Entrenched Geographical and Socioeconomic Disparities in Child Mortality: Trends in Absolute and Relative Inequalities in Cambodia

Background

Cambodia has made considerable improvements in mortality rates for children under the age of five and neonates. These improvements may, however, mask considerable disparities between subnational populations. In this paper, we examine the extent of the country''s child mortality inequalities.

Methods

Mortality rates for children under-five and neonates were directly estimated using the 2000, 2005 and 2010 waves of the Cambodian Demographic Health Survey. Disparities were measured on both absolute and relative scales using rate differences and ratios, and where applicable, slope and relative indices of inequality by levels of rural/urban location, regions and household wealth.

Findings

Since 2000, considerable reductions in under-five and to a lesser extent in neonatal mortality rates have been observed. This mortality decline has, however, been accompanied by an increase in relative inequality in both rates of child mortality for geography-related stratifying markers. For absolute inequality amongst regions, most trends are increasing, particularly for neonatal mortality, but are not statistically significant. The only exception to this general pattern is the statistically significant positive trend in absolute inequality for under-five mortality in the Coastal region. For wealth, some evidence for increases in both relative and absolute inequality for neonates is observed.

Conclusion

Despite considerable gains in reducing under-five and neonatal mortality at a national level, entrenched and increased geographical and wealth-based inequality in mortality, at least on a relative scale, remain. As expected, national progress seems to be associated with the period of political and macroeconomic stability that started in the early 2000s. However, issues of quality of care and potential non-inclusive economic growth might explain remaining disparities, particularly across wealth and geography markers. A focus on further addressing key supply and demand side barriers to accessing maternal and child health care and on the social determinants of health will be essential in narrowing inequalities.     

Absolute versus Relative Environmental Sustainability

The cradle‐to‐cradle (C2C) concept has emerged as an alternative to the more established eco‐efficiency concept based on life cycle assessment (LCA). The two concepts differ fundamentally in that eco‐efficiency aims to reduce the negative environmental footprint of human activities while C2C attempts to increase the positive footprint. This article discusses the strengths and weaknesses of each concept and suggests how they may learn from each other. The eco‐efficiency concept involves no long‐term vision or strategy, the links between resource consumption and waste emissions are not well related to the sustainability state, and increases in eco‐efficiency may lead to increases in consumption levels and hence overall impact. The C2C concept's disregard for energy efficiency means that many current C2C products will likely not perform well in an LCA. Inherent drawbacks are restrictions on the development of new materials posed by the ambition of continuous loop recycling, the perception that human interactions with nature can benefit all parts of all ecosystems, and the hinted compatibility with continued economic growth. Practitioners of eco‐efficiency can benefit from the visions of C2C to avoid a narrow‐minded focus on the eco‐efficiency of products that are inherently unsustainable. Moreover, resource efficiency and positive environmental effects could be included more strongly in LCA. Practitioners of C2C on the other hand should recognize the value of LCA in addressing trade‐offs between resource conservation and energy use. Also, when designing a “healthy emission” it should be recognized that it will often have an adverse effect on parts of the exposed ecosystem.     

Depression-Related Work Disability: Socioeconomic Inequalities in Onset,Duration and Recurrence

Objective

Depression is a major cause of disability in working populations and the reduction of socioeconomic inequalities in disability is an important public health challenge. We examined work disability due to depression with four indicators of socioeconomic status.

Methods

A prospective cohort study of 125 355 Finnish public sector employees was linked to national register data on work disability (>9 days) due to depressive disorders (International Classification of Diseases, codes F32–F34) from January 2005 to December 2011. Primary outcomes were the onset of work disability due to depressive disorders and, among those with such disability, return to work after and recurrent episodes of work disability due to depression.

Results

We found a consistent inverse socioeconomic gradient in work disability due to depression. Lower occupational position, lower educational level, smaller residence size, and rented (vs. owner-occupied) residence were all associated with an increased risk of work disability. Return to work was slower for employees with basic education (cumulative odds ratio = 1.21, 95% CI: 1.05–1.39) compared to those with higher education. Recurrent work disability episodes due to depression were less common among upper-grade non-manual workers (the highest occupational group) than among lower-grade non-manual (hazard ratio = 1.16, 95% CI: 1.07–1.25) and manual (hazard ratio = 1.14, 95% CI: 1.02–1.26) workers.

Conclusions

These data from Finnish public sector employees show persistent socioeconomic inequalities in work disability due to depression from 2005 to 2011 in terms of onset, recovery and recurrence.     

The Relationship between Cortical Blood Flow and Sub-Cortical White-Matter Health across the Adult Age Span

Degeneration of cerebral white matter is commonly observed in aging, and the associated degradation in neural connectivity contributes to cognitive decline in older adults. Vascular dysfunction has been implicated as a potential mechanism for general age-related neural tissue deterioration; however, no prior study has examined the direct relationship between cortical vascular health and subcortical white-matter integrity. In this work, we aimed to determine whether blood supply to the brain is associated with microstructural integrity of connective tissue, and whether such associations are regionally specific and mainly accounted for by aging. We examined the association between cerebral blood flow (CBF) in the cortical mantle, measured using arterial spin labeling (ASL), and subcortical white-matter integrity, measured using diffusion tensor imaging (DTI), in a group of healthy adults spanning early to late adulthood. We found cortical CBF to be significantly associated with white-matter integrity throughout the brain. In addition, these associations were only partially tied to aging, as they remained even when statistically controlling for age, and when restricting the analyses to a young subset of the sample. Furthermore, vascular risk was not a prominent determinant of these effects. These findings suggest that the overall blood supply to the brain is an important indicator of white-matter health in the normal range of variations amongst adults, and that the decline in CBF with advancing age may potentially exacerbate deterioration of the connective anatomy of the brain.     

Dose Scaling and Extrapolation Across Age Groups

This paper considers how the logic of cross-species dose scaling applies (or does not apply) when extrapolating among differently sized humans, and specifically, when extrapolating to children. Scaling children's doses by a power of body weight predicts that they would be less sensitive to chemicals than adults, owing to faster clearance. Possible countervailing factors, however, are the role of quicker pharmacodynamic processes, differences between interspecific and ontogenetic allometry, and the complex role of inherent differences in the metabolism and physiological system of immature bodies, the last leading to uncertainty in extrapolation but not necessarily to systematic sensitivity among children. The issue of scale per se does not appear to provide a basis for positing a systematically greater sensitivity of children to toxic substances     

Neural Sensitivity to Absolute and Relative Anticipated Reward in Adolescents

Adolescence is associated with a dramatic increase in risky and impulsive behaviors that have been attributed to developmental differences in neural processing of rewards. In the present study, we sought to identify age differences in anticipation of absolute and relative rewards. To do so, we modified a commonly used monetary incentive delay (MID) task in order to examine brain activity to relative anticipated reward value (neural sensitivity to the value of a reward as a function of other available rewards). This design also made it possible to examine developmental differences in brain activation to absolute anticipated reward magnitude (the degree to which neural activity increases with increasing reward magnitude). While undergoing fMRI, 18 adolescents and 18 adult participants were presented with cues associated with different reward magnitudes. After the cue, participants responded to a target to win money on that trial. Presentation of cues was blocked such that two reward cues associated with $.20, $1.00, or $5.00 were in play on a given block. Thus, the relative value of the $1.00 reward varied depending on whether it was paired with a smaller or larger reward. Reflecting age differences in neural responses to relative anticipated reward (i.e., reference dependent processing), adults, but not adolescents, demonstrated greater activity to a $1 reward when it was the larger of the two available rewards. Adults also demonstrated a more linear increase in ventral striatal activity as a function of increasing absolute reward magnitude compared to adolescents. Additionally, reduced ventral striatal sensitivity to absolute anticipated reward (i.e., the difference in activity to medium versus small rewards) correlated with higher levels of trait Impulsivity. Thus, ventral striatal activity in anticipation of absolute and relative rewards develops with age. Absolute reward processing is also linked to individual differences in Impulsivity.     

Determinants of Socioeconomic Inequalities in Traumatic Dental Injuries among Urban Indian Adolescents

Objectives

To assess socioeconomic inequalities in traumatic dental injuries (TDIs) in adolescents in New Delhi and examine the role of material, psychosocial and behavioural factors in explaining these inequalities.

Methods

We conducted a cross sectional study of 1386 adolescents aged between 12–15 years residing in three diverse areas of New Delhi. A non-invasive clinical examination was used to estimate the prevalence of TDIs, and an interviewer-administered questionnaire was used to gather relevant behavioural and socio-demographic data. Multiple logistic regression models were used to assess the association between area based socioeconomic position and TDIs.

Results

The overall prevalence of TDIs was 10.9%. Social inequalities in the prevalence of TDIs were observed across the adolescent population according to their area of residence. Socio-economic group differences in the prevalence of TDIs remained statistically significant after adjusting for demographic factors, material resources, social capital, social support and health affecting behaviours (OR 3.36, 95% CI 1.75–6.46 and OR 3.99, 95% CI 1.86–8.56 for adolescents from resettlement areas and urban slums respectively in comparison to middle class adolescents). Different psychosocial, material and socio-demographic variables did not attenuate the estimates for the relationship between area socioeconomic position and TDIs.

Conclusion

Area of residence was a strong predictor of TDIs in adolescents with a higher prevalence in more deprived areas. Social inequalities in TDIs were not explained by psychosocial and behavioural variables. Health promoting policies aimed at improving the physical environment in which adolescents reside might be instrumental in reducing the prevalence of TDIs and associated inequalities.     

Local Modelling Techniques for Assessing Micro-Level Impacts of Risk Factors in Complex Data: Understanding Health and Socioeconomic Inequalities in Childhood Educational Attainments

Although inequalities in health and socioeconomic status have an important influence on childhood educational performance, the interactions between these multiple factors relating to variation in educational outcomes at micro-level is unknown, and how to evaluate the many possible interactions of these factors is not well established. This paper aims to examine multi-dimensional deprivation factors and their impact on childhood educational outcomes at micro-level, focusing on geographic areas having widely different disparity patterns, in which each area is characterised by six deprivation domains (Income, Health, Geographical Access to Services, Housing, Physical Environment, and Community Safety). Traditional health statistical studies tend to use one global model to describe the whole population for macro-analysis. In this paper, we combine linked educational and deprivation data across small areas (median population of 1500), then use a local modelling technique, the Takagi-Sugeno fuzzy system, to predict area educational outcomes at ages 7 and 11. We define two new metrics, “Micro-impact of Domain” and “Contribution of Domain”, to quantify the variations of local impacts of multidimensional factors on educational outcomes across small areas. The two metrics highlight differing priorities. Our study reveals complex multi-way interactions between the deprivation domains, which could not be provided by traditional health statistical methods based on single global model. We demonstrate that although Income has an expected central role, all domains contribute, and in some areas Health, Environment, Access to Services, Housing and Community Safety each could be the dominant factor. Thus the relative importance of health and socioeconomic factors varies considerably for different areas, depending on the levels of each of the other factors, and therefore each component of deprivation must be considered as part of a wider system. Childhood educational achievement could benefit from policies and intervention strategies that are tailored to the local geographic areas'' profiles.     

Socioeconomic Inequalities in Childhood Undernutrition in India: Analyzing Trends between 1992 and 2005

Background

India experienced a rapid economic boom between 1991 and 2007. However, this economic growth has not translated into improved nutritional status among young Indian children. Additionally, no study has assessed the trends in social disparities in childhood undernutrition in the Indian context. We examined the trends in social disparities in underweight and stunting among Indian children aged less than three years using nationally representative data.

Methods

We analyzed data from the three cross-sectional rounds of National Family Health Survey of India from 1992, 1998 and 2005. The social factors of interest were: household wealth, maternal education, caste, and urban residence. Using multilevel modeling to account for the nested structure and clustering of data, we fit multivariable logistic regression models to quantify the association between the social factors and the binary outcome variables. The final models additionally included age, gender, birth order of child, religion, and age of mother. We analyzed the trend by testing for interaction of the social factor and survey year in a dataset pooled from all three surveys.

Results

While the overall prevalence rates of undernutrition among Indian children less than three decreased over the 1992–2005 period, social disparities in undernutrition over these 14 years either widened or stayed the same. The absolute rates of undernutrition decreased for everyone regardless of their social status. The disparities by household wealth were greater than the disparities by maternal education. There were no disparities in undernutrition by caste, gender or rural residence.

Conclusions

There was a steady decrease in the rates of stunting in the 1992–2005 period, while the decline in underweight was greater between 1992 and 1998 than between 1998 and 2005. Social disparities in childhood undernutrition in India either widened or stayed the same during a time of major economic growth. While the advantages of economic growth might be reaching everyone, children from better-off households, with better educated mothers appear to have benefited to a greater extent than less privileged children. The high rates of undernutrition (even among the socially advantaged groups) and the persistent social disparities need to be addressed in an urgent and comprehensive manner.     

同位素标记相对和绝对定量技术研究进展

定量蛋白质组学是蛋白质研究的前沿学科。目前常用的定量蛋白质组学研究技术有荧光差异凝胶电泳（DIGE）、同位素亲和标记（ICAT）等。同位素标记相对和绝对定量（iTRAQ）技术是近年来最新开发的一种新的蛋白质组学定量研究技术。结合非凝胶串联质谱技术,该技术可对复杂样本、细胞器、细胞裂解液等样本进行相对和绝对定量研究,具有较好的定量效果、较高的重复性,并可对多达四种不同样本同时进行定量分析。本文对 iTRAQ 技术的原理、实验方法及应用进展进行了综述。     

Potential Biases in Estimating Absolute and Relative Case-Fatality Risks during Outbreaks

Estimating the case-fatality risk (CFR)—the probability that a person dies from an infection given that they are a case—is a high priority in epidemiologic investigation of newly emerging infectious diseases and sometimes in new outbreaks of known infectious diseases. The data available to estimate the overall CFR are often gathered for other purposes (e.g., surveillance) in challenging circumstances. We describe two forms of bias that may affect the estimation of the overall CFR—preferential ascertainment of severe cases and bias from reporting delays—and review solutions that have been proposed and implemented in past epidemics. Also of interest is the estimation of the causal impact of specific interventions (e.g., hospitalization, or hospitalization at a particular hospital) on survival, which can be estimated as a relative CFR for two or more groups. When observational data are used for this purpose, three more sources of bias may arise: confounding, survivorship bias, and selection due to preferential inclusion in surveillance datasets of those who are hospitalized and/or die. We illustrate these biases and caution against causal interpretation of differential CFR among those receiving different interventions in observational datasets. Again, we discuss ways to reduce these biases, particularly by estimating outcomes in smaller but more systematically defined cohorts ascertained before the onset of symptoms, such as those identified by forward contact tracing. Finally, we discuss the circumstances in which these biases may affect non-causal interpretation of risk factors for death among cases.The case-fatality risk (CFR) is a key quantity in characterizing new infectious agents and new outbreaks of known agents. The CFR can be defined as the probability that a case dies from the infection. Several variations of the definition of “case” are used for different infections, as discussed in Box 1. Under all these definitions, the CFR characterizes the severity of an infection and is useful for planning and determining the intensity of a response to an outbreak [1,2]. Moreover, the CFR may be compared between cases who do and do not receive particular treatments as a way of trying to estimate the causal impact of these treatments on survival. Such causal inference might ideally be done in a randomized trial in which individuals are randomly assigned to treatments, but this is often not possible during an outbreak for logistical, ethical, and other reasons [3]. Therefore, observational estimates of CFR under different treatment conditions may be the only available means to assess the impact of various treatments.

Box 1. Definition of the CFR.

The CFR itself is an ambiguous term, as its definition and value depend on what qualifies an individual to be a “case.” Several different precise definitions of CFR have been used in practice, as have several imprecise ones. The infection-fatality risk (sometimes written IFR) defines a case as a person who has shown evidence of infection, either by clinical detection of the pathogen or by seroconversion or other immune response. Such individuals may or may not be symptomatic, though asymptomatic ones may go undetected. The symptomatic case-fatality risk (sCFR) defines a case as someone who is infected and shows certain symptoms. Infection in many outbreaks is given several gradations, including confirmed (definitive laboratory confirmation), probable (high degree of suspicion, by various clinical and epidemiologic criteria, without laboratory confirmation), and possible or suspected (lower degree of suspicion). This paper describes issues in estimating any of these risks or comparing them across groups, but does not go into the details of each possible definition.Furthermore, unlike risks commonly used in epidemiologic research (e.g., the 5-year mortality risk), the length of the period during which deaths are counted for the CFR is rarely explicit, probably because it is considered to be short enough to avoid ambiguity in the definition of CFR. However, a precise definition of the CFR would need to include the risk period, e.g., the 1-month CFR of Ebola. Clearly, the definition of CFR for a particular investigation should be specified as precisely as possible.However, observational studies conducted in the early phases of an outbreak, when public health authorities are appropriately concentrating on crisis response and not on rigorous study design, are challenging. A common problem is that disease severity of the cases recorded in a surveillance database will differ, perhaps substantially, from that of all cases in the population. This issue has arisen in the present epidemic of Ebola virus disease in West Africa and in many previous outbreaks and epidemics [4–9] and will continue to arise in future ones.Here we outline two biases that may occur when estimating the CFR in a population from a surveillance database, and three more biases that may occur when comparing the CFR between subgroups to estimate the causal effect of medical interventions. We also briefly consider the applicability of these biases to a different application: comparing the CFR across different groups of people, for example, by geography, sex, age, comorbidities, and other “unchangeable” risk factors. Such factors are “unchangeable” in the sense that they are not candidates for intervention in the setting of the outbreak, though some could, of course, change over longer timescales. The goal of estimating the CFR in groups defined by such unchangeable factors is not to understand the causal role of these factors in mortality, but to develop a predictive model for mortality that might be used to improve prognostic accuracy or identify disparities. Such predictions may be affected by survivorship bias and selection bias, but not by confounding, as we discuss.