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BACKGROUND: Interest in modifiable risk factors (MRFs) for dementia is high, given the personal, social, and economic impact of the disorder, especially in ageing societies such as the United Kingdom. Exploring the population attributable fraction (PAF) of dementia attributable to MRFs and how this may have changed over time remains unclear. Unravelling the temporal dynamics of MRFs is crucial for informing the development of evidence-based and effective public health policies. This investigation examined the temporal trajectories of MRFs for dementia in England. METHODS: We used data from the English Longitudinal Study of Ageing, a panel study over eight waves collected between 2004 and 2019 (76,904 interviews in total). We calculated the PAFs for twelve MRFs (including six early- to mid-life factors and six late-life factors), as recommended by the Lancet Commission, and the individual weighted PAFs (IW-PAFs) for each risk factor. Temporal trends were analysed to understand the changes in the overall PAF and IW-PAF over the study period. Subgroup analyses were conducted by sex and socioeconomic status (SES). RESULTS: The overall PAF for dementia MRFs changed from 46.73% in 2004/2005 to 36.79% in 2018/2019, though this trend was not statistically significant. During 2004-2019, hypertension, with an average IW-PAF of 8.21%, was the primary modifiable determinant of dementia, followed by obesity (6.16%), social isolation (5.61%), hearing loss (4.81%), depression (4.72%), low education (4.63%), physical inactivity (3.26%), diabetes mellitus (2.49%), smoking (2.0%), excessive alcohol consumption (1.16%), air pollution (0.42%), and traumatic brain injury (TBI) (0.26%). During 2004-2019, only IW-PAFs of low education, social isolation, and smoking showed significant decreasing trends, while IW-PAFs of other factors either did not change significantly or increased (including TBI, diabetes mellitus, and air pollution). Upon sex-specific disaggregation, a higher overall PAF for MRFs was found among women, predominantly associated with later-life risk factors, most notably social isolation, depression, and physical inactivity. Additionally, hearing loss, classified as an early- to mid-life factor, played a supplementary role in the identified sex disparity. A comparable discrepancy was evident upon PAF evaluation by SES, with lower income groups experiencing a higher dementia risk, largely tied to later-life factors such as social isolation, physical inactivity, depression, and smoking. Early- to mid-life factors, in particular, low education and obesity, were also observed to contribute to the SES-associated divergence in dementia risk. Temporal PAF and IW-PAF trends, stratified by sex and SES, revealed that MRF PAF gaps across sex or SES categories have persisted or increased. CONCLUSIONS: In England, there was little change over time in the proportion of dementia attributable to known modifiable risk factors. The observed trends underscore the continuing relevance of these risk factors and the need for targeted public health strategies to address them.

: Introduction: Disability and HIV are intricately linked, as people with disabilities are at higher risk of contracting HIV, and living with HIV can lead to impairments and disability. Despite this well‐established relationship, there remains limited internationally comparable evidence on HIV knowledge and access to testing for people with disabilities. Methods: We used cross‐sectional data from 37 Multiple Indicator Cluster Surveys. Surveys were from six UNICEF regions, including East Asia and Pacific (n = 6), East and Central Asia (n = 7), Latin America and the Caribbean (n = 6), Middle East and North Africa (n = 4), South Asia (n = 2) and sub‐Saharan Africa (n = 12). A total of 513,252 people were eligible for inclusion, including 24,695 (4.8%) people with disabilities. We examined risk ratios and 95% confidence intervals for key indicators on HIV knowledge and access to testing for people with disabilities by sex and country. We also conducted a meta‐analysis to get a pooled estimate for each sex and indicator. Results: Men and women with disabilities were less likely to have comprehensive knowledge about HIV prevention (aRR: 0.74 [0.67, 0.81] and 0.75 [0.69, 0.83], respectively) and to know of a place to be tested for HIV (aRR: 0.95 [0.92, 0.99] and 0.94 [0.92, 0.97], respectively) compared to men and women without disabilities. Women with disabilities were also less likely to know how to prevent mother‐to‐child transmission (aRR: 0.87 [0.81, 0.93]) and ever have been tested for HIV (aRR: 0.90 [0.85, 0.94]). Conclusions: Men and women with disabilities have lower overall HIV knowledge and in particular women with disabilities also indicate lower testing rates. Governments must include people with disabilities in HIV programmes by improving disability‐inclusion and accessibility to HIV‐related information, education and healthcare services., INTRODUCTION Globally, there are 1.3 billion people with disabilities [1]. There is a close relationship between HIV and disability, as research suggests that people with disabilities are at higher risk [...]

The objectives of this review are to answer the following research questions: (1) What is the nature of the interventions used to support education for people with disabilities? (2) What is the size and quality of the evidence base of the effectiveness of interventions to improve educational outcomes for people with disabilities in low- and middle-income countries (LMICs)? (3) What works to improve educational outcomes for people with disabilities in LMICs? (4) Which interventions appear most effective for different types of disability? (5) What are the barriers and facilitators to improving of educational outcomes for people with disabilities? Is there evidence of cumulative effects--that certain interventions are effective when done in combination with others, but are less or ineffective when done alone?

The objectives of this review are to answer the following research questions: (1) What is the effect size of the effectiveness of interventions to improve livelihood outcomes for people with disabilities in low- and middle-income countries (LMICs), and what is the quality of the evidence base? (2) What works to improve livelihood outcomes for people with disabilities in LMICs? (3) Which interventions appear most effective for different categories of disability? (4) What are the barriers and facilitators to the improvement of livelihood outcomes to people with disabilities?

Purpose: This study aimed to describe and compare the performance of two screening protocols used for preschool hearing screening in resource-constrained settings. Method: Secondary data analysis was done to determine the performance of two protocols implemented during a preschool hearing screening program using mobile health technology in South Africa. Pure-tone audiometry screening at 25 dB HL for 1000, 2000, and 4000 Hz in each ear was used by both protocols. The fail criterion for the first protocol (2,147 children screened) constituted a no-response on one or more frequencies in either ear. The second protocol required two or more no-responses (5,782 children). Multivariate logistic regression models were used to investigate associations between outcomes and protocol, age, gender, and duration. Results: Fail rates for the one-frequency fail protocol was 8.7% (n = 186) and 4.3% (n = 250) for the two-frequency fail protocol. Children screened with the two-frequency fail protocol were 52.9% less likely to fail (p < 0.001; OR = 0.471; 95% confidence interval [0.385, 0.575]). Gender (p = 0.251) and age (p = 0.570) had no significant effect on screening outcome. A percentage of cases screened (44.7%) exceeded permissible noise levels in at least one ear at 1000 Hz across both protocols. True- and false-positive cases did not differ significantly between protocols. Protocol type (p = 0.204), gender (p = 0.314), and age (p = 0.982) did not affect the odds of being a true-positive result. Average screening time was 72.8 s (78.66 SD) and 64.9 s (55.78 SD) for the one-frequency and two-frequency fail protocols, respectively. Conclusions: A two-frequency fail criterion and immediate rescreen of failed frequencies significantly reduced referral rate for follow-up services that are often overburdened in resourced-constrained settings. Future protocol adaptations can also consider increasing the screening levels at 1000 Hz to minimize the influence of environmental noise.

Introduction: Globally, more than 50 million children have hearing or vision loss. Most of these sensory losses are identified late due to a lack of systematic screening, making treatment and rehabilitation less effective. Mobile health (mHealth), which is the use of smartphones or wireless devices in health care, can improve access to screening services. mHealth technologies allow lay health workers (LHWs) to provide hearing and vision screening in communities. Purpose: The aim of the study was to evaluate a hearing and vision school screening program facilitated by LHWs using smartphone applications in a low-income community in South Africa. Method: Three LHWs were trained to provide dual sensory screening using smartphone-based applications. The hearScreen app with calibrated headphones was used to conduct screening audiometry, and the Peek Acuity app was used for visual acuity screening. Schools were selected from low-income communities (Gauteng, South Africa), and children aged between 4 and 9 years received hearing and vision screening. Screening outcomes, associated variables, and program costs were evaluated. Results: A total of 4,888 and 4,933 participants received hearing and vision screening, respectively. Overall, 1.6% of participants failed the hearing screening, and 3.6% failed visual acuity screening. Logistic regression showed that female participants were more likely to pass hearing screening (OR = 1.61, 95% CI [1.11, 2.54]), while older children were less likely to pass visual acuity screening (OR = 0.87, 95% CI [0.79, 0.96]). A third (32.5%) of referred cases followed up for air-conduction threshold audiometry, and one in four (25.1%) followed up for diagnostic vision testing. A high proportion of these cases were confirmed to have hearing (73.1%, 19/26) or vision loss (57.8%, 26/45). Conclusions: mHealth technologies can enable LHWs to identify school-age children with hearing and/or vision loss in low-income communities. This approach allows for low-cost, scalable models for early detection of sensory losses that can affect academic performance.

Background: Children and young people (CYP) with complex neurodisability experience multiple physical, communication, educational and social challenges, which require complex packages of multidisciplinary care. Part of the holistic care required includes supporting the families and parents/caregivers. The aim of the wider study was to introduce a new programme ('Ubuntu') to parents/caregivers and healthcare professionals (HCPs) in order to test the feasibility and acceptability of the concept and content, with the goal of potential adaptation for the UK in mind. Data collection and analysis uncovered rich data on caregiving journeys, navigation of health services, and perceived service gaps. This paper focuses solely on these topics. Further papers will report on the feasibility and adaptation data. Methods: Two rounds of semi‐structured interviews were conducted with 12 caregivers of CYP with complex neurodisability and six HCPs from a variety of disciplines, recruited from a community child health service in London Borough of Newham, UK in 2020. The interviews included open‐ended questions to explore caregiving journeys, experiences of navigating health services and perceived service gaps. Transcripts were analysed using a data‐driven inductive thematic analysis. Results: Three themes were identified that related to the aim of understanding caregivers' experiences and unmet needs relating to current service provision. These were (1) Caregiver Mental Health, (2) The Information Gap and (3) The Need for Holistic Support. Mental health difficulties were reported, particularly around the period of diagnosis. Priority needs included the provision of clear information about the diagnosis and services offered, opportunities to forge peer support networks and for services across the community to collaborate. Conclusions: The delivery of health services for CYP with neurodisability should encompass the broad needs of the family as well as meeting the clinical needs of the CYP. [ABSTRACT FROM AUTHOR]

Background: There are approximately 1 billion people in the world with some form of disability. This corresponds to approximately 15% of the world's population (World Report on Disability, 2011). The majority of people with disabilities (80%) live in low- and middle-income countries (LMICs), where disability has been shown to disproportionately affect the most disadvantaged sector of the population. Decision makers need to know what works, and what does not, to best invest limited resources aimed at improving the well-being of people with disabilities in LMICs. Systematic reviews and impact evaluations help answer this question. Improving the availability of existing evidence will help stakeholders to draw on current knowledge and to understand where new research investments can guide decision-making on appropriate use of resources. Evidence and gap maps (EGMs) contribute by showing what evidence there is, and supporting the prioritization of global evidence synthesis needs and primary data collection. Objectives: The aim of this EGM is to identify, map and describe existing evidence of effectiveness studies and highlight gaps in evidence base for people with disabilities in LMICs. The map helps identify priority evidence gaps for systematic reviews and impact evaluations. Methods: The EGM included impact evaluation and systematic reviews assessing the effect of interventions for people with disabilities and their families/carers. These interventions were categorized across the five components of community-based rehabilitation matrix; health, education, livelihood, social and empowerment. Included studies looked at outcomes such as, health, education, livelihoods, social inclusion and empowerment, and were published for LMICs from 2000 onwards until January 2018. The searches were conducted between February and March 2018. The EGM is presented as a matrix in which the rows are intervention categories (e.g., health) and subcategories (e.g., rehabilitation) and the column outcome domains (e.g., health) and subdomains (e.g., immunization). Each cell lists the studies for that intervention for those outcomes, with links to the available studies. Included studies were therefore mapped according to intervention and outcomes assessed and additional filters as region, population and study design were also coded. Critical appraisal of included systematic review was done using A Measurement Tool to Assess Systematic Reviews' rating scale. We also quality-rated the impact evaluation using a quality assessment tool based on various approaches to risk of bias assessment. Results: The map includes 166 studies, of which 59 are systematic reviews and 107 impact evaluation. The included impact evaluation are predominantly quasiexperimental studies (47%). The numbers of studies published each year have increased steadily from the year 2000, with the largest number published in 2017. The studies are unevenly distributed across intervention areas. Health is the most heavily populated area of the map. A total of 118 studies of the 166 studies concern health interventions. Education is next most heavily populated with 40 studies in the education intervention/outcome sector. There are relatively few studies for livelihoods and social, and virtually none for empowerment. The most frequent outcome measures are health-related, including mental health and cognitive development (n = 93), rehabilitation (n = 32), mortality and morbidity (n = 23) and health check-up (n = 15). Very few studies measured access to assistive devices, nutrition and immunization. Over half (n = 49) the impact evaluation come from upper-middle income countries. There are also geographic gaps, most notably for low income countries (n = 9) and lower-middle income countries (n = 34). There is a fair amount of evidence from South Asia (n = 73) and Sub-Saharan Africa (n = 51). There is a significant gap with respect to study quality, especially with respect to impact evaluation. There appears to be a gap between the framing of the research, which is mostly within the medical model and not using the social model of disability. Conclusion: Investing in interventions to improve well-being of people with disabilities will be critical to achieving the 2030 agenda for sustainable development goals. The EGM summarized here provides a starting point for researchers, decision makers and programme managers to access the available research evidence on the effectiveness of interventions for people with disabilities in LMICs in order to guide policy and programme activity, and encourage a more strategic, policy-oriented approach to setting the future research agenda.

Over the past decade the academic literature on disability outcomes and effectiveness has grown substantially (Andresen, Lollar, & Meyers, 2000; Devon, Lydon, Healy, & McCoy, 2016; Iemmi et al., 2015). Several important questions have not been adequately addressed, however. For example, what type of evidence is needed, and what are realistic expectations for disability outcomes and effectiveness research? A lack of rigorous and comparable data on disability and evidence on programmes that work can impede understanding and action. Understanding the numbers of people with disabilities and their circumstances can improve efforts to remove disabling barriers and provide services to allow people with disabilities to participate on an equal basis with others. For example, better measures of the environment and its impacts on the different aspects of disability need to be developed to facilitate the identification of cost-effective environmental interventions. Knowledge production takes place across several sectors (health, social welfare and education), focuses on various populations (different ages, ethnicities, or with different needs), and involves rather diverse methodical approaches (e.g., systematic reviews, primary studies of different designs, etc.). A mapping of the existing knowledge base is therefore required to provide a comprehensive overview of existing knowledge in this area and enable the purposeful and targeted commissioning of future research, tailored to the most eminent needs for knowledge and guidance. This ambition could be fulfilled by a proposed evidence and gap map (EGM). The proposed EGM will present studies of the effectiveness of these interventions across a range of outcome domains. Specifically, the objectives of the map are to: (1) develop a clear framework of types of interventions and outcomes related to effectiveness of interventions for people with disabilities in low- and middle-income countries (LMICs); (2) map available systematic reviews and primary studies on the effectiveness of disability interventions in low- and middle-income countries in this framework, with an overview provided in a summary report; and (3) provide database entries of included studies which summarise the intervention, context, study design and main findings.

Background: Cervical cancer screening is an important public health priority, yet many marginalized groups are not reached by existing programs. The nearly 700 million women with disabilities globally face substantial barriers in accessing cervical cancer screening and have lower coverage, yet there is limited evidence on what would support enhanced uptake among this population. Methods: We updated a systematic review to estimate the disparity in screening uptake for women with disabilities. We conducted a scoping review to understand key barriers and the inclusion of disability in existing screening policies and possible solutions to improve screening uptakes amongst women with disabilities. We then formulated key principles for improved service delivery for this group, targeted predominantly at clinicians. Results: Our updated review identified an additional five new studies, and confirmed that women with disabilities were less likely to be screened for cervical cancer (RR=0.65, 0.50– 0.84). Disability-specific barriers to accessing screening pertained to: (1) knowledge and autonomy; (2) logistics; and (3) stigma and fear. Few guidelines included specific considerations for women with disabilities. Our scoping review showed that improving access to care must focus on improving (1) autonomy, awareness, and affordability; (2) human resources; and (3) health facility accessibility. Conclusion: Screening programmes and health providers must ensure women with disabilities are included in cervical cancer screening programmes and thereby help to achieve their right to health and eliminate cervical cancer as a public health issue. [ABSTRACT FROM AUTHOR]

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