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Meta-Analysis
. 2020 Jul 8;10(7):e036418.
doi: 10.1136/bmjopen-2019-036418.

Sex differences in the adherence of antihypertensive drugs: a systematic review with meta-analyses

Annalisa Biffi  1   2 , Federico Rea  3   2 , Teresa Iannaccone  2   4 , Amelia Filippelli  2   4 , Giuseppe Mancia  5   6 , Giovanni Corrao  3   2
Affiliations
Meta-Analysis

Sex differences in the adherence of antihypertensive drugs: a systematic review with meta-analyses

Annalisa Biffi et al. BMJ Open. .

Abstract

Objectives: Poor worldwide rate of blood pressure control is largely due to poor adherence to antihypertensive (AHT) drug treatment. The question of whether sex affects adherence has long been debated but conflicting findings have been reported on this issue. Our objective was to evaluate sex differences in the adherence to AHT therapy.

Research design and methods: Studies were identified through a systematic search of PubMed, CINAHL, PsycINFO, Web of Science and Google Scholar (through January 2020) and manual handsearching of relevant articles. Observational studies reporting adherence to AHT drugs measured by self-report or pharmacy refill prescription-based methods among men and women were included. Summarised estimates of ORs with 95% CIs were calculated using random-effects model and meta-regression models.

Results: From 12 849 potentially relevant publications, 82 studies (15 517 457 men and 18 537 599 women) were included. No significant between-sex differences in adherence to AHT were observed, whether all study-specific estimates were summarised (ORs 1.04, 95% CI 1.00 to 1.09, p=0.07), nor estimates were pooled according to the method for measuring adherence. Among patients aged 65 years or older, lower self-reported adherence was observed in women (ORs 0.84, 95% CI 0.72 to 0.97, p=0.02), while the main result remained unchanged according to other subgroup analyses.

Conclusions: Definitive evidence of sex differences in adherence to AHT therapy cannot be drawn. Our little knowledge about factors affecting adherence, in particular of sex effect among elderly, urgently requires high-quality studies investigating these issues.

Keywords: clinical pharmacology; epidemiology; hypertension.

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Conflict of interest statement

Competing interests: GC received research support from the European Community (EC), the Italian Agency of Drug (AIFA) and the Italian Ministry for University and Research (MIUR). He took part to a variety of projects that were funded by pharmaceutical companies (ie, Novartis, GSK, Roche, AMGEN and BMS). He also received honoraria as member of Advisory Board from Roche. GM has received honoraria for participation as speaker/chairman in national/international meetings from Bayer, Boehringer Ingelheim, CVRx, Daiichi Sankyo, Ferrer, Medtronic, Menarini Int., Merck, Novartis, Recordati and Servier.

Figures

Figure 1
Figure 1
Flow diagram of the selection of studies regarding self-reported and refill rates used to measure adherence to AHT. AHT, antihypertensive.
Figure 2
Figure 2
Forest plots of study-specific and summary relative risks for adherence to antihypertensive drugs in women compared with men obtained by the following measurements: PDC, MPR, 4-item and 8-item Morisky Medication Scale. Squares represent study-specific relative risk estimates (size of the square reflects the study-specific statistical weight, ie, the inverse of the variance); horizontal lines represent 95% CIs; diamonds represent summary relative risk estimates with corresponding 95% CIs; p values are from testing for heterogeneity between study-specific estimates. Different lengths of follow-up are shown for PDC and MPR measurements. MPR, medication possession ratio; PDC, proportion of days covered.
Figure 3
Figure 3
Forest plots of study-specific and summary relative risks for adherence to antihypertensive drugs in women compared with men obtained by MPR and PDC measurements together and Morisky among the elderly population (ie, ≥65 years). Squares represent study-specific relative risk estimates (size of the square reflects the study-specific statistical weight, ie, the inverse of the variance); horizontal lines represent 95% CIs; diamonds represent summary relative risk estimates with corresponding 95% CIs; p values are from testing for heterogeneity between study-specific estimates. Different lengths of follow-up are shown. MPR, Medication Possession Ratio; PDC, Proportion of Days Covered.
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