Skip to main content
NCBI home page
PLOS Global Public Health logoLink to PLOS Global Public Health
. 2023 Dec 5;3(12):e0001931. doi: 10.1371/journal.pgph.0001931

Regional prevalence of hypertension among people diagnosed with diabetes in Africa, a systematic review and meta-analysis

Thomas Hinneh 1,*, Samuel Akyirem 2, Irene Fosuhemaa Bossman 3, Victor Lambongang 4, Patriot Ofori-Aning 5, Oluwabunmi Ogungbe 1,6, Yvonne Commodore Mensah 1,6
Editor: Leonor Guariguata7
PMCID: PMC10697518  PMID: 38051707

Abstract

Hypertension and diabetes comorbidity can increase healthcare expenditure and the risk of coronary heart disease. We conducted a systematic review and meta-analysis to estimate the prevalence of hypertension among people with diabetes in African countries. We searched EMBASE, PubMed and HINARI databases from inception to March 2023. Cross-sectional studies reporting the prevalence of hypertension among people with diabetes and published in English in Africa were eligible for inclusion. The cross-sectional study design component of the mixed method appraisal tool was used to assess the quality of the included studies. We quantified the overall and regional prevalence of hypertension among people with diabetes using random-effects meta-analysis. We assessed heterogeneity and publication bias using I2 statistics and funnel plots. Out of 3815 articles retrieved from the various databases, 41 met the inclusion criteria with sample sizes ranging from 80 to 116726. The mean age was 58 years (± 11) and 56% were women. The pooled prevalence of hypertension in people diagnosed with diabetes was 58.1% [95% CI: 52.0% - 63.2%]. By region, Central Africa had the highest hypertension prevalence; 77.6% [95% CI: 53.0% - 91.4%], Southern Africa 69.1% [95% CI: 59.8% - 77.1%;], North Africa 63.4% [95% CI: 37.1% - 69.1%;], West Africa 51.5% [95% CI: 41.8% - 61.1%] and East Africa 53.0% [95% CI: 45.8% - 59.1%]. Increasing age, being overweight/obese, being employed, longer duration of diabetes, urban residence, and male sex were reported to be associated with a higher likelihood of developing hypertension. The high prevalence of hypertension among people with diabetes in Africa highlights the critical need for an integrated differentiated service delivery to improve and strengthen primary care and prevent cardiovascular disease. Findings from this meta-analysis may inform the delivery of interventions to prevent premature cardiovascular disease deaths among persons in the region.

Introduction

Hypertension is the most common leading cause of cardiovascular diseases (CVDs), and a major cause of morbidity and mortality globally [1]. The prevalence of hypertension has risen substantially to over one billion since 1990, according to the Lancet NCD Risk Factor Collaboration Study (NCD-RisC) [1]. During the same period (1990–2017), the global burden of diabetes also increased from 211.2 million to 476 million [2]. Nearly two-thirds of hypertension and diabetes cases occur in low- and middle-income countries (LMICs), where health systems are already burdened with infectious diseases [3]. Even though the Lancet NCD-RisC study reported a decline in the burden of hypertension in high-income countries, LMICs continue to experience an upsurge in rates of hypertension [2–4].

Diabetes and hypertension have a higher likelihood of co-occurring due to the commonalities of risk factors including low physical activity, unhealthy dietary patterns, and obesity [1].

Hypertension and diabetes are linked pathophysiologically. Diabetes can cause microvascular changes including the stiffening of small blood vessels (a condition known as arteriosclerosis). Arteriosclerosis can also elevate peripheral vascular resistance and can significantly increase the risk of developing hypertension [5]. Apart from neuropathic, nephropathic disorders and CVDs, hypertension is the most common comorbid condition and the leading cause of death among people with diabetes [6]. Although the prevalence of hypertension is well studied in sub-Saharan Africa, there is limited research on the prevalence of hypertension among this population who experience a greater burden of hypertension-associated mortality [1].

Comorbid hypertension worsens blood pressure control and quality of life of patients living with diabetes [7–9], increases healthcare costs and complicates healthcare needs. Given the increase in healthcare needs of the diabetes population as a result of the comorbidity, such patients are less likely to receive appropriate care until the occurrence of complications [10]. These negative outcomes of hypertension and diabetes comorbidity underscore the need for an equal prioritization of clinical and community-based interventions for hypertension and diabetes. Moreover, a knowledge of the prevalence of hypertension among healthcare providers and patients is critical to enhancing screening and early case detection and management strategies within the clinical settings to avert negative outcomes from both hypertension and diabetes.

Estimating the prevalence of hypertension among people with diabetes will inform health systems priorities and health policies for CVD response in the African region in reference to achieving a 25% decrease in hypertension by the end of 2025 [11]. To this end, we aimed at assessing prevalence estimates of hypertension among patients with diabetes in Africa.

Methods

This study was conducted according to a pre-designed protocol and the Preferred Reporting Items for a Systematic Review and Meta-analysis (PRISMA) guideline (S1 Checklist) [12]. The review was registered on the International Prospective Register of Systematic Reviews (Prospero Registration ID: CRD42021256221) [13].

Search strategy

A comprehensive literature search was performed on PubMed, EMBASE, and HINARI databases to identify relevant articles that provided data on the prevalence or incidence of hypertension among people diagnosed with diabetes in Africa. The search terms were categorized into population, outcome/phenomenon of interest, and context In accordance with the recommendation of the Joanna Briggs Institute (JBI) Manual for Evidence Synthesis approach for drafting review questions [14]. Specific terms developed under each category were (1) population: adults diagnosed with type 1 and type 2 diabetes mellitus, with or without hypertension, (2) Outcome/phenomenon of interest: prevalence, incidence, risk factors, co-morbidity, treatment outcomes of diabetes and/or hypertension, and (3) Context: Africa. Based on these pre-specified search terms, a search string for: "Diabetes type 1" OR "Diabetes type 2" AND "hypertension" OR "high blood pressure" AND "Incidence" OR "prevalence" OR "co-morbidity" OR "risk factors" OR "treatment outcomes" AND "Africa" OR "All African countries" was derived through an iterative process and adapted for all the databases. Medical Subject Headings (MeSH) were applied for terms in PubMed. The original search covered from inception to September 2021 on each database. An updated search was conducted in March 2023, to cover the entire period from inception to March 2023. This review is the first study to estimate the prevalence of hypertension among people with diabetes, so no limitation was applied in terms of the year of publication. The full search strategy is available (S1 Table).

Eligibility criteria

We used the ‘‘population, outcome/phenomenon of interest, and context” strategy to guide the inclusion and exclusion criteria. The population included participants diagnosed with type 1 diabetes mellitus (T1DM) or type 2 diabetes mellitus (T2DM). Only studies of cross-sectional design were included. The outcome/phenomenon of interest was the prevalence of hypertension among people with diabetes. We excluded studies that included pregnancy-induced hypertension as an outcome. Hypertension threshold was specified as ≥140/90 mm Hg or ≥130/80 mm Hg according to the World Health Organization guideline [15]. Only studies conducted in African countries were included in the review.

Study selection and data extraction

Articles retrieved from the various databases were exported to Endnote Version X 9.0 software and duplicates were removed. Two reviewers, IB and VL independently conducted title and abstract screening using the Rayyan Software platform. TH and SA resolved any disagreements when the two reviewers could not reach a consensus. TH, OP, and SA independently extracted the data from the included articles using Microsoft Office Excel. Data items including study title, authors, date of publication, region, country, type of participants, age, prevalence of hypertension, complications, diagnostic thresholds for hypertension and diabetes, and factors associated with hypertension among people with diabetes were extracted.

Risk of bias assessment

TH and SA independently conducted quality assessments using a Mixed-Method Appraisal Tool (MMAT) [16]. We initially applied the first two mandatory questions to ascertain the feasibility of the tool. We used the standardized set of questions, Q4.1-Q4.5 which is designed for cross-sectional study designs. The overall quality score of the studies was the average of the independent scores of the two reviewers. Studies that met 4 or 5 of the quality assessment criteria were adjudged to be of high quality and low risk of bias. A rating of 3 means the study met three of the quality assessment criteria, and medium quality and medium risk of bias. However, studies rated 2 or 1 showed poor quality and had a high risk of bias.

Statistical analysis

We performed a tabular synthesis of sample characteristics, effect measures (prevalence), main findings, diagnostic threshold, and criteria of included studies. The prevalence of hypertension among people diagnosed with diabetes was pooled in a random-effects meta-analysis using the “metafor” package in R. We used DerSimonian-Laird’s random-effects model to determine the pooled prevalence as we anticipated considerable heterogeneity among the various studies [17]. We also computed 95% confidence interval (CI) for individual studies and the pooled prevalence using the Clopper-Pearson interval. Furthermore, we used narrative synthesis to summarize the factors associated with hypertension among people with diabetes reported by the studies. Heterogeneity among studies was assessed using I2 statistic and with a 10% level of statistical significance [18]. No cut-off was set for heterogeneity. However, we performed a sub-group analysis based on regional blocks in Africa (East, West, North, South, and Central), diabetes sub-types, and risk of bias scores. We assessed publication bias using funnel plots and Peter’s test for funnel plot asymmetry.

Results

Study results and identification

The initial electronic search yielded 3807 records. De-duplication led to the exclusion of 564 articles; the 3243 articles progressed through titles and abstracts screening, with the exclusion of a further 3126 records. The full texts of the remaining 117 records were extensively reviewed and guided by the eligibility criteria. Three additional articles were identified through hand searching of reference lists. The updated search yielded an additional five studies, published between 2021–2022. Overall, 41 articles fully met our inclusion criteria and were included in this review and the meta-analyses. Details of the screening process are provided in the PRISMA flowchart in (Fig 1).

Fig 1.

Fig 1

Open in a new tab

Characteristics of included studies

Studies were representative of the five regions in Africa. There were more studies conducted in East (n = 15) [19–34], West (n = 10) [35–44], North (n = 4) [45–48], Central (n = 2) [49, 50] and South Africa (n = 10) [51–60]. The included studies were published between 2002 and 2022 and the summary of findings is shown in Table 1. The sample sizes of the studies ranged from 80–116726 and the mean age of the participants was 58 years (± 11) (range: 15–87).

Table 1. Studies included that shows the prevalence of hypertension among people with diabetes in Africa, 2002–2022.

Citation Country Study design Sample size Sample characteristics Criteria for DM diagnosis Criteria for HTN diagnosis Major findings
Abdelbagi et al (2021) Sudan Cross-sectional 1973 (1155 females) Median age– 58 years, range 50 to 65 years. Both T1DM and T2DM participants included HbA1c > 6.5% ≥ 140/ 90 mmHg 47.6% of people with diabetes had HTN. Being male, employed, obese and old are associated with HTN in patients with DM
Berraho et al (2012) Morocco Cross-sectional 525 (361 females) No Median or mean age of participants presented. Only T2DM patients included Not provided ≥ 140/ 90 mmHg 70.4% of people with diabetes had HTN. Associated factors include age, BMI and duration of diabetes
Choukem et al (2007) Cameroon Cross-sectional 210 (104 females) Age, Mean = 56.6 years (15–86years). T1DM and T2DM patients included FCG >126 mg/dl ≥130/80mm/hg 66.70% of people with diabetes had HTN. Associated factors include BMI, obese and duration of diabetes
Dagnew et al (2019) Ethiopia Cross-sectional 315 (153 females) Age, mean = 54.1 years, range (22-87years). Only T2DM patients are included. FPG > 126 mg/dl ≥140/90mm/hg 41% of people with diabetes had HTN. Associated factors include males, old age, employed, higher education and being single
Demoz et al (2019) Ethiopia Cross-sectional 357 (189 females) Mean age = 56 years. Only T2DM patients were included HbA1c<7% Not reported 52.70% of people with diabetes had HTN
Makwero et al (2018) Lesotho Cross-sectional 150 (121 females) Age, mean = 58.2years, range 19-97years. Both T1DM and T2DM participants included HbA1c > 7.0% >130/80 mmHg 85.3% of people with diabetes had HTN
Mogre et al (2014) Ghana Cross sectional Study 100 (77 females) Mean age = 67.53 years. T2DM patients FPG ≥6.1 mmol/L ≥140/90mm/hg 21% of people with diabetes had HTN
Regassa et al (2020) Ethiopia Cross-sectional Study 454 (195 females) Mean age = 45.39 years, range (15 – 86years) included only T2DM participants. Not specified >139/89 mmHg. 60% of people with diabetes had HTN
Abdissa et al 2020 Ethiopia Cross-sectional Study 366 (163 females) Mean age = 50.1 years. Both T1DM and T2DM participants included Not specified ≥140/90 mmHg 37.40% of people with diabetes had HTN. Associated factors include age, BMI, and Khat chewing
Adeniyi et al 2016 South Africa Cross sectional Study 265 (190 females) Mean age = 56.7 years. Included only T2DM participant Not specified ≥140/90 mmHg 75.5% of people with diabetes had HTN. Associated factors include male, age, unemployed, excessive alcohol intake and consumption
Arije et al 2007 Nigeria Cross sectional Study 256 (146 females) Mean age = 59.1 years, range (21-83yrs) including only DM patients [type not specified]. Not specified 140/90mm/HG 42.20% of people with diabetes had HTN.
Githinji et al 2018 Kenya Cross-sectional study 1548 (919 females) Mean age = 58 years. Both T1DM and T2DM participants included Not specified ≥140/90 mmHg 34% of people with diabetes had HTN
Ndege et al 2014 Ethiopia Cross sectional Study 218 (122 females) Mean age = 57 years. Only T2DM participants included Not specified ≥140/90 mmHg 85% of people with diabetes had HTN
Thinyane et al 2013 Lesotho Cross-sectional study 80 (39 females) Median age 49 with age range (36 0 56 years) Both T1DM and T2DM participants included Not specified ≥140/90 mmHg 56% of people with diabetes had HTN
Mengesha et al 2007 Botswana Cross sectional Study 401 (287 females) Age range (30–70years) Both T1DM and T2DM participants included Not specified ≥140/90 mmHg 61.20% of people with diabetes had HTN. Associated factors include age, sex, type of DM, BMI and hypertriglyceridemia
Akalu et al 2020 Ethiopia Cross sectional study 378 (153 females) Mean age = 56 years. Only participants with T2DM included HbA1c ≥6.5% ≥140/90 mmHg 59.50% of people with diabetes had HTN. Associated factors include age range (50 -60yrs), patients from urban area, BMI, longer duration of T2DM, patients with poor glycaemic control and patients who were current cigarette smokers
Awadalla et al 2017 Sudan Cross sectional study 424 (209 females) Age range (20 – 75years) T2DM patients included HbA1c ≥7.1% ≥140/90mm/Hg 39.90% of people with diabetes had HTN. Associated factors including longer duration of diabetes and living in urban areas
Chetty et al 2021 South Africa Cross sectional 4122 (3072 females) Mean age = 59.21 years, range (45 – 74yrs); T2DM participants included Not specified Not reported 77.90% of people with diabetes had HTN. Associated factors include female
Gezawa et al 2019 Nigeria Cross sectional study 220 (123 females) Age range (35–65 years) including T2DM and T1DM diabetic patients Not specified SBP≥140mmHg or DBP≥90mmHg 46.80% of people with diabetes had HTN
Hussein et al 2020 Egypt Cross sectional study 800 (200 females) Age, mean = 58.2 years. T2DM patients included. HbA1c ≥7.0% ≥140/90 mmHg 60.25% of people with diabetes had HTN
Kemche et al 2020 Cameroon Cross sectional study 109 (66 females) Mean age = 55 years. Both participants with T1DM and T2DM included Not specified ≥140/90mm/Hg 86.20% of people with diabetes had HTN. Associated factors include eating more than 2 times a day and long duration of diabetes
Tsegaw et al 2021 Ethiopia Cross sectional Study 739 (307 females) Age range (26 – 85years) including T2DM participants HbA1c >7.0–9.0% 140/90mm/Hg 50.20% people with diabetes have HTN
Unadike et al 2011 Nigeria Cross sectional Study 450 (225 females) Mean age = 51.1 years; Only participants with T2DM included. Not specified 140/90mm/Hg 54.20% of people with diabetes had HTN
Wanjohi et al 2002 Ethiopia Cross Sectional Study 100 (63 females) Median age 53.7 years, Age range (34-80years) included Patients with T2DM only HbA1c≥7.0 FPG ≥5.9mmol/L Not reported 50% of people with diabetes had HTN
Amankwah-Poku et al 2020 Ghana Cross-sectional study 162 (128 Females) Mean age = 61.0 years Recruited participants with T2DM Not reported >140/90mm/Hg 79.6% people with diabetes had HTN
Danquah et al 2012 Ghana Cross-sectional study 675 (323 Females) Mean age,54.7 years; Recruited T2DM participants FPG≥ 7mmol/L ≥140/90mm/Hg 63% of people diagnosed with diabetes had HTN. Family history of diabetes, working time, increased triglycerides were associated with HTN
Kalain & Omole 2020 South Africa Cross-sectional Study 200 (128 Females) Mean age,57.8 years; Recruited T2DM participants HbA1c ≥7.0% ≥140/90mm/Hg 92% of people diagnosed with diabetes had HTN.
Goie & Naidoo 2016 South Africa Cross sectional Study 280 (201 were female) Mean Age 59 years, Recruited T2DM participants Not Reported ≥140/90mm/Hg 57.5% of people diagnosed with diabetes had HTN.
Thomas et al 2013, South Africa Cross-sectional Study 5565 (2016 Females) Mean Age, 50.8 years, Recruited people with T1DM and T2DM participants HbA1c ≥7.0% ≥140/90mm/Hg 44.0% of people diagnosed with diabetes had HTN.
Boake & Mash 2022 South Africa Cross-sectional Study 116726 (74471 females) Mean Age, 61.4 years, Recruited people with T1DM and T2DM participants HbA1c ≥7.0% ≥140/90mm/Hg 69.5% of people diagnosed with diabetes had HTN.
Rotchford & Rotchford 2002 South Africa Cross sectional Study 253 (183 were females Mean Age, 56.5 years, Recruited people with T1DM and T2DM participants HbA1c >5.7% ≥140/90mm/Hg 41.8% of people diagnosed with diabetes had HTN.
Mfeukeu-Kuate et al. 2022 Cameroon Cross-sectional study 112(49 were females) Median age was 58 years, recruited participants with T2DM Not Reported ≥140/90mm/Hg 50.4% of people diagnosed with diabetes had HTN.
Amoussou-Guenou et al. 2015 Benin Cross-sectional study 400 (264 were females) Median age was mean age was 55.6 recruited participants with T2DM and HbA1c > 7% ≥140/90mm/Hg 70.0% of people diagnosed with diabetes had HTN. Above 555 years is associated with hypertension
Ovono et al 2011 Gabon Cross-sectional study 1300 (699 were females) Mean age was 53 years, recruited participants with T2DM HbA1c > 7% ≥140/90mm/Hg 35% of people diagnosed with diabetes had HTN
Dzudie et al 2012 Cameroon Cross-sectional study 420 (215 were females) Mean age was 55.9 years, recruited participants with T2DM Not Reported >140/90mm/Hg 50.2% of people diagnosed with diabetes had HTN
Kimando et al 2017 Kenya Cross-sectional study 385 (253 were females) Mean age was 63.3 years, recruited participants with T2DM HbA1c > 7% ≥140/90mm/Hg 49.6% of people diagnosed with diabetes had HTN. Old age above 50 yrs., longer duration with diabetes above 5 yrs. and advanced stages of CKD
Chahbi et al 2018 Morrocco Cross-sectional study 300 (279 were females) Mean age was 57.24 years recruited, participants with T2DM HbA1c >7% ≥140/90mm/Hg 44.3% of people diagnosed with diabetes had HTN
Kilonzo et al 2017 Tanzania Cross-sectional study 295 (161 were females) Mean age was 57 years, recruited, participants with T2DM FBG >7.0mmol/L. ≥130/80mmHg 69.8% of people diagnosed with diabetes had HTN
Munyogwa et al. 2020 Tanzania. Cross-sectional study 330 (189 were females) Mean age was 40.27 years, recruited, participants with T2DM FBG ≥11.1 mmol/l ≥140/90mm/Hg 63.3% of people diagnosed with diabetes had HTN
Mwita et al 2019 Tanzania Cross-sectional study 150 (93 were females) Mean age was 51.6 years, recruited, participants with T2DM and T1DM Not Reported ≥140/90mm/Hg 54.7% of people diagnosed with diabetes had HTN
Kahloun et al.2014 Tunisia Cross-sectional study 2320 (1396 were females) Mean age was 54.5 years, recruited, participants with T2DM Not Reported Not Reported 37.5% of people diagnosed with diabetes had HTN
Open in a new tab

SBP–Systolic Blood Pressure, DBP–Diastolic Blood Pressure, HTN–Hypertension, T1DM–Type 1 diabetes mellitus, T2DM–Type 2 diabetes mellitus, FBG–Fasting Blood Glucose; HbA1C –Hemoglobin A1C; FCG–Fasting Capillary Glucose; FPG–Fasting Plasma Glucose

While most 33 (80%) of the studies utilized a cut-off point of ≥140/90 mm Hg for hypertension diagnosis, some 4 (10%) used ≥130/80 mm Hg, and the remaining 4(10%) did not report. A few of the studies included in the review used a hemoglobin A1c (HbA1c) threshold between (≥5.7 and >7.0) [20–23, 26–29, 31, 34, 35, 37, 39, 46, 48, 50, 53, 58, 59]. In some cases, a fasting plasma/blood glucose level of 5–7 mmol/L or more was used [61]. Other studies used HbA1c levels exceeding 6.5 or 7 as a diagnostic criterion for diabetes [20, 21, 31, 34, 43, 46, 57–59]. Twenty-four studies (59%) included patients diagnosed with only T2DM, seventeen (41%) included both T1DM and T2DM and no study was found among only patients with T1DM. Overall, the prevalence of hypertension among people with diabetes ranged from 21% in a study conducted in Ghana [37] to 92% in South Africa [58].

Prevalence of hypertension in people with diabetes (T1DM and T2DM)

Forty-one studies had complete data on the prevalence of hypertension among people diagnosed with diabetes and hence were eligible for inclusion in the meta-analysis. Overall, the prevalence of hypertension among people diagnosed with diabetes was 58.1% (95% CI: 52.%–63.2%) shown in (Fig 2). This is further depicted in a heat map of Africa highlighting the regional prevalence of hypertension among people with diabetes (Fig 3). There was high and significant statistical heterogeneity across studies (i2 = 98%, p<0.001). The prevalence of hypertension among people diagnosed with diabetes within the five geopolitical regions; East Africa 53.0% [95% CI: 45.8%–59.1%] (S1 Fig), West Africa 51.5% [95% CI: 41.8%–61.1%] (S2 Fig), North Africa 63.4% [95% CI: 37.1%–69.1%;] (S3 Fig), South Africa 69.1% [95% CI: 59.8%–77.1%;] (S4 Fig), and with Central Africa had the highest hypertension prevalence; 77.6% [95% CI: 53.0%–91.4%] (S5 Fig).

Fig 2.

Fig 2

Open in a new tab

Fig 3.

Fig 3

Open in a new tab

Prevalence of hypertension in patients with only T2DM

Twenty-four studies (59%) included people diagnosed with T2DM (Fig 4). Sub-group analysis among those with T2DM showed a prevalence of 60.8% (CI:53.4%-67.7%; i2 = 99%, p<0.01) which was higher than the overall prevalence among T1DM and T2DM “combined” (58%). The highest prevalence was in South Africa (92%) followed by Ethiopia (84.9%), Zimbabwe (80%), and Ghana (74.6%) among participants with only T2DM. Some countries had only one study, hence estimation of the lowest prevalence among people with T2DM was impossible.

Fig 4.

Fig 4

Open in a new tab

Assessment of risk of bias

A summary of the risk of bias is shown in (S2 Table). Thirty-six of the studies had a score of 4 and 5 suggesting high quality and low risk of bias. Most of the studies had adequate sample sizes and were representative enough. However, few studies were at risk of bias due to lack of sample representativeness [25, 26, 37, 45, 49, 50, 53–55, 62]. Statistical appropriateness for the research question was unclear or not consistent with the study aims [22, 28, 33, 36, 38, 41, 50, 54–56, 59]. Except for Abdelbagi, et al, the sampling strategy was clearly stated in all the studies [20]. Although no study was excluded based on the risk assessment score, we conducted further analysis using studies with scores 4 and 5 and found relatively same prevalence (S6 Fig). The prevalence estimates of hypertension according to the risk of bias score were relatively the same as the overall prevalence estimate for the overall studies and among studies that included only participants with type 2 diabetes (S7 Fig). The result of the linear regression test of funnel plot asymmetry; t = -2.22, df = 39, p-value = 0.0322, showed evidence of plot asymmetry, which is suggestive of publication bias (Fig 5).

Fig 5.

Fig 5

Open in a new tab

Factors associated with hypertension among people with diabetes (T1DM and T2DM)

Some studies reported factors associated with developing hypertension among people with diabetes. For instance, Abdellagi and colleagues found that the odds of developing hypertension increased with increasing age, body mass index, and being employed. In one study, age increased the odds of hypertension by more than 600% (OR 7.26 4.20–12.54) [45]. Furthermore, the risk for hypertension among people with diabetes is highest within the 50–60 age category [31]. The duration of diabetes is also associated with an increasing risk of developing hypertension. In three studies, being male increases the odds of developing hypertension among people diagnosed with diabetes. With regards to the residence, Akalu et al. (2020) and Awadalla et al. (2017) reported that people diagnosed with diabetes living in urban residence have higher chances of developing hypertension.

Discussion

We comprehensively reviewed the available literature and conducted a meta-analysis on the prevalence of hypertension among people with diabetes in Africa. The pooled prevalence of hypertension was 58.1%, with high statistical heterogeneity across studies. The prevalence varied across African sub-regions, with Central Africa having the highest prevalence of (77.6%) with West Africa recording the lowest (51.5%). This finding is consistent with a systematic review by Colosia et al. who reported a hypertension prevalence between 38.5–80% among people with diabetes globally [63]. Comparably, while the overall prevalence of hypertension among people with diabetes is slightly higher than the prevalence (55.2%) in the general population in Africa [64], the sub-regional analysis was much higher in the North, Central, and South African sub-regions which can be attributed to the differences in socio-cultural practices, food insecurity, differences in access to healthcare and socio-economic conditions in the sub-region. Furthermore, this high heterogeneity can be explained in terms of the different diagnostic criteria for the diagnosis of hypertension and diabetes in the region.

This review provides evidence of the increasing risk of hypertension among people with diabetes in Africa. For instance, a review conducted in Ethiopia reported a hypertension prevalence of 55% among patients with diabetes, which aligns with the 53% prevalence recorded in this review for the East Africa sub-region [65]. While this highlights the need for further research to explore the physiological mechanism between the risk of hypertension among people with T2DM in the region, the few studies identified from North and Central Africa regions in this review point to the limited research on hypertension among people with diabetes in these African sub-regions.

Among people diagnosed with T2DM, the prevalence of hypertension was 60.8%, which was higher than the overall prevalence among people with both T1DM and T2DM combined. The South African region recorded the highest prevalence of (92%) and its lowest at 57.5%. This finding can be explained in the context of urbanization, increasing prevalence of overweight and obesity in the Southern African region compared to East and West African regions. Given that obesity is a significant risk factor for hypertension, it was not surprising to find that African regions that reported the highest prevalence of obesity also recorded the highest prevalence of hypertension among its diabetes population.

Additional analysis conducted identified age, long duration of diabetes, male sex, and living in urban areas as factors associated with the developing hypertension-diabetes co-morbidity. This finding corroborates the findings of the largest United Kingdom Prospective Diabetes Study (UKPDS) in 1998 which reported an association between age, bigger waist/hip ratio, sedentary lifestyle with diabetes development, and further cardiovascular risk [66]. Moreover, other studies have shown that time since diabetes diagnosis is positively and independently associated with the risk of developing macrovascular and macrovascular complications among people with diabetes.

Strengths and limitations

Previous reviews have focused on hypertension or diabetes burden in infectious diseases such as HIV/AIDS and Tuberculosis in Africa. However, this study is the first review to estimate the prevalence of hypertension among people diagnosed with diabetes in Africa. Additionally, this review captured the prevalence among people with T2DM and T1DM. However, the review needs to be considered in the context of some limitations. Only studies published in English were included and that may cause language bias, especially as some African countries publish in other languages like French. More specifically, countries in central Africa were likely to be under-represented which could affect the prevalence estimates. Nonetheless, this review provides a snapshot of the prevalence of hypertension among people with diabetes in Africa. Additionally, we searched only three databases and may have not captured all the studies conducted in the region about hypertension/diabetes comorbidity. Lastly, there was a high statistical heterogeneity across studies even after accounting for regional variations. The high heterogeneity in our meta-analysis may limit the generalizability of our pooled prevalence estimate and should be considered when interpreting the overall findings.

Implications for policy and practice

The high burden of hypertension among people with diabetes in Africa presents significant implications for health policy and research. Firstly, health systems should be strengthened to meet the needs of people living with hypertension/diabetes comorbidity through the adoption of an integrated model of care that provides an opportunity to cost-effectively manage both hypertension and diabetes without further strain on resources and healthcare providers. Community-based interventions are required to increase awareness of hypertension and diabetes in Africa. The evidence from this review also supports the adoption of a team-based care policy, and further research is required to examine its feasibility in the African region.

Supporting information

S1 Checklist. PRISMA 2009 checklist.

(PDF)

Click here for additional data file. (66.2KB, pdf)
S1 Table. Search strategy.

(PDF)

Click here for additional data file. (112.9KB, pdf)
S2 Table. Assessment of risk of bias.

(PDF)

Click here for additional data file. (134.6KB, pdf)
S1 Fig. Prevalence of hypertension among people with diabetes in West Africa: Systematic review, and meta-analysis.

(TIF)

Click here for additional data file. (1.9MB, tif)
S2 Fig. Prevalence of hypertension among people with diabetes in West Africa: Systematic review, and meta-analysis.

(TIF)

Click here for additional data file. (1.7MB, tif)
S3 Fig. Prevalence of hypertension among people with diabetes in North Africa: Systematic review, and meta-analysis.

(TIF)

Click here for additional data file. (1MB, tif)
S4 Fig. Prevalence of hypertension among people with diabetes in South Africa: Systematic review, and Meta-analysis.

(TIF)

Click here for additional data file. (1.8MB, tif)
S5 Fig. Prevalence of hypertension among people with diabetes in Central Africa: Systematic review, and meta-analysis.

(TIF)

Click here for additional data file. (929.4KB, tif)
S6 Fig. Forest plot of studies showing studies with a high-quality score of 4 or better.

(TIF)

Click here for additional data file. (2.4MB, tif)
S7 Fig. Forest plot of high-quality studies included only participants with type 2 diabetes.

(TIF)

Click here for additional data file. (1.7MB, tif)

Acknowledgments

We thank Emily Hoppe a Ph.D. candidate at the Johns Hopkins University School of Nursing for providing support on using the ArcGIS platform to visually present the map prevalence of hypertension on the African map.

Data Availability

All data used in this manuscript has been included in this manuscript.

Funding Statement

The authors received no specific funding for this work.

References

  • 1.Forouzanfar MH, Alexander L, Bachman VF, Biryukov S, Brauer M, Casey D, et al. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990–2013: A systematic analysis for the Global Burden of Disease Study 2013. The Lancet. 2015;386: 2287–2323. doi: 10.1016/S0140-6736(15)00128-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Lin X, Xu Y, Pan X, Xu J, Ding Y, Sun X, et al. Global, regional, and national burden and trend of diabetes in 195 countries and territories: an analysis from 1990 to 2025. Scientific Reports 2020 10:1. 2020;10: 1–11. doi: 10.1038/s41598-020-71908-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.World Health Organization. Global Hypertension bulletin. In: Key facts Hypertension [Internet]. 2021 [cited 28 Oct 2021]. Available: https://www.who.int/news-room/fact-sheets/detail/hypertension
  • 4.Zhou B, Perel P, Mensah G, Ezzati M. Global epidemiology, health burden and effective interventions for elevated blood pressure and hypertension. Nat Rev Cardiol. 2021. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Voorham J, Haaijer-Ruskamp FM, Wolffenbuttel BHR, de Zeeuw D, Stolk RP, Denig P. Differential Effects of Comorbidity on Antihypertensive and Glucose-Regulating Treatment in Diabetes Mellitus–A Cohort Study. PLoS One. 2012;7. doi: 10.1371/Journal.Pone.0038707 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Eren NK, Harman E, Dolek D, Tütüncüoʇlu AP, Emren SV, Levent F, et al. Rate of blood pressure control and antihypertensive treatment approaches in diabetic patients with hypertension. Turk Kardiyol Dern Ars. 2014;42: 733–740. doi: 10.5543/TKDA.2014.53384 [DOI] [PubMed] [Google Scholar]
  • 7.Kerr EA, Heisler M, Krein SL, Kabeto M, Langa KM, Weir D, et al. Beyond comorbidity counts: how do comorbidity type and severity influence diabetes patients’ treatment priorities and self-management? J Gen Intern Med. 2007;22: 1635–1640. doi: 10.1007/S11606-007-0313-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Du Y, Heidemann C, Göwald A, Schmich P, Scheidt-Nave C. Prevalence and comorbidity of diabetes mellitus among non-institutionalized older adults in Germany—results of the national telephone health interview survey “German Health Update (GEDA)” 2009. BMC Public Health. 2013;13. doi: 10.1186/1471-2458-13-166 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Kaplan MH, Feinstein AR. The importance of classifying initial co-morbidity in evaluating the outcome of diabetes mellitus. J Chronic Dis. 1974;27: 387–404. doi: 10.1016/0021-9681(74)90017-4 [DOI] [PubMed] [Google Scholar]
  • 10.Conwell LJ, Boult C. The effects of complications and comorbidities on the quality of preventive diabetes care: a literature review. Popul Health Manag. 2008;11: 217–228. doi: 10.1089/POP.2007.0017 [DOI] [PubMed] [Google Scholar]
  • 11.World Health Organization. Global NCD target: reduce high blood pressure. 2016 [cited 3 Oct 2023]. Available: https://www.who.int/publications/i/item/global-ncd-target-reduce-high-blood-pressure
  • 12.Moher D, Liberati A, Tetzlaff J, Altman DG. Guidelines and Guidance Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. 2009. doi: 10.1371/journal.pmed.1000097 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Hinneh T, Akyirem S, Fosuhemaa IB, Lambongang V, Ofori-Aning P. Hypertension and diabetes comorbidity in Africa, a systematic review. In: PROSPERO 2021 CRD42021256221; [Internet]. Jun 2021. [cited 19 Mar 2022]. Available: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021256221 [Google Scholar]
  • 14.Munn Z, Aromataris E, Tufanaru C, Stern C, Porritt K, Farrow J, et al. The development of software to support multiple systematic review types: The Joanna Briggs Institute System for the Unified Management, Assessment and Review of Information (JBI SUMARI). Int J Evid Based Healthc. 2019;17: 36–43. doi: 10.1097/XEB.0000000000000152 [DOI] [PubMed] [Google Scholar]
  • 15.Campbell NRC, Paccot Burnens M, Whelton PK, Angell SY, Jaffe MG, Cohn J, et al. 2021 World Health Organization guideline on pharmacological treatment of hypertension: Policy implications for the region of the Americas. Lancet Regional Health—Americas. 2022;9. doi: 10.1016/J.LANA.2022.100219 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Hong QN, Fàbregues S, Bartlett G, Boardman F, Cargo M, Dagenais P, et al. The Mixed Methods Appraisal Tool (MMAT) version 2018 for information professionals and researchers. Education for Information. 2018;34: 285–291. doi: 10.3233/EFI-180221 [DOI] [Google Scholar]
  • 17.Jackson D, Bowden J, Baker R. How does the DerSimonian and Laird procedure for random effects meta-analysis compare with its more efficient but harder to compute counterparts? J Stat Plan Inference. 2010;140: 961–970. doi: 10.1016/J.JSPI.2009.09.017 [DOI] [Google Scholar]
  • 18.Higgins JPT, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;21: 1539–1558. doi: 10.1002/SIM.1186 [DOI] [PubMed] [Google Scholar]
  • 19.Abdissa D, Adugna T, Gerema U, Dereje D. Prevalence of Diabetic Foot Ulcer and Associated Factors among Adult Diabetic Patients on Follow-Up Clinic at Jimma Medical Center, Southwest Ethiopia, 2019: An Institutional-Based Cross-Sectional Study. J Diabetes Res. 2020;2020. doi: 10.1155/2020/4106383 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Abdelbagi O, Musa IR, Musa SM, ALtigani SA, Adam I. Prevalence and associated factors of hypertension among adults with diabetes mellitus in northern Sudan: a cross-sectional study. BMC Cardiovasc Disord. 2021;21: 1–7. doi: 10.1186/S12872-021-01983-X/TABLES/3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Awadalla H, Noor SK, Elmadhoun WM, Almobarak AO, Elmak NE, Abdelaziz SI, et al. Diabetes complications in Sudanese individuals with type 2 diabetes: Overlooked problems in sub-Saharan Africa? Diabetes Metab Syndr. 2017;11 Suppl 2: S1047–S1051. doi: 10.1016/J.DSX.2017.07.039 [DOI] [PubMed] [Google Scholar]
  • 22.Dagnew B, Yeshaw Y. Predictors of isolated systolic hypertension among type 2 diabetes mellitus patients in Jimma University Specialized Hospital, Southwest Ethiopia. BMC Res Notes. 2019;12: 1–7. doi: 10.1186/S13104-019-4550-3/TABLES/3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Demoz GT, Gebremariam A, Yifter H, Alebachew M, Niriayo YL, Gebreslassie G, et al. Predictors of poor glycemic control among patients with type 2 diabetes on follow-up care at a tertiary healthcare setting in Ethiopia. BMC Res Notes. 2019;12: 1–7. doi: 10.1186/S13104-019-4248-6/TABLES/2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Githinji G.G., Hussein A.A., Kimani T. et al. Prevalence of diabetes and co-morbidities in five rural and semi-urban Kenyan counties, 2010–2015. Int J Diabetes Dev Ctries 38, 243–248 (2018). 10.1007/s13410-017-0566-1. [DOI] [Google Scholar]
  • 25.Ndege KBW, Owiti MOG, Anjichi G, Siika AM, Ndege BW, Diero LO. Prevalence, Treatment And Control Of Hypertension Among Type 2 Diabetic Patients At Moi Teaching And Referral Hospital, Eldoret, Kenya. East Afr Med J. 2014. [PubMed] [Google Scholar]
  • 26.Wanjohi FW, Otieno FCF, Ogola EN, Amayo EO. Nephropathy in patients with recently diagnosed type 2 diabetes mellitus in black Africans. East Afr Med J. 2002;79: 399–404. doi: 10.4314/EAMJ.V79I8.8824 [DOI] [PubMed] [Google Scholar]
  • 27.Kimando MW, Otieno FCF, Ogola EN, Mutai K. Adequacy of control of cardiovascular risk factors in ambulatory patients with type 2 diabetes attending diabetes out-patients clinic at a county hospital, Kenya. BMC Endocr Disord. 2017;17. doi: 10.1186/S12902-017-0223-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Kilonzo SB, Gunda DW, Bakshi FA, Kalokola F, Mayala HA, Dadi H. Control of Hypertension among Diabetic Patients in a Referral Hospital in Tanzania: A Cross-Sectional Study. Ethiop J Health Sci. 2017;27: 473–480. doi: 10.4314/EJHS.V27I5.5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Munyogwa MJ, William R, Kibusi SM, Gibore NS. Clinical characteristics and health care received among patients with type 2 diabetes attending secondary and tertiary healthcare facilities in Mwanza Region, Tanzania: A cross-sectional study. BMC Health Serv Res. 2020;20: 1–11. doi: 10.1186/S12913-020-05407-Y/TABLES/6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Mwita JC, Francis JM, Omech B, Botsile E, Oyewo A, Mokgwathi M, et al. Glycaemic, blood pressure and low-density lipoprotein-cholesterol control among patients with diabetes mellitus in a specialised clinic in Botswana: a cross-sectional study. BMJ Open. 2019;9: e026807. doi: 10.1136/BMJOPEN-2018-026807 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Akalu Y, Belsti Y. Hypertension and Its Associated Factors Among Type 2 Diabetes Mellitus Patients at Debre Tabor General Hospital, Northwest Ethiopia. Diabetes Metab Syndr Obes. 2020;13: 1621. doi: 10.2147/DMSO.S254537 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Muleta S, Melaku T, Chelkeba L, Assefa D. Blood pressure control and its determinants among diabetes mellitus co-morbid hypertensive patients at Jimma University medical center, South West Ethiopia. Clin Hypertens. 2017;23: 1–9. doi: 10.1186/S40885-017-0085-X/TABLES/4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Regassa LD, Tola A, Ayele Y. Prevalence of Cardiovascular Disease and Associated Factors Among Type 2 Diabetes Patients in Selected Hospitals of Harari Region, Eastern Ethiopia. Front Public Health. 2020;8: 532719. doi: 10.3389/FPUBH.2020.532719 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Tsegaw A, Alemu S, Dessie A, Patterson CC, Parry EHO, Phillips DIW, et al. Diabetic Retinopathy in Type 2 Diabetes Mellitus Patients Attending the Diabetic Clinic of the University of Gondar Hospital, Northwest Ethiopia. J Ophthalmol. 2021;2021. doi: 10.1155/2021/6696548 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Danquah I, Bedu-Addo G, Terpe KJ, Micah F, Amoako YA, Awuku YA, et al. Diabetes mellitus type 2 in urban Ghana: Characteristics and associated factors. BMC Public Health. 2012;12: 1–8. doi: 10.1186/1471-2458-12-210/TABLES/2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Arije A, Kuti M, Fasanmade A, Akinlade K, Ashaye A, Obajimi M, et al.; Control of hypertension in Nigerians with Diabetes Mellitus: A report of the Ibadan Diabetic / Kidney Disease Study Group. International Journal of Diabetes and Metabolism 1 March 2007; 15 (3): 82–86. [Google Scholar]
  • 37.Mogre V, Abedandi R, Salifu ZS. Prevalence of obesity and systemic hypertension among diabetes mellitus patients attending an out-patient diabetes clinic in a Ghanaian Teaching Hospital. Diabetes & Metabolic Syndrome: Clinical Research & Reviews. 2014;8: 67–71. doi: 10.1016/J.DSX.2014.04.036 [DOI] [PubMed] [Google Scholar]
  • 38.Unadike BC, Eregie A, Ohwovoriole AE. Prevalence of hypertension amongst persons with diabetes mellitus in Benin City, Nigeria. Niger J Clin Pract. 2011;14: 300–302. doi: 10.4103/1119-3077.86772 [DOI] [PubMed] [Google Scholar]
  • 39.Amankwah-Poku M, Amoah AGB, Sefa-Dedeh A, Akpalu J. Psychosocial distress, clinical variables and self-management activities associated with type 2 diabetes: a study in Ghana. Clin Diabetes Endocrinol. 2020;6. doi: 10.1186/S40842-020-00102-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Mfeukeu-Kuate L, Meyanui VA, Jingi AM, Ndobo-Koe V, Mballa F, Ntep-Gweth M, et al. Prevalence and determinants of silent myocardial ischemia in patients with type 2 diabetes in Cameroon: a cross-sectional study. Pan Afr Med J. 2022;42. doi: 10.11604/PAMJ.2022.42.41.34941 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Amoussou-Guenou D, Wanvoegbe A, Agbodandé A, Dansou A, Tchabi Y, Eyissè Y, et al. Prevalence and Risk Factors of Hypertension in Type 2 Diabetics in Benin. J Diabetes Mellitus. 2015;5: 227–232. doi: 10.4236/JDM.2015.54027 [DOI] [Google Scholar]
  • 42.Dzudie A, Kengne AP, Muna WFT, Ba H, Menanga A, Kouam CK, et al. Prevalence, awareness, treatment and control of hypertension in a self-selected sub-Saharan African urban population: a cross-sectional study. BMJ Open. 2012;2. doi: 10.1136/BMJOPEN-2012-001217 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Ovono AF, Bekale S, Fernandez J, Mbang BA, Ngou-Milama E. Cardiovascular risk factors in type 2 diabetic patients in Libreville, Gabon. African Journal of Diabetes Medicine. 2011. [Google Scholar]
  • 44.Gezawa ID, Uloko AE, Gwaram BA, Ibrahim DA, Ugwu ET, Mohammed IY. Pattern of Obesity Among Patients with Type 2 Diabetes at a Tertiary Healthcare Center in Northern Nigeria. Diabetes Metab Syndr Obes. 2019;12: 2785. doi: 10.2147/DMSO.S226054 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Berraho M, El Achhab Y, Benslimane A, El Rhazi KE, Chikri M, Nejjari C. Hypertension and type 2 diabetes: a cross-sectional study in Morocco (EPIDIAM Study). Pan Afr Med J. 2012;11: 52. Available: /pmc/articles/PMC3343680/ [PMC free article] [PubMed] [Google Scholar]
  • 46.Hussein A, Mahmoud SED, Awad MS, Mahmoud HEM. Assessment of Cardiovascular Risk Factors in Patients with Type 2 Diabetes in Upper Egypt Villages. Diabetes Metab Syndr Obes. 2020;13: 4737–4746. doi: 10.2147/DMSO.S282888 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Kahloun R, Jelliti B, Zaouali S, Attia S, Ben Yahia S, Resnikoff S, et al. Prevalence and causes of visual impairment in diabetic patients in Tunisia, North Africa. Eye (Lond). 2014;28: 986–991. doi: 10.1038/EYE.2014.131 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Chahbi Z, Lahmar B, Hadri S El, Abainou L, Kaddouri S, Qacif H, et al. The prevalence of painful diabetic neuropathy in 300 Moroccan diabetics. Pan Afr Med J. 2018;31: 158. doi: 10.11604/PAMJ.2018.31.158.14687 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Kemche B, Saha Foudjo BU, Fokou E. Risk Factors of Hypertension among Diabetic Patients from Yaoundé Central Hospital and Etoug-Ebe Baptist Health Centre, Cameroon. J Diabetes Res. 2020;2020. doi: 10.1155/2020/1853516 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Choukem SP, Kengne AP, Dehayem YM, Simo NL, Mbanya JC. Hypertension in people with diabetes in sub-Saharan Africa: Revealing the hidden face of the iceberg. Diabetes Res Clin Pract. 2007;77: 293–299. doi: 10.1016/j.diabres.2006.11.007 [DOI] [PubMed] [Google Scholar]
  • 51.Adeniji F, Obembe T. Cardiovascular Disease and Its Implication for Higher Catastrophic Health Expenditures Among Households in Sub-Saharan Africa. J Health Econ Outcomes Res. 2023. doi: 10.36469/jkheor.2023.70252 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52.Chetty L, Govender N, Govender GM, Reddy P. Demographic stratification of Type 2 diabetes and comorbidities in district healthcare in KwaZulu-Natal. South African Family Practice. 2021;63. doi: 10.4102/SAFP.V63I1.5218 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Makwero MT, Mollentze WF, Joubert G, Steinberg WJ. Anthropometric profile and complications in patients with diabetes mellitus seen at Maluti Adventist Hospital, Lesotho. South African Family Practice. 2018;60: 97–102. doi: 10.1080/20786190.2018.1426901 [DOI] [Google Scholar]
  • 54.Mengesha AY. Hypertension and related risk factors in type 2 diabetes mellitus (DM) patients in Gaborone City Council (GCC) clinics, Gaborone, Botswana. Afr Health Sci. 2007;7: 244. Available: /pmc/articles/PMC3074377/ [PMC free article] [PubMed] [Google Scholar]
  • 55.Thinyane KH, Theketsa CE. Characteristics of patients admitted with diabetes in Maseru, Lesotho. Original Article African Journal of Diabetes Medicine. 2013;17. [Google Scholar]
  • 56.Goie TT, Naidoo M. Awareness of diabetic foot disease amongst patients with type 2 diabetes mellitus attending the chronic outpatients department at a regional hospital in Durban, South Africa. Afr J Prim Health Care Fam Med. 2016;8. doi: 10.4102/PHCFM.V8I1.1170 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57.Thomas RL, Distiller L, Luzio SD, Chowdhury SR, Melville VJ, Kramer B, et al. Ethnic differences in the prevalence of diabetic retinopathy in persons with diabetes when first presenting at a diabetes clinic in South Africa. Diabetes Care. 2013;36: 336–341. doi: 10.2337/DC12-0683 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58.Kalain A, Omole OB. Lifestyle advice, processes of care and glycaemic control amongst patients with type 2 diabetes in a South African primary care facility. Afr J Prim Health Care Fam Med. 2020;12. doi: 10.4102/PHCFM.V12I1.2163 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59.Boake M, Mash R. Diabetes in the Western Cape, South Africa: A secondary analysis of the diabetes cascade database 2015–2020. Prim Care Diabetes. 2022;16: 555–561. doi: 10.1016/J.PCD.2022.05.011 [DOI] [PubMed] [Google Scholar]
  • 60.Rotchford A, Rotchford K. Diabetes in rural South Africa- An assessment of care and complications. South African Medical Journal. 2002;92: 536–541. Available: https://www.ajol.info/index.php/samj/article/view/132063 [PubMed] [Google Scholar]
  • 61.Sobry A, Kizito W, Van den Bergh R, Tayler-Smith K, Isaakidis P, Cheti E, et al. Caseload, management and treatment outcomes of patients with hypertension and/or diabetes mellitus in a primary health care programme in an informal setting. Tropical Medicine & International Health. 2014;19: 47–57. doi: 10.1111/TMI.12210 [DOI] [PubMed] [Google Scholar]
  • 62.Adeniyi OV, Yogeswaran P, Longo-Mbenza B, Goon D Ter. Uncontrolled Hypertension and Its Determinants in Patients with Concomitant Type 2 Diabetes Mellitus (T2DM) in Rural South Africa. PLoS One. 2016;11. doi: 10.1371/JOURNAL.PONE.0150033 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63.Colosia AD, Palencia R, Khan S. Prevalence of hypertension and obesity in patients with type 2 diabetes mellitus in observational studies: a systematic literature review. Diabetes Metab Syndr Obes. 2013;6: 327–338. doi: 10.2147/DMSO.S51325 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 64.Kaze AD, Schutte AE, Erqou S, Kengne AP, Echouffo-Tcheugui JB. Prevalence of hypertension in older people in Africa: a systematic review and meta-analysis. J Hypertens. 2017;35: 1345–1352. doi: 10.1097/HJH.0000000000001345 [DOI] [PubMed] [Google Scholar]
  • 65.Haile TG, Mariye T, Tadesse DB, Gebremeskel GG, Asefa GG, Getachew T. Prevalence of hypertension among type 2 diabetes mellitus patients in Ethiopia: a systematic review and meta-analysis. Int Health. 2023;15: 235–241. doi: 10.1093/INTHEALTH/IHAC060 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66.Turner RC. The U.K. Prospective Diabetes Study. A review. Diabetes Care. 1998;21 Suppl 3. doi: 10.2337/DIACARE.21.3.C35 [DOI] [PubMed] [Google Scholar]
PLOS Glob Public Health. doi: 10.1371/journal.pgph.0001931.r001

Decision Letter 0

Leonor Guariguata

26 Sep 2023

PGPH-D-23-00718

Regional Prevalence of Hypertension Among People Diagnosed with Diabetes in Africa, A Systematic Review and Meta-analysis

PLOS Global Public Health

Dear Dr. Hinneh,

Thank you for submitting your manuscript to PLOS Global Public Health. After careful consideration, we feel that it has merit but does not fully meet PLOS Global Public Health’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Dear Dr. Hinneh,

Please see the reviewer comments before we can proceed with your submission.

Kind regards,

Leonor Guariguata

Please submit your revised manuscript by Nov 10 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at globalpubhealth@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pgph/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

We look forward to receiving your revised manuscript.

Kind regards,

Leonor Guariguata, MPH, PhD

Academic Editor

PLOS Global Public Health

Journal Requirements:

1. Some material included in your submission may be copyrighted. According to PLOS’s copyright policy, authors who use figures or other material (e.g., graphics, clipart, maps) from another author or copyright holder must demonstrate or obtain permission to publish this material under the Creative Commons Attribution 4.0 International (CC BY 4.0) License used by PLOS journals. Please closely review the details of PLOS’s copyright requirements here: PLOS Licenses and Copyright. If you need to request permissions from a copyright holder, you may use PLOS's Copyright Content Permission form.

Please respond directly to this email or email the journal office and provide any known details concerning your material's license terms and permissions required for reuse, even if you have not yet obtained copyright permissions or are unsure of your material's copyright compatibility. 

Potential Copyright Issues:

Figure 2: please (a) provide a direct link to the base layer of the map (i.e., the country or region border shape) and ensure this is also included in the figure legend; and (b) provide a link to the terms of use / license information for the base layer image or shapefile. We cannot publish proprietary or copyrighted maps (e.g. Google Maps, Mapquest) and the terms of use for your map base layer must be compatible with our CC-BY 4.0 license. 

Note: if you created the map in a software program like R or ArcGIS, please locate and indicate the source of the basemap shapefile onto which data has been plotted.

If your map was obtained from a copyrighted source please amend the figure so that the base map used is from an openly available source. Alternatively, please provide explicit written permission from the copyright holder granting you the right to publish the material under our CC-BY 4.0 license.

Please note that the following CC BY licenses are compatible with PLOS license: CC BY 4.0, CC BY 2.0 and CC BY 3.0, meanwhile such licenses as CC BY-ND 3.0 and others are not compatible due to additional restrictions. 

If you are unsure whether you can use a map or not, please do reach out and we will be able to help you. The following websites are good examples of where you can source open access or public domain maps: 

* U.S. Geological Survey (USGS) - All maps are in the public domain. (http://www.usgs.gov) 

* PlaniGlobe - All maps are published under a Creative Commons license so please cite “PlaniGlobe, http://www.planiglobe.com, CC BY 2.0” in the image credit after the caption. (http://www.planiglobe.com/?lang=enl) 

* Natural Earth - All maps are public domain. (http://www.naturalearthdata.com/about/terms-of-use/)

Additional Editor Comments (if provided):

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Does this manuscript meet PLOS Global Public Health’s publication criteria? Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe methodologically and ethically rigorous research with conclusions that are appropriately drawn based on the data presented.

Reviewer #1: No

Reviewer #2: Partly

**********

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

Reviewer #1: No

Reviewer #2: No

**********

3. Have the authors made all data underlying the findings in their manuscript fully available (please refer to the Data Availability Statement at the start of the manuscript PDF file)?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception. 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

**********

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

PLOS Global Public Health 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

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors have attempted to estimate the burden of non-communicable diseases in Africa, which is an important problem in the region. However, I have some major concerns with the methods used to achieve this aim. The following are my comments.

1. The study rationale for estimating the prevalence of HTN among diabetes is neither clear from the introduction nor a necessary one. I believe it is more important to estimate the prevalence of joint occurrence of HTN and DM in the population. So instead of using Diabetics as the study population, I would suggest to have the entire population as the study population and estimate the prevalence of co-occurrence of HTN and DM in the general population. The search strategy given by the authors may be sufficient for this objective.

2. For prevalence studies, the standard is to include representative surveys conducted in the community. It is not clear whether the authors included only such studies or whether they included hospital or facility-based studies as well.

3. For LMICs, Google Scholar is an important database to search for published/unpublished literature. I suggest to run a search in Google Scholar for additional studies.

4. The eligibility criteria do not mention types of study designs that will be included in the review.

5. MMAT is not the correct tool for assessing the quality of cross-sectional surveys in SR, if that was the study design included in the review.

6. In statistical methods, the authors have mentioned GLM with logit transformation. It is not clear why this methodology was used. For a simple prevalence meta-analysis, it is not required to do a logit transformation.

7. There is no mention of the high level of heterogeneity in the pooled estimate.

Minor comments

1. Abstract is not written as per the PRISMA guideline. [https://doi.org/10.1371/journal.pmed.1001419]

2. Mean age cannot be calculated in this manner in a SRMA. A simple average of extracted mean ages from each study is not statistically correct.

3. It is not possible in this study to determine the risk factors for HTN or DM and how the p-values were calculated for this is not written.

4. In the introduction, the authors have used the word prevalence and proceed to numbers in million. Prevalence has to be given as a proportion or percentage per unit of population or instead the word prevalence may be avoided.

5. Table 1 is not cited in the main text. Main tables should not be provided in the supplement but in the main text itself.

Reviewer #2: I thank the authors for their attempt to capture the burden of hypertension among persons with diabetes in this population given the impact the double burden is likely to have on policy. By their own background, it is clear that it is fairly well known that the burden is high in the diabetes subpopulation but the attempt to quantify it is noted.

I recommend the authors make some changes and clarify a few issues before this publication is accepted. The limited use of databases, limited language and limited grey literature search makes this review not as comprehensive as it could be and this should be noted in limitations.

The background is well written and provides rationale for the study. There are areas of repeated text-

• Lines 117-120 and

• Lines 120-121 and Lines 124-126 are paraphrased but essentially the same.

I could find no reference in the body of the results to Table 1.

For clarification

1. Kindly explain what the “population, outcome, region” strategy is. It is quoted as if a standard. Can you provide a reference for where it is derived or explain how the authors derived the strategy if it de novo.

2. Authors state that the Hypertension cut off was specified as 140/90 and 130/80. Can you reference the guidelines used to make this specification? Under what circumstances did you accept the various definitions. The latest guidelines of the 2022 ADA recommend that BP should be con- trolled to <140/90 mm Hg in patients with diabetes mellitus, but <130/80 mm Hg if there is a higher CV risk with existing ASCVD or 10-year ASCVD risk of ≥15%. I suspect that the authors used older guidelines and should provide reference and clarity on the circumstances (comorbidities) under which they accepted the various cut off points.

3. Line 165-166: Kindly indicate where it was applicable to use MESH terms? On which terms in PUBMED as this used? Was it used on some and not others since the authors say, “where applicable”

4. The search strategy stating only “Africa” or African countries seems limiting to me. Was NESH used here?

5. Why was the MMAT used for risk of bias assessment? Given that the study focused heavily on prevalence which would be primarily quantitative studies can authors justify the use of this tool which is usually for mixed methods?

6. Line 222-223 states: “32 (78%) of the studies utilized a cut-off point of >140/90 mm Hg for hypertension diagnosis, some 3 (7.3%) used >130/80 mm Hg as the cut-off.” What did the other

studies use as their cut-off?

7. Can the authors explain what was done when the strategy was updated? I understand that the search was repeated but I am not clear on how this was matched against what already existed? Was the title and abstract screening repeated? Was there a duplicate comparison between the old and new list? Using what software?

Major changes requested

1. Even though the authors mention in one sentence in the abstract the use of I2 to assess heterogeneity, no such assessment is described in the actual text of the study. Please describe how heterogeneity was assessed. How was I2 used? What were the cut off values? Did you also conduct a qualitative assessment of heterogeneity? Please describe more fully in the methods of main text.

2. Please describe the results of the risk of bias assessment. This is a critical component of systematic reviews and should not be a footnote in the methods. How did the risk of bias assessment affect the use of the studies? Did the scores influence the authors decisions on which studies should be in the meta-analysis?

For example, given the high heterogeneity, were attempts made to do meta-analysis on studies with only the best quality assessment scores? I highly recommend that the authors conduct meta-analyses only on studies with risk of bias of 4/5 to determine the prevalence in these low risk studies. This would be a suitable form of sensitivity analysis especially as the I2 scores are so high.

3. Since age emerged qualitatively as a major factor in hypertension prevalence, consider also doing meta-analysis in two major age groups, again it may help reduce heterogeneity and provide a clearer picture of prevalence that could inform health care access planning.

4. I caution how the authors interpret their findings. They state that their paper shows evidence of ever increasing prevalence of hypertension and given the lack of trending data, it does not show this. There was no previous systematic review in Africa for comparison so I recommend perhaps simply stating that the burden is high as opposed to increasing

Limitations

The lack of grey literature search and limited to only three databases is a weakness of the study that should be acknowledged in the limitations section. Especially given that the authors actually found publication bias.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

Do you want your identity to be public for this peer review? If you choose “no”, your identity will remain anonymous but your review may still be made public.

For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLOS Glob Public Health. doi: 10.1371/journal.pgph.0001931.r003

Decision Letter 1

Leonor Guariguata

7 Nov 2023

Regional Prevalence of Hypertension Among People Diagnosed with Diabetes in Africa, A Systematic Review and Meta-analysis

PGPH-D-23-00718R1

Dear Mr Hinneh,

We are pleased to inform you that your manuscript 'Regional Prevalence of Hypertension Among People Diagnosed with Diabetes in Africa, A Systematic Review and Meta-analysis' has been provisionally accepted for publication in PLOS Global Public Health.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. A member of our team will be in touch with a set of requests.

Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.

IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they'll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact globalpubhealth@plos.org.

Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Global Public Health.

Best regards,

Leonor Guariguata, MPH, PhD

Academic Editor

PLOS Global Public Health

***********************************************************

Reviewer Comments (if any, and for reference):

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Does this manuscript meet PLOS Global Public Health’s publication criteria? Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe methodologically and ethically rigorous research with conclusions that are appropriately drawn based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

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 (please refer to the Data Availability Statement at the start of the manuscript PDF file)?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception. 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

**********

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

PLOS Global Public Health 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

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Responses were satisfactory

Reviewer #2: Thank you for addressing comments made.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

Do you want your identity to be public for this peer review? If you choose “no”, your identity will remain anonymous but your review may still be made public.

For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Natasha Sobers

**********

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Checklist. PRISMA 2009 checklist.

    (PDF)

    Click here for additional data file. (66.2KB, pdf)
    S1 Table. Search strategy.

    (PDF)

    Click here for additional data file. (112.9KB, pdf)
    S2 Table. Assessment of risk of bias.

    (PDF)

    Click here for additional data file. (134.6KB, pdf)
    S1 Fig. Prevalence of hypertension among people with diabetes in West Africa: Systematic review, and meta-analysis.

    (TIF)

    Click here for additional data file. (1.9MB, tif)
    S2 Fig. Prevalence of hypertension among people with diabetes in West Africa: Systematic review, and meta-analysis.

    (TIF)

    Click here for additional data file. (1.7MB, tif)
    S3 Fig. Prevalence of hypertension among people with diabetes in North Africa: Systematic review, and meta-analysis.

    (TIF)

    Click here for additional data file. (1MB, tif)
    S4 Fig. Prevalence of hypertension among people with diabetes in South Africa: Systematic review, and Meta-analysis.

    (TIF)

    Click here for additional data file. (1.8MB, tif)
    S5 Fig. Prevalence of hypertension among people with diabetes in Central Africa: Systematic review, and meta-analysis.

    (TIF)

    Click here for additional data file. (929.4KB, tif)
    S6 Fig. Forest plot of studies showing studies with a high-quality score of 4 or better.

    (TIF)

    Click here for additional data file. (2.4MB, tif)
    S7 Fig. Forest plot of high-quality studies included only participants with type 2 diabetes.

    (TIF)

    Click here for additional data file. (1.7MB, tif)
    Attachment

    Submitted filename: Reviewer Response .docx

    Click here for additional data file. (33.1KB, docx)

    Data Availability Statement

    All data used in this manuscript has been included in this manuscript.

    Articles from PLOS Global Public Health are provided here courtesy of PLOS

    RESOURCES