Prioritizing Elective Surgery During the COVID-19 Pandemic Has Caused Age-Related Inequality: a Multicenter Study

The concern has been that this prioritization has resulted in age-related inequality between patients, with the older population suffering the most. The aim of this multicenter study was to examine the differences in incidence and waiting times of elective surgeries by age during the SARS-CoV-2 coronavirus disease (COVID-19) pandemic in Finland. Data on elective surgery (88 716 operations) were gathered from three Finnish public hospitals for the years 2017–2020. Surgery incidence and waiting times stratified by age groups (younger than 18, 18 to 49, 50 to 69, and 70 or older) were examined, and the year 2020 was compared to the reference years 2017–2019. The mean annual, monthly, and weekly waiting times were calculated with 95% confidence intervals (CI). The first COVID-19 wave decreased surgery incidence most prominently in patients younger than 18 (incidence rate ratio [IRR] 0.64, CI 0.60–0.68) and 70 or older (IRR 0.68, CI 0.66–0.70). After the first wave, the incidence increased in patients aged 50 to 69 and 70 or older by 22% and 29%, respectively. Among patients younger than 18, the incidence in 2020 was 15% lower. In patients younger than 18, waiting times were at mean of 43% longer in June to December compared to the reference years. In patients aged 18 to 49, 50 to 69, and 70 or older, waiting times increased in May but recovered to normal level during fall 2020. COVID-19 decreased the incidence of surgery and led to increased waiting times. Clearing of the treatment backlog started with older patients which resulted in prolonged waiting times among pediatric patients.

Changes in prevalence and risk factors of hypertension among adults in Bangladesh: An analysis of two waves of nationally representative surveys

Introduction Bangladesh is one of the countries where the prevalence of non-communicable diseases (NCDs) such as hypertension is rising due to rising living standards, sedentary lifestyles, and epidemiological transition. Among the NCDs, hypertension is a major risk factor for CVD, accounting for half of all coronary heart disease worldwide. However, detailed research in this area has been limited in Bangladesh. The objective of the study was to estimate changes in the prevalence and risk factors of hypertension among Bangladeshi adult population. The study also sought to identify socioeconomic status-related inequality of hypertension prevalence in Bangladesh. Methods Cross-sectional analysis was conducted using nationally representative two waves of the Bangladesh Demographic and Health Survey (BDHS) in 2011 and 2017–18. Survey participants were adults 18 years or older- which included detailed biomarker and anthropometric measurements of 23539 participants. The change in prevalence of hypertension was estimated, and adjusted odds ratios were obtained using multivariable survey logistic regression models. Further, Wagstaff decomposition method was also used to analyze the relative contributions of factors to hypertension. Results From 2011 to 2018, the hypertension prevalence among adults aged ≥35 years increased from 25.84% to 39.40% (p<0.001), with the largest relative increase (97%) among obese individuals. The prevalence among women remained higher than men whereas the relative increase among men and women were 75% and 39%, respectively. Regression analysis identified age and BMI as the independent risk factors of hypertension. Other risk factors of hypertension were sex, marital status, education, geographic region, wealth index, and diabetes status in both survey years. Female adults had significantly higher hypertension risk in both survey years in the overall analysis in, however, in the subgroup analysis, the gender difference in hypertension risk was not significant in rural 2011 and urban 2018 samples. Decomposition analysis revealed that the contributions of socio-economic status related inequality of hypertension in 2011 were46.58% and 20.85% for wealth index and BMI, respectively. However, the contributions of wealth index and BMI have shifted to 12.60% and 55.29%, respectively in 2018. Conclusion The prevalence of hypertension among Bangladeshi adults has increased significantly, and there is no subgroup where it is decreasing. Population-level approaches directed at high-risk groups (overweight, obese) should be implemented thoroughly. We underscore prevention strategies by following strong collaboration with stakeholders in the health system of the country to adopt healthy lifestyle choices.

Predictors of wealth-related inequality in institutional delivery: a decomposition analysis using Nepal multiple Indicator cluster survey (MICS) 2019

Background Inequality in maternal healthcare use is a major concern for low-and middle-income countries (LMICs). Maternal health indicators at the national level have markedly improved in the last couple of decades in Nepal. However, the progress is not uniform across different population sub-groups. This study aims to identify the determinants of institutional delivery, measure wealth-related inequality, and examine the key components that explain the inequality. Methods Most recent nationally representative Multiple Indicator Cluster Survey (MICS) 2019 was used to extract data about married women (15-49 years) with a live birth within two years preceding the survey. Logistic regression models were employed to assess the association of independent variables with the institutional delivery. The concentration curve (CC) and concentration index (CIX) were used to analyze the inequality in institutional delivery. Wealth index scores were used as a socio-economic variable to rank households. Decomposition was performed to identify the determinants that explain socio-economic inequality. Results The socio-economic status of households to which women belong was a significant predictor of institutional delivery, along with age, parity, four or more ANC visits, education status of women, area of residence, sex of household head, religious belief, and province. The concentration curve was below the line of equality and the relative concentration index (CIX) was 0.097 (p < 0.001), meaning the institutional delivery was disproportionately higher among women from wealthy groups. The decomposition analysis showed the following variables as the most significant contributor to the inequality: wealth status of women (53.20%), education of women (17.02%), residence (8.64%) and ANC visit (6.84%). Conclusions To reduce the existing socio-economic inequality in institutional delivery, health policies and strategies should focus more on poorest and poor quintiles of the population. The strategies should also focus on raising the education level of women especially from the rural and relatively backward province (Province 2). Increasing antenatal care (ANC) coverage through outreach campaigns is likely to increase facility-based delivery and decrease inequality. Monitoring of healthcare indicators at different sub-population levels (for example wealth, residence, province) is key to ensure equitable improvement in health status and achieve universal health coverage (UHC).

Newborn low birth weight: do socio-economic inequality still persist in India?

Background The incidence of preterm birth and subsequent low birth weight (LBW) are vital global public health issues. It contributes to high infant and child mortality in the early stages of life and later on in adult life; it increases the risk for non-communicable diseases. The study aims to understand the socio-economic status-related inequality for LBW among children in India. It hypothesises that there is no association between the socio-economic status of the household and the newborn’s LBW in India. Methods The study utilised data from the fourth round of the National Family Health Survey, a national representative cross-sectional survey conducted in 2015-16 (N = 127,141). The concentration index (CCI) and the concentration curve (CC) measured socio-economic inequality in low birth status among newborns. Wagstaff decomposition further analysed key contributors in CCI by segregating significant covariates. Results About 18.2% of children had low birth weight status. The value of concentration was − 0.05 representing that low birth weight status is concentrated among children from lower socio-economic status. Further, the wealth quintile explained 76.6% of the SES related inequality followed by regions of India (− 44%) and the educational status of mothers (43.4%) for LBW among children in India. Additionally, the body mass index of the women (28.4%), ante-natal care (20.8%) and residential status (− 15.7%) explained SES related inequality for LBW among children in India. Conclusion Adequate attention should be given to the mother’s nutritional status. Awareness of education and usage of health services during pregnancy should be promoted. Further, there is a need to improve the coverage and awareness of the ante-natal care (ANC) program. In such cases, the role of the health workers is of utmost importance. Programs on maternal health services can be merged with maternal nutrition to bring about an overall decline in the LBW of children in India.

Predictors of health insurance enrolment and wealth-related inequality in Nepal: evidence from Multiple Indicator Cluster Survey (MICS) 2019

ObjectivesWe analysed predictors of health insurance enrolment in Nepal, measured wealth-related inequality and decomposed inequality into its contributing factors.DesignCross-sectional study.SettingWe used nationally representative data based on Nepal Multiple Indicator Cluster Survey 2019. Out of 10 958 households included in this study, 6.95% households were enroled in at least one health insurance scheme.Primary outcomemeasures health insurance (of any type) enrolment.ResultsHouseholds were more likely to have health insurance membership when household head have higher secondary education or above compared with households without formal education (adjusted OR 1.87; 95% CI: 1.32 to 2.64)). Households with mass media exposure were nearly three times more likely to get enroled into the schemes compared with their counterparts (adjusted OR 2.96; 95% CI 2.03 to 4.31). Hindus had greater odds of being enroled (adjusted OR 1.82; 95% CI 1.20 to 2.77) compared with non-Hindus. Dalits were less likely to get enroled compared with Brahmin, Chhetri and Madhesi (adjusted OR 0.66; 95% CI 0.47 to 0.94). Households from province 2, Bagmati and Sudurpaschim were less likely to have membership compared with households from province 1. Households from Richer and Richest wealth quintiles were more than two times more likely to have health insurance membership compared with households from the poorest wealth quintile. A positive concentration index 0.25 (95% CI 0.21 to 0.30; p<0.001) indicated disproportionately higher health insurance enrolment among wealthy households.ConclusionsEducation of household head, exposure to mass media, religious and ethnic background, geographical location (province) and wealth status were key predictors of health insurance enrolment in Nepal. There was a significant wealth-related inequality in health insurance affiliation. The study recommends regular monitoring of inequality in health insurance enrolment across demographic and socioeconomic groups to ensure progress towards Universal Health Coverage.

Assessing Income-Related Inequality on Health Service Utilization among Chinese Rural Migrant Workers with New Co-Operative Medical Scheme: A Multilevel Approach

Background: Eliminating inequality in health service utilization is an explicit goal of China’s health system. Rural migrant workers with New Rural Cooperative Medical Insurance (NCMS) still face the dilemma of limited health service; however, there is a lack of analysis or measurement on the income-related inequality of health service utilization. Method: The nationally representative data of the China Labor-Force Dynamic Survey in 2016 were used for analysis. Multilevel regressions were used to obtain robust estimates and to account for various covariates associated with health service utilization of rural migrant workers with NCMS. The concentration index and its decomposition method were applied to quantify the income-related inequality of health service utilization of rural migrant workers. Result: The multilevel model analysis indicated that influencing factors of health service utilization were diversified, including gender, city service quality index, type of industry, the per capita annual income, marital status, health self-assessment, the community health index and the number of friends. The concentration indices of the total cost of inpatient and OOP cost of inpatient were 0.102 (95%CI: 0.031, 0.149), and the CI of OOP cost of inpatient was 0.094 (95%CI: 0.007, 0.119), respectively. The horizontal inequality indices of the total cost of inpatient and OOP cost of inpatient were 0.051 and 0.009, respectively. Conclusion: Our study presented a unique opportunity to examine the potential influence factors of health service utilization of rural migrant workers with NCMS, and highlighted that unequal health service utilization is evident among rural migrant workers with NCMS. This study provides important corroborative evidence to take full account of the contribution of each determinant to the inequality and health service needs among rural migrant workers with NCMS, in order to improve the basic medical insurance and social security systems—particularly for some marginal groups in China.

Urban-rural and Gender Differential in Depressive Symptoms Among Older Adults in India

Background: To date, evidence remained inconclusive explaining rural-urban and male-female differential in depression. Unlike other previous research on the association of several risk factors with depressive symptoms among the elderly, this study focussed on the socio-economic status-related inequality in the prevalence of depression among the elderly along with focussing urban-rural and male-female gradients of depression among the elderly.Methods: This study used data from Longitudinal Ageing Study in India (LASI) wave-I, 2017-18, survey. The outcome variable for this study was self-reported depression. Bivariate analysis was used to understand the prevalence by sociodemographic clusters. Fairlie decomposition analysis has been done to measures rural-urban inequalities for depression among older men and women.Results: Results found that around 22 percent of urban elderly and 17 percent of rural elderly reported depression. A higher proportion of female elderly (22.6% vs. 18.4%) reported depression than male elderly. Almost one in every five elderly (20.6%) reported depression in India. The results found that a higher percentage of women in rural and urban areas reported depression than their male counterparts. While examining SES-related inequality in the prevalence of depression, education was a significant factor explaining the SES-related inequality in the prevalence of depression among female elderly and not in male elderly.Conclusion: Given the large proportion of elderly reporting depression, this study highlights the need for improving health care services among the elderly. The increasing burden of depression in specific sub-populations also highlights the importance of understanding the broader consequences of depression among rural and female elderly.

Socioeconomic Inequalities in Staff Physical Activity: Evidence from the SHAHWAR Cohort Study in Iran

Background: This study was aimed to investigate socioeconomic-related inequality in physical activity (PA) among Staff of Medical Sciences University in Shahroud, Iran.Methods: Data were extracted from the first phase of the SHAHWAR cohort study. The Concentration index (CI) and Wagstaff decomposition method were applied to determine socioeconomic-related inequality in PPA and its contributors, respectively.Results: CIs of poor total PA (PTPA) and poor work-related PA (PWRPA) were 0.092 and 0.141, indicating their more concentration among staff of higher socioeconomic groups. Furthermore, the negative CI of poor leisure-time PA (PLTPA) (-0.191) suggests that it disfavors staff from lower socioeconomic groups. While PWRPA, Subjective social status (SSS), socioeconomic status (SES), and gender were positively contributed to the measured inequality in PTPA (65.3%, 37.9%, 18.6%, and 16.6%, respectively), residence in urban areas and PLTPA have negative contributions (64% and 27%, respectively). Similarly, SES, marital status, and residence in urban areas positively contributed to the inequality of PLTPA by 53.4%, 36.2%, and 23.5% respectively. Whereas, gender had the most negative contribution by 28.7%. Residence in urban areas, SES, SSS, and shift work were all positively contributed to the measured inequality in PWRPA (its more concentration among staff from high SES groups) by 28.4%, 20%, 15.2%, and 12.7%, respectively, while the opposite is true for gender by the contribution of 13.3%.Conclusions: Different patterns of PPA inequality revealed that health promotion programs should aim to educate and support higher SES staff to increase their PA in workplace, leisure time, and transportation, and lower SES staff to increase their leisure-time PA.