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      Patient and practice level factors associated with seasonal influenza vaccine uptake among at-risk adults in England, 2011 to 2016: An age-stratified retrospective cohort study

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          Highlights

          • Disparities in uptake by ethnicity, varying by age, were evident.

          • Older adults with higher socioeconomic deprivation were less likely to be vaccinated.

          • Patients with morbid obesity had the lowest odds of being vaccinated.

          • Patients who had more annual GP consultations were more likely to be vaccinated.

          Abstract

          We sought to gain insights into the determinants of seasonal influenza vaccine (SIV) uptake by conducting an age-stratified analysis (18–64 and 65+) of factors associated with SIV uptake among at-risk adults registered to English practices. Records for at-risk English adults between 2011 and 2016 were identified using the Clinical Practice Research Datalink database. SIV uptake was assessed annually. The associations of patient, practice, and seasonal characteristics with SIV uptake were assessed via cross-sectional and longitudinal analyses, using mixed-effects and general estimating equation logistic regression models. Overall SIV uptake was 35.3% and 74.0% for adults 18–64 and 65+, respectively. Relative to white patients, black patients were least likely to be vaccinated (OR 18-64: 0.82 (95% CI: 0.80, 0.85); OR 65+: 0.59 (95% CI: 0.56, 0.62)), while Asian patients among 18–64 year olds were most likely to be vaccinated (OR 18-64: 1.10 (95% CI: 1.07, 1.13)). Females were more likely than males to be vaccinated among 18–64 year olds (OR 18-64: 1.19 (95% CI: 1.18, 1.20)). Greater socioeconomic deprivation was associated with decreased odds of uptake among older patients (OR 65+: 0.74 (95% CI: 0.71, 0.77)). For each additional at-risk condition, odds of uptake increased (OR 18-64: 2.33 (95% CI: 2.31, 2.36); OR 65+: 1.39 (95% CI: 1.38, 1.39)). Odds of uptake were highest among younger patients with diabetes (OR 18-64: 4.25 (95% CI: 4.18, 4.32)) and older patients with chronic respiratory disease (OR 65+: 1.60 (95% CI: 1.58, 1.63)), whereas they were lowest among morbidly obese patients of all ages (OR 18-64: 0.68 (95% CI: 0.67, 0.70); OR 65+: 0.97 (95% CI: 0.94, 0.99)). Prior influenza season severity and vaccine effectiveness were marginally predictive of uptake. Our age-stratified analysis uncovered SIV uptake disparities by ethnicity, sex, age, socioeconomic deprivation, and co-morbidities, warranting further attention by GPs and policymakers alike.

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          Most cited references21

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          The 5As: A practical taxonomy for the determinants of vaccine uptake.

          Suboptimal vaccine uptake in both childhood and adult immunisation programs limits their full potential impact on global health. A recent progress review of the Global Vaccine Action Plan stated that "countries should urgently identify barriers and bottlenecks and implement targeted approaches to increase and sustain coverage". However, vaccination coverage may be determined by a complex mix of demographic, structural, social and behavioral factors. To develop a practical taxonomy to organise the myriad possible root causes of a gap in vaccination coverage rates, we performed a narrative review of the literature and tested whether all non-socio-demographic determinants of coverage could be organised into 4 dimensions: Access, Affordability, Awareness and Acceptance. Forty-three studies were reviewed, from which we identified 23 primary determinants of vaccination uptake. We identified a fifth domain, Activation, which captured interventions such as SMS reminders which effectively nudge people towards getting vaccinated. The 5As taxonomy captured all identified determinants of vaccine uptake. This intuitive taxonomy has already facilitated mutual understanding of the primary determinants of suboptimal coverage within inter-sectorial working groups, a first step towards them developing targeted and effective solutions.
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            Keep Calm and Learn Multilevel Logistic Modeling: A Simplified Three-Step Procedure Using Stata, R, Mplus, and SPSS

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              Recall bias in epidemiologic studies.

              S Coughlin (1990)
              The factors which contribute to bias due to differential recall between cases and controls in retrospective studies have been little studied. A review of the literature on recall accuracy suggests that the extent of inaccurate recall is related to characteristics of the exposure of interest and of the respondents, though a distinction must be drawn between recall which is biased and that which is simply inaccurate. Interviewing technique and the study protocol, including the design of questionnaires and the motivation of respondents, play a central role and are under the control of the investigator. The results of validation studies carried out to date suggest that the likelihood of recall bias may be greater when recall is poor in general.
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                Author and article information

                Contributors
                Journal
                Vaccine X
                Vaccine X
                Vaccine: X
                Elsevier
                2590-1362
                13 January 2020
                09 April 2020
                13 January 2020
                : 4
                : 100054
                Affiliations
                [a ]Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College St, Toronto, ON M5S 3M2, Canada
                [b ]College of Pharmacy, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3E 0T5, Canada
                [c ]Vaccine and Drug Evaluation Centre, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3E 0T5, Canada
                [d ]Vaccine Epidemiology and Modeling, Sanofi Pasteur, 1 Discovery Dr, Swiftwater, PA 18370, United States
                [e ]Department of Health Sciences, University Medical Center Groningen, University of Groningen, 9700 AB Groningen, the Netherlands
                [f ]ICES, 2075 Bayview Ave, Toronto, ON M4N 3M5, Canada
                [g ]Public Health Ontario, 480 University Ave #300, Toronto, ON M5G 1V2, Canada
                [h ]Dalla Lana School of Public Health, University of Toronto, 155 College St, Toronto, ON M5T 3M7, Canada
                [i ]Department of Family & Community Medicine, University of Toronto, 500 University Ave, Toronto, ON M5G 1V7, Canada
                [j ]University Health Network, 101 College St, Toronto, ON M5G 1L7, Canada
                [k ]Sanofi Pasteur, 410 Thames Valley Park Dr, Earley, Reading RG6 1RH, United Kingdom
                [l ]Department of Mathematics & Statistics, University of Guelph, 50 Stone Road East, Guelph, ON N1G 2W1, Canada
                [m ]Sanofi Pasteur, 14 Espace Henry Vallée, 69007 Lyon, France
                Author notes
                [* ]Corresponding author at: Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College Street, Room 601, Toronto, ON M5S 3M2, Canada. matt.loiacono@ 123456mail.utoronto.ca
                Article
                S2590-1362(20)30001-2 100054
                10.1016/j.jvacx.2020.100054
                7011080
                32072152
                dd905cda-ab0e-473d-a681-4d81cd89d7c3
                © 2020 The Author(s)

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 8 October 2019
                : 23 December 2019
                : 9 January 2020
                Categories
                Regular paper

                seasonal influenza vaccine,vaccine uptake,general practice,determinants,clinical practice research datalink,cprd, clinical practice research datalink,gp, general practitioner,imd, index of multiple deprivations,nhs, national health service,phe, public health england,ses, socioeconomic status,uk, united kingdom,ve, vaccine effectiveness,siv, season influenza vaccine,who, world health organization

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