Search

With overall global improvements in life expectancy, one important concern is whether there is cross-country convergence in life expectancy at various ages. Insights in convergence patterns can help realign research priorities help governments better structure health investments across various age groups. We reveal global patterns in life expectancy improvements and identify convergent clubs in life expectancy at various ages for 201 countries / areas between 1950 and 2015. In the case of life expectancy at younger ages, most countries are moving in the same direction, but we observe significant cross-country variation for older adults and the elderly. Further, we observe increasing variance in life expectancy for older adults and elderly across countries. Increasing global heterogeneity in survival experience of older adults and the elderly population thus has remained a neglected aspect in the discussions on global life expectancy improvements. Data, research and policy focus beyond life-expectancy at birth is therefore critical to accelerate survival gains among older adults and elderly, particularly from the developing world.

BackgroundIn light of the opioid epidemic in the United States, there is growing concern about the use of opioids in Sweden as it may lead to misuse and overuse and, in turn, severe public health problems. However, little is known about the distribution of opioid use across different demographic and socioeconomic dimensions in the Swedish general population. Therefore, we applied an intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA), to obtain an improved mapping of the risk heterogeneity of and socioeconomic inequalities in opioid prescription receipt.Methods and findingsUsing data from 6,846,106 residents in Sweden aged 18 and above, we constructed 72 intersectional strata from combinations of gender, age, income, cohabitation status, and presence or absence of psychological distress. We modelled the absolute risk (AR) of opioid prescription receipt in a series of multilevel logistic regression models distinguishing between additive and interaction effects. By means of the Variance Partitioning Coefficient (VPC) and the area under the receiver operating characteristic curve (AUC), we quantified the discriminatory accuracy (DA) of the intersectional strata for discerning those who received opioid prescriptions from those who did not. The AR of opioid prescription receipt ranged from 2.77% (95% CI 2.69-2.86) among low-income men aged 18-34, living alone, without psychological distress, to 28.25% (95% CI 27.95-28.56) among medium-income women aged 65 and older, living alone, with psychological distress. In a model that conflated both additive and interaction effects, the intersectional strata had a fair DA for discerning opioid users from non-users (VPC = 13.2%, AUC = 0.68). However, in the model that decomposed total effects into additive and interaction effects, the VPC was very low (0.42%) indicating the existence of small interaction effects for a number of the intersectional strata.ConclusionsThe intersectional MAIHDA approach aligns with the aims of precision public health, through improving the evidence base for health policy by increasing understanding of both health inequalities and individual heterogeneity. This approach is particularly relevant for socioeconomically conditioned outcomes such as opioid prescription receipt. We have identified intersections of social position within the Swedish population at greater risk for opioid prescription receipt.

The primary purpose of this study was to examine the association between self-reports of medication side effects and pain-related activity interference in patients with chronic pain. The potential moderators of the association between reports of side effects and pain-related activity interference were also examined. A total of 111 patients with chronic musculoskeletal pain were asked to provide, once a month for a period of 6 months, self-reports of medication use and the presence of any perceived side effects (eg, nausea, dizziness, headaches) associated with their medications. At each of these time points, patients were also asked to provide self-reports of pain intensity, negative affect, and pain-related activity interference. Multilevel modeling analyses revealed that month-to-month increases in perceived medication side effects were associated with heightened pain-related activity interference (P < 0.05). Importantly, multilevel models revealed that perceived medication side effects were associated with heightened pain-related activity interference even after controlling for the influence of patient demographics, pain intensity, and negative affect. This study provides preliminary evidence that reports of medication side effects are associated with heightened pain-related activity interference in patients with chronic pain beyond the influence of other pain-relevant variables. The implications of our findings for clinical practice and the management of patients with chronic pain conditions are discussed.

Background The majority of Countdown countries did not reach the fourth Millennium Development Goal (MDG 4) on reducing child mortality, despite the fact that donor funding to the health sector has drastically increased. When tracking aid invested in child survival, previous studies have exclusively focused on aid targeting reproductive, maternal, newborn, and child health (RMNCH). We take a multi-sectoral approach and extend the estimation to the four sectors that determine child survival: health (RMNCH and non-RMNCH), education, water and sanitation, and food and humanitarian assistance (Food/HA). Methods and findings Using donor reported data, obtained mainly from the OECD Creditor Reporting System and Development Assistance Committee, we tracked the level and trends of aid (in grants or loans) disbursed to each of the four sectors at the global, regional, and country levels. We performed detailed analyses on missing data and conducted imputation with various methods. To identify aid projects for RMNCH, we developed an identification strategy that combined keyword searches and manual coding. To quantify aid for RMNCH in projects with multiple purposes, we adopted an integrated approach and produced the lower and upper bounds of estimates for RMNCH, so as to avoid making assumptions or using weak evidence for allocation. We checked the sensitivity of trends to the estimation methods and compared our estimates to that produced by other studies. Our study yielded time-series and recipient-specific annual estimates of aid disbursed to each sector, as well as their lower- and upper-bounds in 134 countries between 2000 and 2014, with a specific focus on Countdown countries. We found that the upper-bound estimates of total aid disbursed to the four sectors in 134 countries rose from US$ 22.62 billion in 2000 to US$ 59.29 billion in 2014, with the increase occurring in all income groups and regions with sub-Saharan Africa receiving the largest sum. Aid to RMNCH has experienced the fastest growth (12.4%), followed by aid to Food/HA (9.4%), education (5.1%), and water and sanitation (5.0%). With the exception of RMNCH, the average per capita aid disbursed to each sector in the 74 Countdown countries was smaller than in non-Countdown countries. While countries with a large number of child deaths tend to receive the largest amount of disbursements, non-Countdown countries with small populations usually received the highest level of per capita aid for child survival among all 134 countries. Compared to other Countdown countries, those that met MDG 4 with a high reliance on health aid received much higher per capita aid across all sectors. These findings are robust to estimation methods. Conclusions The study suggests that to improve child survival, better targeted investments should be made in the four sectors, and aid to non-health sectors could be a possible contributor to child mortality reduction. We recommend that future studies on tracking aid for child survival go beyond the health sector and include other sectors that directly affect child survival. Investigation should also be made about the link between aid to each of the four sectors and child mortality reduction.

CONTEXT: Prior research on the determinants of child health has focused on contemporaneous risk factors such as maternal behaviors dietary factors and immediate environmental conditions. Research on intergenerational factors that might also predispose a child to increased health adversity remains limited. OBJECTIVE: To examine the association between maternal height and child mortality anthropometric failure and anemia. DESIGN SETTING AND POPULATION: We retrieved data from the 2005-2006 National Family Health Survey in India (released in 2008). The study population constitutes a nationally representative cross-sectional sample of singleton children aged 0 to 59 months and born after January 2000 or January 2001 (n = 50 750) to mothers aged 15 to 49 years from all 29 states of India. Information on children was obtained by a face-to-face interview with mothers with a response rate of 94.5%. Height was measured with an adjustable measuring board calibrated in millimeters. Demographic and socioeconomic variables were considered as covariates. Modified Poisson regression models that account for multistage survey design and sampling weights were estimated. MAIN OUTCOME MEASURES: Mortality was the primary end point; underweight stunting wasting and anemia were included as secondary outcomes. RESULTS: In adjusted models a 1-cm increase in maternal height was associated with a decreased risk of child mortality (relative risk [RR] 0.978; 95% confidence interval [CI] 0.970-0.987; P < .001) underweight (RR 0.971; 95% CI 0.968-0.974; P < .001) stunting (RR 0.971; 95% CI 0.968-0.0973; P < .001) wasting (RR 0.989; 95% CI 0.984-0.994; P < .001) and anemia (RR 0.998; 95% CI 0.997-0.999; P = .02). Children born to mothers who were less than 145 cm in height were 1.71 times more likely to die (95% CI 1.37-2.13) (absolute probability 0.09; 95% CI 0.07-0.12) compared with mothers who were at least 160 cm in height (absolute probability 0.05; 95% CI 0.04-0.07). Similar patterns were observed for anthropometric failure related to underweight and stunting. Paternal height was not associated with child mortality or anemia but was associated with child anthropometric failure. CONCLUSION: In a nationally representative sample of households in India maternal height was inversely associated with child mortality and anthropometric failure.