Predictive global trends in the incidence and mortality of pancreatic cancer based on geographic location, socio-economic status, and demographic shift

2016 ◽  
Vol 114 (6) ◽  
pp. 736-742 ◽  
Author(s):  
Chandrakanth Are ◽  
Sanjib Chowdhury ◽  
Humera Ahmad ◽  
Advaitaa Ravipati ◽  
Tianqiang Song ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Economic Status ◽  
Geographic Location ◽  
Demographic Shift ◽  
Global Trends ◽  
Socio Economic Status ◽  
Incidence And Mortality

Possible Differential Wisc Patterns for Retarded Delinquents

1975 ◽  
Vol 37 (3) ◽  
pp. 887-894 ◽  
Author(s):  
Denis G. Lewandowski ◽  
Dennis P. Saccuzzo
Keyword(s):  
Juvenile Offenders ◽  
Cross Validation ◽  
Economic Status ◽  
Correctional Facility ◽  
Geographic Location ◽  
Post Hoc Analysis ◽  
Socio Economic Status ◽  
Post Hoc ◽  
Criteria For Selection ◽  
Selection Of

Under controlled conditions, an attempt was made to assess the generalizability of Wechsler's WAIS hypotheses for the non-defective adolescent sociopath to 80 retarded juvenile offenders. Groups were separated according to race and sex while IQ, socio-economic status, and geographic location were controlled. The criteria for selection of subjects were incarceration in a state juvenile correctional facility and a Full Scale WISC IQ below 70. Results suggested that many of Wechsler's WAIS signs applicable to non-defective IQ ranges probably are not appropriate for WISC scores of these retarded delinquents. The difficulty in identifying the signs from such a truncated range of scaled scores was discussed. Post hoc analysis, nevertheless, provided some potentially useful WISC signs for combinations of race and sex of retarded delinquents. The need for cross-validation of these signs was stressed.

scholarly journals Municipality and Adjusted Gross Income Influence Outcome of Patients Diagnosed with Pancreatic Cancer in a Newly Developed Cancer Center in Mercer County New Jersey, USA, a Single Center Study

Cancers ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1498
Author(s):  
Cataldo Doria ◽  
Patrick De Deyne ◽  
Sherry Dolan ◽  
Jooyeun Chung ◽  
Karen Yatcilla ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Overall Survival ◽  
New Jersey ◽  
Economic Status ◽  
Outcome Variable ◽  
Cancer Center ◽  
Convenience Sample ◽  
Socio Economic Status ◽  
Gross Income ◽  
Zip Code

Socioeconomic status (SES) correlates directly to ZIP code. Mercer County is not atypical as a collection of a dozen municipalities with a suburban/metropolitan population of 370,430 in the immediate vicinity of a major medical center. The purpose of this study for Mercer County, New Jersey, USA is to determine whether a patient’s ZIP code is related to the outlook of pancreatic cancer defined as staging at diagnosis, prevalence, overall survival, type of insurance, and recurrence. Our hypothesis was that specific variables such as socio-economic status or race could be linked to the outcome of patients with pancreatic cancer. We interrogated a convenience sample from our cancer center registry and obtained 479 subjects diagnosed with pancreatic cancer in 1998-2018. We selected 339 subjects by ZIP code, representing the plurality of the cases in our catchment area. The outcome variable was overall survival; predictor variables were socio-economic status (SES), recurrence, insurance, type of treatment, gender, cancer stage, age, and race. We converted ZIP code to municipality and culled data using adjusted gross income (AGI, FY 2017). Comparative statistical analysis was performed using chi-square tests for nominal and ordinal variables, and a two-way ANOVA test was used for continuous variables; the p-value was set at 0.05. Our analysis confirmed that overall survival was significantly higher for Whites and for individuals who live in a municipality with a high SES. Tumor stage at the time of diagnosis was not different among race and SES; however, statistically significant differences for race or SES existed in the type of treatment received, with disparities found in those who received radiation therapy and surgery but not chemotherapy. The data may point to a lack of access to specific care modalities that subsequently may lead to lower survival in an underserved population. Access to care, optimal nutritional status, overall fitness, and co-morbidities could play a major role and confound the results. Our study suggests that low SES has a negative impact on overall pancreatic cancer survival. Surgery for pancreatic cancer should be appropriately decentralized to those community cancer centers that possess the expertise and the infrastructure to carry out specialized treatments regardless of race, ethnicity, SES, and insurance.

scholarly journals Epidemiological characteristics and outcomes of COVID-19 cases: mortality inequalities by socio-economic status, Barcelona, Spain, 24 February to 4 May 2020

2021 ◽  
Vol 26 (20) ◽  
Author(s):  
Julieta Politi ◽  
Mario Martín-Sánchez ◽  
Lilas Mercuriali ◽  
Blanca Borras-Bermejo ◽  
Joaquín Lopez-Contreras ◽  
...  
Keyword(s):  
Chronic Conditions ◽  
Economic Status ◽  
Health Agency ◽  
Population Based ◽  
Multiple Chronic Conditions ◽  
Risk Of Death ◽  
Socio Economic Status ◽  
Increased Risk ◽  
Incidence And Mortality ◽  
Epidemiological Characteristics

Background Population-based studies characterising outcomes of COVID-19 in European settings are limited, and effects of socio-economic status (SES) on outcomes have not been widely investigated. Aim We describe the epidemiological characteristics of COVID-19 cases, highlighting incidence and mortality rate differences across SES during the first wave in Barcelona, Catalonia, Spain. Methods This population-based study reports individual-level data of laboratory-confirmed COVID-19 cases diagnosed from 24 February to 4 May 2020, notified to the Public Health Agency of Barcelona and followed until 15 June 2020. We analysed end-of-study vital status and the effects of chronic conditions on mortality using logistic regression. Geocoded addresses were linked to basic health area SES data, estimated using the composed socio-economic index. We estimated age-standardised incidence, hospitalisation, and mortality rates by SES. Results Of 15,554 COVID-19-confirmed cases, the majority were women (n = 9,028; 58%), median age was 63 years (interquartile range: 46–83), 8,046 (54%) required hospitalisation, and 2,287 (15%) cases died. Prevalence of chronic conditions varied across SES, and multiple chronic conditions increased risk of death (≥ 3, adjusted odds ratio: 2.3). Age-standardised rates (incidence, hospitalisation, mortality) were highest in the most deprived SES quartile (incidence: 1,011 (95% confidence interval (CI): 975–1,047); hospitalisation: 619 (95% CI: 591–648); mortality: 150 (95% CI: 136–165)) and lowest in the most affluent (incidence: 784 (95% CI: 759–809); hospitalisation: 400 (95% CI: 382–418); mortality: 121 (95% CI: 112–131)). Conclusions COVID-19 outcomes varied markedly across SES, underscoring the need to implement effective preventive strategies for vulnerable populations.

scholarly journals The utility of historical electoral roll records and their effect on the association of regularity of GP contact and potentially preventable diabetic hospitalisations

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Rachael Moorin ◽  
David Youens
Keyword(s):  
At Risk ◽  
Service Use ◽  
Economic Status ◽  
Geographic Location ◽  
Limited Information ◽  
Services Research ◽  
Cross Sectional ◽  
Electoral Roll ◽  
Socio Economic Status

ABSTRACTObjectivesCorrectly ascertaining person-time at risk is paramount to longitudinal studies of health services research and relies on the ability to track the status of individuals throughout the study. Administrative health data contain limited information on where study subjects live in the time between episodes of health service use. Accurate ascertainment of person-time at risk is important particularly when it varies differentially across exposure groups or covariates. Historical electoral roll data allows better specification of person-time and also provides longitudinal information on geographic location facilitating the inclusion of accessibility and socio-economic status longitudinally. This study evaluated the utility of Australian historical electoral roll data to capture place of residence throughout the time line of a whole of population longitudinal cohort study over 20 years to better ascertain person-time at risk and changes in socio-economic status (SES).ApproachThe association between regularity of GP contact and potentially preventable hospitalisations (PPHs) in WA was modelled using person-level linked data where the time at risk and socio-economic status for both the exposure (regularity of GP contact) and outcome (PPHs) was assumed to be constant throughout the follow up until death. The analysis was then repeated incorporating historical (longitudinal) electoral roll data. These data partitioned follow up time and socio-economic status according to location of residence within the State to better characterise access and SES and included removal (out-of-State/country migration) and re-enrolment records.ResultsSubstantial differences were found in the number of people at risk (46,625 (13%) of people were never at risk) and person-time at risk (reduction of 473,708 (22%) person-years at risk) when cross-sectional electoral roll and health administrative data were augmented using historical electoral roll data. Substantial changes in residential postcode (up to 25 changes) were observed and these impacted on the accessibility and SES classification across the duration of the study. These changes significantly impacted the magnitude of the relationship between GP contacts on PPHs determined by models.ConclusionsCurrently cross-sectional electoral roll data are available to researchers in WA solely for the purposes of identifying and characterising a cohort at baseline. However these data are longitudinal and contain important information that improve analyses. Information on their utility is important so as to leverage their availability from the Australian Electoral Commission.

Socio-economic status influences chance of undergoing surgical treatment for pancreatic cancer in The Netherlands

Pancreatology ◽  
2015 ◽  
Vol 15 (3) ◽  
pp. S101
Author(s):  
Maikel Bakens ◽  
Yvette van Gestel ◽  
Marlies Bongers ◽  
Valery Lemmens ◽  
Ignace de Hingh
Keyword(s):  
Pancreatic Cancer ◽  
Surgical Treatment ◽  
The Netherlands ◽  
Economic Status ◽  
Socio Economic Status

scholarly journals Neighbourhood-level risk factors of COVID-19 incidence and mortality

2021 ◽  
Author(s):  
Trevor van Ingen ◽  
Samantha Akingbola ◽  
Kevin A. Brown ◽  
Nick Daneman ◽  
Sarah A. Buchan ◽  
...  
Keyword(s):  
Latin American ◽  
Low Income ◽  
Disease Surveillance ◽  
Economic Status ◽  
Surveillance Systems ◽  
Socio Economic Status ◽  
Housing Characteristics ◽  
Incidence And Mortality ◽  
Neighbourhood Level ◽  
Socio Demographic Factors

AbstractBackgroundRacialized and low income communities face disproportionally high rates of coronavirus 2019 (COVID-19) infection and death. However, data on inequities in COVID-19 across granular categories of socio-demographic characteristics is more sparse.MethodsNeighbourhood-level counts of COVID-19 cases and deaths in Ontario, Canada recorded as of July 28th, 2020 were extracted from provincial and local reportable infectious disease surveillance systems. Associations between COVID-19 incidence and mortality and 18 neighbourhood-level measures of immigration, race, housing and socio-economic characteristics were estimated with Poisson generalized linear mixed models. Housing characteristic variables were subsequently added to models to explore if housing may have a confounding influence on the relationships between immigration, race, and socio-economic status and COVID-19 incidence.ResultsThere were large inequities in COVID-19 incidence and mortality across the socio-demographic variables examined. Neighbourhoods having a higher proportion immigrants, racialized populations, large households and low socio-economic status were associated with COVID-19 risk. Adjusting for housing characteristics, especially unsuitably crowded housing, attenuated COVID-19 risks. However persistent risk remained for neighbourhoods having high proportions of immigrants, racialized populations, and proportion of Black, Latin American, and South Asian residents.ConclusionsSocio-demographic factors account for some of the neighbourhood-level differences in COVID-19 across Ontario. Housing characteristics account for a portion, but not all, of the excess burden of COVID-19 experienced by immigrant, racialized, low income and low education populations.

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