Aggregate Census Data Research Articles

Disparities in gynecologic oncology clinical trial availability in the United States: A state-level analysis.

e23128 Background: Disparities in minority participation in gynecologic cancer clinical trials is well documented. FDA guidance stipulates geographic informed analyses to reduce barriers to trial participation. We performed a geographical analyses of gynecologic cancer clinical trials in the United States relative to racial distribution and social vulnerability indices to identify areas of increased need. Methods: We performed a cross-sectional analysis of NIH ClinicalTrials.gov by retrieving all trials first posted 1/1/2013 through to 1/10/2024. We searched for ovarian, uterine, cervical, endometrial, vaginal/vulvar and gynecological cancer. We reviewed enrollment criteria to exclude non-gynecological cancers (1643 trials) or non-invasive gynecological conditions (224 trials). We aggregated census data, state-level total population size, percent Non-Hispanic White (NHW), and the FEMA Expected Annual Loss per state as a measure of social vulnerability. Using R statistical software (v 4.3.1), we measured the association between these variables and the number of gynecological trials per 100,000 persons using Pearson’s correlation. Results: We identified 3,428 trials, filtered down to 1,561 invasive cancer trials. The most common trials were ovarian (911, 58.3%) and cervical (438, 28.0%), followed by endometrial (385, 24.6%), uterine (158, 10.1%), vulva-vaginal (78, 4.99%), and 7.62% genetic-based. Texas had the highest number of trials (501) followed by California (454) and New York (427). The state with the highest population-adjusted number of trials was South Dakota (8.57 trials per 100,000 persons), followed by Rhode Island at 8.38 per 100,000 persons. California, Mississippi, and Puerto Rico had the lowest number of trials per 100,000 persons with 1.148, 0.979, 0.466 respectively. States/territories with greater than 4 trials per 100,000 were comprised of populations that were > 50% NHW. The correlation between the state-level percentage of NHW in 2020 and the number of trials per 100,000 persons was p = 0.057 indicating that there was a correlation between Whiteness at the state-level and trial availability. We found that states with higher FEMA expected annual loss had lower numbers of gynecological trials per 100,000 persons (p < 0.001). Conclusions: We found a disparity in the geographical distribution of trials available for gynecological cancers that was correlated with racial disparities and social vulnerability. Efforts to increase decentralization of trials and improve access and availability of gynecologic cancer clinical trials are necessary to increase equity for minority representation in clinical trials at the national level.

The role of visa class in the location choices of immigrants in Australia at the regional and neighbourhood scales

Australia’s pro-immigration policies have played a vital role in national population growth, serving to address what would otherwise be chronic labour shortages and population ageing. While migrants to Australian have shown a clear preference for cities and tend to locate with co-ethnics, variations by visa class—employment, family reunification, and asylum—have yet to be fully explored. This paper aims to identify variations in settlement patterns of immigrants in Australia by visa types and the factors underpinning these choices, paying particular attention to ethnic networks and employment opportunities. We apply a series of negative binomial regressions to aggregate census data linked to visa status. At the suburb level, our results show the importance of the presence of compatriots in shaping the location choices of family migrants, with the exception of skilled and humanitarian immigrants from China, Malaysia and Thailand. At the regional level, skilled migrants, including skilled regional migrants, respond to employment opportunities to a greater extent than family and humanitarian migrants.

Multi-scale spatial analysis of household car ownership using distance-based Moran's eigenvector maps: Case study in Loire-Atlantique (France)

Analyzing spatial structures of transportation data at various scales can be of prime interest to transportation planning and governance. In recent years, multi-scale spatial analysis methods have been developed and used in fields like ecology and geography, but only a few studies have applied these methods to transportation data. However, such methods can provide an efficient exploratory tool for: identifying those scales at which transportation data vary spatially; modeling the spatial structures at each scale; and determining the processes at work that explain these spatial structures. This paper describes and demonstrates how a multi-scale spatial analysis method, namely distance-based Moran's eigenvector maps (dbMEM), can be applied to study the spatial layout of car ownership. For this analysis, we rely on aggregated census data for small statistical areas within France's Loire-Atlantique administrative region. At first, 176 spatial vectors representing spatial patterns with a positive autocorrelation are constructed. Among the 176 vectors, only 23 significant ones are retained after performing a regression with car ownership as the dependent variable. Next, we divide these spatial vectors into three sub-models representing three spatial scales: broad scale, medium scale, and fine scale. Lastly, we identify a set of sociodemographic factors capable of explaining the spatial variation at each scale, i.e.: the broad-scale variation is mainly explained by population density, couples with children and income variables; the medium scale by couples with children, share of individuals in the 25–54 year age range and income; and the fine scale by couples with children and income variables.

Changes in ethnic spatial segregation across English housing market areas (2001-2011): identifying ethnic and context configurations

Using a combination of segregation indices – calculated with aggregated census data obtained for small geographies (lower layer super output areas, LSOAs) – the paper shows levels and changes in spatial segregation in eight housing market areas (HMAs) in England between 2001 and 2011, for the six most numerous non-white ethnic minority groups (Indian, Pakistani, Bangladeshi, Chinese, Caribbean, and African). The double comparison between HMAs and between groups, together with the use of different measures of segregation, enables identifying different patterns of segregation, as well as ‘ethnic’ and ‘context’ configurations. Specifically, while some segregation patterns are distinctive to certain ethnic minority groups independently of their location, others are specific to some or most groups residing in certain contexts. As examples of the first, Pakistanis and Bangladeshis’ segregation levels are often the highest, independently of their HMA of residence; and also seem to be following specific (and contrasting) patterns of change over time. As regards context configurations, Birmingham appears as a favourable context for changes in spatial segregation, while the opposite is observed for Leicester and Bradford.

Comparative analysis of the results of censuses of Saint Petersburg, Moscow and Warsaw in the 1880s in the context of studying women's employment

The reforms and post-reform period of the second half of the XIX century mark significant changes in the political, socioeconomic, and cultural life of the country, and acceleration of urbanization by the beginning of the 1880s. The author also indicates the growing number of employed women, which was particularly evident in the large cities of the Russian Empire. For studying the problem of women’s employment of the end XIX century, the article used the aggregated census data of the three largest cities of the Russian Empire – Saint Petersburg (1881), Moscow (1882), and the capital of the Kingdom of Poland Warsaw (1882). The subject of this article is the examination and analysis of the number of female workers in each group and information about occupational groups, contained in the form of tables in separate volumes of censuses. Emphasis is placed on the quantitative distribution of women by occupational groups, as well as broader categories – types of activity; this allows determining the differences for each city, as well as comparing Saint Petersburg, Moscow and Warsaw during the 1880s in percentage terms. The conclusion is made that the market for female household personnel and day laborers was more developed in Warsaw, while the number of women employed in household service and industrial sector prevailed in Moscow and Saint Petersburg.

Getting the best of both worlds: a framework for combining disaggregate travel survey data and aggregate mobile phone data for trip generation modelling

Traditional approaches to travel behaviour modelling primarily rely on household travel survey data, which is expensive to collect, resulting in small sample sizes and infrequent updates. Furthermore, such data is prone to reporting errors which can lead to biased parameter estimates and subsequently incorrect predictions. On the other hand, mobile phone call detail records (CDRs), which report the timestamped locations of mobile communication events, have been successfully used in the context of generating travel patterns. However, due to their anonymous nature, such records have not been widely used in developing mathematical models establishing the relationship between the observed travel behaviour and influencing factors such as the attributes of the alternatives and the decision makers. In this paper, we propose a joint modelling framework that utilises the advantages offered by both travel survey data and low-cost CDR data to optimise the prediction capacity of traditional trip generation models. In this regard, we develop a model that jointly explains the reported trips for each individual in the household survey data and ensures that the aggregated zonal trip productions are close to those derived from CDR data. This framework is tested using data from Dhaka. Bangladesh consisting of household survey data (65,419 persons in 16,750 households), mobile phone CDR data (over 600 million records generated by 6.9 million users), and aggregate census data. The model results show that the proposed framework improves the spatial and temporal transferability of the joint models over the base model which relies on household travel survey data alone. This serves as a proof-of-concept that augmenting travel survey data with mobile phone data holds significant promise for the travel behaviour modelling community, not only by saving the cost of data collection, but also improving the prediction capability of the models.

Previsão da demanda por viagens domiciliares através de método sequencial baseado em população sintética e redes neurais artificiais

A estimativa de viagens por domicílio é fundamental para a tomada de decisões relativas ao planejamento de transportes. Porém, para obter essa estimativa são necessários dados desagregados dos domicílios, que geralmente são obtidos pela Pesquisa Domiciliar de Origem e Destino. No entanto, a maioria das cidades enfrenta problemas para a aquisição desses dados, uma vez que este tipo de pesquisa é de alto custo de preparação e execução. Desta forma, surge a necessidade de ferramentas que forneçam dados confiáveis e com baixo custo. Assim, o objetivo deste artigo é apresentar um método sequencial, para estimativa de viagens domiciliares, a partir de população sintética e Redes Neurais Artificiais (RNAs). A população sintética foi baseada em dados agregados do censo e simulação Monte Carlo. Os resultados obtidos com as RNAs foram comparados aos resultados de um modelo linear tradicional, mostrando-se melhores e corroborando o potencial do uso de RNAs para modelagem da demanda por transportes. As viagens sintéticas por domicílio foram validadas a partir dos dados desagregados da Pesquisa Origem-Destino (2007) e testes de hipótese para comparação de valores típicos e distribuições populacionais. Em 71% dos setores censitários, as viagens sintéticas foram consideradas similares aos dados reais, confirmando a eficiência do método proposto. Assim, a principal lacuna desta pesquisa, é a apresentação do método sequencial, capaz de tanto minimizar problemas de aquisição de dados quanto atenuar as restrições e suposições matemáticas, inerentes aos modelos tradicionais de demanda por transportes.

Geographic scales of residential segregation in English cities

ABSTRACT The barriers to social integration posed by ethnic residential segregation are currently receiving renewed attention in Great Britain. A common characteristic of past studies of ethnic segregation in Britain is reliance upon aggregated Census data, raising potential issues of ecological fallacy. In this study, we address this challenge by using novel individual-level Consumer Register data for the UK to calculate an entropy-based spatial segregation index. We measure changes in segregation over twenty years and examine the impact of geographic scales upon observed levels of segregation in five policy relevant case study areas. Our results and findings can be used to improve the evidence base on segregation dynamics in the United Kingdom and have methodological implications for the future study of the phenomenon.

Ethnicity and neighbourhood attainment in England and Wales: A study of second generations' spatial integration

AbstractEthnic minorities' spatial concentration and their predominance in deprived areas are two well‐known patterns that characterise Britain's social landscape. However, little is known about ethnic minorities' opportunities for spatial integration, especially those of the second generations. Using a large‐scale longitudinal data set of England and Wales covering a 40‐year period (1971–2011), in combination with aggregated census data, the article examines ethnic inequalities in access to neighbourhoods with varying levels of ethnic concentration and deprivation. On equality of individual, social origin, and childhood neighbourhood characteristics, second generation ethnic minorities are less likely than White British individuals to reside in “whiter” and less deprived neighbourhoods. For most minorities, these differences reduce among those with higher education and a higher social class, in line with weak place stratification/ethnic enclave. Growing up in areas with high ethnic concentration and high deprivation has a particularly strong “retention effect” among second generation Asians. The study shows that ethnic spatial segregation is, in part, the product of time‐persisting ethnic inequalities in the access to neighbourhoods and that these inequalities are conditioned both by childhood and by adult resources.

Population Mapping with Multisensor Remote Sensing Images and Point-Of-Interest Data

Fine-resolution population distribution mapping is necessary for many purposes, which cannot be met by aggregated census data due to privacy. Many approaches utilize ancillary data that are related to population density, such as nighttime light imagery and land use, to redistribute the population from census to finer-scale units. However, most of the ancillary data used in the previous studies of population modeling are environmental data, which can only provide a limited capacity to aid population redistribution. Social sensing data with geographic information, such as point-of-interest (POI), are emerging as a new type of ancillary data for urban studies. This study, as a nascent attempt, combined POI and multisensor remote sensing data into new ancillary data to aid population redistribution from census to grid cells at a resolution of 250 m in Zhejiang, China. The accuracy of the results was assessed by comparing them with WorldPop. Results showed that our approach redistributed the population with fewer errors than WorldPop, especially at the extremes of population density. The approach developed in this study—incorporating POI with multisensor remotely sensed data in redistributing the population onto finer-scale spatial units—possessed considerable potential in the era of big data, where a substantial volume of social sensing data is increasingly being collected and becoming available.

Nuptiality in Early 20th Century Yekaterinburg: Quantitative Analysis

This article analyses one of the main characteristics of the demographic behaviour of Russian citizens, i.e. their age at first marriage and its dynamics in the early twentieth century. The authors examine the situation in Yekaterinburg, a compact but an intensively developing industrial city. Together with aggregated census data, the authors refer to microdata extracted from several city parish registers ( metricheskie knigi ), which they transcribed into the Ural Population Project database. As a result of the analysis of nominative data of parish registers, the authors establish the age of first marriages including both averages in the city as a whole and per parish which enables them to conclude about the citizens’ demographic behaviour conditioned by their ethnic or religious affiliation, social status and migration patterns, and other personal characteristics. The analysis demonstrates that Yekaterinburg seems to be closer to the “European” marriage pattern, at least in terms of mean age at first marriage in men which grew with the beginning of the war. However, according to the 1926 Census and the age of first marriage and that of never married significantly decreased as compared to the imperial period. The results of the analysis of aggregated and nominative data for Yekaterinburg enable the authors to put forward an idea that following the revolution and the establishment of a new political regime, migration from western provinces stopped while migration from rural areas increased. Rural migrants brought their own marital patterns to the city which implied mandatory marriage. Living in an increasingly stressful environment as a result of World War I, the revolution and the civil war, migrants were trying to get married earlier than on average to secure family support for themselves.

Integrating Bayesian network and generalized raking for population synthesis in Greater Jakarta

ABSTRACTConstructing agent data with detailed information on their sociodemographics is substantially important for agent-based modelling. However, to collect data about the whole population is not efficient, since it requires an expensive and time-consuming survey, especially for a large population. The paper uses a novel approach that integrates Bayesian network (BN) and generalized raking (GR) multilevel iterative proportional fitting (IPF). Furthermore, the approach is applied to construct the population for Greater Jakarta, Indonesia, which consists of 30 million inhabitants. The results show that the BN approach can produce data that represent the probability distribution of sample data and that the IPF can match it against aggregate census data.

Spatial patterns of the variability of native residentsin a transitional society: The case of the Czech Republic

Abstract Currently, the native residents of a country are an important social phenomenon. Although extensive mobility challenges the bonds between places and their inhabitants, biographies of native residents are less often based in several spatial contexts because they are born and raised in a specific place and live there for their entire lives. This absence of residential mobility has important consequences for the ways native residents relate to their ‘home places’ and how they build local attachments. Using data from the Czech Republic, the main objective of this paper is to explore and analyse recent developments in the structure of native residents. The objects of analysis are the municipalities of the Czech Republic, and aggregate census data are used for the purpose of analysis. Spatial and non-spatial approaches to the analysis showed significant changes in the structure of native residents, revealing statistically significant spatial patterns. In general, the residents of Czech municipalities demonstrate levels of co-residence or ‘mixing’ in a significant way in recent years. Thus, further research into matters such as spatial belonging, attachment and identity should also take into account the influence of mobility.

Entry and Exit of Nonprofit Organizations

AbstractThe latest census of Italian nonprofit organizations – compared with the previous one – showed a significant development of the nonprofit sector between 2001 and 2011. The number of organizations increased more than 28 % while the growth of employees (about 61 %) was even more impressive.These results notwithstanding, the mere comparison of aggregate census data does not give a true understanding of the dynamic of the sector. The entry and exit of organizations, as well as their migration between different sectors of activity, or geographical areas, can be analyzed properly only using firm-level panel data, but these data are rarely available so that only a few authors had a chance to use them. In this paper, we try to fill this gap using firm-level panel data for the first time in Italy. Our analysis tempers the optimism arising from aggregate data. We show that: a) part of the growth is determined by the emergence of already active organizations that were not detected a decade ago; b) because of low barriers, the entry of new nonprofit organizations is very relevant, but their net contribution to the growth of employment is quite small; c) opposite to what happened in other countries, the exit of nonprofit organizations is very significant, and d) organizations that were already active a decade ago gave the most important contribution to the growth of employment. We also investigate geographical trends, showing that the slower growth of the nonprofit sector in Southern Italy depends on the very high exit rate of the area, while the entry rate is more or less in line with the rest of the country.

Ethnicity and Neighborhood Attainment in England and Wales

Ethnic minorities’ spatial concentration and their predominance in deprived areas are two well-known patterns that characterize Britain’s social landscape. However, little is known about ethnic minorities’ opportunities for spatial integration, especially after individual, social origin and childhood neighborhood characteristics have been taken into consideration. Using a large-scale longitudinal dataset of England and Wales covering a forty-year period (1971-2011), in combination with aggregated Census data, the author examines ethnic inequalities in access to neighborhoods with varying levels of ethnic concentration and deprivation. The article reveals that ethnic minorities are less likely than white British individuals to reside in ‘whiter’ and less deprived neighborhoods. These effects, however, reduce, for most groups, among those with higher education and a higher social class, in line with one version of the place stratification/ethnic enclave model. Growing up in areas with high ethnic concentration and high deprivation has a particularly strong ‘retention effect’ among Asians: their probabilities of being found in ‘whiter’ and less deprived areas in adulthood are the lowest. Among Africans, growing up in a less deprived area brings no benefits for future neighborhood outcomes. Ethnic groups’ unequal access to neighborhoods suggests that group-specific preferences and constrains play a role in neighborhood attainment.

Suicide mortality and marital status for specific ages, genders, and education levels in South Korea: Using a virtually individualized dataset from national aggregate data

BackgroundPrevious studies in Eastern as well as Western countries have shown a relationship between marital status and suicide mortality. However, to date, no Korean study has calculated national suicide rates by marital status for specific genders, ages, and education levels. This study investigated whether the relationship between marital status and suicide differs by age, gender, and educational attainment, and analyzed the effect of marital status on suicide risk after controlling for these socio-demographic variables. MethodsUsing national mortality data from 2015, and aggregated census data from 2010 in South Korea, we created a virtually individualized dataset with multiple weighting algorithms, including individual socio-demographic characteristics and suicide rates across the entire population. ResultsThe findings show that the following groups faced the highest relative suicide risks: 1) divorced men of all ages and men aged more than 75 years, particularly divorced men aged more than 75; and 2) never-married men aged 55–64 years, and never-married women of lower education status. LimitationsWe did not account for important variables such as mental health, substance abuse, employment insecurity, social integration, perceived loneness, and family income which we were unable to access. ConclusionsThis current research extends prior theoretical and methodological work on suicide, aiding efforts to reduce suicide mortality in South Korea.

Does Ethnic Concentration Influence Gender Role Views? A Study Across Ethnic Groups in England and Wales

Gender role views have long been a matter of great interest to researchers. In part, this is connected to the negative part that traditional gender role views can play in the social and economic integration of women. In Western Europe, this topic has gained additional attention with the arrival of migrants from countries where gender inequality is greater and where individuals hold more traditional views on the social roles of men and women. Research shows that, though gender role views become less traditional over time and through the generations, differences with respect to the majoritarian white population remain. This study explores one of the possible mechanisms behind the persistence of traditional gender role views among migrants and their children in the UK (i.e. ethnic minority groups): neighbourhood ethnic concentration. Neighbourhoods are spaces of interaction, as well as of transmission of beliefs and ways of doing, and this can affect individuals more or less coercively. This study employs data from Wave 2 of Understanding Society, in combination with aggregated Census data. Using this data I explore the extent to which ethnic minority groups residing in areas with a higher concentration of members of the same group have a higher probability of holding more traditional gender role views. The article finds some evidence of this for Indians and Bangladeshis, but not for Pakistanis. Problems of self-selection and endogeneity are discussed.

Minorities and Diversity in Scotland: Evidence from the 2011 Census

The relatively low proportion of people in ethnic and national minority groups in Scotland has been an obstacle for social research concerning these minorities, especially in characterising and comparing these populations using large scale data. The 2011 census offers an invaluable resource in this regard, especially at a time when minorities are growing to represent a more prominent and significant element in Scotland's population. This paper uses standard aggregate census data and data derived from a 5% sample of census returns to provide an overview and comparison of the six largest minority groups in Scotland, focusing on the origins, identities and socio-economic status of people within these groups. It not only highlights how different minorities contrast with each other and the majority population, but also illuminates the diversity that exists within these groups.

Urban Growth Dynamics in Perth, Western Australia: Using Applied Remote Sensing for Sustainable Future Planning

Earth observation data can provide valuable assessments for monitoring the spatial extent of (un)sustainable urban growth of the world’s cities to better inform planning policy in reducing associated economic, social and environmental costs. Western Australia has witnessed rapid economic expansion since the turn of the century founded upon extensive natural resource extraction. Thus, Perth, the state capital of Western Australia, has encountered significant population and urban growth in response to the booming state economy. However, the recent economic slowdown resulted in the largest decrease in natural resource values that Western Australia has ever experienced. Here, we present multi-temporal urban expansion statistics from 1990 to 2015 for Perth, derived from Landsat imagery. Current urban estimates used for future development plans and progress monitoring of infill and density targets are based upon aggregated census data and metrics unrepresentative of actual land cover change, underestimating overall urban area. Earth observation provides a temporally consistent methodology, identifying areal urban area at higher spatial and temporal resolution than current estimates. Our results indicate that the spatial extent of the Perth Metropolitan Region has increased 45% between 1990 and 2015, over 320 km2. We highlight the applicability of earth observation data in accurately quantifying urban area for sustainable targeted planning practices.

O estymacji preferencji w sztucznych sieciach społecznych

The paper considers a scenario in which public administration (PA) uses an online social platform to collect information on citizens' preferences. However, the opinions of the sub-population that uses the online platform might be not representative. The author develops a method for generalization of the dynamics of the preferences observed on the social platform onto the entire population. The available data include information collected by the PA from the online platform (assuming that it is run and administered by the PA) and census data regarding the population. Hence, the PA has access to basic personal data of platform users (e.g. gender and age), position in the online social network, and opinions revealed on the platform. The online users' data can be analyzed along with the aggregated census data on the entire population. The author has implemented a multi-agent simulation model that takes into account the distribution of personal attributes, social network data, and opinion diffusion dynamics. The analysis involves showing how different algorithms enable generalization of preferences collected by the online platform to the entire population. The results of the analysis prove that the proposed method is efficient in the preference elicitation process – with each simulation step, the preference congruence level between real and synthetic populations increases. The main determinants of preference elicitation errors include the preference diffusion model and the weight of the agents’ own opinions.