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al moderating impact. © 2020 The Authors.No previous study has explored the structure of self-rated health (SRH), a measure holding strong predictive value for future health events, in the oldest old or in individuals with dementia. The aim was to construct a structural equation model of SRH for oldest old in general and for oldest old with dementia, and to explore direct and indirect associations between health-related factors and SRH. Cross-sectional data from the Vitality 90+, a population-based study in the city of Tampere, Finland, was used. Data were gathered by a mailed questionnaire in 2014. Altogether 1299 nonagenarians, of which 408 had self-reported dementia or cognitive decline, were included. Structural equation models were constructed for all participants and separately for participants with dementia. Diseases (heart disease, stroke, diabetes, arthritis, hip fracture, cancer and dementia for the model for all), dizziness, hearing, vision, mobility, activities of daily living, fatigue, depression and SRH were included in the models. Among all participants, fatigue, depression, problems in mobility, dizziness, deficits in vision and heart disease were directly associated with poor SRH. Among participants with dementia, only fatigue, dizziness and deficits in vision were directly associated with poor SRH. Among all participants, dementia and arthritis were indirectly associated with poor SRH through problems in mobility, depression and fatigue. Among the oldest old, the effects of diseases on SRH were mainly manifested through the consequences of diseases, namely fatigue, dizziness, deficits in vision and problems in mobility. Depression has an important direct and indirect role, and dementia and arthritis an important indirect role in the structure of SRH. GPNA nmr Dementia weakens many of the direct and indirect associations for SRH. © 2020 The Authors.Background While previous research has evidently and extensively acknowledged socioeconomic gradients in children's education, we know very little about the determinants of socioeconomic-related inequality in children's education at the population level in Sweden. Therefore, we aimed (i) to assess the extent of income inequality in upper secondary school completion in Sweden; (ii) to examine the contribution of mental health and other determinants to income inequality; and (iii) to explore gender differences in the magnitude and determinants of the inequalities. Method We utilised data from a population-based cohort available in Umeå SIMSAM Lab, linked with several national registries in Sweden. The dataset includes all children who were born in Sweden in 1991 and completed or not completed their upper secondary education in 2010, n = 116,812 (56,612 girls and 60,200 boys). We analysed the data using a Wagstaff-type decomposition method. Results The results first show substantial income-related inequality in upper secondary school incompletion concentrated among the poor in the Swedish setting. Second, these inequalities were in turn to a large degree explained jointly by parental, family and child factors; primarily parents' income and education, number of siblings and child's poor mental health. Third, these inferences remained when boys and girls were considered separately, although the determinants explained a greater share of the inequalities in boys than in girls. Conclusion Our results highlighted substantial income-related inequality in upper secondary school incompletion concentrated among the poor in the Swedish setting. Apart from family level characteristics, which explained a large portion of the inequalities, mental health problems appeared to be of particular importance as they represent a central target for both increasing the population average in upper secondary school completion and for reducing the gap in income-related inequalities in Sweden. © 2020 Published by Elsevier Ltd.We determined the relationship between long hours of care and the assistance in each activity of daily living (ADL) element.•The assistance in wiping of the body, dressing and toileting were significantly associated with longer hours of care .•To support caregivers effectively, it is important to consider the kinds of ADL elements of the care recipients. © 2020 The Authors.The changing demographic structure in India and worldwide accompanies with it a gamut of problems and opportunities. According to the Census of India, the proportion of elderly in the overall population rose from 5.6 per cent in 1961 to 8.6 per cent in 2011 and is expected to rise to 20 per cent in 2050. Considering the consequent growing challenges in healthcare the main aim of the study is to find essential determinants contributing to untreated morbidity among the elderly. Also, the paper examines treatment-seeking behaviour for infectious and chronic diseases among the elderly in India. Data from the 60th and 71st round of National Sample Survey Organization was used for the analysis. Relative differences were calculated along with logistic regression to study the objectives and the heckprobit model was used to carve out the treatment-seeking behaviour among the elderly in India. It was found that the overall decrease in relative decadal difference was 41% for untreated morbidity. In both the rounds, the elderly living below the poverty line had 42% and 50% more likelihood of untreated morbidities respectively in comparison to elderly not living below the poverty line. The study indicates that elderly who were living with a spouse in comparison to those living alone had less likelihood to have untreated morbidities. Also, elderly from rural areas and having lower levels of education had higher likelihood of untreated morbidity. Similar inequalities were observed in treatment-seeking behaviour as well, where it was found that elderly belonging to lower socio-economic status were less likely to seek treatment. Linking the results from the heckprobit model this study provides the evidence that social and economic factors play a significant role in affecting both untreated morbidity and treatment-seeking behaviour of elderly in India. © 2020 Published by Elsevier Ltd.