背景:任何国家的移民人口都是弱势群体,衡量生活满意度的心理人口研究已被用来评估发达国家和发展中国家的移民福祉。然而,南非,随着移民人口的大量涌入,从仇外心理的角度调查了这些热门问题,结果喜忧参半。然而,不,或者很少有研究调查南非移民的生活满意度。这项研究,因此,通过研究南非国内和国际移民人口生活满意度的决定因素,扩展了以前的文献。
方法:我们从2009年至2021年豪登市地区天文台(GCRO)的生活质量(QoL)调查中,以两种方式进行了横断面研究:全样本和性别分层样本。本研究招募了15至49岁的男性和女性移民样本。Cantril的自我锚定阶梯生活满意度量表捕获了他们的生活满意度以及相关的社会人口统计学因素。描述性统计用于人口统计学因素的数据分析。进行了双变量和多变量物流回归分析,以评估移民之间生活满意度的关联和预测因素。国内和国际。
结果:主要发现是生活满意度的性别分布,显示更多的国际移民(男性-66.0%和女性-67.1%)报告有一个繁荣的生活满意度比国内移民(男性-61.7%和女性-61.5%)。皮尔逊相关系数的研究结果表明,个体之间存在显著关联,家庭,和社区因素按移民身份(ρ<0.05)。然而,probit系数显示个体因素(年龄48+:AOR=2.18,95%CI:1.13,3.23,中等/高等教育:AOR=1.1.,95%CI:0.01,1.19)和家庭因素(居住在家庭中的两个人(H/H):AOR=1.05,95%CI:0.50,1.10),和社区因素(国际移民身份:AOR=2.12,95%CI:0.08,2.16)显着增加了按性别划分的移民生活满意度较高的预测几率。有序的logit系数还表明,个人因素(中高收入和拥有健康保险)和家庭因素(接受SASSA社会补助金)预测移民(国内和国际)的生活满意度最高。
结论:我们发现了大量证据表明,house-,社区层面的因素与移民的生活满意度相关。特别是,男性和女性移民的生活满意度模式略有不同,以及南非的移民身份。这些发现可以为政策制定者和从业人员提供有用的信息,以优化移民人口的干预措施,以提高他们的生活满意度。这项研究的证据还呼吁南非政府开始追踪其国民的生活满意度,不管是不是移民。
Migrant populations in any country are a vulnerable group, and psycho-demographic research measuring life satisfaction has been used to assess migrants\' well-being in developed and developing countries. However, South Africa, with its high influx of migrant populations, has investigated these topical concerns from the perspective of xenophobia, with mixed findings. However, no, or very few studies have examined life satisfaction among migrants in South Africa. This study, therefore, extends previous literature by examining the determinants of life satisfaction among South Africa\'s internal and international migrant populations.
We conducted a cross-sectional study from the 2009 to 2021 Gauteng City-Region Observatory (GCRO) Quality of Life (QoL) surveys among migrant populations in two ways: a full sample and a gender-stratified sample. A sample of male and female migrants ranging from 15 to 49 years of age were recruited into this study. Cantril\'s Self-Anchoring Ladder Life Satisfaction scale captured their life satisfaction alongside relevant social demographic factors. Descriptive statistics were applied for the data analysis of the demographic factors. Bivariate and multivariate logistics regression analyses were conducted to assess the associations and the predictive factors of life satisfaction among migrants, both internal and international.
The key findings were the gender distribution of life satisfaction, showing that more international (male - 66.0% and female - 67.1%) migrants reported having a thriving life satisfaction than internal migrants (male - 61.7% and female - 61.5%). Findings from the Pearson correlation coefficient revealed a significant association between the individual, household, and community factors by migrant status (ρ < 0.05). However, the probit coefficients revealed that individual factors (age 48+: AOR = 2.18, 95% CI: 1.13, 3.23, and secondary/higher education: AOR = 1.1., 95% CI: 0.01, 1.19) and household factors (two persons living in households (H/H): AOR = 1.05, 95% CI: 0.50, 1.10), and community factors (international migrant status: AOR = 2.12, 95% CI: 0.08, 2.16) significantly increase the prediction of higher odds of life satisfaction by gender among migrants. The ordered logit coefficients also showed that individual factors (middle and high income and having health insurance) and household factors (receiving SASSA social grant) predicted the highest life satisfaction among migrants (internal and international).
We found substantial evidence that individual-, household-, and community-level factors were associated with life satisfaction among migrants. In particular, the pattern of life satisfaction varied slightly between male and female migrants, as well as with migrant status in South Africa. These findings collectively may provide helpful information for policymakers and practitioners to optimise interventions for migrant populations to improve their life satisfaction. Evidence from this study also calls on the government of South Africa to begin tracking the life satisfaction of its nationals, whether migrants or not.