Prehypertension and hypertension among older adults: prevalence, awareness, treatment, control and associated factors - findings from Iranian STEPS survey (2016 and 2021)

Abstract

Background

Hypertension is a major public health issue and especially in the older adults, it is a leading cause of morbidity and mortality.

Aims

This study assessed the prevalence, awareness, treatment, and control of Hypertension among Iranian adults aged 60 years and older.

Methods

we analyzed data from the Iranian STEP-wise Approach to Non-Communicable Disease Risk Factor Surveillance (STEPS) conducted in 2016 and 2021 across all provinces of Iran. Participants were marked as hypertensive based on the ESC/ESH guidelines. 3874 participants from STEPS 2016 and 4020 participants from STEPS 2021 were included and analyzed using survey package in R statistical software.

Results

Hypertension rates rose between 2016 and 2021 from 54.74% to 60.57% in males and from 65.54% to 71.76% in females. Hypertension treatment increased from 26.53% to 36.03% in males and from 39.25% to 53.70% in females. In 2016, hypertension control rates were 23.06% in males and 24.03% in females. In 2021 these levels rose to 34.28% in males and 36.13% in females. Obesity was strongly associated with hypertension (odds ratio (OR): 2.75, p < 0.001), whereas higher education appeared to be inversely associated with hypertension (OR: 0.64, p < 0.001).

Discussion

Despite the improvement in treatment and control of hypertension among older adults in Iran, hypertension prevalence remains high and on the rise. To address this problem, efforts should focus on weight management, enhanced health education, and expanded screening programs.

Conclusion

Given observed sex and socioeconomic disparities in awareness, treatment, and control, equity-oriented publicci and improved access to care warrant further evaluation in prospective or implementation studies. Additionally, promoting higher educational attainment may contribute to better long-term control of hypertension.

Introduction

Hypertension(HTN) is defined as resting systolic blood pressure (SBP) ≥ 140 mmHg or diastolic blood pressure (DBP) ≥ 90 mmHg, or self-reported usage of antihypertensive medications [1]. It ranks as one of the primary causes of premature death and is closely linked to an elevated risk of cerebrovascular, cardiovascular and renal diseases [2, 3]. Each 2 mmHg rise in systolic blood pressure correlates with a 10% increase in stroke risk and a 7% increase in the risk of ischemic heart disease [4]. The prevalence of HTN has now exceeded 1.2 billion individuals in the world, with approximately two-thirds of those affected residing in low- and middle-income countries [1]. High range of factors impact the prevalence, including sex, age, income level, education, physical activity, marital status, smoking habits [5].

The global population is aging _projected to rise to 16% of individuals aged 65 and older by 2050, up from 9% in 2019, with a substantial concentration in Asia_ [6]. This demographic shift results from longer life expectancies and decreasing fertility rates [7]. A study, gathered in United States, shows that the prevalence of HTN increases significantly with age, soaring from 54.5% in adults aged 40 to 59 years to 74.5% in those aged 60 and above [8].

Apart from the high prevalence of diagnosed HTN, many older adults with HTN remain unaware of their condition due to experiencing atypical symptoms or limited access to healthcare [9], which exposes them to higher risks of hypertension complications [10]. However, not all individuals, aware of their HTN receive treatment or successfully manage their blood pressure [11, 12]. Consequently, evaluation of HTN control in older adults becomes increasingly urgent. These factors highlight the remarkable need for knowledge regarding the awareness, treatment, and control rates of HTN among older adults.

Despite various studies reporting differing prevalence rates of HTN in Iran, our understanding of the condition remains inconsistent, especially in the older adult population. A 2023 systematic review and meta-analysis reports a 26% prevalence of hypertension in Iranian adults using the JNC7 guideline, suggesting that this prevalence could rise to over 50% if the ACC/AHA guideline were applied [13]. Given the higher age of our population, this figure would rise even further.

Therefore, there is a critical need for further research focusing on this population. Using ESC/ESH guideline with higher blood pressure thresholds compared with the JNC7 and ACC/AHA guidelines, prevents over-diagnosis which could lead to inappropriate treatment in this high-risk population. Furthermore, comparing the findings from 2016 to 2021 allows us to examine changes in hypertension prevalence and its associated factors over time and gain a clearer understanding of blood pressure patterns in the older adult population.

This research aims to address mentioned gaps by utilizing data from the 2016 and 2021 Iranian STEPS survey. In doing so, it aims to facilitate informed interventions and contribute to the global discourse on aging populations and non-communicable diseases.

Method

Study design and population

This study applied a cross-sectional design, with the 2016 and 2021 STEPS survey data among community-dwelling older adults in rural and urban areas of 31 provinces of Iran. The STEPS approach was developed by the World Health Organization (WHO) in 2002 as a reliable approach for monitoring non-communicable diseases (NCDs) [14]. The STEPS strategy gathers information in three principal steps: interview (step 1), physical and anthropometric measurements (step 2), and biochemical analysis of blood and urine samples (step 3) [15].

In both survey waves, participants were selected using a multistage cluster sampling design with probability proportional to population size. In 2016, a total of 3,105 clusters were sampled nationwide, with ten eligible adults recruited from each cluster. In 2021, 3,176 clusters were selected from urban and rural areas across all provinces, with approximately 9–10 adults sampled per cluster, yielding data from 27,874 participants. The national postal code database served as the sampling frame, and all data were collected through face-to-face interviews conducted by trained personnel.

Participants were excluded if they had not been resident in Iran for more than six months, lacked a national identification number or were unable to complete each step of the study procedures, including responding to questionnaires (due to cognitive or communication impairments), undergoing anthropometric measurements (due to physical limitations), or providing laboratory samples. Further details on the procedure are found in the 2016 and 2021 Iranian STEPS survey protocols [16, 17]. In our study, we included participants aged 60 and above from 2016 to 2021 survey and excluded participants with missing values needed for the study.

Of the 31,050 respondents to the main survey in 2016, 4,205 met our study’s inclusion criteria. yet, 331 participants (7.87%) were excluded due to incomplete data. As a result, the final sample for analysis included 3,874 participants. The detailed election process for participants is illustrated in Figure 1.

Fig. 1.

Flowchart of study population selection from the 2016 STEPS survey, starting with 4,205 participants. After excluding individuals with missing data, 3,874 participants were included in the final analysis. Numbers of missing values for key variables are indicated.

Out of 27,874 participants of the main survey in this 2021 study, 4,202 met the inclusion criteria of our study. After excluding 182 participants (4.33%) for having incomplete data, the final sample for analysis consisted of 4020 participants. Figure 2 illustrates the selection process.

Fig. 2.

Diagram shows the selection process from 2021 STEPS survey. Starting with 4,202 participants and including 4.020 participants in the final analysis after excluding individuals with missing data. Numbers of missing values for key variables are shown in the diagram.

Definition of variables

Hypertension awareness was defined as participants reporting a prior diagnosis of HTN by a healthcare providers [18]. Hypertensive individuals were defined as systolic blood pressure (SBP) ≥ 140 mmHg or diastolic blood pressure (DBP) ≥ 90 mmHg in accordance with 2018 ESC/ESH guidelines [19]. According to the same guideline, participants were considered to have high-normal blood pressure with 130 mmHg < SBP<139 mmHg and 85 mmHg < DBP<89 mmHg, which in this article we referred to as prehypertension. We used the ESC/ESH guidelines due to their more conservative diagnostic threshold (≥140/90 mmHg), which better aligns with our study’s focus on elderly population, lowering the risk of over-diagnosis and over-treatment in this vulnerable group. According to the ESC/ESH guideline HTN control was defined as the hypertensive population who had their blood pressure within the normal range ((SBP) < 140 mmHg or diastolic blood pressure (DBP) < 90 mmHg) while taking antihypertensive medication [19]. HTN treatment was defined as hypertensive individuals who reported using antihypertensive medications.

Education was classified into three groups based on the number of completed years of schooling: 0 to 6 years, 7 to 12 years and more than 12 years of education. Height was measured ensuring the back of the head, hips, and heels were in alignment with the standard meter. Weight was measured using a standard digital scale (Inofit) with an accuracy of ± 100 g. Body Mass Index (BMI) was calculated by dividing weight (Kg) by height (m²) and categorized into 4 groups. Underweight (< 18.5 kg/m²), normal weight (18.5–24.9 kg/m²), overweight (25.0–29.9 kg/m²), and obese (≥30 kg/m²) [20]. Waist circumference (WC) was assessed following an exhalation at the midpoint between the lower edge of the last rib and the iliac crest. Hip circumference (HC) measurement was on the widest part of the hip. For measuring blood pressure, we used standard Beurer sphyngomanometers with standard cuff sizes. After the individual had remained still for 15 min in sitting position. Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured three times on the brachial artery at 3-minute intervals on a single visit. The final value was the average of second and third readings. Systolic blood pressure with a plausible range of 40–300 mm Hg and Diastolic blood pressure with a plausible range of 30–200 mm Hg. All instruments were calibrated during the survey’s preparation phase [17].

The wealth index was calculated using principal component analysis (PCA) on 59 household assets of the participants and was divided into five quantiles, ranging from the poorest to the wealthiest [21]. Basic Insurance comprises vital health care services, while the complementary insurance includes broader health coverage through private insurance firms. Measurements of physical activity were performed using the Global Physical Activity Questionnaire (GPAQ), categorizing participants into two groups according to their Metabolic Equivalent of Task (MET)-minutes (MET index 600, met index ) [22]. Participants were categorized into three groups of High, moderate and low nutritional quality based on the number of meals and other dietary complements as further described in the study protocol [17]. Smoking status was categorized into four groups: non-smoker (never exposed to tobacco products), smoker (used tobacco products within the past year), past-smoker (quit using tobacco products more than a year ago), second-hand smoker (exposed to second-hand smoke within the past 30 days and were not current and pass smoker). Positive Complementary or Alternative Medicine (CAM) was defined as self-reported current use of traditional medicine, herbal medicine, and other products except for conventional medicine.

Blood samples were taken 12 h past an overnight fast and measured by a certified auto analyzer (Roche-Hitachi Cobas C311, High-Technologies Corporation, Tokyo, Japan) approved by the reference laboratory. Biochemical factors included FPG (fasting plasma glucose), HbA1C (Hemoglobin A1C), Serum total cholesterol, Serum LDL (low-density lipoprotein), Serum HDL-C (high-density lipoprotein cholesterol), Serum triglyceride [17].

Data gathering and statistical analysis

Data were collected electronically using tablets by trained interviewers. Following data collection, two independent biostatisticians performed data cleaning and weighting procedures, with any inconsistencies resolved by a third expert. To obtain nationally and provincially representative estimates, data cleaning and weighting were conducted in accordance with the STEPS 2021 protocol, incorporating adjustments for overall and step-specific non-response, post-stratification by age, sex, and area within each province, and final calibration using the combined weights. Details of the general STEPS methodology have been described previously [16, 17]. Complete-case analysis was performed. Categorical variables were summarized as frequencies and percentages with 95% confidence intervals (CIs), and quantitative variables as mean ± 95% confidence intervals (CIs). For evaluating factors associated with hypertension, candidate variables were initially selected based on a review of relevant literature. Before model building, we assessed multicollinearity among these variables using the Variance Inflation Factor (VIF), and all demonstrated acceptable thresholds (VIF < 5). Variables included in the multiple logistic regression model were determined through a forward stepwise selection procedure. Results were reported as adjusted odds ratios (ORs) with 95% CIs, and statistical significance was defined as a two-sided p-value < 0.05. All statistical analyses were performed using R software version 4.0.5, and all analyses incorporated sampling weights and design characteristics using the survey package [23].

Results

Prevalence of prehypertension, hypertension, awareness, treatment and control

The study found that prehypertension prevalence declined from 2016 to 2021 for both genders with higher decline rates among males (from 29.87% [27.41% to 32.33%] to 23.84% [20.94 to 26.73%]). A notable decrease was seen among individuals in the lowest wealth category (dropping from 26.69% [23.64% to 29.73%] to 17.51% [14.6% to 20.42%]), obese individuals (from 21.81% [18.62% to 24.99%] to 14.21% [11.41% to 17.02%]), and retired population (from 31.05% [27.24% to 34.85%] to 22.02% [18.24% to 25.81%]). Education appeared to have a positive association with prehypertension, as those with higher education levels had the highest prevalence in both surveys (Table 1).

Table 1.

Distribution of demographic, behavioral and health-related characteristics and their association with hypertension outcomes in 2016 and 2021

variable	Prehypertension (%) (95% Confidence interval)		Hypertension (%) (95% Confidence interval)		Hypertension awareness (%) (95% Confidence interval)		Hypertension treatment (%) (95% Confidence interval)		Controlled hypertension (%) (95% Confidence interval)
	2016	2021	2016	2021	2016	2021	2016	2021	2016	2021
Sex
Male	29.87 (27.41–32.33)	23.84 (20.94–26.73)	54.74 (52.08–57.39)	60.57 (57.33–63.80)	34.53 (31.96–37.11)	39.23 (36.19–42.27)	26.53 (24.10-28.96)	36.03 (33.04–39.02)	23.06 (20.02–26.09)	34.28 (30.24–38.32)
Female	22.25 (20.08–24.42)	17.31 (14.87–19.74)	65.54 (63.00-68.08)	71.76 (68.95–74.57)	48.92 (46.22–51.62)	56.41 (53.16–59.67)	39.25 (36.62–41.88)	53.70 (50.46–56.93)	24.03 (21.09–26.96)	36.13 (32.22–40.03)
Age
60 to 69 years old	28.30 (26.01–30.58)	22.69 (20.19–25.19)	57.28 (54.80-59.77)	61.96 (59.20-64.73)	38.10 (35.67–40.53)	44.84 (42.16–47.52)	29.68 (27.39–31.97)	41.42 (38.77–44.08)	23.54 (20.61–26.47)	34.93 (31.77–38.09)
70 to 79 years old	23.07 (20.29–25.86)	17.23 (13.91–20.55)	63.54 (60.18–66.89)	73.06 (69.13-77.00)	47.62 (44.12–51.12)	50.23 (45.41–55.04)	38.46 (35.00-41.93)	48.66 (43.90-53.41)	24.79 (20.92–28.66)	36.15 (29.80-42.49)
80 + years old	21.30 (17.45–25.15)	14.95 (10.64–19.26)	67.21 (62.69–71.73)	76.38 (71.21–81.56)	47.41 (42.26–52.55)	63.33 (57.01–69.65)	37.14 (32.08–42.20)	59.51 (52.98–66.04)	21.41 (16.72–26.09)	34.89 (26.60-43.19)
Residency
Urban	26.20 (24.06–28.35)	20.72 (18.39–23.04)	59.96 (57.55–62.36)	65.82 (63.16–68.48)	41.59 (39.15–44.03)	47.63 (44.91–50.34)	32.54 (30.20-34.89)	44.86 (42.17–47.55)	24.59 (21.77–27.40)	36.97 (33.51–40.43)
Rural	25.46 (23.07–27.86)	19.95 (17.24–22.66)	60.95 (58.27–63.63)	67.56 (64.45–70.67)	42.58 (39.86–45.30)	48.83 (45.51–52.15)	34.12 (31.50-36.74)	45.24 (41.94–48.55)	21.53 (18.67–24.39)	29.70 (26.06–33.33)
Education
0–7 years	24.37 (22.62–26.13)	18.42 (16.63–20.21)	62.36 (60.35–64.37)	70.26 (68.10-72.42)	44.02 (41.94–46.10)	51.78 (49.33–54.24)	34.58 (32.58–36.59)	48.82 (46.38–51.26)	22.83 (20.60-25.05)	33.77 (30.67–36.86)
7–12 years	28.10 (23.31–32.90)	22.34 (16.02–28.65)	54.52 (48.87–60.16)	60.09 (52.23–67.96)	34.75 (29.06–40.45)	38.11 (30.22-46.00)	27.08 (21.54–32.62)	36.37 (28.53–44.22)	20.23 (14.46–26.01)	37.41 (26.62–48.21)
12 and more years	34.71 (28.18–41.25)	26.87 (20.84–32.91)	52.78 (46.25–59.31)	55.34 (49.07–61.60)	36.07 (29.99–42.16)	39.16 (33.46–44.86)	29.84 (24.12–35.56)	35.72 (30.17–41.27)	34.90 (25.46–44.35)	40.76 (32.99–48.52)
Employment
Unemployed	21.49 (19.53–23.44)	17.41 (15.13–19.69)	66.36 (64.05–68.67)	71.41 (68.75–74.07)	48.89 (46.36–51.41)	55.26 (52.20-58.31)	38.23 (35.77–40.69)	52.10 (49.06–55.14)	23.89 (21.16–26.61)	34.96 (31.19–38.73)
Employed	32.22 (28.36–36.09)	27.70 (22.47–32.92)	52.04 (48.01–56.07)	54.36 (48.77–59.94)	30.58 (26.83–34.34)	32.21 (27.61–36.81)	23.83 (20.30-27.35)	29.75 (25.28–34.22)	19.44 (15.31–23.57)	30.70 (24.58–36.82)
Retired	31.05 (27.24–34.85)	22.02 (18.24–25.81)	53.16 (49.08–57.24)	63.76 (59.52–68.01)	35.22 (31.31–39.13)	43.83 (39.59–48.07)	28.73 (24.98–32.49)	40.96 (36.77–45.15)	26.00 (21.03–30.96)	38.09 (32.61–43.56)
Marital status
Married	27.41 (25.47–29.35)	21.99 (19.74–24.25)	57.89 (55.75–60.03)	64.40 (61.85–66.94)	39.87 (37.74–42.01)	44.93 (42.38–47.48)	31.28 (29.23–33.32)	41.69 (39.18–44.20)	22.88 (20.47–25.29)	34.42 (31.12–37.71)
Un-married	21.30 (18.30-24.31)	15.48 (12.22–18.74)	67.97 (64.42–71.53)	72.56 (68.59–76.52)	48.47 (44.52–52.43)	58.27 (53.77–62.76)	38.76 (34.95–42.58)	56.30 (51.82–60.79)	25.57 (21.19–29.95)	38.00 (32.63–43.36)
Wealth index
Poorest quintile	26.69 (23.64–29.73)	17.51 (14.6-20.42)	60.48 (57.07–63.89)	69.56 (65.91–73.21)	42.82 (39.27–46.37)	49.14 (44.84–53.45)	32.82 (29.37–36.27)	46.38 (42.15–50.62)	24.46 (20.36–28.56)	34.04 (27.79–40.30)
Lower middle quintile	23.83 (20.81–26.84)	19.42 (15.97–22.87)	63.51 (60.03–66.99)	67.12 (62.87–71.38)	42.57 (39.06–46.08)	51.45 (46.97–55.93)	33.27 (30.00-36.53)	47.98 (43.54–52.42)	21.37 (17.74–25.01)	35.13 (29.67–40.59)
Middle quintile	22.72 (19.47–25.97)	18.62 (14.90-22.35)	63.84 (59.90-67.78)	67.52 (62.51–72.53)	42.96 (38.70-47.21)	48.78 (43.85–53.71)	34.47 (30.31–38.63)	45.54 (40.67–50.41)	22.81 (17.79–27.82)	37.28 (31.64–42.92)
Upper middle quintile	28.95 (24.48–33.41)	20.77 (16.91–24.63)	55.72 (51.05–60.39)	66.64 (61.96–71.31)	42.15 (37.56–46.74)	46.86 (41.78–51.93)	33.44 (29.04–37.85)	43.37 (38.33–48.40)	25.61 (20.66–30.56)	33.53 (27.76–39.31)
Richest quintile	30.15 (24.77–35.54)	28.48 (21.42–35.53)	54.05 (48.26–59.83)	58.06 (51.03–65.08)	37.58 (31.84–43.32)	41.26 (34.59–47.93)	30.46 (24.94–35.99)	39.57 (32.95–46.18)	25.86 (18.88–32.84)	37.56 (29.25–45.87)
Smoking
Non-smoker	25.48 (23.34–27.63)	21.44 (18.86–24.02)	61.11 (58.71–63.51)	66.70 (63.92–69.48)	43.12 (40.65–45.59)	48.64 (45.77–51.51)	34.01 (31.63–36.39)	45.55 (42.72–48.38)	23.79 (21.03–26.56)	35.41 (31.77–39.05)
Current smoker	29.03 (23.61–34.45)	24.16 (19.11–29.22)	53.38 (47.48–59.27)	55.82 (49.51–62.13)	30.38 (24.67–36.09)	35.65 (28.97–42.32)	22.13 (16.81–27.44)	33.89 (27.18–40.59)	18.16 (10.19–26.12)	37.94 (28.02–47.85)
Past smoker	27.55 (23.22–31.87)	16.55 (11.81–21.30)	57.16 (52.52–61.80)	72.02 (65.46–78.59)	40.32 (35.92–44.72)	51.44 (44.35–58.54)	31.82 (27.66–35.97)	47.22 (40.13–54.31)	24.95 (19.98–29.92)	39.04 (30.78–47.29)
Second-hand smoker	24.46 (20.55–28.36)	16.61 (12.91–20.31)	64.26 (59.59–68.92)	68.7 (63.35–74.04)	45.81 (40.88–50.75)	51.57 (46.15–56.99)	37.26 (32.50-42.03)	48.88 (43.53–54.23)	24.57 (19.43–29.71)	31.90 (26.26–37.53)
Physical activity
Low physical activity		18.05 (15.87–20.24)		69.84 (67.26–72.42)		53.51 (50.58–56.45)		50.52 (47.59–53.44)		37.03 (33.34–40.72)
High physical activity		24.46 (21.04–27.87)		60.52 (56.82–64.22)		39.07 (35.76–42.39)		36.19 (32.95–39.43)		32.13 (27.95–36.31)
Nutrition
First tertile		18.02 (15.26–20.78)		69.09 (65.57–72.62)		47.20 (43.14–51.26)		43.56 (39.61–47.50)		31.16 (25.10-37.23)
Second tertile		19.29 (16.56–22.02)		66.02 (62.39–69.64)		49.20 (45.39-53.00)		46.21 (42.42-50.00)		35.09 (30.44–39.74)
Third tertile		23.62 (19.82–27.42)		64.16 (60.25–68.06)		47.29 (43.49–51.08)		44.9 (41.14–48.66)		38.92 (34.68–43.17)
BMI
normal	29.15 (26.19–32.11)	26.29 (22.20-30.38)	51.76 (48.48–55.04)	54.25 (50.02–58.49)	34.38 (31.18–37.58)	34.58 (30.79–38.38)	25.78 (22.75–28.82)	32.05 (28.32–35.77)	24.52 (20.49–28.55)	30.79 (25.71–35.87)
Under weight	24.69 (16.90-32.49)	27.78 (17.81–37.76)	42.38 (31.89–52.86)	39.78 (28.41–51.15)	27.19 (16.53–37.85)	28.83 (18.85–38.81)	23.55 (12.85–34.25)	25.34 (15.99–34.69)	15.27 (6.14–24.39)	21.52 (8.62–34.42)
Over weight	26.38 (23.72–29.05)	20.24 (17.40-23.08)	63.00 (60.13–65.87)	69.18 (66.02–72.35)	44.54 (41.55–47.53)	50.71 (47.25–54.17)	35.66 (32.75–38.57)	47.23 (43.79–50.66)	23.57 (20.28–26.86)	36.04 (31.88–40.20)
Obese	21.81 (18.62–24.99)	14.21 (11.41–17.02)	68.73 (65.06–72.40)	77.24 (73.71–80.76)	48.90 (44.99–52.82)	59.97 (55.23–64.70)	39.07 (35.37–42.76)	57.32 (52.64-62.00)	23.52 (19.48–27.56)	38.36 (32.84–43.88)
Insurance
Not insured	24.86 (14.74–34.97)	21.98 (13.73–30.23)	65.05 (54.85–75.26)	64.32 (54.90-73.73)	38.53 (29.09–47.97)	38.90 (29.66–48.13)	28.35 (19.82–36.88)	38.27 (29.05–47.50)	15.79 (7.68–23.91)	37.22 (25.41–49.03)
Basic	25.66 (23.71–27.62)	21.62 (18.77–24.48)	61.01 (58.81–63.22)	66.02 (62.96–69.08)	42.58 (40.30-44.86)	47.21 (44.08–50.34)	33.23 (31.03–35.43)	43.87 (40.79–46.95)	22.83 (20.42–25.25)	32.36 (28.24–36.48)
Basic + complementary	26.67 (23.59–29.74)	19.31 (16.66–21.96)	58.29 (54.82–61.76)	66.60 (63.34–69.86)	41.08 (37.62–44.53)	49.51 (46.12–52.91)	33.30 (29.98–36.62)	46.71 (43.34–50.08)	26.20 (21.83–30.58)	38.02 (33.91–42.14)
CAM use
No		21.90 (19.81–23.99)		63.69 (61.33–66.05)		43.60 (41.28–45.92)		40.79 (38.50-43.07)		34.04 (30.96–37.12)
Yes		10.70 (7.14–14.25)		84.55 (79.90-89.21)		79.12 (74.14–84.11)		75.16 (69.91–80.41)		42.12 (35.19–49.06)

Data are presented as weighted percentages with 95% confidence interval.

BMI: Body Mass Index; CAM: Complementary and Alternative Medicine.

The overall HTN prevalence rates increased from 2016 to 2021. Females consistently experienced higher rates than males (65.54% [63.0% to 68.08] in 2016 and 71.76% [68.95% to 74.57%] in 2021). HTN prevalence rose with age, with the most notable increase occurring among individuals aged 80 years and older. HTN prevalence also correlated with higher BMI. (Table 1).

Hypertension awareness also had an increasing prevalence from 2016 to 2021. Among different age groups, awareness was the highest in individuals aged 80 years and older (47.41% [42.26% to 52.55%] in 2016 and 63.33% [57.01% to 69.65%] in 2021). The Poorest quintile had lower awareness rates (42.82% [39.27% to 46.37%] in 2016 and 49.14% [44.84% to 53.45%] in 2021). Awareness also followed a clear pattern with BMI, being highest among obese individuals (48.9% [44.99% to 52.82%] in 2016 and 59.97% [55.23% to 64.70%] in 2021).

Males had lower treatment rates than females in both studies (26.53% [24.10% to 28.96%] in 2016 and 36.03% [33.04% to 39.02%] in 2021), although both genders saw improvements between 2016 and 2021. Those with both basic and complementary insurance had higher treatment rates compared to other groups in both surveys (33.30% [29.98% to 36.62%] in 2016 and 46.71% [43.34% to 50.08%] in 2021).

HTN control rates increased in both males and females. Control rates also improved across all age groups, with the highest increase in individuals aged 80 and older (21.41% [16.72% to 26.09%] in 2016 and 34.89 (26.6-43.19) in 2021). HTN control also improved with wealth, with the richest quintile having the highest rates (25.86% [18.88% to 32.84%] in 2016 and 37.56% [29.25% to 45.87%] in 2021).

Significant associations with prehypertension and hypertension

The average age of the total population was 68.46 year [68.16 to 68.76], increasing from 67.46 years [66.86 to 68.07] in pre-hypertensive population to 69.07 year [68.68 to 69.46] in hypertensive group. Participants with prehypertension had the smallest waist circumference (WC) (95.14 cm [94.04c to 96.23] cm). In contrast, those with HTN had a larger WC of 99.54 cm [98.78 to 100.3] cm. Metabolic and Lifestyle risk factors showed a strong association with HTN. Hypertensive participants had higher FPG (118.29 mg/dl [116.25_120.32] mg/dl) and HbA1C mg/dl (6.65 [6.58_6.73] mg/dl) levels compared to pre-hypertensive population (FPG: 109.26 mg/dl [105.08_113.45] mg/dl, HbA1C: 6.32 mg/dl [6.17_6.47] mg/dl). The pre-hypertensive group had the highest LDL (105.43 mg/dl [101.56_109.3] mg/dl) and total Cholesterol (178.76 mg/dl [174.13_183.4] mg/dl) levels (Table 2).

Table 2.

Clinical and metabolic characteristics of the population according to their hypertension status in STEPS survey 2021. Data are presented as weighted means with 95% confidence interval. The P-Value for HDLC3 and LDL is [P < 0.01] and the P-Value for other variables is [P  < 0.001].

Variable	Total in older adults Mean (SD)	Pre-hypertension Mean (SD)	Hypertension Mean (SD)	Diagnosed hypertension Mean (SD)	Under-treatment hypertension Mean (SD)	Controlled hypertension Mean (SD)
Age (y)	68.46 (68.16–68.76)	67.46 (66.86–68.07)	69.07 (68.68–69.46)	69.28 (68.83–69.73)	69.39 (68.92–69.85)	69.06 (68.32–69.79)
WC (Cm)	97.69 (97.09–98.29)	95.14 (94.04–96.23)	99.54 (98.78–100.30)	100.19 (99.28-101.09)	100.34 (99.39–101.30)	100.24 (98.54-101.94)
WHR	0.95 (0.95–0.96)	0.94 (0.94–0.95)	0.96 (0.95–0.96)	0.96 (0.96–0.97)	0.96 (0.96–0.97)	0.96 (0.95–0.97)
SBP (mmHg)	138.57 (137.76-139.38)	128.84 (128.22-129.45)	146.84 (145.95-147.73)	145.10 (144.00-146.19)	144.37 (143.23–145.50)	128.85 (127.76-129.94)
DBP (mmHg)	80.58 (80.09–81.08)	77.07 (76.40-77.75)	83.72 (83.13–84.32)	82.36 (81.68–83.05)	81.90 (81.18–82.61)	75.63 (74.85–76.41)
FPG (mg/dL)	114.99 (113.29–116.70)	109.26 (105.08-113.45)	118.29 (116.25-120.32)	119.84 (117.41-122.27)	119.67 (117.22-122.12)	119.52 (115.98-123.07)
HbA1C (%)	6.53 (6.47–6.60)	6.32 (6.17–6.47)	6.65 (6.58–6.73)	6.74 (6.65–6.83)	6.75 (6.66–6.84)	6.73 (6.59–6.87)
CHOL (mg/dL)	174.23 (172.03-176.42)	178.76 (174.13–183.40)	172.72 (169.89-175.56)	168.23 (165.62-170.83)	167.64 (164.95-170.34)	165.23 (158.44-172.03)
HDL-C (mg/dL)	43.15 (42.68–43.62)	44.93 (43.57–46.29)	42.52 (42.02–43.02)	42.46 (41.88–43.04)	42.43 (41.84–43.02)	41.96 (41.1-42.82)
LDL (mg/dL)	101.03 (99.22-102.83)	105.43 (101.56–109.30)	99.23 (96.91-101.54)	94.93 (92.76–97.09)	94.27 (92.02–96.52)	93.17 (87.76–98.58)
TRIGL (mg/dL)	150.27 (147.02-153.52)	142.01 (135.23-148.79)	154.88 (150.85-158.92)	154.19 (150.07-158.31)	154.73 (150.4-159.05)	150.50 (142.64-158.37)

Lipoprotein; TRIGL: Triglycerides; WC: waist circumference; WHR: Waist-to-hip ratio

CHOL: Cholesterol; FPG: Fast Plasma Glucose; HDL-C: High-density lipoprotein cholesterol; LDL: low-density 

An analysis of the 2021 survey indicated that consumption of any form of Complementary and alternative medicine (CAM) use showed a significant correlation with the prevalence of HTN (OR: 2.88, 95% CI: 1.95–4.25, P < 0.001). The HTN was significantly associated with being overweight (OR: 1.93, 95% CI: 1.54–2.43, P < 0.001) and being underweight had a reverse association with HTN (OR: 0.48, 95% CI: 0.29–0.78, P < 0.001). The analysis also showed a reverse association between higher education (more than 12 years of schooling) and the HTN prevalence (OR: 0.64, 95% CI: 0.48–0.87, p < 0.001). The 2021 study found no significant correlation between employment status and HTN, there was also no significant association found between smoking and HTN (Table 3).

Table 3.

Association between demographic and lifestyle factors and hypertension in older adults in Iran STEPS survey 2021 in multiple logistic regression model

Variable	OR	95% CI	p-value
Sex
Male	1.00	Reference
Female	1.20	0.90–1.60	0.23
Age (continuous)	1.04	1.03–1.06	< 0.001
Education
0–7	1.00	Reference
7–12	0.76	0.52–1.10	0.14
12+	0.64	0.48–0.87	< 0.001
Employment
Unemployed	1.00	Reference
Employed	0.74	0.53–1.04	0.09
Retired	1.07	0.77–1.50	0.68
BMI category
Normal	1.00	Reference
Obese	2.75	2.10–3.61	< 0.001
Over Weight	1.93	1.54–2.43	< 0.001
Under Weight	0.48	0.29–0.78	< 0.001
Nutrition
First tertile	1.00	Reference
Second tertile	0.87	0.69–1.09	0.23
Third tertile	0.83	0.65–1.06	0.14
Smoking
Non-Smoker	1.00	Reference
Past-Smoker	1.32	0.89–1.96	0.16
Second-Hand smoker	1.06	0.82–1.37	0.68
Current-Smoker	0.9	0.65–1.24	0.51
Complementary and alternative medicine use
No	1.00	Reference
Yes	2.88	1.95–4.25	< 0.001

BMI: Body Mass Index; CI: Confidence Interval; OR: Odds Ratio.

Discussion

The present study builds on previous research by providing updated and comparable estimates of prehypertension and hypertension prevalence among older adults. Unlike earlier analyses that presented single cross-sectional data, the current approach enables a clearer assessment of temporal trends and changes in prevalence, thereby informing health policy decisions more effectively.

Our study showed a decline in the prevalence of prehypertension which is in agreement with the findings of other research, not just in Iran but also in other Middle Eastern countries [24, 25]. One possible explanation for the observed decline is that a proportion of individuals classified as pre-hypertensive in the 2016 survey were classified as normotensive in the later survey. This may be associated with increased awareness of blood pressure monitoring and earlier lifestyle modifications, as discussed in subsequent paragraphs. Alternatively, a proportion of pre-hypertensive population in 2016 may have progressed to hypertensive by the time of the later survey, reflecting the natural course of blood pressure changes over time [26] and highlighting the importance of continued monitoring and preventive measurements. Yet, further studies are needed to clarify the underlying factors contributing to this trend.

On the other hand, we observed an increase in the prevalence of HTN, which is also consistent with the findings from previous studies [25, 27]. Several factors including healthcare access or lifestyle changes may have contributed to this trend. One major factor could be the Coronavirus disease-2019 (COVID-19). Although not directly measured, previous studies suggest that this pandemic disrupted daily routines among Iranian older adults by making people more isolated, less physically active, and changing their diets [28]. All of which may have been associated with developing HTN among older adults.

The higher prevalence of HTN among females is consistent with other research in Iran [11, 29]. This can be associated with hormonal influences, particularly postmenopausal estrogen decline and differing lifestyle habits among different genders [30, 31]. However, despite a higher HTN prevalence, females had enhanced treatment and blood pressure control which may be attributed to higher medication adherence and more frequent healthcare visits [32].

Our study also revealed a higher HTN rate among individuals with lower education, which is comparable to other research [33, 34]. This may be associated with poor health coverage and delayed diagnoses among lower-educated individuals, as well as higher health literacy and access to care among the educated population [34, 35].

We did not find a significant statistical association between employment and HTN. This implies that employment and HTN can be identified by diverse variables during different phases, including transformation of the work environment, stress and hours of working [36, 37]. Therefore, measurement of the influence of work on health is best achieved by longitudinal study designs with an emphasis on their various interactions.

We found a significant r between obesity and HTN prevalence, with 77.24% of the obese individuals in the 2021 survey experiencing HTN. These findings are also suggested by other researches [38, 39]. Angiotensinogen and pro-inflammatory cytokine secretion from adipose tissue may have a correlation with increased blood pressure [40–42]. Obesity can also compress kidneys by activating the sympathetic nervous system and promoting sodium retention [43]. Research indicates that older adults generally engage in less physical activity [44], and the COVID-19 pandemic has likely contributed to an even lower physical activity among this demographic [45]. A systematic review and meta-analysis by Silveira et al. highlights that sedentary lifestyle increases the incidence of HTN [46]. Furthermore, sarcopenic obesity is associated with HTN and HTN-related complications [47], raising possible concerns among older adults who experience higher rates of sarcopenia compared to the general population [48].

We also discovered a significant association between CAM consumption and higher rates of hypertension. One potential explanation for this observation could be that individuals, currently using complementary medicine for hypertension may have a longstanding habit of relying on these therapies for their various health issues. This habitual use could predispose them to elevated blood pressure risks, as certain CAM interventions-such as specific herbal supplements- may contribute to increased blood pressure [49]. Another possible factor relates to cultural influences in our context, where the use of herbal medicines is widely endorsed [50]. This societal encouragement may drive those already diagnosed with hypertension toward greater CAM adoption, thereby amplifying the association in a cross-sectional analysis [50].

The increasing trend of awareness, treatment and control of HTN was aligned with the findings from the studies both in Iran and other countries [51–53]. The WHO emphasizes that awareness is crucial for managing HTN [54]; however, globally, 54% of individuals remain unaware of their status [1]. From 2016 to 2021, in our study, an increase in awareness was consistent with global standards but lagged behind countries with the highest awareness rates, such as Costa Rica, Canada, and the United States (> 77%) [55]. Our findings revealed that females were more aware of their HTN. This can possibly be related to more frequent visits to healthcare facilities for regular check-ups including blood pressure measurements among females [56, 57]. The 2021 Lancet global analysis also points towards reproductive health screening as a factor that contributes to females visiting healthcare facilities more frequently [56]. Awareness also increased with age. This may be related to physiological changes, like arterial stiffening, which make HTN more evident during routine monitoring [56]. Moreover, utilization of health facilities also increases with age, given the increased weight of morbidity [57].

HTN treatment rate was 36.03% in males and 53.7% in females in 2021 which are close to the worldwide HTN treatment rate [56]. In our study, patients with basic and supplementary health insurance and improved economic status are treated at significantly greater extents than the rest. It shows the significant association between inequities like health coverage and income with health outcomes in the population [58, 59].

This study shows an increase in the control of HTN in Iran, just as in other countries [51, 56]. Yet Our findings show higher control rates than the 21% global rate which WHO reported for the 30 to 79 age group [1]. This difference may be explained by the higher age of our study population. Higher control rates with increasing age is also confirmed by the evidence of a 2021 German study that found a 42.7% treatment rate in those aged 65–94 years [60]. Contrary to our results, other countries’ reports show that while women have more control rates at younger ages, control is better in men at older age groups [61–63]. This discrepancy may be related to differences in culture and healthcare in Iran compared to other countries. In Iran, cultural norms may motivate older women to obtain routine medical care, largely because of familial support and gender-specific health programming [64], resulting in better HTN control than in Western nations where male cardiovascular risk management is prioritized [31]. These findings highlight the necessity for gender-specific healthcare approaches [65]. Control rates are higher in the obese population. This may reflect more concern for blood pressure control in this population. Furthermore, Control rates were higher in wealthier patients and patients with both basic and complementary insurance, further highlighting the association between socioeconomic status and health outcomes.

The current study covers a nationally representative sample, displaying an epidemiological assessment of both urban and rural areas of Iran. This study analyzed multivariate factors including socio-demographic, behavioral, and metabolic variables, and thus presented a broad view of the HTN associations. These findings can be helpful in public policy-making in the context of the HTN crisis among older adults in Iran.

However, certain limitations of the current study should be stated. First, it’s cross-sectional nature restricts the possibility of forming cause-and-effect relationships between risk factors and HTN outcomes. Second, in measuring some of the independent variables, recall or reporting bias may have taken place. Third, although an effort was made to use a uniform data collection method across the provinces, variations in healthcare coverage and participants’ socio-demographic characteristics might have influenced the outcomes. Forth, while blood pressure was measured three times after a 15-minute rest, assessing it in only one visit may have led to measurement errors. Fifth, the 2021 survey was conducted during the COVID-19 pandemic. Despite implementing precautions, the pandemic may have influenced participant recruitment and the measurement of key variables, potentially affecting the study findings. The current data reveals that existing strategies and approaches are inadequate to prevent the incidence of HTN and achieve improved control, especially among older adults. This highlights the importance of early detection and controlling the determinants of increased prevalence and inadequate control.

Conclusion

The present study indicates an increasing prevalence of HTN among older Iranian adults, despite improvements in awareness, treatment, and control. A decline in the prevalence of prehypertension was also noted; however, the reasons for the decline remain uncertain. This emphasizes the urgent need for targeted public health interventions. Based on the major associations identified in the study, focusing on promoting weight management through community-based programs and enhancing health education, particularly among individuals with lower educational attainment would be helpful. Furthermore, expanding regular blood pressure screening to ensure early diagnosis and intervention, as well as Improving access to healthcare services and antihypertensive medications, especially in underserved areas, is essential. This study also revealed gender and socioeconomic disparities in awareness and treatment. Therefore, Strengthening Gender-specific approaches as well as educational and socioeconomic support for the older adults could also improve hypertension prevention and management.

Abbreviations

BMI

Body mass 418 index

BP

Blood pressure

CI

Confidence interval

DBP

Diastolic blood pressure

ESC/ESH

European society of cardiology / European society of hypertension

FPG

Fasting plasma glucose

GPAQ

Global physical activity questionnaire

HbA1C

Hemoglobin A1C

HDL-C

High-density lipoprotein cholesterol

HTN

Hypertension

JNC7

Seventh report of the joint national committee on prevention, detection, evaluation, and treatment of high blood pressure

LDL

Low density lipoprotein

NCD

Non-communicable disease

OR

Odds ratio

PCA

Principal component analysis

SBP

Systolic blood pressure

SD

Standard deviation

STEPS

STEP wise approach to non-communicable disease risk factor surveillance

TRIGL

Triglycerides

WC

Waist circumference

WHR

Waist-to-hip ratio

WHO

World health organization

Author contributions

ME, MP, SNF, NR conceptualized and designed the study. YF analyzed the data and estimated results. MH wrote the first draft. ME, MP, MH, FS, MM, were involved in literature review and revising the material and draft for accuracy. All authors contributed to the preparation, critical review and all of them approved the final manuscript.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Competing interests

The authors declare no competing interests.

Ethics approval and consent to participate

Ethical approval for the study was granted following the latest Declaration of Helsinki by the research Ethics Committees of the Endocrine and Metabolism Research Institute, Tehran University of Iran (IR.TUMS.EMRI.REC.1403.053). All participants were fully informed about the study’s objectives and procedures. The entire study process was kept confidential, with access to the survey database restricted to the database manager, and the primary investigator. Each participant provided written informed consent, and in the case of illiterate and cognitively impaired participants, a legal guardian signed the informed consent form on their behalf. Involvement in this research was optional and had no effect on the treatment procedures of participants. Individuals had the option to exit the survey whenever they chose.