Sweden has one of the world's most eminent and exhaustive records of statistical information on its population. As early as the eighteenth century, ethnic notations were being made in parish registers throughout the country, and by the early nineteenth century a specific category for the Sami population had been added to the forms used to collect data for the Tabellverket (National Population Statistics). Beginning in 1860, the Sami were also counted in the first official census of the Swedish state. Nonetheless--and in contrast to many other countries--Sweden today lacks separate statistical information not only about its sole recognized indigenous population but also about other ethnic groups. The present paper investigates Sweden's attempts to enumerate its indigenous Sami population prior to World War II and the cessation of ethnic enumeration after the war. How have the Sami been identified and enumerated? How have statistical categories been constructed, and how have they changed over time? The aim of this essay is not to assess the validity of the demographic sources. Instead the paper will explore the historical, social, and cultural factors that have had a bearing on how a dominant administrative structure has dealt with the statistical construct of an indigenous population.
An analysis of the data from the 1981 census of Canada is presented concerning the aboriginal population aged 15 to 24, defined as including the Inuit, status Indian, non-status Indian, and Metis populations. Comparisons are made with the non-aboriginal population. Factors considered include geographic location, migration, family status, dependent children, educational status, labor force participation, unemployment, income, and industry.
National data about acute care hospitalization of Aboriginal people are scarce. This study addresses that information gap by describing patterns of hospitalization by Aboriginal identity for leading diagnoses for all provinces and territories except Quebec.
The 2006 Census was linked to the 2006/2007-to-2008/2009 Discharge Abstract Database, which contains hospital records from all acute care facilities in Canada (excluding Quebec). With these linked data, hospital records could be examined by Aboriginal identity, as reported to the census. Hospitalizations were grouped by International Classification of Diseases (ICD-10) chapters based on "the most responsible diagnosis." Age-standardized hospitalization rates were calculated per 100,000 population, and rate ratios (RR) were calculated for Aboriginal groups relative to non-Aboriginal people.
Hospitalization rates were almost invariably higher for First Nations living on and off reserve, Métis, and Inuit living in Inuit Nunangat than for the non-Aboriginal population, regardless of ICD diagnostic chapter. The ranking of age-standardized hospitalization rates by frequency of diagnoses varied slightly by Aboriginal identity. RRs were highest among First Nations living on reserve, especially for endocrine, nutritional and metabolic diseases (RR = 4.9), mental and behavioural disorders (RR = 3.6), diseases of the respiratory system (RR = 3.3), and injuries (RR = 3.2). As well, the rate for endocrine, nutritional and metabolic diseases was high among First Nations living off reserve (RR = 2.7). RRs were also high among Inuit for mental and behavioural disorders (RR = 3.3) and for diseases of the respiratory system (RR = 2.7).
Hospitalization rates varied by Aboriginal identity, and were consistent with recognized health disparities between Aboriginal and non-Aboriginal people. Because many factors besides health affect hospital use, further research is required to understand differences in hospital use by Aboriginal identity. These national data are relevant to health policy formulation and service delivery planning.
Research that has examined Aboriginal children's hospitalization rates at the national level has been limited to analyses of areas with large percentages of Aboriginal residents, rather than of Aboriginal individuals. This study uses linked census and administrative data to describe hospitalization patterns among children and youth aged 0 to 19, by Aboriginal identity, for all provinces and territories except Quebec.
The 2006 Census was linked to the 2006/2007-to-2008/2009 Discharge Abstract Database, which contains hospital records from all acute care facilities (except Quebec). Hospital records were examined by Aboriginal identity, as reported to the census, according to International Classification of Diseases chapters based on "the most responsible diagnosis." Age-standardized hospitalization rates (ASHRs) were calculated per 100,000 population, and age-standardized rate ratios (RRs) were calculated for Aboriginal groups relative to non-Aboriginal people.
ASHRs were consistently higher among Aboriginal children and youth relative to their non-Aboriginal counterparts; rates for children aged 0 to 9 were 1.4 to 1.8 times higher; for youth aged 10 to 19, 2.0 to 3.8 times higher. For all children aged 0 to 9, the leading cause of hospitalization was "diseases of the respiratory system," but RRs for Aboriginal children ranged from 1.7 to 2.5, compared with non-Aboriginal children. Disparities between Aboriginal and non-Aboriginal 10- to 19-year-olds were pronounced for injuries due to assaults (RRs from 4.8 to 10.0), self-inflicted injuries (RRs from 2.7 to 14.2), and pregnancy, childbirth and the puerperium (RRs from 4.1 to 9.8).
Additional research is needed to examine reasons for the disparities in hospitalization rates between Aboriginal and non-Aboriginal children and youth.
The association between lower socioeconomic status and poorer health outcomes has been observed using both individual-level and aggregate-level measures of income and education. While both are predictive of health outcomes, previous research indicates poor agreement between individual-level and aggregate-level measures. The purpose of this study was to determine the level of agreement between aggregate-level and individual-level measures of income and education among three distinct patient groups, specifically asthma, diabetes, and rheumatoid patients.
Individual-level measures of annual household income and education were derived from three separate surveys conducted among patients with asthma (n = 359), diabetes (n = 281) and rheumatoid arthritis (n = 275). Aggregate-level measures of income and education were derived from the 2001 Canadian census, including both census tract-and dissemination area-level measures. Cross-tabulations of individual-level income by aggregate-level income were used to determine the percentage of income classifications in agreement. The kappa statistic (simple and weighted), Spearman's rank correlations, and intra-class correlation coefficient (ICC) were also calculated. Individual-level and aggregate-level education was compared using Chi-Square tests within patient groups. Point biserial correlation coefficients between individual-level and aggregate-level education were computed.
Individual-level income was poorly correlated with aggregate-level measures, which provided the worst estimations of income among patients in the lowest income category at the individual-level. Both aggregate-level measures were best at approximating individual-level income in patients with diabetes, in whom aggregate-level estimates were only significantly different from individual-level measures for patients in the lowest income category. Among asthma patients, the proportion of patients classified by aggregate-level measures as having a university degree was significantly lower than that classified by individual-level measures. Among diabetes and rheumatoid arthritis patients, differences between aggregate and individual-level measures of education were not significant.
Agreement between individual-level and aggregate-level measures of socioeconomic status may depend on the patient group as well as patient income. Research is needed to characterize differences between patient groups and help guide the choice of measures of socioeconomic status.
This article documents the prevalence and national profile of American Indian/Alaskan Native (AI/AN) grandparents who are raising their grandchildren, based on data from the American Community Survey/Census 2000 Supplementary Survey. In 2000 there were estimated to be nearly 53,000 AI/AN grandparent caregivers age 45 and older in the United States. Almost half of the caregiving grandparents had been raising a grandchild for five years or longer. The findings reveal a portrait of grandparents committed to raising their grandchildren despite the fact that many were living in extreme poverty, with ill health, and with limited resources and services. One-third of grandparent caregivers were living below the poverty line, and only one-quarter of these were receiving public assistance. Even when compared with their noncaregiving AI/AN peers, grandparents raising grandchildren were disproportionately female, poor, living with a functional disability, and living in overcrowded conditions. Implications for social work practice are presented and recommendations for policy and research are discussed.
A person's racial or ethnic self-identification can change over time and across contexts, which is a component of population change not usually considered in studies that use race and ethnicity as variables. To facilitate incorporation of this aspect of population change, we show patterns and directions of individual-level race and Hispanic response change throughout the United States and among all federally recognized race/ethnic groups. We use internal U.S. Census Bureau data from the 2000 and 2010 censuses in which responses have been linked at the individual level (N = 162 million). Approximately 9.8 million people (6.1 %) in our data have a different race and/or Hispanic-origin response in 2010 than they did in 2000. Race response change was especially common among those reported as American Indian, Alaska Native, Native Hawaiian, Other Pacific Islander, in a multiple-race response group, or Hispanic. People reported as non-Hispanic white, black, or Asian in 2000 usually had the same response in 2010 (3 %, 6 %, and 9 % of responses changed, respectively). Hispanic/non-Hispanic ethnicity responses were also usually consistent (13 % and 1 %, respectively, changed). We found a variety of response change patterns, which we detail. In many race/Hispanic response groups, we see population churn in the form of large countervailing flows of response changes that are hidden in cross-sectional data. We find that response changes happen across ages, sexes, regions, and response modes, with interesting variation across racial/ethnic categories. Researchers should address the implications of race and Hispanic-origin response change when designing analyses and interpreting results.
This study of cancer survival compared adults in Toronto, Ontario and three US metropolitan areas: Seattle, Washington; San Francisco, California; and Hartford, Connecticut. It examined whether socioeconomic status has a differential effect on cancer survival in Canada and the United States.
The Ontario Cancer Registry and the National Cancer Institute's Surveillance, Epidemiology and End
(SEER) programme provided a total of 23,437 and 37,329 population-based primary malignant cancer cases for the Toronto and US samples, respectively (1986-1988, followed until 1994). Census-based measures of socioeconomic status were used to ecologically control absolute income status.
Among residents of low-income areas, persons in Toronto experienced a 5 year survival advantage for 13 of 15 cancer sites [minimally one gender significant at 95 per cent confidence interval (CI)]. An aggregate 35 per cent survival advantage among the Canadian cohort was demonstrated (survival rate ratio (SRR) = 1.35, 95 per cent CI= 1.30-1.40), and this effect was even larger among younger patients not yet eligible for Medicare coverage in the United States (SRR = 1.46, 95 per cent CI = 1.40-1.52).
Systematically replicating a previous Toronto-Detroit comparison, this study's observed consistent pattern of Canadian survival advantage across various cancer sites suggests that their more equitable access to preventive and therapeutic health care services may be responsible for the difference.
Few Canadian data sources allow the examination of disparities by ethnicity, language, or immigrant status in occupational exposures or health outcomes. However, it is possible to document the mechanisms that can create disparities, such as the over-representation of population groups in high-risk jobs. We evaluated, in the Montréal context, the relationship between the social composition of jobs and their associated risk level.
We used data from the 2001 Statistics Canada census and from Québec's workers' compensation board for 2000-2002 to characterize job categories defined as major industrial groups crossed with three professional categories (manual, mixed, non-manual). Immigrant, visible, and linguistic minority status variables were used to describe job composition. The frequency rate of compensated health problems and the average duration of compensation determined job risk level. The relationship between the social composition and risk level of jobs was evaluated with Kendall correlations.
The proportion of immigrants and minorities was positively and significantly linked to the risk level across job categories. Many relationships were significant for women only. In analyses done within manual jobs, relationships with the frequency rate reversed and were significant, except for the relationship with the proportion of individuals with knowledge of French only, which remained positive.
Immigrants, visible, and linguistic minorities in Montréal are more likely to work where there is an increased level of compensated risk. Reversed relationships within manual jobs may be explained by under-reporting and under-compensation in vulnerable populations compared to those with knowledge of the province's majority language.
To test the hypothesis that manual workers are at higher risk of death than are non-manual employees when living in municipalities with higher income inequality.
Hierarchical regression was used for the analysis were individuals were nested within municipalities according to the 1990 Swedish census. The outcome was all-cause mortality 1992-1998. The income measure at the individual level was disposable family income weighted against composition of family; the income inequality measure used at the municipality level was the Gini coefficient.
The study population consisted of 1 578 186 people aged 40-64 years in the 1990 Swedish census, who were being reported as unskilled or skilled manual workers, lower-, intermediate-, or high-level non-manual employees.
There was no significant association between income inequality at the municipality level and risk of death, but an expected gradient with unskilled manual workers having the highest risk and high-level non-manual employees having the lowest. However, in the interaction models the relative risk (RR) of death for high-level non-manual employees was decreasing with increasing income inequality (RR = 0.77; 95% CI, 0.63-0.93), whereas the corresponding risk for unskilled manual workers increased with increasing income inequality (RR = 1.24; 95% CI, 1.06-1.46). The RRs for skilled manual, low- and medium- level non-manual employees were not significant. Controlling for income at the individual level did not substantially alter these findings, neither did potential confounders at the municipality level.
The findings suggest that there could be a differential impact from income inequality on risk of death, dependent on individuals' social position.