As with many global health estimates data
As with many global health estimates, data gaps contribute to substantial uncertainty intervals. To calculate their estimates Bourne and colleagues used data from 288 studies and more than 90 countries, but data gaps persist. For example, primary data were not available for approximately half the world\'s countries, less than a quarter of the 61 studies added to this lxr agonist updated analysis were from countries without previous data, only 15% of the surveys used national-level data, and near-visual impairment estimates were derived with data from only 14 countries.
Researchers and funders of primary surveys could reduce data gaps by prioritising future surveys in locations where known gaps exist, reporting results with standard definitions, and making survey results available, including datasets. Data gaps would also be reduced if vision assessment was included in broader population-based surveys that monitor universal health coverage. Fortunately, advances in mobile-based technology make this inclusion feasible. We recognise the benefit of national-level data to calculate global estimates, but in settings where subnational surveys are more feasible or useful for decision makers to plan services, the ensuing larger uncertainty intervals in global estimates from subnational data are arguably a reasonable trade-off.
These new estimates benefit from the increasingly robust synthesis and modelling methods in global health metrics over the past decade. However, tension exists between calculation of global estimates and planning of services within countries, and we agree that ever-more sophisticated global estimate methods should not come at the expense of strengthening local capacity to collect, analyse, and use data. In response to this concern, WHO recently committed to strengthen country health information systems within a broader strategy to improve global estimates, and we welcome the inclusion of household survey implementation and use of findings in the capacity-strengthening plans.
The GATHER statement was developed to improve reporting of global health estimates. Additionally, we believe decision makers would benefit if authors prepared a so-called plain language summary of the main findings (as used by the Cochrane Collaboration). For example, Bourne and colleagues could explain the relative importance of mild visual impairment so that decision makers in countries with high prevalence of blindness can assess the extent to which MtDNA should consider mild impairment when allocating resources. To further assist interpretation of their findings, we encourage Bourne and colleagues to make their data and codes available and, in future estimates, more fully explain how they handled potentially biased studies in synthesis and uncertainty calculations, as well as differences with previously published estimates.
Are we getting closer to universal eye health? Bourne and colleagues\' projected increase in blindness and visual impairment, and persistent inequities between and within countries, suggest not. Better and more timely data will benefit future global estimates. More importantly, if researchers and funders strengthen country-specific capacity to collect, analyse, and use these data to implement effective and equitable eye health services, universal eye health might yet be realised.
In Fernanda Ewing and colleagues offer a new index for monitoring Sustainable Development Goal (SDG) 5 (to achieve gender equality and empower all girls). The survey-based women\'s empowerment index (the SWPER index) was developed from a series of items in the Demographic and Health Survey (DHS) from 34 African countries using principal component analysis and then validated by assessing associations between its components and important maternal and child health interventions (convergent validation) at the individual level, and then analysing its correlations with the Gender Development Index at the country level (external validation). The study presents a valid quantitative measure that can help track gender empowerment over time and across countries at the individual and country level, extending gender indices such as the Gender Development Index, which are limited to the country level. Further, this index can assess potential effects of gender empowerment on health indicators readily available in DHS data. A similar empirical approach was used to create a wealth index with DHS data, and this index is now widely used to document and change social inequities in health.