Demography and Social Epidemiology of Admissions to the Colorado Insane Asylum, 1879–1899

2014 ◽  
Vol 38 (1-2) ◽  
pp. 251-271 ◽  
Author(s):  
Ann L. Magennis ◽  
Michael G. Lacy
Keyword(s):  
Census Data ◽  
Social Epidemiology ◽  
Foreign Born ◽  
Personal Service ◽  
Admission Rates ◽  
Service Category ◽  
The Us ◽  
Males And Females ◽  
Urban Concentration ◽  
Us Census

This paper analyzes admissions to the Colorado Insane Asylum from 1879 to 1900. We estimate and compare admission rates across sex, age, marital, occupation, and immigration status using original admission records in combination with US census data from 1870 to1900. We show the extent to which persons in various status groups, who varied in power and social advantage, differed in their risk of being institutionalized in the context of nineteenth-century Colorado. Our analysis showed that admission or commitment to the Asylum did not entail permanent incarceration, as more than half of those admitted were discharged within six months. Men were admitted at higher rates than women, even after adjusting for age. Marital status also affected the risk of admission; single and divorced persons were admitted at about 1.5 times the rate of their married counterparts. Widows of either sex were even more likely to be admitted to the Asylum, and the risk increased with age. Persons in lower income/lower prestige occupations were more likely to be institutionalized. This included occupations in the domestic and personal service category in the US census, and this was evident for both males and females. Foreign-born men and women were admitted at, respectively, twice and three times the rate of their native counterparts, with particularly elevated rates observed among the Irish. In general, admission to the Colorado Insane Asylum appears to differ only in a slightly greater admission of males when compared to similar contemporaneous institutions in the East, despite the obvious differences in the Colorado population size and urban concentration.

Choice and Conflict about Census Data Adjusting the American Census Count

1991 ◽  
Vol 11 (4) ◽  
pp. 357-398 ◽  
Author(s):  
Michael L. Cohen
Keyword(s):  
Census Data ◽  
Political Representation ◽  
The United States ◽  
Political Conflict ◽  
Census Bureau ◽  
Census Count ◽  
Social Fact ◽  
The Us ◽  
Census Adjustment ◽  
Us Census

ABSTRACTThe census is a social fact, the outcome of a process that involves the interaction of public laws and institutions and citizens' responses to an official inquiry. However, it is not a ‘hard’ fact. Reasons for inevitable defects in the census count are listed in the first section; the second section reports efforts by the US Census Bureau to identify sources of error in census coverage, and make estimates of the size of the errors. The use of census data for policy purposes, such as political representation and allocating funds, makes these defects controversial. Errors may be removed by making adjustments to the initial census count. However, because adjustment reallocates resources between groups, it has become the subject of political conflict. The paper describes the conflict between statistical practices, laws and public policy about census adjustment in the United States, and concludes by considering the extent to which causes in America are likely to be found in other countries.

scholarly journals The prevalence of MS in the United States

Neurology ◽  
2019 ◽  
Vol 92 (10) ◽  
pp. e1029-e1040 ◽  
Author(s):  
Mitchell T. Wallin ◽  
William J. Culpepper ◽  
Jonathan D. Campbell ◽  
Lorene M. Nelson ◽  
Annette Langer-Gould ◽  
...  
Keyword(s):  
United States ◽  
Census Data ◽  
Adult Population ◽  
The United States ◽  
Health Claims ◽  
The North ◽  
Time Period ◽  
The Us ◽  
Group A ◽  
Us Census

ObjectiveTo generate a national multiple sclerosis (MS) prevalence estimate for the United States by applying a validated algorithm to multiple administrative health claims (AHC) datasets.MethodsA validated algorithm was applied to private, military, and public AHC datasets to identify adult cases of MS between 2008 and 2010. In each dataset, we determined the 3-year cumulative prevalence overall and stratified by age, sex, and census region. We applied insurance-specific and stratum-specific estimates to the 2010 US Census data and pooled the findings to calculate the 2010 prevalence of MS in the United States cumulated over 3 years. We also estimated the 2010 prevalence cumulated over 10 years using 2 models and extrapolated our estimate to 2017.ResultsThe estimated 2010 prevalence of MS in the US adult population cumulated over 10 years was 309.2 per 100,000 (95% confidence interval [CI] 308.1–310.1), representing 727,344 cases. During the same time period, the MS prevalence was 450.1 per 100,000 (95% CI 448.1–451.6) for women and 159.7 (95% CI 158.7–160.6) for men (female:male ratio 2.8). The estimated 2010 prevalence of MS was highest in the 55- to 64-year age group. A US north-south decreasing prevalence gradient was identified. The estimated MS prevalence is also presented for 2017.ConclusionThe estimated US national MS prevalence for 2010 is the highest reported to date and provides evidence that the north-south gradient persists. Our rigorous algorithm-based approach to estimating prevalence is efficient and has the potential to be used for other chronic neurologic conditions.

scholarly journals Ethnic Differences in the Incidence of Leukemia

Blood ◽  
1957 ◽  
Vol 12 (1) ◽  
pp. 1-10 ◽  
Author(s):  
BRIAN MACMAHON ◽  
ERNEST K. KOLLER
Keyword(s):  
Age Differences ◽  
Census Data ◽  
Vital Statistics ◽  
High Rate ◽  
Foreign Born ◽  
Social Differences ◽  
High Incidence ◽  
The Common ◽  
Males And Females ◽  
Two Populations

Abstract A series of 1636 patients with leukemia, representing the white residents of Brooklyn diagnosed in the period 1943-52, is compared with selected census data for the population. After standardization for age differences in the two populations, the incidences of leukemia in the native-born and foreign-born populations of the borough are 45.3 and 61.0 per million per annum, respectively. The data suggest that a high incidence of leukemia in the Russian-born population accounts for the higher rate in the foreign-born group. Using affiliation of cemetery of burial as an index of religion, a series of 1368 deaths from leukemia is compared with a systematic one in 200 samples of all deaths in the same area. Leukemia is recorded as cause of death twice as frequently among Jews, as among others. This relationship is seen in both native-born and foreign-born groups, in males and females, at all ages and in all the common pathologic varieties of leukemia. No difference in leukemia incidence is seen between predominantly Catholic and predominantly Protestant groups. Evidence from United States vital statistics is used to show that the commonly observed difference between whites and Negroes imi leukemia death rates is closely associated with social differences between the two groups. Little or no difference in leukemia death rate exists between these two groups in Brooklyn, when allowance is made for the apparently high rate in the white Jewish population.

scholarly journals Hurricane Katrina Deaths, Louisiana, 2005

2008 ◽  
Vol 2 (4) ◽  
pp. 215-223 ◽  
Author(s):  
Joan Brunkard ◽  
Gonza Namulanda ◽  
Raoult Ratard
Keyword(s):  
Hurricane Katrina ◽  
Disaster Preparedness ◽  
Census Data ◽  
Gulf Coast ◽  
Mortality Data ◽  
Chi Square ◽  
Term Care ◽  
The Us ◽  
State Death ◽  
Us Census

ABSTRACTObjective: Hurricane Katrina struck the US Gulf Coast on August 29, 2005, causing unprecedented damage to numerous communities in Louisiana and Mississippi. Our objectives were to verify, document, and characterize Katrina-related mortality in Louisiana and help identify strategies to reduce mortality in future disasters.Methods: We assessed Hurricane Katrina mortality data sources received in 2007, including Louisiana and out-of-state death certificates for deaths occurring from August 27 to October 31, 2005, and the Disaster Mortuary Operational Response Team's confirmed victims' database. We calculated age-, race-, and sex-specific mortality rates for Orleans, St Bernard, and Jefferson Parishes, where 95% of Katrina victims resided and conducted stratified analyses by parish of residence to compare differences between observed proportions of victim demographic characteristics and expected values based on 2000 US Census data, using Pearson chi square and Fisher exact tests.Results: We identified 971 Katrina-related deaths in Louisiana and 15 deaths among Katrina evacuees in other states. Drowning (40%), injury and trauma (25%), and heart conditions (11%) were the major causes of death among Louisiana victims. Forty-nine percent of victims were people 75 years old and older. Fifty-three percent of victims were men; 51% were black; and 42% were white. In Orleans Parish, the mortality rate among blacks was 1.7 to 4 times higher than that among whites for all people 18 years old and older. People 75 years old and older were significantly more likely to be storm victims (P < .0001).Conclusions: Hurricane Katrina was the deadliest hurricane to strike the US Gulf Coast since 1928. Drowning was the major cause of death and people 75 years old and older were the most affected population cohort. Future disaster preparedness efforts must focus on evacuating and caring for vulnerable populations, including those in hospitals, long-term care facilities, and personal residences. Improving mortality reporting timeliness will enable response teams to provide appropriate interventions to these populations and to prepare and implement preventive measures before the next disaster. (Disaster Med Public Health Preparedness. 2008;2:215–223)

scholarly journals Task Specialization, Immigration, and Wages

2009 ◽  
Vol 1 (3) ◽  
pp. 135-169 ◽  
Author(s):  
Giovanni Peri ◽  
Chad Sparber
Keyword(s):  
Census Data ◽  
Intensity Data ◽  
Foreign Born ◽  
Task Specialization ◽  
Economic Analyses ◽  
Occupational Task ◽  
Us Census ◽  
Labor Skills

Large inflows of less educated immigrants may reduce wages paid to comparably-educated, native-born workers. However, if less educated foreign- and native-born workers specialize in different production tasks, because of different abilities, immigration will cause natives to reallocate their task supply, thereby reducing downward wage pressure. Using occupational task-intensity data from the O*NET dataset and individual US census data, we demonstrate that foreign-born workers specialize in occupations intensive in manual-physical labor skills while natives pursue jobs more intensive in communication-language tasks. This mechanism can explain why economic analyses find only modest wage consequences of immigration for less educated native-born workers. (JEL J24, J31, J61)

Racializing language

2004 ◽  
Vol 3 (3) ◽  
pp. 507-534 ◽  
Author(s):  
Jennifer Leeman
Keyword(s):  
National Identity ◽  
Data Collection ◽  
Language Ideologies ◽  
Census Data ◽  
Language Policies ◽  
Racial Categories ◽  
The Us ◽  
Us Census ◽  
Policies And Practices

This article builds on research on institutional language policies and practices, and on studies of the legitimization of racial categories in census data collection, in an exploration of language ideologies in the US Census. It traces the changes in language-related questions in the two centuries of decennial surveys, contextualizing them within a discussion of changing policies and patterns of immigration and nativism, as well as evolving hegemonic notions of race. It is argued that the US Census has historically used language as an index of race and as a means to racialize speakers of languages other than English, constructing them as essentially different and threatening to US cultural and national identity.

The Changing Space of Families: A Genealogical Approach

2019 ◽  
Vol 43 (1) ◽  
pp. 1-29
Author(s):  
Alice Bee Kasakoff
Keyword(s):  
Big Data ◽  
Spatial Dispersion ◽  
Data Sets ◽  
Foreign Born ◽  
Data Set ◽  
Adult Sons ◽  
Large Numbers ◽  
The Us ◽  
Changing Patterns ◽  
Us Census

This article highlights the usefulness of family trees for visualizing and understanding changing patterns of kin dispersion over time. Such spatial patterns are important in gauging how families influence outcomes such as health and social mobility. The article describes how rapidly growing families, originally from England, dispersed over the US North and established hubs where they originally settled that lasted hundreds of years, even as they repeated the process moving West. Fathers lived much closer to their adult sons in 1850 than they do today and many more had an adult son within a radius of 30 miles. Big Data from genealogical websites is now available to map large numbers of families. Comparing one such data set with the US Census of 1880 shows that the native-born population is well represented, but there are not as many foreign born or African Americans in these data sets. Pedigrees become less and less representative the further back in time they go because they only include lines that have survived into the present. Despite these and other limitations, Big Data make it possible to study family spatial dispersion going back many generations and to map past spatial connections in a wider variety of historical contexts and at a scale never before possible.

Do Federal Regulations Affect Gender, Racial, and Ethnic Disparities in Chronic Rhinosinusitis Research?

2021 ◽  
pp. 019459982110210
Author(s):  
Daniel B. Spielman ◽  
Rodney J. Schlosser ◽  
Andi Liebowitz ◽  
Rahul Sharma ◽  
Jonathan Overdevest ◽  
...  
Keyword(s):  
Clinical Trials ◽  
American Indian ◽  
Chronic Rhinosinusitis ◽  
Census Data ◽  
Ethnic Disparities ◽  
The Us ◽  
And Gender ◽  
Us Census ◽  
Federal Guidelines ◽  
Racial Ethnic

Objective The Food and Drug Administration and the National Institutes of Health (NIH) have asserted that diverse demographic representation in clinical trials is essential. In light of these federal guidelines, the objective of this study is to assess the racial, ethnic, and gender demographics of patients enrolled in clinical trials registered with the NIH that evaluate chronic rhinosinusitis with nasal polyposis (CRSwNP) relative to the demographics of the US population. Study Design Cross-sectional study. Setting Not applicable. Methods ClinicalTrials.gov was queried to identify all prospective clinical trials for CRSwNP. Individual study and pooled data were compared with national US census data. Results Eighteen studies were included comprising 4125 patients and evaluating dupilumab, mepolizumab, omalizumab, fluticasone/OptiNose, MediHoney, mometasone, and SINUVA. Women constituted 42.7% of clinical trial participants. Of the 4125 participants, 69.6% identified as White, 6.6% as Black, 20.8% as Asian, 0.1% as Pacific Islander, 0.4% as American Indian, 8.0% as Hispanic, and 2.4% as other. The racial, ethnic, and gender composition of the pooled study population differs significantly from national US census data, with underrepresentation of Black, Hispanic, Pacific Island, and American Indian individuals, as well as females ( P < .05). Conclusion The racial, ethnic, and gender demographics of patients enrolled in CRSwNP clinical trials registered with the NIH differ significantly from the demographics of the US population, despite federal guidelines advising demographically representative participation. Proactive efforts to enroll participants that better represent anticipated treatment populations should be emphasized by researchers, institutions, and editorial boards.

scholarly journals Creating Unbiased Machine Learning Models by Design

2021 ◽  
Vol 14 (11) ◽  
pp. 565
Author(s):  
Joseph L. Breeden ◽  
Eugenia Leonova
Keyword(s):  
Machine Learning ◽  
Credit Card ◽  
Census Data ◽  
Demographic Data ◽  
Machine Learning Model ◽  
The Us ◽  
Protected Class ◽  
Credit Card Data ◽  
Class Status ◽  
Us Census

Unintended bias against protected groups has become a key obstacle to the widespread adoption of machine learning methods. This work presents a modeling procedure that carefully builds models around protected class information in order to make sure that the final machine learning model is independent of protected class status, even in a nonlinear sense. This procedure works for any machine learning method. The procedure was tested on subprime credit card data combined with demographic data by zip code from the US Census. The census data serves as an imperfect proxy for borrower demographics but serves to illustrate the procedure.

scholarly journals How differential privacy will affect our understanding of population growth in the United States

2020 ◽  
Author(s):  
Alexis R Santos-Lozada ◽  
Danilo T Perez-Rivera ◽  
Aarti C. Bhat
Keyword(s):  
Population Growth ◽  
Census Data ◽  
Differential Privacy ◽  
The United States ◽  
The Us ◽  
Potential Impact ◽  
Us Census ◽  
Population Counts ◽  
Metropolitan Counties ◽  
Racial Ethnic

The implementation of a proposed differential privacy algorithm to 2020 US Census data releases, and other census products has brought about discussions about the consistency and reliability of the data produced under the proposed disclosure avoidance system. We test the potential impact of this change in disclosure avoidance systems to the tracking of population growth and distribution using county-level population counts. We ask how population counts produced under the differential privacy algorithm might lead to different conclusions regarding population growth for the total population and three major racial/ethnic groups in comparison to counts produced using the traditional methods. Our results suggest that the implementation of differential privacy, as proposed, will impact our understanding of population changes in the US. We find potential for overstating and understating growth and decline, with these effects being more pronounced for non-Hispanic blacks and Hispanics, as well as for non-metropolitan counties. These findings draw attention to the potential local consequences of the implementation of differential privacy for tracking demographic changes of the US population, which is bound to have implications for our understanding of the transformations the nation is going through.

Sign in / Sign up

Export Citation Format

Share Document