Inter-arm difference in systolic blood pressure: Prevalence and associated factors in an African population.

OBJECTIVES: Inter-arm blood pressure difference (IABPD) can lead to underdiagnosis and poor management of hypertension, when not recognized and are associated with increased cardiovascular mortality and morbidity. However, the prevalence and associated risk factors of IABPD in sub-Saharan Africa are unknown. This study aims to determine the prevalence and associated risk factors of IABPD among Tanve Health Study (TAHES) participants, a cohort about cardiovascular diseases in a rural area in Benin.
METHODS: The cohort was conducted since 2015 among adults aged 25 years and over in Tanve village. Data were collected from February to March, 2020. Brachial blood pressure were recorded at rest on both arm with an electronic device. Systolic IABPD (sIABPD) was defined as the absolute value of the difference in systolic blood pressure between left and right arms ≥ 10 mmHg. A multivariate logistic regression models identified factors associated with sIABPD.
RESULTS: A total of 1,505 participants (women 59%) were included. The mean age was 45.08 ±15.65 years. The prevalence of sIABPD ≥ 10 mmHg was 19% (95%CI: 17-21). It was 19% (95%CI: 16-22) in men and 20% (95%CI: 17-22) in women. In final multivariable model, the probability of sIABPD ≥ 10 mmHg increased significantly with age (adjusted OR (aOR) = 1.1; 95%CI: 1.02-1.20 per 10-years), hypertension (aOR = 2.33; 95%CI: 1.77-3.07) and diabetes (aOR = 1.96; 95%CI: 1.09-3.53).
CONCLUSION: Almost quarter of sample have a sIABPD ≥ 10 mmHg, with an increased risk with older age and hypertension and diabetes.

Introduction

Cardiovascular diseases (CVD) is the leading cause of death worldwide [1]. Hypertension is one of the most important modifiable cardiovascular risk factors (CVRFs) and can be controlled by lifestyle changes or drug therapy, hence the interest in blood pressure (BP) measurements in high-risk populations [2]. BP measurement is part of routine clinical examination, especially as the detection of hypertension is a key component of clinical cardiovascular assessment [3]. Bilateral measurement of BP in both arms is recommended by many guidelines at initial visit and then annually [4, 5], for preventing misdiagnosis of hypertension [6]. The risk of cardiovascular morbidity and mortality seems to increase with inter-arm blood pressure difference (IABPD) [7, 8]. Indeed, although a threshold of IABPD of 10 mmHg is admitted in clinical practice, any difference beyond 5 mmHg is proportionally associated with cardiovascular and mortality risk increase [8-13].

The vast majority of the studies on IABPD were performed in the developed countries [14-18]. Data on the prevalence and associated risk factors of IABPD in sub-Saharan Africa are scarce. As CVRFs are increasing in low- and middle-income countries, the assessment of IABPD, an easy and inexpensive risk predictor is of high interest in this setting. Taking the opportunity of a population-based study in Benin, we aimed to determine the prevalence and associated risk factors of IABPD in a rural community of Benin.

Methods

Design and population study

Our study is based on data from the TAnve Health Study (TAHES) cohort. This is a prospective cohort in Benin since February 2015, in the two neighbouring villages of Tanve and Dékanme, located in the commune of Agbangninzoun, 150 km away from Cotonou, the economic capital of Benin (S1 File). Tanvè has health center including a dispensary and a maternity [19]. This cohort includes people resident at least 6 months in the villages of Tanvè or Dékanmè, aged 25 years and over. Participants’ consents were obtained. Pregnant woman and participants unable to answer the questions were excluded from the study. This cross-sectional study on IABPD used the fifth annual survey of TAHES conducted from February 8 to March 1, 2020.

Data collection

Data was collected during a systematic door-to-door survey by 7 team of 2 trained investigators, according to the WHO STEPS methodology [20]. Demographic, lifestyle (alcohol, tobacco, sedentary, fruit and vegetable consumption), history of diseases (hypertension, diabetes), weight, height, brachial BP, blood glucose and proteinuria data were collected using a questionnaire adapted from WHO STEPS tools.

Blood pressure measurements

Brachial BP were recorded in both arms, using an electronic device (OMRON M3, HEM-7131), with adequate cuffs for normal and large arms. Three measures were performed on both arms at three minutes intervals, in seated position after a rest of at least 15 minutes. On each arm, BP was defined as the average of the last two measurements. sIABPD ≥10 mmHg was defined as the absolute value of the difference for SBP between the left and right arms greater than or equal to 10 mmHg [9].

Other variables

Covariates were defined according to WHO recommendations for STEPS surveys [20]. Low fruit and vegetable consumption was defined as less than five portions (400 grams) of fruits and vegetables per day. Current and former (less than one year) smokers were considered as active smokers. Sedentary lifestyle was considered as sitting/sleeping for more than 8 hours daily, outside the night-sleep period. Body Mass Index (BMI) was calculated as weight in kilograms divided by the square of height in meters. The BMI was categorized in four groups: underweight (<18.5kg/m2), normal (from 18.5 to 24.9 kg/m2), overweight (from 25 and 29.9 kg/m2), and obesity (≥ 30kg/m2). Hypertension was defined as systolic and/or diastolic blood pressure ≥ 140/90 mmHg in the highest of the two arms, or whether receiving anti-hypertensive medication. Diabetes was defined by fasting capillary whole blood glucose value ≥ 7 mmol/L or currently taking diabetes medication. Semi-quantitative proteinuria was assessed based on urine protein dipstick and defined by the color change of an indicator (from ‘trace ‘ to ‘++++’) [21]. Anxiety and depression were respectively assessed using Goldberg Anxiety Scale (GAS) and Goldberg Depression Scale (GDS) [22]. Each global score, ranges from 0 to 18, and questions/items were based on responses “yes” or “no”, rated one or zero point respectively. Anxiety was defined by GAS ≥ 5 and depression by GDS ≥2 [22]. Data on history of cardiovascular or neurological disease, such as peripheral arterial disease, heart failure, angina, and stroke, were based on previous diagnosis by a professional health care.

Ethics approval and consent to participate

The TAHES protocol received approval No. 026 of August 28, 2014, from the National Committee of Ethics for Health Research (CNERS) of the Ministry of Health of Benin. Informed and written consent was required for each participant before inclusion in TAHES. Furthermore, a physician recruited for the study examined participants with abnormal BP. Following their examinations, they received counseling, prescription drugs and were referred to the Abomey municipal health center for further exams or the regional hospital for cardiologic consultation, depending on the participant’s situation.

Statistical analysis

All analyses were performed using the software R (version 3.6.2). Baseline characteristics of study participants were described and compared according to sIABPD ≥ 10 mmHg status using chi-square or Fisher’s tests for qualitative variables and Wilcoxon test for quantitative variables. The prevalence of sIABPD ≥ 10 mmHg was estimated. This prevalence has been described according to gender and age and compared using chi-square test. Distribution of sIABPD was performed. The prevalence of sIABPD was also described according to SBP classification defined by ESC 2018 guidelines (optimal <120 mmHg, normal: 120–129 mmHg, High normal: 130–139, Grade 1 Hypertension: 140–159, Grade 2 Hypertension: 160–179, Grade 3 Hypertension ≥ 180 mmHg) [5]. Associated factors to sIABPD were identified by using logistic regression models. We have tested association between sIABPD with each covariates and p value less than 0.20 were included in multivariable analysis, along with age and gender systematically.

The interactions between variables included in multivariable model were tested. In addition linearity of quantitative variables on logit of the probability to have a sIABPD ≥ 10 mmHg was checked. We proceeded by backward stepwise selection to obtain the final model. In the sensitivity analysis, the factors associated with sIABPD ≥ 15 mm Hg were identified using a logistic regression model. Odds ratio (OR) and their confidence intervals (CI) at 95% were reported and a p value less than 0.05 was considered as statistically significant.

Results

Study population

A total of 1,571 participants were included in the TAHES cohort in 2020. Among them, 66 pregnant women were excluded. Thus, 1505 participants were included in this study (Fig 1). The mean age was 45.08 ±15.65 years. The sex ratio (male/female) was 0.7 (Table 1).

Fig 1

Flowchart of inclusion in this study population from TAHES cohort, 2020.

Table 1

Systolic inter arm blood pressure difference groups according to socio-demographic characteristics, behavioural characteristics, anxiety, depression and proteinuria, TAHES study, Benin 2020.

	Total (N = 1505)	sIABPD ≥ 10 mmHg (N = 292)	sIABPD < 10 mmHg (N = 1213)	p-valueⱠ
	Mean (sd) / n (%)	Mean (sd) / n (%)	Mean (sd) / n (%)
Age (years)	45.08 ±15.7	49.1 ± 16.7	44.1±15.2	<10–5
Gender
Female	893 (59.3)	176 (60.3)	717 (59.1)	0.7663
Male	612 (40.7)	116 (39.7)	496 (40.9)
Education levels
Illiterate	1019 (67.7)	207 (70.9)	812 (66.9)
Less than primary level	256 (17.0)	43 (14.7)	213 (17.6)	0.3976
Primary level and above	230 (15.3)	42 (14.4)	188 (15.5)
Marital status
In couple	1261 (83.8)	229 (78.4)	1032 (85.1)	<10–5
Single, widowed or divorced	244 (16.2)	63 (21.6)	181 (14.9)
Occupation
Small self-employed without trade register	907 (60.3)	167 (57.2)	740 (61.0)
Independent farmer/contractor	243 (16.1)	58 (19.9)	185 (15.3)	0.0688
Small business employee/farm worker	144 (9.6)	21 (7.2)	123 (10.1)
Private employee or official worker	43 (2.9)	6 (2.1)	37 (3.1)
Retired/unemployed/other/student/apprentice	168 (11.2)	40 (13.7)	128 (10.6)
Monthly income ($US)
< 68	832 (55.3)	155 (53.1)	677 (55.8)
68–117	380 (25.2)	77 (26.4)	303 (25.0)	0.6997
≥ 117	293 (19.5)	60 (20.5)	233 (19.2)
Tobacco smoking	75 (5.0)	21 (7.2)	54 (4.5)	0.0748
Low intake of fruit & vegetable	756 (50.2)	138 (47.3)	618 (50.9)	0.2863
Sedentarity behaviour	162 (10.8)	37 (12.7)	125 (10.3)	0.2864
Alcohol consumption last 30 days	754 (50.1)	148 (50.7)	606 (50.0)	0.8748
BMI (Kg/m 2 )
Normal	870 (57.8)	166 (56.8)	704 (58.0)
Underweight	218 (14.5)	46 (15.8)	172 (14.2)	0.2394
Overweight	283 (18.8)	47 (16.1)	236 (19.5)
Obesity	134 (8.9)	33 (11.3)	101 (8.3)
Cardiovascular or neurological history
Peripheral arterial disease	7	0	7
Heart failure	4	0	4	0.278
Angina pectoris	5	1	4
Stroke	4	2	2
Hypertension	518 (34.4)	155 (53.1)	363 (29.9)	<10–5
Diabetes	55 (3.7)	19 (6.5)	36 (3.0)	<10–5
Anxiety	266 (17.7)	65 (22.3)	201 (16.6)	<10–5
Depression	555 (36.9)	121 (41.4)	434 (35.8)	0.0833
Proteinuria	56 (3.7)	8 (2.7)	48 (4.0)	0.4153

sIABPD: Systolic inter arm blood pressure difference

Ⱡ: p value of chi-square or Fisher’s tests for qualitative variables and Wilcoxon test for quantitative variable

The mean of Systolic blood pressure (SBP) and diastolic blood pressure (DBP) of participants were 126.9±20.2 and 83.5 ±12.9 mmHg, respectively. In our study population, 518 (34.4%) participants had hypertension; among them 161 (10.7%) were on treatment.

Prevalence of sIABPD

Of the participants, 292 had a sIABPD ≥ 10 mmHg for a prevalence estimated at 19.4% (95%CI: 17.4%-21.5%). Among 1,505 participant’s, there were 11.4%, 4.9% and 3.0% with a sIABPD in the ranges: 10-14mmHg, 15-19mmHg and ≥ 20mmHg respectively. Frequency of sIABPD ≥ 10 mmHg was almost the same in men and in women in all sIABPD groups except for the one ≥ 20 mmHg in which sIABPD was slightly more frequent in women (Fig 2). In participants aged 45 to 54 years, the prevalence of sIABPD ≥ 10 mmHg was significantly higher in men than women. In contrast, there was no statistically significant difference in the prevalence of sIABPD ≥ 10 mmHg according to gender in the other age groups (Fig 3). The prevalence of sIABPD increased with the rise in SBP (Fig 4).

Fig 2

Distribution of absolute systolic inter-arm blood pressure difference (sIABPD) by gender, TAHES study, Benin 2020.

Fig 3

Gender prevalence of systolic inter-arm blood pressure difference (sIABPD) ≥ 10 mmHg by age groups, TAHES study, Benin 2020.

Fig 4

Prevalence of sIABPD ≥ 10 mmHg by systolic blood pressure classification, TAHES study, Benin 2020.

Risk factors for sIABPD

Univariate logistic regression has shown a higher probability of sIABPD ≥ 10mmHg per 10-years of age (p<0.001). Increasing age, living alone, hypertension and diabetes were associated with higher prevalence of sIABPD ≥ 10 mmHg (Table 2). In a multivariate model adjusted for age and gender, both diabetes and hypertension were independently associated with sIABPD ≥ 10 mmHg (Table 3).

Table 2

Factors associated with systolic inter-arm blood pressure difference ≥ 10 mmHg, univariate analysis, TAHES study, Benin 2020.

	Univariate analysis
	Crude OR [CI 95%]	p-valueⱠ
Age (per 10 years)	1.21 [1.12–1.31]	< 0.001*
Gender
Female (vs. male)	1.05 [0.81–1.36]	0.716
Education levels
Illiterate	1	0.39
Less than primary level	0.79 [0.55–1.14]
Primary level and above	0.88 [0.61–1.27]
Marital status
Single, widowed or divorced (vs. in couple)	1.57 [1.14–2.16]	0.006*
Occupation
Small self-employed without trade register	1	0.07
Independent farmer/contractor	1.39 [0.99–1.95]
Small business employee/farm worker	0.76 [0.46–1.24]
Private employee or official worker	0.72 [0.30–1.73]
Retired/unemployed/other/student/apprentice	1.38 [0.93–2.05]
Monthly income ($US)
< 68	1	0.7
68–117	1.11 [0.82–1.51]
≥ 117	1.12 [0.81–1.57]
Tobacco smoking (vs non-smokers)	1.66 [0.99–2.80]	0.056
Low intake of fruit & vegetable (Yes vs No)	0.86 [0.67–1.11]	0.258
Sedentarity behavior (Yes vs No)	1.26 [0.85–1.87]	0.242
Alcohol consumption last 30 days (Yes vs No)	1.03 [0.80–1.33]	0.824
BMI (Kg/m 2 )
Normal	1	0.249
Underweight	1.13 [0.79–1.64]
Overweight	0.84 [0.59–1.21]
Obesity	1.39 [0.90–2.13]
Hypertension (Yes vs No)	2.65 [2.04–3.44]	< 0.001*
Diabetes (Yes vs No)	2.28 [1.29–4.03]	0.005*
Anxiety (Yes vs No)	1.44 [1.05–1.97]	0.023*
Depression (Yes vs No)	1.27 [0.98–1.65]	0.072
Proteinuria (Yes vs No)	0.68 [0.32–1.46]	0.327

OR: Odd ratio

Ⱡ: p value of Wald test for binary variables or likelihood test for categorical variables with more than two modalities

*: Statistically significant

Table 3

Factors associated with systolic inter-arm blood pressure difference (sIABPD) ≥ 10 mmHg, multivariable analysis, TAHES study, Benin 2020.

	Initial model		Final model1
	aOR (95%CI)	p valueⱠ	aOR (95%CI)	p valueⱠ
Age (per 10 years)	1.07 [0.97–1.18]	0.181	1.11 [1.02–1.21]	0.012*
Gender
Female (vs. male)	1.01 [0.76–1.34]	0.959	1.03 [0.79–1.35]	0.83
Marital status		0.465
Single, widowed or divorced (vs. couple)	1.15 [0.79–1.69]
Occupation		0.423
Small self-employed without trade register	1
Independent farmer/contractor	1.22 [0.85–1.76]
Small business employee/farm worker	0.76 [0.46–1.25]
Private employee or official worker	0.65 [0.26–1.60]
Retired/unemployed/other/student/apprentice	0.99 [0.64–1.53]
Tobacco smoking (Yes vs No)	1.32 [0.76–2.30]	0.322
Hypertension (Yes vs No)	2.33 [1.77–3.08]	< 0.001	2.33 [1.77–3.07]	< 0.001*
Diabetes (Yes vs No)	2.05 [1.13–3.70]	0.017	1.96 [1.09–3.53]	0.024*
Anxiety (Yes vs No)	1.16 [0.81–1.67]	0.413
Depression (Yes vs No)	1.11 [0.83–1.50]	0.475

aOR: Adjusted odd ratio; Final model adjusted on age, gender, high blood pressure, diabetes and anxiety

Ⱡ: p value of Wald test for binary variables or likelihood test for categorical variables with more than two modalities

*: Statistically significant

1: All the variance inflation factor (VIF) of the variables of the final model are ≤ 5.

In sensitivity analysis, hypertension and education levels were statistically associated with sIABPD ≥ 15 mmHg (S2 File).

Discussion

In this study, we found a very high prevalence (19.4%) of sIABPD ≥ 10 mmHg. Older age, hypertension and diabetes was associated to sIABPD ≥ 10 mmHg. To our knowledge, this is the first report from a study in an African population.

The prevalence of sIABPD ≥ 10 mmHg in this study was higher than some results of previous studies conducted in general populations [23-25]. In Japan, Kimuraa et al. reported a prevalence of 9.1% [24]. In Finland, Johansson et al. reported a prevalence of 10.1% in general population [23]. In the Framingham Heart Study, 9.4% of participants had a sIABPD ≥10 mmHg [25]. Our higher prevalence might be explained by differences in methods used for BP measurement and study populations. In our study, we performed sequentially three successive BP measures on each arm in a seated position. Kimuraa et al. in the Ohasama study measured BP simultaneously in both arms only two times but in supine position [24]. Also, in the Framingham Heart Study, BP was measured sequentially three times in supine position [25]. The guidelines for hypertension recommend repeated BP measurement in seated position to acquire accurate BP values [26, 27]. However, according to a meta-analysis, the number of subjects with a systolic and diastolic IABPD ≥10 mm Hg was significantly lower when BP measurements were performed simultaneously instead of sequentially [12]. This could have overestimated the prevalence of sIABPD ≥10 in this study.

Our prevalence was similar with pooled prevalences of the sIABPD ≥ 10 mmHg found by Clark et al. in a systematic review (19.6%) [7]. In the studies retained in their review, most of the participants were patients with high risk of cardiovascular factors/outcomes (hypertensive, diabetics, and patients with renal or vascular disease). The prevalence of cardiovascular risk factors such as hypertension (34.4%), diabetes (3.7%) and anxiety (17.7%) are also high in our study. This could explain the high prevalence of sIABPD observed [7]. In fact depression and anxiety are significantly correlated with IABPD [28]. A continual anxiety response raises BP, largely due to hormones and chemical reactions. Stress and anxiety do not only increase the workload on the cardiovascular system but also lead to sympathetic activation of the Renin-Angiotensin system [28].

In our study, increasing of age was associated with sIABPD ≥ 10 mmHg. This association has been demonstrated in previous studies [24, 29],as well as significant association between hypertension and sIABPD ≥ 10 mmHg [23–25, 30, 31] and also association between diabetes and sIABPD ≥ 10 mmHg [15, 29].

In sensitivity analysis, using IAD ≥ 15 mmHg as the cutoff for asymmetry, hypertension remained significantly associated with sIABPD. This result is consistent with the literature. Indeed, both UK and European guidelines recognize a systolic difference of 15 mmHg or more between the two arms as the threshold for additional cardiovascular risk [5, 32]. However, a recent study reports that a limit of 10 mm Hg may already leads to cardiovascular issues [9]. In contrast to the results from our main analysis, education level was found to be significantly associated with sIABPD ≥ 15 mmHg in sensitivity analysis. It is well known that educational inequality is one of the important factors that could increase the risk of CVD occurrence. Greater education tends to be associated with healthier behaviors, occupations with healthier working conditions, and better access to health care [33]. In addition, the increase in the cutoff point of the sIABPD value for sensitivity analyses may also explain the observed significance on this relation.

The main limitation of this study is the sequential measurement of BP, where beat-to-beat blood pressure variability explains in part the IABPD. We were unable to provide simultaneous measurement because of lack of specific machines. However, in clinical practice, and even more in low-income countries, BP is measured sequentially, so the clinical consequences of our findings could be considered relevant. Another limitation of our study is the low repeatability of sIABPD. This could lead to variability in the prevalence of sIABPD in our study population. We also had no information about lipid levels and the use of lipid-lowering drugs in our population, these factors might be associated with sIABPD. Single point measurement for hypertension and hyperglycemia is also a limitation of our study as it could lead to an overestimation of their prevalence. The other limitation is the cross-sectional nature of our study so that we are not able to provide the prognostic value of systolic IABPD in our cohort. Long-term follow-up of our cohort will enable to provide this information.

In conclusion, this first study in an African-population, we report a high prevalence of sIABPD ≥ 10 mmHg in a rural population in Benin. Age, hypertension, and diabetes were significantly associated. Assessment of BP in both arms should become an essential component of clinical examination in general population, and cardiovascular risk assessment especially for individuals with hypertension or diabetes.

Subdivision of Benin into departments and geographical location of the study area (Tanve area) in Benin.

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Factors associated with systolic inter-arm blood pressure difference ≥ 15 mmHg, univariate and multivariate analysis, sensitivity analysis, TAHES study, Benin 2020.

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5 Oct 2021

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Reviewer #1: In this manuscript, the authors investigated the prevalence and associated factors of inter-arm difference in systolic blood pressure in an African population. A total of 1,505 participants (women 59%) were included. They found that the prevalence of sIABPD ≥ 10 mmHg was 19% (95% CI: 17–21%). Moreover, the probability of sIABPD ≥ 10 mmHg increased significantly with age, hypertension and diabetes.

1. Prevalence of sIABPD rises in relation to underlying cardiovascular comorbidities of the population studied. Therefore, the prevalence of peripheral arterial disease, CAD, or cerebrovascular disease should be recorded in your manuscript.

2. BP is a variable hemodynamic phenomenon that constantly fluctuates over time, making sequential measurements difficult to compare, therefore, to prevent overestimation and observer bias, sIABPD should be assessed simultaneously at both arms.

3. Lipid related indicators should be included and analyzed as risk factors, such as triacylglycerol, total cholesterol and LDL-C. Moreover, the use of anti-hypertensive drugs, anti-diabetic agents，statins should be recorded and adjusted in your Multivariate analysis.

4. The repeatability of sIABPD is poor, which should be mentioned in the limitation.

5. The results are best to be illustrated in paragraphs:

1）study population

2）Prevalence of sIABP difference

3）Risk factors for sIABP difference

Moreover, the content of the results should be stated more specifically.

6. In Statistical analysis, you mentioned that‘The interactions between variables included in multivariable model were tested as well as linearity of quantitative variables’. While, no related results cannot be found in your manuscript.

7. Your manuscript only excluded pregnant woman, while participants lacking of systolic BP or diastolic BP in both arms or lacking of other risk factors should also be excluded. Moreover, the accurate number or percentage of missing values should be illustrated.

8. In the results, you mentioned that ‘An increase in the prevalence of sIABPD by age group was observed in both men and women (Figure 3)’. While the P value and P-trend value in Figure 3 should be calculated.

9. Why the Multivariate analysis included both Initial model and Final model?

Reviewer #2: This study explored the prevalence and risk factors of inter-arm blood pressure difference in Tanve village. Despite the great efforts of the research team, I think this article cannot yet conclude that IABPD can assess cardiovascular risk.

First, the medical history of subjects was missing in the multiple regression model, especially the history of cardiovascular disease, such as coronary artery disease, stroke or peripheral arteria disease.

Second, the definition of diabetes in this study, which was defined by fasting blood glucose value ≥ 7 mmol/L or currently taking diabetes medication, did not meet the existing diagnostic guidelines.

In addition, I think that the subjects' lipid levels and their use of lipid-lowering drugs will also be associated with IABPD, which was unfortunately not mentioned in the article.

Finally, what is the relationship between different office blood pressure levels and IABPD in this study? Consider including stratified analysis of office blood pressure or as a continuous variable into multiple regression model analysis.

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1 Dec 2021

Dear editor,

We thank you for giving us the opportunity to revise and resubmit our manuscript. We also thank the reviewers for the helpful comments aiming at improving the article. We propose here a revised version accounting for the comments and suggestions made by the reviewers. We remain available for further request.

Best regards

PONE-D-21-28514

Inter-Arm Difference in Systolic Blood Pressure: Prevalence and Associated Factors in an African Population

PLOS ONE

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: No

Reviewer #2: Yes

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: Yes

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer reports:

Reviewer 1:

1. Prevalence of sIABPD rises in relation to underlying cardiovascular comorbidities of the population studied. Therefore, the prevalence of peripheral arterial disease, CAD, or cerebrovascular disease should be recorded in your manuscript.

We thank the reviewer for these comments. We cannot provide information on peripheral arterial disease because the ankle-brachial index was not measured in 2020. Also, the level of diagnosis of coronary artery disease and cerebrovascular disease is very low due to under-medicalization. However, we provided in table 1 information on participants’ history of cardiovascular and neurological diseases.

2. BP is a variable hemodynamic phenomenon that constantly fluctuates over time, making sequential measurements difficult to compare, therefore, to prevent overestimation and observer bias, sIABPD should be assessed simultaneously at both arms.

Thank you for this comment. We agree with the beat-to-beat variability of BP, but devices measuring simultaneously both arms are not available in practice in Africa, so the clinical interest is questionable. Also, most studies on IABPD have been performed with sequential measurement. This point has been highlighted in the discussion.

3. Lipid related indicators should be included and analyzed as risk factors, such as triacylglycerol, total cholesterol and LDL-C. Moreover, the use of anti-hypertensive drugs, anti-diabetic agents，statins should be recorded and adjusted in your Multivariate analysis.

We have presented all the available variables in Tables 1. However, regarding to the insertion of preventive therapies variable in the multivariate model, this lead a methodological concern. Indeed, there was a strong collinearity between the use of a treatment (e.g. antihypertensive therapy) and presence of factor such as Hypertension, or high blood pressure in the same model. Because the level of use of medication very low in this low income community with low medical resource, we preferred to use the risk factors, rather than the treatment, in the models. The proportion of hypertensive participants on treatment has been reported in the results section.

4. The repeatability of sIABPD is poor, which should be mentioned in the limitation.

We thank reviewer for this comment. We have considered this point in the limitation in discussion section.

5. The results are best to be illustrated in paragraphs:

We have considered this point in the result section

1）Study population

2）Prevalence of sIABP difference

3）Risk factors for sIABP difference

Moreover, the content of the results should be stated more specifically.

We have taken this comment in consideration in the results section.

6. In Statistical analysis, you mentioned that‘The interactions between variables included in multivariable model were tested as well as linearity of quantitative variables’. While, no related results cannot be found in your manuscript.

These analyses are multiple and would dramatically lengthen the results chapter. This kind of analysis is rarely presented in manuscripts. We can send to the editorial team the statistical reports if requested. They have been performed.

7. Your manuscript only excluded pregnant woman, while participants lacking of systolic BP or diastolic BP in both arms or lacking of other risk factors should also be excluded. Moreover, the accurate number or percentage of missing values should be illustrated.

All participants had bilateral measurements and data on risk factors collected.

8. In the results, you mentioned that ‘An increase in the prevalence of sIABPD by age group was observed in both men and women (Figure 3)’. While the P value and P-trend value in Figure 3 should be calculated.

We calculated the p value of the association between sex and sIABPD in each age group.

9. Why the Multivariate analysis included both Initial model and Final model?

Any multivariate analysis with stepwise approach has an initial and then final model. We considered fair to present both so to bring more information. We think that the reader would better understand where we have started and where we have ended by showing both.

Reviewer #2:

1. First, the medical history of subjects was missing in the multiple regression model, especially the history of cardiovascular disease, such as coronary artery disease, stroke or peripheral arteria disease.

We thank the reviewer for this comment. As mentioned earlier, we cannot provide information on peripheral arterial disease because the ankle-brachial index was not measured in 2020. Also, the level of diagnosis of coronary artery disease and cerebrovascular disease is very low due to under-medicalization. However, we provided information on cardiovascular and neurological conditions reported by the participants.

2. Second, the definition of diabetes in this study, which was defined by fasting blood glucose value ≥ 7 mmol/L or currently taking diabetes medication, did not meet the existing diagnostic guidelines.

The definition used for diabetes is those recommended by World Health Organization for STEPS surveys. In addition, the cohort is dynamic, so there are participants who have never been evaluated in previous years. Therefore, we cannot use only the data from previous years to define the history. As we performed single point measurement of blood pressure and glycemia, we have added within the limit section (p 10) the following: “Single point measurement for hypertension and hyperglycemia is also a limitation of our study as it could lead to an overestimation of their prevalence”.

3. In addition, I think that the subjects' lipid levels and their use of lipid-lowering drugs will also be associated with IABPD, which was unfortunately not mentioned in the article.

We agree with the reviewers' comment. However, we do not have data on the participants’ lipid levels or the use of lipid-lowering drugs. We have added this point in the limitation in discussion section.

4. Finally, what is the relationship between different office blood pressure levels and IABPD in this study? Consider including stratified analysis of office blood pressure or as a continuous variable into multiple regression model analysis.

We have not done office BP measurements. Therefore, we cannot determine what the relationship is between the sIABPD and the office BP measurements found in a practice. However, in this new version of the manuscript, we have presented a figure that shows the relationship between the sIABPD and the conventional BP classification groups.

Submitted filename: Reviewer2.docx

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9 Feb 2022

4 Apr 2022

Response to Reviewers

Dear editor,

Thank you to giving again the opportunity to review and resubmit our manuscript. We also thank the reviewer for his/her additional comments. A revised version taking into account the reviewer’ comments and journal requirements is provided here.

Best regards

PONE-D-21-28514R1

Inter-Arm Difference in Systolic Blood Pressure: Prevalence and Associated Factors in an African Population

PLOS ONE

Journal requirements

Please consider the additional comments of Reviewer 1 in your revision. In addition, could you try to use the inter-arm SBP difference as a continuous variable to investigate the determinants, and perform sensitivity analyses using 15 mm Hg as a cut-off of the large inter-arm BP difference?

We thank the editor for his/her comments. We have responded to the questions of reviewer 1 and conducted a sensitivity analysis using 15 mm Hg as a cut-off of the large inter-arm BP difference as requested.

Regarding suggestion related to the use of inter-arm SBP difference as a continuous variable to investigate the determinants, we observed that all assumptions and conditions for linear regression (e.g., the normality of error distribution and homoscedasticity) were not satisfied. Therefore, we can’t run linear regression as our predictions won’t be accurate.

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Reference list have been checked. No retracted articles have been cited in our work.

Reviewer #1: Thanks for your modification, while there exist minor questions as following.

1. Table 2 and 3 in Result should be capitalized.

We thank reviewer for this comment. We have taken this comment in consideration in the results section.

2. The P value of female in Table 3 is missing.

This information is now provided in the Table 3.

3. You need not to show me the specific process of collinearity, while you need to tell me the final results about the collinearity. Because the backward stepwise method maybe not solid when the independent variables are highly correlated. Furthermore, I wonder why you chose backward instead of stepwise logistic regression?

The stepwise approches includes backward and forward selection.

Backward selection - starting with the full model has the advantage of considering the effects of all variables simultaneously. In contrast with the reviewer statement, this selection approach is especially important when variables in a model are correlated which each other as backward stepwise may be forced to keep them all in the model unlike forward selection where none of them might be entered. In addition, R and other software automatically calculate the best thresholds required to identify the best model (model with the highest likelihood, the one with the lowest Akaike information criterion).

4. In your manuscript, I suppose that the initial model refers to the result of general multiple logistic regression, while the final model refers to the result of backward stepwise selection with the variables which P value less than 0.2 in Initial model. Is my understanding correct? Dose there exist any reference for similar analyses?

The initial model includes the variables which p-value less than 0.2 in univariables analysis. Except, age and sex that we imposed in the final model, the variables in this model are those obtained at the end of the backward stepwise selection. Compared to initial model, the final model was those with the highest likelihood, the one with the lowest Akaike information criterion (Akaike value of initial model is 1434 and which for final model is 1426). Then, in this final model, only the variables which have a p-value less than 0.05 were considered as statistically associated with our dependent variable.

More detail about the backward stepwise selection method are describe in this manuscript “Sanchez-Pinto LN, Venable LR, Fahrenbach J, Churpek MM. Comparison of variable selection methods for clinical predictive modeling. Int J Med Inform. 2018 Aug;116:10-17. doi: 10.1016/j.ijmedinf.2018.05.006. Epub 2018 May 21. PMID: 29887230; PMCID: PMC6003624. »

Submitted filename: Response to Reviewers.pdf

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16 May 2022

13 Jun 2022

Response to Reviewers

Dear editor,

Thank you to giving again the opportunity to review and resubmit our manuscript. We also thank the reviewer for his/her additional comments. A new revised version taking into account the reviewer’ comments is provided here.

Best regards

PONE-D-21-28514R1

Inter-Arm Difference in Systolic Blood Pressure: Prevalence and Associated Factors in an African Population

PLOS ONE

Reviewer #1:

The actual contents of Supplement 1 and 2 are inconsistent with the supposed contents.

We thank reviewer for this comment. Supplement 1 shows the location of the study area on the Benin map . Supplement 2 presents the results from the sensitivity analysis.

The main approaches for stepwise regression are: Forward selection, Backward elimination and Bidirectional elimination (a combination of the above, testing at each step for variables to be included or excluded.), instead of only backward and forward selection. Backward elimination is especially important in case of collinearity, while whether the multivariable model have multicollinearity or not? Please give the Tolerance value and/or VIF value in the results.

Please find below the VIF values of each variable in this model. All VIF were lower than 5 suggesting that there no multicollinearity issues in our final model. As suggested by the reviewer, we added this information in results section in the table 3.

Age Gender Hypertension Diabetes

VIF 1.11 1.00 1.10 1.00

Please add to the Discussion of your interpretation for the consistent and inconsistent results between sensitivity analyses and the main analyses.

We thank reviewer for this comment. We have taken this comment in consideration in the discussion section. (See Page 10)

Submitted filename: Response to Reviewers.pdf

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25 Jul 2022

Inter-Arm Difference in Systolic Blood Pressure: Prevalence and Associated Factors in an African Population

PONE-D-21-28514R3

Dear Dr. GBAGUIDI,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Academic Editor

PLOS ONE

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Reviewer's Responses to Questions

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Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

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Reviewer #1: Yes

Reviewer #2: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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22 Aug 2022

PONE-D-21-28514R3

Inter-Arm Difference in Systolic Blood Pressure: Prevalence and Associated Factors in an African Population.

Dear Dr. Gbaguidi:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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