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Determinants of Self-Care and Home-Based Management of Hypertension: An Integrative Review Cover

Determinants of Self-Care and Home-Based Management of Hypertension: An Integrative Review

Open Access
|Mar 2023

Figures & Tables

Figure 1

PRISMA flow diagram for selection of studies.

Table 1

Distribution of study characteristics.

AUTHORMAIN GOALSETTINGDESIGNSAMPLEDATA ANALYSIS
Maginga et al., 2015Determine factors associated with BP control among adults attending a hypertension clinicBugando Medical Centre, TanzaniaCross-sectional study300 hypertension patients, selected consecutivelyFisher’s exact, Wilcoxon rank-sum test, univariable and multivariable logistic regression
Berhe et al., 2017Examined determinants of achieving BP control and treatment intensification in patients with uncontrolled BPSix public hospitals, EthiopiaA retrospective cohort study897 adult ambulatory hypertension patientsDescriptive statistics and multivariable logistic regression
Labata et al., 2019Assessed predictors of self-care practices among hypertensive patientsJimma University Specialized Hospital, EthiopiaHospital-based cross-sectional study341 adult hypertensive patientsDescriptive statistics and multivariate logistics regression
Niriayo et al., 2019Assessed the rate of adherence to self-care behaviors and associated factors among hypertensive patientsAyder Comprehensive Specialized Hospital, EthiopiaCross-sectional study276 ambulatory hypertensive patientsUnivariable and binary logistic regression
Berhe et al., 2020Assessed the prevalence and factors associated with uncontrolled hypertension among adultsMekelle public hospitals, Tigray, EthiopiaHospital-based cross-sectional study396 hypertensive patients, systematic random samplingBivariable and multivariable logistic regression
Gebremichael et al., 2019Assessed self-care practices and associated factors among hypertensive patientsAyder Comprehensive Specialized Hospital, EthiopiaHospital-based cross-sectional study320 hypertension patients, simple random samplingDescriptive statistics, logistics, and multivariate regression
Okai et al., 2020Assessed the patient-level factors that influence hypertension controlTwo hospitals in Accra, GhanaCross-sectional study360 hypertensive patientsChi-square tests and logistic regression
Herskind et al., 2019Assessed an initiative conducted by two health clinics to begin treatment of hypertension among patientsTwo clinics, Sierra LeoneRetrospective chart review and survey487 records of patients and 68 hypertension patients’ convenience sampleDescriptive statistics
Adidja et al., 2018Determine the rate and factors associated with nonadherence to antihypertensive pharmacotherapy, the association between nonadherence and BP controlBuea Health District, CameroonCommunity-based cross-sectional study183 adults, stratified cluster samplingDescriptive, chi-square, Fisher’s exact test, t-test, multivariable logistic regression
Gebrezgi et al., 2017Identified barriers and facilitated hypertension management from the perspective of the patientsAsmara, EritreaQualitative study48 individual in-depth interviews and 2 FGDThematic analysis
Ware et al., 2019Investigated traditional risk factors alongside other health and sociodemographic indicators to determine predictors of hypertension prevalence and managementSouth AfricaCross-sectional of a nationally representative cohortWHO-SAGE South Africa Wave 1 recruited 4,223 respondents from selected probability sampledChi-square, Mann-Whitney U test, t-tests, logistic regression
Mohamed et al., 2018Estimated the prevalence of hypertension, awareness, treatment, and controlKenyaA national cross-sectional household survey study4,485 data from the 2015 Kenya STEPs survey, randomly selectedDescriptive statistics, multiple logistic regression, bivariate logistic regression
Adeniyi et al., 2016Examined the sociodemographic and clinical determinants of uncontrolled hypertension among individuals living with T2DM in the rural communitiesMthatha, South Africa.Cross-sectional study265 individuals living with T2DM and hypertensionUnivariate and multivariate logistic regression

[i] Legends: BP = blood pressure; FGD = focus group discussion; T2DM = type 2 diabetes mellitus.

Table 2

Distribution of key findings.

AUTHOROUTCOME AND MEASUREMENTKEY DETERMINANTS OF HYPERTENSION CONTROLKEY FINDINGS
Maginga et al., 2015
  • Medication adherence: MMAS-4

  • Knowledge: Self-developed pretested questionnaire

  • Good knowledge (OR = 2.50, 95% CI, 1.00–6.10, p = 0.047)

  • Attitudes (OR = 2.70, 95% CI, 1.00–7.10, p = 0.004)

  • Practices (OR = 5.40, 95% CI, 2.30–13.0, p < 0.001)

  • Patients (47.7%) had controlled hypertension.

  • Obesity and higher medication costs were associated with decreased control.

  • There was high adherence (56.0%) to medication.

  • Participants had moderate scores for knowledge (41.0%), attitudes (45.3%), and practices (49.3%).

Berhe et al., 2017
  • Medication adherence: MMAS

  • Other determinants: Self-developed questionnaire

  • Treatment at general hospitals (OR = 1.89, 95% CI 1.26–2.83)

  • Previously uncontrolled BP (OR = 0.30, 95% CI 0.21–0.43)

  • Treatment regimens with diuretics (OR = 0.68, 95% CI 0.50–0.94)

  • Age (OR = 0.99, 95% CI = 0.98–1.00)

  • BP was controlled in 37.0%, and treatment was intensified for 23.0% of patients with uncontrolled BP.

  • The antihypertensive medication adherence rate (MMAS ≥ 7) was 40.0% and 57.0% for the lower cutoff (MMAS ≥ 6).

Labata et al., 2019
  • Hypertension self-care practices: Adapted H-SCALE questionnaire

  • Normal weight (AOR = 1.82, 95% CI = 1.07–3.09) a predictor of medication usage

  • Good self-efficacy (AOR = 2.58, 95% CI 1.47–0.52) a predictor of a low-salt diet

  • Female predictor physical activity (AOR = 0.51, 95% CI 0.30–0.88) and nonsmoking (AOR = 3.62, 95% CI 1.21–10.85)

  • 61.9%, 30.5%, 44.9%, 88.3%, 93.5%, and 56.9% were adherent to medication, low-salt diet, physical activity, alcohol abstinence, nonsmoking, and weight management, respectively.

  • Adequate knowledge of hypertension was 2.58 times more likely, and females were less likely to adhere to physical activity.

Niriayo et al., 2019
  • Self-care behaviors: H-SCALE

  • Beliefs about medication: Belief about medicine questionnaire (BMQ)

  • Rural resident (AOR = 0.45, 95% CI: 0.21–0.97)

  • Comorbidity (AOR = 0.16, 95% CI 0.08–0.31)

  • Negative medication belief (AOR = 0.25, 95% CI 0.14–0.46)

  • Antihypertensive medications adherent (48.2%) and recommended physical activity (44.9%)

  • Female (AOR = 1.97, 95% CI 1.03–3.75) and lack of knowledge on self-care (AOR = 0.07, 95% CI 0.03–0.16) were associated with alcohol abstinence and a low-salt diet.

Berhe et al., 2020
  • Adherence to self-care activities: H-SCALE

  • Age ≥ 50 years (AOR = 2.33, 95% CI 1.25, 4.35)

  • Nonadherence to antihypertensive medication (AOR = 1.82, 95% CI 1.08–3.04)

  • Nonadherence to physical exercise (AOR = 1.79, 95% CI 1.13–2.83)

  • Nonadherence to low-salt diet (AOR = 1.98, 95% CI 1.18–3.31)

  • Nonadherence to weight management (AOR = 2.06, 95% CI 1.31–3.23)

  • Prevalence of uncontrolled hypertension was found to be 48.6%.

  • 26.1%, 59.1%, 73.9%, and 38.6% of hypertensive patients were nonadherent to medication, physical exercise, low-salt diet, and weight management, respectively.

Gebremichael et al., 2019
  • Self-care practice: H-SCALE

  • Knowledge: Hypertension evaluation of lifestyle and management (HELM) scale

  • Sex (AOR = 2.25, 95% CI 1.09–4.65)

  • Age (AOR = 3.26, 95% CI 1.03–10.35)

  • Educational status (AOR = 4.20, 95% CI 1.30–13.55)

  • Disease duration (AOR = 3.12, 95% CI 1.20–8.10)

  • BP status (AOR = 2.72, 95% CI 1.25–5.92)

  • Knowledge (AOR = 6.19, 95% CI 2.90–13.21)

  • Good self-care practice was only found among 20.3% of patients.

  • Adherence to not smoking, antihypertensive medication, alcohol abstinence, dietary management, physical exercise, and weight management was found to be 99.1%, 74.1%, 67.2%, 63.1%, 49.4%, and 40.6%, respectively.

Okai et al., 2020
  • Blood pressure control: Pretested self-developed questionnaire with expert opinion

  • Sex (AOR = 3.53, 95% CI 1.73–7.25)

  • Educational at junior high school (AOR = 3.52, 95% CI 1.72–7.22)

  • Senior and junior high school (AOR = 2.64, 95% CI 1.40–6.66 and AOR = 3.06, 95% CI 1.03–6.67)

  • Comorbidity (AOR = 2.41, 95% CI 1.32– 4.42)

  • Increased pill burden (AOR = 0.27, 95% CI 0.10–0.73)

  • Length of diagnosis of 2–5 years (AOR = 0.32, 95% CI 0.18–0.57)

  • No comorbidities (18.0%) had achieved hypertension control.

  • Dyslipidemia (8.9%) had controlled hypertension (p < 0.006).

  • Taking a higher number of antihypertensive pills per day was also associated with a reduced likelihood of attaining hypertension control.

  • Most patients reported forgetfulness, side effects of medication, and high pill burden as reasons for missing their medications.

Herskind et al., 2019
  • Medication adherence: Medication possession ratio

  • Patients were most likely to cite transportation (81.0%), financial burden (69.0%), and schedule conflicts with work or other prior commitments (25.0%) as barriers to care.

  • Forgetfulness (12.0%) and lack of symptoms (9.0%) were challenges that patients reported facing in attending follow-up appointments.

  • Home visits (13.0%), outreach (13.0%), and phone or mobile reminders (12.0%) were strategies to improve adherence.

Adidja et al., 2018
  • Medication adherence: MMAS

  • Forgetfulness (AOR = 7.90, 95% CI 3.00–20.80)

  • Multiple daily doses (AOR = 2.50, 95% CI 1.20–5.60)

  • Financial constraints (AOR = 2.80, 95% CI 1.10–6.90)

  • Adverse drug effects (AOR = 7.60, 95% CI 1.70–33.0)

  • Participants (67.7%) were nonadherent to medications.

  • BP was controlled in only 21.3% of participants and was better in those who were adherent to medication (47.5%, p < 0.010).

Gebrezgi et al., 2017
  • Facilitators and barriers to self-care: Self-developed interview guide and focus group discussion guide

  • Individual factors: economic barriers, stress, nonadherence to medications due to the use of traditional remedies, and difficulties and misconceptions about following physical activity guidelines influenced self-care.

  • Individual knowledge, family, and government support were important factors to the patient’s success in the personal hypertension management.

Ware et al., 2019
  • Predictors of hypertension prevalence and management: World Health Survey (WHS, 2002–2004; 70 countries)

  • Waist-to height ratio > 0.5 and diabetes comorbidity were the most significant predictors of hypertension presence, awareness, and treatment.

  • Women and individuals reporting lower salt use were more likely to be aware of and treated for hypertension.

  • Older age, larger waist-to-height ratio, lower levels of education, and diabetes comorbidity were also predictive of individuals with hypertension being aware of their status.

  • Older age, female sex, larger waist-to-height ratio, diabetes comorbidity, lower levels of education, and not adding salt to food at the table were predictive of current antihypertensive medication use.

Mohamed et al., 2018
  • World Health Organization’s STEPs survey methodology tool

  • Among those aware, only 26.9% were on treatment, and 51.7% among those on treatment had achieved blood pressure control.

  • Factors associated with hypertension were older age, higher BMI, and harmful use of alcohol.

  • The overall age-standardized prevalence for hypertension was 24.5%.

  • Only 15.6% were aware of their elevated blood pressure.

  • Factors associated with awareness were older age (p = 0.013) and being male (p < 0.001).

Adeniyi et al., 2016
  • Uncontrolled hypertension: Self-developed questionnaire

  • Unemployed status (p < 0.001)

  • Excessive alcohol intake (p = 0.007)

  • Consumption of a Western-type diet (p < 0.001)

  • Independent determinants of uncontrolled hypertension were unemployment, current excessive drinker of alcohol and adherence to Western-type diet.

[i] Legends: AOR = adjusted odds rations; BMI = body mass index; BMQ = belief about medicine questionnaire; CI = confidence interval; HELM = hypertension evaluation of lifestyle and management; MMAS = Morisky Medication Adherence Scale; WHS = World Health Survey.

DOI: https://doi.org/10.5334/gh.1190 | Journal eISSN: 2211-8179
Language: English
Submitted on: Jun 20, 2022
Accepted on: Feb 16, 2023
Published on: Mar 20, 2023
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2023 Kennedy Diema Konlan, Jinhee Shin, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.