Dataset Information

Social determinants of pertussis and influenza vaccine uptake in pregnancy: a national cohort study in England using electronic health records.

ABSTRACT:

Objective

To examine the social determinants of influenza and pertussis vaccine uptake among pregnant women in England.

Design

Nationwide population-based cohort study.

Setting

The study used anonymised primary care data from the Clinical Practice Research Datalink and linked Hospital Episode Statistics secondary care data.

Participants

Pregnant women eligible for pertussis (2012-2015, n=68 090) or influenza (2010/2011-2015/2016, n=152 132) vaccination in England.

Main outcome measures

Influenza and pertussis vaccine uptake.

Results

Vaccine uptake was 67.3% for pertussis and 39.1% for influenza. Uptake of both vaccines varied by region, with the lowest uptakes in London and the North East. Lower vaccine uptake was associated with greater deprivation: almost 10% lower in the most deprived quintiles compared with the least deprived for influenza (34.5% vs 44.0%), and almost 20% lower for pertussis (57.7% vs 76.0%). Lower uptake for both vaccines was also associated with non-white ethnicity (lowest among women of black ethnicity), maternal age under 20 years and a greater number of children in the household. The associations between all social factors and vaccine uptake were broadly unchanged in fully adjusted models, suggesting the social determinants of uptake were largely independent of one another. Among 3111 women vaccinated against pertussis in their first eligible pregnancy and pregnant again, 1234 (40%) were not vaccinated in their second eligible pregnancy.

Conclusions

Targeting promotional campaigns to pregnant women who are younger, of non-white ethnicity, with more children, living in areas of greater deprivation or the London or North East regions, has potential to reduce vaccine-preventable disease among infants and pregnant women, and to reduce health inequalities. Vaccination promotion needs to be sustained across successive pregnancies. Further research is needed into whether the effectiveness of vaccine promotion strategies may vary according to social factors.

SUBMITTER: Walker JL

PROVIDER: S-EPMC8217954 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundAlthough vaccination of pregnant women against influenza is recommended, the vaccination rate remains low. We conducted a study to identify determinants of influenza vaccination uptake in pregnancy in order to identify strategies to improve seasonal influenza vaccination rates.MethodsProspective observational hospital-based study in the French hospital performing the highest number of deliveries, located in the city of Lille, among all women who had given birth during the 2014-2015 influenza season. Data were collected through a self-completed questionnaire and from medical files. The vaccination uptake was self-reported. Determinants of vaccination uptake were identified using logistic regression analysis.ResultsOf the 2045 women included in the study, 35.5% reported that they had been vaccinated against influenza during their pregnancy. The principal factors significantly associated with greater vaccination uptake were previous influenza vaccination (50.9% vs 20.2%, OR 4.1, 95% CI 3.1-5.5), nulliparity (41.0% vs 31.3%, OR 2.5, 95% CI 1.7-3.7), history of preterm delivery < 34 weeks (43.4% vs 30.3%, OR 2.3, 95% CI 1.1-4.9), the mother's perception that the frequency of vaccine complications for babies is very low (54.6% vs 20.6%, OR 1.1, 95% CI 0.5-2.2), the mother's good knowledge of influenza and its vaccine (61.7% vs 24.4%, OR 3.1, 95% CI 2.2-4.4), hospital-based prenatal care in their first trimester of pregnancy (55.0% vs 30.2%, OR 2.1, 95% CI 1.2-3.7), vaccination recommendations during pregnancy by a healthcare worker (47.0% vs 2.7%, OR 18.8, 95% CI 10.0-35.8), receipt of a vaccine reimbursement form (52.4% vs 18.6%, OR 2.0, 95% CI 1.5-2.7), and information from at least one healthcare worker about the vaccine (43.8% vs 19.1%, OR 1.8, 95% CI 1.3-2.6).ConclusionsOur findings suggest that in order to increase flu vaccination compliance among pregnant women, future public health programmes must ensure cost-free access to vaccination, and incorporate education about the risks of influenza and the efficacy/safety of vaccination and clear recommendations from healthcare professionals into routine antenatal care.

Project description:ObjectivePreventing suicide in US youth is of paramount concern, with rates increasing over 50% between 2007 and 2018. Statistical modeling using electronic health records may help identify at-risk youth before a suicide attempt. While electronic health records contain diagnostic information, which are known risk factors, they generally lack or poorly document social determinants (e.g., social support), which are also known risk factors. If statistical models are built incorporating not only diagnostic records, but also social determinants measures, additional at-risk youth may be identified before a suicide attempt.MethodsSuicide attempts were predicted in hospitalized patients, ages 10-24, from the State of Connecticut's Hospital Inpatient Discharge Database (HIDD; N = 38943). Predictors included demographic information, diagnosis codes, and using a data fusion framework, social determinants features transferred or fused from an external source of survey data, The National Longitudinal Study of Adolescent to Adult Health (Add Health). Social determinant information for each HIDD patient was generated by averaging values from their most similar Add Health individuals (e.g., top 10), based upon matching shared features between datasets (e.g., Pearson's r). Attempts were then modelled using an elastic net logistic regression with both HIDD features and fused Add Health features.ResultsThe model including fused social determinants outperformed the conventional model (AUC = 0.83 v. 0.82). Sensitivity and positive predictive values at 90 and 95% specificity were almost 10% higher when including fused features (e.g., sensitivity at 90% specificity = 0.48 v. 0.44). Among social determinants variables, the perception that their mother cares and being non-religious appeared particularly important to performance improvement.DiscussionThis proof-of-concept study showed that incorporating social determinants measures from an external survey database could improve prediction of youth suicide risk from clinical data using a data fusion framework. While social determinant data directly from patients might be ideal, estimating these characteristics via data fusion avoids the task of data collection, which is generally time-consuming, expensive, and suffers from non-compliance.

Project description:BackgroundIn England, almost all general practices (GPs) have implemented GP online services such as electronic personal health records (ePHRs) that allow people to schedule appointments, request repeat prescriptions, and access parts of their medical records. The overall adoption rate of GP online services has been low, reaching just 28% in October 2019. In a previous study, Abd-Alrazaq et al adopted a model to assess the factors that influence patients' use of GP online services in England. According to the previous literature, the predictive power of the Abd-Alrazaq model could be improved by proposing new associations between the existing variables in the model.ObjectiveThis study aims to improve the predictive power of the Abd-Alrazaq model by proposing new relationships between the existing variables in the model.MethodsThe Abd-Alrazaq model was amended by proposing new direct, mediating, moderating, and moderated mediating effects. The amended model was examined using data from a previous study, which were collected by a cross-sectional survey of a convenience sample of 4 GPs in West Yorkshire, England. Structural equation modeling was used to examine the theoretical model and hypotheses.ResultsThe new model accounted for 53% of the variance in performance expectancy (PE), 76% of the variance in behavioral intention (BI), and 49% of the variance in use behavior (UB). In addition to the significant associations found in the previous study, this study found that social influence (SI) and facilitating conditions (FCs) are associated with PE directly and BI indirectly through PE. The association between BI and UB was stronger for younger women with higher levels of education, income, and internet access. The indirect effects of effort expectancy (EE), perceived privacy and security (PPS), and SI on BI were statistically stronger for women without internet access, patients with internet access, and patients without internet access, respectively. The indirect effect of PPS on BI was stronger for patients with college education or diploma than for those with secondary school education and lower, whereas the indirect effect of EE on BI was stronger for patients with secondary school education or lower than for those with college education or a diploma.ConclusionsThe predictive power of the Abd-Alrazaq model improved by virtue of new significant associations that were not examined before in the context of ePHRs. Further studies are required to validate the new model in different contexts and to improve its predictive power by proposing new variables. The influential factors found in this study should be considered to improve patients' use of ePHRs.