Natural change of the rural population of Yugoslavia with an emphasis on fertility in the early 1990s

The process of intensive deruralization or decline in total rural population of the FR of Yugoslavia in the second half of the 20th century ??m? exclusively as ? result of migration from rural to urban areas. Though constantly positive at the level of the country as ? whole, the downward tendency in rural population growth was observed throughout the period. The author analyzes components and dynamics of natural change in rural population with emphasis on the period from 1981 to 1997, regional specifics up to the republican and provincial levels, and the main differences from the specifics of natural change in urban population. The author highlights that in analyzing natural change b? type of settlement, particular attention should b? paid to the very pronounced interdependency between the components of population dynamics and the age-sex structure, the more so as the latter is becoming the most significant direct determinant of the natural population growth. Namely, crude birth rate of rural population in Yugoslavia has tor several decades now been lower th?n the corresponding measure for urban population, while the crude death rate has, however, been higher. At the same time, in age-specific terms, fertility was higher and mortality lower in rural relative to urban populations. Such discrepancy evolved primarily from the unfavorable age-specific structure of rural population and its notably disturbed sex-specific structure (pronounced surplus in male, particularly younger middle-aged population). The author goes on to analyze the main features of fertility and reproduction in rural population based on demographic statistics. ?? argues that the general and total fertility rates represent more adequate indicators of fertility in rural population, as the impact of age structure has been partially or even fully eliminated. Thus, in 1990-1992, both indicators are higher for rural relative to urban population, and sufficiently high relative to the mortality level to assure integral replacement (net reproduction was 1.0 in rural relative to 0.9 in urban population). In all m???r regions of the country, fertility was higher in rural relative to urb?n population. Such differences were minimal in low fertility regions, while remaining significant in Kosovo and Metohia. The analysis of fertility was supplemented b? the 1991 census data, which, for the first time, included the number of live born children b? age of mother and type of settlement. Despite the fact that such data on female population illustrate the situation at the moment of census taking only, and not at the moment of birth, the author thinks that the cohort analysis based on the census data provide ? much more realistic account of fertility in rural population than the period analysis based on vital statistics, primarily as it resolves the problem of ???ur?t? registration 0f vital events b? type of settlement. Thus, cohort fertility rates show that fertility of rural female population is notably higher than the effective fertility in urban areas. This is true for all five-year age groups without exception, and equally true for all major regions Finally, the author analyzes cohort fertility of the autochthon versus migrant populations, as well as fertility b? ethnic origin. ?? draws ? general conclusion that fertility is higher in migrant relative to autochthon female population, and that th? differences are much more pronounced in rural relative to urban populations. This phenomenon is explained b? the so-called marriage-motivated migration, which the author assumes to b? dominant in migrant female population. As for fertility rates b? ethnic origin, the well-known differences are also evident in rural population. Namely, all ethnic groups can b? classified b? level fertility into three categories. The highest rate is recorded for ethnic Albanian, Roma and Muslim women. Montenegrin women record moderately high fertility rates, while the rate recorded for women of Croatian descent is generally sufficient for generation replacement. The third category is made u? of Serb, Yugoslav, and ethnic Hungarian women as well as the great majority of women of other ethnic origin (?unj?va?, Romanian and Slovak). ?ll these nationalities record very low fertility levels, which have for years been insufficient to enable generation replacement.

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Rural–urban differentials in fertility levels and fertility preferences in West Bengal, India: a district-level analysis

Journal of Biosocial Science ◽

10.1017/s0021932019000324 ◽

2019 ◽

Vol 52 (1) ◽

pp. 117-131

Author(s):

Sayantani Chatterjee

Keyword(s):

Socioeconomic Factors ◽

Rural Areas ◽

Urban Areas ◽

Census Data ◽

West Bengal ◽

District Level ◽

Low Fertility ◽

Fertility Rates ◽

Number Of Children ◽

Contraception Use

AbstractFertility in West Bengal is one of the lowest in India, and this relies heavily on the use of traditional methods of contraception. Social scientists and demographers have pointed to the historical role of the diffusion process of adhering to a small family size. The Total Fertility Rate (TFR) in Kolkata district, the state capital, is the lowest in the country, and has been a centre of low fertility historically. However, stark differences in rural–urban fertility rates have existed over the last few decades in West Bengal, but these have now started to narrow. This study aimed to capture the macro-level rural–urban differences in fertility levels and preferences in the West Bengal, and understand how socioeconomic factors affect these. Data were drawn from the Census of India (2011) and NFHS-4 (2015–16). Using census data and the Reverse-Surviving Method, the TFR of West Bengal was estimated to be 1.9, varying between 2.1 and 1.7 in rural and urban areas. The rural–urban gap in the district-level fertility rates was prominent, specifically in districts with higher levels of fertility. Kolkata, Hugli and North Twenty-Four Parganas had the lowest-low fertility (TFR = <1.5). Fewer than half of women with only one living child wanted further children, and this was somewhat higher in rural areas. Around 40% of women had achieved their desired number of children. However, a substantial proportion (43.1%) had a lower number of children than desired, varying between 45.9% and 41.7% in urban and rural areas, respectively. Contraception use, female education and age at marriage, along with the other socioeconomic factors, had a greater influence on rural fertility rates than on urban counterparts in the districts of West Bengal. Further research should be directed at understanding the contemporary fertility decline as well as the gap between ideal and desired number of children, specifically in those districts with very low fertility rates.

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Aging of rural population in Yugoslavia

Stanovnistvo ◽

10.2298/stnv9904073a ◽

1999 ◽

Vol 37 (1-4) ◽

pp. 73-92

Author(s):

Jelena Antonovic

Keyword(s):

Age Structure ◽

Rural Population ◽

Urban Areas ◽

Age Groups ◽

Population Ageing ◽

Low Fertility ◽

Demographic Ageing ◽

Substantial Impact ◽

Mass Migration ◽

Rural And Urban

Mass migration to urban areas constitutes the basic direct factor of the decline in rural population of Yugoslavia in the second half of the 20th century. Due to the characteristic migration patterns by age and sex, they have had a substantial impact on the change in age structure of rural population towards rapid demographic ageing. By inducing decline in fertility and an increase in mortality, the newly formed age structure is increasingly becoming one of the basic factors to further decline in population, or even the major factor to rural depopulation in the majority of regions. The paper analyzes changes in age structure of rural population in the FR of Yugoslavia and across its republics and provinces during the period from 1961 to 1991. The conditions prevailing during the last census (1991) are particularly highlighted. The author points to distinct differences in ageing of urban versus rural populations, and considerable regional differences at the achieved level of demographic age. Based on the main demographic age indicators (the share of five-year and larger age groups, average age, ageing index and movement in major age-specific contingents), the author concludes that the process of population ageing had taken place in both rural and urban populations, but was more intensive in villages (higher share of the aged, higher index of ageing and higher average age) during the period under review. The author points to distinct ageing of rural population in all republics and provinces. It was most prominent in central Serbia and Vojvodina, while being quite slow in Kosovo and Metohia and recorded mainly in between the last two censuses (1981-1991). Likewise, Kosovo and Metohia constitute the only major region of Yugoslavia in which rural population in 1991 is still demographically younger than the population in urban settlements. Rural versus urban population ageing was much more intensive in other major regions of the country, both from the base and from the apex of the age pyramid. In view of the minimal differences in fertility and mortality levels by type of settlement (particularly in central Serbia and Vojvodina), the author argues that the inherited age structure constitutes the main cause of rapid acceleration in rural population ageing in low fertility regions.

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Effectiveness of Government Policies in Controlling COVID-19 in India

International Journal of Health Services ◽

10.1177/0020731420983749 ◽

2020 ◽

pp. 002073142098374

Author(s):

Ashutosh Pandey ◽

Nitin Kishore Saxena

Keyword(s):

Population Density ◽

Rural Areas ◽

Rural Population ◽

Urban Areas ◽

Urban Population ◽

Demographic Factors ◽

Poverty Rate ◽

Government Policies ◽

Cumulative Number ◽

Population Number

The purpose of this study is to find the demographic factors associated with the spread of COVID-19 and to suggest a measure for identifying the effectiveness of government policies in controlling COVID-19. The study hypothesizes that the cumulative number of confirmed COVID-19 patients depends on the urban population, rural population, number of persons older than 50, population density, and poverty rate. A log-linear model is used to test the stated hypothesis, with the cumulative number of confirmed COVID-19 patients up to period [Formula: see text] as a dependent variable and demographic factors as an independent variable. The policy effectiveness indicator is calculated by taking the difference of the COVID rank of the [Formula: see text]th state based on the predicted model and the actual COVID rank of the [Formula: see text]th state[Formula: see text]Our study finds that the urban population significantly impacts the spread of COVID-19. On the other hand, demographic factors such as rural population, density, and age structure do not impact the spread of COVID-19 significantly. Thus, people residing in urban areas face a significant threat of COVID-19 as compared to people in rural areas.

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Urbanisation and Growth of Slum Population in Jharkhand: A Spatial Analysis

Space and Culture India ◽

10.20896/saci.v3i1.134 ◽

2015 ◽

Vol 3 (1) ◽

pp. 67

Author(s):

Rahul Harshwardhan ◽

V K Tripathy

Keyword(s):

Population Growth ◽

Affordable Housing ◽

Urban Areas ◽

Urban Population ◽

Census Data ◽

Health And Safety ◽

Secondary Data ◽

Population Pressure ◽

Urban Migration ◽

Slum Population

The objective of this paper is to examine the relation between the pace of urbanisation and growth of slum population in Jharkhand. This paper also attempts to analyse the trends and patterns of growth of slum population at the district level in Jharkhand. In terms of urbanisation process of India, slums have become an integral part of urban scenario. In India, rapid growth of slums is the result of rural-urban migration of the rural poor to the cities/towns in search of employment in the last two decades. In the absence of any affordable housing, there has been growth of slums in the urban areas of the country. In India, out of a total population of 1.21 billion, 31.30% population resides in the urban areas, but 21.68% (61.8 million) of the total urban population live in the slums. Slums are considered as a major problem within the urban areas, particularly in relation to the issues of transportation, population growth, health and safety. The developing states or regions of India are more prone to this problem due to the lack of infrastructural development and heavy urban population pressure. Like other states of India, Jharkhand too is facing the problem of slums. After its separation from Bihar in 2000, the rate of urbanisation and the rate of growth of slums had gone high. The study reveals that in 2001, there were only 11 urban centers consisting of slum population but in 2011, it reached to 31. The slum population registers 23.68% growth while the urban population growth stands at 32%. This paper is primarily based on secondary data collected from different governmental agencies, particularly the Census data of population to analyse the spatial distribution of slum population in the districts of Jharkhand. This study explores the changing urbanisation scenario in Jharkhand and the growth of slums with respect to it.

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Mental Stress and Multiple Risk Factors of Cardiovascular Diseases with Regional Variations in Women of Urban and Rural Areas of Sindh, Pakistan

Cardiology Open Access ◽

10.33140/coa.06.02.02 ◽

2021 ◽

Vol 6 (2) ◽

Keyword(s):

Risk Factors ◽

Urban Area ◽

Rural Area ◽

Psychological Stress ◽

Rural Women ◽

Rural Population ◽

Urban Areas ◽

Mental Stress ◽

Physical Inactivity ◽

Urban Population

Introduction: The high prevalence of risk factors in women in developing countries of South Asia appears to have been translated into early and severe CHD in contrast to their counterpart in the first world nations, which has been related to obesity and insulin resistance and genetically determined increased lipoprotein Lp(a) levels. Mental stress due to urbanization, sedentary life style and physical inactivity may be the most important factor initiating obesity and the clustering of all other risk factors hypertension, dyslipidaemia and (WHR). These risk factors vary in different regions of South Asia. Aims and Objectives: Our aim of the study was to describe and analyse differences between the frequency of risk factors such as psychological stress due to, socio-economical aspects, life style especially physical activity, and health behaviours which may contribute in the course of CAD in women of both rural and urban areas of Pakistan because no such significant data is available in women with CAD. Study Design: This descriptive cross-sectional comparative study was conducted in Cardiology Department of Dow University of Health and Sciences Karachi, Pakistan, from March 2014 to March 2016 by filling a questionnaire and laboratory data. The study group comprised female subjects around 577 (Urban 347 {60.1%} and Rural 230 {39.9%}) women ranged from 25-65 years of age who underwent coronary angiography and had definite coronary atherosclerotic diseases. Our study was conducted by examining the psychological stress in women of both areas and its strength of association with frequency of other risk factors in female patients of urban and rural areas with definite CHD taking account the difference in age and education level into account. Result: Analysis of this study conducted at department of Cardiology in Dow University Karachi from March 2014 to March 2017 revealed that the women of rural area were comparatively more physically active then women of urban area. Prevalence of mental stress, hypertension, diabetes, obesity, higher BMI, hyperlipidaemia (especially TC) waist and hip circumference of both areas were found to be different after adjustment made for age. A considerable association was found between psychological stress and other factors in ischemic heart disease patients showing the p-value (p=0.043). Psychological stress was found 82% in both groups and (13%) women had no stress rated as normal more in rural (26%) vs (04%) in urban population. Physical inactivity in women with CHD was found in 92% urban in contrast to 45% in rural population, (p=0.009). Hypertension prevalence was more in urban 253 in comparison to 151 women in rural area. Diabetes Mellitus was also found more in urban than rural population, especially in age below 50, 79 (23%) urban vs 60 (26%) in rural population. Women beyond 50 years of age, 85 (24%) urban vs 64 (27%) rural area had prevalence of obesity comparatively higher in urban residents 71 (20%) than 44(%) in rural dwellers and 32 (9%) urban vs 16 (7%) in rural women in age range below 50 years. Higher waist circumstance was observed more in urban residents (4.8 cm) whereas BMI was more (1.8 unit) in women of rural area than urban women. Prevalence of smoking and nicotine chewing was relatively higher in urban population in below 50 years of age with 30 (09%) urban vs 13 (05%) in rural women and in age beyond 50, 11 (03%) urban vs 10 (04%) in rural women was witnessed. Average total cholesterol, serum triglycerides and LDL were found to be higher in urban compared to rural area residents and HDL was comparatively lower in urban area group. Mean cholesterol level was seen at average of 353 mg% in urban vs 223 mg% in rural population. Serum cortisol level showed significant variation in urban group 19.1 vs 14.2 in rural group (sample, as well as serum fibrinogen was raised more raised in urban population). Conclusion: Our study shows increased prevalence of mental stress and physical inactivity in female residents of urban area leading to Higher blood pressure, DM, dyslipidaemia and central obesity specially in Waist circumference than rural area. The mental stress induced by excessive demands of work at home and at working place with too little control is not unique to women of urban areas.

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Effectiveness of Government Policies in Controlling COVID-19 in India

10.31124/advance.12612944 ◽

2020 ◽

Author(s):

ASHUTOSH PANDEY ◽

Nitin Saxena

Keyword(s):

Population Density ◽

Rural Areas ◽

Rural Population ◽

Urban Areas ◽

Urban Population ◽

Demographic Factors ◽

Government Policies ◽

Cumulative Number ◽

Indian States ◽

The People

<p>The purpose of this study is to find the demographic factors which are responsible for the spread of COVID-19 and to suggest a measure to identify the effectiveness of government policies in controlling COVID-19. The study hypothesises that the cumulative number of confirmed COVID-19 patients depends on the urban population, rural population, number of persons aged more than fifty, the population density and poverty rate in the state. A log-linear model is used to test the stated hypothesis, with the cumulative number of confirmed COVID-19 patients up to period as a dependent variable and demographic factors as an independent variable. The regression result shows that out of the selected variables, only the urban population significantly impacts the total number of patients tested positive for COVID-19. Our study finds that the urban population significantly impacts the spread of COVID-19. On the other had the demographic factors like rural population, density, and age structure do not impact the spread of COVID-19 significantly. Thus the people residing in the urban areas face a more significant threat of COVID-19 as compared to the people in rural areas. The study identifies the Indian states which need greater effectiveness in the implementation of pandemic control policies. Our study finds that the urban population significantly impacts the spread of COVID-19. On the other had the demographic factors like rural population, density, and age structure do not impact the spread of COVID-19 significantly. Thus the people residing in the urban areas face a more significant threat of COVID-19 as compared to the people in rural areas. The study identifies the Indian states which need greater effectiveness in the implementation of pandemic control policies.</p>

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“New” rural settlements – former urban-type settlements

Izvestiya Rossiiskoi Akademii Nauk Seriya Geograficheskaya ◽

10.31857/s2587-55662019618-34 ◽

2019 ◽

pp. 18-34

Author(s):

A. S. Chuchkalov ◽

A. I. Alekseev

Keyword(s):

Rural Areas ◽

Rural Population ◽

Urban Population ◽

Census Data ◽

Rapid Decline ◽

Rural Settlements ◽

Far North ◽

The North ◽

Type Settlement ◽

Average Population Size

Since the 1920s, when the notion of urban-type settlement (UTS) was introduced in Russia, and until the 1980s the number of UTSs was constantly increasing. But since the 1990s, their rapid decline began, and by 2019 more than a third of them were transformed into rural settlements. In this article, the authors try to find out what the new villages the former UTSs are; where they are located; what their functions (largely lost) are, and what the specific features of their population are. From 1989 to 2010, the processes of transformation of UTSs into rural settlements administratively increased rural population of Russia by 2.4 mln people and held back the growth of the urban population share, which increased only slightly from 73.4 to 73.7%. When comparing the census data of 1989 and 2010 in many regions, the administrative ruralization radically changed the dynamics of the population: instead of a real decrease in the number of rural residents, Census-2010 showed the increase of rural population. Former UTSs are losing population more rapidly than the rural areas of their municipal districts, and the most intensive outflow is in logging settlements, centers of construction and colonies-settlements. The average population size of the former UTSs is minimal in the North of European Russia and the Far North, and maximum in the European South and in the Ural-Volga area, where the former UTSs-district centers are mostly concentrated, in which change of their status was purely formal.

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Authors Response: Clinical Differences Between Children With Asthma And Rhinitis In Rural And Urban Areas

Colombia Medica ◽

10.25100/cm.v50i1.4433 ◽

2019 ◽

pp. 46-48

Author(s):

Jorde Sánchez ◽

Andrés Sánchez ◽

Ricardo Cardona

Keyword(s):

Sample Size ◽

Urban Area ◽

Rural Area ◽

Rural Population ◽

Urban Areas ◽

Urban Population ◽

Sample Size Calculation ◽

Rural And Urban Areas ◽

Rural And Urban ◽

Children With Asthma

Dear Editors: We greatly appreciate the interest shown in the article "Clinical differences between children with asthma and rhinitis in rural and urban areas", which we hope will be one of several future articles that we intend to carry out in the study cohort. To the questions generated by the reader, one is focused on the calculation of the sample size, while the other two questions are focus in the method of analysis, and the reader suggests, it could be more robust. Regarding the sample size, we describe that infant asthma in urban areas of Medellin was 11% and rhinitis 23%, according to previous studies. There is no data available for the rural area. We note that with a confidence level of 95%, a power of 80% and a sample size error of 0.5%, the sample size was calculated; estimating 201 children for the urban area and 128 for the rural area. Finally, we recruited and were able to continue for a year, a total of 248 children from the urban area and 134 from the rural area. The complaint of the reader, is focus that the more appropriated technique would be "… the appropriate sample size calculation must have been the difference of means between two independent populations, although the authors did not report any ACT effect size based on previous studies." First, we fully agree with the reader that for this type of design, the study lost power by the form of sample size calculation. We did not find studies with the urban and rural ACT tests in the studied population, which made it impossible to obtain these parameters to perform the sample size calculation by the technique "power two means" (difference of means of two independent groups). ). As we noted in the article, we do not have previous data in the rural population that allow us to infer the precise prevalence of asthma in this area; as we also noted in the article the prevalence in Colombia of asthma in the general urban population is 11%, there are also data that indicate that in the child population (less than 12 years) it is around 23%; if we work with these two prevalence where we assume that the highest in children is for the urban population and that possibly the lowest corresponds to what happens in the rural population 1 and assuming the parameters; alpha 0.05, power 0.80, delta 0.12 rural prevalence 0.11 vs. urban prevalence 0.23, a sample size of 306 is required; 153 for each group; in the urban area we had the availability of 201 children and in the rural area we made 128, which is close to the desired. Therefore we consider that we fulfill the expectation according to the mathematical formula used (chi-squared test comparing two independent proportions).

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MORTALITY FROM RESPIRATORY SYSTEM CANCER IN THE TOMSK REGION

Siberian Journal of Oncology ◽

10.21294/1814-4861-2018-17-3-5-10 ◽

2018 ◽

Vol 17 (3) ◽

pp. 5-10

Author(s):

E. L. Choynzonov ◽

L. D. Zhuikova ◽

I. N. Odintsova

Keyword(s):

Mortality Rate ◽

Respiratory System ◽

Rural Population ◽

Urban Areas ◽

Urban Population ◽

Malignant Neoplasm ◽

Lifetime Risk ◽

Lung Cancer Death ◽

Respiratory Cancer ◽

Tomsk Region

A retrospective epidemiological analysis of the mortality from respiratory system cancer among the population of the Tomsk region for a ten-year period was carried out using data drawn from the official population and mortality statistics of the Tomsk region. Cancer has the second leading cause of death behind cardiovascular disease. Respiratory system cancer is the 3-rd most common cause of cancer-related death after cancers of the digestive system and genital organs. The standardized mortality rate for respiratory system cancer among the rural population is significantly higher than that in the urban population (p<0.05). Over the study period, the respiratory system mortality rate decreased for males (р=0.0000) and remained relatively constant for females. The lifetime risk of dying from respiratory system cancer in 2016 in the Tomsk region was higher than the national average. For men, it was the highest among the main localizations. Compared to 2007, the mortality rate decreased, as the risk of lung cancer death in men decreased. The lifetime risk of dying from respiratory system cancer was higher in the rural population than in the urban population. The indicator of «severity» of the disease indicates an unfavorable situation in terms of quality and completeness of statistical recording of patients and early diagnosis of respiratory cancer, especially in urban areas of the Tomsk region. In order to ensure timely and adequate routing of patients with suspected malignant neoplasm and timely diagnosis, the continued implementation of the Population-based Cancer Registry with coverage of all administrative territories and areas is of great importance.

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