Is inconsistent reporting of self-assessed health persistent and systematic? Evidence from the UKHLS.

In this paper, we investigate whether individuals provide consistent responses to self-assessed health (SAH) questions in the UK Household Longitudinal Study (UKHLS), and the potential implications for empirical research in case of inconsistent reporting behaviour. We capitalise on an opportunity in the UKHLS, asking respondents the same SAH question twice: with a self-completion and an open interview mode, within the same household interview over four waves. We estimate multivariate models to explore which individual characteristics are systematically relevant for the likelihood and frequency of inconsistent reporting. About 11-24% of those reported a particular SAH category in the self-completion reported inconsistently in the open interview. The probability of inconsistency is systematically associated with individual's demographics, education, income, employment status, cognitive and non-cognitive skills. The same characteristics also predict the frequency of inconsistent reporting across four UKHLS waves. Analysis of the implications of reporting inconsistencies shows no impact of SAH measurement on the association between income and health. A set of dimensions of people's physiological and biological health, captured using biomarkers, is associated equally with both SAH measures, suggesting that the interview mode does not play a role in the relationship between SAH and more objective health measures.

Pay (for it) as you go: Prepaid energy meters and the heat-or-eat dilemma.

The "heat-or-eat" dilemma, a trade-off typically between food consumption and heating, may elevate public health concerns during the 2022 energy-price crisis. Our paper contributes to the literature by exploring the role of domestic energy prepayment meters (PPMs) in the heat-or-eat dilemma, focusing on the association between PPM use and fruit and vegetable consumption. Using a representative sample of 24,811 individuals residing in Great Britain (January 2019-May 2021), we find robust evidence of lower fruit and vegetable consumption amongst individuals using PPMs, compared to those using post-payment energy bill payment methods. On average, our point estimates suggest that individuals using a PPM consume 2.7 fewer portions of fruit and vegetables per week. Our findings hold when bounding analysis is employed to account for omitted variable bias. Using a suite of IV approaches to further alleviate endogeneity concerns we found that our ordinary least squares results are consistent as opposed to IV models. Further robustness analyses highlight the deleterious impact of PPMs on people's healthy eating habits relevant to the consumption of enough fruit and vegetables. Our results suggest that targeted support for PPM users may have beneficial effects on people's fruit and vegetable consumption patterns.

The Covid-19 pandemic and its impact on socioeconomic inequality in psychological distress in the United Kingdom: An update.

This paper extends earlier on socioeconomic inequality in mental health, measured by the General Health Questionnaire, to include the second national lockdown up to March 2021.

Do socioeconomic health gradients persist over time and beyond income? A distributional analysis using UK biomarker data.

This paper analyses the relationship between health and socioeconomic disadvantage by adopting a dynamic approach accounting for spatial and temporal changes across ten domains including social isolation, environment, financial hardship and security. As a first step we develop a measure of overall multidimensional deprivation and undertake a decomposition analysis to explore the role of breadth and duration of deprivation on shaping the deprivation gradient in health. Subsequently, we employ unconditional quantile regression to conduct a distributional analysis of the gradient to understand how the gradient evolves for people with vulnerability in health. In contrast to the majority of existing studies, we capture health status using a range of nurse measured biomarkers, rather than self reported health measures, taken from the UKHLS and BHPS databases. The first main finding is that the socioeconomic gradient in most of our health measures is not solely attributed to income as it accounts for only 3.8% of total deprivation and thus it is important to account for other domains through a multidimensional deprivation measure in health gradient analysis. Our second finding is the existence of a systematic deprivation gradient for BMI, waist circumference, heart rate, C-reactive protein and HbA1c where evolution over time is an important factor particularly for individuals with greater burden of illness lying at the right tail of the biomarker distribution. Thus cost effective health policy would need to adopt targeted interventions prioritising people experiencing persistent deprivation in dimensions such as housing conditions and social isolation.

Weather, mental health, and mobility during the first wave of the COVID-19 pandemic.

During the first United Kingdom wave of the COVID-19 outbreak, the first lockdown was announced on March 23, 2020, with a final easing of the restrictions on July 4, 2020. Among the most important public health costs of lockdown restrictions are the potential adverse effects on mental health and physical activity. Using data from the UK Household Longitudinal Study and Google COVID-19 Mobility Reports we find evidence of reduced park mobility during the initial period of the first UK lockdown and confirm existing evidence of worsening mental health. Linkage with weather data shows that contrary to popular belief, daily or weekly weather conditions do not exacerbate the mental health consequences of the pandemic, as we found no systematic associations during the first lockdown period; on the other hand, we find systematic links between park mobility and weather over the same period.

Unmet health care need and income-Related horizontal equity in use of health care during the COVID-19 pandemic.

Using monthly data from the Understanding Society (UKHLS) COVID-19 Survey we analyse the evolution of unmet need and assess how the UK health care system performed against the principle of horizontal equity in health care use during the first wave of COVID-19 wave. Unmet need was most evident for hospital care, and less pronounced for primary health services (non-emergency medical helplines, GP consultations, community pharmacist advice, over the counter medications and prescriptions). Despite this, there is no evidence that horizontal equity, with respect to income, was violated for NHS hospital outpatient and inpatient care during the first wave of the pandemic. There is evidence of pro-rich inequities in use of GP consultations, prescriptions and medical helplines at the peak of the first wave, but these were eliminated as the pandemic progressed. There are persistent pro-rich inequities for services that may relate to individuals' ability to pay (over the counter medications and advice from community pharmacists).

The first wave of the COVID-19 pandemic and its impact on socioeconomic inequality in psychological distress in the UK.

We use data from the UK Household Longitudinal Study (UKHLS) to compare measures of socioeconomic inequality in psychological distress, measured by the General Health Questionnaire (GHQ), before (Waves 9 and the Interim 2019 Wave) and during the first wave of the COVID-19 pandemic (April to July 2020). Based on a caseness measure, the prevalence of psychological distress increased from 18.5% to 27.7% between the 2019 Wave and April 2020 with some reversion to earlier levels in subsequent months. Also, there was a systematic increase in total inequality in the Likert GHQ-12 score. However, measures of relative socioeconomic inequality have not increased. A Shapley-Shorrocks decomposition analysis shows that during the peak of the first wave of the pandemic (April 2020) other socioeconomic factors declined in their share of socioeconomic inequality, while age and gender account for a larger share. The most notable increase is evident for younger women. The contribution of working in an industry related to the COVID-19 response played a small role at Wave 9 and the Interim 2019 Wave, but more than tripled its share in April 2020. As the first wave of COVID-19 progressed, the contribution of demographics declined from their peak level in April and chronic health conditions, housing conditions, and neighbourhood characteristics increased their contributions to socioeconomic inequality.

Biomarkers, disability and health care demand.

Using longitudinal data from a representative UK panel, we focus on a group of apparently healthy individuals with no history of disability or major chronic health condition at baseline. A latent variable structural equation model is used to analyse the predictive role of latent baseline biological health, indicated by a rich set of biomarkers, and other personal characteristics, in determining the individual's disability state and health service utilisation five years later. We find that baseline biological health affects future health service utilisation very strongly, via progression to functional disability channel. We also find systematic income gradients in future disability risks, with those of higher income experiencing a lower progress to disability. Our model reveals that observed pro-rich inequity in health care utilisation, is driven by the fact that higher-income people tend to make greater use of health care treatment, for any given biological health and disability status; this is despite the lower average need for treatment shown by the negative association of income with both baseline ill biological health and disability progression risk. Factor loadings for latent baseline health show that a broader set of blood-based biomarkers, rather than the current focus mainly on blood pressure, cholesterol and adiposity, may need to be considered for public health screening programs.

Using biomarkers to predict healthcare costs: Evidence from a UK household panel.

We investigate the extent to which healthcare service utilisation and costs can be predicted from biomarkers, using the UK Understanding Society panel. We use a sample of 2314 adults who reported no history of diagnosed long-lasting health conditions at baseline (2010/11), when biomarkers were collected. Five years later, their GP, outpatient (OP) and inpatient (IP) utilisation was observed. We develop an econometric technique for count data observed within ranges and a method of combining administrative reference cost data with the survey data without exact individual-level matching. Our composite biomarker index (allostatic load) is a powerful predictor of costs: for those with a baseline allostatic load of at least one standard deviation (1-s.d.) above mean, a 1-s.d. reduction reduces GP, OP and IP costs by around 18%.

Regional inequalities in adiposity in England: distributional analysis of the contribution of individual-level characteristics and the small area obesogenic environment.

We use nationally representative English data to examine regional variations in body mass index (BMI) and waist circumference (WC), and to explore their underlying sources. Beyond our "at the mean" analysis, Shapley decomposition combined with unconditional quantile regression analysis allow us to explore the relative contribution of small-area level proxies of the obesogenic environment as opposed to our set of individual-level characteristics, across the whole adiposity distribution. We find that the regional BMI differences, that are more evident towards the right tails of its distribution, are fully accounted for by the neighbourhood obesogenic environment. The latter exerts an independent contribution to excess adiposity over and above the potential mediating role of individual-level lifestyle and socio-economic position (SEP). Overall, the relative contribution of demographics (age and gender) becomes less evident moving to higher quantiles of the BMI distribution, while that of obesogenic environment, individual-level lifestyle and SEP measures becoming more relevant. The neighbourhood obesogenic environment is also much more relevant in the tails of the WC distribution. The role of the obesogenic environment on excess adiposity is more pronounced for women than men. Overall, our results highlight that policies that aim to tackle excess adiposity should address both people and places.

A latent class approach to inequity in health using biomarker data.

We adopt an empirical approach to analyse, measure and decompose inequality of opportunity (IOp) in health, based on a latent class model. This addresses some of the limitations that affect earlier work in this literature concerning the definition of types, such as partial observability, the ad hoc selection of circumstances, the curse of dimensionality and unobserved type-specific heterogeneity that may lead to biased estimates of IOp. We apply our latent class approach to measure IOp in allostatic load, a composite measure of biomarker data. Using data from Understanding Society: The UK Household Longitudinal Study (UKHLS), we find that a latent class model with three latent types best fits the data, with the corresponding types characterised in terms of differences in their observed circumstances. Decomposition analysis shows that about two thirds of the total inequalities in allostatic load can be attributed to the direct and indirect contribution of circumstances and that the direct contribution of effort is small. Further analysis conditional on age-sex groups reveals that the relative (percentage) contribution of circumstances to the total inequalities remains mostly unaffected and the direct contribution of effort remains small.

Ex ante inequality of opportunity in health, decomposition and distributional analysis of biomarkers.

We use a set of biomarkers to measure inequality of opportunity (IOp) in the risk of major chronic conditions in the UK. Applying a direct ex ante IOp approach, we find that inequalities in biomarkers attributed to circumstances account for a non-trivial part of the total variation. For example, observed circumstances account for 20 % of the total inequalities in our composite measure of multi-system health risk, allostatic load. We propose an extension to the decomposition of ex ante IOp to complement the mean-based approach, analysing the contribution of circumstances across the quantiles of the biomarker distributions. Shapley decompositions show that, for most of the biomarkers, the percentage contribution of socioeconomic circumstances (education and childhood socioeconomic status), relative to differences attributable to age and gender, increase towards the right tail of the biomarker distribution, where health risks are more pronounced.

Biomarkers as precursors of disability.

Some social surveys now collect physical measurements and markers derived from biological samples, in addition to self-reported health assessments. This information is expensive to collect; its value in medical epidemiology has been clearly established, but its potential contribution to social science research is less certain. We focused on disability, which results from biological processes but is defined in terms of its implications for social functioning and wellbeing. Using data from waves 2 and 3 of the UK Understanding Society panel survey as our baseline, we estimated predictive models for disability 2-4 years ahead, using a wide range of biomarkers in addition to self-assessed health (SAH) and other socio-economic covariates. We found a quantitatively and statistically significant predictive role for a large set of nurse-collected and blood-based biomarkers, over and above the strong predictive power of self-assessed health. We also applied a latent variable model accounting for the longitudinal nature of observed disability outcomes and measurement error in in SAH and biomarkers. Although SAH performed well as a summary measure, it has shortcomings as a leading indicator of disability, since we found it to be biased in the sense of over- or under-sensitivity to certain biological pathways.

Parametric models for biomarkers based on flexible size distributions.

Recent advances in social science surveys include collection of biological samples. Although biomarkers offer a large potential for social science and economic research, they impose a number of statistical challenges, often being distributed asymmetrically with heavy tails. Using data from the UK Household Panel Survey, we illustrate the comparative performance of a set of flexible parametric distributions, which allow for a wide range of skewness and kurtosis: the four-parameter generalized beta of the second kind (GB2), the three-parameter generalized gamma, and their three-, two-, or one-parameter nested and limiting cases. Commonly used blood-based biomarkers for inflammation, diabetes, cholesterol, and stress-related hormones are modelled. Although some of the three-parameter distributions nested within the GB2 outperform the latter for most of the biomarkers considered, the GB2 can be used as a guide for choosing among competing parametric distributions for biomarkers. Going "beyond the mean" to estimate tail probabilities, we find that GB2 performs fairly well with some disparities at the very high levels of glycated hemoglobin and fibrinogen. Commonly used linear models are shown to perform worse than almost all the flexible distributions.

Concordance of health states in couples: Analysis of self-reported, nurse administered and blood-based biomarker data in the UK Understanding Society panel.

We use self-reported health measures, nurse-administered measurements and blood-based biomarkers to examine the concordance between health states of partners in marital/cohabiting relationships in the UK. A model of cumulative health exposures is used to interpret the empirical pattern of between-partner health correlation in relation to elapsed relationship duration, allowing us to distinguish non-causal correlation due to assortative mating from potentially causal effects of shared lifestyle and environmental factors. We find important differences between the results for different health indicators, with strongest homogamy correlations observed for adiposity, followed by blood pressure, heart rate, inflammatory markers and cholesterol, and also self-assessed general health and functional difficulties. We find no evidence of a "dose-response relationship" for marriage duration, and show that this suggests - perhaps counterintuitively - that shared lifestyle factors and homogamous partner selection make roughly equal contributions to the concordance we observe in most of the health measures we examine.

Socio-economic inequalities in C-reactive protein and fibrinogen across the adult age span: Findings from Understanding Society.

Systemic inflammation has been proposed as a physiological process linking socio-economic position (SEP) to health. We examined how SEP inequalities in inflammation -assessed using C-reactive protein (CRP) and fibrinogen- varied across the adult age span. Current (household income) and distal (education) markers of SEP were used. Data from 7,943 participants (aged 25+) of Understanding Society (wave 2, 1/2010-3/2012) were employed. We found that SEP inequalities in inflammation followed heterogeneous patterns by age, which differed by the inflammatory marker examined rather than by SEP measures. SEP inequalities in CRP emerged in 30s, increased up to mid-50s or early 60 s when they peaked and then decreased with age. SEP inequalities in fibrinogen decreased with age. Body mass index (BMI), smoking, physical activity and healthy diet explained part, but not all, of the SEP inequalities in inflammation; in general, BMI exerted the largest attenuation. Cumulative advantage theories and those considering age as a leveler for the accumulation of health and economic advantages across the life-span should be dynamically integrated to better understand the observed heterogeneity in SEP differences in health across the lifespan. The attenuating roles of health-related lifestyle indicators suggest that targeting health promotion policies may help reduce SEP inequalities in health.

Alternative measures to BMI: Exploring income-related inequalities in adiposity in Great Britain.

Socio-economic inequalities in adiposity are of particular interest themselves but also because they may be associated with inequalities in overall health status. Using cross-sectional representative data from Great Britain (1/2010-3/2012) for 13,138 adults (5652 males and 7486 females) over age 20, we aimed to explore the presence of income-related inequalities in alternative adiposity measures by gender and to identify the underlying factors contributing to these inequalities. For this reason, we employed concentration indexes and regression-based decomposition techniques. To control for non-homogeneity in body composition, we employed a variety of adiposity measures including body fat (absolute and percentage) and central adiposity (waist circumference) in addition to the conventional body mass index (BMI). The body fat measures allowed us to distinguish between the fat- and lean-mass components of BMI. We found that the absence of income-related obesity inequalities for males in the existing literature may be attributed to their focus on BMI-based measures. Pro-rich inequalities were evident for the fat-mass and central adiposity measures for males, while this was not the case for BMI. Irrespective of the adiposity measure applied, pro-rich inequalities were evident for females. The decomposition analysis showed that these inequalities were mainly attributable to subjective financial well-being measures (perceptions of financial strain and material deprivation) and education, with the relative contribution of the former being more evident in females. Our findings have important implications for the measurement of socio-economic inequalities in adiposity and indicate that central adiposity and body composition measures should be included health policy agendas. Psycho-social mechanisms, linked to subjective financial well-being, and education -rather than income itself-are more relevant for tackling inequalities.

Association of Adiposity and Mental Health Functioning across the Lifespan: Findings from Understanding Society (The UK Household Longitudinal Study).

BACKGROUND: Evidence on the adiposity-mental health associations is mixed, with studies finding positive, negative or no associations, and less is known about how these associations may vary by age. OBJECTIVE: To examine the association of adiposity -body mass index (BMI), waist circumference (WC) and percentage body fat (BF%)- with mental health functioning across the adult lifespan. METHODS: Data from 11,257 participants (aged 18+) of Understanding Society: the UK Household Longitudinal Study (waves 2 and 3, 5/2010-7/2013) were employed. Regressions of mental health functioning, assessed by the Mental Component Summary (MCS-12) and the General Health Questionnaire (GHQ-12), on adiposity measures (continuous or dichotomous indicators) were estimated adjusted for covariates. Polynomial age-adiposity interactions were estimated. RESULTS: Higher adiposity was associated with poorer mental health functioning. This emerged in the 30s, increased up to mid-40s (all central adiposity and obesity-BF% measures) or early 50s (all BMI measures) and then decreased with age. Underlying physical health generally accounted for these associations except for central adiposity, where associations remained statistically significant from the mid-30s to 50s. Cardiovascular, followed by arthritis and endocrine, conditions played the greatest role in attenuating the associations under investigation. CONCLUSIONS: We found strong age-specific patterns in the adiposity-mental health functioning association that varied across adiposity measures. Underlying physical health had the dominant role in attenuating these associations. Policy makers and health professionals should target increased adiposity, mainly central adiposity, as it is a risk factor for poor mental health functioning in those aged between mid-30s to 50 years.

Obesity persistence and duration dependence: evidence from a cohort of US adults (1985-2010).

This study investigates dynamic patterns of obesity persistence and identifies the determinants of obesity-spell exits and re-entries. We utilize longitudinal data from the NLSY79 covering the period 1985-2010. Non-parametric techniques are applied to investigate the relationship between exit from obesity and spell duration. Multivariate discrete hazard models are also estimated, taking into account duration dependence and observed and time-invariant unobserved heterogeneity. In all cases, the probability of exiting obesity is inversely related to the duration of the obesity spell. Without controlling for unobserved heterogeneity, the probability of exit after one wave in obesity is 31.5 per cent; it is reduced to 3.8 per cent after seven or more waves. When time-invariant unobserved heterogeneity is taken into account, the estimated probabilities are slightly larger and broadly similar (36.8 and 10.3, respectively), which suggests that the identified negative duration dependence is not primarily due to composition effects. The obtained results indicate that public health interventions targeting the newly obese may be particularly effective at reducing incidence of long durations of obesity.