Internal migration, area effects and health: Does where you move to impact upon your health?

Contributions of causes of death to differentials in life expectancy by internal migrant status in the Netherlands. A population register based study, 2015-2019

Important health differences exist in the context of international migration and residential mobility. Less is known about health differences regarding the medium-distance level of internal migration. This study examines life expectancy gaps between internal movers and stayers in the Netherlands and their underlying processes by assessing the contribution of different causes of death by age and sex. It uses individually-linked death counts and population exposures extracted from population registers, covering the native Dutch population aged 10+ from 2015 to 2019. The pooled data were disaggregated by causes-of-death group (neurodegenerative diseases, cardiovascular diseases, lifestyle-related mortality, external causes, and other causes), internal migrant status (movers and stayers, based on past 10-year residence in the 40 NUTS-3 [Nomenclature of Territorial Units for Statistics, level 3] regions), age, and sex. Comparing movers and stayers, we computed life expectancy at age 10 (e10), age- and cause-specific mortality risks, and applied decomposition methods to assess contributions of causes of death to e10 gaps. In the Netherlands in 2015-2019, e10 was lower for movers between NUTS-3 regions than stayers (males: 2.49 years; females: 3.51 years), due to excess mortality for movers at most ages. Movers only had a lower mortality than stayers at younger working ages (males: ages 20-44; females: ages 20-34). Mortality from neurodegenerative diseases and cardiovascular diseases were the largest contributors to the e10 gap, especially at ages 75+ and for females. Mortality from lifestyle-related and external causes of death contributed less, with the largest contributions for females aged 75-89 and males aged 45-69. The lower e10 of movers in the Netherlands is likely explained by health selection effects-in particular care-related moves as coping behaviour-rather than by causal effects through risk accumulation. Research focusing on regional or spatial heterogeneity of the mover-stayer health gap would be insightful to further understand these processes.

Impact of migrants on communicable diseases in Thailand

BACKGROUND

While foreign migrants contribute to economic development, they may impact public health by transmitting communicable diseases to the local population. With its geopolitical position, Thailand has been a primary destination for migrants from neighbouring countries in Southeast Asia and beyond. This positioning makes it a focal point for examining the complexities of migration dynamics and its implications for public health. Through a quantitative analysis, this paper investigates the influence of foreign migrants on physical health issues in Thailand, exploring their impact on various types of communicable diseases. The utilization of provincial-level data from Thailand offers insights into the localized effects of migrant populations on public health within the country. These insights can serve as a valuable resource for researchers and policymakers who conduct comparative analyses, facilitating a deeper understanding of the complex relationship between international migration and public health worldwide.

METHODS

A spatial panel autoregressive model (SAR) is applied on the provincial level communicable diseases and socio-economic data in Thailand from the period 2016 to 2021.

RESULTS

The results indicate that the influence of foreign migrants on communicable diseases in Thailand varies depending on the type of disease. While an increase in migrants correlates with a higher prevalence of respiratory and other communicable diseases, it conversely reduces the prevalence of vaccine-preventable diseases. Additionally, we found that migrants do not significantly impact the prevalence of food- and water-borne diseases, insect-borne diseases, animal-borne diseases, or sexually transmitted diseases in Thailand. Additionally, other factors, such as GPP per capita, unemployment, poverty, and technology access, strongly correlate with most types of communicable diseases.

CONCLUSION

As revealed by this study, the increase in migrants leads to a rise in respiratory and other communicable diseases, as well as a decrease in vaccine-preventable diseases, which carries significant policy implications. These results urge policymakers, the Ministry of Labour, and the Ministry of Public Health to implement tailored policies and measures to enhance public health and effectively mitigate the risk of communicable diseases transmitted by migrants in the future.

How housing burden damages residents' health: evidence from Chinese cities

Background

Currently, China is steadily pursuing high-quality development and promoting common prosperity, for which residents' health is a precondition. However, high housing-price-to-income ratios and rent-to-income ratios have already triggered many social problems and have substantially affected people's work and life. It is of practical significance to examine the relationship between housing burden and residents' health.

Methods

Combining city-level housing price-to-income ratio data and residents' health data from the China Family Panel Studies, this study employs a binary logit model to investigate the impact and mechanism of housing burden on residents' physical and psychological health.

Results

Overall, a 1% increase in the housing-price-to-income ratio leads to a 1.2% decrease in physical health and a 1.9% decrease in psychological health. In terms of different psychological state indicators, a 1% increase in the housing price-to-income ratio leads to a 1.1% increase in depression, 1.1% increase in nervousness, 1.4% increase in relentlessness, 1.4% increase in hopelessness, 1.0% increase in a sense of incapability, and 1.4% increase in meaninglessness. According to mechanistic analyses, a 1% increase in the housing-price-to-income ratio leads to increases of 0.6 and 0.7% in the smoking rate and late sleep rate, respectively, while it leads to a 0.9% decrease in the noon nap rate.

Conclusion

A growing housing burden significantly negatively impacts both the physical and psychological health of residents and increases the possibility of negative emotions. Further investigation revealed that the housing burden damages residents' health by increasing their likelihood of smoking and sleeping late and decreasing their likelihood of taking a nap at noon, while exercise alleviates the negative impacts of the housing burden on residents' physical and psychological health. Finally, we also find that housing burdens' impacts on physical and psychological health differ significantly in terms of gender, age, and educational attainment. From the perspective of improving livelihoods, governments should consider the relationship between housing burdens and residents' health when formulating livelihood policies. Location-specific and targeted policies should be followed. Additionally, efforts should be made to promote exercise among citizens.

The 'welcomed lockdown' hypothesis? Mental wellbeing and mobility restrictions

The COVID-19 pandemic and its mobility restrictions have been an external shock, influencing mental wellbeing. However, does risk exposure to COVID-19 affect the mental wellbeing effect of lockdowns? This paper examines the 'welcomed lockdown' hypothesis, namely the extent to which there is a level of risk where mobility restrictions are not a hindrance to mental wellbeing. We exploit the differential timing of exposure the pandemic, and the different stringency of lockdown policies across European countries and we focus on the effects on two mental health conditions, namely anxiety and depression. We study whether differences in the individual symptoms of anxiety and depression are explained by the combination of pandemic mortality and stringency of lockdown. We draw on an event study approach, complemented with a Difference-in-Difference (DiD), and Regression Discontinuity Design (RDD). Our estimates suggest an average increase in depression (3.95%) and anxiety (10%) symptoms relative to the mean level on the day that lockdown took effect. However, such effects are wiped out when a country's exhibits high mortality ('pandemic category 5'). Hence, we conclude that in an environment of high mortality, lockdowns no longer give rise to a reduction in mental wellbeing consistent with the 'welcome lockdown' hypothesis.

Trusting the Health System and COVID 19 Restriction Compliance

We examine the extent to which exposure to higher relative COVID-19 mortality (RM), influences health system trust (HST), and whether changes in HST explain the perceived ease of compliance with pandemic restrictions during the COVID-19 pandemic. Drawing on evidence from two representative surveys covering all regions of 28 European countries before and after the first COVID-19 wave, and using a difference in differences strategy together with Coarsened Exact Matching (CEM), we document that living in a region with higher RM during the first wave of the pandemic increased HST. However, the positive effect of RM on HST is driven by individuals over 45 years of age, and the opposite effect is found among younger cohorts. Furthemore, we find that a higher HST reduces the costs of complying with COVID-19 restrictions, but only so long as excess mortality does not exceed the average by more than 20%, at which point the ease of complying with COVID-19 restrictions significantly declines, offsetting the positive effect of trust in the healthcare system. Our interpretation of these estimates is that a higher RM is interpreted as a risk signal among those over 45, and as a signal of health-care system failure among younger age individuals.

Effect of residential relocation on environmental exposures in European cohorts: An exposome-wide approach

Residential relocation is increasingly used as a natural experiment in epidemiological studies to assess the health impact of changes in environmental exposures. Since the likelihood of relocation can be influenced by individual characteristics that also influence health, studies may be biased if the predictors of relocation are not appropriately accounted for. Using data from Swedish and Dutch adults (SDPP, AMIGO), and birth cohorts (BAMSE, PIAMA), we investigated factors associated with relocation and changes in multiple environmental exposures across life stages. We used logistic regression to identify baseline predictors of moving, including sociodemographic and household characteristics, health behaviors and health. We identified exposure clusters reflecting three domains of the urban exposome (air pollution, grey surface, and socioeconomic deprivation) and conducted multinomial logistic regression to identify predictors of exposome trajectories among movers. On average, 7 % of the participants relocated each year. Before relocating, movers were consistently exposed to higher levels of air pollution than non-movers. Predictors of moving differed between the adult and birth cohorts, highlighting the importance of life stages. In the adult cohorts, moving was associated with younger age, smoking, and lower education and was independent of cardio-respiratory health indicators (hypertension, BMI, asthma, COPD). Contrary to adult cohorts, higher parental education and household socioeconomic position were associated with a higher probability of relocation in birth cohorts, alongside being the first child and living in a multi-unit dwelling. Among movers in all cohorts, those with a higher socioeconomic position at baseline were more likely to move towards healthier levels of the urban exposome. We provide new insights into predictors of relocation and subsequent changes in multiple aspects of the urban exposome in four cohorts covering different life stages in Sweden and the Netherlands. These results inform strategies to limit bias due to residential self-selection in epidemiological studies using relocation as a natural experiment.

Heterogeneity in Disparities in Life Expectancy Across US Metropolitan Areas

BACKGROUND

Life expectancy in the United States has declined since 2014 but characterization of disparities within and across metropolitan areas of the country is lacking.

METHODS

Using census tract-level life expectancy from the 2010 to 2015 US Small-area Life Expectancy Estimates Project, we calculate 10 measures of total and income-based disparities in life expectancy at birth, age 25, and age 65 within and across 377 metropolitan statistical areas (MSAs) of the United States.

RESULTS

We found wide heterogeneity in disparities in life expectancy at birth across MSAs and regions: MSAs in the West show the narrowest disparities (absolute disparity: 8.7 years, relative disparity: 1.1), while MSAs in the South (absolute disparity: 9.1 years, relative disparity: 1.1) and Midwest (absolute disparity: 9.8 years, relative disparity: 1.1) have the widest life expectancy disparities. We also observed greater variability in life expectancy across MSAs for lower income census tracts (coefficient of variation [CoV] 3.7 for first vs. tenth decile of income) than for higher income census tracts (CoV 2.3). Finally, we found that a series of MSA-level variables, including larger MSAs and greater proportion college graduates, predicted wider life expectancy disparities for all age groups.

CONCLUSIONS

Sociodemographic and policy factors likely help explain variation in life expectancy disparities within and across metro areas.

Determinants of Differences in Health Service Utilization between Older Rural-to-Urban Migrant Workers and Older Rural Residents: Evidence from a Decomposition Approach

Background: The widening gap in health service utilization between different groups in mainland China has become an important issue that cannot be avoided. Our study explored the existence of differences and the causes of the differences in the health service utilization of older rural-to-urban migrant workers in comparison to older rural dwellers. Further, our study explored socioeconomic differences in health service utilization. Methods: The data from the China Labor-Force Dynamic Survey in 2016, the data from the Urban Statistical Yearbook in 2016, and the Statistical Bulletin were used. Our study applied the latest Andersen Model according to China’s current situation. Before we studied health service utilization, we used Coarsened Exact Matching to control the confounding factors. After matching, 2314 respondents were successfully matched (859 older rural-to-urban migrant workers and 1455 older rural dwellers). The Fairlie decomposition method was used to analyze the differences and the sources of health service utilization between older rural-to-urban migrant workers and their rural counterparts. Results: After matching, the probability two-weeks outpatient for older rural-to-urban migrant workers (5.59%) was significantly lower than older rural dwellers (7.57%). The probability of inpatient for older rural-to-urban migrant workers (5.59%) was significantly lower than older rural dwellers (9.07%). Overall, 17.98% of the total difference for two-week outpatient utilization was due to the observed influence factors. Moreover, 71.88% of total difference in inpatient utilization was due to the observed influence factors. Income quantiles (49.57%), health self-assessments (80.91%), and the sex ratio in the community (−102.29%) were significant in the differences in inpatient utilization. Conclusions: The findings provide important insights into the socioeconomic differences in health service utilization among older rural-to-urban migrant workers and older rural residents in China. These insights urge the government to take full account of the heterogeneity in designing health security system reform and public health interventions targeting vulnerable groups.

Work-related internal migration and changes in mental and physical health: A longitudinal study using German data

Work-related internal migration can be associated with various labor market benefits such as improved career opportunities. However, benefits can be offset by specific burdens (relocation stress) which, in turn, can lead to adverse health outcomes. These burdens include organizing the move, difficulties in maintaining social relationships, homesickness or feelings of displacement. However, there is a particular lack of longitudinal studies which deploy advanced methods to examine how internal migration affects shifts in health-related quality of life (HRQOL) over time. Also, there has been little research into whether the consequences of relocations differ by socio-economic position. In order to address these gaps, we apply fixed effects (FE) panel regression models to representative data from the German Socio-Economic Panel (SOEP). We use the SF-12 Health Survey items to capture the subjective assessment of overall mental and physical well-being. Overall, we find an increase in physical HRQOL after the relocation event. Mental HRQOL tends to decrease before the event and then increases afterwards, on average, but there seems to be very little lasting change. Subgroup analyses, however, reveal differential trajectories by educational level, i.e. a clear educational health gradient around migration. While physical and mental HRQOL increases among movers with high educational attainment, individuals with lower levels of education show decreases in both health dimensions upon moving.

Mapping mental health inequalities: The intersecting effects of gender, race, class, and ethnicity on ADHD diagnosis

While the effects of social stratification by gender, race, class, and ethnicity on health inequalities are well-documented, our understanding of the intersecting consequences of these social dimensions on diagnosis remains limited. This is particularly the case in studies of mental health, where "paradoxical" patterns of stratification have been identified. Using a Bayesian multi-level random-effects Poisson model and a nationally representative random sample of 138,009 households from the National Survey of Children's Health, this study updates and extends the literature on mental health inequalities through an intersectional investigation of one of the most commonly diagnosed psychiatric conditions of childhood/adolescence: attention-deficit hyperactivity disorder (ADHD). Findings indicate that gender, race, class, and ethnicity combine in mutually constitutive ways to explain between-group variation in ADHD diagnosis. Observed effects underscore the importance and feasibility of an intersectional, multi-level modelling approach and data mapping technique to advance our understanding of social subgroups more/less likely to be diagnosed with mental health conditions.

Gender differences in depressive symptoms of rural Chinese grandparents caring for grandchildren

BACKGROUND

Caring for grandchildren is regarded as one of the principle roles of middle- and old-aged adults, especially among rural Chinese grandparents. This study aims to examine the gender differences in depressive symptoms of rural Chinese grandparents caring for grandchildren, based on the gender differences in grandparental role engagement and the theories of role strain and role enhancement.

METHODS

A total of 4833 rural citizens with one or more grandchildren were selected from the China Health and Retirement Longitudinal Study (CHARLS) conducted in 2015. Grandchild care was measured by continuous variable (duration) and categorical variable (no care, low intensity, moderate intensity, high intensity). Depressive symptoms were assessed by the Center for Epidemiologic Studies Depression Scale (CES-D). We used coarsened exact matching (CEM) to balance the covariates of caregivers and non-caregivers. Following CEM, 1975 non-caregivers and 2212 caregivers were identified (N = 4187). Multilevel linear regression was employed to examine the gender differences in depressive symptoms. We also tested for the moderating role of gender on the association between grandchild care and depressive symptoms.

RESULTS

Grandmothers were more likely to provide grandchild care (54.42% vs 51.43%) at high intensity (61.46% vs 51.01%), with longer duration (39.24 h vs 33.15 h) than that given by grandfathers. Grandmothers suffered more from depressive symptoms than grandfathers, and such gap increased when grandparents were involved in high-intensity care. Grandmothers providing grandchild care, particularly at moderate intensity, were associated with fewer depressive symptoms (Coef. = - 0.087, 95%CI: - 0.163, - 0.010; Coef. = - 0.291, 95%CI: - 0.435, - 0.147), compared with non-caregivers. Grandmothers giving moderate intensity of grandchild care were also associated with fewer depressive symptoms (Coef. = - 0.171, 95% CI: - 0.313, - 0.029), compared with those with low-intensity care. However, such associations were not significant among grandfathers.

CONCLUSIONS

Our findings highlight the gender differences in depressive symptoms of rural Chinese grandparents caring for grandchildren. Grandparents should be encouraged to engage in grandchild care, but at moderate intensity. The health status of middle- and old-aged adults, particularly females, should be monitored closely. Humanistic care, preventive care and curative treatment strategies focusing on such populations should be developed and refined.

Decomposing Differences of Health Service Utilization among Chinese Rural Migrant Workers with New Cooperative Medical Scheme: A Comparative Study

The New Rural Cooperative Medical Insurance (NCMS) in China has provided benefits for rural migrant workers’ health service utilization, but the financial coordination and mutual aid of NCMS is mainly based on the county or district as a unit, leading NCMS with the characteristics of regional segmentation. Our study aims to explore their health service utilization, as well as to decompose differences of the health service utilization into contributors. Data from the China Labor-Force Dynamic Survey in 2016 and Urban Statistical Yearbook in 2016 were used. We used coarsened exact matching to control the confounding factors in order to enhance the comparison of two groups. The Fairlie decomposition method was used to analyze the differences and the sources of health service utilization. Influencing factors of health service utilization for rural migrant workers with NCMS were diversified, especially contextual characteristic and individual characteristics. The proportion of ethnic minorities, the number of medical institutions for 10,000 people in the community, the number of beds for 10,000 people in the city, and the urban service quality index were the major contributors of the differences. The proportion of difference in the health service utilization of rural migrant workers with NCMS caused by health service need were −54.73% and 6.92%, respectively. The inequities of the probability of two weeks outpatient, and the probability of inpatients, were −0.006 and −0.007, respectively. There were substantial differences in the health service utilization between rural migrant workers with NCMS in the county/district and rural migrant workers with NCMS across the county/district. Our results illustrated the inequity from the differences on basis of characteristic effect and the discrimination effect. Our studies clarified that health service needs of should be fully considered, contributing to a more reliable understanding of the health service utilization of rural migrant workers.

A mixed method study to examine the mental health problems of college students who had left-behind experiences

BACKGROUND

China's rapid urbanization has created a large number of labour transferring from rural to urban areas and large numbers of college students with left-behind experience (LBE). LBE was an important influencing factor on college students' mental health.

METHODS

A mixed method involving quantitative survey and qualitative interview was emplyed to explore the influence of LBE on mental health of college students. In the quantitative survey, 1605 college students from three different universities of Shandong province in China were recruited. Their mental health status was measured using Symptom Check-list 90(SCL-90 scale) compiled by American psychologist Derogatis. In the qualitative interview, 40 college students with left-behind experience from the same three universities were interviewed.

RESULTS

The prevalence estimate of total mental health problems among left-behind students was 2.14 times higher than that among those without left-behindexperience. LBE increased the problems of somatization, obsessive-compulsion (Ocd), international sensitivity, depression, anxiety, hostility, terror, paranoia, psychoticism and other symptoms. The result of qualitative interview showed the mental health problems of the college students with left-behind experience were mainly on anxiety, depression, Ocd, interpersonal sensitive and hostility, which was consistent with the results of quantitative survey.

LIMITATION

Representativeness of the sample is the major limitation of our study. Due to rare similar studies performed in other countries, we could not compare the results in China to that in other countries.

CONCLUSION

Left-behind experience was an important factor associated with the mental health of college students. The mental health of college students with LBE needs more attention.

Rural and urban differences in patient experience in China: a coarsened exact matching study from the perspective of residents

BACKGROUND

Patient experience is a key measure widely used to evaluate quality of healthcare, yet there is little discussion about it in China using national survey data. This study aimed to explore rural and urban differences in patient experience in China.

METHODS

Data regarding this study were drawn from Chinese General Social Survey (CGSS) 2015, with a sample size of 9604. Patient experience was measured by the evaluation on healthcare services. Coarsened exact matching (CEM) method was used to balance covariates between the rural and urban respondents. Three thousand three hundred seventy-two participants finally comprised the matched cohort, including 1592 rural residents and 1780 urban residents. Rural and urban differences in patient experience were tested by ordinary least-squares regression and ordered logistic regression.

RESULTS

The mean (SD) score of patient experience for rural and urban residents was 72.35(17.32) and 69.45(17.00), respectively. Urban residents reported worse patient experience than rural counterparts (Crude analysis: Coef. = - 2.897, 95%CI: - 4.434, - 1.361; OR = 0.706, 95%CI: 0.595, 0.838; Multivariate analysis: Coef. = - 3.040, 95%CI: - 4.473, - 1.607; OR = 0.675, 95%CI: 0.569, 0.801). Older (Coef. = 2.029, 95%CI: 0.338, 3.719) and healthier (Coef. = 2.287, 95%CI: 0.729, 3.845; OR = 1.217, 95%CI: 1.008, 1.469) rural residents living in western area (Coef. = 2.098, 95%CI: 0.464, 3.732; OR = 1.276, 95%CI: 1.044, 1.560) with higher social status (Coef. = 1.158, 95%CI: 0.756, 1.561; OR = 1.145, 95%CI: 1.090, 1.204), evaluation on adequacy (Coef. = 7.018, 95%CI: 5.045, 8.992; OR = 2.163, 95%CI: 1.719, 2.721), distribution (Coef. = 4.464, 95%CI: 2.471, 6.456; OR = 1.658, 95%CI: 1.312, 2.096) and accessibility (Coef. = 2.995, 95%CI: 0.963, 5.026; OR = 1.525, 95%CI: 1.217, 1.911) of healthcare resources had better patient experience. In addition, urban peers with lower education (OR = 0.763, 95%CI: 0.625, 0.931) and higher family economic status (Coef. = 2.990, 95%CI: 0.959, 5.021; OR = 1.371, 95%CI: 1.090,1.723) reported better patient experience.

CONCLUSIONS

Differences in patient experience for rural and urban residents were observed in this study. It is necessary to not only encourage residents to form a habit of seeking healthcare services in local primary healthcare institutions first and then go to large hospitals in urban areas when necessary, but also endeavor to reduce the disparity of healthcare resources between rural and urban areas by improving quality and capacity of rural healthcare institutions and primary healthcare system of China.

Does Lolland-Falster make people sick, or do sick people move to Lolland-Falster? An example of selective migration and mortality in Denmark, 1968-2017

INTRODUCTION

Lolland-Falster is a rural area in south-eastern Denmark that scores unfavourable in health surveys and has the lowest life expectancy in the country. To determine the origin of poor health in Lolland-Falster, we investigated impact on mortality of long-term population movements.

METHODS

We used data from the Danish Central Population Register 1968-2017 to track movements in and out of Lolland-Falster. This enabled us to calculate mortality based on tenure of residence. Poisson regression adjusted for sex, 5-year age-groups, and calendar year; separately for men and women; and ages <30, 30-64 and ≥ 65 years; was reported as mortality rate ratios (MRR) with 95% confidence intervals (95% CI).

RESULTS

Until 1988, mortality in Lolland-Falster was fairly similar to that in the rest of Denmark. Hereafter, mortality rates drifted apart. In 2008-2017, MRR of the total Lolland-Falster population was 1.21 (95% CI: 1.19-1.23). In each 10-year calendar period, people recently in-migrating constituted about one fourth of the population. MRRs of the in-migrating population increased over time from 1.17 (95% CI: 1.08-1.26) in 1968-1977, to 1.82 (95% CI: 1.75-1.89) in 2008-2017. Persons aged 30-64 constituted the largest in-migrating group and had highest excess mortality, MRR 2.34 (95% CI: 2.19-2.50) in 2008-2017.

CONCLUSION

Long-term selective in-migration of vulnerable persons was behind the gradual build-up of the currently high mortality in Lolland-Falster compared to the rest of Denmark. In particular, people of working age in-migrating to Lolland-Falster contributed to this disparity.

Were the hospital bed reductions proposed by English Clinical Commissioning Groups (CCGs) in the sustainability and transformation plans (STPs) achievable? Insights from a new model to compare international bed numbers

A new model for hospital bed numbers which adjusts for end-of-life care and age structure is used to demonstrate that England has 20% fewer occupied beds than the other countries in the United Kingdom. It also shows that occupied beds in English Clinical Commissioning Groups (CCGs) lie parallel to a line of equivalence with New Zealand and Singapore. This is despite New Zealand and Singapore having invested many years into developing integrated care, while England has not. In addition, England has around half the number of nursing home beds per death available in these two countries. Large bed reductions proposed in the sustainability and transformation plans were likely to have been manipulated to meet financial cost-saving targets rather than a result of genuine modelling of demand. The ways in which bed demand models can be manipulated to give whatever answer is required are discussed. Trends in occupied acute medical beds in England over the past 20 years show no real reduction, despite a large reduction in available beds. This has resulted in daytime occupancy for adult beds being close to 100% and with resulting queues to admission. The ways to improve the small-area application of the model including the use of deprivation or social groups are discussed.

Comparison of health care utilization among patients affiliated and not affiliated with healthcare professionals in China

BACKGROUND

Doing "more" in healthcare can be a major threat to the delivery of high-quality health care. It is important to identify the supplier-induced demand (SID) of health care. This study aims to test SID hypothesis by comparing health care utilization among patients affiliated with healthcare professionals and their counterpart patients not affiliated with healthcare professionals.

METHODS

We used coarsened exact matching to compare the health care utilization and expenditure between patients affiliated and not affiliated with healthcare professionals. Using cross-sectional data of the China Labour-force Dynamics Survey (CLDS) in 2014, we identified 806 patients affiliated with healthcare professionals and 22,788 patients not affiliated with healthcare professionals. The main outcomes were outpatient proportion and expenditure as well as inpatient proportion and expenditure.

RESULTS

The matched outpatient proportion of patients not affiliated with healthcare professionals was 0.6% higher (P = 0.754) than that of their counterparts, and the matched inpatient proportion was 1.1% lower (P = 0.167). Patients not affiliated with healthcare professionals paid significantly more (680 CNY or 111 USD, P < 0.001) than their counterparts did per outpatient visit (1126 CNY [95% CI 885-1368] vs. 446 CNY [95% CI 248-643]), while patients not affiliated with healthcare professionals paid insignificantly less (2061 CNY or 336 USD, P = 0.751) than their counterparts did per inpatient visit (15583 CNY [95% CI 12052-19115] vs. 17645 CNY [95% CI 4884-30406]).

CONCLUSION

Our results lend support to the SID hypothesis and highlight the need for policies to address the large outpatient care expenses among patients not affiliated with healthcare professionals. Our study also suggests that as the public becomes more informed, the demand of health care may persist while heath care expenditure per outpatient visit may decline sharply due to the weakened SID. To address misbehaviors and contain health care costs, it is important to realign provider incentives.

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.

Decomposing differences in depressive symptoms between older rural-to-urban migrant workers and their counterparts in mainland China

Background

There has been an increase in older rural-to-urban migrant workers (aged 50 and above) in mainland China, little known about their depressive symptoms. The aim of this study was to identify depressive symptoms among older rural-to-urban migrant workers, as well as explored the factors leading to differences in depressive symptoms between older rural-to-urban migrant workers and their rural counterparts (older rural dwellers) and urban counterparts (older urban residents) in mainland China. The results provided a comprehensive understanding of the depressive symptoms of older rural-to-urban migrant workers, and had great significance for improving the depressive symptoms for this vulnerable group.

Methods

Data were derived from the China Health and Retirement Longitudinal Study (CHARLS) conducted in 2015, and coarsened exact matching (CEM) method was employed to control confounding factors. This study employed a Chinese version 10-item short form of the Center for Epidemiologic Studies-Depression Scale (CES-D 10) to measure depressive symptoms, and used the Social-Ecological Model as a framework to explore influential factors related to depressive symptoms. Specifically, the approach of Fairlie’s decomposition was used to parse out differences into observed and unobserved components.

Results

After matching, our findings indicated that the prevalence of depressive symptoms in older rural-to-urban migrant workers was lower than older rural dwellers; and the prevalence of depressive symptoms in older rural-to-urban migrant workers was higher than older urban residents. Fairlie’s decomposition analysis indicated that type of in-house shower, sleeping time at night and ill in the last month were proved to be major contributors to the differences in depressive symptoms between older rural-to-urban migrant workers and older rural dwellers; self-reported health and sleeping time at night were proved to be major contributors to the differences in depressive symptoms between older rural-to-urban migrant workers and older urban residents.

Conclusions

Differences in depressive symptoms between older rural-to-urban migrant workers and their rural and urban counterparts did exist. Our findings contributed to a more reliable understanding in depressive symptoms among older rural-to-urban migrant workers. Our findings would be of referential significance for improving older rural-to-urban migrant workers’ depressive symptoms.

The Influence of Left-Behind Experience on College Students' Mental Health: A Cross-Sectional Comparative Study

China’s rapid development and urbanization have created large numbers of migrant laborers, with increasing numbers of young adults and couples migrating from rural areas to large cities. As a result, a large number of children have become left-behind children (LBC), who were left behind in their hometown and cared for by one parent, grandparents, relatives or friends. Some of these LBC have a chance to be college students, who are called college students with left-behind experience. Some studies have indicated that the absence of these college students’ parents during childhood may cause them to have some mental health problems. Therefore, we want to examine the effects of left-behind experience on college students’ mental health and compare the prevalence of mental health problems in left-behind students and control students (without left-behind experience). For this purpose, a cross-sectional comparative survey was conducted in a coastal city of Shandong province, Eastern China. First, 1605 college students from three universities (national admissions) were recruited, including 312 students with left-behind experience and 1293 controls. Their mental health level was measured using Symptom Check-list 90 (containing ten dimensions: somatization, obsessive-compulsion (OCD), interpersonal sensitivity, depression, anxiety, hostility, terror, paranoia, psychoticism, and other symptoms). The results showed that left-behind experience was a significant risk factor for the mental health problems of college students (OR = 2.27, 95%CI: 1.73 to 2.97). A comparison of the two groups, after controlling the confounding factors using the coarsened exact matching (CEM) algorithm, showed that the prevalence of mental health problems was 35.69% (n = 311) among the left-behind students, while it was 19.68% (n = 1194) among the controls. The two groups were significantly different in terms of these ten dimensions of the SCL-90 scale (p < 0.001), and the prevalence of each dimension among the left-behind students was consistently higher than that among the controls. In addition, different left-behind experiences and social supports during childhood had different effects on mental health problems.

Health Disparity between the Older Rural-to-Urban Migrant Workers and Their Rural Counterparts in China

Background: China’s older rural-to-urban migrant workers (age 50 and above) are growing old, but comparative health research on older rural-to-urban migrants in China is still in its infancy. The aim is to explore the health status of older rural-to-urban migrant workers in China; as well as to identify health disparity between older rural-to-urban migrant workers and older rural dwellers. Methods: This study employed self-assessed health status (SAH) and chronic disease condition to explore the health status. Coarsened exact matching (CEM) was employed to improve estimation of causal effects. Fairlie’s decomposition analysis was conducted to find the health disparity. Results: Older rural-to-urban migrant workers were more prone to suffer from chronic diseases, but they had higher SAH when comparing older rural dwellers. Fairlie’s decomposition analysis indicated 10.44% of SAH disparities between two older groups can be traced to bath facility; 31.34% of chronic diseases disparities can be traced to educational attainment, sleeping time and medical scheme. Conclusions: This is the first comparative study examining health disparity focusing on older rural-to-urban migrant workers. Our study highlighted substantial health disparities between older rural-to-urban migrant workers and their older rural dwellers. Based on the contributing factors, government should take the drivers of health disparities into consideration in policy setting.

Increased Risk of Hepatocellular Carcinoma Associated With Neighborhood Concentrated Disadvantage

Purpose: Over the past three decades, Hepatocellular Carcinoma (HCC) is one of few cancers for which incidence has increased in the United States (US). It is likely social determinants at the population level are driving this increase. We designed a population-based study to explore whether social determinants at the neighborhood level are geographically associated with HCC incidence in Louisiana by examining the association of HCC incidence with neighborhood concentrated disadvantage. Methods: Primary HCC cases diagnosed from 2008 to 2012 identified from the Louisiana Tumor Registry were geocoded to census tract of residence at the time of diagnosis. Neighborhood concentrated disadvantage index (CDI) for each census tract was calculated according to the PhenX Toolkit data protocol based on population and socioeconomic measures from the US Census. The incidence of HCC was modeled using multilevel binomial regression with individuals nested within neighborhoods. Results: The study included 1,418 HCC cases. Incidence of HCC was greater among males than females and among black than white. In multilevel models controlling for age, race, and sex, neighborhood CDI was positively associated with the incidence of HCC. A one standard deviation increase in CDI was associated with a 22% increase in HCC risk [Risk Ratio (RR) = 1.22; 95% CI (1.15, 1.31)]. Adjusting for contextual effects of an individual's neighborhood reduced the disparity in HCC incidence. Conclusion: Neighborhood concentrated disadvantage, a robust measure of an adverse social environment, was found to be a geographically associated with HCC incidence. Differential exposure to neighborhoods characterized by concentrated disadvantage partially explained the racial disparity in HCC for Louisiana. Our results suggest that increasing rates of HCC, and existing racial disparities for the disease, are partially explained by measures of an adverse social environment.

Does selective migration alter socioeconomic inequalities in mortality in Wales?: a record-linked total population e-cohort study

Recent studies found evidence of health selective migration whereby healthy people move to less deprived areas and less healthy people move to or stay in more deprived areas. There is no consensus, however, on whether this influences health inequalities. Measures of socio-economic inequalities in mortality and life expectancy are widely used by government and health services to track changes over time but do not consider the effect of migration. This study aims to investigate whether and to what extent migration altered the observed socioeconomic gradient in mortality. Data for the population of Wales (3,136,881) registered with the National Health Service on 01/01/2006 and follow-up for 24 quarters were individually record-linked to ONS mortality files. This included moves between lower super output areas (LSOAs), deprivation quintiles and rural-urban class at each quarter, age, sex, and date of death. Cox regression models were used to estimate the hazard ratios for the deprivation quintiles in all-cause mortality, as well as deprivation change between the start and end of the study. We found evidence of health selective migration in some groups, for example people aged under 75 leaving the most deprived areas having a higher mortality risk than those they left behind, suggesting widening inequalities, but also found the opposite pattern for other migration groups. For all ages, those who lived in the most deprived quintile had a 57% higher risk of death than those in the least deprived quintile, allowing deprivation to vary with moves over time. There was little change in this risk when people were artificially kept in their deprivation quintile of origin (54% higher). Overall, migration during the six year window did not substantially alter the deprivation gradient in mortality in Wales between 2006 and 2011.

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Health selective migration was found for selected subgroups.

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Change to inequalities varied by direction of deprivation change and age group.

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Migration overall did not alter the socioeconomic gradient in mortality in Wales.

Comparing the effects of China's three basic health insurance schemes on the equity of health-related quality of life: using the method of coarsened exact matching

BACKGROUND

China has three basic health insurance schemes: Urban Employee Basic Medical Insurance (UEBMI), Urban Resident Basic Medical Insurance (URBMI) and New Rural Cooperative Medical Scheme (NRCMS). This study aimed to compare the equity of health-related quality of life (HRQoL) of residents under any two of the schemes.

METHODS

Using data from the 5th National Health Services Survey of Shaanxi Province, China, coarsened exact matching method was employed to control confounding factors. We included a matched sample of 6802 respondents between UEBMI and URBMI, 34,169 respondents between UEBMI and NRCMS, and 36,928 respondents between URBMI and NRCMS. HRQoL was measured by EQ-5D-3L based on the Chinese-specific value set. Concentration index was adopted to assess health inequality and was decomposed into its contributing factors to explain health inequality.

RESULTS

After matching, the horizontal inequity indexes were 0.0036 and 0.0045 in UEBMI and URBMI, 0.0035 and 0.0058 in UEBMI and NRCMS, and 0.0053 and 0.0052 in URBMI and NRCMS respectively, which were mainly explained by age, educational and economic statuses. The findings demonstrated the pro-rich health inequity was much higher for the rural scheme than that for the urban ones.

CONCLUSION

This study highlights the need to consolidate all three schemes by administrating uniformly, merging funds pooling and benefit packages. Based on the contributing factors, strategies aim to facilitate health conditions of the elderly, narrow economic gap, and reduce educational inequity, are essential. This study will provide evidence-based strategies on consolidating the fragmented health schemes towards reducing health inequity in both China and other developing countries.

Socioeconomic deprivation, mortality and health of within-city migrants: a population cohort study

BACKGROUND

Evidence linking selective migration (the situation where people in good health move from deprived to affluent areas, whilst people in poor health move in the opposite direction) within local areas to mortality is inconclusive.

METHODS

Mortality in within-city migrants was examined using a Sheffield population cohort, adjusted for moves to care homes. The cohort comprised 310 894 people aged 25+ years in 2001 followed up for 9.18 years, with 42 252 (13.6%) deaths. Information on pre-existing medical conditions, socioeconomic indicators and smoking was available from a sample survey.

RESULTS

Relative risks (95% CI) of mortality in migrants from deprived to affluent areas were lower compared with people remaining in deprived areas; 0.53 (0.42 to 0.65), 0.70 (0.61 to 0.80), 0.76 (0.68 to 0.86), 0.93 (0.88 to 1.00) and 0.98 (0.93 to 1.03) in the 25-44, 45-64, 65-74, 75-84 and 85+ year age bands, respectively. They also had lower prevalence ORs (95% CI) for bronchitis (0.59 (0.39 to 0.89)), asthma (0.70 (0.53 to 0.93)), depression (0.59 (0.38 to 0.94)), and were less likely to receive benefits (0.60 (0.47 to 0.76)) and less likely to smoke (0.66 (0.51 to 0.85)).Conversely, mortality relative risks in migrants from affluent to deprived areas were higher compared with people remaining in affluent areas; 1.71 (1.37 to 2.12), 1.59 (1.40 to 1.82), 1.44 (1.26 to 1.63), 1.18 (1.10 to 1.27) and 1.04 (1.00 to 1.09) in the corresponding age groups. They also had higher prevalence odds ratios for long-term illness (2.37 (1.71 to 3.29)), asthma (1.71 (1.25 to 2.35)), diabetes (3.03 (1.70 to 5.41)), depression (2.71 (1.74 to 4.21)), were more likely to receive benefits (2.25 (1.65 to 3.07)) and more likely to smoke (1.51 (1.12 to 2.05)).

CONCLUSIONS

People moving from deprived to affluent areas had lower mortality and better health, and vice versa, especially in the younger age groups. This study provides strong evidence linking selective migration within local areas to mortality.

Health selection into neighborhoods among patients enrolled in a clinical trial

Health selection into neighborhoods may contribute to geographic health disparities. We demonstrate the potential for clinical trial data to help clarify the causal role of health on locational attainment. We used data from the 20-year United Kingdom Prospective Diabetes Study (UKPDS) to explore whether random assignment to intensive blood-glucose control therapy, which improved long-term health outcomes after median 10 years follow-up, subsequently affected what neighborhoods patients lived in. We extracted postcode-level deprivation indices for the 2710 surviving participants of UKPDS living in England at study end in 1996/1997. We observed small neighborhood advantages in the intensive versus conventional therapy group, although these differences were not statistically significant. This analysis failed to show conclusive evidence of health selection into neighborhoods, but data suggest the hypothesis may be worthy of exploration in other clinical trials or in a meta-analysis.

Neighbourhood socioeconomic inequality and gender differences in body mass index: The role of unhealthy behaviours

Reported differences in the severity of the social gradient in body mass index (BMI) by gender may be attributable to differences in behaviour. Self-reported height, weight, socioeconomic and behavioural data were obtained for a sample of 10,281 Australians aged ≥15years in 2009. Multilevel regressions were fitted with BMI as the outcome variable. Two-way interactions between gender and neighbourhood disadvantage were fitted, adjusted for confounders. Models were then adjusted for four behavioural factors ("chips, snacks and confectionary", "smoking, little fruit or veg", "time poor and less physically active" and "alcohol consumption"). Additional models were fitted on a subset with accurate perceptions of weight status (determined by World Health Organization criteria) to control for potential social desirability bias. Although higher BMI was observed for men in most disadvantaged compared with most affluent neighbourhoods (coefficient 0.87, 95% CI 0.35 to 1.40), this pattern was stronger among women (1.80, 95% CI 1.17 to 2.42). Adjusting for differences in behaviours attenuated, but did not fully explain the differences in social gradients observed for men (0.73, 95% CI 0.21 to 1.26) and women (1.73, 1.10 to 2.36). Differences in behaviour did not explain contrasting socioeconomic gradients in adult BMI by gender. Further research on differences in BMI, health and behaviour over time aligned with how heavy a person may perceive themselves to be is warranted.

To move or not to move? Exploring the relationship between residential mobility, risk of cardiovascular disease and ethnicity in New Zealand

Residential mobility can have negative impacts on health, with some studies finding that residential mobility can contribute to widening health gradients in the population. However, ethnically differentiated experiences of residential mobility and the relationship with health are neglected in the literature. To examine the relationship between residential mobility, risk of cardiovascular disease (CVD) and ethnicity, we constructed a cohort of 2,077,470 participants aged 30 + resident in New Zealand using encrypted National Health Index (eNHI) numbers linked to individual level routinely recorded data. Using binary logistic regression, we model the risk of CVD for the population stratified by ethnic group according to mover status, baseline deprivation and transitions between deprivation statuses. We show that the relationship between residential mobility and CVD varies between ethnic groups and is strongly influenced by the inter-relationship between residential mobility and deprivation mobility. Whilst residential mobility is an important determinant of CVD, much of the variation between ethnic groups is explained by contrasting deprivation experiences. To reduce inequalities in CVD within New Zealand, policies must focus on residentially mobile Māori, Pacific and South Asian populations who already have a heightened risk of CVD living in more deprived areas.

How much of the difference in life expectancy between Scottish cities does deprivation explain?

BACKGROUND

Glasgow's low life expectancy and high levels of deprivation are well documented. Studies comparing Glasgow to similarly deprived cities in England suggest an excess of deaths in Glasgow that cannot be accounted for by deprivation. Within Scotland comparisons are more equivocal suggesting deprivation could explain Glasgow's excess mortality. Few studies have used life expectancy, an intuitive measure that quantifies the between-city difference in years. This study aimed to use the most up-to-date data to compare Glasgow to other Scottish cities and to (i) evaluate whether deprivation could account for lower life expectancy in Glasgow and (ii) explore whether the age distribution of mortality in Glasgow could explain its lower life expectancy.

METHODS

Sex specific life expectancy was calculated for 2007-2011 for the population in Glasgow and the combined population of Aberdeen, Dundee and Edinburgh. Life expectancy was calculated for deciles of income deprivation, based on the national ranking of datazones, using the Scottish Index of Multiple Deprivation. Life expectancy in Glasgow overall, and by deprivation decile, was compared to that in Aberdeen, Dundee and Edinburgh combined, and the life expectancy difference decomposed by age using Arriaga's discrete method.

RESULTS

Life expectancy for the whole Glasgow population was lower than the population of Aberdeen, Dundee and Edinburgh combined. When life expectancy was compared by national income deprivation decile, Glasgow's life expectancy was not systematically lower, and deprivation accounted for over 90 % of the difference. This was reduced to 70 % of the difference when carrying out sensitivity analysis using city-specific income deprivation deciles. In both analyses life expectancy was not systematically lower in Glasgow when stratified by deprivation. Decomposing the differences in life expectancy also showed that the age distribution of mortality was not systematically different in Glasgow after accounting for deprivation.

CONCLUSIONS

Life expectancy is not systematically lower across the Glasgow population compared to Aberdeen, Dundee and Edinburgh combined, once deprivation is accounted for. This provides further evidence that tackling deprivation in Glasgow would probably reduce the health inequalities that exist between Scottish cities. The change in the amount of unexplained difference when carrying out sensitivity analysis demonstrates the difficulties in comparing socioeconomic deprivation between populations, even within the same country and when applying an established ecological measure. Although the majority of health inequality between Glasgow and other Scottish cities is explained by deprivation, the difference in the amount of unexplained inequality depending on the relative context of deprivation used demonstrates the challenges associated with attributing mortality inequalities to an independent 'place effect'.