Physical inactivity and its association with hypertension among adults in Ethiopia: A systematic review and meta-analysis

Muche, Temesgen; Sisay, Daniel; Mekuriaw, Birhanie; Kabthymer, Robel Hussen

doi:10.1016/j.heliyon.2022.e12023

Cited by 1 publication

(1 citation statement)

References 34 publications

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“…On the other hand, previous studies have shown that both short and long sleep durations are related to an increased risk of hypertension in most age groups (30,31). Ewunieet alconcluded that sedentary adults are 2.55 times more likely to suffer from hypertension than physically active adults (32). According toWenzhen Li et al,the combined effect of low physical activity and high BMI is associated with the highest risk of hypertension (33).…”

Section: Discussionmentioning

confidence: 99%

Lifestyle Subgroups and its Relationship with the Incidence of Hypertension in the Population of Azar Cohort: A Latent Class Analysis

Naghizadeh,

Faramarzi,

Sarbakhsh

et al. 2023

Preprint

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Background: Hypertension represents a global public health challenge due to its high prevalence and relationship with cardiovascular diseases. Lifestyle-related high-risk behaviors are the leading causes of hypertension, usually occurring simultaneously or in clusters. While prior studies have examined lifestyle variables separately, behaviors related to lifestyle often coincide in specific patterns. Using Latent Class Analysis (LCA), we can simultaneously analyze the effects of variables related to lifestyle on the incidence of hypertension. The aim of present studt was to compare the incidence of hypertension across different lifestyle subgroups of the Azar cohort population identified via LCA. Methods: In the present study, we used the data of 15,006 eligible participants across five follow-up periods. Seven observed variables were used to assess lifestyle behaviors as a latent variable. These indicators were smoking, substance use, alcohol consumption, secondhand smoke exposure, sleep quality, physical activity, and obesity. The analysis was performed using PROC LCA in SAS 9.2 software. Results: Three-class and seven-class models were appropriate for females and males based on the indices for model selection and the interpretability of the model results, respectively. In females, 25.7%, 9% and 65.3% were at “low risk”,“high risk” and “secondhand smoke exposure and poor sleep quality”, respectively. In males, 13.3% and 3.6% were in the “smoker” and “high-risk” classes, respectively. In females and males (up to class 4), after adjusting for age and socioeconomic status, the prevalence and incidence of hypertension increased with the advancement of classes. Conclusion: This study provides important information on lifestyle intervention strategies to minimize the burden of hypertension. Identifying concurrent high-risk behaviors in an at-risk population can lead to simultaneous interventions as an effective means of preventing disease by addressing clusters of high-risk behaviors. Considering the characteristics of the identified classes and the prevalence and occurrence of hypertension in each class, the main focus of lifestyle interventions can be placed on the most high-risk groups. Our findings suggest that poor physical activity, poor sleep quality, and obesity should be adressed as the main targets of lifestyle intervention strategies for preventing and controlling hypertension.

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