Dataset Information

Enabling and constraining successful reablement: Individual and neighbourhood factors.

ABSTRACT: Using multilevel logistic regression to analyse management data of reablement episodes collected by Essex County Council, a UK local authority, this article identifies constraining and enabling factors for successful reablement. Overall, 59.5% of reablement clients were classed as able to care for themselves when assessed after 13 weeks following the reablement intervention (N = 8,118). Several age-related, disability, referral, and social factors were found to constrain reablement, but some of the largest constraining effects were neighbourhood deprivation as measured through the Index of Multiple Deprivation and, particularly, unfavourable geodemographic profiles as measured through Experian Mosaic consumer classifications. The results suggest that in order to optimise reablement, programmes should consider broader social and environmental influences on reablement rather than only individual and organisational aspects. Reablement might also be better tailored and intensified for client groups with particular underlying disabilities and for those displaying specific geodemographic characteristics.

SUBMITTER: Jacobi CJ

PROVIDER: S-EPMC7473582 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Enabling and constraining successful reablement: Individual and neighbourhood factors.

Jacobi Christopher Justin CJ Thiel Darren D Allum Nick N

PloS one 20200904 9

Using multilevel logistic regression to analyse management data of reablement episodes collected by Essex County Council, a UK local authority, this article identifies constraining and enabling factors for successful reablement. Overall, 59.5% of reablement clients were classed as able to care for themselves when assessed after 13 weeks following the reablement intervention (N = 8,118). Several age-related, disability, referral, and social factors were found to constrain reablement, but some of ...[more]

PMID: 32886657

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Project description:PurposeRecovery Education Centres (REC) in mental health offer a new model of providing recovery supports through emancipatory adult education and recovery-oriented service principles. Despite the widespread adoption of RECs, there is limited evidence regarding factors enabling engagement and participation, particularly for unique subpopulations or service delivery contexts. The Supporting Transitions and Recovery Learning Centre (STAR) in Toronto, Ontario is the first REC in Canada and one of few worldwide supporting adults transitioning out of homelessness. This research aimed to investigate individual and program level enablers of engagement and participation in a REC for this population.MethodsQualitative methods were used to explore the experiences of 20 service user participants through semi-structured interviews exploring their experiences of REC participation and perceived key program features. Interviews were conducted between July 2017 and June 2018, six to 14 months following REC enrollment, and analyzed using inductive thematic analysis.ResultsIn contrast to past experiences with health and social services, participants described a welcoming and respectful physical and interpersonal environment with low-barrier seamless access facilitating their engagement and participation. Although the realities of homelessness presented barriers for some, participants described that the involvement of peers, as role models, and the self-directed, strengths, and skills-based curriculum, co-produced and co-delivered by peers and professionals, were instrumental in activating the process of recovery through education.Conclusions/implicationsFindings are consistent with the growing evidence base of the defining features of RECs and suggest this model can be successfully extended to support recovery among adults transitioning out of homelessness. This unique examination of Canada's first REC for adults exiting homelessness can help guide program and policy development to better support this disadvantaged population.

Project description:BackgroundSocio-economic disadvantage at both individual and neighbourhood levels has been found to be associated with single lifestyle risk factors. However, it is unknown to what extent their combined effects contribute to a broad lifestyle profile. We aimed to (i) investigate the associations of individual socio-economic disadvantage (ISED) and neighbourhood socio-economic disadvantage (NSED) in relation to an extended score of health-related lifestyle risk factors (lifestyle risk index); and to (ii) investigate whether NSED modified the association between ISED and the lifestyle risk index.MethodsOf 77 244 participants [median age (IQR): 46 (40-53) years] from the Lifelines cohort study in the northern Netherlands, we calculated a lifestyle risk index by scoring the lifestyle risk factors including smoking status, alcohol consumption, diet quality, physical activity, TV-watching time and sleep time. A higher lifestyle risk index was indicative of an unhealthier lifestyle. Composite scores of ISED and NSED based on a variety of socio-economic indicators were calculated separately. Linear mixed-effect models were used to examine the association of ISED and NSED with the lifestyle risk index and to investigate whether NSED modified the association between ISED and the lifestyle risk index by including an interaction term between ISED and NSED.ResultsBoth ISED and NSED were associated with an unhealthier lifestyle, because ISED and NSED were both positively associated with the lifestyle risk index {highest quartile [Q4] ISED beta-coefficient [95% confidence interval (CI)]: 0.64 [0.62-0.66], P < 0.001; highest quintile [Q5] NSED beta-coefficient [95% CI]: 0.17 [0.14-0.21], P < 0.001} after adjustment for age, sex and body mass index. In addition, a positive interaction was found between NSED and ISED on the lifestyle risk index (beta-coefficient 0.016, 95% CI: 0.011-0.021, Pinteraction < 0.001), which indicated that NSED modified the association between ISED and the lifestyle risk index; i.e. the gradient of the associations across all ISED quartiles (Q4 vs Q1) was steeper among participants residing in the most disadvantaged neighbourhoods compared with those who resided in the less disadvantaged neighbourhoods.ConclusionsOur findings suggest that public health initiatives addressing lifestyle-related socio-economic health differences should not only target individuals, but also consider neighbourhood factors.

Project description:The purpose of the study is to examine whether there is an association between neighbourhood deprivation and incidence of congenital heart disease (CHD), after accounting for family- and individual-level potential confounders.All children aged 0 to 11 years and living in Sweden (n?=?748,951) were followed between January 1, 2000 and December 31, 2010. Data were analysed by multilevel logistic regression, with family- and individual-level characteristics at the first level and level of neighbourhood deprivation at the second level.During the study period, among a total of 748,951 children, 1499 (0.2%) were hospitalised with CHD. Age-adjusted cumulative hospitalisation rates for CHD increased with increasing level of neighbourhood deprivation. In the study population, 1.8 per 1000 and 2.2 per 1000 children in the least and most deprived neighbourhoods, respectively, were hospitalised with CHD. The incidence of hospitalisation for CHD increased with increasing neighbourhood-level deprivation across all family and individual-level socio-demographic categories. The odds ratio (OR) for hospitalisation for CHD for those living in high-deprivation neighbourhoods versus those living in low-deprivation neighbourhoods was 1.23 (95% confidence interval (CI)?=?1.04-1.46). In the full model, which took account for age, paternal and maternal individual-level socio-economic characteristics, comorbidities (e.g. maternal type 2 diabetes, OR?=?3.03; maternal hypertension, OR?=?2.01), and family history of CHD (OR?=?3.27), the odds of CHD were slightly attenuated but did not remain significant in the most deprived neighbourhoods (OR?=?1.20, 95% CI?=?0.99-1.45, p?=?0.057).This study is the largest so far on neighbourhood influences on CHD, and the results suggest that deprived neighbourhoods have higher rates of CHD, which represents important clinical knowledge. However, the association does not seem to be independent of individual- and family-level characteristics.

Project description:BACKGROUND:Car driving is a form of passive transportation associated with higher sedentary behaviour, which is associated with morbidity. The decision to drive a car is likely to be influenced by the 'drivability' of the built environment, but there is lack of scientific evidence regarding the relative contribution of environmental characteristics of car driving in Europe, compared to individual characteristics. This study aimed to determine which neighbourhood- and individual-level characteristics were associated with car driving in adults of five urban areas across Europe. Second, the study aimed to determine the percentage of variance in car driving explained by individual- and neighbourhood-level characteristics. METHODS:Neighbourhood environment characteristics potentially related to car use were identified from the literature. These characteristics were subsequently assessed using a Google Street View audit and available GIS databases, in 59 administrative residential neighbourhoods in five European urban areas. Car driving (min/week) and individual level characteristics were self-reported by study participants (analytic sample n?=?4258). We used linear multilevel regression analyses to assess cross-sectional associations of individual and neighbourhood-level characteristics with weekly minutes of car driving, and assessed explained variance at each level and for the total model. RESULTS:Higher residential density (?:-2.61, 95%CI: -?4.99; -0.22) and higher land-use mix (?:-3.73, 95%CI: -?5.61; -1.86) were significantly associated with fewer weekly minutes of car driving. At the individual level, higher age (?: 1.47, 95%CI: 0.60; 2.33), male sex (?: 43.2, 95%CI:24.7; 61.7), being employed (?:80.1, 95%CI: 53.6; 106.5) and???3 person household composition (?: 47.4, 95%CI: 20.6; 74.2) were associated with higher weekly minutes of car driving. Individual and neighbourhood characteristics contributed about equally to explained variance in minutes of weekly car driving, with 2 and 3% respectively, but total explained variance remained low. CONCLUSIONS:Residential density and land-use mix were neighbourhood characteristics consistently associated with minutes of weekly car driving, besides age, sex, employment and household composition. Although total explained variance was low, both individual- and neighbourhood-level characteristics were similarly important in their associations with car use in five European urban areas. This study suggests that more, higher quality, and longitudinal data are needed to increase our understanding of car use and its effects on determinants of health.

Dataset Information

Enabling and constraining successful reablement: Individual and neighbourhood factors.

Publications

Enabling and constraining successful reablement: Individual and neighbourhood factors.

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