Managing stormwater volume and quality has become an important issue in urban hydrology. Impervious cover associated with urbanization increases surface runoff volumes and degrades the water quality of urban streams and rivers. Cities with combined stormwater and sewer lines such as Philadelphia, have been tasked with decreasing runoff volumes to help reduce combined sewer overflows and improve the water quality of local waterways. The Philadelphia Water Department uses the Environmental Protection Agency’s Storm Water Management Model (SWMM) to predict runoff and evaluate if proposed stormwater infrastructure will reduce overflows. This study focused on the hydrogeological properties of grassy areas on and near Temple University’s main campus in north Philadelphia. The dataset includes terrestrial LiDAR, ground penetrating radar, soil moisture sensor, surface compaction, and double ring and mini disk infiltrometer measurements. These data were used to establish what controls infiltration rates in the area and also provide input parameters for a SWMM model. A terrestrial LiDAR scan of the Berks St. site, a grassy vacant lot located just east of Temple’s campus was used to generate a high-resolution digital elevation model. This elevation model was used to calculate the depression storage parameter, partition subcatchments in the SWMM model, and calculate a topographic wetness index (TWI). The TWI is a microtopography-based predictor of where runoff will collect and infiltrate. The TWI assumes a homogeneous infiltration rate and that runoff is routed by topography. This TWI was compared with soil moisture sensor measurements to determine if the microtopographic index could predict the majority of change in soil moisture at the field site. To determine if accounting for buried debris helped strengthen the TWI, GPR was used to map the extent and depth of subsurface objects. The results indicate that the TWI and GPR data could not predict where runoff would accumulate and then infiltrate because the TWI’s assumptions were not met. Measurements made with a double ring infiltrometer indicate that infiltration rates at the site were both high and heterogeneous (40 to 1060 mm/hr), allowing precipitation to infiltrate into the subsurface rather than become runoff, minimizing the influence of microtopography. Co-located surface compaction and double ring infiltrometer measurements at sites on and nearby Temple’s campus showed a negative correlation between surface compaction and infiltration rate (R2 = 0.67). Compacted areas on campus had lower infiltration rates and exhibited depression storage and runoff during rain events. Less compacted areas off campus had higher infiltration rates and exhibited no depression storage or runoff. The results of this study showed variance in surface compaction caused grassy areas around Temple’s campus respond differently to rain events. The results not only provided field-based parameter values for a SWMM model, but shows that compaction’s influence on infiltration should be considered when constructing a SWMM model. Runoff volumes in SWMM may be underestimated if compacted grassy areas are modeled with high infiltration rates. / Geology

The Ministry of Environment and Climate Change establishes design criteria for the sizing of Low Impact Development (LID) practices in the province of Ontario. The current sizing standards are based on the concept of the 90th percentile storm and require LIDs to provide enough storage capacity to store catchment runoff from a 25 mm rainfall event. The notion of 90th percentile storm means that 90% of all rainfall events have event volumes below a 25 mm rainfall event. This research examines the performance and cost of infiltration trenches and bioretention cells sized for alternative sizing standards ranging from 5–50 mm. Analytical probabilistic equations are used to determine the runoff reduction rates of infiltration trenches and bioretention cells, while the Sustainable Technologies Evaluation Program (STEP)’s LID Practices Costing Tool is used to estimate the overall cost of each LID. The costs are used to create a ratio denoted the fraction of maximum cost by dividing each cost by the cost of the 50 mm sized LID to receive a unitless ratio. This ratio is compared with the runoff reduction rates of both LIDs. Four different catchment sizes and various soil types are included to broaden the scope of the analysis and make the conclusions more dependable. Results indicate that the current sizing standard of 25 mm is probably too high and not cost-effective. In fact, depending on the type of soil and LID, little increase in performance occurs while there is a large increase in cost. A new methodology is proposed for setting sizing criteria for infiltration trenches and bioretention cells which focuses on achieving a desired capture efficiency instead of a required volume of rainfall. The method proposes using the capture efficiency, fraction of maximum cost and sizing criteria to determine what value is an economically more justifiable sizing standard based on individual catchment size and soil type. Use of the analytical probabilistic approach allows for the capture efficiency to be easily calculated and provides better sizing targets on a case by case basis. Recommending a specific capture efficiency can be more uniformly applied LID design in any soil conditions or any catchment size. This can reduce government spending when building LIDs and greatly reduce the possibility of over-design. / Thesis / Master of Applied Science (MASc)

Climate change is expected to lead to more intense and severe rainfall events in the future, significantly increasing the risk of urban flooding. This change, characterized by spatial and temporal shifts in precipitation patterns, presents a challenge to the capacity of existing urban drainage systems, which may lead to higher runoff volumes than they were initially designed to handle. Relying solely on enlarging stormwater infrastructure to tackle this issue could be expensive and may transfer the flooding risk downstream, rather than effectively resolving it. Furthermore, climate change may also lead to prolonged dry spells, potentially resulting in soil compaction and diminished soil infiltration rates. Given these considerations, it is essential to ensure urban drainage systems are both adaptable and space-efficient, with an enhanced capacity to manage the heightened rainfall caused by climate change.   As awareness of the hydrological and environmental impacts of urbanization on catchments grows, there has been a paradigm shift toward adopting green infrastructure solutions. These approaches diverge from traditional 'end-of-pipe' strategies, emphasizing more holistic and sustainable methods. The overall aim of this thesis is to investigate the implications of climatic conditions and geographic location on the retention and detention capacity of three types of infiltration-based facilities: a biofilter cell, a green roof, and a grass swale. A rainfall-runoff model of a biofilter cell and a green roof, combined with swale irrigation experiments, was used to evaluate the capacity of these facilities to reduce runoff volumes and attenuate peak flows. The analysis was conducted in four urban areas representing oceanic (Cfc), humid continental (Dfb), and subarctic (Dfc) climatic zones. The assessment also includes the effect of temporal and spatial variation of saturated hydraulic conductivities (ksat). Swale irrigation experiments were conducted to evaluate the effect of outflow controls on swale retention and detention capacities, under high soil moisture conditions.   Results for biofilter cells and green roofs showed that retention capacities were influenced by the combined effect of antecedent wetness, the extent of winter periods, and the frequency and intensity of rainfall events. Conversely, green roofs were found to have a higher sensitivity to initial soil conditions and antecedent dry weather periods, which was observed through a spread distribution of runoff volume reductions. Grass swales exhibited a large spatial distribution of hydraulic conductivity (ksat) values, with lower values at the swale bottom and higher values at the slope on the right side. Results from a full-scale infiltration test showed that overall, grass swale infiltration capacities are representative of the measured ksat values at the swale bottom. Finally, the presence of outflow controls was observed to enhance the retention and detention capacities of grass swales, even under high levels of soil moisture content. This increase in swale hydrological functionality was influenced by swale outflow controls, leading to greater utilization of the grass swale surface area. Differences between swales with outflow controls and those without were noted due to the effect of the additional storage capacity provided by an outlet control weir. Conversely, it was shown that swales without outflow controls experienced limited retention under high soil moisture content, restricted by the finite capacity of surface depression storage.

Drought conditions and wildfires can induce soil water repellency. Precipitation shifts are expected to exacerbate drought and wildfire in regions such as the southeastern United States, making it critical to understand how repellency affects water exchange processes in soil. The objectives of this dissertation were to 1) quantify the water vapor sorption dynamics of two clay minerals in which water repellency was induced; 2) identify if and for how long wildfires in humid hardwood forests induce water repellency, 3) evaluate if organic carbon content and hydrophobic functional groups explain actual and potential soil water repellency; and 4) understand how vertical position (i.e., depth) of water repellent layers affect infiltration processes. To meet these objectives, a laboratory test was first conducted examining water vapor sorption processes in water-repellent clay minerals. Next, a field study occurred in two forests that experienced wildfires in late 2016: Mount Pleasant Wildfire Refuge, Virginia, and Chimney Rock State Park, North Carolina, United States. Measurements include water drop penetration time, soil water content, and tension infiltration. Complimentary laboratory tests quantified potential soil water repellency, soil organic carbon content and hydrophobic functional groups. Results showed that water repellency inhibited water vapor condensation because of altered mineral surface potentials and decreased surface areas. Burned hardwood forest soils presented water repellency for > 1 year, though laboratory measurements presented different trends than in situ measurements. Total organic carbon content and hydrophobic functional groups correlated with soil water repellency measured in the laboratory but not the field. Soil water content was lower in burned than unburned soils, and negatively correlated with water repellency. Water repellency in the surface layers significantly reduced relative water infiltration rates, whereas subsurface water repellency did not, and water repellency persisted longer in sites with surface compared to subsurface water repellency. Finally, while the wildfires increased the occurrence of water repellency, they did not alter the underlying relationship between relative infiltration and surface water repellency. Altogether, this study provided new insight into water repellency effects on water partitioning at soil-atmosphere interfaces, and presented evidence of soil and hydrological changes induced by wildfires in humid hardwood forests. / PHD / Rising temperatures and shifting precipitation patterns that result from global climate change have the potential to induce long-term droughts, which may induce soil water repellency, as can wildfires that become more prevalent and damaging. Water repellency can alter the physical, chemical, and hydraulic properties of soil. These alterations may drive soil erosional processes and increase the mobility of surface-bound pollutants with the potential to reduce water quality and degrade down-gradient aquatic ecosystems. Thus, it is critical to understand how water repellency affects water movement in and through soils. Despite several decades of research towards this topic, some critical questions still remain. For example, how does water repellent soil influence water characteristics in the vapor phase (which is increasingly important under drought conditions)? Do wildfires in humid hardwood forests cause soil water repellency? If so, how long does water repellency persist? Do water repellency measurements using field and laboratory techniques correspond to one another? How does the depth of water repellent soil layer(s) affect water movement? In order to solve this questions, several tests were conducted in both field and laboratory. The field experiments occurred within forested hillslopes that underwent varying degrees of burning during widespread wildfires that affected the Southeastern United States in late 2016. Choosing two forested locations, we measured actual water repellency, soil moisture, and infiltration in burned and unburned sites after wildfire, and took loose samples for laboratory tests. In the lab, we tested potential water repellency on air-dried soil samples, soil organic carbon content and hydrophobic substance percentage. We also conducted water vapor sorption experiments to quantify water vapor exchange in two types of water repellent minerals: kaolinite and montmorillonite. The results showed that water repellency can affect water exchange between the subsurface and the atmosphere, by both limiting water vapor sorption and reducing liquid water infiltration. Soil organic matter and composition correlate well with potential water repellency measured in the laboratory, though less so with actual water repellency measured in the field. Instead, soil water content provided a high and inverse correlation with actual water repellency. Finally, water infiltration rates were influenced by the vertical position (depth) of water repellent layers, with water repellency at the soil surface causing much reduced initial infiltration rates compared to water-repellent layers in the subsurface.

Today, throughout the world, we are in the midst of a man-made environmental crisis. We must change how we consume and affect natural resources on the planet if we are to retain its richness of landscapes and biodiversity. It is our job as landscape architects to lead the way in changing the human relationship to natural resource consumption and building. My thesis asks the question, how can an understanding of landscape as a system give form to architecture? In natural systems nothing is wasted, everything is interconnected and self-sufficient at the same time. How can we model our buildings -- our built landscapes -- after nature? Three natural systems are key components to modeling nature: water, vegetation and energy. The landscapes that we have constructed for cars exemplify the problems we have ecologically. Cars produce greenhouse gases creating global warming. Highways and parking lots denude the vegetative habitat and lead to excessive water runoff polluting the watersheds. Solving the car problem goes a long way to setting an example for ultimately resolving ecological development issues. Cars are both the epitome of freedom and environmental degradation. Joni Mitchell put it eloquently with "they paved paradise put up a parking lot." My studio project is a mixed use parking facility fabricating the natural systems of water, energy and vegetation in order to mitigate environmental problems as well as resolve the practical necessity of where to put cars in crowded urban centers. Park Park puts the paradise back into the pavement. / Master of Landscape Architecture

No description available.

Surface coal mining has altered Appalachian landscapes, affecting water quality and aquatic ecology. Valley fills created from excess overburden are prominent features of many mined landscapes. Increased total dissolved solids (TDS), as measured by its surrogate specific conductance (SC), is a significant water quality concern related to the exposure of fresh mineral surfaces to weathering in valley fills. Specific conductance levels in waters draining Appalachian mined areas are highly variable, yet the causes for this variability are not well known. Here we sought to improve understanding of such variability by investigating the interior subsurface structure and hydrologic flowpaths within a series of valley fills and relating that to valley fill characteristics such as age and construction method. We used electrical resistivity imaging (ERI) to investigate the subsurface structure of four valley fills in two dimensions. We combined ERI with artificial rainfall to investigate the location and transit time of hydrologic preferential infiltration flowpaths through the fills. Finally, we used our ERI results in conjunction with SC data from effluent streams to improve understanding of SC relationship to fill flowpaths and characteristics. ERI results indicated considerable variability in substrate type and widespread presence of preferential infiltration flowpaths among the valley fills studied. We estimated an average preferential flowpath length of 6.6 meters, average transit time of 1.4 hours, and average velocity of 5.1 m/h or 0.14 cm/s through preferential infiltration flowpaths. ERI successfully distinguished fills constructed using methods of conventional loose-dump and experimental controlled-material compacted-lift construction. Conventional fills had greater ranges of subsurface resistivity, indicating a wider range of substrate types and/or more variable moisture content. Conventional fills also showed more accumulation of water within the fill during artificial rainfall, possibly indicating more quick/deep preferential infiltration flowpaths than in the experimental fill. Relationships between other fill characteristics as well as stream effluent SC were not related in a statistically significant way to fill structure or flowpaths. ERI appears to be a robust non-invasive technique that provides reliable information on valley fill structure and hydrology, and experimental compacted-lift valley fill construction produces significantly altered hydrologic response, which in turn affects downstream SC. / MS / Surface coal mining has altered Appalachian landscapes, affecting water quality and aquatic ecology. Valley fills created from excess mine spoil are prominent features of many mined landscapes. The streams draining valley fills often have very poor water quality, including high levels of increased total dissolved solids (TDS) related to weathering of mine spoils within valley fills. In this work, we investigated the subsurface structure of a series of valley fills and identified preferential hydrologic flowpaths, which are the “paths of least resistance” water follows for rapid infiltration. We related our results to various valley fill characteristics such as age and construction method. We found that the subsurface of a conventionally built fill tends to have more variation in material and/or moisture content than a fill built with an experimental construction method. Conventional fills also showed more accumulation of water within the fill during artificial rainfall experiments, possibly indicating more quick/deep preferential infiltration flowpaths than in the experimental fill.

A rural-urban divide in health status and healthcare infrastructure has been well-documented in the U.S., where populations residing in census regions classified as rural often exhibit more negative health outcomes, adverse health behaviors, and have reduced access to affordable and proximal health services, compared to their urban and peri-urban counterparts. However, it is important to note that such disparities vary based on specific rural regions and individual circumstances. Rural areas may face elevated risk factors for infectious diseases such as increased proximity to wildlife and livestock and disproportionately high reliance on private, non-federally regulated, primary drinking water sources. Chronic conditions prevalent in rural communities such as diabetes and hypertension are frequently linked with longer duration and higher severity of symptoms than in urban areas; this association suggests that the risk of exposure to infectious diseases and the likelihood of progression to serious illness and hospitalization may be elevated, although this is not universally the case across all rural settings. Alongside documented urban-rural health disparities, there also exist disparities in the nature and quality of data on health-related behaviors, outcomes, and service provision in rural areas compared to urban and peri-urban regions. In this dissertation, two key environmental matrices –drinking water and wastewater– were highlighted as vectors of information to better estimate levels of contaminant exposures and health outcomes in rural communities. First, baseline data on drinking water contaminant levels and associated health outcome data were highlighted as crucial for refining holistic exposure estimates as well as understanding drinking water related health burdens in rural communities where a larger proportion of households use private drinking water sources, such as well water, that are not federally regulated. Second, systematic sampling and testing of pathogen biomarkers in wastewater to non-invasively measure population-level health status, also known as wastewater based surveillance (WBS) and, depending on the context, wastewater based epidemiology (WBE) is not constrained by disadvantages of clinical testing, e.g., limited health-care access, long travel times to testing facilities, delay between symptom-onset and testing. Thus, expanded implementation of WBS in rural communities is proposed here as a strategy to address data disparities in clinical testing for infectious diseases. Collectively, this dissertation advances knowledge on estimated drinking water contaminant levels, exposures, and associated public health outcomes and corresponding research gaps in rural Appalachian U.S., and elucidates pathways toward best practices and considerations for public-health focused wastewater testing adoption in rural communities. For the latter, the question of whether WBS challenges unique to rural wastewater systems hinder application of WBS in small, rural communities was explored, as well as methods to advance best-practices for rural WBS. To summarize existing publicly available peer-reviewed literature on drinking water contaminants in rural Appalachian U.S., in Chapter 2, a systematic review and meta-analysis of microbial and chemical drinking water contaminants was performed. Key contaminants were identified as being elevated beyond regulatory, health-based, maximum contaminant levels in our meta-analyses from rural drinking water sources in Appalachia, including E coli, lead, arsenic, uranium. Overall, we found data on drinking water source quality under baseline conditions (i.e., rather than post anomalous contamination events such as chemical spills) in rural Appalachian U.S. was sparse relative to widespread media coverage on the issue. Epidemiologic-based research studies that collected both drinking water exposure data and paired health outcome data were also limited. As a result, although some instances of anomalously high levels of drinking water contaminants were identified in rural Appalachia from the published literature, we could not obtain a clear picture of baseline exposures to drinking water contaminants in most rural Appalachian communities, highlight need to address these knowledge gaps. In Chapter 3, to evaluate whether wastewater could serve as a reliable metric for estimating community circulation of viruses and antimicrobial resistance (AMR) markers, even when sourced from aging and low-resource sewer collection networks, a 12-month wastewater monitoring study was conducted in a small, rural sewer conveyance system with pronounced infrastructural challenges. Specifically, the field site under study was compromised with heavy inflow and infiltration (IandI). Detection rates and concentrations of viral, AMR, and human fecal markers were grouped by levels of IandI impact across the sewershed, and location-, date-, and sample- specific variables were assessed for their relative influence on viral, AMR, and human fecal marker signal using generalized linear models (GLMs). We found that while IandI likely adversely impacted the magnitude of wastewater biomarker signal to some extent throughout the sewershed, especially up-sewer at sites with more pronounced IandI, substantial diminishment of wastewater signal at WWTP influent was not observed in response to precipitation events. Thus, our data indicated that WWTP influent sampling alone can still be used to assess and track community circulation of pathogens in heavily IandI impacted systems, particularly for ubiquitously circulating viruses less prone to dilution induced decay. Delineations were also made for what circumstances up-sewer sampling may be necessary to better inform population shedding of pathogens, especially where IandI is prevalent. Various normalization strategies have been proposed to account for sources of variability for deriving population-level pathogen shedding from wastewater, including those introduced by IandI-driven dilution. Thus, in Chapter 4, we evaluated the temporal and spatial variability of viral and AMR marker signal in wastewater at different levels of IandI, both unnormalized and with the adoption of several normalization strategies. We found that normalization using physicochemical-based wastewater strength metrics (chemical oxygen demand, total suspended solids, phosphate, and ammonia) resulted in higher temporal and site-specific variability of SARS-CoV-2 and human fecal biomarker signal compared to unnormalized data, especially for viral and AMR marker signal measured in wastewater from sites with pronounced IandI. Viral wastewater signal normalized to physicochemical wastewater strength metrics and flow data also closely mirrored precipitation trends, suggesting such normalization approaches may more closely scale wastewater trends towards precipitation patterns rather than per capita signal in an IandI compromised system. We also found that in most cases, normalization did not significantly alter the relationship between wastewater trends and clinical infection trends. These findings suggest a degree of caution is warranted for some normalization approaches, especially where precipitation driven IandI is heightened. However, data and findings largely supported the utility of using human fecal markers such as crAssphage for normalizing wastewater signal to address site-specific differences in dilution levels, since viral signal scaled to this metric did not result in strong correlations between precipitation and wastewater trends, higher spatial and temporal variation was not observed, and strong correlations were observed between viral signal and viral infection trends. Finally, in chapter 5, we assessed the relationship between monthly Norovirus GII, Rotavirus, and SARS-CoV-2 wastewater trends with seasonal infection trends for each of the viruses to ascertain whether WBE could be used in a rural sewershed of this size with substantial IandI impacts to track and potentially predict population level infection trends. Though up-sewer, or near-source sampling, at sites with permanent IandI impacts did not exhibit a clear relationship with seasonal infection trends for Rotavirus, SARS-CoV-2, and Norovirus GII, WWTP influent signal and consensus signals aggregated from multiple up-sewer sites largely mirrored expected seasonal trends. Findings also suggested that for more ubiquitous viral targets, such as SARS-CoV-2, viral trends measured at WWTP influent in a small IandI impacted system may still provide a sufficiently useful measure of infection trends to inform the use of WBE (assuming appropriate normalization to sewershed population). These findings elucidate the potential utility and relative robustness of wastewater testing to ascertain community-level circulation of pathogens in small, rural sewersheds even those compromised by extensive IandI inputs. Overall, this dissertation examined drinking water and wastewater as critical metrics for assessing contaminant exposures and infectious disease trends in rural communities, particularly in the context of small, rural communities which tend to have more limited health infrastructure and lower-resource wastewater systems. Overall, findings underscore the need for baseline data on drinking water quality by identifying gaps in current knowledge and calling for further research to better understand drinking water contaminant exposure levels in rural areas. Wastewater as a non-invasive, population-level health metric was evaluated in the context of a small, rural sewer system overall, and by varying observed levels of IandI, as well as associated tradeoffs for normalization adoption. By evaluating these environmental surveillance metrics using both desk-based and field-based research study designs, findings from this dissertation offer valuable insights and practical recommendations for improving baseline drinking water quality monitoring and wastewater pathogen testing, all with the overarching goal of supporting more targeted public health interventions in rural settings. / Doctor of Philosophy / In the United States, there is a significant health and healthcare gap between rural and urban areas. Rural communities often face worse health outcomes, poorer health behaviors, and have less access to affordable and nearby healthcare services compared to their urban and peri-urban counterparts. Additionally, rural areas are exposed to higher risks for infectious diseases due to closer proximity to wildlife and livestock and proportionately lower access to regulated drinking water sources. Chronic conditions like diabetes and hypertension, which are more common in rural populations, can exacerbate the severity and duration of symptoms for infectious diseases, potentially leading to more serious illness and hospitalizations. Despite these heightened risks, data on health behaviors, outcomes, and healthcare services in rural areas is often lacking and less comprehensive compared to urban regions. This dissertation investigates two promising avenues of improving monitoring to provide information needed to better understand and address contaminant exposures and health trends in rural communities: drinking water and wastewater. Firstly, this dissertation underscores the importance of establishing baseline data on drinking water quality. This is essential for accurately estimating exposure levels and understanding the health impacts associated with elevated levels of drinking water contaminants, particularly in rural areas where a higher share of primary drinking water sources is unregulated by the federal government compared to urban areas. This study reveals significant gaps in current knowledge and highlights the need for more research to provide a clearer picture of drinking water quality in these communities. Secondly, this dissertation explores the use of wastewater as a non-invasive tool for assessing community health. This method, known as wastewater-based surveillance (WBS) or wastewater-based epidemiology (WBE), offers a way to measure population-level health trends without relying on clinical testing, which can be limited by factors such as access to healthcare and delays in testing. The dissertation evaluates how effective wastewater monitoring can be in small, rural sewer systems, even when these systems face challenges like aging infrastructure and significant inflow and infiltration (IandI) from groundwater and surface water. It examines how different normalization strategies for wastewater data can influence the reliability of this method and how wastewater testing can be adapted to account for varying levels of IandI. Overall, the dissertation provides valuable insights into the effectiveness of using drinking water and wastewater as environmental metrics for informing public health intervention strategies in rural settings. It offers justifications for improving drinking water quality monitoring and wastewater testing practices, aiming to support more targeted and effective public health interventions in rural communities. By addressing the challenges and limitations associated with these environmental monitoring strategies this research contributes to a better understanding of how to reduce health data disparities in rural areas.

Tableau d'honneur de la Faculté des études supérieures et postdoctorales, 2018-2019 / Le diabète de type 2 est fortement associé à l’obésité et la prévalence de ces deux conditions progresse rapidement dans les sociétés industrialisées comme en développement. La relation entre ces deux conditions n’est pas complètement élucidée, mais une forte infiltration de lipides dans le muscle squelettique, évaluable entre autres par tomographie axiale au niveau de la micuisse, est associée à l’obésité et pourrait être impliquée dans le développement de la résistance à l’insuline et du diabète de type 2 chez les personnes en surpoids ou obèses. L’obtention d’une image par tomographie axiale entraîne une exposition à des radiations pour les participants des projets de recherche. Nous avons émis l’hypothèse que l’analyse des muscles à partir d’une coupe du tronc au niveau L4-L5, mesure déjà incluse dans les projets ciblant l’adiposité abdominale, permettrait de remplacer la mi-cuisse pour l’évaluation de l’infiltration de lipides dans le muscle squelettique en regard du profil de risque cardiométabolique, diminuant ainsi l’exposition totale des sujets. Les présents travaux de recherche comportent deux phases d’analyses, une transversale et une longitudinale. Nos résultats indiquent que l’infiltration de lipides dans les muscles du tronc est associée au profil de risque cardiométabolique de façon similaire à l’infiltration de lipides dans les muscles de la cuisse, et ce, autant lors d’analyses transversales que lors de l’étude des changements induits par une intervention ciblant les habitudes de vie. En conclusion, nos résultats indiquent que l’analyse d’une image de l’abdomen permet d’étudier l’impact de l’infiltration lipidique dans les muscles sur le profil de risque cardiométabolique et peut donc remplacer l’analyse d’une coupe de la mi-cuisse. / Type 2 diabetes is strongly associated with obesity and the prevalence of both conditions has increased rapidly in industrialized as well as developing countries, with major consequences on population health. The mechanisms responsible for this association are not fully understood, but a high muscular lipid content, measurable by computed tomography at mid-thigh level, has been shown to be elevated in obesity and this phenomenon could play a role in the development of insulin resistance and type 2 diabetes in overweight/obese individuals. Considering that performing an additional scan at the mid-thigh level implies more radiation exposure for participants, we formulated the hypothesis that trunk muscles at L4-L5 level, a slice usually obtained in order to assess abdominal adiposity, could replace the mid-thigh in the evaluation of muscular fat infiltration in the evaluation of cardiometabolic risk. The present study was conducted in two phases of analyses, cross-sectional and longitudinal. Our results suggest that lipid infiltration of the trunk muscles is at least as strongly associated to the cardiometabolic profile as that of the mid-thigh muscles, both for the baseline values and for the changes induced by an intervention program targeting lifestyle. In summary, our results suggest that an abdominal scan dispenses with the need for a midthigh scan when investigating the impact of muscular lipid infiltration on the cardiometabolic risk profile.

No description available.