3 resultados para multidimensional data

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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BACKGROUND: Multidimensional preventive home visit programs aim at maintaining health and autonomy of older adults and preventing disability and subsequent nursing home admission, but results of randomized controlled trials (RCTs) have been inconsistent. Our objective was to systematically review RCTs examining the effect of home visit programs on mortality, nursing home admissions, and functional status decline. METHODS: Data sources were MEDLINE, EMBASE, Cochrane CENTRAL database, and references. Studies were reviewed to identify RCTs that compared outcome data of older participants in preventive home visit programs with control group outcome data. Publications reporting 21 trials were included. Data on study population, intervention characteristics, outcomes, and trial quality were double-extracted. We conducted random effects meta-analyses. RESULTS: Pooled effects estimates revealed statistically nonsignificant favorable, and heterogeneous effects on mortality (odds ratio [OR] 0.92, 95% confidence interval [CI], 0.80-1.05), functional status decline (OR 0.89, 95% CI, 0.77-1.03), and nursing home admission (OR 0.86, 95% CI, 0.68-1.10). A beneficial effect on mortality was seen in younger study populations (OR 0.74, 95% CI, 0.58-0.94) but not in older populations (OR 1.14, 95% CI, 0.90-1.43). Functional decline was reduced in programs including a clinical examination in the initial assessment (OR 0.64, 95% CI, 0.48-0.87) but not in other trials (OR 1.00, 95% CI, 0.88-1.14). There was no single factor explaining the heterogenous effects of trials on nursing home admissions. CONCLUSION: Multidimensional preventive home visits have the potential to reduce disability burden among older adults when based on multidimensional assessment with clinical examination. Effects on nursing home admissions are heterogeneous and likely depend on multiple factors including population factors, program characteristics, and health care setting.

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This study compares monetary and multidimensional poverty measures for the Lao People’s Democratic Republic. Using household data of 2007/2008, we compare the empirical outcomes of the country’s current official monetary poverty measure with those of a multidimensional poverty measure. We analyze which population subgroups are identified as poor by both measures and thus belong to the category of the poorest of the poor; and we look at which subgroups are identified as poor by only one of the measures and belong either to the category of the income-poor (identified as poor only by the monetary measure) or to that of the overlooked poor (identified as poor only by the multidimensional poverty measure). Furthermore, we examined drivers of these differences using a multinomial regression model and found that monetary poverty does not capture the multiple deprivations of ethnic minorities, who are only identified as poor when using a multidimensional poverty measure. We conclude that complementing the monetary poverty measure with a multidimensional poverty index would enable more effective targeting of poverty reduction efforts.