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Esse e-book reúne treze artigos desenvolvidos, a partir de pesquisas de Iniciação Científica e outras produções acadêmicas, realizadas por estudantes e seus respectivos professores orientadores do Uni-FACEF Centro Universitário Municipal de Franca, associados à área de Psicologia e apresentados no XVI Fórum de Estudos Multidisciplinares. O tema da maioria dos trabalhos foi influenciado diretamente pela pandemia da COVID-19, que alterou mundialmente o contexto de vida contemporâneo, e, portanto, mobilizou a curiosidade científica dos autores. Podemos verificar, portanto, o uso da pesquisa como estratégia, para responder problemas apresentados, a partir de demandas concretas que desafiam àqueles que estão comprometidos com a construção do conhecimento crítico, atual e capaz de fundamentar cientificamente a prática profissional. Assim, essa amostra produzida pela comunidade acadêmica do Uni-FACEF reforça o comprometimento com a missão da IES de “construir e difundir o conhecimento, contribuindo para a formação do ser humano, a fim de que ele exerça o seu papel na sociedade com ética e cidadania”. Temos a oportunidade, através da leitura dos artigos desse e-book, de conhecer aspectos importantes acerca da felicidade dos jovens no período da pandemia, da prática do riso e do bom humor no enfrentamento do estresse de formandos, da singularidade envolvida na saúde mental, a partir de uma análise simbólica do filme Bacurau, dos possíveis impactos causados pela pandemia em crianças da terceira infância (fase de latência), da vivência de docentes universitários no desenvolvimento de práticas educacionais em home office no período da pandemia, das habilidades socioemocionais necessárias para o desenvolvimento infantil no contexto pandêmico, dos impactos emocionais em adolescentes durante a pandemia, da influência da depressão pós-parto no aleitamento materno, da elaboração do luto na ausência de rituais fúnebres das vítimas do COVID-19, das consequências da pandemia na saúde mental dos profissionais de saúde da cidade de Franca/SP, dos pressupostos psicanalíticos que sustentam a elaboração do papel do brincar na Psicanálise e na constituição da psique dos indivíduos, das técnicas da Terapia Cognitivo-Comportamental capazes de auxiliar no tratamento de adolescentes diagnosticados com transtorno de ansiedade social em isolamento social durante a pandemia e, por fim, do transtorno de conduta em adolescentes em situação de vulnerabilidade no contexto da pandemia.

Introduction In Ontario, Canada, parents have the responsibility to report their child’s routine infant and childhood vaccines to the provincial immunization registry (the Digital Health Immunization Repository; DHIR) without healthcare provider validation. Despite its use in routine immunization coverage monitoring, no study has previously examined the completeness of immunization data within the DHIR. Methods We assessed the completeness of DHIR immunizations, as compared to immunizations within the Electronic Medical Records—Primary Care (EMRPC) database, also known as EMRALD, a network of family physician electronic medical records (EMRs). We linked client records from the DHIR and EMRPC to a centralized population file. To create the study cohort, we examined children born during 2005–2008 and further defined the cohort based on those rostered to an EMRPC physician, visit criteria to ensure ongoing care by an EMRPC provider, and school attendance in Ontario at age 7. We calculated up-to-date (UTD) immunization coverage at age 7 for individual vaccines and overall using data from the DHIR and EMRPC separately, and compared the estimates. Results The analytic cohort to assess DHIR data completeness included 2,657 children. Overall UTD coverage (all vaccines assessed) was 82.0% in the DHIR and 67.6% in EMRPC. UTD coverage was higher in the DHIR for all vaccines assessed individually, with the exception of meningococcal C conjugate vaccine (difference = 0.3%). After excluding two EMRPC sites with irregularities in immunization data, the difference in overall UTD coverage between systems decreased from 14.4% to 6.6% Interpretation These results validate the use of DHIR for coverage assessment but also suggest that bidirectional exchange of immunization information has the potential to increase immunization data completeness in both systems.

Pertussis surveillance remains essential in Canada, but ascertainment bias limits the accuracy of surveillance data. Introducing other sources to improve detection has highlighted the importance of validation. However, challenges arise due to low prevalence, and oversampling suspected cases can introduce partial verification bias. The aim of this study was to build a reference standard for pertussis validation studies that provides adequate analytic precision and minimizes bias.We used a stratified strategy to sample the reference standard from a primary care electronic medical record cohort. We incorporated abstractor notes into definite, possible, ruled-out, and no mention of pertussis classifications which were based on surveillance case definitions.We abstracted eight hundred records from the cohort of 404,922. There were 208 (26%) definite and 261 (32.6%) possible prevalent pertussis cases. Classifications demonstrated a wide variety of case severities. Abstraction reliability was moderate to substantial based on Cohen's kappa and raw percent agreement.When conducting validation studies for pertussis and other low prevalence diseases, this stratified sampling strategy can be used to develop a reference standard using limited resources. This approach mitigates verification and spectrum bias while providing sufficient precision and incorporating a range of case severities.

BackgroundThe novel coronavirus disease 2019 (COVID-19) has infected 1.9% of the world population by May 2, 2021. Since most previous studies that examined risk factors for mortality and severity were based on hospitalized individuals, population-based cohort studies are called for to provide evidence that can be extrapolated to the general population. Therefore, we aimed to examine the associations of comorbidities with mortality and disease severity in individuals with COVID-19 diagnosed in 2020 in Ontario, Canada.Methods and findingsWe conducted a retrospective cohort study of all individuals with COVID-19 in Ontario, Canada diagnosed between January 15 and December 31, 2020. Cases were linked to health administrative databases maintained in the ICES which covers all residents in Ontario. The primary outcome is all-cause 30-day mortality after the first COVID-19 diagnosis, and the secondary outcome is a composite severity index containing death and hospitalization. To examine the risk factors for the outcomes, we employed Cox proportional hazards regression models and logistic regression models to adjust for demographic, socio-economic variables and comorbidities. Results were also stratified by age groups. A total of 167,500 individuals were diagnosed of COVID-19 in 2020 and included in the study. About half (43.8%, n = 73,378) had at least one comorbidity. The median follow-up period were 30 days. The most common comorbidities were hypertension (24%, n = 40,154), asthma (16%, n = 26,814), and diabetes (14.7%, n = 24,662). Individuals with comorbidity had higher risk of mortality compared to those without (HR = 2.80, 95%CI 2.35–3.34; pConclusionWe found that solid organ transplant, dementia, chronic kidney disease, severe mental illness, CVD, hypertension, COPD, cancer, diabetes, rheumatoid arthritis, HIV, and asthma were associated with mortality or severity. Our study highlights that the number of comorbidities was a strong risk factor for deaths and severe outcomes among younger individuals with COVID-19. Our findings suggest that in addition of prioritizing by age, vaccination priority groups should also include younger population with multiple comorbidities.

Cirrhosis is the result of advanced scarring (or fibrosis) of the liver, and is often diagnosed once decompensation with associated complications has occurred. Current non-invasive tests to detect advanced liver fibrosis have limited performance, with many indeterminate classifications. We aimed to identify patients with advanced liver fibrosis of all-causes using machine learning algorithms (MLAs).In this retrospective study of routinely collected laboratory, clinical, and demographic data, we trained six MLAs (support vector machine, random forest classifier, gradient boosting classifier, logistic regression, artificial neural network, and an ensemble of all these algorithms) to detect advanced fibrosis using 1703 liver biopsies from patients seen at the Toronto Liver Clinic (TLC) between Jan 1, 2000, and Dec 20, 2014. Performance was validated using five datasets derived from patient data provided by the TLC (n=104 patients with a biopsy sample taken between March 24, 2014, and Dec 31, 2017) and McGill University Health Centre (MUHC; n=404). Patients with decompensated cirrhosis were excluded. Performance was benchmarked against aspartate aminotransferase-to-platelet ratio index (APRI), fibrosis-4 index (FIB-4), non-alcoholic fatty liver disease fibrosis score (NFS), transient elastography, and an independent panel of five hepatology experts (MB, GS, HK, KP, and RSK). MLA performance was evaluated using the area under the receiver operating characteristic curve (AUROC) and the percentage of determinate classifications.The best MLA was an ensemble algorithm of support vector machine, random forest classifier, gradient boosting classifier, logistic regression, and neural network algorithms, which achieved 100% determinate classifications (95% CI 100·0-100·0), an AUROC score of 0·870 (95% CI 0·797-0·931) on the TLC validation set (fibrosis stages F0 and F1 vs F4), and an AUROC of 0·716 (95% CI 0·664-0·766) on the MUHC validation set (fibrosis stages F0, F1, and F2 vs F3 and F4). The ensemble MLA outperformed all routinely used biomarkers and achieved comparable performance to hepatologists as measured by AUROC and percentage of indeterminate classifications in both the TLC validation dataset (APRI AUROC score 0·719 [95% CI 0·611-0·820], 83·7% determinate [95% CI 76·0-90·4]; FIB-4 AUROC score 0·825 [95% CI 0·730-0·912], 72·1% determinate [95% CI 63·5-80·8]) and the MUHC validation dataset (APRI AUROC score 0·618 [95% CI 0·548-0·691], 75·5% determinate [95% CI 71·5-79·2]; FIB-4 AUROC score 0·717 (95% CI 0·652-0·776), 75·5% determinate [95% CI 0·713-0·797]), and achieving only slightly lower AUROC than transient elastography (0·773 [95% CI 0·699-0·834] vs 0·826 [95% CI 0·758-0·889]).We have shown that an ensemble MLA outperforms non-imaging-based methods in detecting advanced fibrosis across different causes of liver disease. Our MLA was superior to APRI, FIB-4, and NFS with no indeterminate classifications, while achieving performance comparable to an independent panel of experts. MLAs using routinely collected data could identify patients at high-risk of advanced hepatic fibrosis and cirrhosis among patients with chronic liver disease, allowing intervention before onset of decompensation.Toronto General Hospital Foundation.

Background Approximately 25% of outpatient antibiotic prescriptions are unnecessary among family physicians in Canada. Minimizing unnecessary antibiotics is key for community antibiotic stewardship. However, unnecessary antibiotic prescribing is much harder to measure than total antibiotic prescribing. We investigated the association between total and unnecessary antibiotic use by family physicians and evaluated inter-physician variability in unnecessary antibiotic prescribing. Methods This was a cohort study based on electronic medical records of family physicians in Ontario, Canada, between April 2011 and March 2016. We used predefined expected antibiotic prescribing rates for 23 common primary care conditions to calculate unnecessary antibiotic prescribing rates. We used multilevel Poisson regression models to evaluate the association between total antibiotic volume (number of antibiotic prescriptions per patient visit), adjusted for multiple practice- and physician-level covariates, and unnecessary antibiotic prescribing. Results There were 499 570 physician–patient encounters resulting in 152 853 antibiotic prescriptions from 341 physicians. Substantial inter-physician variability was observed. In the fully adjusted model, we observed a significant association between total antibiotic volume and unnecessary prescribing rate (adjusted rate ratio 2.11 per 10% increase in total use; 95% CI 2.05–2.17), and none of the practice- and physician-level variables were associated with unnecessary prescribing rate. Conclusions We demonstrated substantial inter-physician variability in unnecessary antibiotic prescribing in this cohort of family physicians. Total antibiotic use was strongly correlated with unnecessary antibiotic prescribing. Total antibiotic volume is a reasonable surrogate for unnecessary antibiotic use. These results can inform community antimicrobial stewardship efforts.

Background Unnecessary antibiotic use in the community in Canada is not well defined. Our objective was to quantify unnecessary antibiotic prescribing in a Canadian primary care setting. Methods We performed a descriptive analysis in Ontario from April 2011 to March 2016 using the Electronic Medical Records Primary Care database linked to other health administrative data sets at ICES. We determined antibiotic prescribing rates (per 100 patient-physician encounters) for 23 common conditions and estimated rates of unnecessary prescribing using predefined expected prescribing rates, both stratified by condition and patient age group. Results The study included 341 physicians, 204 313 patients and 499 570 encounters. The rate of unnecessary antibiotic prescribing for included conditions was 15.4% overall and was 17.6% for those less than 2 years of age, 18.6% for those aged 2-18, 14.5% for those aged 19-64 and 13.0% for those aged 65 or more. The highest unnecessary prescribing rates were observed for acute bronchitis (52.6%), acute sinusitis (48.4%) and acute otitis media (39.3%). The common cold, acute bronchitis, acute sinusitis and miscellaneous nonbacterial infections were responsible for 80% of the unnecessary antibiotic prescriptions. Of all antibiotics prescribed, 12.0% were for conditions for which they are never indicated, and 12.3% for conditions for which they are rarely indicated. In children, 25% of antibiotics were for conditions for which they are never indicated (e.g., common cold). Interpretation Antibiotics were prescribed unnecessarily for 15.4% of included encounters in a Canadian primary care setting. Almost one-quarter of antibiotics were prescribed for conditions for which they are rarely or never indicated. These findings should guide safe reductions in the use of antibiotics for the common cold, bronchitis and sinusitis.

OBJECTIVES: The purpose of this study was to estimate the proportion and number of cancer cases diagnosed in Ontario in 2012 that are attributable to alcohol consumption and to compare the impact of drinking within two sets of guidelines on alcohol-attributable cancer incidence. METHODS: We estimated the proportion of cancers in Ontario attributable to alcohol consumption by calculating population-attributable fractions (PAFs) for six cancer types using drinking prevalence from the 2000/2001 Canadian Community Health Survey and relative risks from a meta-analysis. Each PAF was multiplied by the number of incident cancers in 2012, allowing for a 12-year latency period, to calculate the number of alcohol-attributable cases. We also estimated the number of alcohol-attributable cases under two scenarios: (1) assuming consumption had not exceeded the levels recommended by the Low-Risk Alcohol Drinking Guidelines (LRADG) and (2) assuming consumption had not exceeded the recommended levels by the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) guidelines. RESULTS: One thousand two hundred ninety-five (95% confidence interval 1093–1499) new cases of cancer diagnosed in Ontario during 2012 are estimated to be attributed to alcohol consumption, representing approximately 1.7% (1.4–1.9%) of all new cancer cases. If no Ontario adults had exceeded the LRADG, an estimated 321 fewer cancer cases could have been diagnosed in 2012, whereas an estimated 482 fewer cancer cases could have been diagnosed if no Ontario adults had exceeded the stricter WCRF/AICR guidelines. CONCLUSION: Strategies to limit alcohol consumption to the levels recommended by drinking guidelines could potentially reduce the cancer burden in Ontario.

Background: Cirrhosis is often diagnosed once complications such as ascites, encephalopathy and variceal bleeding have occurred. Current non-invasive tests to detect cirrhosis have limited performance, with many patients falling into the indeterminate category. Objectives: To identify patients with well-compensated liver cirrhosis of all-causes using machine learning algorithms (MLAs) trained on routinely measured clinical and laboratory parameters. Design, Setting, and Participants: Retrospective, cross-sectional study on patients with F0, F1, and F4 fibrosis staged via biopsy at the Toronto Liver Clinic, validated on 508 patients with F0 to F4 fibrosis staged via biopsy locally as well as at the McGill University Health Centre. Patients with decompensated cirrhosis were excluded. We trained 7 MLAs to identify patients with compensated cirrhosis. Performance was benchmarked against the Aspartate aminotransferase (AST)-to-Platelet Ratio Index (APRI), Fibrosis-4 index (FIB-4), nonalcoholic fatty liver disease (NAFLD) fibrosis score (NFS), Transient Elastography (TE), and an independent panel of 5 experts. Results: The best MLA achieved a cross-validation area under the receiver operating characteristic curve (AUROC) of 0.88 for identifying patients with well-compensated cirrhosis, with less than 8% indeterminate classifications. The MLA achieved higher or comparable AUROC to FIB-4 on both validation sets with 20% fewer indeterminate classifications. Additionally, we show that by altering cutoffs, the MLA outperformed expert hepatologists and the NFS score and achieved superior specificity to transient elastography. Conclusion: In this study, we have demonstrated that an MLA outperforms non-imaging based methods in detecting well-compensated cirrhosis across multiple etiologies of liver disease. Our MLA was superior to APRI, FIB-4, and NFS with significantly fewer indeterminate classifications, while achieving performance comparable to an independent panel of experts. MLAs using routinely collected data could flag patients with well-compensated liver cirrhosis among patients with chronic liver disease, allowing intervention prior to onset of decompensation and associated complications. Funding Statement: This study was supported by ICES, which is funded by an annual grant from the Ontario Ministry of Health and Long-Term Care (MOHLTC). Declaration of Interests: We have no competing interests to declare. Ethics Approval Statement: Ethics approval was obtained from the Research Ethics Boards at the University Health Network, SickKids Research Institute, and MUHC.

Identification and subsequent intervention of patients at risk of becoming High Cost Users (HCUs) presents the opportunity to improve outcomes while also providing significant savings for the healthcare system. In this paper, the 2016 HCU status of patients was predicted using free-form text data from the 2015 cumulative patient profiles within the electronic medical records of family care practices in Ontario. These unstructured notes make substantial use of domain-specific spellings and abbreviations; we show that word embeddings derived from the same context provide more informative features than pre-trained ones based on Wikipedia, MIMIC, and Pubmed. We further demonstrate that a model using features derived from aggregated word embeddings (EmbEncode) provides a significant performance improvement over the bag-of-words representation (82.48±0.35% versus 81.85±0.36% held-out AUROC, p = 3.2 × 10-4), using far fewer input features (5,492 versus 214,750) and fewer non-zero coefficients (1,177 versus 4,284). The future HCUs of greatest interest are the transitional ones who are not already HCUs, because they provide the greatest scope for interventions. Predicting these new HCU is challenging because most HCUs recur. We show that removing recurrent HCUs from the training set improves the ability of EmbEncode to predict new HCUs, while only slightly decreasing its ability to predict recurrent ones.

Identification and subsequent intervention of patients at risk of becoming High Cost Users (HCUs) presents the opportunity to improve outcomes while also providing significant savings for the healthcare system. In this paper, the 2016 HCU status of patients was predicted using free-form text data from the 2015 cumulative patient profiles within the electronic medical records of family care practices in Ontario. These unstructured notes make substantial use of domain-specific spellings and abbreviations; we show that word embeddings derived from the same context provide more informative features than pre-trained ones based on Wikipedia, MIMIC, and Pubmed. We further demonstrate that a model using features derived from aggregated word embeddings (EmbEncode) provides a significant performance improvement over the bag-of-words representation (82.48±0.35% versus 81.85±0.36% held-out AUROC, p = 3.2 × 10-4), using far fewer input features (5,492 versus 214,750) and fewer non-zero coefficients (1,177 versus 4,284). The future HCUs of greatest interest are the transitional ones who are not already HCUs, because they provide the greatest scope for interventions. Predicting these new HCU is challenging because most HCUs recur. We show that removing recurrent HCUs from the training set improves the ability of EmbEncode to predict new HCUs, while only slightly decreasing its ability to predict recurrent ones.

IntroductionCertain subject behaviours and characteristics increase the risk of some cancer types (e.g., obesity, alcohol intake) while others reduce cancer risk (e.g., physical activity). In 2007, the World Cancer Research Fund (WCRF) and American Institute for Cancer Research (AICR) published recommendations to reduce cancer risk related to these behaviours. Objectives and ApproachThe objective is to examine the association between self-reported behaviour consistent with WCRF/AICR recommendations for body fatness, physical activity, vegetable/fruit consumption, and alcohol intake and the risk of all cancers combined and specific cancer types. The study cohort, comprised of the Canadian Community Health Survey (CCHS) Ontario sample, will be linked with health administrative databases, including the Ontario Cancer Registry to determine cancer outcomes. Individuals will be assessed for behaviours consistent with WCRF/AICR recommendations based on their responses to CCHS questions and the association of these behaviours with cancer risk will be explored using multivariable Cox proportional hazard regression models. ResultsTo detect a log hazard ratio of 1.10 (where a=0.05, power=0.80, proportion of the sample assigned to the exposure group=0.25 and R2=0.20), a sample size of 4,538 is required. Based on the number of records in the CCHS data frame (159,474) and an assumption that the CCHS sample experiences cancer incidence at a similar rate to the rest of the Ontario population, we expect to have 5,000 cancer cases for these analyses. Upon completion of the analysis, we will report hazard ratios that estimate the difference in cancer risk between individuals reporting behaviour consistent with the WCRF/AICR recommendations and those reporting behaviour not consistent with the recommendations. Conclusion/ImplicationsWCRF/AICR recommendations were developed as the basis for primary cancer prevention, both for individuals and population-wide policies and programs. The current study will quantify the difference in overall cancer risk between individuals who do and do not adhere to selected WCRF/AICR recommendations for the first time in a Canadian population.

ObjectiveIdentify patterns in cervical cancer incidence in Ontario according to neighborhood sociodemographic characteristics over time and by morphologic type.MethodsIncident cases of cervical cancer diagnosed from 1991 to 2009 were obtained from the Ontario Cancer Registry. Population data and data on neighborhood sociodemographic characteristics were obtained from the Canadian Census. Age-standardized incidence rates (ASIR) and rate ratios (RRs) with 95% confidence intervals (CIs) were calculated for each sociodemographic characteristic, stratified by morphologic type (squamous cell carcinoma and adenocarcinoma) and time period of diagnosis.ResultsIncidence was 51% higher in the poorest neighborhoods compared with the richest (RR, 1.51; 95% CI, 1.42–1.61) and 7% higher in rural areas compared with urban (RR, 1.07; 95% CI, 1.01–1.13). Incidence of squamous cell carcinoma was significantly higher in the poorest neighborhoods compared with the richest (RR, 1.74; 95% CI, 1.61–1.88), a trend observed for all time periods, and in rural areas compared with urban (RR, 1.10; 95% CI, 1.02–1.18). For adenocarcinoma, ASIRs in the earlier time period (1991–1998) were higher in the poorest neighborhoods compared with richest (RR, 1.26; 95% CI, 1.01–1.57), whereas for the more recent time period (1999–2009), ASIRs were lower for women living in the poorest neighborhoods compared with the richest (RR, 0.82; 95% CI, 0.68–0.99).ConclusionsThis study identified significantly higher incidence of cervical cancer in low-income neighborhoods in Ontario. The association was especially pronounced for squamous cell carcinoma and varied by time period for adenocarcinoma. Improvements to screening and prevention efforts against oncogenic human papillomavirus strains would increase the detection of cervical cancer, adenocarcinoma especially, and may further reduce cervical cancer incidence.

Background Available evidence has demonstrated survival benefits associated with multidisciplinary cardiovascular risk-reduction (CR) (ie, cardiac rehabilitation) programs. The degree to which program capacity meets eligible service demands in Ontario is unknown. We sought to estimate the supply-need care-gap associated with CR programs across regions (Local Health Integration Networks [LHINs]) in Ontario. Methods We conducted a cross-sectional, population-based study during 2006. Administrative data provided estimates of the population eligible for multidisciplinary CR services due to (1) recent cardiovascular hospitalizations and (2) incident diabetes. An Ontario-wide survey of CR programs provided service supply estimates. The coverage rate and the absolute supply-need mismatch were use to quantify the care-gap by LHIN. Results Based on cardiac hospitalizations alone, 53,270 patients in Ontario in 2006 (508.7 per 100,000) were eligible for CR services; 128,869 patients (1245 per 100,000) would have been eligible if newly diagnosed (incident cases) diabetic patients were included. Capacity for CR services was 18,087 patients, corresponding to 34% coverage of the eligible population (absolute unmet needs of 35,189 individuals) if capacity was entirely dedicated to recent hospitalizations and 14% coverage (absolute unmet needs of 110,782) if services were extended to include incident diabetes patients. Marked variation in disease burden, service capacity, and supply-need mismatch was observed across regions, in which supply was not correlated with need. Conclusion Despite proved benefits of multidisciplinary CR programs, unmet population needs remain high in Ontario and are unequally distributed across regions. The magnitude of unmet needs and the lack of correlation between supply and disease burden necessitate broader provincial strategies to plan, allocate, and subsidize CR programs.

Due to a production error, the PDF of this article published without the French translation of its Abstract (Resume) and Keywords (Mots-cles), now displayed here.

Studies suggest that colorectal cancer incidence increased disproportionately among the Aboriginal population of Ontario relative to the general population. Using an ecological approach, this study examined colorectal cancer incidence for the 1998-to-2009 period among Aboriginal people living in Ontario.Based on their postal code when they were diagnosed, cases of colorectal cancer identified from the Ontario Cancer Registry were assigned to census geographic areas with high (33% or more) or low percentages of Aboriginal identity residents, using the Postal Code Conversion File Plus (PCCF+). To account for potential misclassification by the PCCF+, Indian reserves for which assignment through postal codes is likely to be accurate were identified. Age-standardized incidence rates and rate ratios were calculated to compare colorectal cancer incidence in high-Aboriginal identity areas or on Indian reserves with incidence in low-Aboriginal identity areas.Colorectal cancer incidence was significantly higher for residents of high- versus low-Aboriginal identity areas in Ontario (rate ratio for men = 1.44, 95% CI = 1.26-1.63; rate ratio for women = 1.42, 95% CI = 1.23-1.63), a disparity that persisted by age group. When the Aboriginal sample was limited to residents of Indian reserves, the difference was statistically significant only for men and for people aged 50 to 74.The incidence of colorectal cancer differs across areas of Ontario with high and low percentages of Aboriginal identity residents.

To examine the relationship between selective nonresponse to a psychosocial questionnaire and mortality after acute myocardial infarction (AMI).Two thousand six hundred and ninety AMI survivors after AMI hospitalization were recruited to complete a 30-day follow-up interview. Patients were classified into four groups (survey nonparticipation and complete, partial, and no item nonresponse) according to their degree of response to the Medical Outcomes Study (MOS) Social Support Survey (MOS-SSS). Cox proportional hazard models, adjusted for baseline sociodemographic, clinical, and psychosocial (i.e., social isolation) characteristics, were used to examine all-cause mortality, 3 years post-AMI, across the response levels.13.9% of the eligible patients refused follow-up participation; MOS-SSS item nonresponse was present in up to 14.7% of participants and was more frequent among the elderly, socially disadvantaged, and those with higher clinical risk. A nonresponse mortality gradient existed, ranging from 8.9% (no item nonresponse) to 18.7% (complete item nonresponse) (P0.001). After adjusting for baseline characteristics, complete item nonresponse remained significantly associated with mortality (hazard ratio: 1.33; 95% confidence interval: 1.02-1.73).Item nonresponse to a social support questionnaire is associated with higher mortality post-AMI. Although explanatory factors may include age and baseline clinical risk, additional psychosocial and/or unmeasured factors may account for the poorer prognosis.