The current paper presents data on the prevalence and geospatial patterns of Se deficiency in WRA (n = 831) and children aged 6–59 months (n = 741) from a cross-sectional biomarker survey conducted between October 2021 and January 2022. The survey covered three rural districts; Murewa (17.6502°S, 31.7787°E), Shamva (17.04409°S, 31.6739°E), and Mutasa (18.6155°S, 32.6730°E) in Zimbabwe. The districts were chosen based on high stunting rates at 36.2, 37.7, and 30.9%, respectively and low dietary diversity, with 15–29.9% of children 6–59 months getting the minimum number of required food groups (42, 43). The sampling design was nested at the level of the National Demographic Health Survey (DHS) sampling approach (44).

Thirty Enumeration areas (EAs) were selected per district. An EA contains an average of 120 households (44). EAs were selected by proportional probability sampling (PPS) with inclusion probabilities proportional to the most recently recorded population (45). Household listing was undertaken for all eligible households in the selected EAs. Following the listing, 10 households in each EA were selected by random systematic sampling without replacement. In households where more than one set of eligible individuals was identified, one mother–child pair was randomly selected using the Kish Grid (46). The location of each household (sampling point) was determined using a global positioning system receiver (GPS) and verified through matched EA shape files (Figure 1). Recruitment was done at the household level, with participants then directed to the nearest health facility for data collection. Additional information on the sampling design is described in Mutonhodza et al. (70).

The sample size of the three districts (Mutasa/Murewa/Shamva) was proportionate across the two demographic groups. The male/female ratio of the sampled population of children was also proportionate (1,1) across districts (Table 1). The median (Q1, Q3) age for the children was 28.8 months (17.8, 43.5), and that for women was 30 years (24, 37).

Selenium deficiency was highly prevalent in both women and children in all three rural districts. Children were more likely to be deficient than women, with 94.6% (<64.8 μg/L) and 69.8% (<70 μg/L), respectively. The overall median (Q1, Q3) Se concentrations were 61.2 μg/L (48.7, 73.3) and 40.5 μg/L (31.3, 49.5), respectively. Notable evidence of severe Se deficiency risk was observed in the sample population, with children recording plasma Se concentrations as low as 9.41 μg/L and 10.20 μg/L being the minimum in WRA (Table 2). Plasma Se concentrations differed between districts, ranging from a median (Q1, Q3) of 36.5 μg/L (27.8, 44.1) in Murewa district to 71.7 μg/L (62.1, 84.9) in Mutasa district. Variations in plasma Se concentrations were notable between districts. Shamva and Murewa had comparable values. Participants in Murewa district had the lowest median plasma Se concentration and participants in Mutasa had the highest. Remarkably, in Mutasa, there was a substantial difference in plasma Se concentrations between the two demographic groups with median plasma Se concentrations of 71.7 μg/L (62.1, 84.9) in WRA and 47.2 μg/L (37.1, 58.0) in children.

Zimbabwe has a high prevalence of MNDs affecting more than 50% of the population (44). This estimate is from a decade ago and based on anaemia prevalence only. However, anaemia is not synonymous with MNDs (1) since it can be caused by factors unrelated to micronutrient status (61). Direct indicators of MNDs (e.g., biomarkers of Fe, I, Se, and Zn status); are excluded in ZDHS due to cost and gaps in research capacity, such that the last national micronutrient survey was conducted in 2012 (62). Thus, the country does not have current micronutrient data. Additionally, Zimbabwe population studies have been limited to a few micronutrients namely, vitamin A, I, Zn, Fe, and folate (62) as such, data on Se is not nationally available.

The study sought to determine the prevalence, geospatial patterns, and distribution of Se deficiency in WRA and children aged 6–59 months in Mutasa, Shamva, and Murewa. The proportionate representation of participants from the districts allowed fair comparisons. The prevalence of Se deficiency was high and widespread in all three districts. Thus, we contemplate that Se deficiency is potentially a public health issue of national relevance. Selenium deficiency was more prevalent in children compared to women. Variations in Se concentrations were notable across districts, with Murewa having the highest prevalence of Se deficiency. The variations in plasma Se concentration between districts than within districts show that Se status is under strong geospatial control (24). Controls on Se status were driven by short-range spatial variation for WRA and children aged 6–59 months residing in Murewa, Shamva, and Mutasa districts.

The median values of plasma Se concentration in women are similar to those established in other African countries (33), including Malawi and Ethiopia. However, the median plasma Se concentrations in children are low compared to China, a known Se-deficient country reporting levels as low as <40 μg/L (63). Globally, average plasma Se concentrations fall within 80–120 μg/L (23), showing the magnitude of Se deficiency risk among the Zimbabwean population. Different thresholds of adequacy reflect the expression of essential selenoproteins and the hierarchy of biological functions (15), whereby expression of SELENOP, GPX3, and IDI are maximal at plasma Se concentrations of >100, >84.9, and >64.8 μg/L (10), respectively. Recent evidence from laboratory and epidemiologic studies has shed a different light on Se’s health effects and its recommended range of environmental exposure compared with earlier research. Adverse effects (type 2 diabetes) have been reported in Western populations at low Se exposure levels, sometimes below or slightly above Se intakes needed to maximize selenoprotein expression and activity (17). The new evidence indicates the need to reassess Se dietary reference values and upper intake level (17).

Based on earlier research Se adequacy cutoff points, our findings suggest that Se deficiency may lead to an increased risk of oxidative stress among most women and children in our study area, and an increased risk of thyroid dysfunction among most children and approximately half of the women. Widespread Se deficiencies, particularly in rural areas, have been reported in Malawi (24) and Ethiopia (23, 38).

The findings of high Se deficiency prevalence are not surprising considering similarities in geography, diet, and socioeconomic conditions between Zimbabwe and Malawi. In both countries, rural populations rely on highly localised agriculture and food systems, where dietary intakes are supplied through subsistence production and locally based food purchases (64–66). When these localised food systems occur in low Se environments, the entry of Se into diets is limited. To compound matters, Zimbabwe has limited access to freshwater fish, which are an essential source of Se (and many other micronutrients) as observed in Malawi (24). Our current findings indicate Se deficiency is likely widespread in Zimbabwe, with a high risk of severe Se deficiency. Therefore, there is a pressing need to conduct surveillance work in other regions and demographic groups. A nationally representative biomarker survey is recommended to establish the magnitude of the problem based on revised cutoff points as suggested by the new evidence (17).

The minimum number of sampling points used for modelling in the current study was sufficient to avoid bias. Effective variogram estimations require a minimum of 100–150 points (54). In the current study, most of the experimental variograms show variation over short distances up to only 12 km, so the maps appear very “patchy” with similar values in the clusters of observations. This suggests that, in these locations and demographic groups, controls on Se status are driven by short-range variation and are therefore not showing marked spatial trends within districts (54, 59). Selenium status was reasonably homogenous within each district. However, there was substantial inter-district variation, suggesting that there are marked spatial patterns when the sampling area is scaled up; as reflected in other African countries; Côte d’Ivoire (67, 68), Ethiopia (23) and Malawi (24). In Ethiopia spatial factors influencing Se status operated at distances up to 200 km (23) whilst in Malawi spatial dependence was observed at up to 120 km (24). Variations might be explained by the scale of the studies, being a pilot, the current study was just a snapshot limited to district level. Thus, it had a smaller data frame compared to the Ethiopian and Malawian studies that were conducted at a national scale, with sampling points dotted around a larger area which improves the accuracy of the empirical variograms (54). The variation in plasma Se concentration between the districts could also suggest the influence of other spatial parameters, such as soil properties, climate, and landscape (29, 36). Therefore, resource endowment for further investigations may be important to continue to build an evidence base, through complementary surveillance of soils, crops, and biomarkers. Predictions have an attached uncertainty (60) and hence, no map is perfect (69). Nevertheless, the results of the current study predicted a high risk of Se deficiency in both children and WRA residing in the three districts. The maps and the underlying statistical model generated in the current study could be useful to plan further investigations that identify other spatial parameters contributing to the marked between-district variation in the Se status of women and children.

The current study is limited in geographic scope and we are not able to infer Se status or risk of deficiency across Zimbabwe, particularly since Se status is likely to be under strong geographic control, as observed in other contexts. There is no consensus on the most appropriate threshold to indicate Se deficiency risk. The current study only measured plasma Se concentration which was used as a proxy indicator for the status of the secondary biomarkers (SELENOP, GPX3, and IDI), and thus may not be truly reflective of the selenoprotein status. Additional direct measurements of selenoproteins would complement the findings of the current study. Nevertheless, the present study contributes to the body of knowledge on the application of geostatistical modeling for the interpolation and mapping of nutrient deficiencies.