Changes In Socioeconomic Inequalities Research Articles

Changes in suicide inequalities in the context of an increase and a decrease in suicide mortality: The case of South Korea, 1995–2020

South Korea experienced a sharp increase until 2010 followed by a gradual decrease in suicide mortality. This study examined changes in socioeconomic inequalities in suicide over 25 years and how suicide inequalities changed in the context of both an increase and a decrease in suicide mortality. Data with five-year intervals were extracted from the Korean death registry and census data between 1995 and 2020. Using Poisson regression, four measures of suicide inequalities were calculated for the slope of inequality index (SII), relative index of inequality, rate ratios, and ratio differences. Educational inequalities in suicide were obvious across all sub-populations, measures, and periods. The widening of suicide inequalities, particularly with absolute measures, followed an increase in suicide mortality until 2010. In contrast, a decline of suicide inequalities concurred after 2010 during the period of a decline in suicide mortality. SII among the total population decreased by 35.4%, from 62.4 per 100,000 people (95% confidence interval [CI], 59.8–64.9) in 2010 to 40.3 (95% CI, 38.3–42.4) in 2020. The pattern of widening and narrowing in suicide inequalities observed in the whole population was only concordant with the older population. However, the younger and the middle-aged population showed a gradual increase or stalemate in the inequalities throughout the period. Overall, suicide inequalities narrowed in the recent decade. This decline was largely led by the older population, and was attributed to the provision of social protection. A decline of suicide inequalities can accompany a decline in suicide mortality, when the provision of social protection favored the less educated.

Explaining socioeconomic inequality in food consumption patterns among households with women of childbearing age in South Africa.

The changing food environment shifts peoples' eating behaviour toward unhealthy food, including ultra-processed food (UPF), leading to detrimental health outcomes like obesity. This study examines changes in socioeconomic inequalities in food consumption spending between 2005/06 and 2010/11 in South African households with women of childbearing age (15 to 49) (WCBA). Data come from the 2005/06 and 2010/11 Income and Expenditure Surveys. The distribution of spending according to the NOVA food classification system groupings (unprocessed or minimally processed foods, processed culinary ingredients, processed and UPF products) was analysed using standard methodologies. Changes in spending inequalities between 2005/06 and 2010/11 were assessed using the concentration index (C), while the factors explaining the changes in spending inequalities were identified using the Oaxaca decomposition approach. The Kakwani index (K) was used to assess progressivity. Results show that average real spending on all food categories, including UPF, increased between 2005/06 and 2010/11. Socioeconomic inequality in UPF consumption spending decreased (C = 0.498 in 2005/06 and C = 0.432 in 2010/11), and spending on processed foods (C = 0.248 in 2005/06 and C = 0.209 in 2010/11). Socioeconomic status, race, and urban residence contributed to overall socioeconomic inequality and changes in UPF consumption inequality between 2005/06 and 2010/11. Spending on all food categories was regressive in 2005/06 (K = -0.173 for UPF and -0.425 for processed foods) and 2010/11 (K = -0.192 for UPF and -0.418 for processed foods) because such spending comprises a larger share of poorer household's income than their wealthier counterparts. The government should address these contributors to inequality to mitigate the risks associated with UPF consumption, especially among less affluent households.

Socioeconomic inequalities in adverse pregnancy outcomes in India: 2004-2019.

Although India has made substantial improvements in public health, it accounted for one-fifth of global maternal and neonatal deaths in 2015. Stillbirth, abortion, and miscarriage contribute to maternal and infant morbidity and mortality. There are known socioeconomic inequalities in adverse pregnancy outcomes. This study estimated changes in socioeconomic inequalities in rates of stillbirth, abortion, and miscarriage in India across 15 years. We combined data from three nationally representative health surveys. Absolute inequalities were estimated using the slope index of inequality and risk differences, and relative inequalities were estimated using the relative index of inequalities and risk ratios. We used household wealth, maternal education, and Scheduled Caste and Scheduled Tribe membership as socioeconomic indicators. We observed persistent socioeconomic inequalities in abortion and stillbirth from rates of 2004-2019. Women at the top of the wealth distribution reported between 2 and 5 fewer stillbirths per 1,000 pregnancies over the study time period compared to women at the bottom of the wealth distribution. Women who completed primary school, and those at the top of the household wealth distribution, had, over the study period, 5 and 20 additional abortions per 1,000 pregnancies respectively compared to women who did not complete primary school and those at the bottom of the wealth distribution. Women belonging to a Scheduled Caste or Scheduled Tribe had 5 fewer abortions per 1,000 pregnancies compared to other women, although these inequalities diminished by the end of the study period. There was less consistent evidence for socioeconomic inequalities in miscarriage, which increased for all groups over the study period. Despite targeted investments by the Government of India to improve access to health services for socioeconomically disadvantaged groups, disparities in pregnancy outcomes persist.

Decomposing socioeconomic inequality in household out of pocket health expenditures in Pakistan (2010-11–2018-19)

BackgroundThe increased socioeconomic inequality in catastrophic health expenditure (CHE) disproportionately affects disadvantaged populations, subjecting them to financial hardships, limiting their access to healthcare, and exacerbating their vulnerability to morbidity.ObjectivesThis study examines changes in socioeconomic inequality related to CHE and analyzes the contributing factors responsible for these changes in Pakistan between 2010-11 and 2018-19.MethodsThis paper extracted the data on out-of-pocket health expenditures from the National Health Accounts for 2009-10 and 2017-18. Sociodemographic information was gathered from the Household Integrated Economic Surveys of 2010-11 and 2018-19. CHE was calculated using budget share and the ability-to-pay approaches. To assess socioeconomic inequality in CHE in 2010-11 and 2018-19, both generalized and standard concentration indices were used, and Wagstaff inequality decomposition analysis was employed to explore the causes of socioeconomic inequality in each year. Further, an Oaxaca-type decomposition was applied to assess changes in socioeconomic inequality in CHE over time.ResultsThe concentration index reveals that socioeconomic inequality in CHE decreased in 2018-19 compared to 2010-11 in Pakistan. Despite the reduction in inequality, CHE was concentrated among the poor in Pakistan in 2010-11 and 2018-19. The inequality decomposition analysis revealed that wealth status was the main cause of inequality in CHE over time. The upper wealth quantiles indicated a positive contribution, whereas lower quantiles showed a negative contribution to inequality in CHE. Furthermore, urban residence contributed to pro-rich inequality, whereas employed household heads, private healthcare provider, and inpatient healthcare utilization contributed to pro-poor inequality. A noticeable decline in socioeconomic inequality in CHE was observed between 2010 and 2018. However, inequality remained predominantly concentrated among the lower socio-economic strata.ConclusionThese results underscore the need to improve the outreach of subsidized healthcare and expand social safety nets.

Participation in a digital self-management intervention for osteoarthritis and socioeconomic inequalities in patient-related outcomes

Objective To investigate changes in socioeconomic inequalities in patient-related outcomes and pain medication use, following participation in a digital self-management intervention for osteoarthritis (OA) in Sweden. Method Participants with hip/knee OA enrolled in the digital intervention were included. Self-reported outcomes collected were the numerical rating scale (NRS) pain, activity impairment, general health, Knee/Hip injury and Osteoarthritis Outcome Score (KOOS-12, HOOS-12) Pain, Function, and Quality of Life subscales, 5-level EuroQol 5 Dimensions (EQ-5D-5L), Patient Acceptable Symptom State (PASS) for function, walking difficulties, fear of movement, wish for surgery, pain medication use, physical function measured by the 30s chair-stand test, and level of physical activity. Educational attainment was used as a socioeconomic measure and the concentration index was used to assess the magnitude of inequalities at baseline and 3 month follow-up. Results The study included 21,688 participants (mean ± sd age 64.1 ± 9.1 years, 74.4% females). All outcomes except for PASS demonstrated inequalities in favour of highly educated participants at both time-points, with highly educated participants reporting better outcomes. At 3 month follow-up, the magnitude of inequality widened for activity impairment, but narrowed for NRS pain, EQ-5D-5L, KOOS-12/HOOS-12 Pain and Function, physical function, and wish for surgery. There were no statistically conclusive changes in the magnitude of inequalities for the remaining outcomes. Conclusions There were inequalities in patient-related outcomes in favour of those with higher education among participants of a digital self-management intervention for OA, although the magnitude of these pre-existing inequalities generally narrowed after the 3 month intervention.

Socioeconomic disparities in school life expectancy among India and its major states of India in the last decade: Insights from large scale household surveys data

BackgroundThere is a dearth of research on School Life Expectancy (SLE) in India, with limited studies addressing the influence of socioeconomic disparities on SLE. This study aims to investigate the changes in socioeconomic inequalities in SLE across India and its major states during the period spanning from 2007 to 2018. MethodsTo accomplish this, we utilized data from two rounds of the National Sample Survey NSS 64th (2007–08) and 75th (2017–18), to compute the SLE of children aged 6 to 18, encompassing primary to secondary education. To quantify the educational disparities in SLE among various socioeconomic categories over the decade, we employed both Absolute Inequality (AI) and Relative Inequality (RI) indices. ResultsThe overall SLE for primary to secondary education experienced a significant increase of 0.75 years between 2007–08 and 2017–18. Among the 15 major states of India, notable variations in the extent of SLE improvements were observed. During this period, there was an absolute gap that ranged from 0.61 to 0.44 years and a relative gap of 4.79 percent among the states. The disparities between urban and rural areas notably widened during this period. The gap between children from the lowest quintile of monthly per capita expenditutre (MPCE) and those from the highest quintile of MPCE decreased significantly, reducing from 2.18 years in 2007–08 to 1.20 years in 2017–18. Furthermore, differences in SLE based on caste and religion also exhibited significant reductions. ConclusionThis study reveals that socioeconomic disparities in SLE in India are relatively modest, highlighting the importance of further understanding the determinants of these inequalities and assessing the effectiveness of interventions aimed at addressing them.

Equal in ashes? Exploring socioeconomic inequalities in lifespan based on obituary data in Austria

Understanding the emergence of and changes in socioeconomic inequalities in lifespan requires reliable, longitudinal data. In the absence of administrative data, published obituaries may be one such alternative source. With the validity of drawing relevant data from obituaries not yet established in population health research, this study addresses this gap by estimating socioeconomic inequalities in lifespan in Vorarlberg, Austria. Data for all individuals (n = 1490) with obituaries published (July to December 2022) in a regional newspaper (market share: 56%) were extracted, including different markers of the deceased's socioeconomic status. Linear regression analyses showed that, on average, individuals with medium-sized obituaries lived 6.02 years (95% CI: 4.19, 7.85) and individuals with the largest obituaries 12.04 years (95% CI: 7.04, 17.04) longer than individuals with small obituaries while blue-collar workers lived 10.50 years (95% CI: -14.51, -6.49) shorter than individuals with no occupation (reported). This socioeconomic gradient is in line with findings based on national data sources, and comparisons with official regional data are promising regarding data representativeness and completeness. With obituary size reflecting different costs (€210–€1626) and thus being a novel marker for financial ability, obituaries could also be a useful, innovative data source internationally for historical analyses or “nowcasting” health inequalities.

Did the socioeconomic inequalities in avoidable and unavoidable mortality worsen during the first year of the COVID-19 pandemic in Korea?

This study examined changes in socioeconomic inequalities in mortality in Korea before and after the outbreak of coronavirus disease 2019 (COVID-19). From 2017 to 2020, age-standardized mortality rates were calculated for all-cause deaths, avoidable deaths (preventable deaths, treatable deaths), and unavoidable deaths using National Health Insurance claims data and Statistics Korea's cause of death data. In addition, the slope index of inequality (SII) and the relative index of inequality (RII) by six income levels (Medical Aid beneficiary group and quintile of health insurance premiums) were computed to analyze the magnitude and change of mortality inequalities. All-cause and avoidable mortality rates decreased steadily between 2017 and 2020, whereas unavoidable mortality remained relatively stable. In the case of mortality inequalities, the disparity in all-cause mortality between income classes was exacerbated in 2020 compared to 2019, with the SII increasing from 185.44 to 189.22 and the RII increasing from 3.99 to 4.29. In particular, the preventable and unavoidable mortality rates showed an apparent increase in inequality, as both the SII (preventable: 91.31 to 92.01, unavoidable: 69.99 to 75.38) and RII (preventable: 3.42 to 3.66, unavoidable: 5.02 to 5.89) increased. In the first year of the COVID-19 pandemic, mortality inequality continued to increase, although there was no sign of exacerbation. It is necessary to continuously evaluate mortality inequalities, particularly for preventable and unavoidable deaths.

Recent trends in maternal and child health inequalities in Latin America and the Caribbean: analysis of repeated national surveys

BackgroundAlthough most Latin American and the Caribbean (LAC) countries made important progress in maternal and child health indicators from the 1990s up to 2010, little is known about such progress in the last decade. This study aims at documenting progress for each country as a whole, and to assess how within-country socioeconomic inequalities are evolving over time.MethodsWe identified LAC countries for which a national survey was available between 2011–2015 and a second comparable survey in 2018–2020. These included Argentina, Costa Rica, Cuba, the Dominican Republic, Guyana, Honduras, Peru, and Suriname. The 16 surveys included in the analysis collected nationally representative data on 221,989 women and 152,983 children using multistage sampling. Twelve health-related outcomes were studied, seven of which related to intervention coverage: the composite coverage index, demand for family planning satisfied with modern methods, antenatal care (four or more visits and eight or more visits), skilled attendant at birth, postnatal care for the mother and full immunization coverage. Five additional impact indicators were also investigated: stunting prevalence among under-five children, tobacco use by women, adolescent fertility rate, and under-five and neonatal mortality rates. For each of these indicators, average annual relative change rates were calculated between the baseline and endline national level estimates, and changes in socioeconomic inequalities over time were assessed using the slope index of inequality.ResultsProgress over time and the magnitude of inequalities varied according to country and indicator. For countries and indicators where baseline levels were high, as Argentina, Costa Rica and Cuba, progress was slow and inequalities small for most indicators. Countries that still have room for improvements, such as Guyana, Honduras, Peru and Suriname, showed faster progress for some but not all indicators, although also had wider inequalities. Among the countries studied, Peru was the top performer in terms of increasing coverage and reducing inequalities over time, followed by Honduras. Declines in family planning and immunization coverage were observed in some countries, and the widest inequalities were present for adolescent fertility and antenatal care coverage with eight or more visits.ConclusionsAlthough LAC countries are well placed in terms of current levels of health indicators compared to most low- and middle-income countries, important inequalities remain, and reversals are being observed in some areas. More targeted efforts and actions are needed in order to leave no one behind. Monitoring progress with an equity lens is essential, but this will require further investment in conducting surveys routinely.

Changes in Socioeconomic Inequalities in Unintended Pregnancies Among Currently Married Women in India.

Despite the consistent prevalence of unintended pregnancies in India and its adverse impact on maternal and neonatal mortality, the literature discussing socioeconomic inequality remains scarce. This study aims to assess the change in wealth-related inequalities in unintended pregnancy in India from 2005-2006 to 2019-20 and to quantify the contribution of various factors towards inequality. The present study analyzed cross-sectional data from the third and fifth rounds of the National Family Health Survey (NFHS). The information on fertility preferences and pregnancy intention of most recent live birth during the five years preceding the survey was collected from eligible women. The concentration index and Wagstaff decomposition were used to analyze wealth-related inequality and the contributing factors. Our results show that the prevalence of unintended pregnancy has declined in 2019-20 to 8% from 22% in 2005-2006. With the increase in education and wealth status, unintended pregnancy decreases significantly. The results of the concentration index depict that unintended pregnancy is more concentrated among the poor than the rich in India, and the individual's wealth status has the highest contribution to unintended pregnancy inequality. Other factors like mothers' BMI, place of residence and education also contribute majorly to the inequality. The study results are critical and increase the need for strategies and policies. Disadvantaged women need education and family planning information, plus access to reproductive health resources. Governments should improve accessibility and quality of care in family planning methods to prevent unsafe abortions, unwanted births, and miscarriages. Further research is needed to investigate the impact of social and economic status on unintended pregnancies.

Investigating Health Inequality Using Trend, Decomposition and Spatial Analyses: A Study of Maternal Health Service Use in Nepal.

Objectives: (a) To quantify the level and changes in socioeconomic inequality in the utilization of antenatal care (ANC), institutional delivery (ID) and postnatal care (PNC) in Nepal over a 20-year period; (b) identify key drivers of inequality using decomposition analysis; and (c) identify geographical clusters with low service utilization to inform policy. Methods: Data from the most recent five waves of the Demographic Health Survey were used. All outcomes were defined as binary variables: ANC (=1 if ≥4 visits), ID (=1 if place of delivery was a public or private healthcare facility), and PNC (=1 if ≥1 visits). Indices of inequality were computed at national and provincial-level. Inequality was decomposed into explanatory components using Fairile decomposition. Spatial maps identified clusters of low service utilization. Results: During 1996-2016, socioeconomic inequality in ANC and ID reduced by 10 and 23 percentage points, respectively. For PND, the gap remained unchanged at 40 percentage points. Parity, maternal education, and travel time to health facility were the key drivers of inequality. Clusters of low utilization were displayed on spatial maps, alongside deprivation and travel time to health facility. Conclusion: Inequalities in the utilization of ANC, ID and PNC are significant and persistent. Interventions targeting maternal education and distance to health facilities can significantly reduce the gap.

Is socioeconomic inequality in antenatal care coverage widening or reducing between- and within-socioeconomic groups? A case of 19 countries in sub-Saharan Africa

Maternal health statistics have improved in many countries in sub-Saharan Africa (SSA). Still, progress remains slow in meeting the Sustainable Development Goals (SDG) targets. Accelerating antenatal care (ANC) coverage is critical to improving maternal health outcomes. To progress, countries should understand whether to target reducing health disparities between- or within-socioeconomic groups, as policies for achieving these may differ. This paper develops a framework for decomposing changes in socioeconomic inequalities in health into changes in between- and within-socioeconomic groups using the concentration index, a popular measure for assessing socioeconomic inequalities in health. It begins by noting the challenge in decomposing the concentration index into only between- and within-group components due to the possibility of an overlap created by overlapping distributions of socioeconomic status between groups. Using quantiles of socioeconomic status provides a convenient way to decompose the concentration index so that the overlap component disappears. In characterising the decomposition, a pro-poor shift occurs when socioeconomic inequality is reduced over time, including between- and within-socioeconomic groups, while a pro-rich shift or change occurs conversely. The framework is applied to data from two rounds of the Demographic and Health Survey of 19 countries in SSA conducted about ten years apart in each country. It assessed changes in socioeconomic inequalities in an indicator of at least four antenatal care visits (ANC4+) and the count of ANC visits (ANC intensity). The results show that many countries in SSA witnessed significant pro-poor shifts or reductions in socioeconomic inequalities in ANC coverage because pro-rich inequalities in ANC4+ and ANC intensity become less pro-rich. Changes in between-socioeconomic group inequalities drive the changes in ANC service coverage inequalities in all countries. Thus, policies addressing inequalities between-socioeconomic groups are vital to reducing overall disparities and closing the gap between the rich and the poor, a crucial objective for the SDGs.

Inequalities in Household Food Expenditures in South Africa: Implications for the Burden of Non-Communicable Diseases (NCDs) and Health Inequality

Globally, diets are changing. With rising incomes and increased globalisation, low- and middle-income countries are undergoing a shift from traditional diets to an increasingly western diet that is high in sugar and processed foods. Furthermore, many countries undergoing this nutrition transition are plagued by income and wealth inequalities. The interaction of these inequalities with changing dietary patterns has significant implications for the increased burden of Non-Communicable Diseases (NCDs) and health inequality. This study assesses the relative changes in socio-economic inequality in the distribution of food consumption expenditure in South Africa. The data were drawn from the multiple waves of the 2005/2006 Income and Expenditure Survey (IES) and 2014/2015 Living Conditions Survey (LCS). The study uses both descriptive statistics and the concentration index method. The results show that real food expenditures have increased on average and are concentrated among the rich. However, real food expenditure in certain food groups has become less concentrated over time in the richer populations. This is particularly true for sugary food products, with a reduction of about 34% in their concentration among the rich. Undoubtedly, the concentration of real food expenditure on certain food among the lower socioeconomic groups has grave implications for exacerbating the burden of diet-related NCDs and health inequality.

Changes in socioeconomic inequalities in food consumption among Brazilian adults in a 10-years period.

To evaluate changes in socioeconomic inequalities in food consumption in Brazil over a 10-year period. Data on 24-h recalls of adults (aged 20 years or more) from the 2008/9 (n = 26,327) and 2017/8 (n = 37,689). Brazilian Dietary Survey were analyzed. We used the Nova classification system to group food items and estimate the percentage of total energy from ultra-processed foods and plant-based natural or minimally processed foods. For sex and area of residence, we calculated the percentage points (p.p.) difference between the estimates for women and men, and rural and urban populations. Negative values indicate higher consumption among men or urban residents, positive values indicate higher consumption among women or rural residents, and zero indicates equality. For education and wealth levels we calculated the slope index of inequality (SII). The SII varies from -100 to 100, with positive values indicating higher consumption among more educated or wealthiest groups, negative values indicating higher consumption among less educated or poorest groups, and zero equality. Over the period, we observed a reduction in the percentage of total energy from plant-based natural/minimally processed foods from 13.0 to 12.2% and an increase in that of ultra-processed foods from 17.0 to 18.3%. The urban population and those in the wealthier and more educated groups presented higher consumption of ultra-processed foods and lower consumption of plant-based natural/minimally processed foods in both survey years. Over the 10-year period, there was an overall reduction of the socioeconomic inequalities, mainly explained by the greater increase in ultra-processed food consumption by the rural population and those from the poorest and less educated groups (difference for area -7.2 p.p. in 2008/9 and -5.9 p.p. in 2017/8; SII for education 17.7 p.p. in 2008/9 and 13.8 p.p. in 2017/8; SII for wealth 17.0 p.p. in 2008/9 and 11.2 p.p. in 2017/8). Socioeconomic inequalities in food consumption decreased in Brazil, but it may lead to the overall deterioration of the dietary quality of the more vulnerable groups.

Trends and Changes in Socio-Economic Inequality in Self-Rated Health among Migrants and Non-Migrants: Repeated Cross-Sectional Analysis of National Survey Data in Germany, 1995-2017.

Socio-economic inequalities in health may change over time, and monitoring such change is relevant to inform adequate policy responses. We aimed to quantify socio-economic inequalities in health among people with direct, indirect and without migration background in Germany and to assess temporal trends and changes between 1995 and 2017. Using nationally representative survey data from the Socio-Economic Panel (SOEP), we quantified absolute and relative socio-economic inequalities in self-reported general health by calculating the slope (SII) and relative index of inequality (RII) with 95% confidence intervals (CI) among each group and year (1995–2017) in a repeated cross-sectional design. Temporal trends were assessed using a GLM regression over the SII and RII, respectively. The total sample size comprised 492,489 observations, including 108,842 (22.23%) among people with migration background. About 31% of the population with and 15% of the population without migration background had a low socio-economic status. Socio-economic inequalities in health persisted in the group with migration background (1995 to 2017), while inequalities in the non-migrant population increased (SII: = 0.04, p < 0.01) and were on a higher level. The highest socio-economic inequalities in health were found among those with direct migration background ( = −0.23, p< 0.01; = −0.33, p < 0.01). The results show that the magnitude and temporal dynamics of inequalities differ among populations with direct, indirect and without migration background. Monitoring systems can capture and investigate these inequalities if migrant populations are adequately integrated into the respective systems.

Incidence of SARS-CoV-2 Infection and Related Mortality by Education Level during Three Phases of the 2020 Pandemic: A Population-Based Cohort Study in Rome.

Evidence on social determinants of health on the risk of SARS-CoV-2 infection and adverse outcomes is still limited. Therefore, this work investigates educational disparities in the incidence of infection and mortality within 30 days of the onset of infection during 2020 in Rome, with particular attention to changes in socioeconomic inequalities over time. A cohort of 1,538,231 residents in Rome on 1 January 2020, aged 35+, followed from 1 March to 31 December 2020, were considered. Cumulative incidence and mortality rates by education were estimated. Multivariable log-binomial and Cox regression models were used to investigate educational disparities in the incidence of SARS-CoV-2 infection and mortality during the entire study period and in three phases of the pandemic. During 2020, there were 47,736 incident cases and 2281 deaths. The association between education and the incidence of infection changed over time. Till May 2020, low- and medium-educated individuals had a lower risk of infection than that of the highly educated. However, there was no evidence of an association between education and the incidence of SARS-CoV-2 infection during the summer. Lastly, low-educated adults had a 25% higher risk of infection from September to December than that of the highly educated. Similarly, there was substantial evidence of educational inequalities in mortality within 30 days of the onset of infection in the last term of 2020. In Rome, social inequalities in COVID-19 appeared in the last term of 2020, and they strengthen the need for monitoring inequalities emerging from this pandemic.

1392Decline in current tobacco use and socio-economic inequalities in 22 Sub-Saharan African countries- 2003-2018

Abstract Background Tobacco companies have shifted their marketing and production to Sub-Saharan African countries which are in an early stage of tobacco epidemic. We report changes in current tobacco use and socio-economic inequalities between 2003 and 2019. Methods We estimated country-level, sex-wise, age-standardized prevalence estimates of current tobacco use in 22 SSA countries using sequential Demographic and Health Survey data. On pooled baseline (2003-11) and most recent survey (2011-19) data, prevalence by education, wealth, and age groups; Slope index of inequality and relative index of inequality were estimated. Change in prevalence in each country and by socio-economic subgroups and change in socio-economic inequalities (pooled data) were calculated. Results Tobacco use among men ranging [6·1% (Ghana) to 38·3 (Lesotho)] at baseline and [4·5% (Ghana) to 46·0% (Lesotho)] most recent surveys. Decline in prevalence points ranged from 1·5% (Ghana) to 9·6% (Sierra Leone). For women countries where prevalence was &amp;lt;1% rose from nine to 15. In most countries prevalence of current tobacco use significantly declined. WHO target of 30% decline was achieved in 15 and 10 countries for women and men, respectively. In both sexes, tobacco use rate and decline were higher among less educated and poor while magnitude and direction of inequalities were consistently declined. Absolute inequalities three-fold higher among men, while relative inequalities were nearly twice higher among women. Conclusions Tobacco use declined in a third of SSA countries. Persistence of socio-economic inequalities warrants stricter implementation of tobacco control measures to reach the vulnerable groups and continued monitoring of inequalities. Key messages Contrary to the projections, tobacco use had significantly declined in most of the countries, and many achieved the WHO target of 30% reduction. Country-level monitoring by regular surveys is needed to track the equitable progress to international goals.

Decomposition and changes in socio-economic inequalities in mental health in Barcelona between 2006 and 2016

Purpose This study aims, firstly, to analyse the contribution of socio-economic determinants to mental health (MH) inequalities before the economic crisis, in 2006, and again in a year during recovery, 2016, and secondly, to analyse the changes in these contributions between the two points in time in Barcelona city. Design/methodology/approach The concentration index (CI) was calculated for MH inequalities for the population aged 16 or older using the Barcelona Health Surveys for 2006 and 2016. MH was measured with the 12-item General Health Questionnaire. The CI was broken down for each year and gender based on a set of socio-economic determinants plus social support and the presence of chronic diseases. The contribution of each factor to variation in MH inequality between the two points in time was analysed with Oaxaca decomposition. Findings Income inequalities in MH increased for men and women (a CI from −0.06 in 2006 to around −0.16 in 2016). Employment status and social class are the main contributors to MH inequalities (more than 50%), except for women in 2006 that is chronic disease. The main contribution to increases in MH inequality between 2006 and 2016 was due to unemployment (26.5% men, 23.8% women), being a student (22.8% men, 20.7% women), homemaker in women (30.7%) and men in the manual class (31.6%). Originality/value MH inequalities have been amplified between the two years among the economically vulnerable population or for those who are out of the labour market with unexpected changes for women.

Income and Education Inequalities in Brain and Central Nervous System Cancer Incidence in Canada: Trends over Two Decades.

The socioeconomic gradient of brain and central nervous system (CNS) cancer incidence in Canada is poorly understood. This study aimed to measure socioeconomic inequalities in brain and CNS cancer incidence in Canada from 1992 to 2010. Using a unique census division level dataset (n = 280) pooled from the Canadian Cancer Registry (CCR), the Canadian Census of Population and the National Household Survey, we measured brain and CNS cancer incidence in Canada. The age-adjusted concentration index (C) was used to measure income- and education-related inequalities in brain and CNS cancers in Canada, and for men and women, separately. Time trend analyses were conducted to examine the changes in socioeconomic inequalities in brain and CNS cancers in Canada over time. The results indicated that the crude brain and CNS cancer incidence increased from 7.29 to 8.17 per 100,000 (annual percentage change: 0.70) over the study period. The age-adjusted C results suggested that the brain and CNS cancer incidence was not generally significantly different for census division of different income and educational levels. There was insufficient evidence to support changes in income and education-related inequalities over time. Since the incidence of brain and CNS cancers in Canada showed no significant association with socioeconomic status, future cancer control programs should focus on other risk factors for this cancer subset.

Age specific trends in mortality disparities by socio-economic deprivation in small geographical areas of England, 2002-2018: A retrospective registry study.

SummaryBackgroundDisparities in mortality rates according to socioeconomic position (SEP) have been rising in England. We describe the association between recent changes in socioeconomic inequality and trends in mortality disparities for different age and sex groups at small-area level in England.MethodsVital registration data from the Office for National Statistics on resident population size and number of deaths in each Lower Super Output Area (LSOA) in England from 2002 to 2018 were stratified by sex and 5-year age group. We grouped LSOA into ventiles of the Index of Multiple Deprivation (IMD), our indicator of SEP. We examined time trends in smoothed mortality rates, using 3 year moving averages for the period 2003-2017, by age across the IMD distribution. We measured mortality inequalities using the ratio of mortality rates between different deprivation groups. We calculated mortality rate ratios between the most and the least deprived 10% of areas (Total Inequality) and between the median and least deprived (Lower Inequality) 10% of areas by year, gender and age group, to examine where in the distribution of deprivation trends in mortality inequality arose.FindingsAmong <1 year olds, the inequality in mortality rates between the poorest 10% of LSOAs and the richest 10% of LSOAs fell between 2003 and 2017 by 22•7% for men and 22•8% for women. The largest inequalities were observed among 40 to 54 year olds. This inequality increased over the study period – from 3•2 times higher mortality rates for men in the most as opposed to the least deprived 10% of LSOAs in 2003 to 3•3 times in 2017. The rise was from 2•4 to 2•6 for women. Age groups ≥65 years, who experience the highest mortality risk, had low but rising inequality. Men and women aged 65 to 79 living in the most deprived LSOAs had a mortality rate 1•9 times higher than the least deprived in 2003 but this had increased to 2•2 times higher for women and 2•3 times higher for men by 2017. This was due to rising inequality in both halves of the distribution – between the top 10% of LSOA and the middle, and between the middle and the bottom 10% of LSOA.InterpretationOverall mortality inequality rose in England but there were substantial differences in the trends for specific age and sex groups. Infant and child mortality inequality fell. At older ages, mortality inequality rose across cohorts, although in different ways, as each cohort's exposure to life-course to labour market inequality has differed. Policy goals of reducing mortality inequality will be best met by a focus on the risk factors that are specific to particular age and deprivation groups.FundingEconomic and Social Research Council, through the ESRC Centre for the Microeconomic Analysis of Public Policy at the IFS. We gratefully acknowledge the support of the Nuffield Foundation, grant reference WEL/43603. The project has been funded by the Nuffield Foundation, but the views expressed are those of the authors and not necessarily the Foundation. Visit www.nuffieldfoundation.org. Research at UCL Great Ormond Street Institute of Child Health is supported by the NIHR Great Ormond Street Hospital Biomedical Research Centre.