Prevalence and predictive risk factors of hypertension in patients hospitalized in Kamenge Military hospital and Kamenge University teaching hospital in 2019: A fixed effect modelling study in Burundi
Hypertension is a major threat to public health globally. Especially in sub-Saharan African countries, this coexists with high burden of other infectious diseases, creating a complex public health situation which is difficult to address. Tackling this will require targeted public health intervention...
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| Veröffentlicht in: | PloS one 2021-12, Vol.16 (12), p.e0260225 |
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| creator | Iradukunda, Arnaud Odjidja, Emmanuel Nene Ndayishima, Stephane Karl Ngendakumana, Egide Ndayishimiye, Gabin Pacifique Sinarinzi, Darlene Izere, Cheilla Ntakaburimvo, Nestor Akimana, Arlene |
| description | Hypertension is a major threat to public health globally. Especially in sub-Saharan African countries, this coexists with high burden of other infectious diseases, creating a complex public health situation which is difficult to address. Tackling this will require targeted public health intervention based on evidence that well defines the at risk population. In this study, using retrospective data from two referral hospitals in Burundi, we model the risk factors of hypertension in Burundi.
Retrospective data of a sample of 353 randomly selected from a population of 4,380 patients admitted in 2019 in two referral hospitals in Burundi: Military and University teaching hospital of Kamenge. The predictive risk factors were carried out by fixed effect logistic regression. Model performance was assessed with Area under Curve (AUC) method. Model was internally validated using bootstrapping method with 2000 replications. Both data processing and data analysis were done using R software.
Overall, 16.7% of the patients were found to be hypertensive. This study didn't showed any significant difference of hypertension's prevalences among women (16%) and men (17.7%). After adjustment of the model for cofounding covariates, associated risk factors found were advanced age (40-59 years) and above 60 years, high education level, chronic kidney failure, high body mass index, familial history of hypertension. In absence of these highlighted risk factors, the risk of hypertension occurrence was about 2 per 1000 persons. This probability is more than 90% in patients with more than three risk factors.
The relatively high prevalence and associated risk factors of hypertension in Burundi raises a call for concern especially in this context where there exist an equally high burden of infectious diseases, other chronic diseases including chronic malnutrition. Targeting interventions based on these identified risk factors will allow judicious channel of resources and effective public health planning. |
| doi_str_mv | 10.1371/journal.pone.0260225 |
| format | Article |
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Retrospective data of a sample of 353 randomly selected from a population of 4,380 patients admitted in 2019 in two referral hospitals in Burundi: Military and University teaching hospital of Kamenge. The predictive risk factors were carried out by fixed effect logistic regression. Model performance was assessed with Area under Curve (AUC) method. Model was internally validated using bootstrapping method with 2000 replications. Both data processing and data analysis were done using R software.
Overall, 16.7% of the patients were found to be hypertensive. This study didn't showed any significant difference of hypertension's prevalences among women (16%) and men (17.7%). After adjustment of the model for cofounding covariates, associated risk factors found were advanced age (40-59 years) and above 60 years, high education level, chronic kidney failure, high body mass index, familial history of hypertension. In absence of these highlighted risk factors, the risk of hypertension occurrence was about 2 per 1000 persons. This probability is more than 90% in patients with more than three risk factors.
The relatively high prevalence and associated risk factors of hypertension in Burundi raises a call for concern especially in this context where there exist an equally high burden of infectious diseases, other chronic diseases including chronic malnutrition. Targeting interventions based on these identified risk factors will allow judicious channel of resources and effective public health planning.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0260225</identifier><identifier>PMID: 34898616</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adolescent ; Adult ; Age Factors ; Area Under Curve ; Biology and Life Sciences ; Blood pressure ; Body mass ; Body Mass Index ; Body size ; Burundi - epidemiology ; Data analysis ; Data processing ; Distribution ; Educational Status ; Female ; Health aspects ; Health planning ; Health promotion ; Health risks ; Heart ; Hemodialysis ; Hospital patients ; Hospitalization ; Hospitals ; Hospitals, Military ; Hospitals, Teaching ; Humans ; Hypertension ; Hypertension - diagnosis ; Hypertension - epidemiology ; Infectious diseases ; Internal medicine ; Logistic Models ; Male ; Malnutrition ; Medicine ; Medicine and Health Sciences ; Middle Aged ; Modelling ; Mortality ; Obesity ; Overweight ; Patients ; Population studies ; Prevalence ; Public health ; Regression models ; Renal failure ; Retrospective Studies ; Risk analysis ; Risk Factors ; ROC Curve ; Sample size ; Social Sciences ; Statistical analysis ; Statistics ; Teaching hospitals ; Veins & arteries ; Young Adult</subject><ispartof>PloS one, 2021-12, Vol.16 (12), p.e0260225</ispartof><rights>COPYRIGHT 2021 Public Library of Science</rights><rights>2021 Iradukunda et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2021 Iradukunda et al 2021 Iradukunda et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-c1f9cd18eddecae042b8091015993bf48c3b097e9a4031ff92e3e971835f09f03</citedby><cites>FETCH-LOGICAL-c692t-c1f9cd18eddecae042b8091015993bf48c3b097e9a4031ff92e3e971835f09f03</cites><orcidid>0000-0002-0995-800X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8668094/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8668094/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2095,2914,23846,27903,27904,53770,53772,79347,79348</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34898616$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Ilic, Irena</contributor><creatorcontrib>Iradukunda, Arnaud</creatorcontrib><creatorcontrib>Odjidja, Emmanuel Nene</creatorcontrib><creatorcontrib>Ndayishima, Stephane Karl</creatorcontrib><creatorcontrib>Ngendakumana, Egide</creatorcontrib><creatorcontrib>Ndayishimiye, Gabin Pacifique</creatorcontrib><creatorcontrib>Sinarinzi, Darlene</creatorcontrib><creatorcontrib>Izere, Cheilla</creatorcontrib><creatorcontrib>Ntakaburimvo, Nestor</creatorcontrib><creatorcontrib>Akimana, Arlene</creatorcontrib><title>Prevalence and predictive risk factors of hypertension in patients hospitalized in Kamenge Military hospital and Kamenge University teaching hospital in 2019: A fixed effect modelling study in Burundi</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Hypertension is a major threat to public health globally. Especially in sub-Saharan African countries, this coexists with high burden of other infectious diseases, creating a complex public health situation which is difficult to address. Tackling this will require targeted public health intervention based on evidence that well defines the at risk population. In this study, using retrospective data from two referral hospitals in Burundi, we model the risk factors of hypertension in Burundi.
Retrospective data of a sample of 353 randomly selected from a population of 4,380 patients admitted in 2019 in two referral hospitals in Burundi: Military and University teaching hospital of Kamenge. The predictive risk factors were carried out by fixed effect logistic regression. Model performance was assessed with Area under Curve (AUC) method. Model was internally validated using bootstrapping method with 2000 replications. Both data processing and data analysis were done using R software.
Overall, 16.7% of the patients were found to be hypertensive. This study didn't showed any significant difference of hypertension's prevalences among women (16%) and men (17.7%). After adjustment of the model for cofounding covariates, associated risk factors found were advanced age (40-59 years) and above 60 years, high education level, chronic kidney failure, high body mass index, familial history of hypertension. In absence of these highlighted risk factors, the risk of hypertension occurrence was about 2 per 1000 persons. This probability is more than 90% in patients with more than three risk factors.
The relatively high prevalence and associated risk factors of hypertension in Burundi raises a call for concern especially in this context where there exist an equally high burden of infectious diseases, other chronic diseases including chronic malnutrition. Targeting interventions based on these identified risk factors will allow judicious channel of resources and effective public health planning.</description><subject>Adolescent</subject><subject>Adult</subject><subject>Age Factors</subject><subject>Area Under Curve</subject><subject>Biology and Life Sciences</subject><subject>Blood pressure</subject><subject>Body mass</subject><subject>Body Mass Index</subject><subject>Body size</subject><subject>Burundi - epidemiology</subject><subject>Data analysis</subject><subject>Data processing</subject><subject>Distribution</subject><subject>Educational Status</subject><subject>Female</subject><subject>Health aspects</subject><subject>Health planning</subject><subject>Health promotion</subject><subject>Health risks</subject><subject>Heart</subject><subject>Hemodialysis</subject><subject>Hospital patients</subject><subject>Hospitalization</subject><subject>Hospitals</subject><subject>Hospitals, Military</subject><subject>Hospitals, Teaching</subject><subject>Humans</subject><subject>Hypertension</subject><subject>Hypertension - diagnosis</subject><subject>Hypertension - epidemiology</subject><subject>Infectious diseases</subject><subject>Internal medicine</subject><subject>Logistic Models</subject><subject>Male</subject><subject>Malnutrition</subject><subject>Medicine</subject><subject>Medicine and Health Sciences</subject><subject>Middle Aged</subject><subject>Modelling</subject><subject>Mortality</subject><subject>Obesity</subject><subject>Overweight</subject><subject>Patients</subject><subject>Population studies</subject><subject>Prevalence</subject><subject>Public health</subject><subject>Regression models</subject><subject>Renal failure</subject><subject>Retrospective Studies</subject><subject>Risk analysis</subject><subject>Risk Factors</subject><subject>ROC Curve</subject><subject>Sample size</subject><subject>Social Sciences</subject><subject>Statistical analysis</subject><subject>Statistics</subject><subject>Teaching hospitals</subject><subject>Veins & arteries</subject><subject>Young 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Irena</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Prevalence and predictive risk factors of hypertension in patients hospitalized in Kamenge Military hospital and Kamenge University teaching hospital in 2019: A fixed effect modelling study in Burundi</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2021-12-13</date><risdate>2021</risdate><volume>16</volume><issue>12</issue><spage>e0260225</spage><pages>e0260225-</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Hypertension is a major threat to public health globally. Especially in sub-Saharan African countries, this coexists with high burden of other infectious diseases, creating a complex public health situation which is difficult to address. Tackling this will require targeted public health intervention based on evidence that well defines the at risk population. In this study, using retrospective data from two referral hospitals in Burundi, we model the risk factors of hypertension in Burundi.
Retrospective data of a sample of 353 randomly selected from a population of 4,380 patients admitted in 2019 in two referral hospitals in Burundi: Military and University teaching hospital of Kamenge. The predictive risk factors were carried out by fixed effect logistic regression. Model performance was assessed with Area under Curve (AUC) method. Model was internally validated using bootstrapping method with 2000 replications. Both data processing and data analysis were done using R software.
Overall, 16.7% of the patients were found to be hypertensive. This study didn't showed any significant difference of hypertension's prevalences among women (16%) and men (17.7%). After adjustment of the model for cofounding covariates, associated risk factors found were advanced age (40-59 years) and above 60 years, high education level, chronic kidney failure, high body mass index, familial history of hypertension. In absence of these highlighted risk factors, the risk of hypertension occurrence was about 2 per 1000 persons. This probability is more than 90% in patients with more than three risk factors.
The relatively high prevalence and associated risk factors of hypertension in Burundi raises a call for concern especially in this context where there exist an equally high burden of infectious diseases, other chronic diseases including chronic malnutrition. Targeting interventions based on these identified risk factors will allow judicious channel of resources and effective public health planning.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>34898616</pmid><doi>10.1371/journal.pone.0260225</doi><tpages>e0260225</tpages><orcidid>https://orcid.org/0000-0002-0995-800X</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2021-12, Vol.16 (12), p.e0260225 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_2609674627 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Public Library of Science (PLoS); PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Adolescent Adult Age Factors Area Under Curve Biology and Life Sciences Blood pressure Body mass Body Mass Index Body size Burundi - epidemiology Data analysis Data processing Distribution Educational Status Female Health aspects Health planning Health promotion Health risks Heart Hemodialysis Hospital patients Hospitalization Hospitals Hospitals, Military Hospitals, Teaching Humans Hypertension Hypertension - diagnosis Hypertension - epidemiology Infectious diseases Internal medicine Logistic Models Male Malnutrition Medicine Medicine and Health Sciences Middle Aged Modelling Mortality Obesity Overweight Patients Population studies Prevalence Public health Regression models Renal failure Retrospective Studies Risk analysis Risk Factors ROC Curve Sample size Social Sciences Statistical analysis Statistics Teaching hospitals Veins & arteries Young Adult |
| title | Prevalence and predictive risk factors of hypertension in patients hospitalized in Kamenge Military hospital and Kamenge University teaching hospital in 2019: A fixed effect modelling study in Burundi |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-21T16%3A34%3A25IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Prevalence%20and%20predictive%20risk%20factors%20of%20hypertension%20in%20patients%20hospitalized%20in%20Kamenge%20Military%20hospital%20and%20Kamenge%20University%20teaching%20hospital%20in%202019:%20A%20fixed%20effect%20modelling%20study%20in%20Burundi&rft.jtitle=PloS%20one&rft.au=Iradukunda,%20Arnaud&rft.date=2021-12-13&rft.volume=16&rft.issue=12&rft.spage=e0260225&rft.pages=e0260225-&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0260225&rft_dat=%3Cgale_plos_%3EA686608435%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2609674627&rft_id=info:pmid/34898616&rft_galeid=A686608435&rft_doaj_id=oai_doaj_org_article_f5fedca583f94afa93514e42a6fda335&rfr_iscdi=true |