Socio-economic Correlates of Marital Status and Marriage Timing Among Adult Men in Nigeria

There is a gradual tendency towards prolonged bachelorhood among men in Nigeria. Studies have linked this to socio-economic factors, but this evidence is sparsely explored in the context of Nigeria. Hence, this study fills the knowledge gap. The 2016/17 Nigeria Multiple Indicator Cluster Survey data of 7803 adult men (aged 18–34 years) was analysed by using descriptive and fitting binary logitic regression and Cox regression models. Results show that slightly more than one-third of adult men in Nigeria (35%) had a marriage history and their median age at first marriage was about 24 years. Educated men (than the uneducated) and those in middle wealth group (than the poor men) were less likely to have ever been married and to delay marriage, respectively. Wealthy men were more likely to delay marriage. Employed men were more likely to have a marriage history and to delay marriage.

Download Full-text

SURVIVAL ANALYSIS TO DETERMINE AGE TO GIVE FIRST BIRTH IN WOMEN IN EAST JAVA USING EXTENDED COX REGRESSION

Jurnal Biometrika dan Kependudukan ◽

10.20473/jbk.v10i2.2021.144-152 ◽

2021 ◽

Vol 10 (2) ◽

pp. 144

Author(s):

Santi Wulan Purnami ◽

Fitria Nur Aida ◽

Sutikno Sutikno ◽

Diyah Herowati ◽

Achmad Sjafii ◽

...

Keyword(s):

Cox Regression ◽

Educational Status ◽

Age At First Birth ◽

Childbearing Age ◽

First Birth ◽

Risk Of Death ◽

First Marriage ◽

Age At First Marriage ◽

First Child ◽

First Time

The age of a woman when giving birth to her first child needs to be a concern because it is related to the safety of the mother and baby. A woman being too young or too old increases the risk of death for both the mother and baby. Every woman giving birth for the first time is likely to experience psychological disorders such as anxiety and excessive fear during labor, and even postpartum depression. Given the importance and possible extent of the consequences of women giving birth for the first time, this study intended to assess the factors that influence the age at first birth, especially amongst women of childbearing age in East Java. These factors include the age at first marriage, education, and region. The method used was the extended Cox regression model. The analysis shows that the age at first marriage and education are factors that significantly influence the age at first birth. The more mature the age at first marriage, the more mature the age at first birth. Likewise, the higher the educational status, the higher the potential for giving birth to a first child over the age of 23, especially amongst women who graduated high school and university.

Download Full-text

Vegetarian and vegan diets and risks of total and site-specific fractures: results from the prospective EPIC-Oxford study

BMC Medicine ◽

10.1186/s12916-020-01815-3 ◽

2020 ◽

Vol 18 (1) ◽

Cited By ~ 1

Author(s):

Tammy Y. N. Tong ◽

Paul N. Appleby ◽

Miranda E. G. Armstrong ◽

Georgina K. Fensom ◽

Anika Knuppel ◽

...

Keyword(s):

Cox Regression ◽

Diet Group ◽

Economic Factors ◽

Death Certificates ◽

Site Specific ◽

Main Site ◽

Specific Fracture ◽

Fracture Risks ◽

Socio Economic Factors

Abstract Background There is limited prospective evidence on possible differences in fracture risks between vegetarians, vegans, and non-vegetarians. We aimed to study this in a prospective cohort with a large proportion of non-meat eaters. Methods In EPIC-Oxford, dietary information was collected at baseline (1993–2001) and at follow-up (≈ 2010). Participants were categorised into four diet groups at both time points (with 29,380 meat eaters, 8037 fish eaters, 15,499 vegetarians, and 1982 vegans at baseline in analyses of total fractures). Outcomes were identified through linkage to hospital records or death certificates until mid-2016. Using multivariable Cox regression, we estimated the risks of total (n = 3941) and site-specific fractures (arm, n = 566; wrist, n = 889; hip, n = 945; leg, n = 366; ankle, n = 520; other main sites, i.e. clavicle, rib, and vertebra, n = 467) by diet group over an average of 17.6 years of follow-up. Results Compared with meat eaters and after adjustment for socio-economic factors, lifestyle confounders, and body mass index (BMI), the risks of hip fracture were higher in fish eaters (hazard ratio 1.26; 95% CI 1.02–1.54), vegetarians (1.25; 1.04–1.50), and vegans (2.31; 1.66–3.22), equivalent to rate differences of 2.9 (0.6–5.7), 2.9 (0.9–5.2), and 14.9 (7.9–24.5) more cases for every 1000 people over 10 years, respectively. The vegans also had higher risks of total (1.43; 1.20–1.70), leg (2.05; 1.23–3.41), and other main site fractures (1.59; 1.02–2.50) than meat eaters. Overall, the significant associations appeared to be stronger without adjustment for BMI and were slightly attenuated but remained significant with additional adjustment for dietary calcium and/or total protein. No significant differences were observed in risks of wrist or ankle fractures by diet group with or without BMI adjustment, nor for arm fractures after BMI adjustment. Conclusions Non-meat eaters, especially vegans, had higher risks of either total or some site-specific fractures, particularly hip fractures. This is the first prospective study of diet group with both total and multiple specific fracture sites in vegetarians and vegans, and the findings suggest that bone health in vegans requires further research.

Download Full-text

Fertilitas Migran dan Faktor Yang Memengaruhi Fertilitas di Jawa Barat

Populasi ◽

10.22146/jp.36203 ◽

2018 ◽

Vol 25 (2) ◽

pp. 44

Author(s):

Rindang Ekawati ◽

Rina Herartri ◽

Nuraini Nuraini ◽

Laili Rahayuwati ◽

Sukamdi Sukamdi

Keyword(s):

Considerable Increase ◽

Economic Factors ◽

West Java ◽

Marriage Age ◽

Factors Affecting ◽

First Marriage ◽

Dynamics Of Population ◽

Economic Survey ◽

The Difference ◽

Socio Economic Factors

Migrasi merupakan salah satu faktor yang memengaruhi dinamika penduduk, baik melalui jumlah migran maupun fertilitas migran. Jumlah migrasi yang besar ke Provinsi Jawa Barat merupakan salah satu penyebab peningkatan jumlah penduduk yang cukup besar. Jika migran memiliki fertilitas yang lebih tinggi dibandingkan dengan nonmigran, maka pengaruh tersebut akan lebih besar lagi. Penelitian ini bertujuan untuk mengkaji perbedaan fertilitas antara migran dan nonmigran serta faktor-faktor yang memengaruhi fertilitas di Jawa Barat. Data yang digunakan adalah data Survei Sosial Ekonomi Nasional (Susenas) tahun 2015. Analisis dilakukan menggunakan statistik deskriptif dan inferensial. Hasil penelitian menunjukkan terdapat kecenderungan migran memiliki fertilitas yang lebih tinggi dibandingkan dengan nonmigran. Sementara itu, faktor sosial ekonomi yang berpengaruh terhadap fertilitas adalah pendidikan, usia kawin pertama, penggunaan alat kontrasepsi, dan kegiatan utama (pekerjaan). Migration is one of the factors that influences the dynamics of population, both through the number of migrants and the fertility of migrants. The large number of migrants to West Java Province is one of the causes of a considerable increase in population. If migrants have higher fertility than non-migrants, the effect will be even greater. This study aims to examine the difference of fertility between migrants and non-migrants as well as factors affecting fertility in West Java. The data used is 2015 National Socio-Economic Survey (Susenas). The analysis is done using descriptive and inferential statistics. The results show that there is a tendency for migrants to have higher fertility compared with non-migrants while the socio-economic factors that have an effect on fertility are education, first marriage age, use of contraceptives, and main activities (work).

Download Full-text

Lifestyle Segmentation Variables as Predictors of Home-Based Trips for Atlanta, Georgia, Airport

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/2266-03 ◽

2012 ◽

Vol 2266 (1) ◽

pp. 20-30 ◽

Cited By ~ 7

Author(s):

Josephine D. Kressner ◽

Laurie A. Garrow

Keyword(s):

Regression Models ◽

Travel Demand ◽

Economic Factors ◽

Linear Regression Models ◽

Data Set ◽

Credit Reporting ◽

Adequate Information ◽

Home Based ◽

Air Travel Demand ◽

Socio Economic Factors

This research investigated the influence of demographic and socio-economic factors on air travel demand by using a unique data set purchased from a credit-reporting agency. Linear regression models based on lifestyle segmentation variables were used to predict air passenger trips for Hartsfield–Jackson International Airport in Atlanta, Georgia. The study focused on predicting trips that originated from or terminated at residences in Atlanta's 13-county metropolitan area. The lifestyle regression models were compared with regression models based on income, because the latter were similar to the regression models currently used by the Atlanta Regional Commission to predict home-based airport passenger trips. The results provide directional evidence for using lifestyle clusters over income groups in predicting airport passenger trips. The evidence suggests that alternative data sources with adequate information for lifestyle segmentation can improve airport passenger models. The discussion points out the need for air passenger surveys to collect information about the number of annual air trips a surveyed individual takes.

Download Full-text

Forecasting of Tourism Processes in Uzbekistan in Correlation Regression Models

INTERNATIONAL JOURNAL OF MULTIDISCIPLINARY RESEARCH AND ANALYSIS ◽

10.47191/ijmra/v4-i11-43 ◽

2021 ◽

Vol 04 (11) ◽

Author(s):

F.E. Gulmurodov ◽

Keyword(s):

Future Development ◽

Regression Models ◽

Regression Function ◽

Development Trend ◽

Tourism Industry ◽

Economic Factors ◽

Factors Affecting ◽

The Future ◽

The Development Trend ◽

Socio Economic Factors

The article provides detailed information on the process of developing effective plans for the development of the tourism industry and choosing the optimal one based on them, forecasting the future development of the industry. It also considers the processes of using special computational and arithmetic methods that allow predicting the events and happenings in the tourism industry, to determine the regression function as a result of the interaction and interaction of indicators representing the type of activity. As a result of targeted research, using correlation-regression models, a forecast of the development trend of the tourism industry based on socio-economic factors affecting the tourism process was developed.

Download Full-text

Factors influencing desired number of children among Ethiopian women: Application of count regression models.

10.21203/rs.2.17780/v1 ◽

2019 ◽

Author(s):

Habitu Liyew Molla ◽

Essey Kebede Muluneh

Keyword(s):

Family Size ◽

Women's Education ◽

Regression Models ◽

Wealth Index ◽

Reproductive Age ◽

Number Of Children ◽

First Marriage ◽

Factors Influencing ◽

Age At First Marriage ◽

Desired Family Size

Abstract Background: Desired family size, the number of children wanted in one’s lifetime, is one of the major factors influencing the population dynamics. Knowledge of factors influencing the desired family size is crucial in regulating the population growth. This study assesses the desired family size and its determinants among Ethiopian women. Methods: The study was based on the 2016 Ethiopian Demographic and Health Survey (EDHS) data. A total of 13,941 women with complete information were considered in the study. Count regression models, a family of generalized linear models, were used to identify determinant factors for the desired number of children among women in Ethiopia. Results: Results showed that the average number of children per women was 4.5. The highest average was recorded in Somali region (10.58) and the lowest in Addis Ababa city administration (3.56). The random intercept negative binomial regression model was found to be the most appropriate model for the data. Women’s age, household head, contraception using, wealth index, women’s education, religion, marital status, husband’s work, family size and age at first marriage were significantly associated with the desired number of children by women at reproductive age. The study also showed that there was significant regional variation in desired number of children among Ethiopian women. Conclusions: Variables such as women’s age and family size were positively associated with the desired number of children by women at reproductive age while age at first marriage, contraception using, wealth index and women’s education were negatively associated with the desired number of children by women. Women who attained higher level of education preferred small family size compared to women with no formal education. Desire for children was high among mothers from rural areas, women in the poorest economic level and woman having no work. Keywords: Desired number of children, statistical weight, EDHS, Count regression models, multilevel analysis.

Download Full-text

Statistical Data Research on Staff Training for the Digital Economy in the Russian Federation

Высшее образование в России ◽

10.31992/0869-3617-2021-30-11-29-41 ◽

2021 ◽

Vol 30 (11) ◽

pp. 29-41

Author(s):

Yu. V. Frolov ◽

T. M. Bosenko

Keyword(s):

Russian Federation ◽

Regression Models ◽

Statistical Data ◽

Digital Economy ◽

Economic Factors ◽

Objective Functions ◽

Economic Sectors ◽

Different Dimensions ◽

The Russian Federation ◽

Socio Economic Factors

The article analyzes the statistical data relating to training specialists for digitalized economy by secondary vocational and higher education institutions. The purpose of the study was to develop and test personnel support indices for digitalization of the economy, as well as to identify social and economic factors that significantly affect the level of personnel support for the processes of digital transformation of the economy. The authors applied data from the official statistical reporting of the Russian Federation. The proposed staffing indices were modeled as objective functions depending on socio-economic factors characterizing the development of the economy in different dimensions. At the same time, the indices themselves were calculated as values in which the parameters of the output of digital specialists and their relevance in the economy were correlated. In the course of the study, a comparison of statistical and neural network data modeling methods and generalizing indices was performed. An analysis of the obtained regression models and an analysis of the sensitivity of trained neural networks made it possible to evaluate their accuracy in predicting the trends in the staffing of the digital economy and to identify factors that significantly affect the achievement of the goal of matching the output of specialists and the demands of economic sectors.

Download Full-text

Exploring the Spatial Variation Characteristics and Influencing Factors of PM2.5 Pollution in China: Evidence from 289 Chinese Cities

Sustainability ◽

10.3390/su11174751 ◽

2019 ◽

Vol 11 (17) ◽

pp. 4751 ◽

Cited By ~ 5

Author(s):

Zhao ◽

Keyword(s):

Spatial Variation ◽

Environmental Conditions ◽

Regression Models ◽

Economic Factors ◽

Spatial Agglomeration ◽

Chinese Cities ◽

Explanatory Variables ◽

Haze Pollution ◽

Pm2.5 Concentration ◽

Socio Economic Factors

Haze pollution has become an urgent environmental problem due to its impact on the environment as well as human health. PM2.5 is one of the core pollutants which cause haze pollution in China. Existing studies have rarely taken a comprehensive view of natural environmental conditions and socio-economic factors to figure out the cause and diffusion mechanism of PM2.5 pollution. This paper selected both natural environmental conditions (precipitation (PRE), wind speed (WIN), and terrain relief (TR)) and socio-economic factors (human activity intensity of land surface (HAILS), the secondary industry's proportion (SEC), and the total particulate matter emissions of motor vehicles (VE)) to analyze the effects on the spatial variation of PM2.5 concentrations. Based on the spatial panel data of 289 cities in China in 2015, we used spatial statistical methods to visually describe the spatial distribution characteristics of PM2.5 pollution; secondly, the spatial agglomeration state of PM2.5 pollution was characterized by Moran’s I; finally, several regression models were used to quantitatively analyze the correlation between PM2.5 pollution and the selected explanatory variables. Results from this paper confirm that in 2015, most cities in China suffered from severe PM2.5 pollution, and only 17.6% of the sample cities were up to standard. The spatial agglomeration characteristics of PM2.5 pollution in China were particularly significant in the Beijing–Tianjin–Hebei region. Results from the global regression models suggest that WIN exerts the most significant effects on decreasing PM2.5 concentration (p < 0.01), while VE is the most critical driver of increasing PM2.5 concentration (p < 0.01). Results from the local regression model show reliable evidence that the relation between PM2.5 concentrations and the explanatory variables varied differently over space. VE is the most critical factor that influences PM2.5 concentrations, which means controlling motor vehicle pollutant emissions is an effective measure to reduce PM2.5 pollution in Chinese cities.

Download Full-text