تغییرپذیری فضایی و زمانی نرخ باروری گروه های ویژه سنی در نواحی روستایی ایران (1385-1395) (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
باروری یک فرآیند جمعیتی کلیدی است که نقش مهمی در پویایی و روندهای جمعیت دارد. کاهش بارروی، به پدیده ای جهانی تبدیل شده است؛ و در اولویت های سیاستی بسیاری از کشورهای جهان قرار گرفته است. با این حال، مطالعات اندکی هستند که به طور مستقیم بر پایه مفاهیم جغرافیایی و بعد فضایی باروری، تمرکز کرده باشند. هدف از این پژوهش بررسی روند تغییرپذیری فضایی و زمانی نرخ باروری گروه های ویژه سنی (ASFRs) زنان روستایی در سال های 1385 و 1395 است. داده های موالید و گروه های سنی زنان(49- 15) روستایی از سرشماری نفوس و مسکن مرکز آمار در دو دوره 1385 و 1395 جمع آوری و از آزمون های موران I سراسری (GMI) و موران محلی با بیز تجربی (LM-EB) برای سنجش خود همبستگی فضایی و کشف الگوهای فضایی نرخ باروری ویژه گروه های سنی در نرم افزار GeoDa استفاده شد. نتایج نشان داد که نرخ باروری گروه های ویژه سنی طی دوره مورد بررسی افزایش یافته است و بیشترین افزایش باروری در گروه سنی 24 -20 ساله رخ داده است. خوشه بندی فضایی نرخ باروری ویژه سنی نشان می دهد در سال 1395 قوی تر و گسترده تر از سال 1385 بوده است. در بین گروه های سنی و در هر دو دوره، گروه سنی 39- 35 سال و 49- 45 سال به ترتیب بیشترین (447/0=GMI1385671/0=GMI1395) و کمترین(07/0=GMI1385 ،198/0=GMI1395) مقدار خودهمبستگی فضایی را داشته اند. همچنین مناطق روستایی جنوب شرق کشور خوشه بندی باروری ویژه سنی بالا را داشته اند. در برخی از گروه های سنی در شرق، شمال شرق، شمال غرب، جنوب غرب و تا حدودی جنوب نیز الگوی بالا- بالا شکل گرفته اند. الگوی بالا- بالا در شمال غرب تنها در گروه سنی 19- 15 سال شکل گرفته است و الگوی پایین- پایین باروری در مناطق روستایی عمدتاً در قسمت های داخلی، شمال و غرب متمرکز شده اند. شناسایی و کشف خوشه های فضایی، زمینه را برای ساخت مفروضات و مدل برای تحقیقات آینده فراهم می کند. بنابراین آنچه در این پژوهش انجام شده است، می تواند بستر مناسب علمی و دقیق برای تحقیقات بنیادین بعدی در حوزه جمعیت و باروری روستایی و توسعه را فراهم می کند.Spatial and Temporal Variation of Age- Specific Fertility Rates Across Rural Areas of Iran (2006-2016)
Fertility is a key demographic process that plays an important role in population dynamics and trends. Fertility decline has become a global phenomenon; also, it has been placed in the policy priorities of many countries in the world. However, there are few studies that have focused directly on the concepts of geography and the spatial dimension of fertility. The purpose of this study is to exploring the spatial and temporal variation in age specific fertility rates (ASFRs) across Iran’s rural areas in 2006 and 2016. Data on births and age groups of rural women (15-49) were collected from the census of the Statistics Center in 2006 and 2016. Global Moran’s I and local Moran with Empirical Bayes (LM-EB) tests were used to measure spatial autocorrelation and discover the ASFRs local patterns. The results show that the fertility rate of age-specific groups has increased and the highest increase in fertility has occurred in the age group of 20-24 years. Spatial patterns of ASFRs shows that autocorrelation in 2016 was stronger and wider than in 2006. Among the age groups and in both periods, the age groups of 35-39 years and 45-49 years had the highest (GMI1385= 0.447; GMI1395= 0.671) and lowest (GMI1385= 0.070; GMI1395= 0.198) spatial autocorrelation, respectively. Rural areas in the southeast of the country have had a strong ASFRs clustering. In some age groups in the east, northeast, southwest and to some extent in the south, a high-high pattern has been formed. The high-high pattern in the northwest is formed only in the age group of 15-19 and the low-low pattern of fertility is mainly concentrated in the interior, north and west areas. Identifying spatial clusters will provide the basis for constructing assumptions and models for future research. Therefore, what has been done in this research can provide a suitable scientific and accurate basis for further basic research in the field of population and rural fertility and development. IntroductionFertility is a key demographic process that plays an important role in population dynamics and trends. In addition to its fluctuations over time, the spatial dimension of fertility can show how it affects population dynamics in a particular region. Identifying and explaining spatial variation of fertility is considered an important component of the subfields of population geography and spatial demography. Reviewing the literature of sources in the field of population geography of Iran also shows that the issue of fertility has been less discussed compared to other population processes including migration. However, a geographic perspective is one of the keys to understanding fertility change.Place or geographical context plays an important role in fertility behavior, so the study of fertility variability reveals the importance of geographic variability or lack thereof. Also, the analysis of spatial variability in fertility helps to understand and predict the dynamics of the regional population and to test the hypotheses related to the general determinants of fertility. This study attempts to investigate the spatial and temporal variability of fertility of age- specific fertility rates (ASFRs) in rural areas. Identifying and discovering spatial and temporal patterns of fertility is important in two aspect. First, identifying spatial and temporal variability of fertility at the regional level can be useful in designing policies and programs to provide social services, education, health, as well as population and development programs. Second, the discovery of spatial and temporal patterns can be used to construct assumptions, test and model in future research. MethodologyThe present study is applied in terms of purpose and exploratory-descriptive in terms of method. In this research, the data related to the results of the census of population and housing were used. The time period is from 2006-2016; the spatial scale in the analysis is the county level. Spatial data exploratory analysis (ESDA) techniques were used to analyze age- specific fertility rates (ASFRs) in rural areas of Iran. There are a variety of techniques for exploratory analysis of spatial data that vary according to the nature of the data. In this study, global Moran’s I (GMI) and local Moran with Empirical Bayes (LM-EB) tests in GeoDa software were used. Due to the importance of age specific fertility rate (ASFR) in this study, this index has been used: Where B is the number of live births of one year in each age group and w is the population of women in the same age group in the same year and a is the corresponding age group of 50 years (49 to 15 years). Results and Discussion The results showed that the ASFRs increased during the study period and the highest increase in fertility occurred in the age group of 20-24 years. The findings of this study show that 1) Spatial clustering of rural ASFRs in 2016 was stronger than in 2006. Among the age groups and in both periods, the age groups of 35-39 years and 45-49 years had the highest and lowest spatial autocorrelation, respectively. 2) In all age groups in the two years studied, rural areas in the southeast of the country had high ASFRs clustering. However, in some age groups in other regions, a high-high pattern has been formed. These include east, northeast, northwest, southwest and to some extent south. The high-high pattern in the northwest is formed only in the age group of 15-19. 3) In the low-low pattern, ASFR in rural areas are mainly concentrated in the center, north and west, however, in the age groups and in terms of time, these patterns have increased or decreased in the mentioned areas. ConclusionIn this study, the spatial and temporal variability of age-specific fertility rates (ASFRs) was investigated using spatial exploratory data analysis (ESDA) techniques for 2006 and 2016.This study is one of the first attempts to analyze the fertility of age groups in rural areas with a spatial approach. Although the identification and discovery of spatial clusters does not provide a causal explanation for the reasons for the formation of fertility patterns, it can provide a basis for constructing assumptions and models for future research. What has been done in this research provides a suitable scientific and accurate basis for further fundamental research in the field of rural fertility and development.
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