Internal Migration in Kyrgyzstan: A Geographical and Sociological Study of Rural Migration

2013 ◽  
pp. 117-147 ◽  
Keyword(s):  
Internal Migration ◽  
Rural Migration ◽  
Sociological Study

scholarly journals Spatial inequality, characteristics of internal migration, and pulmonary tuberculosis in China, 2011–2017: A spatial analysis

2020 ◽  
Author(s):  
Wen-Chong He ◽  
Ke Ju ◽  
Ya-Min Gao ◽  
Pei Zhang ◽  
Yin-Xia Zhang ◽  
...  
Keyword(s):  
Spatial Variation ◽  
Internal Migration ◽  
Spatial Clustering ◽  
Rural Households ◽  
Spatial Inequality ◽  
Gdp Per Capita ◽  
Lower Income ◽  
Rural Migration ◽  
Spatial Autoregressive ◽  
Per Capita

Abstract Background: Human migration facilitate the spread of tuberculosis (TB). Migrants face an increased risk of TB infection. In this study, we aim to explore the spatial inequity of sputum smear-positive pulmonary TB (SS + PTB) in China; and the spatial heterogeneity between SS + PTB and internal migration.Methods: Notified SS + PTB cases in 31 provinces in mainland China were obtained from the national web-based PTB surveillance system database. Internal migrant data were extracted from the report on China’s migrant population development. Spatial autocorrelations were explored using the global Moran’s statistic and local indicators of spatial association. The spatial variation in temporal trends was performed using Kulldorff’s scan statistic. Fixed effect and spatial autoregressive models were used to explore the spatial inequity between SS + PTB and internal migration.Results: A total of 2 380 233 SS+PTB cases were reported in China between 2011 and 2017, of which, 1 716 382 (72.11%) were male and 663 851 (27.89%) were female. Over 70% of internal migrants were from rural households and had lower income and less education. The spatial variation in temporal trend results showed that there was an 9.9% average annual decrease in the notification rate of SS + PTB from 2011 to 2017; and spatial clustering of SS + PTB cases was mainly located in western and southern China. The spatial autocorrelation results revealed spatial clustering of internal migration each year (2011–2017), and the clusters were stable within most provinces. Internal emigration, urban-to-rural migration and GDP per capita were significantly associated with SS + PTB, further, internal emigration could explain more variation in SS + PTB in the eastern region in mainland. However, internal immigration and rural-to-urban migration were not significantly associated with SS + PTB across China. Conclusions: Our study found the spatial inequity between SS + PTB and internal migration. Internal emigration, urban-to-rural migration and GDP per capita were statistically associated with SS + PTB; the negative association was identified between internal emigration, urban-to-rural migration and SS + PTB. Further, we found those migrants with lower income and less education, and most of them were from rural households. These findings can help stakeholders to implement effective PTB control strategies for areas at high risk of PTB and those with high rates of internal migration.

Urban poverty and its connection to internal migration: a sociological study of some of the inner-city neighbourhoods of Riyadh*

2010 ◽  
Vol 3 (4) ◽  
pp. 534-550
Author(s):  
Aziza A. Alnuaim
Keyword(s):  
Inner City ◽  
Social Adjustment ◽  
Internal Migration ◽  
Rural Areas ◽  
Urban Poverty ◽  
Average Rate ◽  
Large Family ◽  
High Rate ◽  
Sociological Study ◽  
The City

This study deals with an important sociological aspect of the city of Riyadh in Saudi Arabia. It analyses urban poverty in the old, slum (shaʿbī) neighbourhoods in the centre of the city, such as those affiliated to the municipality of ‘al-Baṭḥāʾ’ where families in these areas have witnessed an increase in numbers along with a decrease in income and an increased rate of illiteracy. The residents of these neighbourhoods generally live in small houses – on average, measuring 10 m deep by 5 m wide (50 m2). Riyadh, like other Saudi cities, is characterized by a capacity to attract; however, it is at the forefront of Saudi cities with regard to the size of its population which reached approximately 4.4 million inhabitants in 1422 AH/2002 CE. The number of families is expected to grow by an average rate of 7% over the next ten years to reach 941,000. Similarly, the average rate of population growth reached 8.1% for the five-year period beginning in 1417 AH/1999 CE; and Saudis exhibit a high rate of annual growth reaching 9.6% and representing 69% of the total urban population. This urban growth, in the main, is attributable to internal migration that ranks as one of the chief factors in the size of the population. A demographic survey in 1999 clarified through the use of the variable of ‘place of birth’ that the region of Riyadh was ranked the foremost in the region for attracting Saudis. Similarly, it was obvious from results of the pilot study (Alnuaim 1999) of ‘social adjustment to immigrants from rural areas’ carried out in the neighbourhood of ‘al-ʿŪd’ and that of ‘Manfūḥah’ that there were Saudi families which had immigrated from the south-west region of the country, six years previously or less, to the impoverished inner city neighbourhoods of Riyadh, and that these families suffered a reduced or lack of income in conjunction with their large family size. Similarly, they also suffered from increased rates of illiteracy among men, women and children altogether. This study, which is a completion of some previous sociological and exploratory studies, attempts to answer the following question. To what extent is recent internal migration to the city of Riyadh and residency in its slum neighbourhoods connected to the phenomenon of urban poverty in them?

scholarly journals Spatial inequality, characteristics of internal migration, and pulmonary tuberculosis in China, 2011–2017: A spatial analysis

2020 ◽  
Author(s):  
Wen-Chong He ◽  
Ke Ju ◽  
Ya-Min Gao ◽  
Pei Zhang ◽  
Yin-Xia Zhang ◽  
...  
Keyword(s):  
Spatial Variation ◽  
Internal Migration ◽  
Spatial Clustering ◽  
Rural Households ◽  
Spatial Inequality ◽  
Gdp Per Capita ◽  
Lower Income ◽  
Rural Migration ◽  
Spatial Autoregressive ◽  
Per Capita

Abstract Background: Human migration facilitate the spread of tuberculosis (TB). Migrants face an increased risk of TB infection. In this study, we aim to explore the spatial inequity of sputum smear-positive pulmonary TB (SS + PTB) in China; and the spatial heterogeneity between SS + PTB and internal migration. Methods: Notified SS + PTB cases in 31 provinces in mainland China were obtained from the national web-based PTB surveillance system database. Internal migrant data were extracted from the report on China’s migrant population development. Spatial autocorrelations were explored using the global Moran’s statistic and local indicators of spatial association. The spatial variation in temporal trends was performed using Kulldorff’s scan statistic. Fixed effect and spatial autoregressive models were used to explore the spatial inequity between SS + PTB and internal migration. Results: A total of 2 380 233 SS+PTB cases were reported in China between 2011 and 2017, of which, 1 716 382 (72.11%) were male and 663 851 (27.89%) were female. Over 70% of internal migrants were from rural households and had lower income and less education. The spatial variation in temporal trend results showed that there was an 9.9% average annual decrease in the notification rate of SS + PTB from 2011 to 2017; and spatial clustering of SS + PTB cases was mainly located in western and southern China. The spatial autocorrelation results revealed spatial clustering of internal migration each year (2011–2017), and the clusters were stable within most provinces. Internal emigration, urban-to-rural migration and GDP per capita were significantly associated with SS + PTB, further, internal emigration could explain more variation in SS + PTB in the eastern region in mainland. However, internal immigration and rural-to-urban migration were not significantly associated with SS + PTB across China. Conclusions: Our study found the spatial inequity between SS + PTB and internal migration. Internal emigration, urban-to-rural migration and GDP per capita were statistically associated with SS + PTB; the negative association was identified between internal emigration, urban-to-rural migration and SS + PTB. Further, we found those migrants with lower income and less education, and most of them were from rural households. These findings can help stakeholders to implement effective PTB control strategies for areas at high risk of PTB and those with high rates of internal migration.

scholarly journals Spatial inequality, characteristics of internal migration, and pulmonary tuberculosis in China, 2011–2017: a spatial analysis

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Wen-Chong He ◽  
Ke Ju ◽  
Ya-Min Gao ◽  
Pei Zhang ◽  
Yin-Xia Zhang ◽  
...  
Keyword(s):  
Spatial Variation ◽  
Internal Migration ◽  
Spatial Clustering ◽  
Rural Households ◽  
Spatial Inequality ◽  
Gdp Per Capita ◽  
Lower Income ◽  
Rural Migration ◽  
Spatial Autoregressive ◽  
Per Capita

Abstract Background Human migration facilitate the spread of tuberculosis (TB). Migrants face an increased risk of TB infection. In this study, we aim to explore the spatial inequity of sputum smear-positive pulmonary TB (SS + PTB) in China; and the spatial heterogeneity between SS + PTB and internal migration. Methods Notified SS + PTB cases in 31 provinces in mainland China were obtained from the national web-based PTB surveillance system database. Internal migrant data were extracted from the report on China’s migrant population development. Spatial autocorrelations were explored using the global Moran’s statistic and local indicators of spatial association. The spatial variation in temporal trends was performed using Kulldorff’s scan statistic. Fixed effect and spatial autoregressive models were used to explore the spatial inequity between SS + PTB and internal migration. Results A total of 2 380 233 SS + PTB cases were reported in China between 2011 and 2017, of which, 1 716 382 (72.11%) were male and 663 851 (27.89%) were female. Over 70% of internal migrants were from rural households and had lower income and less education. The spatial variation in temporal trend results showed that there was an 9.9% average annual decrease in the notification rate of SS + PTB from 2011 to 2017; and spatial clustering of SS + PTB cases was mainly located in western and southern China. The spatial autocorrelation results revealed spatial clustering of internal migration each year (2011–2017), and the clusters were stable within most provinces. Internal emigration, urban-to-rural migration and GDP per capita were significantly associated with SS + PTB, further, internal emigration could explain more variation in SS + PTB in the eastern region in mainland. However, internal immigration and rural-to-urban migration were not significantly associated with SS + PTB across China. Conclusions Our study found the spatial inequity between SS + PTB and internal migration. Internal emigration, urban-to-rural migration and GDP per capita were statistically associated with SS + PTB; the negative association was identified between internal emigration, urban-to-rural migration and SS + PTB. Further, we found those migrants with lower income and less education, and most of them were from rural households. These findings can help stakeholders to implement effective PTB control strategies for areas at high risk of PTB and those with high rates of internal migration.

SOCIOLOGICAL ANALYSIS OF THE CAUSES AND CONSEQUENCES OF STUDENT EDUCATIONAL MIGRATION

2021 ◽  
Vol 75 (3) ◽  
pp. 72-80
Author(s):  
М.К. Shnarbekova ◽  
◽  
M.D. Kalmukhanbetova ◽  
Keyword(s):  
Theoretical Analysis ◽  
Internal Migration ◽  
Statistical Data ◽  
Sociological Analysis ◽  
Negative Consequences ◽  
Sociological Study ◽  
Short And Long Term ◽  
Educational Migration ◽  
External Migration

The article is aimed at identifying new trends in international and internal migration of Kazakhstani students based on the analysis of the results of a sociological study. The authors, paying special attention to foreign and domestic research within the framework of the topic, determine the need for an empirical study of the short-and long-term causes of international and internal migration of students in Kazakhstan.The article provides a qualitative analysis of statistical data on international and internal migration of Kazakhstani students, identifies the main causes of internal and external migration and a theoretical analysis of ways to prevent its negative consequences.

Phenomenology and sociology An analytical sociological study

2016 ◽  
Vol 5 (2) ◽  
pp. 267-277
Author(s):  
Aram ali faraj ◽  
◽  
Ameer khwdakaram zandi ◽  
Keyword(s):  
Sociological Study

Internal migration in Italy. Long-run analysis of push and pull factors across regions and macro-areas of the country.

2016 ◽  
Vol 13 (3) ◽  
pp. 443-454
Author(s):  
Piras Romano
Keyword(s):  
Gravity Model ◽  
Internal Migration ◽  
Empirical Studies ◽  
Great Majority ◽  
Pull Factors ◽  
Push And Pull Factors ◽  
Long Run ◽  
Italian Regions ◽  
Migration Flows ◽  
Push And Pull

The great majority of empirical studies on internal migration across Italian regions either ignores the long-run perspective of the phenomenon or do not consider push and pull factors separately. In addition, Centre-North to South flows, intra-South and intra-Centre-North migration have not been studied. We aim to fill this gap and tackle interregional migration flows from different geographical perspectives. We apply four panel data estimators with different statistical assumptions and show that long-run migration flows from the Mezzogiorno towards Centre-Northern regions are well explained by a gravity model in which per capita GDP, unemployment and population play a major role. On the contrary, migration flows from Centre-North to South has probably much to do with other social and demographic factors. Finally, intra Centre-North and intra South migration flows roughly obey to the gravity model, though not all explicative variables are relevant.

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