| Literature DB >> 35340367 |
Koussoh Simone Malik1, Kassi Anicet Adoubi2, Jérôme Kouame3, Madikiny Coulibaly1, Marie-Laure Tiade3, Serge Oga3, Michèle Ake1, Odile Ake1, Luc Kouadio3.
Abstract
Background: Hypertension is one of the major factors for high mortality of adults in Africa. However, complications occur at lower values than those previously classified as hypertension. Thus, prehypertension is considered as a new category of hypertension and a major risk factor for developing clinical hypertension relative to those with normotension, it has been linked with increased future risk of hypertension as well as cardiovascular diseases.Entities:
Mesh:
Year: 2022 PMID: 35340367 PMCID: PMC8896244 DOI: 10.5334/aogh.2769
Source DB: PubMed Journal: Ann Glob Health ISSN: 2214-9996 Impact factor: 2.462
Figure 1Flow diagram of the study selection process.
Articles characteristics.
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| AUTHORS | POPULATION AGE (YEARS) | PREVALENCE OF PREHTN | SAMPLE SIZE | RISKS FACTORS | STUDY COUNTRY |
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| Redjala et al. 2021 [ | 6–18 | 10.0¨% | 3562 | – overweight/obesity | Algiers |
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| Ongosi et al. 2020 [ | 25–64 | Male: 49.0% | 593 | – men | Kenya |
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| Sungwa et al. 2020 [ | 6–16 | 9.6% | 742 | – women | Tanzania |
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| Umuerri et Aiwuyo 2020 [ | ≥18 | 42.5% | 852 | – age | Nigeria |
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| Katamba et al. 2020 [ | 12–19 | 7.1% | 616 | Not evaluated | Uganda |
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| Owiredu et al. 2019 [ | ≥25 | 49.0% | 204 | – having lower level of education | Ghana |
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| Nsanya et al. 2019 [ | 12–24 | 29% | 1596 | – men | Tanzania and Uganda |
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| Muhihi et al. 2018 [ | 6–17 | 4.4% | 446 | – overweight/obesity | Tanzania |
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| Osei-Yeboah et al. 2018 [ | 22–59 | 52.68% | 112 | Not evaluated | Ghana |
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| Bhimma et al. 2018 [ | 16.2–21.7 | 29.7% | 575 | – overweight/obesity | South Africa |
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| Msemo et al. 2018 [ | 18–40 | 37.2% | 1247 | – increasing age, | Tanzania |
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| Ezeudu et al. 2018 [ | 10–19 | 5.0% | 984 | – overweight/obesity | Nigeria |
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| Okpokowuruk et al. 2017 [ | 3–17 | 2.5% | 200 | – age | Nigeria |
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| Mosha et al. 2017 [ | ≥15 | 36.2% | 9678 | – level of education | Tanzania |
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| Nwatu et al. 2017 [ | ≥18 | 34.8% | 834 | – sex: male | Nigeria |
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| Muchanga et al. 2016 [ | 40–60 | 38.5 % | 200 | – menopause | Congo |
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| Ezekwesili et al. 2016 [ | 17–79 | 42.54% | 912 | Not evaluated | Nigeria |
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| Guwatudde et al. 2015 [ | ≥ 18 | 36.9%. | 3906 | – Male gender | Uganda |
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| Nkeh-Chungag et al. 2015 [ | 13–17 | 12.3% | 388 | Not evaluated | South Africa |
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| Abdissa et al. 2015 [ | ≥ 18 | 47.3% | 2716 | Not evaluated | Ethiopia |
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| Ellenga Mbolla et al. 2014 [ | 5–18 | 20.7% | 603 | – overweight/obesity | Congo |
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| Ale et al. 2014 [ | 26–86 | 43.56% | 101 | – higher left ventricular mass | Nigeria |
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| Mehdad Silmane et al. 2013 [ | 11–17 | 9.6% | 167 | – overweight/obesity | Morocco |
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| Tayel et al. 2013 [ | 12–18 | 34% | – overweight/obesity | Egypt | |
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| Nuwaha et Musinguzi 2013 [ | ≥18 | 33.9% | 4142 | – overweight/obesuty | Uganda |
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| Ujunwa et al. 2013 [ | 10–18 | 17.3% | 2694 | – female | Nigeria |
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| Allal-Elasmi et al. 2012 [ | 35–69 | Males: 56.8% Females: 43.1% | 2712 | – age | Tunisia |
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