Children's environmental health: an under-recognised area in paediatric health care

The knowledge that the environment in which we live, grow and play, can have negative or positive impacts on our health and development is not new. However the recognition that adverse environments can significantly and specifically affect the growth and development of a child from early intrauterine life through to adolescence, as well as impact their health later in adulthood, is relatively recent and has not fully reached health care providers involved in paediatric care

Developing core sets for persons following amputation based on the International Classification of Functioning, Disability and Health as a way to specify functioning

Amputation is a common late stage sequel of peripheral vascular disease and diabetes or a sequel of accidental trauma, civil unrest and landmines. The functional impairments affect many facets of life including but not limited to: Mobility; activities of daily living; body image and sexuality. Classification, measurement and comparison of the consequences of amputations has been impeded by the limited availability of internationally, multiculturally standardized instruments in the amputee setting. The introduction of the International Classification of Functioning, Disability and Health (ICF) by the World Health Assembly in May 2001 provides a globally accepted framework and classification system to describe, assess and compare function and disability. In order to facilitate the use of the ICF in everyday clinical practice and research, ICF core sets have been developed that focus on specific aspects of function typically associated with a particular disability. The objective of this paper is to outline the development process for the ICF core sets for persons following amputation. The ICF core sets are designed to translate the benefits of the ICF into clinical routine. The ICF core sets will be defined at a Consensus conference which will integrate evidence from preparatory studies, namely: (a) a systematic literature review regarding the outcome measures of clinical trails and observational studies, (b) semi-structured patient interviews, (c) international experts participating in an internet-based survey, and (d) cross-sectional, multi-center studies for clinical applicability. To validate the ICF core sets field-testing will follow. Invitation for participation: The development of ICF Core Sets is an inclusive and open process. Anyone who wishes to actively participate in this process is invited to do so

Economic Aspects of Sanitation in Developing Countries

Improved sanitation has been shown to have great impacts on people's health and economy. However, the progress of achieving the Millennium Development Goals (MDGs) on halving the proportion of people without access to clean water and basic sanitation by 2015 has thus far been delayed. One of the reasons for the slow progress is that policy makers, as well as the general public, have not fully understood the importance of the improved sanitation solutions. This paper, by gathering relevant research findings, aims to report and discuss currently available evidence on the economic aspects of sanitation, including the economic impacts of unimproved sanitation and the costs and economic benefits of some common improved sanitation options in developing countries.; DATA USED IN THIS PAPER WERE OBTAINED FROM DIFFERENT INFORMATION SOURCES: international and national journal articles and reports, web-based statistics, and fact sheets. We used both online search and hand search methods to gather the information.; Scientific evidence has demonstrated that the economic cost associated with poor sanitation is substantial. At the global level, failure to meet the MDG water and sanitation target would have ramifications in the area of US$38 billion, and sanitation accounts for 92$142 billion (US$year 2005). This translates to a per capita spending of US$28 for sanitation. Annually, this translates to roughly US$14 million. The evidence complied in this paper demonstrates that investing in sanitation is socially and economically worthwhile. For every US$1 invested, achieving the sanitation MDG target and universal sanitation access in the non-OECD countries would result in a global return of US$9.1 and US$11.2, respectively.; Given the current state of knowledge, sanitation is undeniably a profitable investment. It is clear that achieving the MDG sanitation target not only saves lives but also provides a foundation for economic growth

The Feature Importance Ranking Measure

Most accurate predictions are typically obtained by learning machines with complex feature spaces (as e.g. induced by kernels). Unfortunately, such decision rules are hardly accessible to humans and cannot easily be used to gain insights about the application domain. Therefore, one often resorts to linear models in combination with variable selection, thereby sacrificing some predictive power for presumptive interpretability. Here, we introduce the Feature Importance Ranking Measure (FIRM), which by retrospective analysis of arbitrary learning machines allows to achieve both excellent predictive performance and superior interpretation. In contrast to standard raw feature weighting, FIRM takes the underlying correlation structure of the features into account. Thereby, it is able to discover the most relevant features, even if their appearance in the training data is entirely prevented by noise. The desirable properties of FIRM are investigated analytically and illustrated in simulations.Comment: 15 pages, 3 figures. to appear in the Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), 200

Describing the longitudinal course of major depression using Markov models: Data integration across three national surveys

BACKGROUND: Most epidemiological studies of major depression report period prevalence estimates. These are of limited utility in characterizing the longitudinal epidemiology of this condition. Markov models provide a methodological framework for increasing the utility of epidemiological data. Markov models relating incidence and recovery to major depression prevalence have been described in a series of prior papers. In this paper, the models are extended to describe the longitudinal course of the disorder. METHODS: Data from three national surveys conducted by the Canadian national statistical agency (Statistics Canada) were used in this analysis. These data were integrated using a Markov model. Incidence, recurrence and recovery were represented as weekly transition probabilities. Model parameters were calibrated to the survey estimates. RESULTS: The population was divided into three categories: low, moderate and high recurrence groups. The size of each category was approximated using lifetime data from a study using the WHO Mental Health Composite International Diagnostic Interview (WMH-CIDI). Consistent with previous work, transition probabilities reflecting recovery were high in the initial weeks of the episodes, and declined by a fixed proportion with each passing week. CONCLUSION: Markov models provide a framework for integrating psychiatric epidemiological data. Previous studies have illustrated the utility of Markov models for decomposing prevalence into its various determinants: incidence, recovery and mortality. This study extends the Markov approach by distinguishing several recurrence categories

Including information about co-morbidity in estimates of disease burden: results from the World Health Organization World Mental Health Surveys

Background The methodology commonly used to estimate disease burden, featuring ratings of severity of individual conditions, has been criticized for ignoring co-morbidity. A methodology that addresses this problem is proposed and illustrated here with data from the World Health Organization World Mental Health Surveys. Although the analysis is based on self-reports about one's own conditions in a community survey, the logic applies equally well to analysis of hypothetical vignettes describing co-morbid condition profiles. Method Face-to-face interviews in 13 countries (six developing, nine developed; n=31 067; response rate=69.6%) assessed 10 classes of chronic physical and nine of mental conditions. A visual analog scale (VAS) was used to assess overall perceived health. Multiple regression analysis with interactions for co-morbidity was used to estimate associations of conditions with VAS. Simulation was used to estimate condition-specific effects. Results The best-fitting model included condition main effects and interactions of types by numbers of conditions. Neurological conditions, insomnia and major depression were rated most severe. Adjustment for co-morbidity reduced condition-specific estimates with substantial between-condition variation (0.24-0.70 ratios of condition-specific estimates with and without adjustment for co-morbidity). The societal-level burden rankings were quite different from the individual-level rankings, with the highest societal-level rankings associated with conditions having high prevalence rather than high individual-level severity. Conclusions Plausible estimates of disorder-specific effects on VAS can be obtained using methods that adjust for co-morbidity. These adjustments substantially influence condition-specific rating

Social capital in relation to depression, musculoskeletal pain, and psychosomatic symptoms: a cross-sectional study of a large population-based cohort of Swedish adolescents

<p>Abstract</p> <p>Background</p> <p>Social capital has lately received much attention in health research. The present study investigated whether two measures of subjective social capital were related to psychosomatic symptoms, musculoskeletal pain, and depression in a large population of Swedish adolescents.</p> <p>Methods</p> <p>A total of 7757 13-18 year old students anonymously completed the Survey of Adolescent Life in Vestmanland 2008 which included questions on sociodemographic background, neighbourhood social capital, general social trust, and ill health.</p> <p>Results</p> <p>Low neighbourhood social capital and low general social trust were associated with higher rates of psychosomatic symptoms, musculoskeletal pain, and depression. Individuals with low general social trust had more than three times increased odds of being depressed, three times increased odds of having many psychosomatic symptoms, and double the odds of having many symptoms of musculoskeletal pain.</p> <p>Conclusions</p> <p>The findings make an important contribution to the social capital - health debate by demonstrating relations between social capital factors and self-reported ill health in a young population.</p

Balkans' Asteraceae Species as a Source of Biologically Active Compounds for the Pharmaceutical and Food Industry

Herbal drugs are a useful source of different bioactive compounds. Asteraceae species, as the most widespread vascular plants, can be used both as food and as medicine due to the great diversity of recorded chemical components - different phenolic compounds, terpenes, carotenoids, vitamins, alkaloids, etc. The Balkan Peninsula is characterized by great diversity of plants from Asteraceae family, including presence of rare and endemic species. In this review, results of the survey of chemical composition and biological activity, mainly focusing on antioxidant, antimicrobial and anticancer effects of selected Balkans' Asteraceae species were provided. In addition, information on edible plants from Asteraceae family is presented, due to growing interest for the so-called 'healthy diet' and possible application of Balkans' Asteraceae species as food of high nutritional value or as a source of functional food ingredients.This is peer-reviewed version of the following article: Kostić, A.; Janacković, P.; Kolasinac, S. M.; Dajić-Stevanović, Z. Balkans’ Asteraceae Species as a Source of Biologically Active Compounds for the Pharmaceutical and Food Industry. Chemistry & Biodiversity 2020, 17 (6). [https://doi.org/10.1002/cbdv.202000097