213.0 (38.7)225.0 (36.8)209.8 (30.8)211.0 (27.0)<.05
HDL cholesterol (SD), mg/dL67.6 (14.9)66.5 (49.0)66.7 (39.3)63.0 (10.8)NS
High UAER, No. (%)-4 (3.8)1 (1.0)1 (1.0)<.05
LVH, No. (%)27 (25.7)12 (11.5)26 (25.0)27 (26.0)<.05
Advanced FO lesions, No. (%)16 (15.2)12 (11.5)6 (5.8)10 (9.6)<.05
GFR <60 mL/min/1.73 m2, No. (%)12 (11.4)6 (5.7)4 (3.8)<.05

Multivariate Models of Clinical Features and SVD According to Height

To analyze differences in clinical characteristics and SVD depending on height, in multivariate models (Table 3) patients were grouped according to height (above or below the median for each sex). In model A (adjusted for sex and body mass index [BMI]), patients whose adult height was higher than the median of each sex had greater CBP and SBPM diastolic BP (OR for mm Hg, 1.01; 95% CI, 1.01–1.02) and higher rates of LVH (OR, 1.45; 95% CI, 1.01–2.08). When adjusted for age, sex, and BMI (model B), there was an association with LVH (OR, 1.57; 95% CI, 1.10–2.24), with the association of diastolic BP disappearing (OR for mm Hg, 1.01; 95% CI, 1.00–1.03). Both models showed a significant association between adult height and fasting glucose, HDL cholesterol, and triglycerides.

Table 3. Multivariate Models of Clinical Characteristics and Vascular Involvement by Sizea
 Model AModel B
  1. Abbreviations: CBP, clinic blood pressure; FO, fundus oculi; GFR, glomerular filtration rate; HDL, high-density lipoprotein; LVH, left ventricular hypertrophy; SBPM, self–blood pressure monitoring; UAER, urinary albumin excretion rate. Height median=men 170 cm, women=157 cm. Model A: adjusted for sex and body mass index (BMI); model B: adjusted for age, sex, and BMI. High UAER >21 mg/g for men and >32 mg/g for women. GFR <60 mL/min/1.73 m2 and/or high UAER and/or advanced FO lesions. aHeight > median odds ratio for each centimeter, 95% confidence interval. bP<.05. cP<.10.

CBP (for mm Hg)
Systolic1.0 (0.98–1.01)1.0 (0.98–1.01)
Diastolic1.02 (1.00–1.04)b1.00(0.99–1.02)
SBPM (for mmHg)
Systolic0.99 (0.97–1.00)0.99 (0.97–1.00)
Diastolic1.03 (1.01–1.05)b1.01 (1.00–1.03)c
Tobacco (yes)1.23 (0.86–1.77)1.11 (0.76–1.62)
Alcohol (yes)1.07 (0.76–1.51)1.18 (0.82–1.70)
Fasting glucose (for mg/dL)1.02 (1.00–1.04)b1.04 (1.02–1.06)b
Cholesterol (for mg/dL)0.98 (0.96–1.00)0.99 (0.97–1.01)
HDL cholesterol (for mg/dL)0.93 (0.89–0.96)b0.96 (0.92–0.99)b
Triglycerides (for mg/dL)1.13 (1.06–1.20)b1.07 (1.01–1.15)b
Creatinine (for mg/dL)1.02 (0.99–1.06)1.04 (1.00–1.08)c
GFR <60 mL/min/1.73 m2 (yes)0.66 (0.35–1.21)1.16 (0.59–2.27)
High UAER (yes)0.51 (0.17–1.49)0.54 (0.18–1.65)
Advanced FO lesions (yes)0.78 (0.47–1.30)0.92 (0.54–1.56)
Microvascular lesions (2) (yes)0.69 (0.46–1.02)c0.94 (0.61–1.43)
LVH (yes)1.46 (1.05–2.04)b1.57 (1.10–2.24)b

AVR According to Adult Height

There were interquartile differences in AVR in the total cohort and among women, with higher AVR in Q1 and Q3 (P<.05; Scheffe test for continuous variables). Grouping patients according to adult height above or below the median of the entire cohort and by sex showed that patients whose final height was above the median have greater AVR than patients whose height was below the median. The age-adjusted model (model B) showed that the association disappears for women while it is maintained for the total cohort and for men (Table 4).

Table 4. Baseline AVR According to Sex and Height (n=166), Multivariate Analysis
 Baseline AVR < Median Odds Ratio (Confidence Interval 95%)
Model AModel B
  1. Abbreviation: AVR, arteriole-to-venula ratio. Model A: adjusted for sex and body mass index (BMI); model B: adjusted for age, sex, and BMI. Height median=men 170 cm, women=157 cm; AVR median=men 0.8220, women=0.8540. aP<.05.

All (height < median)

Height > median (for each centimeter)


0.95 (0.93–0.97)a


0.97 (0.94–0.99)a

Men (height < median)

Height > median (for each centimeter)


0.94 (0.91–0.97)a


0.95 (0.92–0.98)a

Women (height < median)

Height > median (for each centimeter)


0.95 (0.91–0.99)a


0.97 (0.93–1.02)


The results of this study, conducted in newly diagnosed hypertensive treatment-naive adult patients, show a direct relationship between the size and prevalence of LVH. This relationship was independent of BP and other common CV risk factors and persists after adjusting for age, sex, and BMI.

Various mechanisms have been identified in the development of LVH. First is mechanical overload, mainly caused by BP,[25] particularly sustained BP diagnosed by ambulatory monitoring techniques.[26] However, this mechanism explains only 30% of the changes in ventricular mass. Other humoral and genetic factors have been reported to be involved in the increase in ventricular mass, either independently or in combination with mechanical overload, as well as genetic factors.[27] Some anthropometric variables such as body size expressed by BMI[28] or adult height[29] are associated with LV mass increase. Height adjustment improves CV prognosis associated with LVH detected by echocardiography[30] in relation to body surface area adjustment.

Our study shows that the association between adult height and LVH is independent of BP, weight, and BMI. Adult height was used as a marker of socioeconomic deprivation during the perinatal period and the growth period.[1, 16] It could be assumed that exposure to various factors resulting from this situation could cause further vascular damage, as well as LVH. These factors may indicate increased exposure to tobacco or other environmental toxins, poor housing conditions, or incomplete combustion with poor ventilation; however, our results favor the opposite hypothesis, showing that the association between adult height above the median and LVH is independent of age and reasonably eliminates the effect of deprivation in older patients. Several hypotheses may explain this relationship between height and LVH. First, that tall stature is associated with a mechanical overload distinct from BP, such as an increase in peripheral resistance or greater volume overload. In our cohort there were no differences in diastolic CBP or diastolic SBPM, which is a parameter associated with an increase in peripheral resistance. Moreover, the association is independent of BMI, thus the hypothesis of volume overload, often linked to obesity, is highly unlikely. Second, adult height is a phenotypic expression associated with increased likelihood of developing increased ventricular mass in response to certain stimuli such as BP. It seems that tall stature is associated with an increased risk of atrial fibrillation independent of left atrial size and left ventricular mass.[31] The authors believe that genes associated with atrial fibrillation and growth pathways are closely related. The increased workload on the heart in hypertensive patients produces initialing signals response of growth cardiac myocyte, apoptosis, and coupling mechanism.[32] This response has a regulation gene expression that may explain the relationship between high stature and greater prevalence of LVH.

ECG criteria for the diagnosis of LVH have distinct sensitivity and specificity depending on ethnicity and body habitus. Some authors have developed LVH ECG criteria adjusted for age and BMI.[31] We did not find any studies adjusting ECG findings by height even though height provides a better estimator of muscle mass than BMI, which is influenced by body fat.[32]

In our study we used the criteria of Sokolow-Lyon and those of Cornell modified by Dalfó.[22] Cornell ECG criteria have been reported to have good correlation with ventricular mass in overweight or obese patients while the Sokolow-Lyon is useful in thinner patients.[33] Despite the foregoing and that our results are adjusted for BMI, it cannot be excluded that the ECG technique would be subject to the influence of height for the diagnosis of LVH.

No significant differences were found in small vessel lesions, except for a marginal value (P<.10) for total microvascular injury that disappeared when adjusted for age. It has been reported that alteration of kidney function in diabetic patients depends on the time of disease progression.[34] The presence of small vessel lesions may be related to the years of the disease's evolution in patients, and for this reason the marginal association with short stature disappears when adjusted for age. However, when calculating the size of small arterial and venous vessels of the retina, which is considered an indicator of early changes in retinal microcirculation,[35] we found that tallest patients have higher AVR than those whose adult height is lower, indicating a better microvascular circulation in taller patients.

There are at least two hypotheses to explain the association between short stature and early small vessel lesions. First, small vessel lesions represent a consequence of vascular damage experienced by patients in the perinatal period and during development as a result of increased exposure to tobacco or other environmental toxins, the consumption of toxic substances, or poor nutrition in both periods.[8] This assumes that short stature can be considered as an indicator of socioeconomic status in addition to being associated with high levels of both biologic and behavioral risk factors.[7] Second, there is a genetic association between short stature and increased vulnerability of small vessels by unknown mechanisms. In this regard, the literature describes babies born small for gestational age having higher BP, blood glucose levels, and cholesterol.[36] In any case in our study, it was the taller patients who had higher concentrations of glucose and total cholesterol, which could indicate that the vascular damage associated with short stature at birth should occur during this period.

Study Limitations

This study has various limitations. First, ECG was used to detect LVH. Although the criteria revealed the presence of LVH in 21% of patients, echocardiography would have been a more sensitive technique. It cannot be assessed how much the increased sensitivity of the echocardiogram would have influenced results considering that the ventricular mass has a close relationship with size. Second, the prevalence of SVD, particularly LVH, showed some heterogeneity in the distribution by quartiles. However, when grouped quartiles and analysis was performed according to the median adult height, the results were significant in the multivariate models. This is likely the result of the importance of some variables such as BMI or basal glucose levels, triglycerides, and HDL cholesterol that were included in the models. Because of this, the results should be considered with caution. Third, the results of AVR were obtained in a small sample of patients because of technical limitations of the automatic application. This subgroup of patients showed significant differences in CBP and SBPM with respect to the entire cohort, with no difference in the other variables. The influence of this fact on the results of the AVR is unknown, but although the retinal selection was made solely on the basis of quality criteria by an investigator who was unaware of patient data, the results should be evaluated with caution. There is a possibility that high BP in this subset caused the development of retinal microcirculation impairment, but, in this case, it would have happened in all patients. Finally, one cannot exclude the presence of some unidentified confounding factors or a bias related to the cohort, although multiple adjustments had been made to avoid this.


Our results show that in recently diagnosed hypertensive patients, the prevalence of SVD is different depending on the height attained in adulthood. Taller patients showed an association with LVH while initial small vessel lesions, represented by the vessels of the retina, were associated with lower height. The results allow for two considerations. First, that the current European Society of Hypertension recommendations[20] for initial evaluation of hypertensive patients including major vessel injury (ECG) and small vessel (GFR and UAER) are suitable for hypertensive patients of any size. Second, we can assume that if more scans are needed to detect SVD, the decision to perform them could depend on the size of the patient. Taller patients may require echocardiography to detect LVH, while, in patients of smaller size, AVR measurements may be most appropriate. The association between LVH and height could possibly be secondary to an increased response of the ventricular mass to mechanical overload caused by BP in taller patients. The greater damage to the retinal microcirculation in shorter hypertensive patients may be related to socioeconomic factors at the time of birth and during perinatal development as well as behavioral risk factors, although it cannot be excluded that stature constitutes a phenotypic expression associated with greater involvement of the small vessel. In any case, future studies are warranted to determine the relationship between genes that regulate final height, the pathophysiological mechanisms of ventricular mass growth and microcirculation injuries, and environmental factors.


List of those participating in the VAMPAHICA study: EAP Angles: Antonio Rodriguez Poncelas (HC), Anna Tura Suner, Manuel Roman Pomares, Gemma Caparros Boixes, Elena Cardus Gomez, Maria Sanmartin, Carme Comalada Daniel, Cati Ferriol Busquets, Eugenia Diaz Giraldos, Nuria Alsina, Gabriel Coll-de-Tuero. EAP Can Gibert del Pla: Joaquim Franquesa Salvador (HC) Pilar Franco Comet. Ma Angels Sieira Ribot, Pilar Font i Roura, Jacqueline Llaveria Fernandez, Margarida Puigvert Vilalta, Carmen Peruga Pascua, Aida Fortuny i Borsot, Dolors Boix Pujol. EAP Cassa de la Selva: Marta Beltran Vilella (HC), Gloria Ribas Miquel, Neus Ferre Morell, Josep Ma Gifre Hipolit, Anna Serra Joaniquet, Sonia Rubau Camps, Elena Navarro Pou, Marta Raset Pimas, Jordi Vilano Vives, Ruth Arnau Torres, Merce Ribot Igualada, Celia Esteban Romero, Carolina Roig Buscato, Jacobo Martinez Rodriguez, Susana Vargas Vila, Susana Tremols Iglesias, Marian Fernandez Yanez, Elena Amoros Guillem, Raquel Jimenez Quinonez. EAP Celra. Ma Jesus Gelado Ferrero (HC), Artemi Rosell Ferrer, Julio Gil Rubio, Pere Peya Fusellas, Irene Pere Solavilla, Marta Quirch Nunez. EAP Hostalrich-Breda: Antonio Ubieto Lope (HC), Anna Escura Reixach, Montse Pomes Casas, Silvia Sanchez Fraile, Tamara Garcia Ulloa, Sandra Ortiz Alonso. EAP La Bisbal: Helena Badia Capdevila (HC), Dolors Gelabert Ribas, Merce Agusti Sanchez. EAP La Jonquera: Jordi Isart Rafecas (HC), Lorenzo de la Pena Lopez, Jaume Domenech Domenech, Merce Fores Vineta, Xavier Lecumberri Acedo, Conchita Valls Domenech, Dolors Perez Rodriguez, Pilar Pujol Adrados, Angels Lopez Sabater,Anna Costa Porxas. EAP Llanca: Manolo de la Cruz Lopez, Conxita Rojo Ratera, Isabel Fernandez Martin,Carme Montenegro Famada, Margarita Rodriguez Gisado, Montserrat Mallol Castello. EAP Montilivi: Narcis Salleras Marco (HC), Julia Massana Masgrau, Pedro Ferrer Jimenez, Laia Sanchez Solanilla, Nuria Gispert-Sauch Puigdevall, Lota Font Bertrana, Anna Ma Perez Gutierrez, Dolors Perpina Bosch, Anna Garcia Chumillas, Eva Vega Garcia, Nuria Pugiver Viu, Anna Rebarter Rius, Dolors Melcio Soler. EAP Palafrugell: Emili Mas Parareda (HC), Esther Vilert Garrofa,Clara Carrasco Rauret, Montse Verdaguer Clavera, Rosa Pascual, Pilar Rovira Camino, Margarita Mauri Junque, Josep Bargallo Roige. EAP Peralada: Lluis Martinez Via (HC), Judit Noguera Suquet, Ferran Vaquero Belmonte, Jose Vallejo Gracia, Ramon Tarres Gimferrer, Teia Marsillach Daunis, Jero Dorado Diaz, Joan Pages Perez, Pere Sors Cuffi. EAP Salt: Victoria Sala Fita (HC), Miquel Quesada Sabate, Artur Marques Vidal, Fernando Montesinos Vicente, Helena Comas Soler, Carmen Jimenez Ruiz, Silvia Cairo Corominas. EAP Sarria de Ter: Ramon Creus Bosch (HC), Jordi Taberner Mundet, Merce Algans Coll, Emili Marco Segarra, Carme Rigau Lleal,Mireia LLoveras Garriga, Emilia Rustullet Felip, Dolors Antequera Lopez. EAP Sils: Josep Ma. Garrido Martin (HC), Merce Lluch Burget, Montse Torra Pla, Marta Cortes Lopez, Pilar Sola Bohigas. HC indicates head of center; EAP: Equipo de Atencion Primaria (Primary Health Care Service in that location).


The authors declared no conflict of interest.


This paper was partly funded by projects 07/0140 and ETES 08/90539 of the Fondo de Investigacion Sanitaria, Health Care Research Foundation, Ministry of Health, Spain.