The prevalence of hypertension and its relationship with demographic factors, biochemical, and anthropometric indicators: A population-based study.

BACKGROUND: Hypertension (HTN) is an important public health challenge worldwide. The prevalence of HTN varies across countries. It is necessary to obtain valid information about the prevalence of chronic condition like HTN and its predictors in different societies. Hence, this study was conducted to assess the prevalence of HTN and associated factors in Mashhad, Iran, 2015.
METHODS: This cross-sectional study was performed on 2974 adults residing in Mashhad in 2015. Multistage random sampling was used. A checklist was fulfilled for each subject, and a blood sample was taken for measuring fasting blood sugar, total cholesterol, triglycerides, hemoglobin, serum creatinine, high-density lipoproteins, and low-density lipoproteins. The height and weight of participants and their blood pressure were measured according to protocols.
RESULTS: The prevalence of HTN in this population was 22% (25.9% in male and 20% in female). Most interestingly, smoking and drug abuse were more prevalent in men (14.9% and 3.8%), but the sedentary behavior was more prevalent in women (51%). Interestingly, by increasing the age, the frequency of optimum, normal and high normal type was decreased and the frequency of HTN, specially sever form were increased. In binary logistic regression model, age [odds ratio (OR): 1.07, 95% confidence interval (CI): 1.06-1.09], gender (Ref:Female) (OR: 1.39, 95% CI: 1.05-1.83), and obesity (OR: 1.09, 95% CI: 1.06-1.12) were the predictors of HTN.
CONCLUSION: The prevalence of HTN among this population was found to be high; which indicates the need for HTN-screening programs, especially for the elderly, male and obese population. Given the close relationship between obesity and various diseases, including HTN, practical solutions, including lifestyle interventions, need to be developed.

Introduction

Hypertension (HTN) has become very common worldwide and can lead to major health outcomes, such as myocardial infarction, stroke, renal failure, and ultimately death. The prevalence of HTN is increasing in developing countries and is one of the leading causes of death and disability.1 The prevalence of HTN increases with age.2

The results of descriptive studies showed that death from ischemic heart disease and stroke increased linearly in those with a systolic blood pressure (SBP) level as low as 115 mmHg and a diastolic BP (DBP) level of 75 mm Hg.3,4 According to one study, the awareness of HTN among general population varied from 25.2% to 75%.5 The World Health Organization reported that annually, complications of HTN accounted for 9.4 million deaths worldwide.6

Based on a systematic review in Iran, the estimated overall prevalence of HTN among those aged 30-55 years and older than 55 years was reported to be around 23% and 50%, respectively.6 This prevalence was lower in men than in women and it increased by about 0.5% per each year of increase in the mean age of the subjects.6 Other studies reported HTN prevalence rates of 21.2-41.8%. Among the Iranian adult population, the prevalence of HTN was higher in females, older age groups, illiterate individuals, poor people, and urban residents.7-12

Information on the prevalence of chronic conditions, such as HTN, and its predictors in different societies are needed to aid disease management. This study was conducted to assess the prevalence of HTN and associated factors in Mashhad, Iran, in 2015.

Materials and Methods

This was a cross-sectional study of the adult population (> 16 years) in Mashhad, a metropolitan area in the northeast of Iran in 2015. A sample size of 2700 was required, by considering all the assumption and a 30% attrition rate and finally multiplied by 3 for clustering design. Multi-stage cluster random sampling was used.

In the first stage of the study, the population was divided based on the population covered in each district (central health centers numbers 1, 2, 3 and 5). Then, five clusters (health centers) were selected randomly in each district. To allocate samples at the cluster level, the probability proportional to size (each district) method was used. In the second stage of the study, streets were selected randomly, and interviewers who had taken part in 2-day training workshop on data collection visited the homes of potential participants (they were masters in nursery or midwifery who were coworkers in this research). At each house, using a checklist, the interviewers obtained information on the demographic characteristics and socioeconomic status of the residents (maximum of two different genders from a family). The participants who agreed to take part in the study underwent a physical examination at their nearest health center by a general practitioner who had received training (three sessions) in how to minimize measurement and inter-observer bias.

The exclusion criteria were absent in any step of the study, passengers who are not resident in Mashhad.

In this study, sedentary behavior refers to any sitting or reclining posture and included television viewing, video game playing, computer use, driving automobiles and reading. If the respondent says yes to the question that they were spending more time in this activity daily, we considered them yes.

Obesity refers to a body mass index (BMI) ≥ 30.

Diabetes is defined as a fasting blood sugar (FBS) of > 126 mg/dl.13

A cigarette smoker refers to someone who smokes more than one cigarette per day or uses a hookah each day.

Drug abused was asked by a question “have you ever used illegal substances”?

In this study, the 3600 IR Rials was equal to 1 US dollar (exchange rate).

The seven blood pressure (BP) categories were defined as follows: “Optimal” SBP < 120 mmHg and DBP < 80 mmHg); “normal” (SBP 120-129 mmHg and/or DBP 80-84 mmHg); high normal (SBP 130-139 mmHg and/or 85-89 mmHg); Stage 1 HTN (mild) (SBP 140-159 and/or DBP 90-99 mmHg); Stage 2 HTN (moderate) (SBP 160-179 and/or DBP 100-109 mmHg); Stage 3 HTN (severe) (SBP 180-209 and/or DBP 110-119 mmHg); HTN Stage 4 (very severe) (SBP ≥ 210 and/or DBP ≥ 120).14

BP readings were obtained from the right arm of each subject, with the subject in a sitting period after a period of relaxation for 5 minutes using a standard mercury sphygmomanometer (Omron M6 Comfort, BP Monitors, Japan). Each subject’s heart rate was also measured. The BMI was calculated based on the following formula: weight (kg) divided by the height (m2). Body weight was measured using an analog scale, with the participants wearing single layer of clothing. Height was measured using a stadiometer. Blood samples were taken at health centers after 12 hours of fasting to determine the lipid profile, FBS, serum creatinine (Cr), and hemoglobin (Hb). All the samples were sent to a dedicated laboratory for analysis.

The study was conducted in accordance with the principles of the Declaration of Helsinki (1996 version) and good practice standard. All subjects signed informed consent forms.

Descriptive statistical measures, including measures of central tendency and dispersion, were used to describe the data. The continues variable presented by mean ± standard deviation (SD) and qualitative variable described by number (percent). The distribution of data was checked by one sample Kolmogorov-Smirnov test, and according to the result of this test, the appropriate test was selected.

Chi-square )nominal variable), Kruskal-Wallis, Mann-Whitney (for quantitative or ordinal variables), and binary logistic regression test is used to estimate the probability of HTN based on independent variables All reported P values are based on two-sided tests and compared to a significance level of 0.05. SPSS software for Windows (version 11.5, SPSS Inc., Chicago, IL, USA) was used for all the analyses.

Results

The study consisted of 2974 participants (age ranged 16-90). The prevalence of HTN in the study population was 22% (25.9% in males and 20% in females). The overall average age of participants was 43.52 ± 14.69 years old; men had a significantly higher age in comparison with female [46.10 ± 15.75 and 42.12 ± 13.89 (P < 0.001), respectively].

Table 1 shows the BP distribution of males and females. The total distribution was statistically different in both genders (P < 0.001). Moreover, based on the American Heart Association writing committee,15 elderly was defined as those ≥ 65 years of age and accordingly we compared the distribution of different BP categories in our elderly and non-elderly subjects in table 1, which showed that a significantly greater number of subjects in each gender was known to be < 65-year-old.

Table 1

Blood pressure (BP) distribution in males and females

BP	Sex	Age		P	Sex	Age		P	Total	P Total comparison in two gender
	n (%)	n (%)			n (%)	n (%)
	Female	< 65	≥ 65		Male	< 65	≥ 65		n (%)
	(n =1930)	1840 (95.4)	88 (4.6)		(n = 1044)	922 (88.6)	119 (11.4)		(n = 2974)
Optimal*	1378 (71.4)	1319 (73.6)	22 (25.6)	< 0.001	634 (60.7)	581 (64.6)	35 (29.9)	< 0.001	2012 (67.7)	< 0.001
Normal	152 (7.9)	136 (7.6)	12 (14.0)		132 (12.6)	111 (12.3)	17 (14.5)		284 (9.6)
High normal	14 (0.7)	12 (0.7)	1 (1.2)		8 (0.8)	7 (0.8)	1 (0.1)		22 (0.7)
HTN	386 (20.0)	325 (18.0)	51 (59.3)		270 (25.9)	200 (22.2)	65 (49.3)		656 (22.0)
Mild	222 (11.5)	189 (10.5)	26 (30.2)		171 (16.4)	133 (14.8)	35 (29.9)		393 (13.2)
Moderate	127 (6.6)	103 (5.7)	22 (25.6)		78 (7.5)	55 (6.1)	21 (17.9)		205 (6.9)
Sever	31 (1.6)	29 (1.6)	2 (2.3)		16 (1.5)	8 (0.9)	8 (0.6)		47 (1.6)
Very sever	6 (0.3)	4 (0.2)	1 (1.2)		5 (0.5)	4 (0.4)	1 (0.9)		11 (0.3)

n (%). Based on chi-square test

HTN: Hypertension; BP: Blood pressure

According to the new category that consisted of three major groups (optimal, normal and hypertensive), we compared the underlying factors in these groups. As demonstrated in table 2, the following factors were statistically different between the groups: Educational level (P < 0.001), job (P < 0.001), marital status (P < 0.001), drug abuse (P = 0.040), sedentary behavior (P = 0.010), and BMI (P < 0.001).

Table 2

Comparison of underlying factors in the three groups [optimal blood pressure (BP), normal BP and Hypertension (HTN)]

Variables	Optimal (n = 2011)	Normal BP (n = 307)	HTN (n = 656)	P
Educational level
Illiterate	172 (45.1)	49 (13.0)	160 (41.9)	< 0.001
Elementary	562 (59.7)	106 (11.3)	273 (29.0)
Not completed high school	400 (75.3)	53 (10.0)	78 (14.7)
High school diploma	568 (78.9)	67 (9.4)	85 (11.7)
College diploma	119 (76.0)	12 (8.0)	25 (16.0)
License and higher degree	190 (77.7)	18 (7.4)	37 (14.9)
Job
Jobless	100 (57.3)	19 (10.8)	56 (31.9)	< 0.001
Employee	177 (58.8)	41 (13.5)	83 (27.7)
worker	92 (64.4)	20 (14.1)	31 (21.5)
Free lancer	375 (66.5)	69 (12.3)	120 (21.2)
Student	121 (91.4)	5 (3.9)	6 (4.7)
Housewife	1151 (69.4)	154 (9.3)	354 (21.3)
Marital status
Single	249 (86.9)	17 (5.8)	21 (7.3)	< 0.001
Married	1686 (66.9)	267 (10.6)	567 (22.5)
Widow	71 (46.9)	22 (14.3)	58 (38.8)
Divorced	9 (58.8)	2 (11.8)	5 (29.4)
Tobacco use
Yes	158 (63.1)	27 (10.8)	66 (26.1)	0.240
No	1852 (68.0)	280 (10.3)	591 (21.7)
Drug abuse
Yes	33 (60.4)	2 (4.2)	19 (35.4)	0.040
No	1974 (67.6)	307 (10.5)	639 (21.9)
Sedentary behavior
Yes	909 (66.8)	121 (8.9)	331 (24.3)	0.010
No	1097 (68.0)	184 (11.4)	332 (20.6)
BMI
Low	93 (91.7)	1 (1.0)	7 (7.3)	< 0.001
Normal	792 (76.8)	88 (8.5)	152 (14.7)
Over weight	768 (64.9)	136 (11.5)	279 (23.6)
Obesity	295 (58.7)	58 (11.5)	150 (29.8)
Very obesity	72 (46.6)	20 (12.8)	63 (40.6)
Diabetes
Yes	111 (44.9)	38 (15.6)	98 (39.5)	< 0.001
No	1869 (68.6)	294 (10.8)	561 (20.6)

Based on chi-square test. BMI: Body mass index; BP: Blood pressure; HTN: Hypertension

Table 3 shows the comparison of the mean lipid profile, FBS, serum Cr, urine Cr, and Hb in the three groups according to gender. As can be seen from the table, FBS, cholesterol, triglyceride (TG), low-density lipoprotein (LDL), and serum Cr were higher in the hypertensive group of women. FBS, cholesterol, TG, LDL and, surprisingly, high-density lipoprotein were higher in the hypertensive group of men.

Table 3

Comparison of the lipid profile, fasting blood sugar (FBS), serum creatinine (Cr), urine Cr and hemoglobin (Hb) according to blood pressure (BP) and gender

BP	Female (n = 1930)				Male (n = 1044)
	Optimal (n = 1378)	Normal (n = 166)	HTN (n = 386)	P	Optimal (n = 634)	Normal (n = 140)	HTN (n = 270)	P
FBS	89.88 ± 23.87	99.50 ±33.40	104.03 ± 36.94	< 0.001	97.97 ± 31.56	106.71 ± 45.54	107.42 ± 43.51	0.002
Cholesterol	175.63 ± 38.24	187.27 ± 39.46	193.52 ± 40.10	< 0.001	176.53 ± 35.97	184.79 ± 40.57	190.41 ± 41.61	< 0.001
TG	123.69 ± 100.51	142.14 ± 79.71	160.34 ± 74.92	< 0.001	148.06 ± 85.10	171.05 ± 100.01	173.56 ± 92.76	0.002
LDL	107.43 ± 26.65	113.11 ± 26.48	114.78 ± 29.88	< 0.001	104.79 ± 26.91	108.00 ± 26.53	110.22 ± 33.79	0.040
HDL	43.53 ± 10.47	47.04 ± 11.64	46.65 ± 12.25	< 0.001	42.38 ± 9.99	44.66 ± 10.13	45.40 ± 13.01	0.001
Serum Cr	1.03 ± 0.21	1.07 ± 0.20	1.10 ± 137.00	< 0.001	1.21 ± 0.22	1.27 ± 0.31	1.25 ± 0.28	0.400
Urine Cr	131.91 ± 71.10	114.81 ± 73.58	108.36 ± 56.07	< 0.001	150.19 ± 75.83	134.37 ± 81.39	129.85 ± 65.28	0.010
Hb	13.32 ± 1.55	13.57 ± 1.57	13.38 ± 1.59	0.310	15.19 ± 1.86	14.79 ± 1.89	14.93 ± 1.55	0.370

Based on Kruskal–Wallis test; Hb: Hemoglobin; Cr: Creatinine; HDL: High-density lipoprotein; LDL: Low-density lipoprotein; BP: Blood pressure; HTN: Hypertension; FBS: Fasting blood sugar; TG: Triglyceride

In the binary logistic regression (enter model) of the predictors of HTN in this population, age, gender and obesity were meaningful predictors (Table 4).

Table 4

Binary logistic regression (enter model) of the predictors of hypertension (HTN) in this population

Variables	B	SE	Wald	df	Significant	OR	95% CI for OR
							Lower	Upper
Gender (Ref: F)	0.329	0.142	5.377	1	0.020	1.390	1.052	1.836
Educational level (Ref:Illitrate)			8.686	5	0.122
Elementary	−0.283	0.177	2.548	1	0.110	0.753	0.532	1.067
Not completed high school	−0.614	0.232	7.038	1	0.008	0.541	0.344	0.852
High school diploma	−0.566	0.234	5.828	1	0.016	0.568	0.359	0.899
College diploma	−0.392	0.353	1.232	1	0.267	0.676	0.338	1.350
License and higher degree	−0.459	0.334	1.882	1	0.170	0.632	0.328	1.217
Marital status (Ref:Single)			4.754	3	0.191
Married	−0.432	0.369	1.368	1	0.242	0.649	0.315	1.339
Widow	−0.822	0.455	3.261	1	0.071	0.439	0.180	1.073
Divorced	−1.818	1.307	1.933	1	0.164	0.162	0.013	2.105
Ethnicity (Ref: Fars)			5.599	6	0.470
TURK	0.054	0.265	0.041	1	0.840	1.055	0.628	1.773
Kurd	−0.793	0.484	2.682	1	0.101	0.452	0.175	1.169
Baloch	−18.878	40192.970	< 0.001	1	1.000	< 0.001	< 0.001	< 0.001
Lurs	2.630	1.781	2.181	1	0.140	13.868	0.423	454.593
Turkmens	−18.588	40192.970	0.000	1	1.000	< 0.001	< 0.001	< 0.001
Afghani	0.243	0.311	0.609	1	0.435	1.275	0.693	2.348
Family income	0.000	0.000	0.028	1	0.866	1.000	1.000	1.000
Smoking (Ref:No)	0.071	0.215	0.109	1	0.741	1.074	0.705	1.635
Drug abuse (Ref:No)	0.630	0.401	2.470	1	0.116	1.877	0.856	4.116
Sedantary behavior (Ref: No)	−0.197	0.128	2.383	1	0.123	0.821	0.640	1.055
Obesity	0.090	0.014	44.242	1	< 0.001	1.095	1.066	1.124
Age	0.069	0.006	137.917	1	< 0.001	1.071	1.059	1.084
Constant	−6.278	0.566	122.851	1	< 0.001	0.002

For doing binary logistic regression, we defined two groups; hypertensive (HTN mild, moderate, severe and very severe) and normal (optimal, normal, high normal). Hosmer and Leme show test: chi-square: 11.905, P = 0.15. HTN: Hypertension; Df: Degrees of freedom; 95% Cl: Confidence interval; SE: Standard error; OR: Odds ratio

The sensitivity of the model was 53%, and its specificity was 81%.

Discussion

The prevalence of HTN in this population was 22% (25.9% in males and 20% in females). Interestingly, smoking and drug abuse were more prevalent in men (14.9% and 3.8%, respectively), but the sedentary behavior was more prevalent in women (51%). A total of 71.4% of women and 60.7% of men had optimal BP.

The urban HEART-2 study, which was conducted in 2011 in Tehran, Iran, reported a prevalence of self-reported HTN of 5.27% in the population (3.83% in men and 6.64% in women) (P < 0.001).16 To some extent, the difference in the prevalence of HTN in that study compared to that of this study may be explained by the different years of the two studies that certainly affect the prevalence rate.

Furthermore, the findings of the Urban HEART-2 were based on self-report data, which are subject to reporting bias. Increased awareness by the public of their HTN status may also increase the likelihood of reporting.

The higher prevalence of HTN found in this study (25.9% in men and 20%% in women) is similar to that reported in most previous studies8,17-19 although some discordance with previous reports was observed.12,20-23 The discordance may be due to the self-report questionnaire design of the study and the fact that women are generally more likely than men to say they are unwell.

In accordance with other reports, this study showed a significant association between obesity and BP. In a previous study of 3423 adults aged 30-65 years in China, 1929 adults in the Philippines and 7957 adults in the U.S., a high BMI was correlated with increasing rates of HTN.24 A study in Denmark of 13,577 adolescents aged 15-20 years demonstrated an association between fitness and BMIs with HTN.25 Another study reported that obesity and being overweight could increase BP via physiological changes, including increased insulin resistance, elevated activity of the renin-angiotensin system in the kidney and increased pressure on peripheral vessels.26 The results of this study, which showed that BP increased with age, are similar to those of other reports.11,27 In a survey in the U.K., after adjustment for age, BMI, alcohol and social class, a significantly higher SBP was found in older men and in heavy and moderate smokers than in never smokers, whereas no such differences were seen in DBP.28

In the binary logistic regression after adjustment for other variables, smoking was not a meaningful predictor of HTN.

Furthermore, in this study, after adjustment for other variables, sedentary behavior was not a meaningful predictor of HTN. In a dynamic cohort study (SUN Study)29 of 11,837 Spanish university graduates, with a mean age of 36 years, self-reported total sedentary behavior (i.e., interactive and noninteractive) was directly associated with a higher risk of HTN (hazard ratio: 1.48; 95% confidence interval: 1.01-2.18.29 In a subtype analyses, the same study reported that interactive sedentary behavior (driving and computer use) but not noninteractive sedentary behavior (television viewing and sleeping) was associated with a higher risk of HTN.29

The difference in the results of that study compared to the current one may be due to the different populations and dissimilar lifestyles in Iranian and Spanish culture and the differences in the age range of the participants in the studies.

Previous research indicated that the prevalence of HTN was strongly highly associated with social class, as measured by education, occupation or income.30 However, in this study, neither educational level nor family income was a meaningful predictor of HTN. In common with the findings of the current study, a study conducted in China also found no association between education and BP.31 In another study in Iran, it was found significant relationships between HTN and education.32

The results in this study should be interpreted with caution, as the study contains a number of limitations. First, the design of the study was cross-sectional, which could result in reverse causality. Second, the sample population consisted of urban citizens. Third, we did not assess health care access. Further studies should consider the roles of diet and health care access as risk factors for high BP and HTN.

Conclusion

We hope that this study facilitates a better understanding of the relationship between anthropometric indicators and demographic factors and HTN. Continued and accelerating urbanization are likely to increase the prevalence of HTN.33 Urgent preventive interventions on a national scale are needed to target HTN, which is highly prevalent. Given the close relationship between obesity and various diseases, including HTN, practical solutions, including lifestyle interventions, need to be developed.