Measuring inequalities in immunization in Wales and the impact of interventions.
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ABSTRACT:
SUBMITTER: Roberts RJ
PROVIDER: S-EPMC5085010 | biostudies-other | 2016 Oct
REPOSITORIES: biostudies-other
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Project description:BackgroundThroughout Wales and the world, health inequality remains a problem that is interconnected with a wider and complex social, economic and environmental dynamic. Subsequently, action to tackle inequality in health needs to take place at a structural level, acknowledging the constraints affecting an individual's (or community's) capability and opportunity to enable change. While the 'social determinants of health' is an established concept, fully understanding the composition of the health gap is dependent on capturing the relative contributions of a myriad of social, economic and environmental factors within a quantitative analysis.MethodThe decomposition analysis sought to explain the differences in the prevalence of these outcomes in groups stratified by their ability to save at least £10 a month, whether they were in material deprivation, and the presence of a limiting long-standing illness, disability of infirmity. Responses to over 4,200 questions within the National Survey for Wales (n = 46,189; 2016-17 to 2019-20) were considered for analysis. Variables were included based on (1) their alignment to a World Health Organization (WHO) health equity framework ("Health Equity Status Report initiative") and (2) their ability to allow for stratification of the survey sample into distinct groups where considerable gaps in health outcomes existed. A pooled Blinder-Oaxaca model was used to analyse inequalities in self-reported health (fair/poor health, low mental well-being and low life satisfaction) and were stratified by the variables relating to financial security, material deprivation and disability status.ResultsThe prevalence of fair/poor health was 75% higher in those who were financially insecure and 95% higher in those who are materially deprived. Decomposition of the outcome revealed that just under half of the health gap was "explained" i.e., 45.5% when stratifying by the respondent's ability to save and 46% when stratifying by material deprivation status. Further analysis of the explained component showed that "Social/Human Capital" and "Income Security/Social Protection" determinants accounted the most for disparities observed; it also showed that "Health Services" determinants accounted the least. These findings were consistent across the majority of scenarios modeled.ConclusionThe analysis not only quantified the significant health gaps that existed in the years leading up to the COVID-19 pandemic but it has also shown what determinants of health were most influential. Understanding the factors most closely associated with disparities in health is key in identifying policy levers to reduce health inequalities and improve the health and well-being across populations.
| S-EPMC9797964 | biostudies-literature
Project description:The Global Polio Eradication Initiative is closer than ever to achieving a polio-free world. Immunization activities must still be carried out in non-endemic countries to maintain population immunity at levels which will stop poliovirus from spreading if it is re-introduced from still-infected areas. In areas where there is no active transmission of poliovirus, programs must rely on surrogate indicators of population immunity to determine the appropriate immunization activities, typically caregiver-reported vaccination history obtained from non-polio acute flaccid paralysis patients identified through polio surveillance. We used regression models to examine the relationship between polio vaccination campaigns and caregiver-reported polio vaccination history. We find that in many countries, vaccination campaigns have a surprisingly weak impact on these commonly used indicators. We conclude that alternative criteria and data, such as routine immunization indicators from vaccination records or household surveys, should be considered for planning polio vaccination campaigns, and that validation of such surrogate indicators is necessary if they are to be used as the basis for program planning and risk assessment. We recommend that the GPEI and similar organizations consider or continue devoting additional resources to rigorously study population immunity and campaign effectiveness in at-risk countries.
| S-EPMC5104692 | biostudies-literature
Project description:We examined national trends and socioeconomic inequalities in cancer survival in England and Wales during the 1990s, using population-based data on 2.2 million patients who were diagnosed with one of the 20 most common cancers between 1986 and 1999 and followed up to 2001. Patients were assigned to one of five deprivation categories (from 'affluent' to 'deprived') using characteristics of their electoral ward of residence at diagnosis. We estimated relative survival up to 5 years after diagnosis, adjusting separately in each deprivation category for background mortality by age, sex and calendar period. We estimated trends in survival and in the difference in survival between deprivation categories ('deprivation gap') over the periods 1986-90, 1991-95 and 1996-99. We used period analysis to examine likely survival rates in the near future. Survival improved for most cancers in both sexes during the 1990s, and appears likely to continue improving for most cancers in the near future. The deprivation gap in survival between rich and poor was wider for patients diagnosed in the late 1990s than in the late 1980s. Increases in cancer survival in England and Wales during the 1990s are shown to be significantly associated with a widening deprivation gap in survival.
| S-EPMC2409687 | biostudies-other
Project description:BackgroundIncome inequalities in sports participation are shaped by a system in which individuals and the environment interact. We developed an agent-based model (ABM) that could represent this system and used it to provide a proof-of-concept of its potential to explore the impact of individual and environmental interventions on reducing inequalities in sports participation.MethodsOur ABM simulates sports participation of individuals in the Dutch city of Eindhoven. In the model, sports participation is determined by an individual's tendency to start sports (at a fitness center, sports club or self-organized), which is influenced by attributes of individuals (i.e. age, sex, income), sports facilities (i.e. price, accessibility) and the social environment (i.e. social cohesion, social influence). Sports facilities can adapt to changes in the demand by closures or startups, which in turn influence the tendency of individuals to participate in sport. We explored the impact of five interventions scenarios.ResultsExplorative results show that providing health education, increasing the availability of sports facilities, lowering prices of facilities and improving safety levels can increase sports participation and modestly reduce absolute income inequalities in sports participation. The largest gain can be attained through health education, if the effect and reach is sufficiently large. Environmental interventions alone have a modest impact. Marked effects are only achieved after five to 10 years.ConclusionsABMs have much potential to test the population-level effects of various interventions in the context of a system. Our study highlights the challenges of ABM development and reveals gaps in empirical data. With further refinements, our model could aid in understanding and finding optimal pathways to reduce income inequalities in sports participation.
| S-EPMC6211418 | biostudies-literature
Project description:BackgroundResponse to the early stages of the COVID-19 pandemic resulted in the temporary disruption of cancer screening in the UK, and strong public messaging to stay safe and to protect NHS capacity. Following reintroduction in services, we explored the impact on inequalities in uptake of the Bowel Screening Wales (BSW) programme to identify groups who may benefit from tailored interventions.MethodsRecords within the BSW were linked to electronic health records (EHR) and administrative data within the Secured Anonymised Information Linkage (SAIL) Databank. Ethnic group was obtained from a linked data method available within SAIL. We examined uptake for the first 3 months of invitations (August to October) following the reintroduction of BSW programme in 2020, compared to the same period in the preceding 3 years. Uptake was measured across a 6 month follow-up period. Logistic models were conducted to analyse variations in uptake by sex, age group, income deprivation quintile, urban/rural location, ethnic group, and clinically extremely vulnerable (CEV) status in each period; and to compare uptake within sociodemographic groups between different periods.ResultsUptake during August to October 2020 (period 2020/21; 60.4%) declined compared to the same period in 2019/20 (62.7%) but remained above the 60% Welsh standard. Variation by sex, age, income deprivation, and ethnic groups was observed in all periods studied. Compared to the pre-pandemic period in 2019/20, uptake declined for most demographic groups, except for older individuals (70-74 years) and those in the most income deprived group. Uptake continues to be lower in males, younger individuals, people living in the most income deprived areas and those of Asian and unknown ethnic backgrounds.ConclusionOur findings are encouraging with overall uptake achieving the 60% Welsh standard during the first three months after the programme restarted in 2020 despite the disruption. Inequalities did not worsen after the programme resumed activities but variations in CRC screening in Wales associated with sex, age, deprivation and ethnic group remain. This needs to be considered in targeting strategies to improve uptake and informed choice in CRC screening to avoid exacerbating disparities in CRC outcomes as screening services recover from the pandemic.
| S-EPMC10031708 | biostudies-literature
Project description:Cities are home to an increasing majority of the world's population. Currently, it is difficult to track social, economic, environmental and health outcomes in cities with high spatial and temporal resolution, needed to evaluate policies regarding urban inequalities. We applied a deep learning approach to street images for measuring spatial distributions of income, education, unemployment, housing, living environment, health and crime. Our model predicts different outcomes directly from raw images without extracting intermediate user-defined features. To evaluate the performance of the approach, we first trained neural networks on a subset of images from London using ground truth data at high spatial resolution from official statistics. We then compared how trained networks separated the best-off from worst-off deciles for different outcomes in images not used in training. The best performance was achieved for quality of the living environment and mean income. Allocation was least successful for crime and self-reported health (but not objectively measured health). We also evaluated how networks trained in London predict outcomes three other major cities in the UK: Birmingham, Manchester, and Leeds. The transferability analysis showed that networks trained in London, fine-tuned with only 1% of images in other cities, achieved performances similar to ones from trained on data from target cities themselves. Our findings demonstrate that street imagery has the potential complement traditional survey-based and administrative data sources for high-resolution urban surveillance to measure inequalities and monitor the impacts of policies that aim to address them.
| S-EPMC6473002 | biostudies-literature
Project description:BackgroundVaccination coverage is widely used to assess immunization performance but, on its own, provides insufficient information to drive improvements. Assessing the performance of underlying components of immunization systems is less clear, with several monitoring and evaluation (M&E) resources available for use in different operational settings and for different purposes. We studied these resources to understand how immunization system performance is measured.MethodsWe reviewed peer-reviewed and gray literature published since 2000 to identify M&E resources that include national-level indicators measuring the performance of immunization systems or their components (governance, financing, regulation, information systems, vaccine logistics, workforce, service delivery, and demand generation). We summarize indicators by the system components or outcomes measured and describe findings narratively.ResultsWe identified 20 resources to monitor immunization program objectives and guide national strategic decision-making, encompassing 631 distinct indicators. Indicators for immunization program outcomes comprised the majority (124/631 [19.7%]), largely vaccination coverage (110/124 [88.7%]). Almost all resources (19/20 [95%]) included indicators for vaccine logistics (83/631 [13.2%]), and those for regulation (19/631 [3.0%]) and demand generation (28/631 [4.4%]) were least common. There was heterogeneity in how information systems (92/563 [14.6%]) and workforce (47/631 [7.4%]) were assessed across resources. Indicators for vaccination coverage in adults, data use in decision-making, equity and diversity, effectiveness of safety surveillance, and availability of a public health workforce were notably lacking.ConclusionsBetween the resources identified in this review, we identified considerable variability and gaps in indicators assessing the performance of some immunization system components. Given the multitude of indicators, policymakers may be better served by tailoring evaluation resources to their specific context to gain useful insight into health system performance and improve data use in decision-making for immunization programs.
| S-EPMC10285727 | biostudies-literature
Project description:BackgroundTo plan for pensions and health and social services, future mortality and life expectancy need to be forecast. Consistent forecasts for all subnational units within a country are very rare. Our aim was to forecast mortality and life expectancy for England and Wales' districts.MethodsWe developed Bayesian spatiotemporal models for forecasting of age-specific mortality and life expectancy at a local, small-area level. The models included components that accounted for mortality in relation to age, birth cohort, time, and space. We used geocoded mortality and population data between 1981 and 2012 from the Office for National Statistics together with the model with the smallest error to forecast age-specific death rates and life expectancy to 2030 for 375 of England and Wales' 376 districts. We measured model performance by withholding recent data and comparing forecasts with this withheld data.FindingsLife expectancy at birth in England and Wales was 79·5 years (95% credible interval 79·5-79·6) for men and 83·3 years (83·3-83·4) for women in 2012. District life expectancies ranged between 75·2 years (74·9-75·6) and 83·4 years (82·1-84·8) for men and between 80·2 years (79·8-80·5) and 87·3 years (86·0-88·8) for women. Between 1981 and 2012, life expectancy increased by 8·2 years for men and 6·0 years for women, closing the female-male gap from 6·0 to 3·8 years. National life expectancy in 2030 is expected to reach 85·7 (84·2-87·4) years for men and 87·6 (86·7-88·9) years for women, further reducing the female advantage to 1·9 years. Life expectancy will reach or surpass 81·4 years for men and reach or surpass 84·5 years for women in every district by 2030. Longevity inequality across districts, measured as the difference between the 1st and 99th percentiles of district life expectancies, has risen since 1981, and is forecast to rise steadily to 8·3 years (6·8-9·7) for men and 8·3 years (7·1-9·4) for women by 2030.InterpretationPresent forecasts underestimate the expected rise in life expectancy, especially for men, and hence the need to provide improved health and social services and pensions for elderly people in England and Wales. Health and social policies are needed to curb widening life expectancy inequalities, help deprived districts catch up in longevity gains, and avoid a so-called grand divergence in health and longevity.FundingUK Medical Research Council and Public Health England.
| S-EPMC4502253 | biostudies-literature
Project description:BackgroundIn the United Kingdom, rates of childhood obesity are high and inequalities in obesity have widened in recent years. Children with obesity face heightened risks of living with obesity as adults and suffering from associated morbidities. Addressing population prevalence and inequalities in childhood obesity is a key priority for public health policymakers in the United Kingdom and elsewhere. Where randomized controlled trials are not possible, potential policy actions can be simulated using causal modeling techniques.ObjectivesUsing data from the Southampton Women's Survey (SWS), a cohort with high quality dietary and lifestyle data, the potential impact of policy-relevant calorie-reduction interventions on population prevalence and inequalities of childhood obesity was investigated.MethodsPredicted probabilities of obesity (using UK90 cut-offs) at age 6-7 years were estimated from logistic marginal structural models adjusting for observed calorie consumption at age 3 years (using food diaries) and confounding. A series of policy-relevant intervention scenarios were modeled to simulate reductions in energy intake (differing in effectiveness, the targeting mechanisms, and level of uptake).ResultsAt age 6-7 years, 8.3% of children were living with obesity, after accounting for observed energy intake and confounding. A universal intervention to lower median energy intake to the estimated average requirement (a 13% decrease), with an uptake of 75%, reduced obesity prevalence by 1% but relative and absolute inequalities remained broadly unchanged.ConclusionsSimulated interventions substantially reduced population prevalence of obesity, which may be useful in informing policymakers.
| S-EPMC8488449 | biostudies-literature
Project description:ObjectiveTo analyse subnational inequality in diphtheria-tetanus-pertussis (DTP) immunization dropout in 24 African countries using administrative data on receipt of the first and third vaccine doses (DTP1 and DTP3, respectively) collected by the Joint Reporting Process of the World Health Organization and the United Nations Children's Fund.MethodsDistricts in each country were grouped into quintiles according to the proportion of children who dropped out between DTP1 and DTP3 (i.e. the dropout rate). We used six summary measures to quantify inequalities in dropout rates between districts and compared rates with national dropout rates and DTP1 and DTP3 immunization coverage.FindingsThe median dropout rate across countries was 2.4% in quintiles with the lowest rate and 14.6% in quintiles with the highest rate. In eight countries, the difference between the highest and lowest quintiles was 14.9 percentage points or more. In most countries, underperforming districts in the quintile with the highest rate tended to lag disproportionately behind the others. This divergence was not evident from looking only at national dropout rates. Countries with the largest inequalities in absolute subnational dropout rate tended to have lower estimated national DTP1 and DTP3 immunization coverage.ConclusionThere were marked inequalities in DTP immunization dropout rates between districts in most countries studied. Monitoring dropout at the subnational level could help guide immunization interventions that address inequalities in underserved areas, thereby improving overall DTP3 coverage. The quality of administrative data should be improved to ensure accurate and timely assessment of geographical inequalities in immunization.
| S-EPMC8381099 | biostudies-literature