HTN has been identified as the leading risk factor for mortality and is ranked as the third cause of disability worldwide [
In 2008, it was estimated that, globally, 4 in 10 adults over the age of 25 years and at the prime of their productivity were hypertensive [
The fact that the populations in the LMICs are bearing one of the highest burdens of the disease can be owed to the alarming rates of demographic changes including the growth and ageing of the populations, urbanization, and globalization [
The Arab world reported a higher crude prevalence of HTN (29.5%) when compared to other regions of the world such as the sub-Saharan Africa (27.6%) and the USA (28%) [
Epidemiological data has revealed the need for increased awareness of HTN especially in low and middle income countries where the public awareness of the disease is moderately dismal [
This was a community based cross-sectional study conducted in 2014 in Greater Beirut Area (GBA). The study recruitment was done at the American University of Beirut (AUB) over a 3-month period from March until May 2014. The study included Lebanese adults aged 18-79 years and residing in GBA. It excluded vulnerable populations, mainly pregnant and lactating women, dialysis patients, and subjects with mental disabilities. The study was approved by the Institutional Review Board of AUB. A study by Nasrallah et al. reported the prevalence of type 2 diabetes in the Lebanese population from the collected data [
The selection criteria were based on multistage probability sampling. First, the districts of Central Administrative Beirut in addition to areas in the districts of Chouf, Aley, Baabda, Metn, and Keserwan were selected as clusters. Second, within each selected cluster, neighborhoods were selected to represent the make-up of the areas, followed by the selection of the households which was based on a systematic random sampling according to the estimated number of buildings in the neighborhood. Finally, sampling a primary respondent within each household based on the most recent birthday was done. The objectives of the study along with the methods were clearly explained to the selected participants who accepted to get enrolled. Those who agreed on the objectives and conditions had signed an informed consent.
Information collected from subjects included (1) demographic and socioeconomic data: age, gender, marital status, education, and income level; (2) lifestyle-related data: smoking (current smoker defined as any daily smoking, regardless of the number of cigarettes or water-pipe), alcohol intake (defined as any intake), caffeine intake, and being physical active, assessed as (yes/no); (3) medical history: coronary artery disease and diabetes mellitus; (4) anthropometric measures: waist circumference and waist-to-hip ratio using a standardized method [
According to the thresholds of the Joint National Committee on Prevention, Detection, Evaluation and Treatment of High Blood Pressure Seven (JNC 7) and the (JNC 8) guidelines for the management of hypertension in adults, the participants were classified as follows: Hypertensive individuals: defined as those with SBP ≥140 mm Hg and/or DBP ≥ 90 mmHg [ Prehypertensive individuals: defined as those who have not been informed of HTN diagnosis and with SBP 120- 139 mm Hg and/or DBP 80-89 mm Hg [ Normotensive individuals: defined as those who have not been informed of HTN diagnosis and with SBP < 120 mm Hg and DBP < 80 mm Hg [ Aware individuals: defined as those who have been informed of HTN diagnosis [ Unaware individuals: defined as those who have never been informed of HTN diagnosis and with SBP ≥140 mm Hg and/or DBP ≥ 90 mm Hg. Controlled HTN: defined as SBP < 140 mmHg for individuals below the age of 60; SBP < 150 mm Hg for individuals above the age of 60 years and DBP < 90 mmHg as a result of pharmacologic treatment among the aware hypertensive [ Treated individuals: defined as those who were aware of being hypertensive and are on pharmacologic treatment
Descriptive statistics were conducted for the overall characteristics of the study population through presenting the numbers and percent for the categorical variables and means and standard deviations for the continuous ones. Inferential bivariate analysis was carried out where Chi square or Fisher exact tests were used for the categorical and binary factors, as appropriate. Independent t-test and one-way ANOVA tests were conducted for the continuous variables. Results were presented by the p-values in addition to the descriptive statistics for each of the outcome groups identified. Multiple and multinomial logistic regression were carried out to adjust for potential confounding and/or interaction effect of variables under study. The stepwise approach was used to choose the best model. The results were presented by the odds ratios and 95% confidence intervals (CI). P-value < 0.05 was set as an indicator of statistical significance. The data analysis was done on two types of software: SPSS 22 and STATA 13.
A total of 501 subjects participated in the study. The sample consisted of 322 women (64.3%) and 179 men (35.7%), with a mean age of 45.4 ± 15.0 years. Approximately 10% of the study participants reported a monthly income above 2000 USD per household and university level of education. The lifestyle habits results showed that 43% of the participants were current cigarettes smokers, 28.3% were current nargileh smokers, and 19% were current alcohol drinkers. The majority of the study participants reported drinking coffee (80.4%) and engaging in physical activity (84.2%) (Table
Baseline characteristics of the study sample.
|
|||
---|---|---|---|
|
501 | ||
|
|||
|
|
≤ 30 | 107 (21.4%) |
31-40 | 78 (15.6%) | ||
41-50 | 118 (23.6%) | ||
51-60 | 123 (24.6%) | ||
> 60 | 75 (14.9%) | ||
|
mean ± SD | 45.4 ± 15.0 | |
|
Males | 179 (35.7%) | |
Females | 322 (64.3%) | ||
|
Married | 332 (66.3%) | |
Single | 98 (19.6%) | ||
Others | 71 (14.2%) | ||
|
|||
|
|
<600$ | 153 (33.8%) |
600-999.9$ | 170 (37.5%) | ||
1000-2000$ | 90 (19.9%) | ||
>2000$ | 40 (8.8%) | ||
|
No school /Primary | 181 (36.3%) | |
Intermediate/Secondary/Technical | 263 (52.8%) | ||
University degree | 54 (10.8%) | ||
|
|||
|
|
Never | 236 (47.1%) |
Current | 216 (43.1%) | ||
Ex-smoker | 49 (9.8%) | ||
|
Never | 311 (62.1%) | |
Current | 142 (28.3%) | ||
Ex-smoker | 48 (9.6%) | ||
|
Never | 372 (74.3%) | |
Current | 95 (19.0%) | ||
Ex-smoker | 34 (6.8%) | ||
|
403 (80.4%) | ||
|
422 (84.2%) |
Table
The association of demographic, socioeconomic, lifestyle, anthropometric, dietary intake, and medical history and laboratory tests with BP.
|
|
|
|
|
||
---|---|---|---|---|---|---|
|
|
|
||||
|
|
|
||||
|
|
|
40.2 ± 12.8 | 41.6 ± 14.2 | 53.6 ± 14.2 | <0.0001 |
|
|
51 (26.7%) | 36 (28.3%) | 19 (10.4%) | <0.0001 |
|
|
42 (22.0%) | 23 (18.1%) | 13 (7.1%) | |||
|
57 (29.8%) | 32 (25.2%) | 29 (15.9%) | |||
|
34 (17.8%) | 23 (18.1%) | 66 (36.3%) | |||
|
7 (4.0%) | 13 (10.2%) | 55 (30.2%) | |||
|
|
143 (74.9%) | 64 (50.4%) | 114 (62.6%) | <0.0001 |
|
|
48 (25.1%) | 63 (49.6%) | 68 (37.4%) | |||
|
|
138 (72.3%) | 80 (63.0%) | 113 (62.1%) | <0.0001 |
|
|
39 (20.4%) | 35 (27.6%) | 24 (13.2%) | |||
|
14 (7.3%) | 12 (9.4%) | 45 (24.7%) | |||
|
||||||
|
|
|
44 (25.3%) | 27 (22.9%) | 82 (51.2%) | <0.0001 |
|
64 (36.8%) | 58 (49.2%) | 47 (29.4%) | |||
|
48 (27.6%) | 18 (15.3%) | 24 (15.0%) | |||
|
18 (10.3%) | 15 (12.7%) | 7 (4.4%) | |||
|
|
50 (26.6%) | 44 (34.6%) | 87 (47.8%) | <0.0001 |
|
|
114 (60.6%) | 65 (51.2%) | 83 (45.6%) | |||
|
24 (12.8%) | 18 (14.2%) | 12 (6.6%) | |||
|
||||||
|
|
|
90 (47.1%) | 59 (46.5%) | 86 (47.3%) | 0.09 |
|
89 (46.6%) | 57 (44.9%) | 70 (38.5%) | |||
|
12 (6.3%) | 11 (8.7%) | 26 (14.3%) | |||
|
|
108 (56.5%) | 78 (61.4%) | 124 (68.1%) | 0.11 | |
|
62 (32.5%) | 40 (31.5%) | 40 (22.0%) | |||
|
21 (11.0%) | 9 (7.1%) | 18 (9.9%) | |||
|
|
41 (21.5%) | 29 (22.8%) | 27 (14.8%) | 0.14 | |
|
150 (78.5%) | 98 (77.2%) | 155 (85.2%) | |||
|
|
151 (79.1%) | 85 (66.9%) | 135 (74.2%) | 0.08 | |
|
31 (16.2%) | 33 (26.0%) | 31 (17.0%) | |||
|
9 (4.7%) | 9 (7.1 %) | 16 (8.8%) | |||
|
|
27 (14.1%) | 21 (16.5%) | 31 (17.0%) | 0.71 | |
|
164 (85.9%) | 106 (83.5%) | 151 (83.0%) | |||
|
||||||
|
|
|
66 (34.9%) | 34 (27.2%) | 16 (8.8%) | <0.0001 |
|
79 (41.8%) | 34 (27.2%) | 58 (31.9%) | |||
|
44 (23.3%) | 57 (45.6%) | 108 (59.3%) | |||
|
83 (43.7%) | 59 (46.8%) | 136 (74.7%) | <0.0001 |
||
|
152 (80.4%) | 82 (65.6%) | 149 (82.3%) | 0.001 |
||
|
|
24.9 ± 9.8 | 27.5 ± 12.3 | 33.4 ± 11.1 | <0.0001 |
|
|
||||||
|
|
|
3291.0 ± 1532.3 | 3714.2 ± 1534.5 | 3057.4 ± 1473.2 | 0.01 |
|
|
108.9 ± 77.2 | 118.7 ± 54.2 | 101.9 ± 60.1 | 0.14 | |
|
|
390.5 ± 224.2 | 438.8 ± 268.7 | 374.9 ± 211.8 | 0.05 |
|
|
|
144.4 ± 89.4 | 159.3 ± 96.1 | 129.7 ± 78.1 | 0.01 |
|
|
|
38.5 ± 25.4 | 43.65 ± 31.8 | 32.9 ± 21.3 | 0.002 |
|
|
|
48.8 ± 8.7 | 48.5 ± 7.8 | 49.5 ± 8.7 | 0.57 | |
|
|
13.2 ± 3.9 | 12.9 ± 2.6 | 13.5 ± 3.0 | 0.40 | |
|
|
38.9 ± 7.8 | 38.9 ± 7.6 | 37.9 ± 8.7 | 0.28 | |
|
|
10.2 ± 2.7 | 10.2 ± 2.8 | 9.5 ± 2.7 | 0.03 |
|
|
||||||
|
|
|
10 (5.2%) | 6 (4.7%) | 29 (15.9%) | <0.0001 |
|
7 (3.7%) | 2 (1.6%) | 13 (7.1%) | 0.05 |
||
|
70 (36.6%) | 56 (44.1%) | 63 (34.6%) | 0.22 | ||
|
9 (4.7%) | 12 (9.4%) | 54 (29.7%) | <0.0001 |
||
|
||||||
|
|
|
100.3 ± 28.0 | 107.5 ± 32.7 | 127.1 ± 56.6 | <0.0001 |
|
|
5.5 ± 0.8 | 5.8 ± 1.1 | 6.4 ± 1.7 | <0.0001 |
|
|
|
10.2 ± 7.2 | 11.3 ± 8.2 | 14.76 ± 13.0 | <0.0001 |
|
|
|
182.2± 37.5 | 182.8 ± 40.3 | 192.3 ± 50.1 | 0.052 | |
|
|
118.8 ± 68.8 | 143.3 ± 145.9 | 164.3 ± 88.4 | <0.0001 |
|
|
|
50.8 ± 14.8 | 51.5 ± 16.4 | 46.9 ± 13.1 | 0.01 |
|
|
|
107.0 ± 32.9 | 105.1 ± 35.4 | 113.3 ± 48.3 | 0.12 | |
|
|
126.2 ± 47.9 | 125.6 ± 57.4 | 113.7 ± 48.3 | 0.03 |
|
|
|
79.3 ± 34.9 | 69.6 ± 31.8 | 76.2 ± 32.9 | 0.03 |
|
|
|
104.9 ± 22.8 | 102.3 ± 23.9 | 93.0 ± 26.1 | <0.0001 |
BMI and abdominal obesity were found to be significant correlates. The percentage of the obese individuals increased significantly and gradually among the three groups (23.3% for the normotensive, 45.6% for the pre-HTN, and 59.3% for the hypertensive individuals). Furthermore, the results showed significant differences in the mean of the macronutrients (carbohydrates, total fat, and the saturated fats in addition to the total energy) among the different groups, where the highest mean of each of the mentioned macronutrients was among the pre-HTN group while the lowest was among the hypertensive group when compared to the normotensive (p-value <0.05) (Table
Results of the logistic regression analyses showed that the main factors that were significantly associated with HTN were age, income level, T2D, triglyceride, and CRP (Table
The multinomial logistic regression model for the BP groups.
|
|
|
|
|
||
---|---|---|---|---|---|---|
|
|
|||||
|
|
51 (26.7%) | 36 (28.3%) | Ref | 19 (10.4%) | Ref |
|
42 (22.0%) | 23 (18.1%) | 1.04 (0.43-2.59) | 13 (7.1%) | 1.39 (0.46-4.19) | |
|
57 (29.8%) | 32 (25.2%) | 1.25 (0.50-3.02) | 29 (15.9%) | 1.72 (0.57-5.19) | |
|
34 (17.8%) | 23 (18.1%) | 1.39 (0.43-3.04) | 66 (36.3%) | 4.93 (1.67-14.51) | |
|
7 (3.7%) | 13 (10.2%) | 3.53 (0.94-11.72) | 55 (30.2%) | 17.91 (4.97- 64.45) | |
|
||||||
|
|
143 (74.9%) | 64 (50.4%) | Ref | 114 (62.6%) | Ref |
|
48 (25.1%) | 63 (49.6%) | 3.71 (2.56-9.72) | 68 (37.4%) | 4.78 (2.25-11.11) | |
|
||||||
|
|
138 (72.3%) | 80 (63.0%) | Ref | 113 (62.1%) | Ref |
|
39 (20.4%) | 35 (27.6%) | 1.82 (0.71-4.41) | 24 (13.2%) | 3.57 (1.02-8.09) | |
|
14 (7.3%) | 12 (9.4%) | 1.15 (0.43-2.96) | 45 (24.7%) | 2.22 (0.95-5.16) | |
|
||||||
|
|
44 (25.3%) | 27 (22.9%) | Ref | 82 (51.2%) | Ref |
|
64 (36.8%) | 58 (49.2%) | 1.56 (0.83-3.14) | 47 (29.4%) | 0.67 (0.38-1.42) | |
|
48 (27.6%) | 18 (15.3%) | 0.64 (0.29-1.44) | 24 (15.0%) | 0.55 (0.25-1.19) | |
|
18 (10.3%) | 15 (12.7%) | 1.03 (0.38-2.98) | 7 (4.4%) | 0.22 (0.07-0.88) | |
|
||||||
|
9 (4.7%) | 12 (9.4%) | 1.21 (0.44-3.87) | 54 (29.7%) | 2.41 (1.08-7.02) | |
|
||||||
|
152 (80.4%) | 82 (65.6%) | 0.54 (0.21-1.43) | 149 (82.3%) | 1.09 (0.41-2.89) | |
|
||||||
|
|
24.9 ± 9.8 | 27.5 ± 12.3 | 1.05 (1.02-1.09) | 33.4 ± 11.1 | 1.08 (1.05-1.12) |
|
||||||
|
|
79.3 ± 34.9 | 69.6 ± 31.8 | 0.89 (0.98-0.99) | 76.2 ± 32.9 | 0.95 (0.98-1.003) |
|
||||||
|
|
118.8 ± 68.8 | 143.3 ± 145.9 | 1.01 (0.99-1.01) | 164.3 ± 88.4 | 1.04 (1.01-1.08) |
|
||||||
|
|
50.8 ± 14.8 | 51.5 ± 16.4 | 1.37 (1.01-1.05) | 46.9 ± 13.1 | 1.15 (0.93-1.42) |
|
||||||
|
|
10.2 ± 7.2 | 11.3 ± 8.2 | 1.17 (0.82-1.62) | 14.76 ± 13.0 | 1.46 (1.08-2.01) |
The logistic regression analysis results (Table
Table
The association of demographic, socioeconomic, lifestyle, anthropometric, dietary intake, and medical history and laboratory tests with unaware hypertensive.
|
|
|
|
||
---|---|---|---|---|---|
|
|
|
|||
|
|
||||
|
|
|
40.2 ± 12.8 | 47.6 ± 16.6 | 0.002 |
|
|
51 (26.7%) | 16 (25.4%) | 0.002 | |
|
42 (22.0%) | 5 (7.9%) | |||
|
57 (29.8%) | 8 (12.7%) | |||
|
34 (17.8%) | 20 (31.7%) | |||
|
7 (3.7%) | 14 (22.2%) | |||
|
|
48 (25.1%) | 34 (54.0%) | <0.0001 | |
|
143 (74.9%) | 29 (46.0%) | |||
|
|
138 (72.3%) | 32 (50.8%) | 0.002 | |
|
39 (20.4%) | 18 (28.6%) | |||
|
14 (7.3%) | 13 (20.6%) | |||
|
|||||
|
|
|
44 (25.3%) | 25 (44.6%) | 0.03 |
|
64 (36.8%) | 16 (28.6%) | |||
|
48 (27.6%) | 9 (16.1%) | |||
|
18 (10.3%) | 6 (10.7%) | |||
|
|
50 (26.6%) | 23 (36.5%) | 0.33 | |
|
114 (60.6%) | 33 (52.4%) | |||
|
24 (12.8%) | 7 (11.1%) | |||
|
|||||
|
|
|
90 (47.1%) | 28 (44.4%) | 0.025 |
|
89 (46.6%) | 24 (38.1%) | |||
|
12 (6.3%) | 11 (17.5%) | |||
|
|
108 (56.5%) | 37 (58.7%) | 0.63 | |
|
62 (32.5%) | 17 (27.0%) | |||
|
21 (11.0%) | 9 (14.3%) | |||
|
|
41 (21.5%) | 12 (19.0%) | 0.68 | |
|
150 (78.5%) | 51 (81.0%) | |||
|
|
151 (79.1%) | 45 (71.4%) | 0.41 | |
|
31 (16.2%) | 13 (20.6%) | |||
|
9 (4.7%) | 5 (7.9%) | |||
|
|
27 (14.1%) | 9 (14.3%) | 0.97 | |
|
164 (85.9%) | 54 (85.7%) | |||
|
|||||
|
|
|
66 (34.6%) | 10 (15.9%) | <0.0001 |
|
79 (41.4%) | 16 (25.4%) | |||
|
44 (23.0%) | 37 (58.7%) | |||
|
|
107 (56.3%) | 23 (36.5%) | 0.005 | |
|
83 (43.7%) | 40 (63.5%) | |||
|
|
37 (19.6%) | 13 (21.0%) | 0.82 | |
|
152 (80.4%) | 49 (79.0 %) | |||
|
|
24.9 ± 9.7 | 32.9 ± 12.3 | 0.001 | |
|
|||||
|
|
|
3134.0 ± 1532.3 | 3268.6 ± 1487.6 | 0.55 |
|
|
104.7 ± 71.2 | 107.7 ± 55.8 | 0.76 | |
|
|
372.5 ± 174.1 | 396.9 ± 175.2 | 0.34 | |
|
|
137.4 ± 76.5 | 139.7 ± 70.62 | 0.84 | |
|
|
36.7 ± 22.4 | 37.7 ± 20.4 | 0.76 | |
|
|
48.8 ± 8.7 | 48.9 ± 7.6 | 0.88 | |
|
|
13.2 ± 3.9 | 13.3 ± 2.9 | 0.73 | |
|
|
38.9 ± 7.9 | 38.3 ± 7.4 | 0.56 | |
|
|
10.2 ± 2.7 | 10.3 ± 3.0 | 0.72 | |
|
|||||
|
|
|
10 (5.2%) | 2 (3.2%) | 0.73 |
|
7 (3.7%) | 2 (3.2%) | 1.00 | ||
|
70 (36.6%) | 24 (38.1%) | 0.83 | ||
|
9 (4.7%) | 6 (9.5%) | 0.21 | ||
|
|||||
|
|
|
100.3 ± 28.1 | 112.1 ± 34.5 | 0.01 |
|
|
5.5 ± 0.8 | 5.9 ± 1.3 | 0.01 | |
|
|
10.1 ± 7.1 | 13.9 ± 9.8 | 0.006 | |
|
|
182.2 ± 37.5 | 198.4 ± 53.1 | 0.008 | |
|
|
118.7 ± 68.8 | 153.8 ± 87.2 | 0.001 | |
|
|
50.8 ± 14.8 | 47.7 ± 13.1 | 0.13 | |
|
|
107.0 ± 32.8 | 125.5 ± 49.0 | 0.028 | |
|
|
126.2 ± 47.9 | 125.5 ± 49.0 | 0.92 | |
|
|
79.3 ± 34.8 | 76.3 ± 35.6 | 0.54 | |
|
|||||
|
|
104.9 ± 22.8 | 95.8 ± 21.1 | 0.006 |
Upon adjustment, age was found to be the significant predictor with the strongest association for the unawareness. Significant results were reported among those who are above the age of 60 years, such that the odds for an older person to be unaware of being hypertensive increased up to OR = 7.36 as compared to those ≤ 30 years old (p-value = 0.01). Also, males were found to be at higher odds of being unaware of the disease with an OR = 5.15 (95% CI 2.16-12.25; p-value <0.0001) and the same applies to the single participants with an OR = 4.55 (95% CI: 1.16-17.76; p-value = 0.02). Higher BMI was more common among the unaware patients such that the odds of being unaware hypertensive patient among the obese were found to be 7 times more likely when compared to those with normal weight (OR = 6.83, 95% CI: 2.59-22.01; p<0.0001) (Table
Multiple logistic regression model for the unaware hypertensive versus the normotensive participants.
|
|
|
||
---|---|---|---|---|
|
|
|
|
|
|
1.09 | 0.25-4.65 | 0.91 | |
|
1.90 | 0.41-8.78 | 0.41 | |
|
3.39 | 0.81-14.21 | 0.09 | |
|
7.36 | 1.18-33.07 | 0.01 | |
|
||||
|
|
|
|
|
|
4.57 | 1.97-10.59 | <0.0001 | |
|
||||
|
|
|
|
|
|
4.55 | 1.16-17.76 | 0.02 | |
|
2.27 | 0.68-7.54 | 0.17 | |
|
||||
|
|
|
|
|
|
0.69 | 0.27-1.78 | 0.20 | |
|
0.51 | 0.17-1.53 | 0.18 | |
|
0.26 | 0.06-1.15 | 0.07 | |
|
||||
|
|
|
|
|
|
2.53 | 0.83-7.69 | 0.16 | |
|
6.83 | 2.59-22.01 | <0.0001 |
Table
The association of demographic, socioeconomic, lifestyle, anthropometric, dietary intake, and medical history and laboratory test with the uncontrolled HTN.
|
|
|
|
||
---|---|---|---|---|---|
|
|
|
|||
|
|
|
0(0%) | 0 (0%) | 0.75 |
|
2(3.2%) | 2 (5.0%) | |||
|
12 (19.0%) | 5 (12.5%) | |||
|
25 (39.7%) | 16 (40.0%) | |||
|
24 (38.1%) | 17 (42.5%) | |||
|
|
14 (22.2%) | 15 (37.5%) | 0.09 | |
|
49 (77.8%) | 25 (62.5%) | |||
|
|
43 (68.3%) | 29 (72.5%) | 0.83 | |
|
1 (1.6%) | 1 (2.5%) | |||
|
19 (30.2%) | 10 (25.0%) | |||
|
|||||
|
|
|
33 (61.1%) | 20 (55.6%) | 0.74 |
|
15 (27.8%) | 11 (30.6%) | |||
|
6 (11.1%) | 4 (11.1%) | |||
|
0 (0.0%) | 1 (2.8%) | |||
|
|
30 (61.2%) | 14 (56.0%) | 0.37 | |
|
18 (36.7%) | 10 (40.0%) | |||
|
1 (2.0%) | 1 (4.0%) | |||
|
|||||
|
|
|
31 (49.2%) | 20 (50.0%) | 0.44 |
|
22 (34.9%) | 17 (42.5%) | |||
|
10 (15.9%) | 3 (7.5%) | |||
|
|
46 (73.0%) | 32 (80.0%) | 0.34 | |
|
13 (20.6%) | 4 (10.0%) | |||
|
4 (6.3%) | 4 (10.0%) | |||
|
|
6 (9.5%) | 7 (17.5%) | 0.36 | |
|
57 (90.5 %) | 33 (82.5%) | |||
|
|
53 (84.1%) | 27 (67.5%) | 0.12 | |
|
7 (11.1%) | 8 (20.0%) | |||
|
3 (4.8%) | 5 (12.5%) | |||
|
|
9 (14.3%) | 11 (27.5%) | 0.13 | |
|
54 (85.7%) | 29 (72.5%) | |||
|
|||||
|
|
|
3 (4.8%) | 2 (5.0%) | 0.33 |
|
24 (38.1%) | 10 (25.0%) | |||
|
36 (57.1%) | 28 (70.0%) | |||
|
|
13 (20.6%) | 5 (12.5%) | 0.42 | |
|
50 (79.4%) | 35 (87.5%) | |||
|
|
7 (11.1%) | 6 (15.0%) | 0.76 | |
|
56 (88.9%) | 34 (85.0%) | |||
|
|
34.6 ± 9.9 | 37.2 ± 8.4 | 0.27 | |
|
|||||
|
|
|
2795.7 ± 1439.0 | 2638.4 ± 1307.8 | 0.58 |
|
|
96.6 ± 57.7 | 87.1 ± 44.2 | 0.38 | |
|
|
348.7 ± 188.8 | 336.0 ± 221.9 | 0.75 | |
|
|
115.9 ± 68.9 | 107.3 ± 61.6 | 0.52 | |
|
|
27.7 ± 15.5 | 24.7 ± 13.2 | 0.32 | |
|
|
50.3 ± 9.4 | 50.5 ± 9.6 | 0.93 | |
|
|
13.7 ± 3.0 | 13.7 ± 3.4 | 0.95 | |
|
|
36.9 ± 9.1 | 36.7 ± 10.4 | 0.89 | |
|
|
8.9 ± 2.4 | 8.5 ± 2.5 | 0.42 | |
|
|||||
|
|
|
14 (22.2%) | 11 (27.5%) | 0.54 |
|
6 (9.5%) | 6 (15.0%) | 0.53 | ||
|
20 (31.7%) | 14 (35.0%) | 0.73 | ||
|
27 (42.9%) | 18 (45.0%) | 0.83 | ||
|
|||||
|
|
|
131.5 ± 62.6 | 132.26 ± 62.6 | 0.13 |
|
|
6.5 ± 1.6 | 7.1 ± 2.0 | 0.13 | |
|
|
14.1 ± 9.2 | 17.4 ± 19.0 | 0.24 | |
|
|
186.5 ± 42.3 | 196.1 ± 57.1 | 0.33 | |
|
|
160.1 ± 78.2 | 192.4 ± 95.7 | 0.06 | |
|
|
47.3 ± 13.0 | 45.3 ± 11.7 | 0.43 | |
|
|
107.3 ± 37.0 | 112.4 ± 46.6 | 0.53 | |
|
|
101.7 ± 48.9 | 112.2 ± 39.8 | 0.26 | |
|
|
74.4 ± 31.2 | 76.5 ± 35.2 | 0.74 | |
|
|
90.1 ± 26.2 | 83.6 ± 27.9 | 0.23 |
This cross-sectional study provided an estimate of the current prevalence and control rates of HTN in a community sample representative of the GBA adult population. It highlighted the burden of the disease: 36.4% of the study participants were hypertensive, 25.3% were prehypertensive, and only 38.2% had optimal BP. The awareness rate among the hypertensive participants was estimated at 65.4% and the control rate at 61%.
Our findings of HTN prevalence is comparable to those of a cross sectional study conducted in 2013 in all six provinces of Lebanon and including a sample of 1697 participants, which reported a crude prevalence of 36.9% for HTN and 30% for pre-HTN while the control rate was 54% [
Comparing the findings of our study with similar studies in the adjacent countries, Lebanon had the higher prevalence of HTN when compared to Palestine (27.6%), Egypt (26.3%), and Turkey (31.8%) [
Regression analyses showed that increasing age, male gender and T2D were positive correlates for HTN. The findings were in concordance to the results of the national study by Matar et al. with similar strengths of associations [
Additionally, body fat was found to be high among the hypertensive and prehypertensive population of GBA when compared to the normal. Likewise, TG and CRP are biochemical factors that were positively associated with HTN. High TG, body fat, and CRP are factors linked to the metabolic syndrome which increases the overall cardiovascular risk [
On the other hand, potassium was found to be the only dietary factor that is significantly negatively associated with pre-HTN. A study reported that, in borderline hypertensive patients, a low-potassium diet (16 mmol/day) for 10 days increases systolic and diastolic pressures by 7 and 6 mmHg, respectively, relative to 10 days on a high-potassium diet (96 mmol/day) [
Unaware hypertensive patients among community members not known to have HTN were mostly above the age of 60, males, single, and obese. Interestingly, the SES was no longer significant after the adjustment. Comparing the findings with those of Matar et al. (2015), results were similar showing that HTN awareness was poorer in males when compared to females and in single individuals compared to the married, yet our findings showed that unawareness was among the older subjects and those who had diabetes or hyperlipidemia [
Healthcare access and utilization play a major role in increasing the awareness of HTN. Studies showed that gender difference in the healthcare use is one of the main reasons contributing to the differences in the awareness of the disease [
We could not identify any predictor of HTN control in treated aware hypertensive patients. The control of HTN relies on the modifications in the lifestyle habits and on pharmacologic treatment [
The study has several limitations. Being a cross-sectional study, general associations and hypothesis may be derived, but temporal relationship and causality cannot be established. Even though it is a community based study, selection bias is another limitation due to the small cohort of participants enrolled in the study and the female overrepresentations. The national statistics show that one-third of the Lebanese population are residing in GBA where 50.6% of the population are females while 49.4% are males [
Our findings showed that the prevalence of HTN is consistently high, yet there is an improvement in the awareness and management of the disease. The identified predictors of HTN in GBA were the same as those presented in previous studies done in Lebanon. However, income level, body fat, and CRP were additional factors identified among HTN patients in GBA. Interestingly, among the unaware hypertensive patients who perceive themselves as normal, obesity remains a major problem in the population. Furthermore, our study could not identify any predictor for HTN control and further investigations are needed.
Our results can advise the development and establishment of national interventions by the public health sectors to achieve better awareness, primary prevention, and better control of the disease. The development of a national awareness campaign for hypertension can serve in increasing the detection of the disease, educating the community on factors impacting their BP level, and promoting the importance of following healthy lifestyle habits (healthy diet) and medication adherence.
Blood pressure
Body mass index
Cardiovascular diseases
Chronic kidney diseases
Fasting blood sugar
Greater Beirut Area
Glomerular filtration rate
High density lipoprotein
Glycosylated hemoglobin
Hypertension
Joint National Committee 7
Joint National Committee 8
Prehypertension
Low density lipoprotein
Low and middle income countries
Milligram
Milligram per deciliter
Millimeter of mercury
Odds ratio
Socioeconomic status
Systolic blood pressure
Triglyceride
Type 2 diabetes.
The data used to support the findings of this study are available from the corresponding author upon “reasonable’’ request.
The authors have no multiplicity of interest to disclose.
Aya Noubani and Hussain Isma’eel are equal contributors.
The study was supported by grants from the Medical Practice Plan of the American University of Beirut (MPP, award number 102856), Munib Shahid Development Fund, Lebanese National Council for Scientific Research (LNCSR, award number 102900), and Novo Nordisk Development Fund.