Poorest Fifth Research Articles

The cost-of-living crisis is feeding the paradox of obesity and food insecurities in the UK.

Interconnections between the cost of living crisis and health inequality.

Socioeconomic inequality in awareness, treatment and control of diabetes among adults in India: Evidence from National Family Health Survey of India (NFHS), 2019–2021

Diabetes is a growing epidemic and a major threat to most of the households in India. Yet, there is little evidence on the extent of awareness, treatment, and control (ATC) among adults in the country. In this study, we estimate the prevalence and ATC of diabetes among adults across various sociodemographic groups and states of India. We used data on 2,078,315 individuals aged 15 years and over from the recent fifth round, the most recent one, of the National Family Health Survey (NFHS-5), 2019–2021, that was carried out across all the states of India. Diabetic individuals were identified as those who had random blood glucose above 140 mg/dL or were taking diabetes medication or has doctor-diagnosed diabetes. Diabetic individuals who reported diagnosis were labelled as aware, those who reported taking medication for controlling blood glucose levels were labelled as treated and those whose blood glucose levels were < 140 mg/dL were labelled as controlled. The estimates of prevalence of diabetes, and ATC were age-sex adjusted and disaggregated by household wealth quintile, education, age, sex, urban–rural residence, caste, religion, marital status, household size, and state. Concentration index was used to quantify socioeconomic inequalities and multivariable logistic regression was used to estimate the adjusted differences in those outcomes. We estimated diabetes prevalence to be 16.1% (15.9–16.1%). Among those with diabetes, 27.5% (27.1–27.9%) were aware, 21.5% (21.1–21.7%) were taking treatment and 7% (6.8–7.1%) had their diabetes under control. Across the states of India, the adjusted rates of awareness varied from 14.4% (12.1–16.8%) to 54.4% (40.3–68.4%), of treatment from 9.3% (7.5–11.1%) to 41.2% (39.9–42.6%), and of control from 2.7% (1.6–3.7%) to 11.9% (9.7–14.0%). The age-sex adjusted rates were lower (p < 0.001) among the poorer and less educated individuals as well as among males, residents of rural areas, and those from the socially backward groups Among individuals with diabetes, the richest fifth were respectively 12.4 percentage points (pp) (11.3–13.4; p < 0.001), 10.5 pp (9.7–11.4; p < 0.001), and 2.3 pp (1.6–3.0; p < 0.001) more likely to be aware, getting treated, and having diabetes under control, than the poorest fifth. The concentration indices of ATC were 0.089 (0.085–0.092), 0.083 (0.079–0.085) and 0.017 (0.015–0.018) respectively. Overall, the ATC of diabetes is low in India. It is especially low the poorer and the less educated individuals. Targeted interventions and management can reduce the diabetes burden in India.

Ethnic diversity and mortality in northwest Burkina Faso: An analysis of the Nouna health and demographic surveillance system from 2000 to 2012.

Ethnic diversity has been a topic of contention across the globe, contrasted with economic development, social security, and political stability. The link between health and ethnic diversity is not yet well established especially in low-middle- income countries. Our study aims to explore the association between ethnic diversity and all-cause mortality in rural areas of Burkina Faso. We used data from the Nouna Health & Demographic Surveillance System (HDSS) collected between 2000 and 2012. To derive Standardized Mortality Ratios (SMR), the observed number of deaths was compared to the expected deaths based on the entire HDSS taking into account sex, age, rainy season, calendar year, and village. SMR were calculated for ethnic and religious diversity on a village level (using the Simpson Index), sub-region, wealth, and distance to Healthcare Facilities (HCF). Furthermore, we modeled SMR with a multilevel random intercept Poisson regression considering individual ethnic and religious groups in addition to the above-mentioned village-level information. Village wealth (poorest fifth: SMR 1.07; 95% CI: 1.02-1.13, richest fifth: SMR 0.85; 95% CI: 0.82-0.88), distance to HCF (within the village: SMR 0.88; 95% CI: 0.85-0.91, further than 5km: SMR 1.13; 95% CI: 1.10-1.16), and sub-region showed significant associations with overall mortality. Villages belonging to the third with the highest ethnic diversity had lowered SMR (0.86; 95% CI: 0.84-0.89) compared to the entire HDSS, while those belonging to the lowest diversity third yielded elevated SMR (1.13; 95% CI: 1.09-1.17). The multilevel model confirmed the association. Our study showed that historically established ethnic diversity in rural areas of Burkina Faso was associated with lower all-cause mortality. Generally, the literature suffers from a lack of standardization in defining ethnic diversity, along with measuring it. More research is needed to understand this relation and to establish it in different settings.

Towards an Understanding of Population Health Data in a Single NHS Trust during COVID-19.

The objective of this study was to determine the further care needs of people discharged from the hospital following a COVID-19 illness from April–September 2020. Methods: In partnership with an NHS trust in the UK, data analysis was undertaken by linking data from the Trust, to facilitated a triage process. The intention was to provide information in a format that enabled an examination of the population data and highlight any inequality in provision. Data were mapped onto the indices of multiple deprivation, and a range of text and graphical methods were used to represent the population data to the hospital leadership. The visual representation of the demographics and deprivation of people discharged during a critical period of the pandemic was intended to support planning for community services. The results demonstrated that just under half of those discharged were from the poorest fifth of the English population and that just under half were aged 75 or older. This reflected the disproportional effect of COVID-19 on those who were poorer, older or had pre-existing multiple morbidities. Referral to community or outpatient services was informed by the analysis, and further understanding of the diversity of the population health was established in the Trust. Conclusion: By identifying the population and mapping to the IMD, it was possible to show that over half of discharged patients were from deprived communities, and there was significant organisational learning bout using data to identify inequalities.. The challenge of planning services that target underserved communities remains an important issue following the pandemic, and lessons learnt from one health system are being shared.

1539Australia’s worsening mental health – what’s next?

Abstract Background The population prevalence of mental illness over time, and by sociodemographic subgroups, are important benchmark data. Examining reliable population level data can highlight groups with greater mental-illness related symptom burden and inform policy and strategy. Methods Secondary analysis of Australian National Health Surveys (n = 78,204) from 2001-02 to 2017-18. Trends in the prevalence of very high scores on the Kessler-10 (K10), a measure of psychological distress capturing symptoms of affective and anxiety disorders, were examined by time, age, gender, and socioeconomic status. Data were standardised to the 2001 Australian census population on the strata of sex and age. Results In 2017-18, the rate of probable mental illness was estimated at 5.1%, a 1.5% increase (representing an additional 367,000 Australians) since 2007. In 2017-18, the subgroups with the highest rates were women aged 18-24 (8.01%, 95% CI = 5.9%-10.2%), and the poorest fifth of Australians (8.02%, 95% CI = 7.0%-9.0%). Women aged 55-64 demonstrated the greatest increase in rates (2001: 3.5%, 95% CI = 2.5%-4.6%; 2017: 7.2%, 95% CI = 5.9%-8.5%; z = 4.10, p ≤ 0.001). Conclusions Despite efforts to improve population mental health, rates of probable mental illness in Australia have increased since 2007. Findings will be discussed in conjunction to extant social and health policies, and potential gaps in the delivery of gold-standard mental health care. Key messages The rate of probable mental illness in Australia seem to be increasing, especially in women aged 55-64, and those from low-SES backgrounds.

Awareness, treatment, and control of hypertension in adults aged 45 years and over and their spouses in India: A nationally representative cross-sectional study.

Lack of nationwide evidence on awareness, treatment, and control (ATC) of hypertension among older adults in India impeded targeted management of this condition. We aimed to estimate rates of hypertension ATC in the older population and to assess differences in these rates across sociodemographic groups and states in India. We used a nationally representative survey of individuals aged 45 years and over and their spouses in all Indian states (except one) in 2017 to 2018. We identified hypertension by blood pressure (BP) measurement ≥140/90 mm Hg or self-reported diagnosis if also taking medication or observing salt/diet restriction to control BP. We distinguished those who (i) reported diagnosis ("aware"); (ii) reported taking medication or being under salt/diet restriction to control BP ("treated"); and (iii) had measured systolic BP <140 and diastolic BP <90 ("controlled"). We estimated age-sex adjusted hypertension prevalence and rates of ATC by consumption quintile, education, age, sex, urban-rural, caste, religion, marital status, living arrangement, employment status, health insurance, and state. We used concentration indices to measure socioeconomic inequalities and multivariable logistic regression to estimate fully adjusted differences in these outcomes. Study limitations included reliance on BP measurement on a single occasion, missing measurements of BP for some participants, and lack of data on nonadherence to medication. The 64,427 participants in the analysis sample had a median age of 57 years: 58% were female, and 70% were rural dwellers. We estimated hypertension prevalence to be 41.9% (95% CI 41.0 to 42.9). Among those with hypertension, we estimated that 54.4% (95% CI 53.1 to 55.7), 50.8% (95% CI 49.5 to 52.0), and 28.8% (95% CI 27.4 to 30.1) were aware, treated, and controlled, respectively. Across states, adjusted rates of ATC ranged from 27.5% (95% CI 22.2 to 32.8) to 75.9% (95% CI 70.8 to 81.1), from 23.8% (95% CI 17.6 to 30.1) to 74.9% (95% CI 69.8 to 79.9), and from 4.6% (95% CI 1.1 to 8.1) to 41.9% (95% CI 36.8 to 46.9), respectively. Age-sex adjusted rates were lower (p < 0.001) in poorer, less educated, and socially disadvantaged groups, as well as for males, rural residents, and the employed. Among individuals with hypertension, the richest fifth were 8.5 percentage points (pp) (95% CI 5.3 to 11.7; p < 0.001), 8.9 pp (95% CI 5.7 to 12.0; p < 0.001), and 7.1 pp (95% CI 4.2 to 10.1; p < 0.001) more likely to be aware, treated, and controlled, respectively, than the poorest fifth. Hypertension prevalence was high, and ATC of the condition were low among older adults in India. Inequalities in these indicators pointed to opportunities to target hypertension management more effectively and equitably on socially disadvantaged groups.

Education, immigration and rising mental health inequality in Sweden.

Educational and income gradients in health are well established in the literature but there is need for a better understanding of how mental health inequalities change over time, and what drives the development. We aim to study how psychiatric diagnosis and its income-related inequality have changed over time in Sweden and to make a first attempt at disentangling the development by decomposing any changes in terms of changes in two important demographic characteristics: education and migration background. We use administrative patient data to study psychiatric inpatient diagnosis in the years 1994 and 2011. The study population comprises all individuals aged 31-64 years living in Sweden. Income-related inequalities are measured by the Concentration Index (CI). We decompose changes in the probability of receiving a diagnosis and changes in income-related inequality over time to understand the role of changing demographics. Our results show that over the study period the probability of receiving a psychiatric inpatient diagnosis increased by 12.6%, while the relative and absolute income-related inequalities in diagnosis increased by 48.2% and 66.7% respectively. In 2011, more than half of psychiatric inpatients were found among the poorest fifth of the population. The decomposition results suggest that changes in education and migration background have not played a substantial role in determining these increases. Education levels increased substantially over the study period which would be expected to protect against mental ill-health. Instead, we find that diagnoses have become more concentrated amongst the lowest educated individuals and the lowest income families, groups who appear to be increasingly disadvantaged. The growing proportion of individuals with foreign background in Sweden does, in fact, predict small increases in the probability of diagnosis, while the impact on diagnosis inequality varies depending on the definition of foreign background.

Socioeconomic inequality in life expectancy in India

IntroductionConcern for health inequalities is an important driver of health policy in India; however, much of the empirical evidence regarding health inequalities in the country is piecemeal focusing only on...

Labour Income, Social Transfers and Child Poverty

This paper documents the variation in living standards of the poorest fifth of children in rich (and some middle-income) nations, with a focus on the relative importance and interaction of social transfers (net of taxes) and labour market incomes. Overall, the cross-national variation in the disposable income of disadvantaged children is comprised equally of variation in market and transfer income (with the two negatively correlated). The English-speaking countries stand out as all having relatively low market incomes, but substantial variation in transfer income. Their low market incomes reflect low employment hours in Australia and primarily low hours in the UK and Ireland, while in the US and Canada low hours and low pay contribute equally. Comparing incomes prior to and after the 2008 financial crisis, the real disposable incomes of the poorest fifth decreased substantially in Greece, Spain and Ireland, but were relatively stable in other rich nations.

Who attends out-of-hours general practice appointments? Analysis of a patient cohort accessing new out-of-hours units

ObjectivesThis report describes the patients who used additional out-of-hours (OOH) appointments offered through a UK scheme intended to increase patient access to primary care by extending OOH provision.DesignCohort study and...

Within country inequalities in caesarean section rates: observational study of 72 low and middle income countries

ObjectiveTo provide an update on economic related inequalities in caesarean section rates within countries.DesignSecondary analysis of demographic and health surveys and multiple indicator cluster surveys.Setting72 low and middle income countries...

Spending on Health Care in the Netherlands: Not Going So Dutch

The Netherlands is among the top spenders on health in the OECD. We document the life-cycle profile, concentration and persistence of this expenditure using claims data covering both curative and long-term care expenses for the full Dutch population. Spending on health care is strongly concentrated: the one per cent of individuals with the highest levels of expenditure account for one quarter of the aggregate in any one year. Averaged over three years, the top one per cent still accounts for more than a fifth of the total, indicating a very high degree of persistence in the largest expenses. Spending on long-term care, which amounts to one third of all expenditure on health care, is even more concentrated: the top one per cent accounts for more than half of total spending on this type of care. Average expenditure rises steeply with age and even more so with proximity to death. Spending on individuals in their last year of life absorbs one tenth of aggregate health care expenditure. In a given year, spending on health care is highly skewed toward individuals with lower incomes. Average expenditure on the poorest fifth is more than three times that on the richest fifth. Spending on long-term care is five times more concentrated on the poor.

Eliciting the Level of Health Inequality Aversion in England

Health inequality aversion parameters can be used to represent alternative value judgements about policy concern for reducing health inequality versus improving total health. In this study, we use data from an online survey of the general public in England (n = 244) to elicit health inequality aversion parameters for both Atkinson and Kolm social welfare functions. We find median inequality aversion parameters of 10.95 for Atkinson and 0.15 for Kolm. These values suggest substantial concern for health inequality among the English general public which, at current levels of quality adjusted life expectancy, implies weighting health gains to the poorest fifth of people in society six to seven times as highly as health gains to the richest fifth. © 2016 The Authors. Health Economics published by John Wiley & Sons, Ltd.

Medical Spending in Denmark

AbstractUsing full population longitudinal data from merged administrative registers for Denmark, we document that medical spending is highly concentrated in the population and is persistent through time at the individual level. In addition, we provide overviews of institutional details of the Danish health care system, aggregate trends in health care expenditures and the relevant register data. Nearly two‐thirds of expenditures are on hospitals and one‐fifth on long‐term care, with the remainder roughly equally split between primary care and prescription drugs. Health expenditures are higher for men than for women from ages 61 to 78, and otherwise higher for women. Between ages 50 and 80, hospital expenditures more than triple for men while more than doubling for women, and total health expenditures quadruple for men while tripling for women. The top 1 per cent of all spenders account for nearly one‐quarter of total spending in a given year, and averaging over three years only reduces this fraction to one‐fifth. The top 20 per cent of spenders in a given year are more likely to remain in that category two years later than not. The poorest fifth of the population aged 25 and above are responsible for more than twice as much spending on health as the richest, and this reverse social gradient is even stronger for long‐term care and is stronger among men than among women, especially in hospital expenses. Expenditures in the year (over the three years) before death are nearly 12 times (respectively nine times) higher than average, but nevertheless are only 11 per cent (respectively a quarter) of lifetime spending. Out‐of‐pocket expenses on prescription drugs only amount to 3 per cent of total health expenditures and are less concentrated than these.

Spending on Health Care in the Netherlands: Not Going So Dutch

AbstractThe Netherlands is among the top spenders on health in the OECD. We document the life‐cycle profile, concentration and persistence of this expenditure using claims data covering both curative and long‐term care expenses for the full Dutch population. Spending on health care is strongly concentrated: the 1 per cent of individuals with the highest levels of expenditure account for one‐quarter of the aggregate in any one year. Averaged over three years, the top 1 per cent still account for more than a fifth of the total, indicating a very high degree of persistence in the largest expenses. Spending on long‐term care, which amounts to one‐third of all expenditure on health care, is even more concentrated: the top 1 per cent account for more than half of total spending on this type of care. Average expenditure rises steeply with age and even more so with proximity to death. Spending on individuals in their last year of life absorbs one‐tenth of aggregate health care expenditure. In a given year, spending on health care is highly skewed toward individuals with lower incomes. Average expenditure on the poorest fifth is more than three times that on the richest fifth.

Spending on Health Care in the Netherlands: Not Going So Dutch

The Netherlands is among the top spenders on health in the OECD. We document the life-cycle profile, concentration and persistence of this expenditure using claims data covering both curative and long-term care expenses for the full Dutch population. Spending on health care is strongly concentrated: the one per cent of individuals with the highest levels of expenditure account for one quarter of the aggregate in any one year. Averaged over three years, the top one per cent still accounts for more than a fifth of the total, indicating a very high degree of persistence in the largest expenses. Spending on long-term care, which amounts to one third of all expenditure on health care, is even more concentrated: the top one per cent accounts for more than half of total spending on this type of care. Average expenditure rises steeply with age and even more so with proximity to death. Spending on individuals in their last year of life absorbs one tenth of aggregate health care expenditure. In a given year, spending on health care is highly skewed toward individuals with lower incomes. Average expenditure on the poorest fifth is more than three times that on the richest fifth. Spending on long-term care is five times more concentrated on the poor.

Selfishness, Greed and Capitalism

It is often asserted that supporters of a market economy believe that ‘greed is good’. This is simply not true. Economists know that people are capable of a range of thoughts, feelings, motivations and emotions and a market economy works regardless of whether people are selfish or altruistic. A further straw man often erected by opponents of market economies is that free-market economists assume that individuals always behave with perfect rationality. Again, this is not true, though it is assumed that individuals are better placed to know their own preferences than government planners or officials. It is frequently suggested that the rich are getting richer while the poor get poorer. For example: ‘[the] late 70s saw the most equal time in British history, but since then the rich have got richer and the poor poorer’ (Polly Toynbee writing in 2012). This is false. Between 1977 and 2011/12, the incomes of the poorest fifth of the population have risen by 93 per cent. It is also not true that median earnings have stagnated. Median earners saw their hourly wage rise by 62 per cent between 1986 and 2011. The average number of hours worked by British workers continues to fall. It fell from 37.7 hours a week in 2000 to 36.4 per week in 2011, having fallen from 38.1 hours in 1992. Fewer than 12 per cent of British employees work more than fifty hours a week. Working hours in Britain are neither much longer nor much shorter than those in other wealthy countries. The reason we have not reduced our working hours to the extent that Keynes, for example, believed likely is that we aspire to a lifestyle that is better than a typical 1930s working class lifestyle without central heating, hot running water, a telephone, wall-to-wall carpets, a car, an indoor toilet, a computer, a television and so on. Many commentators argue that the UK is suffering from growing inequality. For example, Deborah Hargreaves, director of The High Pay Centre, asserts that ‘Inequality has been rising rapidly in Britain for the past 30 years … If the growth in inequality continues at its current rate, we are heading towards Victorian extremes in the next 20 years.’ Such statements are not true. The peak in inequality was in 1990 and the income gap has been flat or in decline ever since. Between 1990 and 2006–7, those in the bottom quintile increased their disposable income by 40 per cent, a faster rate than was seen among the top quintile, whose disposable income rose by only 29 per cent. In 2011–12, income inequality in Britain fell to its lowest level since 1986. It is only within the top 10 per cent of income earners that incomes are becoming more unequal. Once income has been redistributed through tax, cash payments and benefits in kind, the ratio between the incomes of the top and bottom fifth of the population is reduced from 14 to 1 to 4 to 1. This is almost exactly the same ratio as in 1987. Many claims have been made about the relationship between inequality and various social outcomes such as murder rates, health outcomes and so on, especially in The Spirit Level. However, the claims do not stand up to thorough scrutiny. They are often reliant on outliers within the data or the particular way in which the relevant countries were selected. These issues have been studied much more thoroughly by specialists who come to more nuanced conclusions about how social outcomes can be improved. The authors of The Spirit Level argue that there is a relationship between reduced inequality and happiness. However, there is a stronger relationship between happiness and higher average incomes. While there is good reason to be sceptical about ‘happiness economics’ it would seem just from these figures that the best strategy to increase happiness would be to reduce poverty through faster national income growth – even if this led to higher inequality. It is not true that social mobility has ground to a halt, nor is Alan Milburn correct when he says that ‘we still live in a country where, invariably, if you’re born poor, you die poor’. Over the last generation, if the income of a boy’s parents was in the poorest quarter of the income distribution, the probability of the boy moving into the top half of the income distribution is 37 per cent. If the income of a boy’s parents was in the top quarter of the income distribution, the probability of the boy moving into the bottom half of the income distribution is 33 per cent. There is substantial mobility within society.

Aggressively Regressive: The 'Sin Taxes' that Make the Poor Poorer

Poorest hit hardest by consumption taxes, new research shows Summary The poorest twenty per cent of households in Britain spend an average of £1,286 per year on ‘sin taxes’, including betting taxes, vehicle excise duty, air passenger duty, ‘green taxes’ and duty on tobacco, alcohol and motor fuels. In addition, they also spend £1,165 on VAT. The £1,286 spent on sin taxes represents 11.4 per cent of the disposable income of Britain’s poorest fifth of households. For every eight pounds spent by the poorest fifth of households, one pound is taken from them in sin taxes. Despite significantly lower rates of alcohol consumption and car ownership, the poorest income group spends twice as much on sin taxes and VAT than the wealthiest income group as a proportion of their income. Tax is the single biggest source of expenditure for those who live in poverty and indirect taxes are a major cause of Britain’s cost of living crisis. The average smoker from the poorest fifth of households spends between 18 and 22 per cent of their disposable income on cigarettes. The tax on these cigarettes consumes 15 to 17 per cent of their income. Motoring taxes absorb eight per cent of the income of a typical driver from the bottom fifth of households. Alcohol taxes consume 2 to 4 per cent of the income of moderate drinkers in the bottom fifth of households. People in the bottom fifth of the income stream who drink moderately, smoke and drive a car spend 37 per cent of their disposable household income on sin taxes and VAT. The comparable figure for people in the top fifth of the income stream is 15 per cent. Halving ‘sin taxes’ on fuel, tobacco and alcohol, scrapping green energy subsidies and returning the rate of VAT to 15 per cent would reduce tax evasion, reduce black market activity, improve labour market flexibility and stimulate the economy. Above all, it would put money back in the pockets of those who are in greatest need of it.

Transport and health

Transport - whether walking, cycling, travelling in cars, buses, trains, ships or planes - affects health. It provides access to education, work, leisure activities, family and friends. Walking and cycling are cheap, simple, everyday, forms of physical activity, and don't require dedicated sports and exercise facilities or time. Walking or cycling to work increases fitness, potentially fulfilling physical activity recommendations. Pedestrian-permeable environments are associated with 6lb lower mean population weight. However, motor vehicles cause injury, noise and air pollution; promote inactivity; reduce social interaction; and increase inequalities. Particulate air pollution precipitates cardiorespiratory mortality and morbidity; benzene causes leukaemia; greenhouse gas emissions exacerbate climate change. Community severance, whereby access to goods, services, and people beyond a road are prevented or impeded by the traffic is important. Appleyard and Lintell's study in San Francisco and Hart's recent study in Bristol found the number of friends and acquaintances falling dramatically as traffic volume increased. It should no longer be acceptable to create a residential street with a steady flow of traffic; streets should be viewed as community facilities, not just passages for vehicles. Until the Transport and Health Study Group's 1991 report Health on the Move, these effects were considered in isolation, not holistically. This often still applies but is becoming less true for transport professionals and public health specialists. Transport contributes to health inequalities. It affects access to education and employment, important health determinants. Areas affected by community severance tend to be poorer. Social exclusion occurs when access assumes use of private cars or public transport that is unaffordable to some. Air and noise pollution and injuries are commoner in deprived areas with higher road and traffic density. Social class V children have five times the mortality rate from road traffic as social class I. The poor are both exposed to higher levels of pollution and more susceptible due to pre-existing disease. Poor diet and worse health care access further exacerbate inequalities. In 2005, 45% of people aged 70+ had mobility difficulties, as did 14% of all adults; those in the poorest fifth of households were five times likelier than the wealthiest to have mobility difficulties. Country dwellers make more trips and spend longer travelling than those in urban areas, except London. Rural households are generally further from key services often without public transport so cars are more often required. Treating car ownership as a sign of affluence for deprivation-linked resources unfairly impacts on rural communities. In 2007, cars, vans or taxis provided 84% of distance travelled in Great Britain. A shift from cars towards walking, cycling and public transport would benefit individuals, society, and the environment and reduce the negative impacts of transport. …

Self-reported heart symptoms are strongly linked to past and present poverty in Russia: evidence from the 1998 Taganrog interview survey

In this Russian-Swedish collaborative study the question of how symptoms of heart disease are linked to poverty in Russia was addressed. A random sample household survey was conducted in Taganrog, southern Russia. It covered questions about living circumstances, poverty and health. Health questions included both symptoms of heart problems, such as chest pain and high blood pressure, psychological problems such as depression and anxiety, as well as health-related behaviours such as alcohol drinking. Answers from 1972 women and men aged 18-70 are analysed here. The poorest fifth of the population were more than twice as likely as others to report heart symptoms. Problems in affording vegetables, meat or fish, clothes and footwear were linked to heart symptoms more closely than other economic indicators, such as car ownership or ownership of consumer durables. Psychological symptoms, sleeping problems and alcohol drinking were all related to self-reported heart symptoms, but explained little of the excess risks attributable to present poverty. Childhood poverty was also linked to present heart symptoms. Life-time accumulated experience of economic hardship contributes to present levels of heart disease symptomology in Russia.