Old and new anthropometric indices in relation to blood pressure among the elderly: Birjand longitudinal aging study

doi:10.21203/rs.3.rs-2824131/v1

Background: This study aimed to investigate whether or not anthropometric indices are associated with hypertension in a sample of Iranian older adults.

Methods: This cross-sectional study used the data from the first wave of Birjand Longitudinal Aging Study (BLAS) (n=1364). Body mass index (BMI) and waist circumference (WC) were assessed as the old anthropometric indices, and body roundness index (BRI) and a body shape index (ABSI) were assessed as new body composition indices. Both systolic and diastolic blood pressure (SBP & DBP) were measured and used to assess hypertension (HTN). Analyses were conducted using binary logistic regression and receiver-operating characteristic curves (AUC) analysis.

Results: Prevalence of obesity was the highest based on BMI (59%). The best predictor of HTN were WC and BMI (AUC= 0.6 and 0.62). Before and after adjusting for confounders, high BMI and high WC had the strongest direct association with the presence of HTN, high SBP and high DBP in total population and in men and women separately. In women, BRI was significantly associated with DBP (OR: 1.60, 95%CI: 1.01; 2.52, P= 0.04. ABSI was not associated with blood pressure (P> 0.05).

Conclusions: The result of this study showed that old obesity indices are better predictors of HTN and BMI and WC are more strongly associated with HTN than the new indices. BRI is only associated with DBP in women.

Obesity

Abdominal obesity

Body mass index

Hypertension

Elderly

Hypertension (HTN) is a global health challenge in which excessive pressure is imposed on the vessel’s walls (1). According to the world health organization (WHO) and world heart federation, nowadays 1.3 billion people, one out of four men and one out of five women, have this disease and two third of these patients are from low and middle income countries (2, 3). Similarly, Iran has shown an increasing trend in the past twenty years, and the prevalence of this disease was 52.8% in 2020 after adjusting for sex and age (4).

Patients with HTN are predisposed to cardiovascular, renal and other medical problems which lead to further disability or even death (5). 7.6 million premature deaths are related to high blood pressure, and about 50% of strokes and ischemic heart diseases are attributed to this condition (6). Hypertension is known to be a multifactorial disease affected by both genetics and environmental factors (7). Aging with its inevitable changes in cardiovascular system is strongly associated with this disease as in Iran 42% of the elderly have been diagnosed with HTN (8). In addition, underlying disturbances like diabetes and hyperlipidemia, family history of HTN, alcohol drinking habits and obesity increase the risk of HTN (4, 9).

Obesity, especially when it is associated with visceral adiposity, stands for 70% of the risk of primary hypertension (10). Impaired renal function due to physical compression of the kidneys (11) and renin angiotensin aldosterone system (RAAS) activation in adipose tissue including plasma renin activity, angiotensinogen, angiotensin converting enzyme (ACE), angiotensin II, and aldosterone despite all suppressors (12) may contribute to HTN in obese. Moreover, hyperleptinemia in obesity leads to sympathetic nerve system (SNS) activation and has been suggested to play a role in HTN (13).

Body mass index (BMI) is the most commonly used index to define obesity in studies, although it cannot distinguish between fat and lean mass, and it is not sensitive to the location of the adipose tissue (14). Waist circumference (WC) is another obesity index which can indicate abdominal obesity, but it is not able to take height and weight into account (15). Recently, a body shape index (ABSI) and body roundness index (BRI) have been introduced as new obesity indicators, and they have been considered in some studies to compare with previous obesity indices (16, 17), but whether they can predict obesity adverse effects like HTN, or they are better predictors than the conventional obesity indices in this regard is still controversial.

A considerable percent of Iranian people are overweight/obese, and the rate of old population with its accompanying health disturbances including HTN is growing at a fast speed as well (18). As little information exists about new obesity indices in this part of the world and there is controversy toward the best index to predict HTN, we aim to evaluate old and new anthropometric indices in the elderly population of the eastern regions of Iran, and compare their association with HTN in order to prevent the occurrence of this disease or its consequences by early diagnosis, appropriate treatment and control.

The present study is based on data from the first wave of Birjand longitudinal aging study (BLAS), a prospective cohort carried out on the elderly residents of Birjand city, Iran. Older adults (≥ 60 years old), both sexes were asked to come to the appointed place for examinations and interviews. Approval for the protocol of the present study was obtained from the research ethical committee of Endocrinology Metabolism Research Institute of Tehran University of Medical Sciences (code: IR.TUMS.EMRI.REC.1396.00158) and written informed consent was obtained from all participants prior to participation. All examinations for participants were free and no participant was paid. Details of sampling and participant recruitment is previously published (19).

Anthropometric indices

All physicians, interviewers and technicians received unified training before the survey started, in order that the same standards of measurements were used for all participating elderly. Weight was measured with a calibrated SECA digital scale at nearest to 0.1 kg (SECA, Germany). Height was measured to the nearest 0.1 cm using a non-stretchable tape measure. WC was measured at the midpoint between the bottom of the ribs and the top of the iliac crest to the nearest 0.1 cm with an inelastic tape. All anthropometric measures were taken with the participants dressed in light clothing and without shoes. BMI, BRI and ABSI were calculated using the following formulas:

BMI = weight (kg)/ height (m²)

ABSI = WC/ (BMI 2/3. height ½)) (20)

BRI = 365.2 − 365.5 × √ (1 − (((WC/(2π))^2)/ (0.5 × height)^2)) (20)

Blood pressure measurements

Each participant’s blood pressure was measured after 10 minutes resting in the right arm at sitting position with their arm supported at the level of the heart, using automatic blood pressure (BP) measuring device OMRON M4. All subjects wore light clothing (no tight clothing constricting the arm) and were in optimal room conditions. Each participant’s blood pressure was measured two times with a 5-min interval between measurements. The mean of the two readings was recorded as the final value. Systolic blood pressure (SBP) was accepted as the first Korotkoff sound phase and diastolic blood pressure (DBP) as the fifth phase (disappearance of sounds). A SBP ≥ 140 mmHg and DBP ≥ 90 mmHg were considered as high systolic blood pressure and high diastolic blood pressure, respectively. A SBP ≥ 140 mmHg and/or a DBP ≥ 90 mmHg, and/or use of antihypertensive drugs were considered as hypertension (HTN).

Other variables

Each participant filled out a general information questionnaire, especially designed for BLAS. This questionnaire included demographic details, age, marital status, education level, and smoking habits. International Physical Activity Questionnaire (IPAQ) was also used to measure the amount of physical activity.

Statistical analysis

Statistical analyses were performed using SPSS software version 26 (SPSS for Windows, SPSS Inc., Chicago, IL, USA) or STATA version 14.2 (StataCorp. 2015. Stata Statistical Software: Release 14. College Station, TX: StataCorp LP.), and the significance level was set at P-value ≤ 0.05. Differences in continuous variables between the two groups of high and normal BP were tested with independent sample t test. Differences in categorical variables between the two groups were analyzed with Chi-square or Fisher’s exact test. ABSI and BRI were categorized as binary variables using their mean as cut-off points; for BMI ≥ 25 kg/m² defined as overweight/obese (21) and WC > 102 cm in men and > 88 in women defined as abdominal obesity (22). Binary logistic regression was used to investigate the association of body composition indices (binary) and elevated SBP and DBP, and HTN (binary), after adjustment for age (continuous), sex (only for the total population), smoking (binary), physical activity (categorical), and diabetes mellitus (binary). Multivariate linear stepwise regression was performed to analyze the association of each anthropometric index (continuous) with high SBP, high DBP, and HTN (binary). Also, ordinal logistic regression was performed to assess the association between BMI status based on the 4 categories determined by WHO and high blood pressure, after adjustment for age (continuous), sex (only for the total population), smoking (binary), physical activity (categorical), diabetes mellitus (binary), and the use of antihypertensive drugs (binary, only for high SBP and high DBP).

Receiver-operating characteristic (ROC) curve analysis was also performed. Area under the curve (AUC) was calculated as an indicator of how well the anthropometric indices can distinguish the presence of HTN, elevated SBP or elevated DBP.

The anthropometric obesity indices, demographic characteristics and disease variables of the study population are shown in Table 1. The present cross-sectional study investigated 1364 older adults with the mean age of 69.77 (7.66), including 657 (48.2%) men and 707 (51.8%) women. Seven hundred and ninety-seven individuals were hypertensive. Participants were mostly consisted of non-smokers (93.0%) and the proportion of inactive individuals was higher among the HTN group (P-value = 0.03). There was a significant difference between the two groups of normal and high BP regarding weight, BMI, and WC (P˂ 0.001), while BRI and ABSI were not remarkably different between the two groups (P > 0.05). Prevalence of obesity among the elderly participants was the highest according to BMI (807 (59.3%)) and the lowest according to BRI (615 (45.1%)). According to BMI, the majority of elderly with high BP were obese/overweight (P˂ 0.001).

Table 1

General characteristics of the participants.
Variables			Blood pressure
Variables		Overall (n = 1364)	NTN (n = 567)	HTN (n = 797)	P-value
Age (years)		69.77 (7.66)	68.57 (7.62)	70.63 (7.59)	˂0.001
Height (cm)		157.46 (10.28)	157.20 (10.05)	157.65 (10.44)	0.21
Weight (kg)		65.41 (13.38)	62.61 (12.84)	67.40 (13.41)	˂0.001
BMI		26.43 (5.33)	25.43 (5.48)	27.14 (5.11)	˂0.001
WC (cm)		95.30 (11.89)	92.48 (12.39)	97.31 (11.11)	˂0.001
ABSI		0.086 (0.01)	0.09 (001)	0.09 (0.00)	0.20
BRI		4.66 (1.71)	4.67 (1.67)	4.65 (1.74)	0.86
SBP (mmHg)		131.61 (20.91)	119.16 (13.55)	140.47 (20.71)	˂0.001
DBP (mmHg)		78.43 (11.65)	73.46 (8.25)	81.96 (12.41)	˂0.001
Physical activity	Inactive	510 (37.4%)	191 (33.7%)	319 (40.0%)	0.03
	Low	180 (13.2%)	73 (12.9%)	107 (13.4%)
	Moderate	674 (49.6%)	303 (53.4%)	371 (46.5%)
sex	Female	707 (51.8%)	294 (51.9%)	413 (51.8%)	0.99
sex	Male	657 (48.2%)	273 (48.1%)	384 (48.2%)	0.99
Marital status	Single, divorced or widowed	255 (18.7%)	106 (18.7%)	149 (18.7%)	1.00
Marital status	Married	1109 (81.3%)	461 (81.3%)	648 (81.3%)	1.00
Smoking status	Yes	96 (7.0%)	62 (10.9%)	34 (4.3%)	˂0.001
Smoking status	No	1268 (93.0%)	505 (89.1%)	763 (95.7%)	˂0.001
Education	Illiterate	623 (45.7%)	261 (46.0%)	362 (45.4%)	0.66
	School	507 (37.2%)	215 (37.9%)	292 (36.6%)
	Diploma	129 (9.5%)	47 (8.3%)	82 (10.3%)
	University	107 (7.7%)	44 (7.8%)	61 (7.7%)
Job status	Retired or unemployed	566 (41.5%)	236 (41.6%)	330 (41.4%)	0.99
	Housewife or freelancer	753 (55.2%)	312 (55.0%)	441 (55.3%)
	Farmer or employed	45 (3.3%)	19 (3.4%)	26 (3.3%)
BMI	Normal	555 (25.0%)	278 (49.0%)	277 (34.8%)	˂0.001
BMI	Overweight or obese	807 (59.3%)	289 (51.0%)	518 (65.2%)	˂0.001
WC	Normal	671 (49.2%)	283 (49.9%)	388 (48.7%)	0.65
WC	Overweight or obese	693 (50.8%)	284 (50.1%)	409 (51.3%)	0.65
ABSI	Normal	711 (52.1%)	310 (54.7%)	401 (50.3%)	0.11
ABSI	Overweight or obese	653 (47.9%)	257 (45.3%)	396 (49.7%)	0.11
BRI	Normal	749 (54.9%)	313 (55.2%)	436 (54.7%)	0.86
BRI	Overweight or obese	615 (45.1%)	254 (44.8%)	361 (45.3%)	0.86
Data represented as mean (SD) or n (%).
HTN: hypertensive elderly; NTN: normotensive elderly; SBP: systolic blood pressure; DBP: diastolic blood pressure; BMI: body mass index; WC: waist circumference; ABSI: A Body Shape Index; BRI: Body Roundness Index

AUC in elderly men and women are showed in Table 2, and ROC analyses for associations between the four body composition indices and HTN, SBP, and DBP are shown in Fig. 1. ROC curve analysis showed that AUC of WC for HTN was always the largest, and BRI was the smallest among the four anthropometric indices. In men, BMI and WC equally represented the largest AUC, while BRI and ABSI represented the smallest AUC. In women, the AUC of different indices were not remarkably different (in the range of 0.50 to 0.59), with BMI and WC indwelling the largest, AUC. Results regarding SBP and DBP were similar to that of HTN in total population and men and women separately.

Table 2

Areas under the receiver-operating characteristic curves (AUC) of body composition indices for high blood pressure in total population and in men and women separately.
	Obesity indices	HTN		SBP		DBP
	Obesity indices	AUC	95% CI	AUC	95% CI	AUC	95% CI
Total	BMI	0.60	0.57; 0.63	0.55	0.52; 0.58	0.59	0.55; 0.63
	WC	0.62	0.59; 0.65	0.56	0.53; 0.60	0.60	0.56; 0.64
	ABSI	0.53	0.50; 0.56	0.50	0.46; 0.53	0.50	0.46; 0.55
	BRI	0.49	0.46; 0.52	0.52	0.49; 0.55	0.53	0.49; 0.57
Men	BMI	0.64	0.60; 0.68	0.62	0.58; 0.66	0.64	0.59; 0.70
	WC	0.65	0.60; 0.69	0.61	0.57; 0.66	0.65	0.60; 0.70
	ABSI	0.54	0.49; 0.58	0.51	0.46; 0.55	0.51	0.46; 0.57
	BRI	0.48	0.44; 0.53	0.52	0.47; 0.56	0.51	0.45; 0.56
Women	BMI	0.58	0.54; 0.62	0.53	0.49; 0.58	0.57	0.51; 0.64
	WC	0.59	0.55; 0.64	0.55	0.50; 0.60	0.58	0.52; 0.64
	ABSI	0.53	0.49; 0.58	0.53	0.48; 0.58	0.53	0.46; 0.60
	BRI	0.50	0.46; 0.55	0.52	0.48; 0.56	0.56	0.50; 0.62
HTN: hypertension; SBP: systolic blood pressure; DBP: diastolic blood pressure; BMI: body mass index; WC: waist circumference; ABSI: A Body Shape Index; BRI: Body Roundness Index

Binary logistic regression analyses were performed using WC, BMI, BRI, and ABSI (binary) as the independent variables, and HTN, high SBP, and high DBP (binary) as the dependent variables to test the association between each measure of obesity and blood pressure. The results are shown in Table 3. Whether with or without adjustment, BMI was directly associated with high SBP, high DBP, and HTN in men (OR: 2.21, 95%CI: 1.59–3.07, OR: 2.86, 95%CI: 1.83–4.47, OR: 2.55, 95%CI: 1.84–4.55, respectively) and women (OR: 1.56, 95%CI: 1.06–2.31, OR: 2, 95%CI: 1.14–3.5, OR: 1.87, 95%CI: 1.33–2.64, respectively) and in total population (OR: 1.92, 95%CI: 1.49–2.47, OR: 2.51, 95%CI: 1.76–3.58, OR: 2.18, 95%CI: 1.72–2.76, respectively) of the elderly. The same association applies for WC. ABSI was not associated with high blood pressure (P˂ 0.05), and high BRI was a risk factor for high DBP, only among women (OR: 1.63_ 95%CI: 1.03–2.57). In other words, BRI increased the odds of high DBP by 60%. Using the continuous values of body composition indices in the regression model (Table 4), the same results were drawn. Except for BMI, which was not significantly associated with high SBP among women (OR > 1.00, P > 0.05)

Table 3

Association between obesity (binary) and high blood pressure (binary) in the elderly participants.
			Obesity
			BMI		WC		ABSI		BRI
			OR (95% CI)	P-value	OR (95% CI)	P-value	OR (95% CI)	P-value	OR (95% CI)	P-value
Total*	HTN	Crude	1.80 (1.44; 2.24)	˂0.001	1.67 (1.34; 2.07)	˂0.001	1.19 (0.96; 1.48)	0.11	1.02 (0.82; 1.27)	0.86
		Model 1	2.18 (1.72; 2.76)	˂0.001	2.51 (1.88; 3.34)	˂0.001	1.10 (0.88; 1.38)	0.39	1.05 (0.84; 1.31)	0.66
		Model 2	1.99 (1.56; 2.53)	˂0.001	2.24 (1.67; 3.01)	˂0.001	1.10 (0.87; 1.38)	0.44	1.03 (0.82; 1.28)	0.82
	HighSBP	Crude	1.43 (1.13; 1.80)	0.003	1.05 (0.84; 1.32)	0.65	0.91 (0.72; 1.14)	0.42	1.09 (0.87; 1.37)	0.46
		Model 1	1.92 (1.49; 2.47)	˂0.001	2.09 (1.54; 2.83)	˂0.001	0.95 (0.75; 1.21)	0.71	1.13 (0.90; 1.42)	0.30
		Model 2	1.68 (1.29; 2.17)	˂0.001	1.77 (1.29; 2.42)	˂0.001	0.93 (0.73; 1.18)	0.55	1.15 (0.91; 1.45)	0.25
	HighDBP	Crude	2.16 (1.54; 3.04)	˂0.001	1.28 (0.95; 1.74)	0.11	1.10 (0.82; 1.49)	0.52	1.17 (0.86; 1.59)	0.30
		Model 1	2.51 (1.76; 3.58)	˂0.001	2.12(1.44; 3.11)	˂0.001	1.22 (0.89; 1.68)	0.21	1.17 (0.87; 1.59)	0.30
		Model 2	2.29 (1.60; 3.28)	˂0.001	1.89 (1.28; 2.80)	0.001	1.21 (0.88; 1.66)	0.24	1.18 (0.87; 1.61)	0.28
Men	HTN	Crude	2.30 (1.67; 3.16)	˂0.001	2.31 (1.51; 3.54)	˂0.001	1.27 (0.92; 1.75)	0.15	0.92 (0.67; 1.26)	0.60
		Model 1	2.55 (1.84; 3.55)	˂0.001	2.44 (1.59; 3.76)	˂0.001	1.21 (0.87; 1.69)	0.24	0.94 (0.69; 1.29)	0.70
		Model 2	2.26 (1.61; 3.17)	˂0.001	2.16 (1.38; 3.37)	0.001	1.16 (0.83; 1.63)	0.39	0.98 (0.71; 1.35)	0.90
	HighSBP	Crude	2.02 (1.47; 2.78)	˂0.001	1.92 (1.30; 2.83)	0.001	1.03 (0.74; 1.43)	0.85	1.01 (0.74; 1.38)	0.95
		Model 1	2.21 (1.59; 3.07)	˂0.001	2.01 (1.36; 2.98)	˂0.001	0.99 (0.71; 1.38)	0.96	1.03 (0.75; 1.41)	0.86
		Model 2	1.92 (1.37; 2.69)	˂0.001	1.72 (1.14; 2.58)	0.01	0.92 (0.96; 1.30)	0.66	1.06 (0.77; 1.47)	0.70
	HighDBP	Crude	2.94 (1.89; 4.58)	˂0.001	2.01 (1.27; 3.20)	0.003	1.14 (0.75; 1.74)	0.54	0.91 (0.60; 1.38)	0.67
		Model 1	2.86 (1.83; 4.47)	˂0.001	1.95 (1.22; 3.10)	0.005	1.20 (0.78; 1.83)	0.40	0.89 (0.59; 1.35)	0.60
		Model 2	2.57 (1.63; 4.06)	˂0.001	1.72 (1.07; 2.77)	0.03	1.17 (0.76; 1.80)	0.48	0.91 (0.60; 1.38)	0.66
Women	HTN	Crude	1.47 (1.07; 2.03)	0.02	2.23 (1.54; 3.24)	˂0.001	1.15 (0.85; 1.55)	0.37	1.12 (0.83; 1.51)	0.45
		Model 1	1.87 (1.33; 2.64)	˂0.001	2.63 (1.78; 3.88)	˂0.001	0.99 (0.73; 1.36)	0.97	1.16 (0.86; 1.58)	0.33
		Model 2	1.78 (1.26; 2.53)	0.001	2.36 (1.59; 3.52)	˂0.001	1.02 (0.74; 1.40)	0.91	1.06 (0.78; 1.46)	0.70
	HighSBP	Crude	1.27 (0.88; 1.85)	0.20	1.92 (1.20; 3.06)	0.01	1.03 (0.74; 1.45)	0.84	1.20 (0.86; 1.68)	0.28
		Model 1	1.56 (1.06; 2.31)	0.02	2.22 (1.37; 3.59)	0.001	0.90 (0.64; 1.28)	0.56	1.25 (0.89; 1.76)	0.19
		Model 2	1.40 (0.94; 2.09)	0.09	1.85 (1.13; 3.04)	0.01	0.92 (0.65; 1.32)	0.66	1.26 (0.89; 1.79)	0.19
	HighDBP	Crude	1.79 (1.04; 3.10)	0.04	2.35 (1.15; 4.82)	0.02	1.03 (0.82; 2.08)	0.27	1.60 (1.01; 2.52)	0.04
		Model 1	2.00 (1.14; 3.50)	0.01	2.50 (1.21; 5.15)	0.01	1.24 (0.77; 1.99)	0.38	1.63 (1.03; 2.57)	0.04
		Model 2	1.93 (1.09; 3.40)	0.02	2.29 (1.10; 4.78)	0.03	1.28 (0.79; 2.07)	0.31	1.60 (1.01; 2.54)	0.04
Binary logistic regression
Model 1: adjusted for age
Model 2: adjusted for age, smoking, physical activity, diabetes mellitus
* antihypertensive drug use was also adjusted in the models of high SBP and high DBP.
*sex was also added to both of the adjusted models in total population
BMI: body mass index; WC: waist circumference; HTN: hypertension; SBP: systolic blood pressure; DBP: diastolic blood pressure; ABSI: A Body Shape Index; BRI: Body Roundness Index

Table 4

Association between body composition indices (continuous) and high blood pressure (binary) in the elderly participants.
			Obesity
			BMI		WC		ABSI		BRI
			OR (95% CI)	P-value	OR (95% CI)	P-value	OR (95% CI)	P-value	OR (95% CI)	P-value
Total*	HTN	Crude	1.07 (1.04; 1.09)	˂0.001	1.04 (1.03; 1.05)	˂0.001	1.07 (0.96; 1.20)	0.20	0.99 (0.93; 1.06)	0.86
		Model 1	1.09 (1.06; 1.12)	˂0.001	1.04 (1.03; 1.05)	˂0.001	1.03 (0.92; 1.16)	0.58	1.00 (0.94; 1.07)	0.92
		Model 2	1.08 (1.05; 1.10)	˂0.001	1.04 (1.02; 1.05)	˂0.001	1.02 (0.90; 1.14)	0.78	0.99 (0.93; 1.06)	0.83
	HighSBP	Crude	1.02 (1.00; 1.04)	0.03	1.02 (1.01; 1.03)	˂0.001	1.01 (0.90; 1.13)	0.86	1.04 (0.97; 1.11)	0.24
		Model 1	1.05 (1.03; 1.08)	˂0.001	1.03 (1.2; 1.04)	˂0.001	1.04 (0.92; 1.17)	0.49	1.05 (0.99; 1.13)	0.12
		Model 2	1.04 (1.01; 1.06)	0.003	1.02 (1.01; 1.04)	˂0.001	1.03 (0.91; 1.16)	0.62	1.07 (1.00; 1.14)	0.06
	HighDBP	Crude	1.04 (1.02; 1.07)	0.001	1.03 (1.02; 1.05)	˂0.001	1.02 (0.88; 1.19)	0.77	1.07 (0.98; 1.17)	0.12
		Model 1	1.06 (1.03; 1.09)	˂0.001	1.04 (1.02; 1.05)	˂0.001	1.07 (0.92; 1.26)	0.37	1.07 (0.98; 1.17)	0.11
		Model 2	1.05 (1.02; 1.08)	0.001	1.03 (1.02; 1.05)	˂0.001	1.07 (0.91; 1.26)	0.39	1.08 (0.99; 1.18)	0.08
Men	HTN	Crude	1.05 (1.02; 1.08)	0.001	1.05 (1.03; 1.06)	˂0.001	1.16 (0.96; 1.41)	0.11	0.95 (0.87; 1.05)	0.35
		Model 1	1.13 (1.09; 1.18)	˂0.001	1.05 (1.04; 1.07)	˂0.001	1.14 (0.94; 1.38)	0.17	0.96 (0.87; 1.06)	0.44
		Model 2	1.11 (1.06; 1.16)	˂0.001	1.04 (1.03; 1.06)	˂0.001	1.09 (0.89; 1.32)	0.41	0.97 (0.88; 1.07)	0.53
	HighSBP	Crude	1.10 (1.05; 1.14)	˂0.001	1.04 (1.02; 1.05)	˂0.001	1.06 (0.88; 1.29)	0.51	1.03 (0.94; 1.14)	0.49
		Model 1	1.11 (1.06; 1.15)	˂0.001	1.04 (0.03; 1.06)	˂0.001	1.05 (0.87; 1.27)	0.63	1.04 (0.94; 1.15)	0.40
		Model 2	1.09 (1.04; 1.13)	˂0.001	1.03 (1.02; 1.05)	˂0.001	1.00 (0.82; 1.22)	1.00	1.06 (0.96; 1.18)	0.21
	HighDBP	Crude	1.10 (1.04; 1.15)	˂0.001	1.05 (1.03; 1.07)	˂0.001	1.09 (0.85; 1.39)	0.48	1.02 (0.90; 1.16)	0.75
		Model 1	1.09 (1.04; 1.15)	˂0.001	1.05 (1.03; 1.07)	˂0.001	1.11 (0.87; 1.42)	0.39	1.01 (0.89; 1.15)	0.85
		Model 2	1.08 (1.03; 1.13)	0.002	1.04 (1.02; 1.06)	˂0.001	1.09 (0.85; 1.41)	0.48	1.03 (0.90; 1.17)	0.68
Women	HTN	Crude	1.05 (1.02; 1.08)	0.001	1.03 (1.01; 1.04)	˂0.001	1.03 (0.90; 1.18)	0.65	1.02 (0.94; 1.11)	0.56
		Model 1	1.07 (1.04; 1.10)	˂0.001	1.03 (1.02; 1.05)	˂0.001	0.96 (0.83; 1.11)	0.57	1.03 (0.95; 1.12)	0.46
		Model 2	1.06 (1.03; 1.09)	˂0.001	1.03 (1.01; 1.04)	˂0.001	0.96 (0.83; 1.11)	0.58	1.01 (0.92; 1.10)	0.88
	HighSBP	Crude	1.01 (0.98; 1.04)	0.42	1.01 (1.00; 1.03)	0.04	1.09 (0.94; 1.27)	0.26	1.05 (0.96; 1.15)	0.26
		Model 1	1.02 (0.99; 1.05)	0.18	1.02 (1.00; 1.04)	0.01	1.02 (0.88; 1.19)	0.74	1.06 (0.97; 1.16)	0.20
		Model 2	1.01 (0.97; 1.04)	0.69	1.01 (1.00; 1.03)	0.10	1.04 (0.89; 1.21)	0.64	1.07 (0.97; 1.17)	0.17
	HighDBP	Crude	1.03 (1.00; 1.07)	0.07	1.03 (1.01; 1.05)	0.01	1.06 (0.86; 1.29)	0.60	1.12 (1.00; 1.26)	0.05
		Model 1	1.04 (1.00; 1.08)	0.05	1.03 (1.01; 1.05)	0.005	1.03 (0.84; 1.26)	0.80	1.13 (1.00; 1.27)	0.04
		Model 2	1.03 (0.99; 1.07)	0.13	1.03 (1.00; 1.05)	0.01	1.04 (0.85; 1.27)	0.72	1.12 (1.00; 1.26)	0.056
Linear regression
Model 1: adjusted for age
Model 2: adjusted for age, smoking, physical activity, diabetes mellitus
* antihypertensive drug use was also adjusted in the models of high SBP and high DBP.
*sex was also added to both of the adjusted models in total population
BMI: body mass index; WC: waist circumference; HTN: hypertension; SBP: systolic blood pressure; DBP: diastolic blood pressure; ABSI: A Body Shape Index; BRI: Body Roundness Index

The association of BMI categorized according to WHO categories and blood pressure was investigated and represented in Table 5. In total population and among men, overweight significantly increased the odds of HTN (OR: 1.68, 95%CI: 1.3–2.19, OR: 1.93, 95%CI: 1.35–2.76, respectively), high SBP (OR: 1.66, 95%CI: 1.25–2.19, OR: 1.85, 95%CI: 1.29–2.65, respectively) and high DBP (OR: 2.23, 95%CI: 1.52–3.27, OR: 2.49, 95%CI: 1.54–4.03, respectively), the same as obesity (OR: 2.65, 95%CI: 1.91–3.68, OR: 3.9, 95%CI: 2.12–7.18 for HTN and OR: 2.08, 95%CI: 1.49–2.9, OR: 2.9, 95%CI: 1.7–4.92 for high SBP and OR: 2.63, 95%CI: 1.68–4.11, OR: 3.27, 95%CI: 1.73–6.17 for high DBP in total population and men, respectively), while underweight was only related to HTN (OR: 0.33, 95%CI: 0.19–0.6, OR: 0.33, 95%CI: 0.16–0.67, respectively) and high SBP (OR: 0.43, 95%CI: 0.22–0.87, OR: 0.44, 95%CI: 0.2-1, respectively). On the other hand, in female population, no significant association was observed for underweight and overweight, but obesity significantly elevated the odds of HTN (OR: 2.18, 95%CI: 1.43–3.31) and high DBP (OR:1.02, 95%CI: 1.07–3.8).

Table 5: Association between BMI status (WHO categories) and high blood pressure (binary) in the elderly participants.

	frailty		BMI
			18.5 ≤BMI≤ 24.9	BMI˂ 18.5			25≤ BMI≤ 29.9			BMI≥ 30
			18.5 ≤BMI≤ 24.9	OR	95% CI	P-value	OR	95% CI	P-value	OR	95% CI	P-value
Total	HTN	Crude	reference	0.38	0.21; 0.66	0.001	1.40	1.09; 1.80	0.01	2.07	1.52; 2.81	˂0.001
		Model 1	reference	0.33	0.19; 0.60	˂0.001	1.68	1.30; 2.19	˂0.001	2.65	1.91; 3.68	˂0.001
		Model 2	reference	0.40	0.22; 0.73	0.003	1.60	1.22; 2.09	0.001	2.40	1.22; 3.35	˂0.001
	High SBP	Crude	reference	0.50	0.25; 0.98	0.04	1.32	1.01; 1.72	0.04	1.37	1.01; 1.87	0.04
		Model 1	reference	0.43	0.22; 0.87	0.02	1.66	1.25; 2.19	˂0.001	2.08	1.49; 2.90	˂0.001
		Model 2	reference	0.51	0.25; 1.04	0.06	1.54	1.16; 2.04	0.003	1.75	1.24; 2.46	0.001
	High DBP	Crude	reference	0.45	0.14; 1.51	0.20	2.01	1.38; 2.92	˂0.001	2.06	1.35; 3.14	0.001
		Model 1	reference	0.43	0.13; 1.43	0.17	2.23	1.52; 3.27	˂0.001	2.63	1.68; 4.11	˂0.001
		Model 2	reference	0.51	0.15; 1.70	0.27	2.12	1.44; 3.12	˂0.001	2.36	1.50; 3.71	˂0.001
Men	HTN	Crude	reference	0.36	0.18; 0.72	0.004	1.76	1.24; 2.49	0.002	3.34	1.84; 6.08	˂0.001
		Model 1	reference	0.33	0.16; 0.67	0.002	1.93	1.35; 2.76	˂0.001	3.90	2.12; 7.18	˂0.001
		Model 2	reference	0.40	0.19; 0.84	0.02	1.78	1.24; 2.57	0.002	3.47	1.85; 6.49	˂0.001
	High SBP	Crude	reference	0.47	0.21; 1.05	0.06	1.71	1.21; 2.43	0.003	2.55	1.52; 4.28	˂0.001
		Model 1	reference	0.44	0.20; 1.00	0.05	1.85	1.29; 2.65	0.001	2.90	1.70; 4.92	˂0.001
		Model 2	reference	0.51	0.22; 1.18	0.12	1.69	1.18; 2.44	0.004	2.43	1.41; 4.20	0.001
	High DBP	Crude	reference	0.42	0.10; 1.81	0.24	2.55	1.58; 4.10	˂0.001	3.39	1.81; 6.34	˂0.001
		Model 1	reference	0.42	0.10; 1.83	0.25	2.49	1.54; 4.03	˂0.001	3.27	1.73; 6.17	˂0.001
		Model 2	reference	0.49	0.11; 2.17	0.35	2.34	1.44; 3.81	0.001	2.88	1.51; 5.51	0.001
women	HTN	Crude	reference	0.43	0.17; 1.11	0.08	1.14	0.79; 1.64	0.49	1.73	1.16; 2.57	0.01
		Model 1	reference	0.38	0.14; 1.02	0.06	1.44	0.98; 2.12	0.06	2.18	1.43; 3.31	˂0.001
		Model 2	reference	0.43	0.16; 1.19	0.10	1.43	0.96; 2.13	0.07	2.03	1.32; 3.11	0.001
	High SBP	Crude	reference	0.52	0.15; 1.83	0.31	1.12	0.73; 1.70	0.61	1.33	0.86; 2.05	0.20
		Model 1	reference	0.47	0.13; 1.72	0.26	1.37	0.88; 2.13	0.16	1.60	1.02; 2.52	0.04
		Model 2	reference	0.59	0.16; 2.20	0.43	1.33	0.85; 2.09	0.21	1.38	0.86; 2.19	0.18
	High DBP	Crude	reference	0.53	0.07; 4.19	0.55	1.61	0.88; 2.97	0.12	1.83	0.98; 3.41	0.06
		Model 1	reference	0.51	0.06; 4.06	0.53	1.81	0.97; 3.36	0.06	1.02	1.07; 3.80	0.03
		Model 2	reference	0.64	0.08; 5.17	0.68	1.86	0.99; 1.05	0.05	1.89	0.99; 3.60	0.05

Ordinal logistic regression

Model 1: adjusted for age

Model 2: adjusted for age, smoking, physical activity, diabetes mellitus

* antihypertensive drug use was also adjusted in the models of high SBP and high DBP.

*sex was also added to both of the adjusted models in total population

BMI: body mass index; WC: waist circumference; HTN: hypertension; SBP: systolic blood pressure; DBP: diastolic blood pressure; ABSI: A Body Shape Index; BRI: Body Roundness Index

In this study, we found that 58.4% of adults over 60 years old had HTN. BMI was significantly associated with HTN, high SBP and high DBP in total population and both genders, as a categorical and continuous variable except for high SBP in women as a continuous variable. Also, WC showed a significant relationship with HTN, high SBP and high DBP in total population, men and women. BRI and ABSI were not significantly associated with HTN, SBP, and DBP as neither a categorical variable nor a continuous one, except for BRI, which showed a significant relationship with high DBP as a categorical variable and DBP as a continuous variable in women.

In the current study, participants with HTN had significantly higher BMI. BMI ≥ 25 kg/m² could increase the risk of HTN and high DBP by 2.18 and 2.51 times, respectively in the adjusted model, and the risk of high SBP increased by 0.92 as BMI increased by one unit. Based on BMI, in total population and men being underweight was protective against HTN and high SBP, and overweight increased the risk of HTN, high SBP and high DBP. Also, the risk of HTN increased with increasing BMI, as obesity increased the risk of HTN, high SBP and DBP in total population and both gender, except for high SBP in women, even more than overweight. This result is in line with a cohort study by Lee M, et al. in Korea in which BMI increased the risk of HTN significantly (23). Another investigation on 498 participants in Brazil found a great association between BMI and the risk of hypertension. In addition, participants with HTN had significantly higher WC, and abdominal obesity based on WC could increase the risk of HTN by 2.51 times in total population in the adjusted model. A large population-based study in china indicated that the risk of HTN rises up to 97% as patients have higher WC (24), and Sun J, et al. found 18% higher risk of HTN as WC increases by 10cm (25).

Obesity causes pressure natriuresis in kidneys to shift to higher BP due to a rise in extracellular fluid volume and also provides a local renin-angiotensin system in adipose tissue which leads to systemic vasoconstriction and HTN (26, 27). Moreover, inflammatory condition and hyperinsulinemia as a result of obesity and insulin resistance provoke endothelial dysfunction which play a prominent role in developing HTN (28). BMI is an indicator of overall obesity and multiple studies reported its significant association with HTN, but abdominal obesity seems to be more strongly associated with HTN especially in women (29). A meta-analysis on 19 cross-sectional studies in Asians showed that indices of central obesity were more consistent among different groups and preferred to predict HTN (30). In 2018, Mutsert R, et al. indicated a significant association between visceral adipose tissue and insulin resistance which is a well-known risk factor in developing HTN (31). In addition, visceral adipose tissue acts as a source of leptin which stimulates sympathetic responses but has selective resistance to metabolic actions like energy expenditure (32). Moreover, Lin Y, et al. in a study on 396 participants in Taiwan found that WC can predict HTN more accurately than BMI and body fat percentage (33).

In our study, participants with HTN were not significantly different in ABSI and BRI with normotensives. In logistic regression analysis after adjusting for other variables, BRI was significantly associated with elevated DBP in women, but ABSI was not considered as a significant factor in HTN, high SBP and high DBP. A systematic review and meta-analysis on 11 studies evaluated these new indices and could not find a significant advantage over the older ones in predicting HTN (34). Also, in rural areas of Africa assessing 624 young adults, ABSI and BRI were not significantly associated with SBP and DBP (35).

Because of the limitation of BMI and WC, new anthropometric indices were introduced; in BRI formula, WC and height were used while ABSI used WC in relation to weight and height. Multiple studies evaluated the ability of conventional obesity indices to predict HTN including the study by Jayed A, et al. in which 57 cohort studies were evaluated and BMI was the strongest (36, 37). The results of the meta-analysis by Calderon G, et al. evaluating 11 studies was in consistent with our study, WC and BMI had the best performance in predicting HTN, and BRI was a better predictor than ABSI (34). ABSI is mostly used to assess the mortality risk regardless of BMI as Ji M, et al. reported a 55% increase in all-cause mortality risk which was higher than BMI and WC, and a 13% increase in the odds of HTN which was significantly lower (38).

However, in a study on 445 Portuguese adolescents, ABSI was superior in predicting HTN than BMI and WC (39). Another study in Iran on 5115 overweight/obese adults, mostly women, younger than our study, introduced BRI as a significant predictor of HTN in women (OR: 3.335, 95%CI: 1.589–7.286) (40). This can be due to differences in ethnicity of the participants which may affect body composition. James R, et al. revealed a higher risk of HTN at any level of BMI and WC among Asians compared to Caucasians (41), and Bell A, et al. explained that the distribution of fat differs in different ethnicities and Asians tend to have more abdominal fat (42).

AUC for BMI and WC was higher than new indices in almost all parts of our study, and ROC for HTN particularly in men demonstrates the higher power of BMI and WC in predicting hypertension, but for women there was not a large difference between different indices. However, AUC in all groups were under 0.7 which means their ability to predict HTN is not strong enough. Also, AUC for BRI, especially in women was higher than ABSI which means that BRI is more powerful in predicting HTN. Regression coefficients for BMI and WC with continuous BP and binary high SBP and high DBP were greater in men than women which suggests that BP in men is more sensitive to excess weight or abdominal fat. Zhou, et al. assessing a large population of Chinese people found the same results in this regard (43). BMI cannot distinguish between fat and muscle mass, so BMI in men having greater fat-free proportion may over-estimated the risk of HTN (44). Moreover, ABSI is analogous to BMI using WC in relation to both height and weight, but BRI uses WC in relation to only height which results in a more precise obesity index and HTN predictor in women than ABSI as Nkwana M, et al. revealed similar results evaluating 624 adults (20). On the other hand, in our study, men tend to develop HTN more than women as it is the same for the study by Eghbali M, et al. which revealed these differences more clearly (45).

We included a large community-dwelling population of adults over 60 years old and collected data about multiple related variables like physical activity, smoking habits, and other social ones to adjust our results and present a reliable conclusion. Nonetheless, we used WHO cut-offs to define obesity and introducing new cut-offs based on different populations, especially for older adults would help achieve more precise results. Moreover, the study faced the usual limitation of a cross-sectional research and all data were gathered at a certain point of time. Future longitudinal studies may better determine the association between HTN and body composition indices.

To conclude, BMI and WC showed the most powerful association with HTN among other indices, and BRI and ABSI, as new obesity indices, were not associated with HTN except for a slight but significant association between BRI and DBP in women. Further studies are suggested to address the ability of these new indices to predict cardio-metabolic diseases in different genders utilizing more accurate methodologies and certain cut-offs specific for that population.

Hypertension (HTN)

World health organization (WHO)

Renin angiotensin aldosterone system (RAAS)

Angiotensin converting enzyme (ACE)

Sympathetic nerve system (SNS)

Body mass index (BMI)

Waist circumference (WC)

A body shape index (ABSI)

Body roundness index (BRI)

Birjand longitudinal aging study (BLAS)

blood pressure (BP)

Systolic blood pressure (SBP)

diastolic blood pressure (DBP)

International Physical Activity Questionnaire (IPAQ)

Receiver-operating characteristic (ROC)

Area under the curve (AUC)

Ethics approval and consent to participate:

All procedure was approved by the ethical committee of the endocrinology and metabolism research institute of Tehran university of medical sciences under the code: IR.TUMS.EMRI.REC.1396.00158. The study was in accordance with Helsinki guidelines. The purpose and the process of the research were explained for each participant and written informed consent was obtained from all participants or their authorized representatives prior to participation.

Consent for publication:

Not applicable.

Availability of data and materials:

All data analyzed in this study are available from corresponding author upon reasonable request.

Competing interests:

The authors declare that they have no competing interests.

Funding:

This study received no external funding.

Author Contributions

F.S designed the study. M.M and F.E contributed to running of the population-based study and collecting the data. Z.S and H.F analyzed the data. A.P and H-S.E wrote the first draft of the manuscript. H-S.E, M.K and M.T contributed to the revision of the first draft. All the authors read and confirmed the final manuscript.

Acknowledgements

The authors would like to express their respect to the personnel involved in performing this study, and all the participants taking part in the BLAS.

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No competing interests reported.

Old and new anthropometric indices in relation to blood pressure among the elderly: Birjand longitudinal aging study

Status:

Version 1

Abstract

Figures

Introduction

Methods

Anthropometric indices

Blood pressure measurements

Other variables

Statistical analysis

Results

Discussion

Conclusions

Abbreviations

Declarations

References

Additional Declarations

Status:

Version 1