Nolwenn Noisel - Academia.edu (original) (raw)
Papers by Nolwenn Noisel
BMC Infectious Diseases
Background By mid-July 2020, more than 108,000 COVID-19 cases had been diagnosed in Canada with m... more Background By mid-July 2020, more than 108,000 COVID-19 cases had been diagnosed in Canada with more than half in the province of Quebec. In this context, we launched a study to analyze the epidemiological characteristics and the socio-economic impact of the spring outbreak in the population. Method We conducted an online survey of the participants of the CARTaGENE population-based cohort, composed of middle-aged and older adults. We collected information on socio-demographic, lifestyle, health condition, COVID-19 related symptoms and COVID-19 testing. We studied the association between these factors and two outcomes: the status of having been tested for SARS-CoV-2 and the status of having received a positive test. These associations were measured with univariate and multivariate analyses using a hybrid tree-based regression model. Results Among the 8,129 respondents from the CARTaGENE cohort, 649 were tested for COVID-19 and 41 were positive. Medical workers and individuals having ...
Brain and Behavior
This is an open access article under the terms of the Creative Commons Attribution License, which... more This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
International Journal of Population Data Science, Mar 26, 2020
Background Population health studies often use existing databases that are not necessarily consti... more Background Population health studies often use existing databases that are not necessarily constituted for research purposes. The question arises as to whether different data sources such as in administrative health data (AHD) and self-report questionnaires are equivalent and lead to similar information. Objectives The main objective of this study was to assess the level of agreement between self-reported medical conditions and medical diagnosis captured in AHD. A secondary objective was to identify predictors of agreement among medical conditions between the two data sources. Therefore, the purposes of the study were to explore the extent to which these two methods of commonly used public health data collection provide concordant records and identify the main predictors of statistical variations. Methods Data were extracted from CARTaGENE, a population-based cohort in Québec, Canada, which was linked to the provincial health insurance records of the same individuals, namely the MED-ÉCHO database from the Régie de l'assurance maladie du Québec (RAMQ) and the fee-for-service billing records provided by the physician, for the time period 1998-2012. Agreement statistics (kappa coefficient) along with sensitivity, specificity and predictive positive value were calculated for 19 chronic conditions and 12 types of cancers. Logistic regressions were used to identify predictors of concordance between self-report and AHD from significant covariates (sex, age groups, education, region, income, heavy utilization of health care system and Charlson comorbidity index). Results Agreement between self-reported data and AHD across diseases ranged from kappa of 0.09 for chronic renal failure to 0.86 for type 2 diabetes. Sensitivity of self-reported data was higher than 50% for 14 out of the 31 medical conditions studied, especially for myocardial infarction (88.62%), breast cancer (86.28%), and diabetes (85.06%). Specificity was generally high with a minimum value of 89.70%. Lower concordance between data sources was observed for higher frequency of health care utilization and higher comorbidity scores.
Frontiers in Genetics
With the increasing use of polygenic risk scores (PRS) there is a need for adapted methods to eva... more With the increasing use of polygenic risk scores (PRS) there is a need for adapted methods to evaluate the predictivity of these tools. In this work, we propose a new pseudo-R 2 criterion to evaluate PRS predictive accuracy for time-to-event data. This new criterion is related to the score statistic derived under a two-component mixture model. It evaluates the effect of the PRS on both the propensity to experience the event and on the dynamic of the event among the susceptible subjects. Simulation results show that our index has good properties. We compared our index to other implemented pseudo-R 2 for survival data. Along with our index, two other indices have comparable good behavior when the PRS has a non-null propensity effect, and our index is the only one to detect when the PRS has only a dynamic effect. We evaluated the 5-year predictivity of an 18-single-nucleotide-polymorphism PRS for incident breast cancer cases on the CARTaGENE cohort using several pseudo-R 2 indices. We report that our index, which summarizes both a propensity and a dynamic effect, had the highest predictive accuracy. In conclusion, our proposed pseudo-R 2 is easy to implement and well suited to evaluate PRS for predicting incident events in cohort studies.
Atmosphere
Household air pollution (HAP) is of public health concern, with ~3 billion people worldwide (incl... more Household air pollution (HAP) is of public health concern, with ~3 billion people worldwide (including >15 million in the US) exposed. HAP from coal use is a human lung carcinogen, yet the epidemiological evidence on carcinogenicity of HAP from biomass use, primarily wood, is not conclusive. To robustly assess biomass’s carcinogenic potential, prospective studies of individuals experiencing a variety of HAP exposures are needed. We have built a global consortium of 13 prospective cohorts (HAPCO: Household Air Pollution Consortium) that have site- and disease-specific mortality and solid fuel use data, for a combined sample size of 587,257 participants and 57,483 deaths. HAPCO provides a novel opportunity to assess the association of HAP with lung cancer death while controlling for important confounders such as tobacco and outdoor air pollution exposures. HAPCO is also uniquely positioned to determine the risks associated with cancers other than lung as well as nonmalignant respir...
Environmental Epidemiology
Background: Urban green space may be important to mental health, but the association between long... more Background: Urban green space may be important to mental health, but the association between long-term green space exposures and depression, anxiety, and cognitive function in adults remains unknown. Methods: We examined 8,144 adults enrolled in the CARTaGENE cohort in Quebec Canada. Average green space and change in green space with residential mobility were assessed using satellite-derived normalized difference vegetation index from 5-year residential address histories. Outcomes included depression and anxiety determined through medical record linkages, self-reported doctor diagnosis of depression, and the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7scales. Cognitive function was available for 6,658 individuals from computerized tests of reaction time, working memory, and executive function. We used linear and logistic multivariate models to assess associations between green space and each mental health and cognitive function measure. Results: In fully adjusted analyses, a 0.1 increase in residential normalized difference vegetation index within 500 m was associated with an odds ratio of 0.85 (95% CI: 0.76, 0.95) for a self-reported doctor diagnosis of depression and 0.81 (95% CI: 0.70, 0.93) for moderate anxiety assessed using the Generalized Anxiety Disorder 7 scale. Other models showed protective effects of urban green space on depression and anxiety but were not statistically significant, and the magnitude of association varied by green space exposure and mental health outcome assessment method. We did not observe any evidence of associations between green space and cognitive function. Conclusions: We observed some evidence to support the hypothesis that urban green space is associated with decreased depression and anxiety but not cognitive function.
International Journal of Hygiene and Environmental Health
In order to characterize exposure of the Canadian population to environmental chemicals, a human ... more In order to characterize exposure of the Canadian population to environmental chemicals, a human biomonitoring component has been included in the Canadian Health Measures Survey (CHMS). This nationally-representative survey, launched in 2007 by the Government of Canada, has measured over 250 chemicals in approximately 30,000 Canadians during the last decade. The capacity to interpret these data at the population level in a health risk context is gradually improving with the development of biomonitoring screening values, such as biomonitoring equivalents (BE) and human biomonitoring (HBM) values. This study evaluates recent population level biomonitoring data from the CHMS in a health risk context using biomonitoring screening values. Nationally representative biomonitoring data for fluoride, selenium, molybdenum, arsenic, silver, thallium, cyfluthrin, 2,4-dichlorophenoxyacetic acid (2,4-D), 3-phenoxybenzoic acid (3-PBA), chlorpyrifos, deltamethrin, bisphenol A, triclosan, acrylamide, cadmium, perfluorooctane sulfonate (PFOS), perfluorooctanoic acid (PFOA), bromoform, chloroform, benzene, toluene, xylene, ethylbenzene, styrene and tetrachloroethylene were screened as part as this study. For non-cancer endpoints, hazard quotients (HQs) were calculated as the ratio of population level concentrations of a specific chemical at the geometric mean and 95th percentile to the corresponding biomonitoring screening value. Cancer risks were calculated at the 5th, 25th, 50th, 75th and 95th percentiles of the population concentration using BEs based on a risk specific dose. Most of the chemicals analyzed had HQs below 1 suggesting that levels of exposure to these chemicals are not a concern at the population level. However, HQs exceeded 1 in smokers for cadmium, acrylamide and benzene, as well as in the general population for inorganic arsenic, PFOS and PFOA, 3-PBA and fluoride. Furthermore, cancer risks for inorganic arsenic, acrylamide, and benzene at most population percentiles of exposure were elevated (> 10 −5). Specifically, for inorganic arsenic in the general population, the HQ was 3.13 at the 95th percentile concentration and the cancer risk was 3.4 × 10 −4 at the 50th percentile of population concentrations. These results suggest that the levels of exposure in the Canadian population to some of the environmental chemicals assessed might be of concern. The results of this screening exercise support the findings of previous risk assessments and ongoing efforts to reduce risks from exposure to chemicals evaluated as part of this study. Although paucity of biomonitoring screening values for several environmental contaminants may be a limitation to this approach, our assessment contributes to the prioritization of a number of chemicals measured as part of CHMS for followup activities such as more detailed characterization of exposure sources.
Revue D Epidemiologie Et De Sante Publique, Sep 1, 2005
BMC Infectious Diseases
Background By mid-July 2020, more than 108,000 COVID-19 cases had been diagnosed in Canada with m... more Background By mid-July 2020, more than 108,000 COVID-19 cases had been diagnosed in Canada with more than half in the province of Quebec. In this context, we launched a study to analyze the epidemiological characteristics and the socio-economic impact of the spring outbreak in the population. Method We conducted an online survey of the participants of the CARTaGENE population-based cohort, composed of middle-aged and older adults. We collected information on socio-demographic, lifestyle, health condition, COVID-19 related symptoms and COVID-19 testing. We studied the association between these factors and two outcomes: the status of having been tested for SARS-CoV-2 and the status of having received a positive test. These associations were measured with univariate and multivariate analyses using a hybrid tree-based regression model. Results Among the 8,129 respondents from the CARTaGENE cohort, 649 were tested for COVID-19 and 41 were positive. Medical workers and individuals having ...
Brain and Behavior
This is an open access article under the terms of the Creative Commons Attribution License, which... more This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
International Journal of Population Data Science, Mar 26, 2020
Background Population health studies often use existing databases that are not necessarily consti... more Background Population health studies often use existing databases that are not necessarily constituted for research purposes. The question arises as to whether different data sources such as in administrative health data (AHD) and self-report questionnaires are equivalent and lead to similar information. Objectives The main objective of this study was to assess the level of agreement between self-reported medical conditions and medical diagnosis captured in AHD. A secondary objective was to identify predictors of agreement among medical conditions between the two data sources. Therefore, the purposes of the study were to explore the extent to which these two methods of commonly used public health data collection provide concordant records and identify the main predictors of statistical variations. Methods Data were extracted from CARTaGENE, a population-based cohort in Québec, Canada, which was linked to the provincial health insurance records of the same individuals, namely the MED-ÉCHO database from the Régie de l'assurance maladie du Québec (RAMQ) and the fee-for-service billing records provided by the physician, for the time period 1998-2012. Agreement statistics (kappa coefficient) along with sensitivity, specificity and predictive positive value were calculated for 19 chronic conditions and 12 types of cancers. Logistic regressions were used to identify predictors of concordance between self-report and AHD from significant covariates (sex, age groups, education, region, income, heavy utilization of health care system and Charlson comorbidity index). Results Agreement between self-reported data and AHD across diseases ranged from kappa of 0.09 for chronic renal failure to 0.86 for type 2 diabetes. Sensitivity of self-reported data was higher than 50% for 14 out of the 31 medical conditions studied, especially for myocardial infarction (88.62%), breast cancer (86.28%), and diabetes (85.06%). Specificity was generally high with a minimum value of 89.70%. Lower concordance between data sources was observed for higher frequency of health care utilization and higher comorbidity scores.
Frontiers in Genetics
With the increasing use of polygenic risk scores (PRS) there is a need for adapted methods to eva... more With the increasing use of polygenic risk scores (PRS) there is a need for adapted methods to evaluate the predictivity of these tools. In this work, we propose a new pseudo-R 2 criterion to evaluate PRS predictive accuracy for time-to-event data. This new criterion is related to the score statistic derived under a two-component mixture model. It evaluates the effect of the PRS on both the propensity to experience the event and on the dynamic of the event among the susceptible subjects. Simulation results show that our index has good properties. We compared our index to other implemented pseudo-R 2 for survival data. Along with our index, two other indices have comparable good behavior when the PRS has a non-null propensity effect, and our index is the only one to detect when the PRS has only a dynamic effect. We evaluated the 5-year predictivity of an 18-single-nucleotide-polymorphism PRS for incident breast cancer cases on the CARTaGENE cohort using several pseudo-R 2 indices. We report that our index, which summarizes both a propensity and a dynamic effect, had the highest predictive accuracy. In conclusion, our proposed pseudo-R 2 is easy to implement and well suited to evaluate PRS for predicting incident events in cohort studies.
Atmosphere
Household air pollution (HAP) is of public health concern, with ~3 billion people worldwide (incl... more Household air pollution (HAP) is of public health concern, with ~3 billion people worldwide (including >15 million in the US) exposed. HAP from coal use is a human lung carcinogen, yet the epidemiological evidence on carcinogenicity of HAP from biomass use, primarily wood, is not conclusive. To robustly assess biomass’s carcinogenic potential, prospective studies of individuals experiencing a variety of HAP exposures are needed. We have built a global consortium of 13 prospective cohorts (HAPCO: Household Air Pollution Consortium) that have site- and disease-specific mortality and solid fuel use data, for a combined sample size of 587,257 participants and 57,483 deaths. HAPCO provides a novel opportunity to assess the association of HAP with lung cancer death while controlling for important confounders such as tobacco and outdoor air pollution exposures. HAPCO is also uniquely positioned to determine the risks associated with cancers other than lung as well as nonmalignant respir...
Environmental Epidemiology
Background: Urban green space may be important to mental health, but the association between long... more Background: Urban green space may be important to mental health, but the association between long-term green space exposures and depression, anxiety, and cognitive function in adults remains unknown. Methods: We examined 8,144 adults enrolled in the CARTaGENE cohort in Quebec Canada. Average green space and change in green space with residential mobility were assessed using satellite-derived normalized difference vegetation index from 5-year residential address histories. Outcomes included depression and anxiety determined through medical record linkages, self-reported doctor diagnosis of depression, and the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7scales. Cognitive function was available for 6,658 individuals from computerized tests of reaction time, working memory, and executive function. We used linear and logistic multivariate models to assess associations between green space and each mental health and cognitive function measure. Results: In fully adjusted analyses, a 0.1 increase in residential normalized difference vegetation index within 500 m was associated with an odds ratio of 0.85 (95% CI: 0.76, 0.95) for a self-reported doctor diagnosis of depression and 0.81 (95% CI: 0.70, 0.93) for moderate anxiety assessed using the Generalized Anxiety Disorder 7 scale. Other models showed protective effects of urban green space on depression and anxiety but were not statistically significant, and the magnitude of association varied by green space exposure and mental health outcome assessment method. We did not observe any evidence of associations between green space and cognitive function. Conclusions: We observed some evidence to support the hypothesis that urban green space is associated with decreased depression and anxiety but not cognitive function.
International Journal of Hygiene and Environmental Health
In order to characterize exposure of the Canadian population to environmental chemicals, a human ... more In order to characterize exposure of the Canadian population to environmental chemicals, a human biomonitoring component has been included in the Canadian Health Measures Survey (CHMS). This nationally-representative survey, launched in 2007 by the Government of Canada, has measured over 250 chemicals in approximately 30,000 Canadians during the last decade. The capacity to interpret these data at the population level in a health risk context is gradually improving with the development of biomonitoring screening values, such as biomonitoring equivalents (BE) and human biomonitoring (HBM) values. This study evaluates recent population level biomonitoring data from the CHMS in a health risk context using biomonitoring screening values. Nationally representative biomonitoring data for fluoride, selenium, molybdenum, arsenic, silver, thallium, cyfluthrin, 2,4-dichlorophenoxyacetic acid (2,4-D), 3-phenoxybenzoic acid (3-PBA), chlorpyrifos, deltamethrin, bisphenol A, triclosan, acrylamide, cadmium, perfluorooctane sulfonate (PFOS), perfluorooctanoic acid (PFOA), bromoform, chloroform, benzene, toluene, xylene, ethylbenzene, styrene and tetrachloroethylene were screened as part as this study. For non-cancer endpoints, hazard quotients (HQs) were calculated as the ratio of population level concentrations of a specific chemical at the geometric mean and 95th percentile to the corresponding biomonitoring screening value. Cancer risks were calculated at the 5th, 25th, 50th, 75th and 95th percentiles of the population concentration using BEs based on a risk specific dose. Most of the chemicals analyzed had HQs below 1 suggesting that levels of exposure to these chemicals are not a concern at the population level. However, HQs exceeded 1 in smokers for cadmium, acrylamide and benzene, as well as in the general population for inorganic arsenic, PFOS and PFOA, 3-PBA and fluoride. Furthermore, cancer risks for inorganic arsenic, acrylamide, and benzene at most population percentiles of exposure were elevated (> 10 −5). Specifically, for inorganic arsenic in the general population, the HQ was 3.13 at the 95th percentile concentration and the cancer risk was 3.4 × 10 −4 at the 50th percentile of population concentrations. These results suggest that the levels of exposure in the Canadian population to some of the environmental chemicals assessed might be of concern. The results of this screening exercise support the findings of previous risk assessments and ongoing efforts to reduce risks from exposure to chemicals evaluated as part of this study. Although paucity of biomonitoring screening values for several environmental contaminants may be a limitation to this approach, our assessment contributes to the prioritization of a number of chemicals measured as part of CHMS for followup activities such as more detailed characterization of exposure sources.
Revue D Epidemiologie Et De Sante Publique, Sep 1, 2005