4 research outputs found

    āļĢāļđāļ›āđāļšāļšāļāļēāļĢāđāļˆāļāđāļˆāļ‡āļ‚āļ­āļ‡āļ›āļĢāļ°āļŠāļēāļāļĢāđƒāļ™āļ›āļĢāļ°āđ€āļ—āļĻāđ„āļ—āļĒāđāļĨāļ°āđ€āļ™āļ›āļēāļĨ:āļāļēāļĢāļ›āļĢāļ°āļĒāļļāļāļ•āđŒāđƒāļŠāđ‰āļāļēāļĢāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāļ­āļ‡āļ„āđŒāļ›āļĢāļ°āļāļ­āļš

    No full text
    Thesis (Ph.D.(Research Methodology))--Prince of Songkla University, 2015Thailand is in the low stationary phase of demographic transition and Nepal is in the late expanding phase of demographic transition. The probability of future population change depends mainly on current age-sex distribution of the population. Therefore, this thesis focuses on application of factor analysis in clustering provinces and districts based on age-sex distribution of population in Thailand and Nepal. The descriptive and comparative analytical strategies were adopted, including application of multivariate statistical method called factor analysis in demographic data. This thesis consists of three parts. The first part of the study aims to apply factor analysis to cluster provinces based on age-sex distribution of population in Thailand. The data table consists of population counts by 5 years age group for each sex and 76 provinces. Data were managed using spline interpolation. Three-factor model was best fitted to data. Three factors were interpreted as pattern of age-sex distribution. This study found three distinct patterns of population distribution in Thailand. Twenty-seven southern and northeastern region provinces, mainly bordering Myanmar, Cambodia or Malaysia, share the classical pattern of population distribution. The majority of central region provinces, and also Phuket from the south share a similar population distribution pattern, which peaked at the young age group. So too, most of the northern region provinces share another pattern that dipped at the young age group. In conclusion, population distribution is not symmetrical across Thailand. The factor model approximated well this variation and clustered the provinces in three patterns. The second part of this study used population data form 2011 census in Nepal. This study clustered the districts in Nepal based on the patterns of age-sex structures by applying factor analysis. The factor analysis was applied to spline smooth single-year age population by sex and district. A three-factor model was best fitted to the data from Nepal. These three common factors were interpreted as three different patterns based on common characteristics of age and sex distribution. The study found that 23, 17 and 5 districts correlated purely to factor 1, 2 and 3, respectively. Thirty districts were found correlated with two or more factors. In conclusion, the age-sex structure varied substantially between the different districts of Nepal in 2011. The variations were explained well by a three-factor model. The third part focuses on inter-census population changes in Nepal. The population data from Nepal census 2001 and 2011 were used for this part. This descriptive study aimed to summarize the variation in inter-census population changes at the district level by age and sex and explore possible componentsof these changes. The districts were grouped based on both absolute number and percentage of inter-census changes and presented in the thematic map. Spline interpolated single year age population plotted separately for positive and negative inter census district by sex. The top three highly increased districts by percentage were Kathmandu (61.23%), Lalitpur (38.59%), Bhaktapur (35.12%) whereas the top three highly decreased districts were Manang (-31.80%), Khotang (-10.84%) and Mustang (-10.21%). The decreasing pattern was found in mountain and hilly districts of Eastern, Central and Western development regions, whereas the increasing pattern was found in all the districts from Terai and almost all the districts of the Mid- and Far-western region of Nepal including three districts in Kathmandu valley. Each new smaller cohort indicated the decreasing fertility in both male and female but the proportion of working age population is increasing. In conclusion, three main inter-census population changes were found. The first is decreasing new cohorts in majority of the districts, the second one is increasing working age population, but absence of young adult male in some districts, and the last one is beginning of an ageing population. In conclusion, the age-sex distribution varied substantially in both Thailand and Nepal. Based on the results obtained from first and second part of the study, the variations were explained well by three-factor models. The method used in this study is straightforward and the novel concept of using factor as a basis for clustering provinces is applicable to the further demographic studies. Inter-census population change also varied between districts in Nepal. Fertility and migration were the main components responsible for such variation. It is believed that the results from this study pertaining to population dynamics would greatly contribute to population programs. āļāļēāļĢāđ€āļ›āļĨāļĩāđˆāļĒāļ™āđāļ›āļĨāļ‡āļ—āļēāļ‡āļ”āđ‰āļēāļ™āļ›āļĢāļ°āļŠāļēāļāļĢāļĻāļēāļŠāļ•āļĢāđŒāļ‚āļ­āļ‡āļ›āļĢāļ°āđ€āļ—āļĻāđ„āļ—āļĒāļ­āļĒāļđāđˆāđƒāļ™āļĢāļ°āļĒāļ°āļ„āļ‡āļ—āļĩāđˆāđƒāļ™āļĢāļ°āļ”āļąāļšāļ•āđˆāļģ (low stationary phase) āđāļĨāļ°āļāļēāļĢāđ€āļ›āļĨāļĩāđˆāļĒāļ™āđāļ›āļĨāļ‡āļ—āļēāļ‡āļ”āđ‰āļēāļ™āļ›āļĢāļ°āļŠāļēāļāļĢāļĻāļēāļŠāļ•āļĢāđŒāļ‚āļ­āļ‡āļ›āļĢāļ°āđ€āļ—āļĻāđ€āļ™āļ›āļēāļĨāļ­āļĒāļđāđˆāđƒāļ™āļĢāļ°āļĒāļ°āļ›āļĨāļēāļĒāļ‚āļ­āļ‡āļāļēāļĢāļ‚āļĒāļēāļĒāļ•āļąāļ§ (late expanding phase) āļ„āļ§āļēāļĄāļ™āđˆāļēāļˆāļ°āđ€āļ›āđ‡āļ™āļāļēāļĢāđ€āļ›āļĨāļĩāđˆāļĒāļ™āđāļ›āļĨāļ‡āļ‚āļ­āļ‡āļ›āļĢāļ°āļŠāļēāļāļĢāđƒāļ™āļ­āļ™āļēāļ„āļ•āļ‚āļķāđ‰āļ™āļ­āļĒāļđāđˆāļāļąāļšāļ­āļēāļĒāļļāđāļĨāļ°āđ€āļžāļĻāļ‚āļ­āļ‡āļ›āļĢāļ°āļŠāļēāļāļĢāđƒāļ™āļ›āļąāļˆāļˆāļļāļšāļąāļ™āđ€āļ›āđ‡āļ™āļŦāļĨāļąāļ āļ”āļąāļ‡āļ™āļąāđ‰āļ™āļ§āļīāļ—āļĒāļēāļ™āļīāļžāļ™āļ˜āđŒāđ€āļĨāđˆāļĄāļ™āļĩāđ‰āļĄāļĩāļ§āļąāļ•āļ–āļļāļ›āļĢāļ°āļŠāļ‡āļ„āđŒāđ€āļžāļ·āđˆāļ­āļ›āļĢāļ°āļĒāļļāļāļ•āđŒāđƒāļŠāđ‰āļāļēāļĢāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāđ€āļŠāļīāļ‡āļ›āļąāļˆāļˆāļąāļĒ (Factor Analysis) āđƒāļ™āļāļēāļĢāļˆāļąāļ”āļāļĨāļļāđˆāļĄāļ›āļĢāļ°āļŠāļēāļāļĢāļ‚āļ­āļ‡āđāļ•āđˆāļĨāļ°āļˆāļąāļ‡āļŦāļ§āļąāļ”āđāļĨāļ°āļ­āļģāđ€āļ āļ­ āļ—āļĩāđˆāļ‚āļķāđ‰āļ™āļāļąāļšāļāļēāļĢāļāļĢāļ°āļˆāļēāļĒāļ‚āļ­āļ‡āļ›āļĢāļ°āļŠāļēāļāļĢāļ•āļēāļĄāļ­āļēāļĒāļļāđāļĨāļ°āđ€āļžāļĻāļ‚āļ­āļ‡āļ›āļĢāļ°āđ€āļ—āļĻāđ„āļ—āļĒāđāļĨāļ°āđ€āļ™āļ›āļēāļĨ āļŠāļ–āļīāļ•āļīāļ—āļĩāđˆāđƒāļŠāđ‰āđƒāļ™āļāļēāļĢāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒ āđ„āļ”āđ‰āđāļāđˆ āļāļēāļĢāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāđ€āļŠāļīāļ‡āļžāļĢāļĢāļ“āļ™āļē āļāļēāļĢāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāđ€āļŠāļīāļ‡āđ€āļ›āļĢāļĩāļĒāļšāđ€āļ—āļĩāļĒāļš āļ‹āļķāđˆāļ‡āļĢāļ§āļĄāļ–āļķāļ‡āļ§āļīāļ˜āļĩāļāļēāļĢāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāļŦāļĨāļēāļĒāļ›āļąāļˆāļˆāļąāļĒ āđ€āļĢāļĩāļĒāļāļ§āđˆāļē āļāļēāļĢāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāđ€āļŠāļīāļ‡āļ›āļąāļˆāļˆāļąāļĒ āļ—āļĩāđˆāļ›āļĢāļ°āļĒāļļāļāļ•āđŒāđƒāļŠāđ‰āļāļąāļšāļ‚āđ‰āļ­āļĄāļđāļĨāļ›āļĢāļ°āļŠāļēāļāļĢāļĻāļēāļŠāļ•āļĢāđŒ āļ§āļīāļ—āļĒāļēāļ™āļīāļžāļ™āļ˜āđŒāļ‰āļšāļąāļšāļ™āļĩāđ‰āļ›āļĢāļ°āļāļ­āļšāđ„āļ›āļ”āđ‰āļ§āļĒāļŠāļēāļĄāļŠāđˆāļ§āļ™āļ”āļąāļ‡āļ•āđˆāļ­āđ„āļ›āļ™āļĩāđ‰ āļŠāđˆāļ§āļ™āđāļĢāļāļ‚āļ­āļ‡āļāļēāļĢāļĻāļķāļāļĐāļēāļĄāļĩāļ§āļąāļ•āļ–āļļāļ›āļĢāļ°āļŠāļ‡āļ„āđŒāđ€āļžāļ·āđˆāļ­āļ›āļĢāļ°āļĒāļļāļāļ•āđŒāđƒāļŠāđ‰āļ§āļīāļ˜āļĩāļāļēāļĢāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāđ€āļŠāļīāļ‡āļ›āļąāļˆāļˆāļąāļĒāđƒāļ™āļāļēāļĢāļˆāļąāļ”āļāļĨāļļāđˆāļĄāļ›āļĢāļ°āļŠāļēāļāļĢāđƒāļ™āļ›āļĢāļ°āđ€āļ—āļĻāđ„āļ—āļĒāđƒāļ™āđāļ•āđˆāļĨāļ°āļˆāļąāļ‡āļŦāļ§āļąāļ”āļ•āļēāļĄāļāļēāļĢāļāļĢāļ°āļˆāļēāļĒāļ‚āļ­āļ‡āļ­āļēāļĒāļļāđāļĨāļ°āđ€āļžāļĻ āļ‚āđ‰āļ­āļĄāļđāļĨāļ›āļĢāļ°āļāļ­āļšāđ„āļ›āļ”āđ‰āļ§āļĒāļˆāļģāļ™āļ§āļ™āļ›āļĢāļ°āļŠāļēāļāļĢāđƒāļ™āđāļ•āđˆāļĨāļ°āļāļĨāļļāđˆāļĄāļ­āļēāļĒāļļāđ‚āļ”āļĒāđāļšāđˆāļ‡āđ€āļ›āđ‡āļ™āļāļĨāļļāđˆāļĄāļ­āļēāļĒāļļāļĨāļ° 5 āļ›āļĩ āđ€āļžāļĻ āđāļĨāļ°āļˆāļąāļ‡āļŦāļ§āļąāļ” āļ‹āļķāđˆāļ‡āļĄāļĩāļ—āļąāđ‰āļ‡āļŦāļĄāļ” 76 āļˆāļąāļ‡āļŦāļ§āļąāļ” āļ—āļąāđ‰āļ‡āļ™āļĩāđ‰āļˆāļąāļ”āļāļēāļĢāļ‚āđ‰āļ­āļĄāļđāļĨāļ”āđ‰āļ§āļĒāļāļēāļĢāļ›āļĢāļ°āļĄāļēāļ“āļ„āđˆāļēāđƒāļ™āļŠāđˆāļ§āļ‡āļ”āđ‰āļ§āļĒāđ€āļŠāđ‰āļ™āđ‚āļ„āđ‰āļ‡āļ›āļĢāļ°āđ€āļ āļ— spline āļœāļĨāļˆāļēāļāļāļēāļĢāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāđ€āļŠāļīāļ‡āļ›āļąāļˆāļˆāļąāļĒāļŠāļēāļĄāļēāļĢāļ–āļˆāļąāļ”āļāļĨāļļāđˆāļĄāļ›āļĢāļ°āļŠāļēāļāļĢāļ‚āļ­āļ‡āļ›āļĢāļ°āđ€āļ—āļĻāđ„āļ—āļĒāđ„āļ”āđ‰āļŠāļēāļĄāļāļĨāļļāđˆāļĄāļ—āļĩāđˆāļĄāļĩāļĢāļđāļ›āđāļšāļšāļ—āļĩāđˆāđāļ•āļāļ•āđˆāļēāļ‡āļāļąāļ™ āļ—āļąāđ‰āļ‡āļ™āļĩāđ‰āļŠāļēāļĄāļēāļĢāļ–āļ­āļ˜āļīāļšāļēāļĒāļĢāļđāļ›āđāļšāļš (pattern) āļ‚āļ­āļ‡āļ›āļĢāļ°āļŠāļēāļāļĢāļ•āļēāļĄāļāļēāļĢāļāļĢāļ°āļˆāļēāļĒāļ‚āļ­āļ‡āļ­āļēāļĒāļļāđāļĨāļ°āđ€āļžāļĻ āļžāļšāļ§āđˆāļēāļˆāļģāļ™āļ§āļ™ 27 āļˆāļąāļ‡āļŦāļ§āļąāļ”āļ—āļēāļ‡āļ āļēāļ„āđƒāļ•āđ‰āđāļĨāļ°āļ āļēāļ„āļ•āļ°āļ§āļąāļ™āļ­āļ­āļāđ€āļ‰āļĩāļĒāļ‡āđ€āļŦāļ™āļ·āļ­āļ‚āļ­āļ‡āļ›āļĢāļ°āđ€āļ—āļĻāđ„āļ—āļĒ āļ‹āļķāđˆāļ‡āļŠāđˆāļ§āļ™āđƒāļŦāļāđˆāļĄāļĩāļžāļĢāļĄāđāļ”āļ™āļ•āļīāļ”āļ•āđˆāļ­āļāļąāļšāļ›āļĢāļ°āđ€āļ—āļĻāļžāļĄāđˆāļē āļāļąāļĄāļžāļđāļŠāļē āđāļĨāļ°āļĄāļēāđ€āļĨāđ€āļ‹āļĩāļĒ āļĄāļĩāļĢāļđāļ›āđāļšāļšāļāļēāļĢāļāļĢāļ°āļˆāļēāļĒāļ‚āļ­āļ‡āļ›āļĢāļ°āļŠāļēāļāļĢāļ•āļēāļĄāļĄāļēāļ•āļĢāļāļēāļ™ (classical pattern) āļŠāđˆāļ§āļ™āļ›āļĢāļ°āļŠāļēāļāļĢāđƒāļ™āļˆāļąāļ‡āļŦāļ§āļąāļ”āļ āļēāļ„āļāļĨāļēāļ‡āđāļĨāļ°āļ āļđāđ€āļāđ‡āļ•āļŠāđˆāļ§āļ™āđƒāļŦāļāđˆāļĄāļĩāļĢāļđāļ›āđāļšāļšāļāļēāļĢāļāļĢāļ°āļˆāļēāļĒāļ‚āļ­āļ‡āļ›āļĢāļ°āļŠāļēāļāļĢāļ—āļĩāđˆāļ„āļĨāđ‰āļēāļĒāļāļąāļ™ āļ‹āļķāđˆāļ‡āļĄāļĩāļˆāļģāļ™āļ§āļ™āļ›āļĢāļ°āļŠāļēāļāļĢāļŠāļđāļ‡āļŠāļļāļ”āđƒāļ™āļāļĨāļļāđˆāļĄāļ­āļēāļĒāļļāļ—āļĩāđˆāđ€āļ›āđ‡āļ™āđ€āļĒāļēāļ§āļŠāļ™ āđƒāļ™āļ—āļēāļ‡āļāļĨāļąāļšāļāļąāļ™āļˆāļąāļ‡āļŦāļ§āļąāļ”āļ—āļēāļ‡āļ āļēāļ„āđ€āļŦāļ™āļ·āļ­āļˆāļģāļ™āļ§āļ™āļ›āļĢāļ°āļŠāļēāļāļĢāļŠāđˆāļ§āļ™āđƒāļŦāļāđˆāļĨāļ”āļĨāļ‡āđƒāļ™āļāļĨāļļāđˆāļĄāļ­āļēāļĒāļļāļ—āļĩāđˆāđ€āļ›āđ‡āļ™āđ€āļĒāļēāļ§āļŠāļ™ āļŠāļĢāļļāļ›āđ„āļ”āđ‰āļ§āđˆāļēāļāļēāļĢāļāļĢāļ°āļˆāļēāļĒāļ‚āļ­āļ‡āļ›āļĢāļ°āļŠāļēāļāļĢāđƒāļ™āļ›āļĢāļ°āđ€āļ—āļĻāđ„āļ—āļĒāđ„āļĄāđˆāđ„āļ”āđ‰āļĄāļĩāļŠāļąāļ”āļŠāđˆāļ§āļ™āļ—āļĩāđˆāđ€āļŦāļĄāļ·āļ­āļ™āļāļąāļ™āļ—āļąāđˆāļ§āļ›āļĢāļ°āđ€āļ—āļĻ āđāļĨāļ°āļāļēāļĢāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāđ€āļŠāļīāļ‡āļ›āļąāļˆāļˆāļąāļĒāļŠāļēāļĄāļēāļĢāļ–āļ›āļĢāļ°āļĄāļēāļ“āļ„āļ§āļēāļĄāđāļ›āļĢāļ›āļĢāļ§āļ™āļ‚āļ­āļ‡āļ›āļĢāļ°āļŠāļēāļāļĢāđ„āļ”āđ‰āļ­āļĒāđˆāļēāļ‡āđ€āļŦāļĄāļēāļ°āļŠāļĄ āđāļĨāļ°āļŠāļēāļĄāļēāļĢāļ–āļˆāļąāļ”āļāļĨāļļāđˆāļĄāļ‚āļ­āļ‡āļ›āļĢāļ°āļŠāļēāļāļĢāđƒāļ™āđāļ•āđˆāļĨāļ°āļˆāļąāļ‡āļŦāļ§āļąāļ”āđ„āļ”āđ‰āļŠāļēāļĄāļāļĨāļļāđˆāļĄ āļŠāđˆāļ§āļ™āļ—āļĩāđˆāļŠāļ­āļ‡āļ‚āļ­āļ‡āļāļēāļĢāļĻāļķāļāļĐāļēāđƒāļŠāđ‰āļ‚āđ‰āļ­āļĄāļđāļĨāļˆāļēāļāļāļēāļĢāļŠāļģāļĄāļ°āđ‚āļ™āļ›āļĢāļ°āļŠāļēāļāļĢāļ›āļĩ āļž.āļĻ. 2554 āļ›āļĢāļ°āđ€āļ—āļĻāđ€āļ™āļ›āļēāļĨ āļāļēāļĢāļĻāļķāļāļĐāļēāļ™āļĩāđ‰āđ€āļ›āđ‡āļ™āļāļēāļĢāļˆāļąāļ”āļāļĨāļļāđˆāļĄāļ›āļĢāļ°āļŠāļēāļāļĢāđƒāļ™āđāļ•āđˆāļĨāļ°āļ­āļģāđ€āļ āļ­āļ‚āļ­āļ‡āļ›āļĢāļ°āđ€āļ—āļĻāđ€āļ™āļ›āļēāļĨ āļ‹āļķāđˆāļ‡āļ‚āļķāđ‰āļ™āļ­āļĒāļđāđˆāļāļąāļšāļĢāļđāļ›āđāļšāļšāđ‚āļ„āļĢāļ‡āļŠāļĢāđ‰āļēāļ‡āļ‚āļ­āļ‡āļ­āļēāļĒāļļāđāļĨāļ°āđ€āļžāļĻāļ”āđ‰āļ§āļĒāļ§āļīāļ˜āļĩāļāļēāļĢāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāđ€āļŠāļīāļ‡āļ›āļąāļˆāļˆāļąāļĒ āđ€āļžāļ·āđˆāļ­āļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāļ›āļĢāļ°āļŠāļēāļāļĢāļ­āļēāļĒāļļāļĢāļēāļĒāļ›āļĩ (single-year) āļ—āļĩāđˆāļ›āļĢāļąāļšāđƒāļŦāđ‰āđ€āļĢāļĩāļĒāļšāļ”āđ‰āļ§āļĒāļ§āļīāļ˜āļĩ spline āđāļĒāļāļ•āļēāļĄāđ€āļžāļĻāđāļĨāļ°āļ­āļģāđ€āļ āļ­ āļœāļĨāļˆāļēāļāļāļēāļĢāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāđ€āļŠāļīāļ‡āļ›āļąāļˆāļˆāļąāļĒ āļ•āļąāļ§āđāļšāļšāļ—āļĩāđˆāļāļĨāļĄāļāļĨāļ·āļ™āļāļąāļšāļ‚āđ‰āļ­āļĄāļđāļĨāļ›āļĢāļ°āļŠāļēāļāļĢāđƒāļ™āļ›āļĢāļ°āđ€āļ—āļĻāđ€āļ™āļ›āļēāļĨāļĄāļēāļāļ—āļĩāđˆāļŠāļļāļ” āļ„āļ·āļ­ āļ•āļąāļ§āđāļšāļšāļ—āļĩāđˆāļˆāļąāļ”āļ›āļąāļˆāļˆāļąāļĒāđ€āļ›āđ‡āļ™ 3 āļāļĨāļļāđˆāļĄ āļ‹āļķāđˆāļ‡āļ­āļ˜āļīāļšāļēāļĒāļ–āļķāļ‡āļĢāļđāļ›āđāļšāļšāļāļēāļĢāļāļĢāļ°āļˆāļēāļĒ 3 āļĢāļđāļ›āđāļšāļšāļ•āļēāļĄāļĨāļąāļāļĐāļ“āļ°āļ‚āļ­āļ‡āļāļēāļĢāļāļĢāļ°āļˆāļēāļĒāļ‚āļ­āļ‡āļ›āļĢāļ°āļŠāļēāļāļĢāļ•āļēāļĄāļ­āļēāļĒāļļāđāļĨāļ°āđ€āļžāļĻ āļ—āļąāđ‰āļ‡āļ™āļĩāđ‰āļžāļšāļ§āđˆāļēāļāļĨāļļāđˆāļĄāļ­āļģāđ€āļ āļ­āļˆāļģāļ™āļ§āļ™ 23, 17 āđāļĨāļ° 5 āļ­āļģāđ€āļ āļ­āļĄāļĩāļ„āļ§āļēāļĄāļŠāļąāļĄāļžāļąāļ™āļ˜āđŒāļāļąāļšāļ›āļąāļˆāļˆāļąāļĒāđ€āļ”āļĩāļĒāļ§āļ„āļ·āļ­āļ›āļąāļˆāļˆāļąāļĒāļ—āļĩāđˆāļŦāļ™āļķāđˆāļ‡ āļŠāļ­āļ‡ āđāļĨāļ°āļŠāļēāļĄ āļ•āļēāļĄāļĨāļģāļ”āļąāļš āđāļĨāļ°āļžāļšāļ§āđˆāļēāļˆāļģāļ™āļ§āļ™ 30 āļ­āļģāđ€āļ āļ­āļĄāļĩāļ„āļ§āļēāļĄāļŠāļąāļĄāļžāļąāļ™āļ˜āđŒāļāļąāļšāļŠāļ­āļ‡āļ›āļąāļˆāļˆāļąāļĒāļ‚āļķāđ‰āļ™āđ„āļ› āļŠāļĢāļļāļ›āđ„āļ”āđ‰āļ§āđˆāļēāđ‚āļ„āļĢāļ‡āļŠāļĢāđ‰āļēāļ‡āļ‚āļ­āļ‡āļ­āļēāļĒāļļāđāļĨāļ°āđ€āļžāļĻāđƒāļ™āļ›āļĢāļ°āđ€āļ—āļĻāđ€āļ™āļ›āļēāļĨāđƒāļ™āļ›āļĩ āļž.āļĻ. 2554 āļĄāļĩāļ„āļ§āļēāļĄāđāļ•āļāļ•āđˆāļēāļ‡āļāļąāļ™āļ­āļĒāđˆāļēāļ‡āļĄāļēāļāđƒāļ™āđāļ•āđˆāļĨāļ°āļ­āļģāđ€āļ āļ­āļ—āļĩāđˆāļĄāļĩāļ„āļ§āļēāļĄāļ„āļ§āļēāļĄāđāļ•āļāļ•āđˆāļēāļ‡āļāļąāļ™ āđāļĨāļ°āļ•āļąāļ§āđāļšāļšāđ€āļŠāļīāļ‡āļ›āļąāļˆāļˆāļąāļĒāļ—āļąāđ‰āļ‡āļŠāļēāļĄāļāļĨāļļāđˆāļĄāļŠāļēāļĄāļēāļĢāļ–āļ­āļ˜āļīāļšāļēāļĒāļ„āļ§āļēāļĄāđāļ›āļĢāļ›āļĢāļ§āļ™āļ‚āļ­āļ‡āļ‚āđ‰āļ­āļĄāļđāļĨāđ„āļ”āđ‰āļ­āļĒāđˆāļēāļ‡āđ€āļŦāļĄāļēāļ°āļŠāļĄ āļŠāđˆāļ§āļ™āļ—āļĩāđˆāļŠāļēāļĄ āļ„āļ·āļ­ āļāļēāļĢāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāļāļēāļĢāđ€āļ›āļĨāļĩāđˆāļĒāļ™āđāļ›āļĨāļ‡āļĢāļ°āļŦāļ§āđˆāļēāļ‡āļ›āļĩāļŠāļģāļĄāļ°āđ‚āļ™āļ›āļĢāļ°āļŠāļēāļāļĢ (inter-census) āđƒāļ™āļ›āļĢāļ°āđ€āļ—āļĻāđ€āļ™āļ›āļēāļĨ āđ‚āļ”āļĒāđƒāļŠāđ‰āļ‚āđ‰āļ­āļĄāļđāļĨāļāļēāļĢāļŠāļģāļĢāļ§āļˆāļŠāļģāļĄāļ°āđ‚āļ™āļ›āļĢāļ°āļŠāļēāļāļĢāļ›āļĢāļ°āđ€āļ—āļĻāđ€āļ™āļ›āļēāļĨāļ›āļĩ āļž.āļĻ. 2544 āđāļĨāļ° 2554 āļāļēāļĢāļĻāļķāļāļĐāļēāđ€āļŠāļīāļ‡āļžāļĢāļĢāļ“āļ™āļēāđƒāļ™āļ„āļĢāļąāđ‰āļ‡āļ™āļĩāđ‰āļĄāļĩāļ§āļąāļ•āļ–āļļāļ›āļĢāļ°āļŠāļ‡āļ„āđŒāđ€āļžāļ·āđˆāļ­āļŠāļĢāļļāļ›āļ„āļ§āļēāļĄāđāļ›āļĢāļ›āļĢāļ§āļ™āđƒāļ™āļāļēāļĢāđ€āļ›āļĨāļĩāđˆāļĒāļ™āđāļ›āļĨāļ‡āļĢāļ°āļŦāļ§āđˆāļēāļ‡āļ›āļĩāļŠāļģāļĄāļ°āđ‚āļ™āļ›āļĢāļ°āļŠāļēāļāļĢāđƒāļ™āļĢāļ°āļ”āļąāļšāļ­āļģāđ€āļ āļ­ āđāļĒāļāļ•āļēāļĄāļāļĨāļļāđˆāļĄāļ­āļēāļĒāļļāđāļĨāļ°āđ€āļžāļĻ āđāļĨāļ°āļŠāļģāļĢāļ§āļˆāļ­āļ‡āļ„āđŒāļ›āļĢāļ°āļāļ­āļšāļ—āļĩāđˆāđ€āļ›āđ‡āļ™āđ„āļ›āđ„āļ”āđ‰āļ‚āļ­āļ‡āļāļēāļĢāđ€āļ›āļĨāļĩāđˆāļĒāļ™āđāļ›āļĨāļ‡āđ€āļŦāļĨāđˆāļēāļ™āļĩāđ‰ āļāļēāļĢāļˆāļąāļ”āļāļĨāļļāđˆāļĄāļ‚āļ­āļ‡āļ›āļĢāļ°āļŠāļēāļāļĢāđāļ•āđˆāļĨāļ°āļ­āļģāđ€āļ āļ­āļ‚āļķāđ‰āļ™āļ­āļĒāļđāđˆāļāļąāļšāļˆāļģāļ™āļ§āļ™āđāļĨāļ°āļĢāđ‰āļ­āļĒāļĨāļ°āļ‚āļ­āļ‡āļāļēāļĢāđ€āļ›āļĨāļĩāđˆāļĒāļ™āđāļ›āļĨāļ‡āļĢāļ°āļŦāļ§āđˆāļēāļ‡āļ›āļĩāļŠāļģāļĄāļ°āđ‚āļ™āļ›āļĢāļ°āļŠāļēāļāļĢ āđāļĨāļ°āļ™āļģāđ€āļŠāļ™āļ­āļ‚āđ‰āļ­āļĄāļđāļĨāļ”āđ‰āļ§āļĒāđāļœāļ™āļ—āļĩāđˆ āļ—āļąāđ‰āļ‡āļ™āļĩāđ‰āļ›āļĢāļ°āļŠāļēāļāļĢāļ­āļēāļĒāļļāļĢāļēāļĒāļ›āļĩ (single year age population) āļŠāļĢāđ‰āļēāļ‡āļāļĢāļēāļŸāļŠāļģāļŦāļĢāļąāļšāļāļēāļĢāļ›āļĢāļ°āļĄāļēāļ“āļ„āđˆāļēāđƒāļ™āļŠāđˆāļ§āļ‡āļ”āđ‰āļ§āļĒāđ€āļŠāđ‰āļ™āđ‚āļ„āđ‰āļ‡āļ›āļĢāļ°āđ€āļ āļ— spline āļŠāļģāļŦāļĢāļąāļšāļ­āļēāļĒāļļāļĢāļēāļĒāļ›āļĩāļ‚āļ­āļ‡āļ›āļĢāļ°āļŠāļēāļāļĢ āđāļĒāļāļ•āļēāļĄāļ­āļģāđ€āļ āļ­āļ—āļĩāđˆāļĄāļĩāļ„āđˆāļēāļĢāđ‰āļ­āļĒāļĨāļ°āļĢāļ°āļŦāļ§āđˆāļēāļ‡āļ›āļĩāļŠāļģāļĄāļ°āđ‚āļ™āļ›āļĢāļ°āļŠāļēāļāļĢāļ—āļĩāđˆāđ€āļ›āđ‡āļ™āļ„āđˆāļēāļĨāļšāđāļĨāļ°āļšāļ§āļāļ‚āļ­āļ‡āđƒāļ™āđāļ•āđˆāļĨāļ°āđ€āļžāļĻ āļ­āļģāđ€āļ āļ­āđƒāļ™āļŠāļēāļĄāļ­āļąāļ™āļ”āļąāļšāđāļĢāļāļ—āļĩāđˆāļĄāļĩāļĢāđ‰āļ­āļĒāļĨāļ°āļ‚āļ­āļ‡āļ›āļĢāļ°āļŠāļēāļāļĢāđ€āļžāļīāđˆāļĄāļ‚āļķāđ‰āļ™āļŠāļđāļ‡ āļ„āļ·āļ­ āļāļēāļāļĄāļēāļ“āļ‘āļļ (Kathmandu) 61.23% āļĨāļēāļĨāļīāļ•āđ€āļ›āļ­āļĢāđŒ (Lalitpur) 38.59% āđāļĨāļ° āļšāļąāļ„āļ•āļēāđ€āļ›āļ­āļĢāđŒ (Bhaktapur) 35.12% āđƒāļ™āļ‚āļ“āļ°āļ—āļĩāđˆāļŠāļēāļĄāļ­āļąāļ™āļ”āļąāļšāđāļĢāļāļ‚āļ­āļ‡āļ­āļģāđ€āļ āļ­āļ—āļĩāđˆāļĄāļĩāļ›āļĢāļ°āļŠāļēāļāļĢāļĨāļ”āļĨāļ‡āļ­āļĒāđˆāļēāļ‡āļĢāļ§āļ”āđ€āļĢāđ‡āļ§ āļ„āļ·āļ­ āļĄāļēāļ™āļąāļ‡ (Manang) -31.80% āļ„āļ­āļ•āļąāļ‡ (Khotang) -10.84% āđāļĨāļ° āļĄāļļāļŠāļ•āļąāļ‡ (Mustang) -10.21% āļĢāļđāļ›āđāļšāļšāļ—āļĩāđˆāļĄāļĩāļāļēāļĢāļĨāļ”āļĨāļ‡āļ‚āļ­āļ‡āļ›āļĢāļ°āļŠāļēāļāļĢ āļžāļšāđƒāļ™āļ­āļģāđ€āļ āļ­āļ—āļĩāđˆāļ­āļĒāļđāđˆāđƒāļ™āđ€āļ‚āļ•āļ āļđāđ€āļ‚āļē āđāļĨāļ°āđ€āļ™āļīāļ™āđ€āļ‚āļēāđƒāļ™āļ āļēāļ„āļ•āļ°āļ§āļąāļ™āļ­āļ­āļ āļ āļēāļ„āļāļĨāļēāļ‡āđāļĨāļ°āđ€āļ‚āļ•āļžāļ·āđ‰āļ™āļ—āļĩāđˆāļāļēāļĢāļžāļąāļ’āļ™āļēāļ āļēāļ„āļ•āļ°āļ§āļąāļ™āļ•āļ āđƒāļ™āļ‚āļ“āļ°āļ—āļĩāđˆāļĢāļđāļ›āđāļšāļšāļāļēāļĢāđ€āļžāļīāđˆāļĄāļ‚āļķāđ‰āļ™āļŠāļēāļĄāļēāļĢāļ–āļžāļšāđ„āļ”āđ‰āđƒāļ™āļ—āļļāļāļ­āļģāđ€āļ āļ­āļ‚āļ­āļ‡āļžāļ·āđ‰āļ™āļ—āļĩāđˆāđ€āļ—āļ­āļĢāļēāļĒ (Terai) āđāļĨāļ°āđ€āļāļ·āļ­āļšāļ—āļļāļāļ­āļģāđ€āļ āļ­āđƒāļ™āļ āļēāļ„āļāļĨāļēāļ‡āđāļĨāļ°āļžāļ·āđ‰āļ™āļ—āļĩāđˆāļŦāđˆāļēāļ‡āđ„āļāļĨāđƒāļ™āļ āļēāļ„āļ•āļ°āļ§āļąāļ™āļ•āļāļ‚āļ­āļ‡āļ›āļĢāļ°āđ€āļ—āļĻāđ€āļ™āļ›āļēāļĨ āļĢāļ§āļĄāļ–āļķāļ‡āļŠāļēāļĄāļ­āļģāđ€āļ āļ­āđƒāļ™āļŦāļļāļšāđ€āļ‚āļēāļāļēāļāļĄāļēāļ“āļ‘āļļ (Kathmandu) āļ›āļĢāļ°āļŠāļēāļāļĢāļāļĨāļļāđˆāļĄāđƒāļŦāļĄāđˆāļ—āļĩāđˆāļĄāļĩāļ‚āļ™āļēāļ”āđ€āļĨāđ‡āļāđƒāļ™āđāļ•āđˆāļĨāļ°āļāļĨāļļāđˆāļĄ āļŠāļĩāđ‰āđƒāļŦāđ‰āđ€āļŦāđ‡āļ™āļ–āļķāļ‡āļ­āļąāļ•āļĢāļēāļāļēāļĢāđ€āļāļīāļ”āļ—āļĩāđˆāļĨāļ”āļĨāļ‡āļ—āļąāđ‰āļ‡āđƒāļ™āđ€āļžāļĻāļŠāļēāļĒāđāļĨāļ°āļŦāļāļīāļ‡ āđƒāļ™āļ‚āļ“āļ°āļ—āļĩāđˆāļŠāļąāļ”āļŠāđˆāļ§āļ™āļ‚āļ­āļ‡āļ›āļĢāļ°āļŠāļēāļāļĢāđƒāļ™āļāļĨāļļāđˆāļĄāļ­āļēāļĒāļļāļ§āļąāļĒāļ—āļģāļ‡āļēāļ™āļāļĨāļąāļšāđ€āļžāļīāđˆāļĄāļ‚āļķāđ‰āļ™ āļŠāļĢāļļāļ›āđ„āļ”āđ‰āļ§āđˆāļē āļāļēāļĢāđ€āļ›āļĨāļĩāđˆāļĒāļ™āđāļ›āļĨāļ‡āļĢāļ°āļŦāļ§āđˆāļēāļ‡āļ›āļĩāļŠāļģāļĄāļ°āđ‚āļ™āļ›āļĢāļ°āļŠāļēāļāļĢāļĄāļĩāļŠāļēāļĄāđāļšāļš āđāļšāļšāļ—āļĩāđˆāļŦāļ™āļķāđˆāļ‡āļ„āļ·āļ­ āļāļēāļĢāļĨāļ”āļĨāļ‡āļ‚āļ­āļ‡āļ›āļĢāļ°āļŠāļēāļāļĢāļāļĨāļļāđˆāļĄāđƒāļŦāļĄāđˆ (new cohort) āđƒāļ™āļ­āļģāđ€āļ āļ­āļŠāđˆāļ§āļ™āđƒāļŦāļāđˆ āđāļšāļšāļ—āļĩāđˆāļŠāļ­āļ‡ āļ„āļ·āļ­ āļāļēāļĢāđ€āļžāļīāđˆāļĄāļ‚āļķāđ‰āļ™āļ‚āļ­āļ‡āļ›āļĢāļ°āļŠāļēāļāļĢāļāļĨāļļāđˆāļĄāļ­āļēāļĒāļļāļ§āļąāļĒāļ—āļģāļ‡āļēāļ™ āđāļ•āđˆāļ‚āļēāļ”āđāļ„āļĨāļ™āđ€āļžāļĻāļŠāļēāļĒāļ§āļąāļĒāļœāļđāđ‰āđƒāļŦāļāđˆ (young adult male) āđƒāļ™āļšāļēāļ‡āļ­āļģāđ€āļ āļ­ āđāļĨāļ°āđāļšāļšāļŠāļļāļ”āļ—āđ‰āļēāļĒāļ„āļ·āļ­ āļāļēāļĢāđ€āļĢāļīāđˆāļĄāļĄāļĩāļ›āļĢāļ°āļŠāļēāļāļĢāļ§āļąāļĒāļŠāļĢāļēāđ€āļžāļīāđˆāļĄāļ‚āļķāđ‰āļ™ āļŠāļĢāļļāļ› āļāļēāļĢāļāļĢāļ°āļˆāļēāļĒāļ‚āļ­āļ‡āļ›āļĢāļ°āļŠāļēāļāļĢāļ•āļēāļĄāļ­āļēāļĒāļļāđāļĨāļ°āđ€āļžāļĻāļĄāļĩāļ„āļ§āļēāļĄāđāļ•āļāļ•āđˆāļēāļ‡āļāļąāļ™āļ­āļĒāđˆāļēāļ‡āļĄāļĩāļ™āļąāļĒāļŠāļģāļ„āļąāļāļ—āļąāđ‰āļ‡āđƒāļ™āļ›āļĢāļ°āđ€āļ—āļĻāđ„āļ—āļĒāđāļĨāļ°āļ›āļĢāļ°āđ€āļ—āļĻāđ€āļ™āļ›āļēāļĨ āļˆāļēāļāļœāļĨāļ‚āļ­āļ‡āļāļēāļĢāļĻāļķāļāļĐāļēāđƒāļ™āļŠāđˆāļ§āļ™āļ—āļĩāđˆāļŦāļ™āļķāđˆāļ‡āđāļĨāļ°āļŠāļ­āļ‡ āļžāļšāļ§āđˆāļē āļ•āļąāļ§āđāļšāļšāļ—āļĩāđˆāļˆāļąāļ”āļ›āļąāļˆāļˆāļąāļĒāđ€āļ›āđ‡āļ™āļŠāļēāļĄāļāļĨāļļāđˆāļĄāļ—āļĩāđˆāđ„āļ”āđ‰āļˆāļēāļāļāļēāļĢāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāđ€āļŠāļīāļ‡āļ›āļąāļˆāļˆāļąāļĒāļŠāļēāļĄāļēāļĢāļ–āļ­āļ˜āļīāļšāļēāļĒāļ„āļ§āļēāļĄāđāļ›āļĢāļ›āļĢāļ§āļ™āļ‚āļ­āļ‡āļ‚āđ‰āļ­āļĄāļđāļĨāđ„āļ”āđ‰āļ­āļĒāđˆāļēāļ‡āđ€āļŦāļĄāļēāļ°āļŠāļĄ āļ§āļīāļ˜āļĩāļāļēāļĢāļ—āļĩāđˆāđƒāļŠāđ‰āđƒāļ™āļāļēāļĢāļĻāļķāļāļĐāļēāļ™āļĩāđ‰āļ„āļ·āļ­ āđƒāļŠāđ‰āļŦāļĨāļąāļāļāļēāļĢāđāļĨāļ°āđāļ™āļ§āļ„āļīāļ”āđƒāļŦāļĄāđˆāđ‚āļ”āļĒāļāļēāļĢāđƒāļŠāđ‰āļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāđ€āļŠāļīāļ‡āļ›āļąāļˆāļˆāļąāļĒāđ€āļ›āđ‡āļ™āļžāļ·āđ‰āļ™āļāļēāļ™āđƒāļ™āļāļēāļĢāļˆāļąāļ”āļāļĨāļļāđˆāļĄāļ›āļĢāļ°āļŠāļēāļāļĢāđāļ•āđˆāļĨāļ°āļˆāļąāļ‡āļŦāļ§āļąāļ” āļ‹āļķāđˆāļ‡āļŠāļēāļĄāļēāļĢāļ–āļ™āļģāđ„āļ›āļ›āļĢāļ°āļĒāļļāļāļ•āđŒāđƒāļŠāđ‰āļāļąāļšāļāļēāļĢāļĻāļķāļāļĐāļēāļ—āļēāļ‡āļ”āđ‰āļēāļ™āļ›āļĢāļ°āļŠāļēāļāļĢāļĻāļēāļŠāļ•āļĢāđŒāđƒāļ™āđ‚āļ­āļāļēāļŠāļ•āđˆāļ­āđ„āļ› āļāļēāļĢāđ€āļ›āļĨāļĩāđˆāļĒāļ™āđāļ›āļĨāļ‡āļĢāļ°āļŦāļ§āđˆāļēāļ‡āļ›āļĩāļŠāļģāļĄāļ°āđ‚āļ™āļ›āļĢāļ°āļŠāļēāļāļĢāļĄāļĩāļ„āļ§āļēāļĄāđāļ•āļāļ•āđˆāļēāļ‡āļāļąāļ™āđƒāļ™āđāļ•āđˆāļĨāļ°āļ­āļģāđ€āļ āļ­āļ‚āļ­āļ‡āļ›āļĢāļ°āđ€āļ—āļĻāđ€āļ™āļ›āļēāļĨ āļ­āļąāļ•āļĢāļēāļāļēāļĢāđ€āļāļīāļ”āđāļĨāļ°āļāļēāļĢāļ­āļžāļĒāļžāļĒāđ‰āļēāļĒāļ–āļīāđˆāļ™āđ€āļ›āđ‡āļ™āļ­āļ‡āļ„āđŒāļ›āļĢāļ°āļāļ­āļšāļŦāļĨāļąāļāļ—āļĩāđˆāļĄāļĩāļœāļĨāļ•āđˆāļ­āļ„āļ§āļēāļĄāđāļ›āļĢāļ›āļĢāļ§āļ™āļ‚āļ­āļ‡āļ›āļĢāļ°āļŠāļēāļāļĢ āļœāļĨāļˆāļēāļāļāļēāļĢāļĻāļķāļāļĐāļēāļ„āļĢāļąāđ‰āļ‡āļ™āļĩāđ‰āđ€āļŠāļ·āđˆāļ­āđ„āļ”āđ‰āļ§āđˆāļēāļĄāļĩāļ„āļ§āļēāļĄāđ€āļāļĩāđˆāļĒāļ§āļ‚āđ‰āļ­āļ‡āļāļąāļšāļāļēāļĢāđ€āļ›āļĨāļĩāđˆāļĒāļ™āđāļ›āļĨāļ‡āļ›āļĢāļ°āļŠāļēāļāļĢ āļ”āļąāļ‡āļ™āļąāđ‰āļ™āļˆāļķāļ‡āļŠāļēāļĄāļēāļĢāļ–āļ™āļģāđ„āļ›āļ›āļĢāļ°āļĒāļļāļāļ•āđŒāđƒāļŠāđ‰āđƒāļ™āļāļēāļĢāļ§āļēāļ‡āđāļœāļ™āļ”āđ‰āļēāļ™āļ›āļĢāļ°āļŠāļēāļāļĢāļ•āđˆāļ­āđ„āļ›āđ„āļ”

    Analyzing age-sex structure patterns in Nepal using factor analysis

    No full text
    This study aimed to cluster the districts in Nepal based on the patterns of age-sex structures by applying factor analysis. The population data, which is grouped by 5-year age gap, by sex and by districts, was used. The factor analysis was applied to spline smooth single-year age population by sex and district. A three factor model was best fitted to the data. These three common factors were interpreted as three different patterns based on common characteristics of age and sex distribution. The study found that 23, 17 and 5 districts correlated purely to factor 1, 2 and 3, respectively. Thirty districts were found correlated with two or more factors. In conclusion, the age-sex structure varied substantially between the different districts of Nepal in 2011. The variations were explained well by a three-factor model. The method used in this study is straightforward and applicable to the further demographic study

    Incidence Of Needle Stick Injury Among Proficiency Certificate Level Nursing Students In

    No full text
    Abstract: An academic institution based cross- sectional survey was done to identify the incidence density of needle stick injury among PCL level nursing students. Multi stage sampling method was used to select 407 samples from nursing students studying inside Kathmandu valley. Self administered questionnaire and review the records guideline were used as research tool. Incidence density was calculated by using R software. Out of total participated students, 46.9 % had have needle stick injuries in the past and 44.7 % experienced it more than one time. The overall incidence density was found 5.82/person 1000 days exposure. The incidence density in night shift (6.86) and in second year practicum period (6.91) was found higher than day shift (5.41) and first year (4.21) respectively. Out of total 298 injuries, 67.8 % were happened during medication, 41 % while drawing medicine, 20 % while recapping the needle and 45.1 % at medical ward. Only 46.6 % injuries were reported and prophylaxis was used only in five injuries. However, almost all the students (98.3%) stated that they follow universal precaution but only 28 % practicing no-recapping. Although the curriculum focuses on no recapping, there is a common practice of reusing syringes for the same patient in Nepal. Therefore, students must have to recap the needle. So, it is recommended that content in the curriculum and universal precaution training should be revised in the context of Nepal. Thirty one percent students also stated that needle should recap properly by using one hand technique for the prevention of needle stick injury. It is also recommended to develop standard operating procedure for proper post exposure management of needle stick injury
    corecore