The Weight of Migration: Reconsidering Health Selection and Return Migration among Mexicans

While migration plays a key role in shaping the health of Mexican migrants in the US and those in Mexico, contemporary Mexican migration trends may challenge the health selection and return migration hypotheses, two prevailing assumptions of how migration shapes health. Using data from the Mexican Family Life Survey (2002; 2005), we tested these two hypotheses by comparing the cardiometabolic health profiles of (1) Mexico–US future migrants and nonmigrants and (2) Mexico–US return migrants and nonmigrants. First, we found limited evidence for health selection: the cardiometabolic health of Mexico–US future migrants was not measurably better than the health of their compatriots who did not migrate, although migrants differed demographically from nonmigrants. However, return migrants had higher levels of adiposity compared to those who stayed in Mexico throughout their lives; time spent in the US was also associated with obesity and elevated waist circumference. Differences in physical activity and smoking behavior did not mediate these associations. Our findings suggest positive health selection might not drive the favorable health profiles among recent cohorts of Mexican immigrants in the US. However, the adverse health of return migrants with respect to that of nonmigrants underscores the importance of considering the lived experience of Mexican migrants in the US as an important determinant of their health.

Life Course Neighborhood Deprivation Effects on Body Mass Index: Quantifying the Importance of Selective Migration

Neighborhood effects research is plagued by the inability to circumvent selection effects —the process of people sorting into neighborhoods. Data from two British Birth Cohorts, 1958 (ages 16, 23, 33, 42, 55) and 1970 (ages 16, 24, 34, 42), and structural equation modelling, were used to investigate life course relationships between body mass index (BMI) and area deprivation (addresses at each age linked to the closest census 1971–2011 Townsend score [TOWN], re-calculated to reflect consistent 2011 lower super output area boundaries). Initially, models were examined for: (1) area deprivation only, (2) health selection only and (3) both. In the best-fitting model, all relationships were then tested for effect modification by residential mobility by inclusion of interaction terms. For both cohorts, both BMI and area deprivation strongly tracked across the life course. Health selection, or higher BMI associated with higher area deprivation at the next study wave, was apparent at three intervals: 1958 cohort, BMI at age 23 y and TOWN at age 33 y and BMI at age 33 y and TOWN at age 42 y; 1970 cohort, BMI at age 34 y and TOWN at age 42 y, while paths between area deprivation and BMI at the next interval were seen in both cohorts, over all intervals, except for the association between TOWN at age 23 y and BMI at age 33 y in the 1958 cohort. None of the associations varied by moving status. In conclusion, for BMI, selective migration does not appear to account for associations between area deprivation and BMI across the life course.

Socioeconomic position, social mobility, and health selection effects on allostatic load in the United States

The contemporaneous association between higher socioeconomic position and better health is well established. Life course research has also demonstrated a lasting effect of childhood socioeconomic conditions on adult health and well-being. Yet, little is known about the separate health effects of intergenerational mobility—moving into a different socioeconomic position than one’s parents—among early adults in the United States. Most studies on the health implications of mobility rely on cross-sectional datasets, which makes it impossible to differentiate between health selection and social causation effects. In addition, understanding the effects of social mobility on health at a relatively young age has been hampered by the paucity of health measures that reliably predict disease onset. Analysing 4,713 respondents aged 25 to 32 from the National Longitudinal Study of Adolescent Health’s Waves I and IV, we use diagonal reference models to separately identify the effects of socioeconomic origin and destination, as well as social mobility on allostatic load among individuals in the United States. Using a combined measure of educational and occupational attainment, and accounting for individuals’ initial health, we demonstrate that in addition to health gradient among the socially immobile, individuals’ socioeconomic origin and destination are equally important for multi-system physiological dysregulation. Short-range upward mobility also has a positive and significant association with health. After mitigating health selection concerns in our observational data, this effect is observed only among those reporting poor health before experiencing social mobility. Our findings move towards the reconciliation of two theoretical perspectives, confirming the positive effect of upward mobility as predicted by the “rags to riches” perspective, while not contradicting potential costs associated with more extensive upward mobility experiences as predicted by the dissociative thesis.

Living Alone Transitions and Mortality in Older Men and Women

Living alone has been established as a risk factor for mortality, with biopsychosocial mechanisms suggested as plausible. However, it is unclear whether this is due to health selection. We analysed data from 4,888 individuals who participated in both wave 2 (2004-2005) and wave 4 (2008-2009) of the English Longitudinal Study of Ageing. Mortality status was ascertained from linked mortality register data. An association was found between living alone at wave four and mortality (HR: 1·20, 95% CI 1·04–1·38) in a model adjusted for a range of factors. We also found that participants who transitioned into a solo household due to divorce or bereavement had a higher risk of mortality (HR: 1·34, 95% CI 1·01–1·79). Transitioning into a solo household is also associated with mortality and the underlying reason for this transition was found to be important.

Distribution of sickness absence risk across different levels and patterns of drinking: findings from the Stockholm Public Health Cohort

Aim: This study estimated (i) the risk function between different indicators of alcohol use and long-term sickness absence, adjusting for possible confounding factors, (ii) whether the risk function between average volume of consumption and sickness absence is modified by heavy episodic drinking (HED), and (iii) to what extent the risk for sickness absence among abstainers is due to health selection bias. Data and methods: The study was based on data from the Stockholm Public Health Cohort 2006, with an analytical sample of 16,477 respondents aged 18–64 years. The outcome included register-based long-term (> 14 days) sickness absence. Negative binominal regression was used to estimate the association between sickness absence and average weekly volume of consumption, frequency of HED, and both in interaction. Results: Abstainers, chronic heavy drinkers and respondents with the highest frequency of HED had approximately two-fold higher rates of sickness absence relative to the reference groups, i.e., moderate drinkers and those with HED one to 6 times per year. Adjustment for confounding factors did not materially affect the shape of the risk function. After exclusion of abstainers with alcohol-related problems, or poor health, the estimates for abstainers became non-significant. Moderate drinkers with HED did not have significantly higher rates of sickness absence than moderate drinkers without HED. Conclusions: Our results suggest a significant association between alcohol use and sickness absence. There were indications that the U-shaped risk function may largely be due to health selection bias among abstainers. We found no indication of effect modification of HED on moderate drinking.

Are the Sick Left Behind at the Peripheries? Health Selection in Migration to Growing Urban Centres in Finland

We study health selection in rural–urban migration in Finland using register data. Specifically, we ask whether ‘movers’ differ from ‘stayers’ in their use of special health care services prior to moving. We focus on migration to twelve growing urban centres in different sub-groups of the population as well as in different regions, using multinomial logistic regression and multilevel modelling and by distinguishing between short- and long-distance moves. The results show that urban centres attract healthier individuals, while people with health problems are also prone to move, but not to urban centres. The results were similar when looking only at psychiatric diagnoses. The findings suggest that it is important to distinguish between different types of moves when studying health-selective migration. Studying the patterns of migration according to health enables us to understand drivers of regional health differences. Moreover, such evidence will help in projecting future demand for healthcare across the country.

Dynamics of Health Among Adults in South Africa

BackgroundThis paper estimates trend of health mobility in South Africa using National Income Dynamic Study (NIDS) and investigate whether the patterns of health mobility differs within socioeconomic groups created by income and gender. Health is measured by SRHS, which correlates with mortality and morbidity; thus, it is the best measure of health. MethodsUsing five waves of NIDS and various econometric models, this research estimates health mobility in the period between 2007 and 2017. This study will use transition matrix as descriptive analysis of health mobility and Conditional Maximum Likelihood Estimations to analyse health mobility, trend of health mobility and relationship between health mobility and health inequality within NIDS. ResultsThe study shows that, among poor males, health mobility neither follows a health selection or health constraint mobility trend; the high health mobility with ambiguous trends has not decreased health inequality. Among the poor females, a negative health mobility trend is observed; this research also found that health inequality has not creased. Among the non-poor males, it is found that health mobility follows a gradient constraint trend which has decreased health inequality. Among non-poor females, it is found that health mobility follows a health selection trend which has not decreased health inequality. The results suggest that policy makers should target both social determinants of health and health campaigns to deal with health inequality among the poor males. ConclusionsThe trend of health mobility among poor females suggest that policy makers should target the social determinants of health to combat health inequality. The trend of health mobility among the non-poor males suggests that health mobility will eliminate health inequality. Lastly, the trend of health mobility suggests that policymakers should target health campaigns to deal with health inequality.