Joint analysis of blood pressure changes over time and survival of hypertensive patients under treatment at Sawula hospital in Southern Ethiopia

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Abstract

Introduction

Hypertension is among the most significant non-communicable public health issues worldwide. High blood pressure, or hypertension, has been associated with severe health consequences, including death, aneurysms, stroke, chronic renal disease, eye damage, heart attack, heart failure, peripheral artery disease, and vascular dementia. Consequently, this study aimed to investigate the predictors linked to survival time and the progression of blood pressure measurements in hypertensive patients.

Methods

This study on retrospective cohort analysis was conducted among hypertensive patients receiving follow-up treatment. A total of 200 hypertensive patients were screened during their follow-up at Sawula General Hospital. Multivariate joint models typically combine a multivariate linear mixed-effects model for repeated measurements with a Cox model for time-to-event outcomes.

Result

The baseline characteristics of patients indicated that, out of 200 hypertensive patients, the majority were male, totaling 116 (58%). Regarding alcohol consumption, 72 (36%) of the hypertensive patients reported using alcohol, while 128 (64%) did not. The multivariate joint model emerged as the most effective model in this study. The analysis revealed that observation time, economic status, sex, place of residence, baseline FBS, and age significantly influenced log FBS, while visiting time, age, sex, pulse rate, place of residence, and baseline DBP were identified as significant factors for log diastolic blood pressure.

Conclusion

The multivariate joint model exhibited superior performance. Hypertension continues to be a non-communicable disease and a public health issue in Sawula and Ethiopia, deserving greater attention.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-024-21176-3.

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Most cited references 16

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Regression Models and Life-Tables

D R Cox (1972)

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Worldwide trends in hypertension prevalence and progress in treatment and control from 1990 to 2019: a pooled analysis of 1201 population-representative studies with 104 million participants

José Huerta (2022)

Summary Background Hypertension can be detected at the primary health-care level and low-cost treatments can effectively control hypertension. We aimed to measure the prevalence of hypertension and progress in its detection, treatment, and control from 1990 to 2019 for 200 countries and territories. Methods We used data from 1990 to 2019 on people aged 30–79 years from population-representative studies with measurement of blood pressure and data on blood pressure treatment. We defined hypertension as having systolic blood pressure 140 mm Hg or greater, diastolic blood pressure 90 mm Hg or greater, or taking medication for hypertension. We applied a Bayesian hierarchical model to estimate the prevalence of hypertension and the proportion of people with hypertension who had a previous diagnosis (detection), who were taking medication for hypertension (treatment), and whose hypertension was controlled to below 140/90 mm Hg (control). The model allowed for trends over time to be non-linear and to vary by age. Findings The number of people aged 30–79 years with hypertension doubled from 1990 to 2019, from 331 (95% credible interval 306–359) million women and 317 (292–344) million men in 1990 to 626 (584–668) million women and 652 (604–698) million men in 2019, despite stable global age-standardised prevalence. In 2019, age-standardised hypertension prevalence was lowest in Canada and Peru for both men and women; in Taiwan, South Korea, Japan, and some countries in western Europe including Switzerland, Spain, and the UK for women; and in several low-income and middle-income countries such as Eritrea, Bangladesh, Ethiopia, and Solomon Islands for men. Hypertension prevalence surpassed 50% for women in two countries and men in nine countries, in central and eastern Europe, central Asia, Oceania, and Latin America. Globally, 59% (55–62) of women and 49% (46–52) of men with hypertension reported a previous diagnosis of hypertension in 2019, and 47% (43–51) of women and 38% (35–41) of men were treated. Control rates among people with hypertension in 2019 were 23% (20–27) for women and 18% (16–21) for men. In 2019, treatment and control rates were highest in South Korea, Canada, and Iceland (treatment >70%; control >50%), followed by the USA, Costa Rica, Germany, Portugal, and Taiwan. Treatment rates were less than 25% for women and less than 20% for men in Nepal, Indonesia, and some countries in sub-Saharan Africa and Oceania. Control rates were below 10% for women and men in these countries and for men in some countries in north Africa, central and south Asia, and eastern Europe. Treatment and control rates have improved in most countries since 1990, but we found little change in most countries in sub-Saharan Africa and Oceania. Improvements were largest in high-income countries, central Europe, and some upper-middle-income and recently high-income countries including Costa Rica, Taiwan, Kazakhstan, South Africa, Brazil, Chile, Turkey, and Iran. Interpretation Improvements in the detection, treatment, and control of hypertension have varied substantially across countries, with some middle-income countries now outperforming most high-income nations. The dual approach of reducing hypertension prevalence through primary prevention and enhancing its treatment and control is achievable not only in high-income countries but also in low-income and middle-income settings. Funding WHO.

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Basic concepts and methods for joint models of longitudinal and survival data.

Haitao Chu, Joseph Ibrahim, L. Chen (2010)

Joint models for longitudinal and survival data are particularly relevant to many cancer clinical trials and observational studies in which longitudinal biomarkers (eg, circulating tumor cells, immune response to a vaccine, and quality-of-life measurements) may be highly associated with time to event, such as relapse-free survival or overall survival. In this article, we give an introductory overview on joint modeling and present a general discussion of a broad range of issues that arise in the design and analysis of clinical trials using joint models. To demonstrate our points throughout, we present an analysis from the Eastern Cooperative Oncology Group trial E1193, as well as examine some operating characteristics of joint models through simulation studies.

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Author and article information

Contributors

Galgalo Jaba Nura: galgalojaba20@gmail.com , galgalojaba19@gmail.com

Journal

Journal ID (nlm-ta): BMC Public Health

Journal ID (iso-abbrev): BMC Public Health

Title: BMC Public Health

Publisher: BioMed Central (London )

ISSN (Electronic): 1471-2458

Publication date (Electronic): 3 January 2025

Publication date PMC-release: 3 January 2025

Publication date Collection: 2025

Volume: 25

Electronic Location Identifier: 23

Affiliations

[1 ]Department of Statistics, Arba Minch University, ( https://ror.org/00ssp9h11) Arba Minch, Ethiopia

[2 ]Department of Statistics, Borana University, Borena, Oromia Region Ethiopia

Article

Publisher ID: 21176

DOI: 10.1186/s12889-024-21176-3

PMC ID: 11697462

PubMed ID: 39754151

SO-VID: 8ccf0f83-4caf-4852-b475-0a3a1a37adfd

License:

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

History

Date received : 21 August 2024

Date accepted : 20 December 2024

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ScienceOpen disciplines: Public health

Keywords: cox ph,hypertensive,longitudinal measurement,joint model

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ScienceOpen disciplines: Public health

Keywords: cox ph, hypertensive, longitudinal measurement, joint model

Joint analysis of blood pressure changes over time and survival of hypertensive patients under treatment at Sawula hospital in Southern Ethiopia

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Abstract

Introduction

Methods

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Conclusion

Supplementary Information

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Most cited references 16

Regression Models and Life-Tables

Worldwide trends in hypertension prevalence and progress in treatment and control from 1990 to 2019: a pooled analysis of 1201 population-representative studies with 104 million participants

Basic concepts and methods for joint models of longitudinal and survival data.

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