Association between substance use and psychosocial characteristics among adolescents of the Seychelles

BACKGROUND: We examined the associations between substance use (cigarette smoking, alcohol drinking, and cannabis use) and psychosocial characteristics at the individual and family levels among adolescents of the Seychelles, a rapidly developing small island state in the African region. METHODS: A school survey was conducted in a representative sample of 1432 students aged 11-17 years from all secondary schools. Data came from a self-administered anonymous questionnaire conducted along a standard methodology (Global School-based Health Survey, GSHS). Risk behaviors and psychosocial characteristics were dichotomized. Association analyses were adjusted for a possible classroom effect. RESULTS: The prevalence of cigarette smoking, alcohol drinking and cannabis use was higher in boys than in girls and increased with age. Age-adjusted and multivariate analyses showed that several individual level characteristics (e.g. suicidal ideation and truancy) and family level characteristics (e.g. poor parental monitoring) were associated with substance use among students. CONCLUSIONS: Our results suggest that health promotion programs should simultaneously address multiple risk behaviors and take into account a wide range of psychosocial characteristics of the students at the individual and family levels

Five insights from the Global Burden of Disease Study 2019

The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a rules-based synthesis of the available evidence on levels and trends in health outcomes, a diverse set of risk factors, and health system responses. GBD 2019 covered 204 countries and territories, as well as first administrative level disaggregations for 22 countries, from 1990 to 2019. Because GBD is highly standardised and comprehensive, spanning both fatal and non-fatal outcomes, and uses a mutually exclusive and collectively exhaustive list of hierarchical disease and injury causes, the study provides a powerful basis for detailed and broad insights on global health trends and emerging challenges. GBD 2019 incorporates data from 281 586 sources and provides more than 3.5 billion estimates of health outcome and health system measures of interest for global, national, and subnational policy dialogue. All GBD estimates are publicly available and adhere to the Guidelines on Accurate and Transparent Health Estimate Reporting. From this vast amount of information, five key insights that are important for health, social, and economic development strategies have been distilled. These insights are subject to the many limitations outlined in each of the component GBD capstone papers.Peer reviewe

Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010–2019 relative to 1990–2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach $1398 pooled health spending per capita (US$ adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6–421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0–3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5–1040·3]) residing in south Asia. Interpretation The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people—the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close—or how far—all populations are in benefiting from UHC. Funding Bill & Melinda Gates Foundation

Influence of upper ocean on Indian summer monsoon rainfall: studies by observation and NCEP climate forecast system(CFSv2)

This study explores the role played by ocean processes in influencing Indian summer monsoon rainfall (ISMR) and compares the observed findings with National Centers for Environmental Prediction (NCEP)-coupled model Climate Forecast System, version 2 (CFSv2). The excess and deficit ISMR clearly brings out the distinct signatures in sea surface height (SSH) anomaly, thermocline and mixed layer depth over north Indian Ocean. CFSv2 is successful in simulating SSH anomalies, especially over Arabian Sea and Bay of Bengal region. CFSv2 captures observed findings of SSH anomalies during flood and drought (e.g., Rossby wave propagation which reaches western Bay of Bengal (BoB) during flood years, Rossby wave propagation which did not reach western BoB during drought). It highlights the ability of CFSv2 to simulate the basic ocean processes which governs the SSH variability. These differences are basically generated by upwelling and downwelling caused by the equatorial and coastal Kelvin and Rossby waves, thereby causing difference in SSH anomaly and thermocline, and subsequently modifying the convection centers, which dictates precipitation over the Indian subcontinent region. Since the observed SSH anomaly and thermal structure show distinct characteristic features with respect to strong and weak ISMR variability, the assimilation of real ocean data in terms of satellite products (like SSHA from AVISO/SARAL) bestow great promise for the future improvement

Evaporation-precipitation variability over Indian Ocean and its assessment in NCEP Climate Forecast System (CFSv2)

An attempt has been made to explore all the facets of Evaporation-Precipitation (E-P) distribution and variability over the Indian Ocean (IO) basin using Objectively Analyzed air-sea Fluxes (OAFlux) data and subsequently a thorough assessment of the latest version of National Centers for Environment Prediction (NCEP) Climate Forecast System (CFS) version-2 is done. This study primarily focuses on two fundamental issues, first, the core issue of pervasive cold SST bias in the CFS simulation in the context of moisture flux exchange between the atmosphere and the ocean and second, the fidelity of the model in simulating mean and variability of E-P and its elemental components associated with the climatic anomalies occurring over the Indian and the Pacific ocean basin. Valuation of evaporation and precipitation, the two integral component of E-P, along with the similar details of wind speed, air-sea humidity difference ( ΔQ ) and Sea Surface Temperature (SST) are performed. CFS simulation is vitiated by the presence of basin wide systematic positive bias in evaporation, ΔQ and similar negative bias in wind speed and SST. Bifurcation of the evaporation bias into its components reveals that bias in air humidity ( Qa ) is basically responsible for the presence of pervasive positive evaporation bias. The regions where CFS does not adhere to the observed wind-evaporation and Qa -evaporation relation was found to lie over the northern Arabian Sea (AS), the western Bay of Bengal (BoB) and the western Equatorial IO. Evaporation bias is found to control a significant quantum of cold SST bias over most of the basin owing to its intimate association with SST in a coupled feedback system. This area is stretched over the almost entire north IO, north of 15∘S excluding a small equatorial strip, where the evaporation bias may essentially explain 20–100 % of cold SST bias. This percentage is maximum over the western IO, central AS and BoB. The CFS simulation comply the distinct feature of the observed mean annual cycle of evaporation and precipitation, but with the additive systematic bias over most of the region. El Niño and negative Indian Ocean Dipole (NIOD) seems to have much better control over the interannual variability of evaporation in the CFS simulation, contrary to the observation where El Niño and positive Indian Ocean Dipole (PIOD) has the larger say. Both El Niño and PIOD (La Niña and NIOD) have the negative (positive) influence on the basin wide evaporation with the exception over a limited region and this relation holds for the twain. The seasonal (JJA and SON) locking of El Niño and PIOD to evaporation and precipitation is displayed by the north-south and east-west asymmetric correlation pattern respectively and this is much perspicuous in the observation as compared to the CFS. The conjoined influence of El Niño and PIOD on evaporation (precipitation) reveals the dominance of PIOD (PIOD + El Niño) response in case of both the observation as well as the CFS. This study will lead a way forward to rectify the ubiquitous cold SST bias in the CFS simulation and help in establishing the credibility of the CFS in terms of seasonal predictabilit