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Women now account for roughly half of all participants in National Institutes of Health (NIH)-supported clinical research, which is subject to NIH's Policy on the Inclusion of Women in Clinical Research. However, more often than not, basic and preclinical biomedical research has focused on male animals and cells. An over-reliance on male animals and cells may obscure understanding of key sex influences on health processes and outcomes. 

Accounting for sex as a biological variable begins with the development of research questions and study design. It also includes data collection and analysis of results, as well as reporting of findings. Consideration of sex may be critical to the interpretation, validation, and generalizability of research findings.  Adequate consideration of both sexes in experiments and disaggregation of data by sex allows for sex-based comparisons and may inform clinical interventions. Appropriate analysis and transparent reporting of data by sex may therefore enhance the rigor and applicability of preclinical biomedical research.

Worldwide, the prevalence of moderate to severe visual impairment and blindness is 285 millions, with 65% of visually impaired and 82% of all blind people being 50 years and older. Meta-analyses have shown that two out of three blind people are women, a gender discrepancy that holds true for both developed and developing countries. Cataract accounts for more than half of all blindness globally and gender inequity in access to cataract surgery is the major cause of the higher prevalence of blindness in women. In addition to gender differences in cataract surgical coverage, population-based studies on the prevalence of lens opacities indicate that women have a higher risk of developing cataract. Laboratory as well as epidemiologic studies suggest that estrogen may confer antioxidative protection against cataractogenesis, but the withdrawal effect of estrogen in menopause leads to increased risk of cataract in women. For the other major age-related eye diseases; glaucoma, age-related macular degeneration (AMD) and diabetic retinopathy, data are inconclusive. Due to anatomic factors, angle closure glaucoma is more common in women, whereas the dominating glaucoma type; primary open-angle glaucoma (POAG), is more prevalent in men. Diabetic retinopathy also has a male predominance and vascular/circulatory factors have been implied both in diabetic retinopathy and in POAG. For AMD, data on gender differences are conflicting although some studies indicate increased prevalence of drusen and neovascular AMD in women. To conclude, both biologic and socioeconomic factors must be considered when investigating causes of gender differences in the prevalence of age-related eye disease.

Gender relations and gendered power relations are major defining features of science and technology. This article addresses the question of how to understand gender, and considers their various implications for science and technology. Gender and gender relations can be understood as operating and as relevant to science and technology at several levels: who does science and technology; how science and technology are organized; and the con- struction of knowledge in science and technology. We review five underlying formulations that inform both policy interventions and theorizing around gender and science — gender based on sex; masculinity/femininity and sex roles; categoricalism, structure and plural structures; poststructuralist, discursive and deconstructive approaches; the material-discursive.

Data2X, named for the power women have to multiply progress in their societies, aims to advance gender equality and women’s empowerment through improved data collection and analysis that can provide a solid evidence-base to guide development policy. To provide basic information for a Data2X roadmap, this report maps gender data gaps in developing countries across five domains of women’s empowerment: (1) health, (2) education, (3) economic opportunities, (4) political participation, and (5) human security. Need, population coverage and policy relevance were the three criteria used to select which data gaps to map. The report suggests ‘ways forward’ to close these gaps using existing and new data sources, including censuses and micro-level surveys, service and administrative records, and the potential use of ‘big data’ as a new source of gender data. These ways forward build on recent and ongoing data initiatives and are intended to inform the Data Revolution (High Level Panel Report, 2013) and the stand-alone gender equality goal (UN Women, 2013) called for in the post-2015 period. Existing international databases often have data that could be disaggregated by sex and analyzed to address gender data gaps. These data sources should be mined before initiating new data collection efforts. Going forward, data mining and collection should be undertaken efficiently and in response to meaningful demand for and capability to use the data for policy purposes, and as a tool to drive social change. Globally, close to 80 percent of countries regularly produce sex-disaggregated statistics on mortality, labor force participation, and education and training. Less than a third of countries disaggregate statistics by gender on informal employment, entrepreneurship (ownership and management of a firm or business), violence against women, and unpaid work. Reflecting these gaps, the UN Inter-Agency and Expert Group on Gender Statistics (IAEG-GS) has compiled a minimum set of 52 gender indicators and divided them into three tiers according to their conceptual clarity, international standards and regular production (UNSD, 2012). Educational indicators, followed by health, lead the way in terms of clarity, comparability and country coverage. Availability and coverage in the other domains highlighted in this report are poor, and this is especially the case for economic indicators. Throughout, this report makes reference to this minimum set of gender indicators as well as a proposed set to track a stand-alone gender equality goal in the post-2015 period (UN Women, 2013). Laws and policies, particularly those related to marriage, property, and labor rights, influence health, education, and economic outcomes for women. However, comprehensive information on policies related to women is difficult to obtain. Databases that help document laws and policies affecting women’s outcomes are reviewed in this report. Additional efforts to expand coverage and improve the robustness of these databases are warranted to round out the availability of policy relevant data on women.