Exploration de la fusion des informations pour améliorer la fiabilité locale d'une carte forestière

Sur la carte forestière traditionnelle du Québec, les frontières entre les peuplements sont représentées par des lignes, les estimations du volume ligneux proviennent de regroupements des échantillons de terrain (p-e) et sont assignées aux strates forestières, qui sont considérées comme homogènes pour les attributs cartographiés. L’objectif général de cette recherche est d’explorer comment la complémentarité de différentes méthodes peuvent permettre de mieux caractériser les frontières entre les peuplements, les strates forestières et les estimations du volume ligneux et ce, en fusionnant les informations de la carte et des p-e. Le contraste et le contexte spatial des frontières sont quantifiés, tout comme le contexte des peuplements. Ces aspects sont complémentaires et ils permettent de détecter les secteurs du territoire où l’identification des frontières serait plus facile. Il existe une relation statistiquement significative entre le contraste des variables examinées et la probabilité d’existence d’une frontière. D’autres frontières sont identifiées à partir des p-e. Elles correspondent aux groupes de p-e semblables ainsi qu’aux discontinuités spatiales des variables. Les deux types de frontières coïncident lorsque les différences par rapport au voisinage sont intenses. Quant aux estimations du volume ligneux, les modèles de régression arborescente forment des groupes de p-e dont la variabilité est inférieure à celle des groupes définis par la méthode actuelle utilisée au Québec. Les strates forestières auxquelles ces estimations sont associées sont caractérisées en fonction de la concordance carte/p-e, aux échelles locale et du voisinage. Pour certaines strates, la concordance locale est élevée, tandis que celle du voisinage est faible et vice-versa. La concordance locale peut être attribuée au degré d’homogénéité interne des strates et à la représentativité des p-e, tandis que la concordance avec le voisinage rend compte de l’incertitude positionnelle des p-e, des frontières et/ou des conditions structurales de ces dernières. Finalement, la fusion des frontières cartographiques et de terrain peut se faire sur le plan des connaissances, étant données les différences de résolution spatiale et du degré de généralisation des deux cartes. De façon générale, les méthodes employées dans cette thèse permettent de mieux caractériser la carte forestière et ses éléments améliorant l’estimation locale du volume ligneux.In the traditional forest maps in Quebec, sharp lines represent stand boundaries, forest strata are considered equally concordant in relation to field/cartographic attributes and the woody volume estimations issue from successive regrouping of field plots. The general objective of this research is to explore how different methods can be combined to characterize stand boundaries, forest strata and woody volume estimations, from geomatic and ecological points of view, by map and field information fusion. In order to qualify boundaries, their contrast and spatial contexts are quantified. The integration of these aspects allows the detection of forest sectors where boundary identification could be easiest. A significant relationship exists among the contrast of examined variables with the existence probability of boundaries. Other boundaries are identified from the field plots. These ones correspond to homogeneous plot clusters and to strong spatial discontinuities in the field variables. The two boundary types coincide spatially when neighbourhood differences are intense. The woody volume boundaries are, in this scale, spatially dependent on forest and topographic boundaries. Regression trees are used for grouping field plots considering minimum volume variability. The most effective tree model is associated with field variables. The groups formed with this method present less spatial variability in comparison with the plot groups presently used in Quebec. The forest strata are qualified by their accord map/plot level. For many forest strata the local accord is high while the neighbourhood accord is low. The local accord is attributed to internal strata homogeneity and/or the fact that plots poorly represent the forest stratum. The neighbourhood accord is associated with positional uncertainty of field samples, of boundaries or both. Finally, in order to permit cartographic and field boundary fusion at the element level, the resolution of heterogeneity between field and forest map data must be addressed first. The spatial resolution and semantic ecological significance of cartographic units are the most important of these heterogeneities

Rural-urban disparities in the management and health issues of chronic diseases in Quebec (Canada) in the early 2000s

Abstract: Introduction: The ‘Commission on the Future of Health Care in Canada’ recognized that people living in rural and remote areas of Canada are at a disadvantage in health status, access to care and health professionals, and it considers the fight against these problems as a national priority. Although some attention has been paid to the prevalence of chronic diseases, very few studies have studied specifically the management and health issues in populations with chronic diseases in relation to rurality. The objective of this study was to describe systematic gaps across rural and urban populations in incidence, mortality, morbidity, material and human resources utilization, and drug management for three important chronic diseases: atherosclerosis, osteoporosis and diabetes. Methods: Three retrospective population-based cohort studies were used. Three study populations were selected: an atherosclerotic population including patients newly hospitalized for a myocardial infarction (MI), an osteoporotic population including the at risk population who have suffered from a fragility fracture (FF) and, finally, a diabetic population that includes only incident cases of diabetes patients. For each of the three chronic diseases, variables were selected and classified in six categories: incidence, mortality, morbidity, material resources utilization, physician consultation and drug treatment. The Statistical Area Classification (SAC) was used as the rurality definition and contains six categories including two urban areas − Census Metropolitan Areas (CMA), or metropolitan areas, and Census Agglomeration (CA), or small towns − and four rural areas: Strong, Moderate, Weak and No Metropolitan influenced zones (MIZ), depending on the proportion of the workforce that commutes to urban areas. Each disease-related variable was described using age- and sex-adjusted rates. For comparing rates between rurality classes, the adjusted relative risks were calculated using the CMA as the reference group. The χ2 was used to test for the equality of risks. Results: A common pattern was identified from this study: for all three studied diseases, the material resources utilization rates and the specialist (other than internist) consultation rates were almost always statistically lower in small towns and rural areas when compared with metropolitan areas. Mortality rates and drug utilization rates were very similar among regions, except for hormone replacement therapy in women where utilization rates were higher in small towns and rural areas compared with metropolitan areas. Among observations that were not common to all three chronic diseases, the first is that MI incidence was greater in small towns and in Weak MIZ compared with metropolitan areas, fragility fractures seem to be marginally more frequent in small towns but less frequent in rural areas compared with metropolitan areas, while an increased incidence rate of diabetes is observed in remote region and a smaller risk in moderate MIZ compared with metropolitan areas. For both atherosclerosis and diabetes, morbidity rates were always statistically higher in small towns and in rural areas. This was not the case for patients with osteoporotic fractures where similar morbidity rates across regions were observed, except in strong MI which show the lowest morbidity rate. Conclusions: There was substantially lower utilization of specialized services in non-metropolitan areas for all three diseases (myocardial infarction, osteoporosis, and diabetes). However, this did not translate into consistent differences in mortality and morbidity outcomes. This suggests that the impact of differential care utilization is specific to each disease, with indications that some important services may be under-utilized in rural areas, while others may be over-utilized in urban areas without improvement in outcomes

Neighbourhood immigration, health care utilization and outcomes in patients with diabetes living in the Montreal metropolitan area (Canada): a population health perspective

Abstract: Background: Understanding health care utilization by neighbourhood is essential for optimal allocation of resources, but links between neighbourhood immigration and health have rarely been explored. Our objective was to understand how immigrant composition of neighbourhoods relates to health outcomes and health care utilization of individuals living with diabetes. Methods: This is a secondary analysis of administrative data using a retrospective cohort of 111,556 patients living with diabetes without previous cardiovascular diseases (CVD) and living in the metropolitan region of Montreal (Canada). A score for immigration was calculated at the neighbourhood level using a principal component analysis with six neighbourhood-level variables (% of people with maternal language other than French or English, % of people who do not speak French or English, % of immigrants with different times since immigration (<5 years, 5–10 years, 10–15 years, 15–25 years)). Dependent variables were all-cause death, all-cause hospitalization, CVD event (death or hospitalization), frequent use of emergency departments, frequent use of general practitioner care, frequent use of specialist care, and purchase of at least one antidiabetic drug. For each of these variables, adjusted odds ratios were estimated using a multilevel logistic regression. Results: Compared to patients with diabetes living in neighbourhoods with low immigration scores, those living in neighbourhoods with high immigration scores were less likely to die, to suffer a CVD event, to frequently visit general practitioners, but more likely to visit emergency departments or a specialist and to use an antidiabetic drug. These differences remained after controlling for patient-level variables such as age, sex, and comorbidities, as well as for neighbourhood attributes like material and social deprivation or living in the urban core. Conclusions: In this study, patients with diabetes living in neighbourhoods with high immigration scores had different health outcomes and health care utilizations compared to those living in neighbourhoods with low immigration scores. Although we cannot disentangle the individual versus the area-based effect of immigration, these results may have an important impact for health care planning

Rural-urban disparities in the management and health issues of chronic diseases in Quebec (Canada) in the early 2000s

Abstract: Introduction: The ‘Commission on the Future of Health Care in Canada’ recognized that people living in rural and remote areas of Canada are at a disadvantage in health status, access to care and health professionals, and it considers the fight against these problems as a national priority. Although some attention has been paid to the prevalence of chronic diseases, very few studies have studied specifically the management and health issues in populations with chronic diseases in relation to rurality. The objective of this study was to describe systematic gaps across rural and urban populations in incidence, mortality, morbidity, material and human resources utilization, and drug management for three important chronic diseases: atherosclerosis, osteoporosis and diabetes. Methods: Three retrospective population-based cohort studies were used. Three study populations were selected: an atherosclerotic population including patients newly hospitalized for a myocardial infarction (MI), an osteoporotic population including the at risk population who have suffered from a fragility fracture (FF) and, finally, a diabetic population that includes only incident cases of diabetes patients. For each of the three chronic diseases, variables were selected and classified in six categories: incidence, mortality, morbidity, material resources utilization, physician consultation and drug treatment. The Statistical Area Classification (SAC) was used as the rurality definition and contains six categories including two urban areas − Census Metropolitan Areas (CMA), or metropolitan areas, and Census Agglomeration (CA), or small towns − and four rural areas: Strong, Moderate, Weak and No Metropolitan influenced zones (MIZ), depending on the proportion of the workforce that commutes to urban areas. Each disease-related variable was described using age- and sex-adjusted rates. For comparing rates between rurality classes, the adjusted relative risks were calculated using the CMA as the reference group. The χ2 was used to test for the equality of risks. Results: A common pattern was identified from this study: for all three studied diseases, the material resources utilization rates and the specialist (other than internist) consultation rates were almost always statistically lower in small towns and rural areas when compared with metropolitan areas. Mortality rates and drug utilization rates were very similar among regions, except for hormone replacement therapy in women where utilization rates were higher in small towns and rural areas compared with metropolitan areas. Among observations that were not common to all three chronic diseases, the first is that MI incidence was greater in small towns and in Weak MIZ compared with metropolitan areas, fragility fractures seem to be marginally more frequent in small towns but less frequent in rural areas compared with metropolitan areas, while an increased incidence rate of diabetes is observed in remote region and a smaller risk in moderate MIZ compared with metropolitan areas. For both atherosclerosis and diabetes, morbidity rates were always statistically higher in small towns and in rural areas. This was not the case for patients with osteoporotic fractures where similar morbidity rates across regions were observed, except in strong MI which show the lowest morbidity rate. Conclusions: There was substantially lower utilization of specialized services in non-metropolitan areas for all three diseases (myocardial infarction, osteoporosis, and diabetes). However, this did not translate into consistent differences in mortality and morbidity outcomes. This suggests that the impact of differential care utilization is specific to each disease, with indications that some important services may be under-utilized in rural areas, while others may be over-utilized in urban areas without improvement in outcomes