Percentage Of Urban Population Research Articles

Examining 35 years of individualism-collectivism research in Asia: A meta-analysis

Traditionally, research in communication and culture (e.g., “cross-cultural communication,” “intercultural communication,” “international communication”) has examined the notions of individualism (IND) and collectivism (COL) extensively. However, the results of these studies are sometimes inconsistent, as documented in previous meta-analyses. This study posits that the theory-data inconsistency can be attributed to accelerated globalization, particularly, improved economic and political situations within traditionally under-developed or developing Asian nations. To examine this prediction, 99 IND-COL studies published between 1988 and 2023 were compiled that compared the U.S. to Asian countries (N = 87,735, kIND = 131, kCOL = 156), and augmented with national-level socio-political indices (i.e., percent of urban population, gross domestic product, democracy) as predictors of the IND-COL effects. Partially consistent with this study’s prediction, Asian nations with improved socio-political conditions manifested a decline in collectivism. However, these improvements with time did not predict an increase in individualism. The results are discussed in relation to the theoretical definitions of IND and COL, and the limitations of the traditional approach to understanding cross-cultural differences.

Suicide and its risk factors - An ecological study.

There is tremendous variation in both the prevalence of suicide and the factors that contribute to its occurrence across geographic locations, cultures, and time. Therefore, the present study aims to identify the various socio-demographic risk factors and psychosocial stressors using population data. The countries that were included in the study were based on data from the World Health Organization. We considered the top ten suicide countries and the ten lowest suicide nations. We searched five global databases for the most recent socio-demographic data and data on psychosocial stressors during the period of August and September 2022. We analyzed the correlation between suicide rates and various factors, and we considered a P value of less than 0.05 to be statistically significant. The correlation of suicide with sociodemographic factors like age (P 0.246), gender (male, P 0.357, and female, P 0.357), net enrolment rate (P 0.725), gender parity index (P 0.929), urban population percentage (P 0.571), marital status (male, P 0.345, and female, P 0.752), and literacy rate percentage (P 0.199) was not significant. The correlation of suicide with psychosocial stressors like unemployment percentage (P 0.552), alcoholism percentage (P 0.271), the prevalence of depression (P 0.523), the number of psychiatrists (P 0.605), the number of mental hospitals (r = -0.090, P 0.713), and the poverty rate percentage (P 0.538) were also not significant. Suicide is a major public health issue, yet global suicide data is scarce. Sociodemographic factors like age, urbanization, and literacy rate were negatively correlated, whereas psychosocial stressors like unemployment, alcohol misuse, and poverty were positively correlated, but none were significantly associated.

Health economic analysis and medical cost analysis of children with severe hepatitis B in China: A retrospective study from 2016 to 2022.

Hepatitis B poses a heavy burden for children in China, however, the national studies on the distributional characteristics and health care costs of children with severe hepatitis B is still lacking. This study aimed to analyze the disease characteristics, health economic effects, and medical cost for children with severe hepatitis B in China. Based on patient information in the Hospital Quality Monitoring System, cases with severe hepatitis B were divided into four groups according to age, and the etiology and symptoms of each group were quantified. The cost of hospitalization was calculated for cases with different disease processes, and severity of disease. The spatial aggregation of cases and the relationship with health economic factors were analyzed by Moran's Ianalysis. The total number of children discharged with hepatitis B from January 2016 to April 2022 was 1603, with an average age of 10.5 years. Liver failure cases accounted for 43.48% (697/1603,) of total cases and cirrhosis cases accounted for 11.23% (180/1603,). According to the grouping of disease progression, there were 1292 cases without associated complications, and the median hospitalization cost was $818.12. According to the spatial analysis, the aggregation of cases was statistically significant at the prefectural and provincial levels in 2019, 2020, and 2021 (all P <0.05). The number of severe cases was negatively correlated with gross domestic product (GDP, Moran's I <0) and percentage of urban population (Moran's I <0), and positively correlated with the number of pediatric beds per million population (Moran's I >0). The number of severe hepatitis B cases is low in areas with high GDP levels and high urban population ratios, and health care costs have been declining over the years.

Cluster Analysis of Factors Associated with Leishmaniasis in Peru.

To analyze the factors associated with leishmaniasis in Peru, according to the cluster classification in the period 2017-2021. Quantitative approach, with an ecological, descriptive correlational, and cross-sectional design. The population was from the geographical region of Peru, where a total of 26,956 cases of leishmaniasis were registered by the Peruvian Ministry of Health from 2017 to 2021. Spearman's Rho statistic was used to analyze the variables that are most associated with the cases of leishmaniasis reported per year, and, in addition, the multivariate technique of cluster analysis was applied. Annual rainfall and areas with humid forest (climatic factors) and mortality from transmissible diseases (health factor) are directly associated with reported cases of leishmaniasis. Households with basic access to infrastructure, drinking water, drainage, and electric lighting; illiteracy, regional social progress, and unsatisfied basic needs (social factors); and percentage of urban population (demographic factor) are inversely and significantly associated with cases of leishmaniasis. Climatic and environmental factors contribute to the multiplication of the leishmaniasis disease vector. The incidence of leishmaniasis adds up to the mortality rates for transmissible diseases in Peru. As living conditions improve, the incidence of this pathology decreases.

The searchscape of fear: A global analysis of internet search trends for biophobias

Abstract Human relationships with nature may sometimes manifest through fear, disgust and other disease‐avoidance mechanisms. While there is an evolutionary utility to these so‐called ‘biophobias’, many people exhibit phobic responses towards organisms that pose no tangible threats, potentially leading to excessive anxiety and avoidance of interactions with nature. Understanding the drivers of the prevalence and spread of biophobias in modern societies is, therefore, a growing concern. Here, we posit that online information‐seeking patterns may reveal general insights into biophobias. Using a culturomics approach, we gathered temporal (2004–2022) and country‐level data on the volume of internet searches for 25 biophobias, as well as 25 general phobias acting as a benchmark group. We explored temporal trends in the volume of search for each biophobias and modelled relationships between search volume for biophobias and five country‐level variables. We observed a steady increase in online search volume for biophobias between 2004 and 2022. Yet, there were marked differences in individual trends, with 17 biophobias showing positive, three negative and five stationary temporal trends. Arachnophobia (fear of spiders) attracted the most interest, followed by mysophobia (fear of microbes) and parasitophobia (fear of parasites). The United States, the United Kingdom, Australia, Canada, Mexico and India recorded wide interest in most biophobias, whereas 49% of countries showed no search volume for any biophobia. Search patterns for biophobias were strongly associated with the percentage of urban population, urban population growth and the number of extant venomous species in a given country. Conversely, search patterns for biophobias were weakly correlated with the incidence of anxiety disorders in a country's population and the likelihood of encounters with venomous animals. Our results provide quantitative support to the hypothesis that biophobias are broadly prevalent and possibly increasing as a result of widespread urbanisation and loss of experiences with nature. We suggest that people affected by biophobic disorders may be using the Internet as a key venue to seek relevant information to appraise their condition and identify coping mechanisms. These findings have broad ramifications for understanding and mitigating human–wildlife conflicts and the prevalence of widespread biophobic sentiments in modern societies.

County characteristics associated with refusing breast cancer surgery: Evidence from the Surveillance, Epidemiology, and End Results program

BackgroundIndividuals’ communities impact cancer disparities and are intimately related to social determinants of health. Studies show that personal factors affect treatment refusals for a potentially curable cancer, but few studies have investigated whether community-based characteristics affect the receipt of surgery. MethodsWe used Surveillance Epidemiology and End Results Program registries from 2010 to 2015 to examine differences in rates of surgery refusal among non-Hispanic White, non-Hispanic Black, and Hispanic women diagnosed with nonmetastatic breast cancer. The community factor measures were based on county-level factors. Sociodemographic and community differences were analyzed using Pearson’s χ2 tests and analysis of variance. Multivariate logistic regression of predictors of surgery refusal and the Cox proportional hazard model of disease-specific mortality were performed. ResultsSurgery refusers among non-Hispanic Black and Hispanic all races lived in counties with lower rates of educational attainment, median family and household income, and higher rates of poverty, unemployment, foreign-born, language isolation, urban population, and women more than 40 years old having mammography in last 2 years. Multivariate analysis shows surgery refusal rates increased in counties having a high percentage of urban population and declined in counties with an increased percentage of less than high school level education, unemployment, and median household income. Breast cancer-specific mortality increased significantly with surgery refusal. ConclusionResidence in counties with the lowest socioeconomic status and disproportionately populated by racial and ethnic minorities is associated with surgery refusal. Given the high mortality associated with refusing surgery, culturally sensitive education on the benefits of care may be appropriate.

Environmental correlates of adolescent active travel to school in Asia: An ecological study.

This study aimed to examine the association between country-level environmental correlates and the prevalence of active school travel (AST) in Asia and country-level differences in AST by age and sex. This ecological study involved 31 Asian countries. Dependent variables were AST prevalence, AST prevalence difference by age, and by sex. Independent variables were country-level environmental correlates extracted using publicly available datasets, classified into physical and social environments. Association estimates of each dependent variable and each of the independent variables were calculated using univariate linear regression. All variables were standardized to have a mean of 0 and a standard deviation of 1. Results showed that 1 standard deviation (SD) difference in urban population percentage, night-time light, secondary-school enrolment, and prevalence of adult insufficient physical activity were negatively associated with AST prevalence (SD difference: -0.44 (-0.78 to -0.09), -0.40 (-0.76 to -0.04), -0.39 (-0.74 to -0.04), and -0.40 (-0.76 to -0.03), respectively). A 1 SD difference in car per people was associated with a -0.46 (-0.84 to -0.09) difference of AST prevalence by age. A 1 SD difference in PM2.5 concentration and of prevalence of adult insufficient physical activity were associated with a difference of 0.38 (0.01-0.74) and 0.42 (0.03-0.80) difference of AST prevalence by sex. This study shows that Asian countries with a greater number of people living in urban areas, lower levels of overall adult physical activity and higher levels of night-time light have a lower prevalence of adolescent AST. Country-level physical and social environmental correlates explained some of the regional variance in AST. Future policy actions and interventions for the region need to be contextually sensitive to the environmental correlates that vary between countries.

Gender differences in premature mortality for cardiovascular disease in India, 2017–18

BackgroundThe present study tries to provide a comprehensive estimate of gender differences in the years of life lost due to CVD across the major states of India during 2017–18.MethodsThe information on the CVD related data were collected from medical certification of causes of death (MCCD reports, 2018). Apart from this, information from census of India (2001, 2011), SRS (2018) were also used to estimate YLL. To understand the variation in YLL due to CVD at the state level, nine sets of covariates were chosen: share of elderly population, percentage of urban population, literacy rate, health expenditure, social sector expenditure, labour force participation, HDI Score and co-existence of other NCDs such as diabetes, & obesity. The absolute number of YLL and YLL rates were calculated. Further, Pearson’s correlation had been calculated and to understand the effect of explanatory variables on YLL due to CVD, multiple linear regression analysis had been applied.ResultsMen have a higher burden of premature mortality in terms of Years of life lost (YLL) due to CVD than women in India, with pronounced differences at adult ages of 50–54 years and over. The age pattern of YLL rate suggests that the age group 85 + makes the highest contribution to the overall YLL rate due to CVD. YLL rate showed a J-shaped relationship with age, starting high at ages below 1 years, dropping to their lowest among children aged 1–4 years, and rising again to highest levels at 85 + years among both men and women. In all the states except Bihar men had higher estimated YLL due to CVD for all ages than women. Among men the YLL due to CVD was higher in Tamil Nadu followed by Madhya Pradesh and Chhattisgarh. On the other hand, the YLL due to CVD among men was lowest in Jharkhand followed by Assam. Similarly, among women the YLL due to CVD was highest in Tamil Nadu followed by Madhya Pradesh and Chhattisgarh. While, the YLL due to CVD among women was lowest in Jharkhand. Irrespective of gender, all factors except state health expenditure were positively linked with YLL due to CVD, i.e., as state health expenditure increases, the years of life lost (YLL) due to CVDs falls. Among all the covariates, the proportion of a state's elderly population emerges as the most significant predictor variable for YLL for CVDs (r = 0.42 for men and r = 0.50 for women).ConclusionYLL due to cardiovascular disease varies among men and women across the states of India. The state-specific findings of gender differences in years of life lost due to CVD may be used to improve policies and programmes in India.

One stream, two channels? A parallel-process latent class growth model of homicide rates and suicide rates in 183 countries, between 2000 and 2019

BackgroundSuicide and homicide have long been viewed in Western culture as moral, ethical and legal equivalents. This view has underpinned many theoretical and empirical explorations into their relationship over the centuries. However, there has been little evaluation of longitudinal heterogeneity. MethodsSuicide and homicide rates in 183 countries between 2000 and 2019 were collected from the World Health Organization Global Health Observatory Repository. Corresponding structural variables (i.e., GDP per capita, unemployment rate, percentage of urban population, percentage of elderly population, and Gini index) were acquired from The World Bank and Standardized World Income Inequality Database. Parallel-process latent class growth modelling was applied to identify different classes within the joint suicide and homicide rate trajectories. Multinomial logistic regression examined relationships between the structural covariates and trajectory classes. ResultsFour trajectory classes were identified, two with inverse relationships between suicide and homicide, and two with parallel relationships: 1) countries with increasing suicide rates and decreasing homicide rates (“suicide up, homicide down”: UD, n = 41) or 2) countries with decreasing suicide rates and increasing homicide rates (“suicide down, homicide up”: DU, n = 17); and 3) countries where suicide and homicide rates both trended up (UU, n = 19), or 4) both trended down (DD, n = 106). A higher average annual growth rate (AAGR) of GDP per capita was related to an increased possibility of being in DD than in DU. Countries with higher AAGR in unemployment rates were more likely to be in UD and UU than in DD, while those with higher AAGR in urbanization were less likely to be in UD than in DD. ConclusionThe over-time relationship between suicide and homicide is heterogenous and complex. It is influenced differently by GDP per capita, urbanization and unemployment in different countries, and it is not well described by a single theory.

Analysis Of The Urbanisation Pattern In Haryana In 2011

The urban population of Haryana was 88.2 lakh in 2011. Haryana experienced a significant increase in urbanisation level from 28.92 percent in 2001 to 34.88 percent in the next census enumeration in 2011, resulting in a decadal change of 5.95 percent. Faridabad district has the highest urban population as a percentage of the total population, with 79.51 percent. Additionally, it accounts for 16.27 percent of the state's total urban population. The region of Mewat has the lowest urban population percentage due to the dominance of social traditionalists among the Muslim community in this area. Panipat district has the highest urban density, with 6995.40 persons per sq. km. Among the 21 districts, it is worth noting that 3 districts in Haryana exhibit a relatively lower level of urban density. These districts primarily revolve around agricultural activity. Mewat has the lowest urban density in the state, historically it is a backward and underdeveloped area. The present study aims to describe the spatial pattern of urbanisation in Haryana. The data is derived from the census conducted in 2011.

Gender gap in life expectancy at birth and the role of socioeconomic indicators in South and East Europe, 1991 – 2020: Evidence from a dynamic panel model

The purpose of this paper is to explain the role of socioeconomic development, economic, employment, and demographic factors on gender gap in life expectancy at birth (LEAB) in 24 South and East European countries. Aggregated yearly time series mainly from the UN and World Bank database for the period 1991 – 2020 were used. The generalized method of moments/dynamic panel data (GMM/DPD) model, a dynamic panel model, was used to explore the role of socioeconomic development, economic, employment, and demographic factors on sex differences in LEAB. The study shows that in these countries, a narrowed gender gap in LEAB is associated with a higher percentage of urban population in total population. There was found a significant impact of GDP per capita with a 2-year lag and Gini index with a 2-year lag as well as to LEAB on the gender gap in LEAB. There was not found a significant relationship between employment and education variables on gender gap in LEAB. However, the findings are important for policy discussions in terms of population health, labor policy, etc. The results are supported by the number of studies which show the relationship between socioeconomic development, economic, and demographic indicators and employment issues with gender gap in LEAB.

Neuroticism, urbanization, and the state prevalence of Parkinson’s disease in the USA

This study was conducted primarily to determine whether state prevalence rates of Parkinson’s disease (PD) among Medicare beneficiaries 65 and over are associated with U.S. state resident standing on the Big Five personality dimensions. Key variables for the 50 states were PD prevalence rates in 2014, Big Five scores based on 619,397 survey respondents, socioeconomic status (SES), White population percent, urban population percent, health environment, and overall health outcomes. A sequential multiple regression equation with the SES, White, and urbanization variables selected stepwise and followed by the Big Five selected stepwise showed state PD prevalence rate variance was significantly accounted for by urbanization (16.9 %, β = 0.53) and neuroticism (32.8 %, β = 0.59). This prediction pattern persisted in another equation when state health environment and health outcomes served as additional controls, with neuroticism accounting for an additional 17.4 % of the variance. The only independent predictors in that equation also were urbanization (β = 0.57) and neuroticism (β = 0.48). Essentially similar results were found using simultaneous entry equations. Spatial analysis using Moran’s I test for residual spatial autocorrelation also showed that spatial autocorrelation was not an issue. The present results based on the geographical psychology perspective underline the importance of corroborating correlative patterns found in personality studies with individuals as the analytic units with research using aggregates of individuals as the units of analysis. It also is speculated that health policy and promotion managers eventually might profit from tailoring PD initiatives according to resident neuroticism levels and degree of urbanization.

The daily mobility of older adults: Urban/rural differences in ten developed countries

AbstractThis paper explores the mobility patterns of older adults in ten countries, with a focus on the differences produced by urban environments in their non-work trips. Using detailed time use diaries from the Multinational Time Use Study for the last two decades, we analyze the trips associated with leisure and housework of non-working older adults. The results show that older adults in urban areas spend more time in leisure trips than similar individuals in rural areas. On the other hand, male older adults in urban areas spend less time in housework trips than do their counterparts in rural areas. However, such correlations are found to differ by country, gender, type of trip, and mode of transport, revealing complex correlations between urban forms and older adults’ daily mobility. Furthermore, factors such as the number of railway kilometers, gross domestic product growth rates, and the percentage of urban population in the country seem to be associated with differences in the behavior of older adults in their non-work daily trips.

Global-scale modeling of early factors and country-specific trajectories of COVID-19 incidence: a cross-sectional study of the first 6 months of the pandemic

BackgroundStudies examining factors responsible for COVID-19 incidence have been mostly focused at the national or sub-national level. A global-level characterization of contributing factors and temporal trajectories of disease incidence is currently lacking. Here we conducted a global-scale analysis of COVID-19 infections to identify key factors associated with early disease incidence. Additionally, we compared longitudinal trends of COVID-19 incidence at a per-country level, and classified countries based on COVID-19 incidence trajectories and effects of lockdown responses.MethodsThis is an observational cross-sectional study covering COVID-19 incidence over the first 6 months of the pandemic (Jan 1, 2020 to June 30, 2020). A retrospective analysis was performed using publicly available data for total confirmed COVID-19 cases by country, and using recent data on demographic, meteorological, economic and health-related indicators per country. Data was analyzed in a regression modeling framework. Longitudinal trends were assessed via linear and non-linear model fitting. Competing models of disease trajectories were ranked by the Akaike’s Information Criterion (AIC). A novel approach involving hierarchical clustering was developed to classify countries based on the effects of lockdown measures on new COVID-19 caseloads surrounding the lockdown period.ResultsUnivariate analysis identified 11 variables (employments in the agriculture, service and industrial sectors, percent population residing in urban areas, population age, number of visitors, and temperatures in the months of Jan-Apr) as independently associated with COVID-19 infections at a global level (variable p < 1E-05). Multivariable analysis identified a 5-variable model (percent urban population, percent employed in agriculture, population density, percent population aged 15–64 years, and temperature in March) as optimal for explaining global variations in COVID-19 (model adjusted R-squared = 0.68, model p < 2.20E-16). COVID-19 case trajectories for most countries were best captured by a log-logistic model, as determined by AIC estimates. Six predominant country clusters were identified when characterizing the effects of lockdown intervals on variations in COVID-19 new cases per country.ConclusionsGlobally, economic and meteorological factors are important determinants of early COVID-19 incidence. Analysis of longitudinal trends and lockdown effects on COVID-19 highlights important nuances in country-specific responses to infections. These results provide valuable insights into disease incidence at a per-country level, possibly allowing for more informed decision making by individual governments in future disease outbreaks.

Do Cities Improve Our Health Status? A State-Level Analysis in India

While several cross-country level studies suggest urbanization increases health outcomes; national-level studies are missing. On the other hand, India is experiencing a very low level of urbanization due to policy failures. In this context, this study assesses the impact of urbanization on health outcomes in Indian states from the period of 1991 to 2011. Urbanization is measured by the total urban population and percentage of urban population as different states are having a different level of urbanization. Health outcomes are measured by total fertility rate, infant mortality rate, and life expectancy at birth. The static panel data models such as fixed-effect and random-effect panel data models suggest that the total urban population and the percentage of the urban population have a positive effect on life expectancy at birth and have a negative effect on the infant mortality rate and total fertility rate. Among the control variables, the percentage of urban households having access to electricity, urban monthly per capita consumption expenditure, and per capita net state domestic product has also had a similar effect on the health outcomes. Other important variables such as rural to urban migration, literacy rate, poverty rate, access to safe drinking water, labor force participation rate, and the extent of inequality also play an important role in increasing health outcomes. We also checked the robustness of our results by using the instrumental variable generalized method of moments. Our results support the Theory of Demographic Transition and suggest that Indian policymakers must support increasing the urbanization rate for achieving higher health outcomes. However, proper management of urbanization by providing basic services to urban dwellers is also very important in this regard.

Exploring the socioeconomic determinants of water security in developing regions

AbstractThe objectives of this study are two fold: first, to develop a composite water security metric to assess water security at a national scale, and second, to explore the determinants of water security at the same scale in three developing regions – Africa, Asia-Pacific and Latin America and the Caribbean (LAC). The water security index (WSI) was developed using three biophysical (water availability, climate risk and ecosystem vitality) and two socioeconomic (water accessibility and integrated water resources management) variables. Five independent variables (governance, gross domestic product (GDP) per capita, percentage of urban population, official development assistance for water and sanitation services (ODA-WSS) and female primary school completion rate) were used to explore the determinants of water security. Results show that &amp;gt;90% of countries in Africa and the Asia-Pacific regions are water-insecure, whereas most countries in LAC are water-secure except Haiti, Guatemala and Nicaragua. Statistical analyses show that GDP per capita, female primary school completion rate and governance are the key determinants of water security. This study provides empirical evidence on the link between female primary school completion rate and water security. Results further show a strong correlation between water security and ODA-WSS in the region with a higher ODA-WSS per capita than in regions with a low ODA-WSS per capita. This suggests that increasing ODA-WSS per capita may enhance water security in developing regions.

Abstract P5-14-05: Are neighborhood and community factors associated with refusing breast cancer surgery?

Abstract Background: The importance of an individual’s community impacts cancer disparities and is intimately related to social determinants of health. Surgery refusal is associated with a high disease-specific mortality. Studies of factors associated with refusal of treatment for potentially curable breast cancer show personal factors including age, marital status, and insurance are at play. However, few studies have investigated whether community or area-based characteristics may affect receipt of surgery. Methods: We selected all women diagnosed with non-metastatic (Stage I-III) breast cancer in the Surveillance, Epidemiology, and End Results (SEER) database. We focused on those who refused surgery comparing racial and ethnic differences between Non-Hispanic White (NHW), Non-Hispanic Black (NHB), and Hispanic all races. Yost index calculated as neighborhood socio-economic status (nSES- divided into tertiles) and RUCA code-derived rural-urban status were based on an NCI census tract-level index, a composite score that includes income, education, housing, and employment; the remaining community factor measures were based on county-level index. Sociodemographic and community differences were analyzed using Pearson’s Chi-Square tests and analysis of variance. Multivariate logistic regression of predictors of refusal of surgery and Cox-proportional hazard model of disease-specific mortality were performed. A p-value of 0.05 was considered statistically significant. Results: 2,155 (0.7%) of 322,538 people refused surgery (NHW: 1,435 (66.6%), NHB: 353(16.3%), Hispanic all races: 166(7.7%)). Surgery refusers were more likely to live in areas with high poverty (&amp;lt;200% level), lower education attainment, lower unemployment, higher percentage urban population, higher percentage foreign-born, higher rates of language isolation, and lower rates of women over 40 having undergone mammography in the previous two years. Multivariate analysis shows surgery refusal is associated with high percentage of having a bachelor’s degree or higher (OR: 1.29, 95% CI:1.05-1.60, p-value &amp;lt;0.05), high percentage of poverty (&amp;lt;200% of poverty) (OR: 1.50, 95% CI:1.04-2.16, p-value &amp;lt;0.05), and high percentage of urban population (OR: 1.26, 95% CI:1.06-1.49, p-value &amp;lt;0.01). Surgery refusal rates declined with increasing nSES. Breast cancer-specific mortality increased significantly for those who refused surgery (HR:3.92, 95% CI: 3.41-4.51, p-value &amp;lt;0.01). Conclusion: Risk of refusing surgery for an otherwise curable breast cancer is associated with residence in communities with the lowest nSES. These are communities disproportionately populated by racial and ethnic minorities. Given the high mortality associated with refusing surgery, further investigation into the reasons why women decline treatment is necessary. For women living in impoverished communities, culturally sensitive education on benefits of care may be appropriate, while women of means may face different challenges such as utilization of alternative medicine. Citation Format: Theresa Relation, Oindrila Bhattacharyya, Jay Fisher, Yaming Li, Allan Tsung, Ahmad Hamad, Amara Ndumele, Bridget Oppong. Are neighborhood and community factors associated with refusing breast cancer surgery? [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-14-05.

Reidentificación de lo rural/urbano: un estudio de caso de Pakistán

The historical census of Pakistan has always categorized the urban and rural areas with criteria lacking a clear discernibility. In this research study I chose 2 criteria i.e., density and urban core proximity to differentiate areas into either rural, urban and urbanizing area. The urbanizing area was added in the methodology to identify the places which neither fit in the of rural and urban category. The 2017 population census was taken for analysis. The analysis shows that the provinces of Punjab and Khyber Pakhtunkhwa have higher percentage of urban population by 27% and 3% than the official census, respectively. While province of Sindh shows a contradicting scenario showing a decrease by 18% of urban area than official census while in the province of Balochistan the urban area doesn’t exist, while the remaining areas was occupied by urbanizing area. The findings shows that urban areas far exceed the Government statistics.

Selective migration in American interstate residential flow: Similarity of Big Five personality factors among origin and destination state residents

Two studies using the 48 contiguous American states tested the general hypothesis that the percent of the total number of movers leaving an origin state that migrates to a particular destination state is related to the degree of similarity in Big Five personality between the residents of the origin state and the destination state. Datasets for 2005–2006 and 2016–2017 were analyzed. The hypothesis was tested using Pearson correlation and multiple regression strategies without and with consideration of the following state-level statistical controls: socioeconomic status based on two economic and two educational variables, unemployment rate, White population percent, urban population percent, conservatism, and road distance between state capitals for the 48 states. A consistent pattern of support for the hypothesis was found for each of the Big Five personality dimensions—openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism—for both datasets without and with statistical controls. Results without statistical controls demonstrated that movers from states with residents higher on a Big Five personality dimension indeed are more likely to migrate to states with residents higher on that personality dimension, and that movers from states with residents lower on a personality dimension are more likely to migrate to states with residents lower on that personality dimension. Similar results were obtained with statistical controls but the relations for conscientiousness were in the supportive direction but not statistically significant. It is speculated that these state-level relations are grounded in parallel individual-level relations suggested by the theories of selective migration, homophily, similarity-attraction, and person-environment fit.

Forecasting analysis of selected health- and economy-related indicators in South Eastern European and Balkan countries

Background/Aim. Health indicators provide comparable in-formation relevant to defining health goals. The aim of this study was to perform a forecasting analysis of the selected indicators, which could help anticipate the future necessities in the health economy and prevent the problems that would predictively grow in the future. Methods. Health indicators are collected from publicly available databases of the World Health Organization and Eurostat. We used the quantitative forecasting technique, commonly used for historical data, to predict several years in the future concerning selected health- and economy-related indicators. Results. Total health expenditures as a percentage of gross domestic product (GDP) by 2025 will increase in most of the 17 surveyed countries. The percentage of direct household budget payments (out-of-pocket) for health services will decrease in half of the countries, while values of GDP expressed in US$ will increase significantly com-pared to the last surveyed year (2017), except in Greece. The infant mortality indicator shows that the numbers will decrease in each surveyed country, while the urban population percent-age will rise almost in each country except Estonia. Life expectancy will increase in each surveyed country. Conclusion. Health- and economy-related indicators must be monitored over time, as they provide significant information concerning the relevant issues in the health care system. Moreover, they may indicate changes that should be made in order to accomplish progress in each individual country.