Intermediary and structural determinants of early childhood health in Colombia: exploring the role of communities

This study examines how structural determinants influence intermediary factors of child health inequities and how they operate through the communities where children live. In particular, we explore individual, family and community level characteristics associated with a composite indicator that quantitatively measures intermediary determinants of early childhood health in Colombia. We use data from the 2010 Colombian Demographic and Health Survey (DHS). Adopting the conceptual framework of the Commission on Social Determinants of Health (CSDH), three dimensions related to child health are represented in the index: behavioural factors, psychosocial factors and health system. In order to generate the weight of the variables and take into account the discrete nature of the data, principal component analysis (PCA) using polychoric correlations are employed in the index construction. Weighted multilevel models are used to examine community effects. The results show that the effect of household’s SES is attenuated when community characteristics are included, indicating the importance that the level of community development may have in mediating individual and family characteristics. The findings indicate that there is a significant variance in intermediary determinants of child health between-community, especially for those determinants linked to the health system, even after controlling for individual, family and community characteristics. These results likely reflect that whilst the community context can exert a greater influence on intermediary factors linked directly to health, in the case of psychosocial factors and the parent’s behaviours, the family context can be more important. This underlines the importance of distinguishing between community and family intervention programmes.

Contextual effects on subjective national identity and nationalist vote in Catalonia

The important inflow of foreign population to western countries has boosted the study of acculturation processes among scholars in the last decades. By using the case of Catalonia, a receiver region of international and national migration since the fifties, this paper seeks to intersect a classic acculturation model and a newly reemerging literature in political science on contextual determinants on individual behavior. Does the context matters for understanding individual’s subjective national identity and, therefore, its voting behavior? Multilevel models show that environment matters. Percentage of Spain-born population in the town is statistically significant to account for variance in the subjective national identity and nationalist vote, even after controlling for age, sex, origin, language and left – right orientation and other contextual factors. This conclusion invites researchers not to underestimate the direct effect of the environment on individual outcomes such as feelings of belonging and vote orientation in contexts of rival identities.

Social Determinants of Child Health in Colombia: Can Community Education Moderate the Effect of Family Characteristics?

Contextual effects on child health have been investigated extensively in previous research. However, few studies have considered the interplay between community characteristics and individual-level variables. This study examines the influence of community education and family socioeconomic characteristics on child health (as measured by height and weight-for-age Z-scores), as well as their interactions. We adapted the Commission on Social Determinants of Health (CSDH) framework to the context of child health. Using data from the 2010 Colombian Demographic and Health Survey (DHS), weighted multilevel models are fitted since the data are not self-weighting. The results show a positive impact of the level of education of other women in the community on child health, even after controlling for individual and family socioeconomic characteristics. Different pathways through which community education can substitute for the effect of family characteristics on child nutrition are found. The interaction terms highlight the importance of community education as a moderator of the impact of the mother’s own education and autonomy, on child health. In addition, the results reveal differences between height and weight-for-age indicators in their responsiveness to individual and contextual factors. Our findings suggest that community intervention programmes may have differential effects on child health. Therefore, their identification can contribute to a better targeting of child care policies.

Drug Utilization Studies and Data Registries in Primary Care.

This article reviews the methodology of the studies on drug utilization with particular emphasis on primary care. Population based studies of drug inappropriateness can be done with microdata from Health Electronic Records and e-prescriptions. Multilevel models estimate the influence of factors affecting the appropriateness of drug prescription at different hierarchical levels: patient, doctor, health care organization and regulatory environment. Work by the GIUMAP suggest that patient characteristics are the most important factor in the appropriateness of prescriptions with significant effects at the general practicioner level.

Drug utilization studies and data registries in primary care

This article reviews the methodology of the studies on drug utilization with particular emphasis on primary care. Population based studies of drug inappropriateness can be done with microdata from Health Electronic Records and e-prescriptions. Multilevel models estimate the influence of factors affecting the appropriateness of drug prescription at different hierarchical levels: patient, doctor, health care organization and regulatory environment.Work by the GIUMAP suggest that patient characteristics are the most important factor in the appropriateness of prescriptions with significant effects at the general practicioner level.

Disentangling the link between health and social capital: A comparison of immigrant and native-born populations in Spain

An increasing body of research has pointed to the relevance of social capital in studying a great variety of socio-economic phenomena, ranging from economics growth and development to educational attainment and public health. Conceptually, our paper is framed within the debates about the possible links between health and social capital, on one hand, and within the hypotheses regarding the importance of social and community networks in all stages of the dynamics of international migration, on the other hand. Our primary objective is to explore the ways social relations contribute to health differences between the immigrants and the native-born population of Spain. We also try to reveal differences in the nature of the social networks of foreign-born, as compared to that of the native-born persons. The empirical analysis is based on an individual-level data coming from the 2006 Spanish Health Survey, which contains a representative sample of the immigrant population. To assess the relationship between various health indicators (self-assessed health, chronic conditions and long-term illness) and social capital, controlling for other covariates, we estimate multilevel models separately for the two population groups of interest. In the estimates we distinguish between individual and community-level social capital. While the Health Survey contains information that allows us to define individual social capital measures, the collective indicators come from other official sources. In particular, for the subsample of immigrants, we proxy community-level networks and relationships by variables contained in the Spanish National Survey of Immigrants 2007. The results obtained so far point to the relevance of social capital as a covariate in the health equation, although, the significance varies according to the specific health indicator used. Additionally, and contrary to what is expected, immigrants’ social networks seem to be inferior to those of the native-born population in many aspects; and they also affect immigrant’s health to a lesser extent. Policy implications of the findings are discussed. Keywords: health status, social capital, immigration, Spain

The psychosocial difficulties in brain disorders that explain short term changes in health outcomes.

BACKGROUND: This study identifies a set of psychosocial difficulties that are associated with short term changes in health outcomes across a heterogeneous set of brain disorders, neurological and psychiatric. METHODS: Longitudinal observational study over approximately 12 weeks with three time points of assessment and 741 patients with depression, bipolar disorders, multiple sclerosis, parkinson's disease, migraine, traumatic brain injury and stroke. The data on disability was collected with the checklist of the International Classification of Functioning, Disability and Health. The selected health outcomes were the Short Form 36 and the World Health Organization Disability Assessment Schedule. Multilevel models for change were applied controlling for age, gender and disease severity. RESULTS: The psychosocial difficulties that explain the variability and change over time of the selected health outcomes were energy and drive, sleep, and emotional functions, and a broad range of activities and participation domains, such as solving problems, conversation, areas of mobility and self-care, relationships, community life and recreation and leisure. CONCLUSIONS: Our findings are of interest to researchers and clinicians for interventions and health systems planning as they show that in addition to difficulties that are diagnostic criteria of these disorders, there are other difficulties that explain small changes in health outcomes over short periods of time.

The influence of decision-maker effort and case complexity on appealed rulings subject to multi-categorical selection

This study extends the standard econometric treatment of appellate court outcomes by 1) considering the role of decision-maker effort and case complexity, and 2) adopting a multi-categorical selection process of appealed cases. We find evidence of appellate courts being affected by both the effort made by first-stage decision makers and case complexity. This illustrates the value of widening the narrowly defined focus on heterogeneity in individual-specific preferences that characterises many applied studies on legal decision-making. Further, the majority of appealed cases represent non-random sub-samples and the multi-categorical selection process appears to offer advantages over the more commonly used dichotomous selection models.

Line search multilevel optimization as computational methods for dense optical flow

We evaluate the performance of different optimization techniques developed in the context of optical flowcomputation with different variational models. In particular, based on truncated Newton methods (TN) that have been an effective approach for large-scale unconstrained optimization, we develop the use of efficient multilevel schemes for computing the optical flow. More precisely, we evaluate the performance of a standard unidirectional multilevel algorithm - called multiresolution optimization (MR/OPT), to a bidrectional multilevel algorithm - called full multigrid optimization (FMG/OPT). The FMG/OPT algorithm treats the coarse grid correction as an optimization search direction and eventually scales it using a line search. Experimental results on different image sequences using four models of optical flow computation show that the FMG/OPT algorithm outperforms both the TN and MR/OPT algorithms in terms of the computational work and the quality of the optical flow estimation.

A multilevel analysis on the determinants of regional health care expenditure. A note

We apply a multilevel hierarchical model to explore whether anaggregation fallacy exists in estimating the income elasticity of healthexpenditure by ignoring the regional composition of national healthexpenditure figures. We use data for 110 regions in eight OECD countriesin 1997: Australia, Canada, France, Germany, Italy, Spain, Sweden andUnited Kingdom. In doing this we have tried to identify two sources ofrandom variation: within countries and between-countries. Our resultsshow that: 1- Variability between countries amounts to (SD) 0.5433, andjust 13% of that can be attributed to income elasticity and the remaining87% to autonomous health expenditure; 2- Within countries, variabilityamounts to (SD) 1.0249; and 3- The intra-class correlation is 0.5300. Weconclude that we have to take into account the degree of fiscaldecentralisation within countries in estimating income elasticity ofhealth expenditure. Two reasons lie behind this: a) where there isdecentralisation to the regions, policies aimed at emulating diversitytend to increase national health care expenditure; and b) without fiscaldecentralisation, central monitoring of finance tends to reduce regionaldiversity and therefore decrease national health expenditure.

Line search multilevel optimization as computational methods for dense optical flow

We evaluate the performance of different optimization techniques developed in the context of optical flow computation with different variational models. In particular, based on truncated Newton methods (TN) that have been an effective approach for large-scale unconstrained optimization, we de- velop the use of efficient multilevel schemes for computing the optical flow. More precisely, we evaluate the performance of a standard unidirectional mul- tilevel algorithm - called multiresolution optimization (MR/OPT), to a bidrec- tional multilevel algorithm - called full multigrid optimization (FMG/OPT). The FMG/OPT algorithm treats the coarse grid correction as an optimiza- tion search direction and eventually scales it using a line search. Experimental results on different image sequences using four models of optical flow com- putation show that the FMG/OPT algorithm outperforms both the TN and MR/OPT algorithms in terms of the computational work and the quality of the optical flow estimation.

When culture does (not) matter: role models and self-efficacy as drivers of entrepreneurial behavior

The correlation between facets of national culture and startup activities has received confirmation in empirical research while many mechanisms behind the correlation remain unclear. We study the interplay between the individualism-collectivism orientation of national culture, the incidence of entrepreneurial role models and selfefficacy understood as the perception of possessing relevant skills and knowledge to become a successful entrepreneur. We find that exposure to entrepreneurial role models offsets self-efficacy as a driver of entrepreneurial intentions. The effect is magnified by the individualistic character of the national culture. Key words: entrepreneurial intentions, role models, self-efficacy, individualism, multilevel regressions

Parametric and semiparametric estimation of sample selection models: an empirical application to the female labour force in Portugal

This comment corrects the errors in the estimation process that appear in Martins (2001). The first error is in the parametric probit estimation, as the previously presented results do not maximize the log-likelihood function. In the global maximum more variables become significant. As for the semiparametric estimation method, the kernel function used in Martins (2001) can take on both positive and negative values, which implies that the participation probability estimates may be outside the interval [0,1]. We have solved the problem by applying local smoothing in the kernel estimation, as suggested by Klein and Spady (1993).

Are one factor logarithmic volatility models useful to fit the features of financial data? An application to microsoft data.

This paper provides empirical evidence that continuous time models with one factor of volatility, in some conditions, are able to fit the main characteristics of financial data. It also reports the importance of the feedback factor in capturing the strong volatility clustering of data, caused by a possible change in the pattern of volatility in the last part of the sample. We use the Efficient Method of Moments (EMM) by Gallant and Tauchen (1996) to estimate logarithmic models with one and two stochastic volatility factors (with and without feedback) and to select among them.