What explains socioeconomic inequalities in dental flossing? Cross-sectional results from the RaNCD cohort study

Introduction: The magnitude of or determinants underlying socioeconomic inequalities in the use of dental floss is poorly understood in Iran. This study aimed to measure and decompose socioeconomic inequalities in dental flossing in Ravansar, Iran. Methods: This cross-sectional study used data of 10002 individuals aged 35-65 years obtained from the Ravansar Non-communicable Disease (RaNCD) cohort study located in Kermanshah province, west of Iran.  Socioeconomic status was measured through an asset-based method and principal component analysis was carried out to determine the socioeconomic status (SES). The concentration index and curve were used to measure socioeconomic inequality in dental flossing. Decomposition analysis was also used to determine the main determinants that contribute to inequalities in dental flossing. Findings: Of 10,002 participants, 11.74% were found to use dental floss. The normalized CI for use of dental floss was 0.327 in the entire population, 0.323 in females and 0.329 in males, indicating that the use of dental floss is more concentrated among high-SES individuals. The decomposition analysis indicated that SES (50.58%) and level of education (44.90%) respectively contributed the most to this inequality. Place of residence (10.55%) and age group (2.7%) were the next main contributors, respectively. Conclusion: There are a low prevalence and a relatively high degree of pro-rich socioeconomic-related inequality in dental flossing among Iranian adults. Socioeconomic status, level of education and place of residence contributed the most to the observed inequalities in dental flossing. Policy interventions should consider these factors to reduce inequality in the use of dental floss and increase the prevalence of dental flossing. &nbsp

Measuring and Decomposing Socioeconomic Inequalities in Adult Obesity in Western Iran

Objectives Obesity is a considerable and growing public health concern worldwide. The present study aimed to quantify socioeconomic inequalities in adult obesity in western Iran. Methods A total of 10 086 participants, aged 35-65 years, from the Ravansar Non-communicable Disease Cohort Study (2014-2016) were included in the study to examine socioeconomic inequalities in obesity. We defined obesity as a body mass index ≥30 kg/m2. The concentration index and concentration curve were used to illustrate and measure wealth-related inequality in obesity. Additionally, we decomposed the concentration index to identify factors that explained wealth-related inequality in obesity. Results Overall, the prevalence of obesity in the total sample was 26.7%. The concentration index of obesity was 0.04; indicating that obesity was more concentrated among the rich (p<0.001). Decomposition analysis indicated that wealth, place of residence, and marital status were the main contributors to the observed inequality in obesity. Conclusions Socioeconomic-related inequalities in obesity among adults warrant more attention. Policies should be designed to reduce both the prevalence of obesity and inequalities in obesity by focusing on those with higher socioeconomic status, urban residents, and married individuals

Socioeconomic - related inequalities in overweight and obesity: findings from the PERSIAN cohort study

BackgroundOverweight and obesity are major health concerns worldwide, with adverse health consequences during the life span. This study measured socioeconomic inequality in overweight and obesity among Iranian adults.MethodsData were extracted from 129,257 Iranian adults (aged 35years and older) participated in the Prospective Epidemiologic Research Studies in IrAN (PERSIAN) in 14 provinces of Iran in 2014. Socioeconomic-related inequality in overweight and obesity was estimated using the Concentration Index (C-n). The C-n further decomposed to find factors explaining the variability within the Socioeconomic related inequality in overweight and obesity.ResultsOf the total number of participants, 1.98, 26.82, 40.76 and 30.43% had underweight, normal weight, overweight and obesity respectively. The age-and sex standardized prevalence of obesity was higher in females than males (39.85% vs 18.79%). People with high socioeconomic status (SES) had a 39 and 15% higher chance of being overweight and obese than low SES people, respectively. The positive value of C-n suggested a higher concentration of overweight (0.081, 95% confidence interval [CI]; 0.074-0.087) and obesity (0.027, 95% CI; 0.021-0.034) among groups with high SES. There was a wide variation in socioeconomic-related inequality in overweight and obesity rate across 14 provinces. The decomposition results suggested that SES factor itself explained 66.77 and 89.07% of the observed socioeconomic inequalities in overweight and obesity among Iranian adults respectively. Following SES, province of residence, physical activity, using hookah and smoking were the major contributors to the concentration of overweight and obesity among the rich.ConclusionsOverall, we found that overweight and obesity is concentrated among high SES people in the study population. . Accordingly, it seems that intersectional actions should be taken to control and prevent overweight and obesity among higher socioeconomic groups. Keywords:Socioeconomic Factors; Inequality; Concentration index; overweight and obesity; PERSIAN; Ira

Socioeconomic-related inequalities in oral hygiene behaviors: a cross-sectional analysis of the PERSIAN cohort study

Background Socioeconomic-related inequality in oral hygiene behaviors in Iran is poorly understood. This study aims to measure and decompose socioeconomic-related inequalities in oral hygiene behaviors among middle-aged and elderly adults in Iran. Methods A cross-sectional analysis was performed using data from the Prospective Epidemiological Research Studies in IrAN (PERSIAN), a large national cohort study. A total of 130,016 individuals aged 35 years and above from 17 cohort centers in Iran were included in the study. The normalized concentration index (C-n) was used to measure the magnitude of inequality in oral hygiene behaviors, i.e. brushing at least twice and flossing once daily, among middle-aged and elderly Iranian adults included in the cohort centers. Decomposition analysis was performed to quantify the contribution of each determinant to the observed inequality in oral hygiene behaviors. Results Totally, 65.5% of middle-aged and elderly adults brushed their teeth twice a day or more, 7.6% flossed at least once a day and 3.48% had both habits. The estimated C-n of the two habits combined, i.e. tooth brushing and dental flossing, for all provinces taken part in the PERSIAN cohort study was 0.399 (95% confidence interval [CI]: 0.383 to 0.417), indicating that the prevalence of the two habits combined is more concentrated among individuals with higher socioeconomic status. Inequality in oral hygiene behaviors was pro-rich in all cohort centers. The decomposition results suggested socioeconomic status as the main factor contributing to the overall inequality, followed by the level of education, and the province of residence. Conclusion A low prevalence of oral hygiene behaviors among middle-aged and elderly Iranian adults was observed. There was also a pro-rich inequality in oral hygiene behaviors among middle-aged and elderly adults in all cohort centers. These results suggest an urgent need for targeted policy interventions to increase the prevalence of preventive oral hygiene behaviors among the poor and less-educated middle-aged and elderly adults in Iran

Privatization of Medical Education in the Islamic Republic of Iran; Main Policies According to the Packages for Reform and Innovation in Medical Education

Keywords: Privatization, Medical Educatio

Decomposing socioeconomic inequality in poor mental health among Iranian adult population: results from the PERSIAN cohort study

Background Socioeconomic inequality in mental health in Iran is poorly understood. This study aimed to assess socioeconomic inequality in poor mental health among Iranian adults. Methods The study used the baseline data of PERSIAN cohort study including 131,813 participants from 17 geographically distinct areas of Iran. The Erreygers Concentration index (E) was used to quantify the socioeconomic inequalities in poor mental health. Moreover, we decomposed the E to identify factors contributing to the observed socioeconomic inequality in poor mental health in Iran. Results The estimated E for poor mental health was - 0.012 (95% CI: - 0.0144, - 0.0089), indicating slightly higher concentration of mental health problem among socioeconomically disadvantaged adults in Iran. Socioeconomic inequality in poor mental health was mainly explained by gender (19.93%) and age (12.70%). Region, SES itself, and physical activity were other important factors that contributed to the concentration of poor mental health among adults with low socioeconomic status. Conclusion There exists nearly equitable distribution in poor mental health among Iranian adults, but with important variations by gender, SES, and geography. These results suggested that interventional programs in Iran should focus on should focus more on socioeconomically disadvantaged people as a whole, with particular attention to the needs of women and those living in more socially disadvantaged regions. Keywords:Mental health; Socioeconomic inequality; Concentration index; Decompositio

Socioeconomic inequalities in prevalence, awareness, treatment and control of hypertension: evidence from the PERSIAN cohort study

Background Elevated blood pressure is associated with cardiovascular disease, stroke and chronic kidney disease. In this study, we examined the socioeconomic inequality and its related factors in prevalence, Awareness, Treatment and Control (ATC) of hypertension (HTN) in Iran. Method The study used data from the recruitment phase of The Prospective Epidemiological Research Studies in IrAN (PERSIAN). A sample of 162,842 adults aged > = 35 years was analyzed. HTN was defined according to the Joint National Committee)JNC-7(. socioeconomic inequality was measured using concentration index (Cn) and curve. Results The mean age of participants was 49.38(SD = +/- 9.14) years and 44.74% of the them were men. The prevalence of HTN in the total population was 22.3%(95% CI: 20.6%; 24.1%), and 18.8%(95% CI: 16.8%; 20.9%) and 25.2%(95% CI: 24.2%; 27.7%) in men and women, respectively. The percentage of awareness treatment and control among individuals with HTN were 77.5%(95% CI: 73.3%; 81.8%), 82.2%(95% CI: 70.2%; 81.6%) and 75.9%(95% CI: 70.2%; 81.6%), respectively. The Cn for prevalence of HTN was -0.084. Two factors, age (58.46%) and wealth (32.40%), contributed most to the socioeconomic inequality in the prevalence of HTN. Conclusion The prevalence of HTN was higher among low-SES individuals, who also showed higher levels of awareness. However, treatment and control of HTN were more concentrated among those who had higher levels of SES, indicating that people at a higher risk of adverse event related to HTN (the low SES individuals) are not benefiting from the advantage of treatment and control of HTN. Such a gap between diagnosis (prevalence) and control (treatment and control) of HTN needs to be addressed by public health policymakers

Mapping 123 million neonatal, infant and child deaths between 2000 and 2017

Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2—to end preventable child deaths by 2030—we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000–2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations

Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017 : a systematic analysis for the Global Burden of Disease Study 2017

Background: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk outcome pairs, and new data on risk exposure levels and risk outcome associations. Methods: We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017. Findings: In 2017,34.1 million (95% uncertainty interval [UI] 33.3-35.0) deaths and 121 billion (144-1.28) DALYs were attributable to GBD risk factors. Globally, 61.0% (59.6-62.4) of deaths and 48.3% (46.3-50.2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10.4 million (9.39-11.5) deaths and 218 million (198-237) DALYs, followed by smoking (7.10 million [6.83-7.37] deaths and 182 million [173-193] DALYs), high fasting plasma glucose (6.53 million [5.23-8.23] deaths and 171 million [144-201] DALYs), high body-mass index (BMI; 4.72 million [2.99-6.70] deaths and 148 million [98.6-202] DALYs), and short gestation for birthweight (1.43 million [1.36-1.51] deaths and 139 million [131-147] DALYs). In total, risk-attributable DALYs declined by 4.9% (3.3-6.5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23.5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18.6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low. Interpretation: By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning

Trends in future health financing and coverage: future health spending and universal health coverage in 188 countries, 2016–40

Background: Achieving universal health coverage (UHC) requires health financing systems that provide prepaid pooled resources for key health services without placing undue financial stress on households. Understanding current and future trajectories of health financing is vital for progress towards UHC. We used historical health financing data for 188 countries from 1995 to 2015 to estimate future scenarios of health spending and pooled health spending through to 2040. Methods: We extracted historical data on gross domestic product (GDP) and health spending for 188 countries from 1995 to 2015, and projected annual GDP, development assistance for health, and government, out-of-pocket, and prepaid private health spending from 2015 through to 2040 as a reference scenario. These estimates were generated using an ensemble of models that varied key demographic and socioeconomic determinants. We generated better and worse alternative future scenarios based on the global distribution of historic health spending growth rates. Last, we used stochastic frontier analysis to investigate the association between pooled health resources and UHC index, a measure of a country's UHC service coverage. Finally, we estimated future UHC performance and the number of people covered under the three future scenarios. Findings: In the reference scenario, global health spending was projected to increase from US$10 trillion (95$20 trillion (18 trillion to 22 trillion) in 2040. Per capita health spending was projected to increase fastest in upper-middle-income countries, at 4·2% (3·4–5·1) per year, followed by lower-middle-income countries (4·0%, 3·6–4·5) and low-income countries (2·2%, 1·7–2·8). Despite global growth, per capita health spending was projected to range from only $40 (24–65) to$413 (263–668) in 2040 in low-income countries, and from $140 (90–200) to$1699 (711–3423) in lower-middle-income countries. Globally, the share of health spending covered by pooled resources would range widely, from 19·8% (10·3–38·6) in Nigeria to 97·9% (96·4–98·5) in Seychelles. Historical performance on the UHC index was significantly associated with pooled resources per capita. Across the alternative scenarios, we estimate UHC reaching between 5·1 billion (4·9 billion to 5·3 billion) and 5·6 billion (5·3 billion to 5·8 billion) lives in 2030. Interpretation: We chart future scenarios for health spending and its relationship with UHC. Ensuring that all countries have sustainable pooled health resources is crucial to the achievement of UHC. Funding: The Bill & Melinda Gates Foundation