Income-related inequality and inequity in children's health care: A longitudinal analysis using data from Brazil

Concept analysis of Neonatal Near Miss

OBJECTIVE

To analyze the concept of Neonatal Near Miss (NNM) using Walker and Avant's method.

METHOD

This study employs conceptual analysis following Walker and Avant's model, involving concept selection, objective definition, identification of potential uses, determination of attributes, model case creation, additional case consideration, antecedent identification, consequent analysis, and empirical reference examination. To elucidate the concept, a scoping review was conducted across journals indexed in scientific databases such as Web of Science, EMBASE, SCOPUS, and MEDLINE/PubMed.

RESULTS

The analysis encompassed 43 articles, revealing diverse definitions of neonatal near miss across different contexts. A comprehensive definition emerged from identified antecedents: risk of death, susceptibility to adverse outcomes, and potential adverse events. These antecedents were categorized into maternal conditions, neonatal conditions, and healthcare assistance.

CONCLUSION

The analysis and definition of the NNM concept was successful, and its antecedents, attributes, and consequences were delineated.

IMPLICATIONS

Identifying the risk factors associated with NNM cases may contribute to reducing infant morbidity and mortality and improving the quality of care, facilitating future research and improving the use of the NNM concept.

Intimate Partner Violence Against Brazilian Mothers is Associated With Their Children's Lower Quality-of-Life Scores: A Cross-Sectional Study During the COVID-19 Pandemic

The COVID-19 pandemic led to family and routine reorganization, triggering social problems. Women were further exposed to domestic violence, especially intimate partner violence (IPV), with consequences to their and their children's health. However, few Brazilian studies address the issue, especially considering the pandemic and its restrictive measures. The objective was to verify the relationship between mothers'/caregivers' IPV and their children's neuropsychomotor development (NPMD) and quality of life (QOL) during the pandemic. Seven hundred one female mothers/caregivers of children (0-12 years old) responded to the online epidemiological inquiry. NPMD was investigated with the Caregiver Reported Early Development Instruments (CREDI-short version); QOL, with the Pediatric Quality of Life Inventory (PedsQL™); and IPV, with the Composite Abuse Scale (CAS). The independence chi-square test was used, with Fisher's exact statistics, in SPSS Statistics 27^®. Children whose mothers were exposed to IPV were 2.68 times as likely to have a "low" QOL score (χ²(1) = 13.144, P < .001; φ = 0.137). This indicates a possible environmental influence on the children's QOL, which may have been aggravated by strict social distancing during the COVID-19 pandemic.

Explanation of Socio-economic Inequality in Medicine Use: A Cross-sectional Analysis from Iran

Background

Despite the favorable progress in the production of medicines, there is no significant access to these important health inputs among different socio-economic groups.

Objectives

This study aimed to measure and explain socio-economic inequality in prescribed and non-prescribed medicine use in Iran.

Methods

Data were obtained from a recent household survey on health services in Iran conducted in 2016. The Erreygers concentration index (ECI) was used to measure socio-economic inequality in the use of prescribed and non-prescribed medicines. In addition, Decomposition analysis was conducted to explain socio-economic inequality.

Results

The ECI revealed pro-rich socio-economic inequality in prescribed medicine use (ECI = 0.067, SE = 0.010), indicating that prescribed medicine use was concentrated on the better-offs. On the other hand, this index showed pro-poor inequality in non-prescribed medicine use (ECI = -0.064, SE = 0.009). Decomposition analysis showed that economic status and place of residence were the main determinants of socio-economic inequality in prescribing medicines. These factors and the number of health care needs explained the majority of socio-economic inequality in non-prescribed medicine use.

Conclusions

Despite previous positive beliefs, we found remarkable socio-economic inequality in the use of medicines in Iran. Facilitating access to pharmaceutical services for disadvantaged households and rural residents and promoting of national essential medicines list could be recommended against socio-economic inequality in the pharmaceutical market of Iran.

Grandchild care, inadequate medical insurance protection, and inequalities in socioeconomic factors exacerbate childhood obesity in China

This study examines the influences of grandchild care and medical insurance on childhood obesity. Nationally representative longitudinal data-from the China Family Panel Studies 2010-2020-of 26,902 school-age children and adolescents aged 6-16 years and China's new reference standard ("WS/T586-2018") are used to identify a child's obesity status. Using binary mixed-effects logistic regression models and the Blinder-Oaxaca decomposition method, this study explores the roots of obesity inequalities and finds that at least 15% of Chinese children aged 6-16 were obese in the 2010s. The logistic regression analysis results indicate that grandchild care, public medical insurance, and commercial medical insurance are key risk factors of child obesity. However, the influences are heterogeneous in different groups: Grandchild care and public medical insurance increase urban-rural obesity inequalities because of a distribution effect, and grandchild care may also exacerbate children obesity inequalities between left-behind and non-left-behind children owing to the event shock of parental absence. Inequalities in socioeconomic status (SES) factors such as income, education, and region also cause obesity inequalities. These results indicate that child obesity and its inequalities are rooted in multidimensional environmental inequalities, including medical protection policies and its benefit incidence; intergenerational behavior and family SES factors; and urban-rural and left-behind risk shocks. This study provides new evidence for the development of population-based interventions and equitable medical insurance policies to prevent the deterioration of child obesity among Chinese school-age children and adolescents.

Inequality and Inequity in the Use of Oral Health Services in Australian Adults

OBJECTIVE

Social determinants drive disparities in dental visiting. This study aimed to measure inequality and inequity in dental visiting among Australian adults.

METHODS

Data were obtained from the National Study of Adult Oral Health (2017 to 2018). Participants were Australian adults aged ≥30 y. The outcome of interest was dental visiting in the last 12 mo. Disparity indicators included education and income. Other sociodemographic characteristics included age, gender, Indigenous status, main language, place of birth, residential location, health card and dental insurance status, and individual's self-rated and impaired oral health. To characterize inequality in dental service use, we examined bivariate relationships using indices of inequality: the absolute and relative concentration indexes and the slope and relative indexes of inequality. Inequalities were depicted through concentration curves. Indirect standardization with a nonlinear model was used to measure inequity.

RESULTS

A total of 9,919 Australian adults were included. Bivariate analysis showed a gradient by education and income on dental visiting, with 48% of those with lowest educational attainment/income having not visited a dentist in the last 12 mo. The concentration curves showed pro-low education and pro-poor income inequalities. All measures of absolute and relative indices were negative, indicating that from the bottom to the top of the socioeconomic ladder (education and income), the prevalence of no dental visiting decreased: absolute and relative concentration index estimates were approximately 2.5% and 5.0%, while the slope and relative indexes of inequality estimates were 14% to 18% and 0.4%, respectively. After need standardization, the group with the highest education or income had almost 1.5-times less probability of not having a dental visit in the previous year than those with the lowest education or income.

CONCLUSION

The use of oral health services exhibited socioeconomic inequalities and inequities, disproportionately burdening disadvantaged Australian adults.

KNOWLEDGE TRANSFER STATEMENT

The results of this study can be used by policy makers when planning a dental labor force in relation to the capacity of supply dental services to 1) reduce the inequality and inequity in the use of oral health services and 2) meet identified oral health needs across the Australian population, which is important for preventive dental care.

Use of oral health care services in the United States: unequal, inequitable-a cross-sectional study

Background

Social determinants drive disparities in dental visiting. Disparities can be measured simply by comparing outcomes between groups (inequality) but can also consider concepts of social justice or fairness (inequity). This study aimed to assess differences in dental visiting in the United States in terms of both social inequality and inequity.

Methods

Data were obtained from a cross-sectional study—the National Health and Nutrition Examination Survey (NHANES) 2015–2016, and participants were US adults aged 30+ years. The outcome of interest, use of oral health care services, was measured in terms of dental visiting in the past 12 months. Disparity was operationalized through education and income. Other characteristics included age, gender, race/ethnicity, main language, country of birth, citizenship and oral health status. To characterize existing inequality in dental service use, we examined bivariate relationships using indices of inequality: the absolute and relative concentration index (ACI and RCI), the slope index of inequality (SII) and relative index of inequality (RII) and through concentration curves (CC). Indirect standardization with a non-linear model was used to measure inequity.

Results

A total of 4745 US adults were included. Bivariate analysis showed a gradient by both education and income in dental visiting, with a higher proportion (> 60%) of those with lower educational attainment /lower income having not visited a dentist. The concentration curves showed pro-higher education and income inequality. All measures of absolute and relative indices were negative, indicating that from lower to higher socioeconomic position (education and income), the prevalence of no dental visiting decreased: ACI and RCI estimates were approximately 8% and 20%, while SII and RII estimates were 50% and 30%. After need-standardization, the group with the highest educational level had nearly 2.5 times- and the highest income had near three times less probability of not having a dental visit in the past 12 months than those with the lowest education and income, respectively.

Conclusion

The findings indicate that use of oral health care is threatened by existing social inequalities and inequities, disproportionately burdening disadvantaged populations. Efforts to reduce both oral health inequalities and inequities must start with action in the social, economic and policy spheres.

Sociodemographic inequities in nurturing care for early childhood development across Brazilian municipalities

Providing an enabling nurturing care environment for early childhood development (ECD) that cuts across the five domains of the Nurturing Care Framework (i.e., good health, adequate nutrition, opportunities for early learning, security and safety and responsive caregiving) has become a global priority. Brazil is home to approximately 18.5 million children under 5 years of age, of which 13% are at risk of poor development due to socio‐economic inequalities. We explored whether the Early Childhood Friendly Municipal Index (IMAPI) can detect inequities in nurturing care ECD environments across the 5570 Brazilian municipalities. We examined the validity of the IMAPI scores and conducted descriptive analyses for assessing sociodemographic inequities by nurturing care domains and between and within regions. The strong correlations between school achievement (positive) and socially vulnerable children (negative) confirmed the IMAPI as a multidimensional nurturing care indicator. Low IMAPI scores were more frequent in the North (72.7%) and Northeast (63.3%) regions and in small (47.7%) and medium (43.3%) size municipalities. Conversely, high IMAPI scores were more frequent in the more prosperous South (52.9%) and Southeast (41.2%) regions and in metropolitan areas (41.2%). The security and safety domain had the lowest mean differences (MDs) among Brazilian regions (MD = 5) and population size (MD = 3). Between‐region analyses confirmed inequities between the North/Northeast and South/Southeast. The biggest within‐region inequity gaps were found in the Northeast (from −22 to 15) and the North (−21 to 19). The IMAPI distinguished the nurturing care ECD environments across Brazilian municipalities and can inform equitable and intersectoral multilevel decision making.

Nurturing care indicators for the Brazilian Early Childhood Friendly Municipal Index (IMAPI)

The Nurturing Care Framework (NCF) calls for establishing a global monitoring and accountability systems for early childhood development (ECD). Major gaps to build low-cost and large-scale ECD monitoring systems at the local level remain. In this manuscript, we describe the process of selecting nurturing care indicators at the municipal level from existing routine information systems to develop the Brazilian Early Childhood Friendly Index (IMAPI). Three methodological steps developed through a participatory decision-making process were followed. First, a literature review identified potential indicators to translate the NCF domains. Four technical panels composed of stakeholders from federal, state and municipal levels were consulted to identify data sources, their availability at the municipal level and the strengths and weakness of each potential indicator. Second, national and international ECD experts participated in two surveys to score, following a SMART approach, the expected performance of each nurturing care indicator. This information was used to develop analytical weights for each indicator. Third, informed by strengths and weaknesses pointed out in the previous steps, the IMAPI team reached consensus on 31 nurturing care indicators across the five NCF domains (Good health [n = 14], Adequate nutrition [4], Responsive caregiving [1], Opportunities for early learning [7] and Security and safety [4]). IMAPI represents the first attempt to select nurturing care indicators at the municipal level using data from existing routine information systems.