Lifestyle differences between older migrants and non-migrants in 14 European countries using propensity score matching method

Abstract

ObjectivesWe examine the differences in lifestyle between four groups of migrants—first generation of older migrants originating from one of the EU countries, Africa or the Middle East and second-generation older EU migrants—with non-migrants in their country of destination.MethodsWe use wave 5 of the SHARE data. To control for differences in socio-demographic characteristics, cultural factors and duration of stay in country of destination between migrants and non-migrants, we use propensity matching score analysis.ResultsOlder migrants from Southern European countries are more likely to smoke than non-migrants in their country of origin. Older migrants originating from Africa and the Middle East are more likely to smoke than non-migrants in their country of destination. Some groups of second-generation older migrants are more likely to consume alcohol and to have lower levels of physical activity than non-migrants in their country of destination.ConclusionsOur results show that differences in lifestyle between migrants and non-migrants exist, but they are not solely related to their migrant status. Cultural and socio-demographic characteristics also play a role.

Evaluation of the effectiveness of a WHO-5A model based comprehensive tobacco control program among migrant workers in Guangdong, China: a pilot study

“…Great global efforts geared towards smoking cessation have been made, such as the WHO Framework Convention on Tobacco Control approved in 2003, and many countries have made a series of strict tobacco control policies [30][31][32]. Although the global smoking problems have been improved, tobacco control among migrants all around the world is still relatively hard to conduct for various reasons, such as high mobility, high smoking rates, limited education levels, and psychological pressures [10]. Evidence on promoting smoking cessation practices among migrant populations is urgently needed.…”

“…However, the high smoking rate was not a unique problem among Chinese internal migrants, but an international problem [10][11][12]. For instance, a larger scale study in Europe found that migrants were more likely to smoke than non-migrants [10].…”

“…For instance, a larger scale study in Europe found that migrants were more likely to smoke than non-migrants [10]. Another study revealed that the smoking rate in an Indian city was up to 90% among interstate migrant construction workers [11].…”

Social Support Moderates the Association Between Traumatic Life Events and Depression Among Migrant and Nonmigrant Men in Almaty, Kazakhstan

“…A fully latent interaction model was specified and carried out through structural equation modeling (SEM) to examine the effects of traumatic life events and social support on depression. Because of significant differences observed in the bivariate analyses when examining independent and dependent variable scores based upon migrant status, as well as potential lifestyle, cul-tural, and sociodemographic differences that may exist between migrants and nonmigrants based on their different backgrounds and contexts (Arsenijevic & Groot, 2018;Nawrotzki, Hunter, & Dickinson, 2012), we performed multiple-group modeling by migrant status in our analyses. Because of significant differences observed in the bivariate analyses when examining independent and dependent variable scores based upon migrant status, as well as potential lifestyle, cul-tural, and sociodemographic differences that may exist between migrants and nonmigrants based on their different backgrounds and contexts (Arsenijevic & Groot, 2018;Nawrotzki, Hunter, & Dickinson, 2012), we performed multiple-group modeling by migrant status in our analyses.…”

“…The SEM method was particularly advantageous due to its accounting of measurement error, which may lead to improved estimation (Kline, 2016). Because of significant differences observed in the bivariate analyses when examining independent and dependent variable scores based upon migrant status, as well as potential lifestyle, cul-tural, and sociodemographic differences that may exist between migrants and nonmigrants based on their different backgrounds and contexts (Arsenijevic & Groot, 2018;Nawrotzki, Hunter, & Dickinson, 2012), we performed multiple-group modeling by migrant status in our analyses. Latent constructs included traumatic life events, social support, and depression with four, six, and six indicators, respectively (see Figure 1).…”