Mapping the research and development (R&D) landscape using a data series: A 20-year reflection on measuring R&D capacity in South Africa.

Science, technology, and innovation (STI) play a vital role in driving economic growth and social development. STI measurement, including the measurement of Research and Development (R&D) investment, is crucial in providing evidence for policy and decision-making to support STI in a country. In South Africa, the Human Sciences Research Council's Centre for Science, Technology and Innovation Indicators (CeSTII), has, on behalf of the Department of Science and Innovation (DSI), conducted the annual national R&D Survey over the past two decades. As part of this, CeSTII has maintained an extensive database of historic unit-level survey responses. To date, the centre has a rich repository of curated R&D survey data series. These datasets are key tools for enhancing the system of STI indicators for evidence-based policy-making within the National System of Innovation (NSI). In this survey, CeSTII annually collects and reports on the country's R&D expenditure and personnel data across five sectors: business, not-for-profit organisations, government, science councils, and higher education institutions. Recently, these individual datasets have been merged to establish a coherent time series dataset to mitigate the challenge of repeatedly seeking historical data, which may be cumbersome and time-intensive process. The R&D indicators statistics are used by the government to inform STI policy on R&D for national priorities and required R&D funding levels and for monitoring and benchmarking purposes.

Understanding the determinants of hemoglobin and iron status: adolescent-adult women comparisons in SANHANES-1.

The study compared hemoglobin (Hb) and serum ferritin levels between adolescent and adult women with different body mass indices, dietary intake, and sociodemography. A secondary analysis of data for 3177 South African women ⩾15 years of age who participated in the SANHANES-1 study was undertaken. Abnormal Hb (≤12 g/dL) and serum ferritin (<15 µg/mL) were based on the World Health Organization's criteria for nonpregnant women aged ⩾15 years. Data were analyzed using STATA version 11. Overall, anemia was detected in 740 (23.3%) participants. Of the individuals in the subsample (n = 1123, 15-35 years) who had serum ferritin measured, 6.0% presented with iron depletion (ID) and 10.8% presented with iron-deficiency anemia (IDA). The highest prevalences of anemia, ID, and IDA were in 15- to 18-year-olds (11.2%, 8.8%, and 20.2%, respectively). Black young adults (19-24 years) were up to 40 times more likely to present with ID compared with their non-black counterparts. While overweight adolescents were three times more likely to be anemic, overweight and obese young adults, as well as obese older adults (25-35 years), were less likely to be anemic compared with normal-weight women of all age groups. Overconsumption of dietary fat increased ID by up to 54- and 11-fold (adolescents and 25- to 35-year-olds, respectively). In South Africa, anemia is most prevalent in adolescents and black women. Anemia is also an indicator of overconsumption of dietary fat and a marker of socioeconomic disadvantage.

The impact of sociodemography, diet, and body size on serum retinol in women 16-35 years of age: SANHANES-1.

To determine the current vitamin A status of a nationally representative sample of women aged 16-35 years, compare it with previous national data, and determine the impact of sociodemography, diet, and body size on vitamin A status, we performed secondary analysis of data on South African women who participated in the first South African National Health and Nutrition Examination Survey (SANHANES-1). Vitamin A status was assessed by serum retinol, and the findings are reported as means and prevalences with corresponding 95% confidence intervals. Overall, the age-standardized vitamin A deficiency prevalence was 11.7%, a decrease from previous national data, but serum retinol levels remained lower than in other developing countries. Overall, unweighted, multilevel, multivariate logistic regression showed that vitamin A deficiency was influenced by race only (odds ratio (OR) = 1.89, P = 0.031), while weighted multiple logistic regression for 16- to 18-year-olds showed that vitamin A deficiency was influenced by locality (OR = 9.83, P = 0.005) and household income (intermediate (OR = 0.2, P = 0.022) and upper (OR = 0.25, P = 0.049)). Despite the decreased prevalence, vitamin A deficiency remains a moderate public health problem in the country. Opportunities for targeted interventions have been identified.