
==== Front
BMC Cardiovasc Disord
BMC Cardiovasc Disord
BMC Cardiovascular Disorders
1471-2261
BioMed Central London

4150
10.1186/s12872-024-04150-0
Research
Masked uncontrolled hypertension among elderly black sub-saharan africans compared to younger adults: a cross-sectional in-hospital study
Swambulu Tresor Mvunzi 1
Mundedi Yannick Samafundu 1
Nsimbi Yves Lubenga 1
Bompeka François Lepira 2
Natuhoyila Aliocha Nkodila 3
Risasi Jean-Robert Makulo 2
Ilunga Cédric 2
Kintoki Vita Eleuthère 1
Kiese Diane Kuntonda 1
Onembo Noel Otshudi 1
Minga Roger Kongo 4
Madoda Olivier Tuyinama 5
M’buyamba-Kabangu Jean-René 1
http://orcid.org/0000-0001-9836-9532
Phanzu Bernard Kianu doctorkianu@gmail.com

1
1 grid.9783.5 0000 0000 9927 0991 Cardiology Unit, University of Kinshasa, Kinshasa 1, PO Box 1038, Kinshasa, Democratic Republic of Congo
2 grid.9783.5 0000 0000 9927 0991 Division of Nephrology, Department of Internal Medicine, University of Kinshasa, Kinshasa, Democratic Republic of Congo
3 grid.442362.5 0000 0001 2168 290X Department of Family Medicine and Primary Health Care, Protestant University in the Congo, Kinshasa, Democratic Republic of Congo
4 Unit of cardiology, Clinique Ngaliema, Kinshasa, Democratic Republic of Congo
5 Emergency Unit, Centre Médical de Kinshasa, Kinshasa, Democratic Republic of Congo
4 9 2024
4 9 2024
2024
24 47229 1 2024
29 8 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Background

Although aging and being of African descent are well-known risk factors for masked uncontrolled hypertension (MUCH), data on MUCH among elderly black sub-Saharan Africans (BSSA) are limited. Furthermore, it is unclear whether the determinants of MUCH in younger individuals differ from those in the elderly.

Objective

This study aimed to determine the prevalence and risk factors associated with MUCH in both elderly and younger BSSA individuals.

Methods

In this study, 168 patients with treated hypertension were assessed for medical history, clinical examination, fundoscopy, echocardiography, and laboratory data. All patients underwent ambulatory blood pressure (BP) monitoring for 24 h. MUCH was diagnosed if the average 24-h mean BP ≥ 130/80 mmHg, the daytime mean BP ≥ 135/85 mmHg, and/or the nighttime mean BP ≥ 120/70 mmHg, despite controlled clinic BP (≤ 140/90 mmHg). Logistic regression analysis was performed to assess independent factors associated with MUCH, including elderly and younger adults separately. P-values < 0.05 were used to indicate statistical significance.

Results

Of the 168 patients aged 53.6 ± 11.6 years, 92 (54.8%) were men, with a sex ratio of 1.2, and, 66 (39%) were aged ≥ 60 years. The proportion of patients with MUCH (27.4% for all patients) was significantly higher (p = 0.002) among elderly patients than among younger patients (45.5% vs. 15.7%). Diabetes mellitus (adjusted odds ratio [aOR], 2.44; 95% confidence interval [CI], 1.27–4.46; p = 0.043), anemia (aOR, 3.18; 95% CI, 1.07–5.81; p = 0.043), hypertensive retinopathy (aOR, 4.50; 95% CI, 1.57–5.4; p = 0.043), and left ventricular hypertrophy (aOR, 4.48; 95% CI, 2.26–8.35; p = 0.043) were independently associated with MUCH in the elderly. In younger individuals, male gender (aOR, 2.16; 95% CI, (1.33–4.80); p = 0.029), obesity (aOR, 3.02; 95% CI, (1.26–5.32); p = 0.001), and left ventricular hypertrophy (LVH) (aOR, 3.08; 95% CI, (2.14–6.24); p = 0.019) were independently associated with MUCH were independently associated with MUCH.

Conclusion

MUCH is more prevalent among elderly than among younger BSSA individuals. Determinants of MUCH vary by age. MUCH prevention and management strategies should be age-specific.

Keywords

Masked uncontrolled hypertension
Prevalence
Risk factors
Elderly blacks
Sub-saharan africans
issue-copyright-statement© BioMed Central Ltd., part of Springer Nature 2024
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pmcIntroduction

Hypertension is the main driver of cardiovascular disease (CVD), stroke, chronic kidney disease, and dementia [1, 2], affecting more than half of the elderly population. Furthermore, it is the leading preventable risk factor for premature death and disability worldwide [2, 3].

Sub-Saharan Africa (SSA) is one of the regions of the world where average levels of systolic and diastolic blood pressure among the population, as well as the prevalence of hypertension, have increased. In contrast, these parameters have declined substantially in high-income regions since at least the 1970s [1, 4]. In 2015, an estimated 8.5 million deaths were attributable to hypertension, 88% of which occurred in low- and middle-income countries [1], where the proportions of hypertension awareness, treatment, and BP control are the lowest [1].

In the Democratic Republic of the Congo (DRC), the prevalence of hypertension is estimated to be between 30% and 40% [5, 6] and is associated with a low BP control rate and elevated subsequent cardiovascular morbidity and mortality [7]. Three population-based studies conducted in Kinshasa [8] and eastern DRC [9, 10] have shown a trend toward an increase in the prevalence of hypertension between 1993 and 2007 [8], between 2012 and 2016 [9], and between 2012 and 2019 [10].

Treatment of hypertension is critically important and can effectively reduce BP and the risk of associated morbidity and mortality [11–13].

In a recent large study, office BP (OBP) misclassified hypertension status in > 40% of patients [14]. Thus, a patient with treated hypertension can be classified as being uncontrolled when considering OBP but may be controlled in ambulatory BP monitoring (ABPM), a false uncontrolled hypertension, a fact termed white-coat uncontrolled hypertension (WUCH). In contrast, patients with treated hypertension classified as being controlled when considering OBP can be found to be uncontrolled when resorting to out-of-office BP as assessed by either 24-h ABPM or home BP monitoring, a false controlled hypertension, a fact termed masked uncontrolled hypertension (MUCH), which has been shown to be associated with an increased risk of cardiovascular events and all-cause mortality [15–17].

In studies conducted elsewhere, MUCH was associated with smoking, diabetes mellitus, positive family history of diabetes mellitus, older age, male sex, obesity, higher office systolic BP [18–20], and longer duration of hypertension [20].

MUCH is frequently observed among elderly patients with treated hypertension, the proportion of which is expected to substantially increase in SSA in the future [21, 22]. Furthermore, according to Piedermino’s meta-analysis, the increased risk of MUCH is greater in blacks than in other ethnic groups [17]. Despite all these worrying facts, data on the prevalence and factors associated with MUCH in elderly black SSA (BSSA) individuals are almost nonexistent. Furthermore, it is unclear whether the determinants of MUCH in younger individuals differ from those in the elderly.

Therefore, we evaluated the prevalence and risk factors associated with MUCH in both elderly and younger BSSA individuals.

Materials and methods

Study design and patients

In this hospital-based cross-sectional study, 168 black outpatients with treated hypertension were referred for 24-h ABPM at Monkole Hospital as part of the present study.

Sample size calculation

A sample size of 261 was determined using an estimated prevalence of 13% [23], a 95% confidence level with a standard value of 1.96, a 5% margin of error, and a design effect of 1.5.

Patient selection

From July to December 2022, doctors from primary and secondary level hospitals in the commune of Mont-Ngafula, one of the largest communes in Kinshasa (with an area of 358.92 km2 and a population density of 727 inhabitants per km2), were asked to refer their hypertensive patients who met the inclusion criteria of the present study to Monkole Hospital for ambulatory blood pressure monitoring. Monkole Hospital is the main secondary level hospital in the commune of Mont-Ngafula.

Inclusion and exclusion criteria

Participant selection

All patients referred for 24-h ABPM in the aforementioned hospital throughout the predetermined study period were approached. The inclusion criteria were as follows: hypertensive men and women aged 18 years and over who have been on antihypertensive treatment for at least 2 months. The exclusion criteria were as follows: poor adherence and inadequate ABMP.

Independent variables

The independent variables included demographic information (sex), detailed clinical history, anthropometric parameters (i.e., weight, height, and body mass index [BMI]), OBP parameters (i.e., systolic BP [SBP], diastolic BP [DBP], and pulsed BP [PBP]), biochemistry (e.g., renal function tests, fasting blood glucose [FBG], glycated hemoglobin [HbA1C], and fasting lipid profile [high-density lipoprotein (HDL-C), low-density lipoprotein (LDL-C), total cholesterol (TC), and triglycerides (TG)], and hypertension-mediated organ damage (HMOD) (i.e., hypertensive retinopathy, semiquantitative proteinuria, and left ventricular hypertrophy [LVH]).

Dependent variables

The MUCH pattern was the dependent variable.

Study procedures

Anamnestic data

A standard questionnaire was used to collect anamnestic information focused on self-reported age and sex, excessive alcohol consumption, cigarette smoking habits, family history of diabetes mellitus, duration of hypertension, current hypertensive medications (classes of BP medications), and adherence to antihypertensive treatment evaluated using Girerd’s questionnaire [24].

Anthropometric data

A final-year medical student who had been trained for this task measured the anthropometric parameters according to standard protocols.

BP measurement

A trained nurse performed OBP measurement on the patient’s nondominant arm after 5 min of rest using an automated electronic sphygmomanometer (OMRON M3 HEM-7200-E Omron Matsusaka Co. Ltd., Kyoto, Japan). An appropriate cuff size was used with the cuff bladder encircling at least 80% of the patient’s arm. Three consecutive OBP measurements were taken at 1-min intervals. The average of the last two measurements was recorded for analysis.

A 24-h ABPM was performed using an automated, noninvasive, oscillometric device (Space Labs 90207 system, 35301 SE Center St., Snoqualmie, WA 98065, UNITED STATES). A typical weekday was chosen for different patients, and normal daily activities were allowed; however, patients were instructed to remain still during the measurements. BP was recorded every 15 min during the day (from 07:00 to 21:00) and every 30 min during the night (from 21:00 to 07:00). The mean SBP and DBP were calculated for daytime, night time, and 24 h of recording. Patients were counseled to take all antihypertensive medications during the ABPM period. Adequate ABPM recordings should fulfill many prespecified criteria, including successful recording of ≥ 70% SBP and DBP during both daytime and nocturnal periods, and at least 7 valid readings while asleep (with at least 1 valid reading per hour). Failing to fulfill these conditions, the patients underwent a second recording.

Laboratory measurements

Blood samples obtained in the morning between 8:00 AM and 10:00 AM after a 10–12-h overnight fast were used for all analyses performed in the same laboratory using standard methods detailed elsewhere [25].

Semiquantitative proteinuria was assessed using a urine dipstick (Multistix 8 SG®, Siemens Healthcare Diagnostics, France).

Echocardiographic data

Two certified cardiac sonographers performed thorough two-dimensional transthoracic echocardiography for each patient using commercial 3. 5-MHz equipment (Vivid T8, GE Health Care, Freiburg, Germany). Left ventricle dimensions (i.e., diastolic interventricular septum thickness [IVSd], diastolic left ventricular posterior wall thickness [PWTd], and left ventricular end-diastolic diameter [LVEDd]) were measured according to the 2016 updated guidelines from the American Society of Echocardiography and the European Association of Cardiovascular Imaging global guidelines [26]. Left ventricular mass (LVM) was calculated based on the American Society of Echocardiography simplified cubed equation linear method: LVM (g) = 0.8 × 1.04 × [(LVEDd + IVSd + PWTd)3 − (LVEDd)3] + 0.6 g. LVM was indexed to body surface area (BSA) and height as mass/BSA and mass/height.2.7.

Fundoscopy

Direct bilateral ophthalmoscopic fundus evaluation after pupil dilation with 1% tropicamide and 10% phenylephrine was performed using slit-lamp indirect ophthalmoscopy with noncontact slit-lamp lenses (90D double aspheric Volk lens; Shanghai, China). During fundus examination, retinal abnormalities consistent with hypertensive retinopathy were specifically examined.

Operational definitions

MUCH was defined as elevated 24-h mean BP ≥ 130/80 mmHg, and/or daytime mean BP ≥ 135/85 mmHg, and/or nighttime mean BP ≥ 120/70 mmHg, despite controlled OBP (< 140/90 mmHg) [27, 28]; patients with MUCH were trichotomized into daytime MUCH (when only daytime BP was elevated (≥ 135/85 mmHg), nighttime MUCH (when only nocturnal BP was elevated (≥ 120/70 mmHg), or 24-h MUCH (when both daytime and nighttime BP values were elevated [28].

Controlled hypertension is defined as a 24-hour ABPM of ≤ 130/80 mmHg [27].

Poor adherence was defined as a total score ≥ 3 on Girerd’s questionnaire [24].

Inadequate ABPM recording was defined as not meeting one or more of the aforementioned prespecified criteria established by the ACC/AHA Hypertension Guidelines [29].

An abnormal dipper pattern (non-dipper) was diagnosed when the night average SBP reduction was < 10% with respect to day values; riser or reverse dipper was diagnosed when the mean night SBP was higher than the day one [27]. The reverse dipper was considered “non-dipping pattern” for analysis.

Smoking was defined as cigarette use in the year before this study [30], and excessive alcohol consumption was defined as the average consumption of more than 7 drinks per week for women and more than 14 drinks per week for men in the past year [31].

Dyslipidemia was defined by the presence of at least one of the following parameters: total cholesterol level > 200 mg/dL, LDL cholesterol > 130 mg/dL, HDL cholesterol < 40 mg/dL in men and < 50 mg mg/dL in women, triglycerides > 150 mg/dL [32], and obesity (BMI ≥ 30 kg/m2) [33]. Diabetes mellitus was defined by a history of diabetes mellitus, at least two fasting blood glucose > 126 mg/dL, a glycated hemoglobin level > 6.5%, and/or current use of antidiabetic drugs [34].

As per the recommendations on the use of echocardiography in adult hypertension from the European Association of Cardiovascular Imaging (EACVI) and the American Society of Echocardiography (ASE) [35] LVH was defined based on LVM indexed to height exponent 2.7 for obese individuals and indexed to body surface area (BSA) for non-obese individuals. In obese individuals, LVH was defined as LVM > 48 g/m2.7for males or > 44 g/m2.7for females. In non-obese individuals, it was defined as LVM > 115 g/m2for males and > 95 g/m2for females.

Obesity was defined as a BMI equal to or greater than 30 kg/m2of BSA [33].

Hypertensive retinopathy was defined by the presence of one or more of the following: arteriolar constriction, flame-shaped hemorrhages, cotton wool patches, star-figure edema at the macula, and papilla edema [36].

Albuminuria was defined as proteinuria ≥ “trace” using a dipstick [37]. Impaired kidney function was defined as an estimated glomerular filtration rate < 60 mL/min/1.73 m2 of body surface calculated using the Modification of Diet in Renal Disease formula [38].

Statistical analyses

Statistical analyses were performed using Statistical Package for the Social Sciences (version 17.0; SPSS Inc., Chicago, Illinois, USA). Patients were categorized into two subgroups according to age: age < 60 years versus ≥ 60 years. Continuous and categorical variables are expressed as means ± standard deviations and relative frequency in percent, respectively. Comparisons of means and proportions were performed using Student’s t-test and the chi-square test, respectively. Logistic regression analysis was performed to assess independent factors associated with MUCH, including elderly and younger adults separately. P-values ˂ 0.05 were used to denote statistical significance.

Results

Initially, 223 patients were approached for the study, of whom 55 were excluded for the following reasons: irregular antihypertensive treatment (n = 52), inadequate ABPM [2], and refusal to provide consent to participate in the study [1]. Figure 1 summarizes the patient selection procedure.

Fig. 1 Study flow chart

General characteristics of the study population

The study population comprised 168 patients, with a mean age of 53.6 ± 11.6 years; of the 168 patients, 92 (54.8%) were men and 76 (45.2%) were women, with a sex ratio of 1.2 (in favor of men). Sixty-six (39.3%) patients were aged ≥ 60 years.

Sociodemographic, cardiovascular risk factors, and biological characteristics of the participants according to age

Table 1 summarizes the sociodemographic and biological characteristics and cardiovascular risk factors of the participants according to age categories. The average age, duration of hypertension, and BMI values were 53.6 ± 11.6 years,9 years (range, 6–15 years), and 28.9 ± 4.6 kg/m2, respectively. The cardiovascular risk factor profiles of the patients were characterized by dyslipidemia (48.8%), obesity (38.1%), alcohol consumption (34.5%), smoking (13.1%), and diabetes mellitus (11.3%). Target organ damage included hypertensive retinopathy (61.9%), LVH (43%), semiquantitative proteinuria (35.6%), and impaired kidney function (18.9%). Compared with patients aged < 60 years, those aged ≥ 60 years had longer duration of hypertension (14 [range, 9–18] vs. 5 years [range, 6–15 years], p = 0.003), higher prevalence of LVH (58.5% vs. 33%; p = 0.001), more likely to have impaired kidney function (27.7% vs. 13.1%; p = 0.017), and lesser propensity to alcohol intake (25.8% vs. 40.2%; p = 0.039), obesity (28.8% vs. 44.1%; p = 0.032), and hypertensive retinopathy (45.2% vs. 72.4%; p = 0.001).

Table 1 General characteristics of black patients with treated hypertension as a whole and according to age categories

Variable	N	All
(n = 168)	˂60 years
(n = 102)	≥ 60 years
(n = 66)	P	
Age, years	168	53.6 ± 11.6	46.5 ± 6.9	66.6 ± 5.4	< 0.001	
Sex, n (%)	168				0.037	
M		92 (54.8)	62 (60.8)	30 (45.5)		
F		76 (45.2)	40 (39.2)	36 (54.5)		
Alcohol, n (%)	168	58 (34.5)	41 (40.2)	17 (25.8)	0.039	
Smoking, n (%)	168	22 (13.1)	12 (11.8)	10 (15.2)	0.341	
Diabetes mellitus, n (%)	168	19 (11.3)	9 (8.8)	10 (15.2)	0.155	
DHT, years	168	9 (6–15)	5 (2.3–10)	14 (9–18)	0.003	
BMI, kg/m²	168	28.9 ± 4.6	29.1 ± 4.8	28.3 ± 4.2	0.206	
Obesity, n (%)	168	64 (38.1)	45 (44.1)	19 (28.8)	0.032	
Dyslipidemia, n (%)	168	82 (48.8)	54 (52.9)	28 (42.4)	0.120	
LVH, n (%)	165	71 (43.0)	33 (33.0)	38 (58.5)	0.001	
Hypertensive retinopathy, n (%)	160	99 (61.9)	71 (72.4)	28 (45.2)	0.001	
Hb, g/Dl	121	12.5 ± 1.6	12.7 ± 1.7	12.2 ± 1.4	0.054	
Anemia, n (%)	121	20 (16.5)	13 (18.8)	7 (13.5)	0.297	
HbA1c, %	34	7.1 ± 1.8	7.0 ± 1.6	7.3 ± 2.2	0.558	
TC, mg/dL	158	203.5 ± 41.9	201.6 ± 38.6	207.2 ± 47.7	0.365	
HDL-c, mg/dL	158	50.3 ± 14.7	50.1 ± 14.4	50.7 ± 15.3	0.794	
LDL-c, mg/dL	158	130.7 ± 38.8	128.4 ± 34.9	134.8 ± 45.2	0.261	
TG, mg/dL	158	112.6 ± 37.5	115.5 ± 40.7	107.3 ± 29.9	0.131	
FPG, mg/dL	163	99.4 ± 31.2	97.4 ± 28.8	103.4 ± 35.5	0.245	
Creatinine, mg/dL	164	1.1 ± 0.8	1.1 ± 0.9	1.2 ± 0.5	0.847	
eGFR, ml/min/1.73 m2	164	95.3 ± 36.8	102.1 ± 38.9	83.3 ± 29.4	< 0.001	
eGFR˂60 ml/min/1.73 m2	164	31 (18.9)	13 (13.1)	18 (27.7)	0.017	
Proteinuria, n(%)	163	58 (35.6)	31 (31.6)	27 (41.5)	0.130	
M, male; F, female; DHT, duration of hypertension; BMI, body mass index; LVH, left ventricular hypertrophy; Hb, hemoglobin; HbA1c, glycated hemoglobin; TC, total cholesterol; LDL-c, low-density lipoprotein cholesterol; HDL-c, high-density lipoprotein cholesterol; TG, triglycerides; FPG, fasting plasma glucose; eGFR, estimated glomerular filtration rate

Mean BP and BP patterns in the participants as a whole and according to age categories

The mean OBP and 24-h ABP values of the participants as a whole and according to age categories are shown in Table 2. In the entire study group, the mean office SBP and DBP, 24-h ABPM SBP and DBP, daytime SBP and DBP, and nighttime SBP and DBP were 144 ± 20.4 and 88.8 ± 13.0 mmHg, 133.0 ± 12.9 and 86.8 ± 10.3 mmHg, 134.4 ± 12.4 and 88.7 ± 10.2 mmHg, and 127.8 ± 16.5 and 79.1 ± 11.7 mmHg, respectively. Compared with patients aged ˂60 years, those aged ≥ 60 years had on average significantly lower 24-h DBP (82.9 ± 8.8 vs. 88.9 ± 10.5 mmHg; p < 0.001), daytime SBP (132.1 ± 12.7 vs. 135.7 ± 12.1 mmHg; p = 0.039), DBP (84.4 ± 9.5 vs. 91.0 ± 9.8 mmHg; p < 0.001), and nighttime DBP (76.8 ± 9.6 vs. 80.4 ± 12.6 mmHg; p = 0.029).

Table 2 also shows the BP patterns using OBP and 24-h ABPM and indicates that the proportion of patients with MUCH (27.4% for all patients) was significantly higher (p = 0.002) among elderly patients than among younger patients (45.5% vs. 15.7%). Among patients aged ≥ 60 years, the 24-h (76.6%) and nighttime (16.7%) MUCH subtypes were the most prominently observed forms; the difference in the proportion of patients with the nighttime MUCH subtype between elderly and younger patients was statistically significant (16.7% vs. 6.2%; p = 0.002).

Table 2 Mean office BP and 24-h ambulatory BP and BP patterns in black patients with treated hypertension as a whole and according to age categories

Variable	N	All
n = 168	˂60 years
(n = 102)	≥ 60 years
(n = 66)	P	
Office BP						
SBP, mmHg	168	144.0 ± 20.4	144.4 ± 21.3	143.4 ± 18.7	0.735	
DBP, mmHg	168	88.8 ± 13.0	89.0 ± 13.2	88.6 ± 12.8	0.828	
24 H ABPM						
SBP, mmHg	168	133.0 ± 12.9	134.2 ± 12.8	130.9 ± 12.9	0.069	
DBP, mmHg	168	86.8 ± 10.3	88.9 ± 10.5	82.9 ± 8.8	< 0.001	
Daytime ABPM						
SBP, mmHg	168	134.4 ± 12.4	135.7 ± 12.1	132.1 ± 12.7	0.039	
DBP, mmHg	168	88.7 ± 10.2	91.0 ± 9.8	84.4 ± 9.5	< 0.001	
Nighttime ABPM	168					
SBP, mmHg	168	127.8 ± 16.5	128.4 ± 16.7	126.7 ± 16.1	0.462	
DBP, mmHg	168	79.1 ± 11.7	80.4 ± 12.6	76.8 ± 9.6	0.029	
BP patterns						
Controlled HT, n (%)	168	43 (25.6)	31 (30.4)	12 (18.2)	0.030	
WUCH, n (%)	168	38 (22.6)	29 (28.4)	9 (13.6)	0.019	
MUCH, n (%)	168	46 (27.4)	16 (15.7)	30 (45.5)	0.002	
24-h MUCH, n(%)	46	38 (82.6)	15 (93.8)	23 (76.6)		
Nighttime MUCH, n(%)	46	6 (13.0)	1 (6.2)	5 (16.7)		
Daytime MUCH, n(%)	46	2 (4.3)	0 (0.0)	2 (6.7)		
SUCH, n(%)	168	104 (61.9)	59 (57.8)	45 (68.2)	0.018	
Non-dipping, n(%)	168	107 (63.7)	63 (61.8)	44 (66.7)	0.316	
BP, blood pressure; SBP, systolic blood pressure; DBP, diastolic blood pressure; ABPM, ambulatory blood pressure monitoring; HT, hypertension; WUCH, white-coat uncontrolled hypertension; MUCH, masked uncontrolled hypertension; SUCH, sustained uncontrolled hypertension

Factors associated with MUCH in univariate and multivariate logistic regression analyses

Table 3 shows the clinical factors associated with MUCH in the treated elderly patients using logistic regression analysis. In the univariate analysis, diabetes mellitus, obesity, anemia, hypertensive retinopathy, and LVH were the main clinical factors correlated with MUCH. In the multivariate analysis, the association persisted for diabetes mellitus (adjust odds ratio [aOR], 2.44; 95% confidence interval [CI], 1.27–4.46; p = 0.043), anemia (aOR, 3.18; 95% CI, 1.07–5.81; p = 0.043), hypertensive retinopathy (aOR, 4.50; 95% CI, 1.57–5.4; p = 0.043), and LVH (aOR, 4.48; 95% CI, 2.26–8.35; p = 0.043).

Table 3 Factors associated with MUCH in univariate and multivariate logistic regression analyses among the elderly participants

	Univariate analysis	Multivariate analysis	
Variables	P	OR (95% CI)	P	aOR (95% CI)	
Diabetes mellitus					
No		1		1	
Yes	0.046	2.81 (1.32–6.28)	0.043	2.44 (1.27–4.46)	
Obesity					
No		1		1	
Yes	0.045	1.64 (1.27–3.94)	0.275	1.52 (0.37–1.81)	
Anemia					
No		1		1	
Yes	0.036	4.71(1.18–5.95)	0.014	3.18 (1.07–5.81)	
Hypertensive retinopathy					
No		1		1	
Yes	0.025	2.11(1.59–7.54)	0.016	4.51(1.57–5,84)	
LVH					
No		1		1	
Yes	0.008	3.61(1.27–4.46)	0.005	4.48 (2.26–8.35)	
aOR, adjusted odds ratio; CI, confidence interval; LVH, left ventricular hypertrophy; 95% CI, 95% confidence interval

Table 4 shows the clinical factors associated with MUCH in the treated younger patients using logistic regression analysis. In the univariate analysis, male gender, obesity, alcohol intake, cigarette smoking, hypertensive retinopathy, and LVH were the main clinical factors associated with MUCH. In the multivariate analysis, the association persisted for male gender (aOR, 2.16; 95% CI, (1.33–4.80); p = 0.029), obesity (aOR, 3.02; 95% CI, (1.26–5.32); p = 0.001), and LVH (aOR, 3.08; 95% CI, (2.14–6.24); p = 0.019).

Table 4 Factors associated with MUCH in univariate and multivariate logistic regression analyses among younger participants

	Univariate analysis	Multivariate analysis	
Variables	P	OR (95% CI)	P	aOR (95% CI)	
Male gender					
No		1		1	
Yes	0.008	2.01 (1.26–4.36)	0.029	2.16 (1.33–4.80)	
Obesity					
No		1		1	
Yes	0.012	3.51 (2.21–5.84)	0.001	3.02 (1.26–5.32)	
Alcohol intake					
No		1		1	
Yes	0.022	2.08 (1.62–6.01)	0.074	2.11 (1.91–6.72)	
Cigarette smoking					
No		1		1	
Yes	0.019	5.03 (2.26–7.15)	0.102	3.22 (2.01–6.90)	
Hypertensive retinopathy					
No		1		1	
Yes	0.015	2.05(1.36–6.70)	0.086	2.59(1.24–5.22)	
LVH					
No		1		1	
Yes	0.014	2.03 (1.19–5.32)	0.019	3.08 (2.14–6.24)	
aOR, adjusted odds ratio; CI, confidence interval; LVH, left ventricular hypertrophy; 95% CI, 95% confidence interval

Discussion

This study aimed to determine the prevalence and risk factors associated with MUCH in both elderly and younger BSSA individuals.

Several studies have evaluated the prevalence and risk factors associated with masked hypertension. Studies on uncontrolled hypertension are also numerous, both globally and even in Africa. Studies on MUCH are rarer globally and nonexistent in SSA. Furthermore, there are no studies on whether the determinants of MUCH differ between younger individuals and the elderly. The term “MUCH” refers to hypertension treated with non-elevated OBP but elevated BP in ABPM, whereas “masked hypertension” has been used to describe untreated hypertension [39, 40]. Note that many authors have used the term “uncontrolled hypertension” to refer interchangeably to both treated and untreated hypertension. However, a European Society of Hypertension position paper [39] suggested that “masked hypertension“ and “MUCH“ should be separately defined entities.

To the best of our knowledge, this is the first SSA study to address the prevalence and risk factors associated with MUCH. Most notably, this study is the very first study to determine the prevalence and risk factors associated with MUCH in the elderly, as compared to younger individuals.

The pioneering nature of our study and the new insights it provides into MUCH within SSA represent a significant contribution to the field. This research offers a foundation for future studies and potential clinical applications, despite limitations related to its small sample size that could impact the generalizability of the results and the robustness of the observed associations.

The main findings of the study are as follows: First, the proportion of patients with MUCH (27.4% for all patients) was significantly higher (p = 0.002) among elderly patients than among younger patients (45.5% vs. 15.7%). Second, the nighttime MUCH subtype was more frequently encountered in the elderly patients than in the younger patients. Third, predictors of MUCH differ by age: diabetes mellitus, anemia, hypertensive retinopathy, and LVH were the main independent factors associated with MUCH in elderly patients, while in the younger individuals, male gender, obesity, and LVH were independently associated with MUCH.

In this analysis, nearly half of the elderly patients with treated hypertension had a significantly higher frequency of MUCH than patients below 60 years of age. Depending on the definition of MUCH and on the characteristics and types of populations across studies, the prevalence of MUCH varies from 31.1% as found in a Spanish study [28] to 48% as found in a Swedish study [41]. The prevalence found in this study falls within this range but is one of the highest ever reported.

Indeed, this study used the mean 24-h, daytime, and nighttime ABPM to define MUCH, in contrast to other studies where MUCH was defined based solely on the mean daytime ABPM compared with OBP [28, 42]. This might at least partly explain the increased prevalence we observed. In this regard, the prevalence of MUCH has been reported to be higher when nighttime BP is included in the definition than when it is defined by daytime [43].

Furthermore, 24-h and nighttime MUCH were the subtypes most frequently encountered in this study, which agrees with the findings of other studies [43–46]. Nighttime hypertension has been reported to increase the risk of nephropathy [47] and overall cardiovascular events and total mortality [48, 49].

The independent factors associated with MUCH in the elderly were diabetes mellitus, hypertensive retinopathy, LVH, and anemia. This agrees with the findings of previous studies that reported MUCH to be associated with a greater prevalence and severity of metabolic risk factors [49–51], particularly diabetes mellitus [18–20], hypertensive retinopathy [52], LVH [53–55], and anemia [56–58].

The association between these various factors and MUCH is challenging to explain, as the mechanisms supporting the phenomenon are not well understood. The study by Siddiqui et al. [59] provides insight into a possible explanation. This study found a higher out-of-clinic secretion of aldosterone and an increased prevalence of hyperaldosteronism in patients with MUCH compared with those with true controlled hypertension. These findings suggest that patients with MUCH likely have higher out-of-clinic sympathetic nervous system activity, leading to increased out-of-clinic aldosterone secretion mediated by renin. This may play a role in the development of MUCH and contribute to their higher out-of-clinic blood pressure. The reasons for the higher out-of-clinic secretion of aldosterone compared to that in the clinic are unclear. It is reasonable to assume that sympathetic activation may be the pathological link between MUCH and the various determinants found in the present study. Indeed, previous studies have shown higher sympathetic hyperactivity in both diabetes mellitus [60], hypertensive retinopathy [61], left ventricular hypertrophy [62], and anemia [63].

In nighttime MUCH, this association could be explained by poor sleep quality. Indeed, diabetes mellitus exerts a direct negative effect on patients’ sleep quality because of nocturia, diabetic neuropathy, and neuropathy pain [64]. Furthermore, diabetes mellitus has been associated with obstructive sleep apnea [64, 65], which, according to Cuspidi meta-analyses, results in a significantly increased risk of non-dipping [66]. A significant correlation was observed between iron deficiency anemia and sleep disorders [67–69].

LVH has also been found to be independently associated with MUCH in younger participants, while diabetes mellitus, hypertensive retinopathy, and anemia were not. In this group of participants, male gender and obesity were also factors independently associated with MUCH. This association between male gender and obesity with MUCH was also found by Andalib et al. [18]. This suggests that OBP measurement may overestimate the effect of antihypertensive treatment in young male and obese patients.

Despite the well-known negative prognostic value of nighttime MUCH, its therapeutic approach remains uncertain. Indeed, studies have shown that routine use of ≥ 1 prescribed BP-lowering medications at bedtime improves ABPM control and markedly decreases the occurrence of major CVD events [50, 70]. However, a larger recent prospective study, one of the largest cardiovascular studies ever conducted, showed that taking an antihypertensive drug in the morning or evening has no benefit because heart attack, stroke, and vascular death occurred to a similar degree, regardless of the time of administration [71]. Youssef et al. found that taking an extra antihypertensive pill at night did not decrease the nighttime or average 24-h BP in patients with hypertension with controlled OBP [72].

Thus, the management of MUCH, regardless of the pattern (daytime MUCH or nighttime MUCH), remains challenging. This is mostly because this issue has not been specifically examined. Indeed, unlike patients with WCE who were included in all hypertension trials, all major clinical trials in hypertension have used OBP to assess eligibility and monitor treatment effects. In treat-to-target studies, OBP has been used to guide therapy in the standard and intensive treatment groups. Furthermore, patients with MUCH were excluded from hypertension trials and would not have had their antihypertensive medications intensified during the maintenance or treat-to-target phase of these trials. Pierdomenico’s meta-analysis [17] included only observational studies and was therefore unable to address whether treatment modifies the MUCH phenotype or reduces the risk of adverse outcomes in patients with MUCH. Studies are required to determine whether the rigorous management of factors found in this study is effective in treating MUCH and preventing related poor outcomes.

Study strengths and limitations

The strength of this study lies in its originality because it is, to the best of our knowledge, the first in sub-Saharan Africa to to determine the frequency and factors associated with MUCH in older adults, as compared to younger individuals.

This study has some limitations that must be underscored. First, the cross-sectional design precludes the establishment of any temporal relationship between the variables of interest. Second, the small sample size did not confer much power to statistical tests to identify potential associations between the variables of interest and preclude, in addition to the hospital-based characteristics of the study, the generalization of the findings to all elderly BSSA patients with hypertension. Multicenter population-based studies are required. Furthermore, these findings must be confirmed in other geographic regions across SSA. Moreover, larger sample sizes are needed to validate these findings and to explore the underlying mechanisms in greater depth.

Conclusion

MUCH is more prevalent among elderly than among younger BSSA hypertensive individuals. Determinants of MUCH vary by age. MUCH prevention and management strategies should be age-specific. Population-based, larger, and prospective studies are required to better illuminate the remaining gray areas regarding etiopathogenesis and the best therapeutic approach for treating MUCH and reducing its associated risk.

Acknowledgements

The authors gratefully thank Dr. Alphonse Mosolo, Dr. Wilfrid Mbombo, all medical Staff of Monkole Hospital/Kinshasa, Dr. Roger Kongo, Dr. Jean Takombe, all medical Staff of Ngaliema Clinc/Kinshasa, Dr. Albert Mvunzi Nlopo from the University of Kinshasa School of Medicine, Dr. Pierre Akilimali from Kinshasa Public Health School, and Mr. Yvon Cizubu from Denk-Pharma/Kinshasa for their support. Finally, we express our gratitude to all patients who provided their consent to the research team to conduct the study.

Author contributions

Design and concept of the study: TMS, BKP, FLB, and JRMK. Acquisition of data: TMS, YSM, YLN, CI, DKK, NOO, and RKM. Manuscript draft: TMS, YSM, and BKP. Analysis and interpretation of data: ANN, TMS, YSM, and BKP. Final manuscript revision and approval: TMS, YSM, YLN, FLB, JRMR, IC, KVE, KKD, OON, KMR, TMO, and MKJR.

Funding

Not applicable.

Data availability

Because the consent given by study participants did not include data sharing with third parties, anonymized data can be made available to investigators for analysis on reasonable request to the corresponding author.

Declarations

Ethics approval and consent to participate

This study was reviewed and approved by the Congolese National Health Ethics Committee (No. 219/CNES/BN/PMMF/220), and all included patients provided written informed consent. The rules of confidentiality and ethics were respected according to the 1964 Declaration of Helsinki.

Consent to publish

Not applicable.

Competing interests

The authors declare no competing interests.

Generative AI and AI-assisted technologies in the writing process

We certify that no artificial intelligence / large language model were used at any stage of this research manuscript writing.

Abbreviations

ABPM Ambulatory blood pressure monitoring

ACC American College of Cardiology

AHA American Heart Association

aOR Adjusted odds ratio

BMI Body mass index

BP Blood pressure

BSA Body surface area

BSSA Black sub-Saharan Africans

CI Confidence interval

CVD Cardiovascular disease

DBP Diastolic blood pressure

DHT Duration of hypertension

DRC Democratic Republic of the Congo

eGFR Estimated glomerular filtration rate

FBG Fasting blood glucose

Hb Hemoglobin

HbA1C Glycated hemoglobin

HDL-C High-density lipoprotein cholesterol

HMOD Hypertension-mediated organ damage

HT Hypertension

IVSd Diastolic interventricular septum thickness

LDL-C Low-density lipoprotein

LVEDd Left ventricular end-diastolic diameter

LVM Left ventricular mass

LVH Left ventricular hypertrophy

MUCH Masked uncontrolled hypertension

OBP Office blood pressure

OR Odds ratio

PBP Pulsed blood pressure

PWTd Diastolic left ventricular posterior wall thickness

SBP Systolic blood pressure

SPSS Statistical Package for the Social Sciences

SSA Sub-Saharan Africa

SUCH Sustained uncontrolled hypertension

TC Total cholesterol

TG Triglycerides

WCE White coat effect

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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