2,673 research outputs found

    Systemic function impairment and neurodegeneration in the general population

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    The ins and outs of open-angle Glaucoma:drugs, diet, and defecation

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    Glaucoma is the leading cause of irreversible blindness and second leading cause of blindness. The primary aim of this thesis is to provide insight into the role of systemic effectsin the pathophysiology of OAG.<br/

    Keep on track:Monitoring growth and development in children born preterm and full-term

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    Environmental factors in early life influence early development and growth, and influence long-term health. In this thesis we showed that in premature infants, the length and growth of the cerebral cortex (corpus callosum) is a good marker of brain growth and a predictor of later neurological development. An eye-tracking test (watching a video) at the age of 1 year also appeared to be a predictive factor for overall cognitive and motor development 1 year later. We also found that weight gain after preterm birth is associated with body composition in childhood. We also compared 2 methods of measuring body composition in children (DXA and ADP) and found that the results of fat mass (percentage) and fat-free mass at 3-5 years of age differ significantly between both methods, and that these differences are greater in very preterm children compared to full-term children. We present improvements to the algorithm to improve results with ADP. We also investigated sleep and found that parent-reported sleep characteristics and problems are similar between very preterm and full-term children at the age of 3 years. In the general population, we have shown that low birth weight (&lt;2500 grams) and growth retardation during fetal life and childhood are associated with longer sleep duration and higher sleep efficiency at 10-15 years of age. Furthermore, at the same school age, greater intraday variability (fragmentation of the 24-hour activity rhythm) was associated with a higher fat mass index and higher visceral fat mass in boys

    Photocatalysis in the Wastewater Treatment

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    The use of photocatalysis for wastewater treatment is an important area of research, which is not yet fully exploited at an industrial level and has significant potential in the disposal of many industrial effluents, particularly the effluents that are difficult to treat by conventional treatment processes. This reprint tries to know the latest advances in the field of wastewater treatment by photocatalysis. In this sense, it is worth mentioning the treatments based on photolysis, TiO2/solar light, oxidants/ultraviolet irradiation, oxidants/catalyst/ultraviolet irradiation, etc. In addition, the reprint describes catalyst manufacturing methods and reaction mechanisms

    Combined Nutrition and Exercise Interventions in Community Groups

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    Diet and physical activity are two key modifiable lifestyle factors that influence health across the lifespan (prevention and management of chronic diseases and reduction of the risk of premature death through several biological mechanisms). Community-based interventions contribute to public health, as they have the potential to reach high population-level impact, through the focus on groups that share a common culture or identity in their natural living environment. While the health benefits of a balanced diet and regular physical activity are commonly studied separately, interventions that combine these two lifestyle factors have the potential to induce greater benefits in community groups rather than strategies focusing only on one or the other. Thus, this Special Issue entitled “Combined Nutrition and Exercise Interventions in Community Groups” is comprised of manuscripts that highlight this combined approach (balanced diet and regular physical activity) in community settings. The contributors to this Special Issue are well-recognized professionals in complementary fields such as education, public health, nutrition, and exercise. This Special Issue highlights the latest research regarding combined nutrition and exercise interventions among different community groups and includes research articles developed through five continents (Africa, Asia, America, Europe and Oceania), as well as reviews and systematic reviews

    Evaluating the sustainability and resiliency of local food systems

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    With an ever-rising global population and looming environmental challenges such as climate change and soil degradation, it is imperative to increase the sustainability of food production. The drastic rise in food insecurity during the COVID-19 pandemic has further shown a pressing need to increase the resiliency of food systems. One strategy to reduce the dependence on complex, vulnerable global supply chains is to strengthen local food systems, such as by producing more food in cities. This thesis uses an interdisciplinary, food systems approach to explore aspects of sustainability and resiliency within local food systems. Lifecycle assessment (LCA) was used to evaluate how farm scale, distance to consumer, and management practices influence environmental impacts for different local agriculture models in two case study locations: Georgia, USA and England, UK. Farms were grouped based on urbanisation level and management practices, including: urban organic, peri-urban organic, rural organic, and rural conventional. A total of 25 farms and 40 crop lifecycles were evaluated, focusing on two crops (kale and tomatoes) and including impacts from seedling production through final distribution to the point of sale. Results were extremely sensitive to the allocation of composting burdens (decomposition emissions), with impact variation between organic farms driven mainly by levels of compost use. When composting burdens were attributed to compost inputs, the rural conventional category in the U.S. and the rural organic category in the UK had the lowest average impacts per kg sellable crop produced, including the lowest global warming potential (GWP). However, when subtracting avoided burdens from the municipal waste stream from compost inputs, trends reversed entirely, with urban or peri-urban farm categories having the lowest impacts (often negative) for GWP and marine eutrophication. Overall, farm management practices were the most important factor driving environmental impacts from local food supply chains. A soil health assessment was then performed on a subset of the UK farms to provide insight to ecosystem services that are not captured within LCA frameworks. Better soil health was observed in organically-farmed and uncultivated soils compared to conventionally farmed soils, suggesting higher ecosystem service provisioning as related to improved soil structure, flood mitigation, erosion control, and carbon storage. However, relatively high heavy metal concentrations were seen on urban and peri-urban farms, as well as those located in areas with previous mining activity. This implies that there are important services and disservices on farms that are not captured by LCAs. Zooming out from a focus on food production, a qualitative methodology was used to explore experiences of food insecurity and related health and social challenges during the COVID-19 pandemic. Fourteen individuals receiving emergency food parcels from a community food project in Sheffield, UK were interviewed. Results showed that maintaining food security in times of crisis requires a diverse set of individual, household, social, and place-based resources, which were largely diminished or strained during the pandemic. Drawing upon social capital and community support was essential to cope with a multiplicity of hardship, highlighting a need to develop community food infrastructure that supports ideals of mutual aid and builds connections throughout the food supply chain. Overall, this thesis shows that a range of context-specific solutions are required to build sustainable and resilient food systems. This can be supported by increasing local control of food systems and designing strategies to meet specific community needs, whilst still acknowledging a shared global responsibility to protect ecosystem, human, and planetary health

    Anwendungen maschinellen Lernens fĂŒr datengetriebene PrĂ€vention auf Populationsebene

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    Healthcare costs are systematically rising, and current therapy-focused healthcare systems are not sustainable in the long run. While disease prevention is a viable instrument for reducing costs and suffering, it requires risk modeling to stratify populations, identify high- risk individuals and enable personalized interventions. In current clinical practice, however, systematic risk stratification is limited: on the one hand, for the vast majority of endpoints, no risk models exist. On the other hand, available models focus on predicting a single disease at a time, rendering predictor collection burdensome. At the same time, the den- sity of individual patient data is constantly increasing. Especially complex data modalities, such as -omics measurements or images, may contain systemic information on future health trajectories relevant for multiple endpoints simultaneously. However, to date, this data is inaccessible for risk modeling as no dedicated methods exist to extract clinically relevant information. This study built on recent advances in machine learning to investigate the ap- plicability of four distinct data modalities not yet leveraged for risk modeling in primary prevention. For each data modality, a neural network-based survival model was developed to extract predictive information, scrutinize performance gains over commonly collected covariates, and pinpoint potential clinical utility. Notably, the developed methodology was able to integrate polygenic risk scores for cardiovascular prevention, outperforming existing approaches and identifying benefiting subpopulations. Investigating NMR metabolomics, the developed methodology allowed the prediction of future disease onset for many common diseases at once, indicating potential applicability as a drop-in replacement for commonly collected covariates. Extending the methodology to phenome-wide risk modeling, elec- tronic health records were found to be a general source of predictive information with high systemic relevance for thousands of endpoints. Assessing retinal fundus photographs, the developed methodology identified diseases where retinal information most impacted health trajectories. In summary, the results demonstrate the capability of neural survival models to integrate complex data modalities for multi-disease risk modeling in primary prevention and illustrate the tremendous potential of machine learning models to disrupt medical practice toward data-driven prevention at population scale.Die Kosten im Gesundheitswesen steigen systematisch und derzeitige therapieorientierte Gesundheitssysteme sind nicht nachhaltig. Angesichts vieler verhinderbarer Krankheiten stellt die PrĂ€vention ein veritables Instrument zur Verringerung von Kosten und Leiden dar. Risikostratifizierung ist die grundlegende Voraussetzung fĂŒr ein prĂ€ventionszentri- ertes Gesundheitswesen um Personen mit hohem Risiko zu identifizieren und Maßnah- men einzuleiten. Heute ist eine systematische Risikostratifizierung jedoch nur begrenzt möglich, da fĂŒr die meisten Krankheiten keine Risikomodelle existieren und sich verfĂŒg- bare Modelle auf einzelne Krankheiten beschrĂ€nken. Weil fĂŒr deren Berechnung jeweils spezielle Sets an PrĂ€diktoren zu erheben sind werden in Praxis oft nur wenige Modelle angewandt. Gleichzeitig versprechen komplexe DatenmodalitĂ€ten, wie Bilder oder -omics- Messungen, systemische Informationen ĂŒber zukĂŒnftige GesundheitsverlĂ€ufe, mit poten- tieller Relevanz fĂŒr viele Endpunkte gleichzeitig. Da es an dedizierten Methoden zur Ex- traktion klinisch relevanter Informationen fehlt, sind diese Daten jedoch fĂŒr die Risikomod- ellierung unzugĂ€nglich, und ihr Potenzial blieb bislang unbewertet. Diese Studie nutzt ma- chinelles Lernen, um die Anwendbarkeit von vier DatenmodalitĂ€ten in der PrimĂ€rprĂ€ven- tion zu untersuchen: polygene Risikoscores fĂŒr die kardiovaskulĂ€re PrĂ€vention, NMR Meta- bolomicsdaten, elektronische Gesundheitsakten und Netzhautfundusfotos. Pro Datenmodal- itĂ€t wurde ein neuronales Risikomodell entwickelt, um relevante Informationen zu extra- hieren, additive Information gegenĂŒber ĂŒblicherweise erfassten Kovariaten zu quantifizieren und den potenziellen klinischen Nutzen der DatenmodalitĂ€t zu ermitteln. Die entwickelte Me-thodik konnte polygene Risikoscores fĂŒr die kardiovaskulĂ€re PrĂ€vention integrieren. Im Falle der NMR-Metabolomik erschloss die entwickelte Methodik wertvolle Informa- tionen ĂŒber den zukĂŒnftigen Ausbruch von Krankheiten. Unter Einsatz einer phĂ€nomen- weiten Risikomodellierung erwiesen sich elektronische Gesundheitsakten als Quelle prĂ€dik- tiver Information mit hoher systemischer Relevanz. Bei der Analyse von Fundusfotografien der Netzhaut wurden Krankheiten identifiziert fĂŒr deren Vorhersage Netzhautinformationen genutzt werden könnten. Zusammengefasst zeigten die Ergebnisse das Potential neuronaler Risikomodelle die medizinische Praxis in Richtung einer datengesteuerten, prĂ€ventionsori- entierten Medizin zu verĂ€ndern

    An investigation into mild traumatic brain injury identification, management, and mitigation

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    Concussion is classified as a mild traumatic brain injury which can be induced by biomechanical forces such as a physical impact to the head or body, which results in a transient neurological disturbance without obvious structural brain damage. Immediate access to tools that can identify, diagnosis and manage concussion are wide ranging and can lack consistency in application. It is well documented that there are frequent incidences of concussion across amateur and professional sport such as popular contact sports like rugby union. A primary aim of this thesis was to establish the current modalities of ‘pitch side’ concussion management, identification, and diagnosis across amateur and professional sporting populations. Furthermore, the research sought to understand existing concussion management and concussion experiences by means of recording the player’s experiences and perceptions (retired professional rugby union players). These qualitative studies sought to gain insights into concussion experiences, the language used to discuss concussion and the duty of care which medical staff, coaching personnel, and club owners have towards professional rugby players in their employment. In addition, possible interventions to reduce the incidence of concussion in amateur and professional sports were investigated. These included a ‘proof of concept’ using inertial measurement units and a smartphone application, a tackle technique coaching app for amateur sports. Other research data investigating the use of neurological function data and neuromuscular fatigue in current professional rugby players as a novel means of monitoring injury risk were included in this research theme. The findings of these studies suggest that there is an established head injury assessment process for professional sports. However, in amateur sport settings, this is not the existing practice and may expose amateur players to an increased risk of post-concussion syndrome or early retirement. Many past professional rugby union players stated that they did not know the effects of cumulative repetitive head impacts. They discussed how they minimised and ignored repeated concussions due to peer pressure or pressure from coaches or their own internal pressures of maintaining a livelihood. These data suggest that players believed that strong willed medical staff, immutable to pressures from coaching staff or even athletes themselves, were essential for player welfare and that club owners have a long-term duty of care to retired professional rugby union players. However, there are anecdotal methods suggested to reduce concussion incidence. For example, neck strengthening techniques to mitigate against collision impacts. There is, no longitudinal evidence to suggest that neck strength can reduce the impacts of concussion in adult populations . Additionally, other factors such as lowering the tackle height in the professional and amateur game is currently being investigated as a mitigating factor to reduce head injury risk. The final theme of the thesis investigated possible methods to reduce injury incidence in amateur and professional athletes. The novel tackle technique platform could assist inexperienced amateur coaches on how to coach effective tackle technique to youth players. The findings from the neurological function data suggests that this may be an alternative way for coaches to assess and gather fatigue data on professional rugby union players alongside additional subjective measures and neuromuscular function data. Recently, the awareness of concussion as an injury and the recognition of concussion in many sports settings has improved. These incremental improvements have led to increased discussion regarding possible measures to mitigate the effects of concussion. There are many additional procedures to be implemented before a comprehensive concussion management is universally available, particularly in amateur and community sports. These necessary processes could be technological advances (e.g., using smart phone technology) for parents and amateur coaches to assist in the early identification of concussion or evidence-based concussion reduction strategies

    Obesity Risk and Comorbidities Among Colombians in New York City and in Colombia

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    Introduction: The prevalence of obesity and overweight in adults and children continues to increase worldwide, accounting for the mortality and morbidity from several diseases. Obesity disproportionally impacts Latinos in the United States (U.S.), and despite their diversity in origins, ancestry, and culture, it is still unclear the burden of obesity by specific Latino groups. For example, little information is available about how obesity impacts Colombians in the U.S. (the largest South American population). New evidence also indicates that Latino immigrants may no longer be arriving with healthy weight status to the U.S. because Latin American countries are undergoing epidemiologic and nutrition transitions. More obesity research is required to understand the heterogeneity of Latinos in the U.S. and to examine the relationship between migration and obesity, including comparisons of Latino immigrant populations in the U.S. (e.g., Colombians in New York City (NYC)) with their source population in Latin America. Furthermore, Latino children embedded in migrant networks with relatives who live in the U.S. are at increased risk of excess weight. It is unclear if the same findings apply to intraregional migration networks in Latin America, such as Colombian children with migrant parents from South-to-South migration trajectories. Methods: Secondary analysis of data from two public health surveys (i.e., NYC Community Health Survey (NYC CHS) years 2013-2017 and the National Survey of the Nutritional Situation (ENSIN) year 2015) using weighted multivariable logistic regression models. The first study (Chapter 2) estimates how obesity (Body Mass Index (BMI) ≄30 kg/m2) may differ between adult Colombians and the four largest Latino adult populations in NYC (i.e., Puerto Rican, Mexican, Ecuadorian, and Dominican) controlling for lifestyle behaviors (i.e., daily consumption of sugar-sweetened beverages (SSB) and PA in the past 30 days), health status (i.e., Type 2 Diabetes and Hypertension diagnosis) and socio-demographic factors (e.g., age, gender, education level), using data from the NYC CHS 2013-2017. The second study (Chapter 3) compares obesity prevalence between adult immigrant Colombians residing in NYC and adult nonimmigrant Colombians residing in main Colombia cities and their home country controlling for age, gender, education level, and daily SSB consumption, using data from the ENSIN 2015 and NYC CHS 2013-2017. The third study (Chapter 4) explores the role of migrant parents on excess weight (BMI z-score ≄1) among children in Colombia, controlling for demographics (e.g., age, gender), behavior indicators (e.g., compliance with recommended PA and daily intake of fried food, fruits, and vegetables), urbanicity, and household indicators (e.g., wealth index, family characteristics, reasons for emigration, food insecurity), using data from ENSIN 2015. Results: In Chapter 2, we found that obesity prevalence among Colombians (23.8%; 95% CI 18.8, 29.5) was significantly lower than among Mexicans (36.8%; 95% CI 31.5, 42.4) and Puerto Ricans (36.3%; 95% CI 31.7, 41.3). After full adjustment, the prevalence ratios (PR) of obesity remained significantly lower for Colombians (PR=0.80; 95% CI 0.64-1.00) compared to Mexicans. No significant differences were found in the prevalence of obesity for comparisons between Colombians and Ecuadorians or Dominicans. In Chapter 3, we found that obesity prevalence was 49-62% greater for immigrant Colombians living in NYC when compared to nonimmigrant Colombians living in their home country (PR=1.49; 95% CI 1.08, 2.07) and in main Colombian cities (PR=1.62; 95% CI 1.01, 2.62). Sex strengthened these differences as Colombian immigrant men in NYC were 72% more likely to have obesity compared to nonimmigrant men living in their home country and in main cities (PR=1.72; 95% CI 1.03, 2.87). No significant differences were found in the adjusted models among women. In Chapter 4, we found that most migrant parents returned to Colombia from Venezuela (84%) and reported higher moderate and severe household food insecurity than non-migrant parents (59% versus 32%). Models excluding household food insecurity showed that PRs for excess weight were 48% lower for children with return migrant parents (PR=0.52; 95% CI 0.27, 0.99) compared to children with non-migrant parents. After adjustment for household food insecurity, the PR comparing both groups was no longer significantly different. Discussion: Colombians in NYC experience a higher prevalence of obesity compared to non-Latino Whites. However, Colombians have a lower prevalence of obesity compared to other Latino groups in NYC, such as Mexicans and Puerto Ricans. Any protection among men in Colombia is no longer present after immigration to the U.S., while Colombian women have a similarly high prevalence of obesity both in Colombia and NYC. Colombian children with migrant parents from other South American countries experienced less excess weight than children with non-migrant parents; however, disparities in household food insecurity largely explained the difference. Future research focused on understudied Latino populations in the U.S. may further our understanding of the diversity in the community in terms of obesity, obesity-related risk factors, and migration networks, which will inform public health efforts to combat obesity and other health risks. Collectively, the findings of this dissertation support the need to: disaggregate Latinos into distinct cultural groups in future obesity research; prioritize public health action for adult women in Colombia and both Colombian men and women in the U.S.; prioritize migrant populations in Colombia for public health efforts addressing food insecurity; and support binational obesity initiatives to prevent and avert the long-term consequences of obesity in Latino communities in the U.S. and countries of origin
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