Does women's age matter in the SDGs era: coverage of demand for family planning satisfied with modern methods and institutional delivery in 91 low- and middle-income countries.

BACKGROUND: The Sustainable Development Goals (SDGs) include specific targets for family planning (SDG 3.7) and birth attendance (SDG 3.1.2), and require analyses disaggregated by age and other dimensions of inequality (SDG 17.18). We aimed to describe coverage with demand for family planning satisfied with modern methods (DFPSm) and institutional delivery in low- and middle-income countries across the reproductive age spectrum. We attempted to identify a typology of patterns of coverage by age and compare their distribution according to geographic regions, World Bank income groups and intervention coverage levels. METHODS: We used Demographic and Health Survey and Multiple Indicator Cluster Surveys. For DFPSm, we considered the woman's age at the time of the survey, whereas for institutional delivery we considered the woman's age at birth of the child. Both age variables were categorized into seven groups of 5 year-intervals, 15-19 up to 45-49. Five distinct patterns were identified: (a) increasing coverage with age; (b) similar coverage in all age groups; (c) U-shaped; (d) inverse U-shaped; and (e) declining coverage with age. The frequency of the five patterns was examined according to UNICEF regions, World Bank income groups, and coverage at national level of the given indicator. RESULTS: We analyzed 91 countries. For DFPSm, the most frequent age patterns were inverse U-shaped (53%, 47 countries) and increasing coverage with age (41%, 36 countries). Inverse-U shaped patterns for DFPSm was the commonest pattern among lower-middle income countries, while low- and upper middle-income countries showed a more balanced distribution between increasing with age and U-shaped patterns. In the first and second tertiles of national coverage of DFPSm, inverse U-shaped was observed in more than half of countries. For institutional delivery, declining coverage with age was the prevailing pattern (44%, 39 countries), followed by similar coverage across age groups (39%, 35 countries). Most (79%) upper-middle income countries showed no variation by age group while most low-income countries showed declining coverage with age (71%). CONCLUSION: Large inequalities in DFPSm and institutional delivery were identified by age, varying from one intervention to the other. Policy and programmatic approaches must be tailored to national patterns, and in most cases older women and adolescents will require special attention due to lower coverage and because they are at higher risk for maternal mortality and other poor obstetrical outcomes

Countdown to 2030 : tracking progress towards universal coverage for reproductive, maternal, newborn, and child health

Building upon the successes of Countdown to 2015, Countdown to 2030 aims to support the monitoring and measurement of women's, children's, and adolescents' health in the 81 countries that account for 95% of maternal and 90% of all child deaths worldwide. To achieve the Sustainable Development Goals by 2030, the rate of decline in prevalence of maternal and child mortality, stillbirths, and stunting among children younger than 5 years of age needs to accelerate considerably compared with progress since 2000. Such accelerations are only possible with a rapid scale-up of effective interventions to all population groups within countries (particularly in countries with the highest mortality and in those affected by conflict), supported by improvements in underlying socioeconomic conditions, including women's empowerment. Three main conclusions emerge from our analysis of intervention coverage, equity, and drivers of reproductive, maternal, newborn, and child health (RMNCH) in the 81 Countdown countries. First, even though strong progress was made in the coverage of many essential RMNCH interventions during the past decade, many countries are still a long way from universal coverage for most essential interventions. Furthermore, a growing body of evidence suggests that available services in many countries are of poor quality, limiting the potential effect on RMNCH outcomes. Second, within-country inequalities in intervention coverage are reducing in most countries (and are now almost non-existent in a few countries), but the pace is too slow. Third, health-sector (eg, weak country health systems) and non-health-sector drivers (eg, conflict settings) are major impediments to delivering high-quality services to all populations. Although more data for RMNCH interventions are available now, major data gaps still preclude the use of evidence to drive decision making and accountability. Countdown to 2030 is investing in improvements in measurement in several areas, such as quality of care and effective coverage, nutrition programmes, adolescent health, early childhood development, and evidence for conflict settings, and is prioritising its regional networks to enhance local analytic capacity and evidence for RMNCH

The Inverse Equity Hypothesis: Analyses of Institutional Deliveries in 286 National Surveys.

OBJECTIVES: To test the inverse equity hypothesis, which postulates that new health interventions are initially adopted by the wealthy and thus increase inequalities-as population coverage increases, only the poorest will lag behind all other groups. METHODS: We analyzed the proportion of births occurring in a health facility by wealth quintile in 286 surveys from 89 low- and middle-income countries (1993-2015) and developed an inequality pattern index. Positive values indicate that inequality is driven by early adoption by the wealthy (top inequality), whereas negative values signal bottom inequality. RESULTS: Absolute inequalities were widest when national coverage was around 50%. At low national coverage levels, top inequality was evident with coverage in the wealthiest quintile taking off rapidly; at 60% or higher national coverage, bottom inequality became the predominant pattern, with the poorest quintile lagging behind. CONCLUSIONS: Policies need to be tailored to inequality patterns. When top inequalities are present, barriers that limit uptake by most of the population must be identified and addressed. When bottom inequalities exist, interventions must be targeted at specific subgroups that are left behind

Heritability estimates on Hodgkin’s lymphoma: a genomic- versus population-based approach

Genome-wide association studies (GWASs) have identified several single-nucleotide polymorphisms (SNPs) influencing the risk of Hodgkin's lymphoma (HL) and demonstrated the association of common genetic variation for this type of cancer. Such evidence for inherited genetic risk is also provided by the family history and the very high concordance between monozygotic twins. However, little is known about the genetic and environmental contributions. A common measure for describing the phenotypic variation due to genetics is the heritability. Using GWAS data on 906 HL cases by considering all typed SNPs simultaneously, we have calculated that the common variance explained by SNPs accounts for >35% of the total variation on the liability scale in HL (95% confidence interval 6-62%). These findings are consistent with similar heritability estimates of ∼0.40 (95% confidence interval 0.17-0.58) based on Swedish population data. Our estimates support the underlying polygenic basis for susceptibility to HL, and show that heritability based on the population data is somehow larger than heritability based on the genomic data because of the possibility of some missing heritability in the GWAS data. Besides that there is still major evidence for multiple loci causing HL on chromosomes other than chromosome 6 that need to be detected. Because of limited findings in prior GWASs, it seems worth checking for more loci causing susceptibility to HL.European Journal of Human Genetics advance online publication, 17 September 2014; doi:10.1038/ejhg.2014.184