Income trajectories and self-rated health status in the UK

Longitudinal Income Dynamics and Risk of End-Stage Kidney Disease in Type 2 Diabetes: A South Korean Population-Based Cohort Study

RATIONALE & OBJECTIVE

The prevalence of end-stage kidney disease (ESKD) continues to rise, with socioeconomic status (SES), particularly income, having associations with ESKD risk among individuals with type 2 diabetes (T2D). This study examined the longitudinal association of income changes with ESKD risk among non-elderly adults with T2D in South Korea.

STUDY DESIGN

Population-based retrospective cohort study.

SETTING & PARTICIPANTS

1,481,371 adults aged 30 to 64 years with T2D represented in the South Korean National Health Insurance Service (NHIS) database in 2015 and 2016, followed to 2020.

EXPOSURE

Sustained income levels, income variability, and income changes over five years prior to entry into the study cohort.

OUTCOMES

Primary outcome was progression to ESKD, defined as initiation of dialysis or kidney transplantation.

ANALYTICAL APPROACH

Cox proportional hazards models were used to assess the risk of ESKD, adjusting for demographic, behavioral, and clinical variables.

RESULTS

Compared with those who never reached the lowest income quartile, individuals who spent any time (1-5 years) in the lowest quartile had a higher risk of ESKD (P for trend < 0.001). Conversely, spending 2-5 years in the highest quartile was significantly associated with a lower ESKD risk (P for trend < 0.001), whereas spending only 1 year in the highest quartile was not associated with ESKD risk. Income that dropped from a higher quartile to the lowest quartile was associated with higher risk, and even those moving from the lowest to the highest quartile had a higher ESKD risk than those who remained consistently in the highest quartile. Individuals with the highest income variability exhibited an increased risk of ESKD (hazard ratio 1.14, 95% confidence interval 1.01-1.29, P for trend = 0.02).

LIMITATIONS

Residual confounding, lack of data on medication adherence, and missing laboratory results.

CONCLUSIONS

Dynamic changes in income were associated with ESKD risk among adults with T2D, findings that may inform healthcare policies that address the economic factors potentially contributing to kidney disease progression in South Korean adults with diabetes.

Examining the relationship between income and both mental and physical health among adults in the UK: Analysis of 12 waves (2009-2022) of Understanding Society

There is growing evidence of a causal relationship between income and health. At the same time, pressure on reactive health and care services in the UK is increasing. Previous work to quantify the relationship has focused on particular age groups, conditions, or single-item self-rated health. This article reports findings from a study that aimed to provide more comprehensive estimates with an objective of creating an evidential basis for microsimulation modelling of upstream income interventions. We analyse the relationship between income and two health measures - SF-12 Mental Component Summary (MCS-12) and Physical Component Summary (PCS-12) - across 12 waves (2009/11-2020/22) of Understanding Society: The UK Household Longitudinal Study. Using a 'within-between' model (Model 1), we find that increases in income compared with an individual's average and a higher income compared with the sample average is associated with better mental health (higher MCS-12 score) and better functional physical health (higher PCS-12 score). However, for a given increase in household income (say £100 per month), the association with better mental and physical health is smaller at higher incomes. This suggests that redistribution from high-income to lower income households would increase average population physical and mental health, other things being equal. Using a random-effects logistic regression (Model 2), we similarly find that average income quintile is inversely and monotonically associated with the probability of having clinically significant symptoms of depressive disorders (MCS-12 ≤ 45.6) and physical health problems (PCS-12 score ≤ 50.0), with smaller changes in these probabilities from increases in income at higher points in the income distribution. These findings facilitate microsimulation modelling including an estimation of the impact of changes in QALYs, from changes in income, enabling a more detailed and complete understanding of which socioeconomic interventions might begin to address some of the causes of long-term health conditions that are underpinned by socioeconomic determinants.

Parking and Public Health

PURPOSE OF REVIEW

Parking is a ubiquitous feature of the built environment, but its implications for public health are under-examined. This narrative review synthesizes literature to describe pathways through which parking may affect population health.

RECENT FINDINGS

We begin by contextualizing the issue, outlining key terminology, the sheer scale of land dedicated to parking, and the historical factors that led to this dominant land use. Next, we delineate four pathways linking parking with public health: 1) Promoting driving and car dependency, affecting air pollution, greenhouse-gas emissions, physical activity, traffic-related injuries and fatalities, and accessibility; 2) Creating impervious surfaces, with consequences for urban heat, flooding, water pollution, and green space; 3) Affecting housing affordability and associated health outcomes of this social determinant; and 4) Design, construction, and maintenance, the health impacts of which include on-street parking's positive and negative impacts on safety for all roadway users, air-quality effects of parking's construction and maintenance, and the potential for green parking lots to mitigate some health consequences of impervious surfaces. While evidence supports each pathway, additional empirical research is needed to evaluate impacts of parking on public-health outcomes. As a dominant feature of the built environment with many health implications, parking warrants attention by public-health research and practice.

Income loss and subsequent poor psychological well-being among the Chinese population during the early COVID-19 pandemic

BACKGROUND

The COVID-19 pandemic has had major ramifications for health and the economy at both the individual and collective levels. This study examined exogenous negative changes in household income and their implications on psychological well-being (PWB) among the Chinese population during the COVID-19 pandemic.

METHODS

Data were drawn from the early China COVID-19 Survey, a cross-sectional anonymous online survey administered to the general population in China. Self-reported PWB was measured using a 5-point Likert scale with five questions related to the participants' recent psychological state. Hierarchical multiple linear regression was employed to examine whether income loss during the COVID-19 pandemic was associated with poor psychological health.

RESULTS

This study included 8,428 adults, of which 90% had suffered from a moderate or severe loss of household income due to the early COVID-19 pandemic. Those who had experienced moderate or severe loss of income scored significantly lower on psychological well-being than those who did not experience income loss (19.96 or 18.07 vs. 21.46; P < 0.001); after controlling for confounders, income loss was negatively associated with PWB scores (moderate income loss: B = - 0.603, P < 0.001; severe income loss: B = - 1.261, P < 0.001). An interaction effect existed between the degree of income loss and pre-pandemic income groups. Specifically, participants in the middle-income group who had suffered severe income loss scored the lowest on PWB (B = - 1.529, P < 0.001). There was also a main effect on income loss, such that participants with varying degrees of income loss differed across five dimensions, including anhedonia, sleep problems, irritability or anger, difficulty with concentration, and repeated disturbing dreams related to COVID-19.

CONCLUSIONS

Income loss during the pandemic has had detrimental consequences on psychological well-being, and the magnitude of the impact of income loss on psychological well-being varied according to previous income levels. Future policy efforts should be directed toward improving the psychological well-being of the economically vulnerable and helping them recover from lost income in the shortest time possible.

Understanding the relationship between income and mental health among 16- to 24-year-olds: Analysis of 10 waves (2009-2020) of Understanding Society to enable modelling of income interventions

A substantial body of evidence suggests that young people, including those at the crucial transition points between 16 and 24, now face severe mental health challenges. In this article, we analyse data from 10 waves of a major UK longitudinal household cohort study, Understanding Society, to examine the relationship between income and anxiety and depression among 16- to 24-year-olds. Using random effects logistic regression (Model 1) allowing for whether the individual was depressed in the previous period as well as sex, age, ethnicity, whether the individual was born in the UK, region, rurality, highest qualification, marital status, employment status and attrition, we find a significant and inversely monotonic adjusted association between average net equivalised household income quintiles and clinical threshold levels of depressive symptoms SF-12 Mental Component Summary (MCS score ≤45.6). This means that being in a higher income group is associated with a reduced likelihood of clinically significant depressive symptoms, allowing for observable confounding variables. Using a 'within-between' model (Model 2), we find that apart from among those with the very highest incomes, increases in average net equivalised household income over the course of childhood and adolescence are significantly associated with reduced symptoms of anxiety and depression as measured by a higher SF-12 MCS score. Compared with previous reviews, the data presented here provides an estimate of the magnitude of effect that helps facilitate microsimulation modelling of impact on anxiety and depression from changes in socioeconomic circumstances. This enables a more detailed and complete understanding of the types of socioeconomic intervention that might begin to address some of the causes of youth mental health problems.