scholarly journals Regional patterns of belonging among young Latvian returnees

2018 ◽  
Author(s):  
Elina Apsite–Berina ◽  
◽  
Zaiga Krisjane ◽  
Guido Sechi ◽  
Maris Berzins
Keyword(s):  
Regional Patterns

A Note On Consumption Patterns in the Rural Areas of East Pakistan

1963 ◽  
Vol 3 (3) ◽  
pp. 399-413
Author(s):  
Mohammad Irshad Khan
Keyword(s):  
Rural Areas ◽  
The United States ◽  
Development Planning ◽  
Consumption Patterns ◽  
Regional Patterns ◽  
Effective Utilization ◽  
Income Elasticities ◽  
On Demand ◽  
Limited Applicability ◽  
Made In

The main purpose of this paper is to present estimates of income elasticities for various commodity groups in East Pakistan. To date no such studies have been conducted in that province; and estimates made in other areas of the subcontinent have only limited applicability. Analysis of consumption patterns is essential for development planning because priorities and investment targets have to be based on demand forecasts for different commodities. Forecasting demand requires, among other variables, reliable estimates of income elasticities. In addition, knowledge about elasticities can be useful in deciding taxation policies and other controls over consumption. Further, in countries like Pakistan where large quantities of surplus foods are imported under the United States PL 480 programme, knowledge of income elasticities and regional patterns of consumption is important to permit effective utilization of these imports for economic development.

scholarly journals Social Vulnerability across the Great Lakes Basin: A County-Level Comparative and Spatial Analysis

2021 ◽  
Vol 13 (13) ◽  
pp. 7274
Author(s):  
Joshua T. Fergen ◽  
Ryan D. Bergstrom
Keyword(s):  
Great Lakes ◽  
Spatial Patterns ◽  
Social Vulnerability ◽  
Vulnerability Index ◽  
Social Vulnerability Index ◽  
Great Lakes Basin ◽  
Empirical Examination ◽  
Regional Patterns ◽  
Urban Rural ◽  
Social Vulnerabilities

Social vulnerability refers to how social positions affect the ability to access resources during a disaster or disturbance, but there is limited empirical examination of its spatial patterns in the Great Lakes Basin (GLB) region of North America. In this study, we map four themes of social vulnerability for the GLB by using the Center for Disease Control’s Social Vulnerability Index (CDC SVI) for every county in the basin and compare mean scores for each sub-basin to assess inter-basin differences. Additionally, we map LISA results to identify clusters of high and low social vulnerability along with the outliers across the region. Results show the spatial patterns depend on the social vulnerability theme selected, with some overlapping clusters of high vulnerability existing in Northern and Central Michigan, and clusters of low vulnerability in Eastern Wisconsin along with outliers across the basins. Differences in these patterns also indicate the existence of an urban–rural dimension to the variance in social vulnerabilities measured in this study. Understanding regional patterns of social vulnerability help identify the most vulnerable people, and this paper presents a framework for policymakers and researchers to address the unique social vulnerabilities across heterogeneous regions.

scholarly journals COVID-19-related state-wise racial and ethnic disparities across the USA: an observational study based on publicly available data from The COVID Tracking Project

BMJ Open ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. e048006
Author(s):  
Zhaoying Xian ◽  
Anshul Saxena ◽  
Zulqarnain Javed ◽  
John E Jordan ◽  
Safa Alkarawi ◽  
...  
Keyword(s):  
Asian American ◽  
Alaska Native ◽  
Ethnic Disparities ◽  
Relative Difference ◽  
Ethnic Composition ◽  
Regional Patterns ◽  
Population Proportion ◽  
Asian Populations ◽  
The Usa ◽  
Racial Ethnic

ObjectiveTo evaluate COVID-19 infection and mortality disparities in ethnic and racial subgroups in a state-wise manner across the USA.MethodsPublicly available data from The COVID Tracking Project at The Atlantic were accessed between 9 September 2020 and 14 September 2020. For each state and the District of Columbia, % infection, % death, and % population proportion for subgroups of race (African American/black (AA/black), Asian, American Indian or Alaska Native (AI/AN), and white) and ethnicity (Hispanic/Latino, non-Hispanic) were recorded. Crude and normalised disparity estimates were generated for COVID-19 infection (CDI and NDI) and mortality (CDM and NDM), computed as absolute and relative difference between % infection or % mortality and % population proportion per state. Choropleth map display was created as thematic representation proportionate to CDI, NDI, CDM and NDM.ResultsThe Hispanic population had a median of 158% higher COVID-19 infection relative to their % population proportion (median 158%, IQR 100%–200%). This was followed by AA, with 50% higher COVID-19 infection relative to their % population proportion (median 50%, IQR 25%–100%). The AA population had the most disproportionate mortality, with a median of 46% higher mortality than the % population proportion (median 46%, IQR 18%–66%). Disproportionate impact of COVID-19 was also seen in AI/AN and Asian populations, with 100% excess infections than the % population proportion seen in nine states for AI/AN and seven states for Asian populations. There was no disproportionate impact in the white population in any state.ConclusionsThere are racial/ethnic disparities in COVID-19 infection/mortality, with distinct state-wise patterns across the USA based on racial/ethnic composition. There were missing and inconsistently reported racial/ethnic data in many states. This underscores the need for standardised reporting, attention to specific regional patterns, adequate resource allocation and addressing the underlying social determinants of health adversely affecting chronically marginalised groups.

scholarly journals Mapping chronic disease prevalence based on medication use and socio-demographic variables: an application of LASSO on administrative data sources in healthcare in the Netherlands

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Koen Füssenich ◽  
Hendriek C. Boshuizen ◽  
Markus M. J. Nielen ◽  
Erik Buskens ◽  
Talitha L. Feenstra
Keyword(s):  
Chronic Disease ◽  
Hospital Admission ◽  
Medication Use ◽  
Disease Prevalence ◽  
Percentage Error ◽  
Economic Variables ◽  
Regional Patterns ◽  
Prevalence Estimates ◽  
Socio Economic Variables ◽  
Chronic Disease Prevalence

Abstract Background Policymakers generally lack sufficiently detailed health information to develop localized health policy plans. Chronic disease prevalence mapping is difficult as accurate direct sources are often lacking. Improvement is possible by adding extra information such as medication use and demographic information to identify disease. The aim of the current study was to obtain small geographic area prevalence estimates for four common chronic diseases by modelling based on medication use and socio-economic variables and next to investigate regional patterns of disease. Methods Administrative hospital records and general practitioner registry data were linked to medication use and socio-economic characteristics. The training set (n = 707,021) contained GP diagnosis and/or hospital admission diagnosis as the standard for disease prevalence. For the entire Dutch population (n = 16,777,888), all information except GP diagnosis and hospital admission was available. LASSO regression models for binary outcomes were used to select variables strongly associated with disease. Dutch municipality (non-)standardized prevalence estimates for stroke, CHD, COPD and diabetes were then based on averages of predicted probabilities for each individual inhabitant. Results Adding medication use data as a predictor substantially improved model performance. Estimates at the municipality level performed best for diabetes with a weighted percentage error (WPE) of 6.8%, and worst for COPD (WPE 14.5%)Disease prevalence showed clear regional patterns, also after standardization for age. Conclusion Adding medication use as an indicator of disease prevalence next to socio-economic variables substantially improved estimates at the municipality level. The resulting individual disease probabilities could be aggregated into any desired regional level and provide a useful tool to identify regional patterns and inform local policy.

scholarly journals Water quality drives the regional patterns of an algal metacommunity in interconnected lakes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Min Sung Kim ◽  
Seok Hyun Ahn ◽  
In Jae Jeong ◽  
Tae Kwon Lee
Keyword(s):  
Water Quality ◽  
Community Assembly ◽  
River Flow ◽  
Geographical Area ◽  
Oxygen Demand ◽  
Algal Community ◽  
Regional Patterns ◽  
Algal Communities ◽  
Species Sorting ◽  
Metacommunity Structure

AbstractThe metacommunity approach provides insights into how the biological communities are assembled along the environmental variations. The current study presents the importance of water quality on the metacommunity structure of algal communities in six river-connected lakes using long-term (8 years) monitoring datasets. Elements of metacommunity structure were analyzed to evaluate whether water quality structured the metacommunity across biogeographic regions in the riverine ecosystem. The algal community in all lakes was found to exhibit Clementsian or quasi-Clementsian structure properties such as significant turnover, grouped and species sorting indicating that the communities responded to the environmental gradient. Reciprocal averaging clearly classified the lakes into three clusters according to the geographical region in river flow (upstream, midstream, and downstream). The dispersal patterns of algal genera, including Aulacoseira, Cyclotella, Stephanodiscus, and Chlamydomonas across the regions also supported the spatial-based classification results. Although conductivity, chemical oxygen demand, and biological oxygen demand were found to be important variables (loading > |0.5|) of the entire algal community assembly, water temperature was a critical factor in water quality associated with community assembly in each geographical area. These results support the notion that the structure of algal communities is strongly associated with water quality, but the relative importance of variables in structuring algal communities differed by geological regions.

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