Assessment of stature in Iron Age populations of South Africa

Assessment of stature in Iron Age populations of South Africa | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Assessment of stature in Iron Age populations of South Africa Maryna Steyn This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3282701/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 22 Nov, 2023 Read the published version in Archaeological and Anthropological Sciences → Version 1 posted 7 You are reading this latest preprint version Abstract Worldwide and in South African Stone Age contexts, much research has been done on the relationship between stature of past populations and general well-being, as well as trends and patterns in stature through time. This research aimed at collating and assessing all available stature and long bone data for Bantu-speaker individuals living in the South African Iron Age. Data for only 25 female and 32 male individuals, dating from circa AD 550 to AD 1823, could be found. In general, methods used to reconstruct stature were inconsistent and data were poorly reported. From the available data, no clear trends or patterns in stature through time could be observed and stature seems to be on a par relative to those of early 20th century individuals. Recommendations are made as to which methods to use in stature estimations in this context. The data provided in this research can serve as reference material for future similar studies and can assist in interpreting individual stature estimations from bioarchaeological research in the region. long bones regression equations femur:stature ratio stature reconstruction Figures Figure 1 Introduction Stature, and changes in stature, are often used to gain information on health and well-being of past and present populations (e.g., Komlos 1994 ; Tanner 1994 ; Steckel 1995 ; Vercelotti et al. 2014; Mays 2016 ). It should, however, be kept in mind that final adult stature is the result of many factors, the most important of which is genetics (e.g, Tanner 1994 ; Bogin et al. 2001 ). Tobias ( 1972 ) was one of the first researchers to provide general information on stature of historic South Africans. Much more research has since been added on stature in past populations, with studies by Sealy and Pfeiffer ( 2000 ) and others (e.g., Kurki et al. 2010 ; Pfeiffer and Harrington 2011 ; Kinahan 2013 ), particularly in Stone Age groups in southern Africa, providing examples of how growth and stature in autochtonous groups can help us to understand the influence of environmental and other factors on body size. In their paper, Sealy and Pfeiffer ( 2000 ) provide maximum femur lengths and femoral head diameters, with dates, for a large number of Stone Age Holocene individuals from the Southern Cape, South Africa. Amongst other things, they found a pattern of stability among already-small San people, with a noteworthy increase in diversity and decline in mean body size from ca. 3 300 to 2 000 BP. Before 2 000 BP, the people of smallest stature were often also those who ate mostly terrestrial foods. After this date, this pattern no longer holds true. Very small people, all apparently women, occurred from 4 000 to 2 000 BP. This was followed by several other studies with similar themes (e.g., Sealy 2006 ; Pfeiffer and Sealy 2006 ; Pfeiffer 2012 ) which reflected on the relationship between small body size and population density, food availability and types (through isotopic analysis), trauma, possible sexual selection etc. Other themes explored aspects of body size (Kurki et al. 2010 ; Kurki et al. 2012 ), child growth (Pfeiffer and Harrington 2011 ) and activity patters (Stock and Pfeiffer 2004 ). These papers, mainly focusing on Stone Age hunter- and gatherer populations, show the value of looking at body size and stature, as well as trends in stature across time, as it reflects the general adaptation and well-being of populations as well as possible environmental changes. Stature is of course dependent on both environmental and genetic factors. In the changing landscape of southern Africa, with its continuous migrations and diffusion of populations, it is hard to separate genetic influences (e.g., the short stature of the Khoe-San) with changes that may have been brought on by environmental stressors or the absence thereof. Unfortunately, much less research of this nature has been done on Iron Age Bantu-speaker populations of South Africa, with stature reconstructions usually mentioned in passing as part of individual skeletal reports. In most older publications of the early 20th century dealing with human skeletal remains, unfortunately, the focus was on the identification of racial characteristics of skulls (see Morris 2022 ) with hardly any emphasis on anything related to the postcranial skeleton. Most of these early papers do not report on the long bones at all and do not make any attempt to reconstruct stature. These practices changed somewhat by the 1970’s, with physical anthropologists such as De Villiers ( 1972 ; 1973 ) including stature reconstructions in her reports, sometimes (but rarely) with attempts to bring it into a greater context. Unfortunately, De Villiers and others (e.g., Wells 1935 ) mostly do not report raw measurements, but rather provided reconstructed statures. At the time, population-specific stature reconstruction formulae were not available, and formulae developed by Trotter and Gleser ( 1952 ) developed for North American populations were often employed in earlier publications. More recently other methods (e.g., Lundy and Feldesman 1987 ; Feldesman and Fountain 1996 ) became available and were used in skeletal reports. It is not clear from the literature exactly which methods are the most appropriate for the reconstruction of stature in South Africans, and particularly in Iron Age Bantu-speaker individuals. The aim of this paper is to assess the availability of long bone and stature data relating to Iron Age Bantu-speaker remains in South Africa, and to investigate which methods were used to reconstruct stature. An overview of available methods will be provided for practitioners not so familiar with the topic, as a guideline to use in such estimations – this will include recommendations of what to use for South Africans and in this case particularly for the skeletal remains of Iron Age Bantu-speakers. All long bone and stature data from the literature, as well as unpublished reports, will be collated in order to assess for trends in stature in the past 2000 years, in an attempt to add information on the health and well-being (and perhaps possible genetic influences) of these individuals. Stature reconstruction in archaeological populations It is widely accepted in the forensic anthropological context that population-specific formulae should be used to reconstruct stature (e.g., Ross and Konigsberg 2002 ; İşcan and Steyn 2013 ). This, of course, is problematic when it comes to past populations and if ancestry / population is not known. It has conclusively been demonstrated that long bone lengths versus overall stature varies in different populations, and this is most probably related to the well-known associations between climate and body proportion (Allen 1877 ; Ruff 1993 ; Feldesman and Fountain 1996 ). Generally speaking, individuals in warmer climates have longer limbs relative to their overall heights, as a heat adaptation. The opposite is true for people living in colder climates. Of course, this picture becomes confounded in modern populations where people no longer live in their ancestral lands. One of the oldest methods of stature estimation is the use of a femur:stature ratio, as it was found that there is a relatively constant relationship between femur and overall stature in various populations across the world (Dupertius and Hadden 1951; Sjovold 2000 ). The femur:stature ratio of various groups worldwide was assessed in detail by Feldesman and Fountain ( 1996 ) using a large and diverse sample of individuals from various regions of the world – from Eskimos to pygmee populations. The femur:stature ratio of Black African population groups was shown to be different from the generally observed value of 3.74 – i.e., where maximum femur length multiplied by 3.74 provides a stature estimate (Feldesman & Fountain 1996 ; Sjovold 2000 ). According to Feldesman and Fountain ( 1996 ), the femur length constitutes approximately 26.75% of the stature across all ancestry groups (translating to the ratio of 3.74) but 27.13% in individuals of African descent and 26.48% in individuals of European decent – demonstrating the somewhat longer limbs in Africans. While there are slight differences between males and females, they advise one generic formula – in the case of individuals of African descent, the formula: Stature = 30.285687 + (2.986895 x femur) should be used, as this regression formula gives a slightly better result than using the ratio itself. It should be noted that the femur length to be used in this formula is the maximum femur length, recorded in cm (in standard reports, both maximum and physiological length are usually recorded, with the physiological length being shorter than the maximum length). An advantage of this method is that it provides an estimate of the living stature, and it is not necessary to add a soft tissue correction factor (as is necessary for method based on Total Skeletal Height, TSH, introduced by Fully 1956 ). A disadvantage is that the ratio does not provide an estimate of the uncertainty around this point estimate – other traditional formulae usually provide an SEE (Standard Error of Estimate) that allows one to provide a stature estimate with a 95% confidence interval. The largest disadvantage of using femur:stature ratios in archaeological populations, as opposed to other methods to assess stature, however, is the fact that the femora may not be complete or not preserved at all and that maximum femur length is therefore not avialable. Other long bones and measurements are therefore often used to estimate the stature. In South Africa, the formulae of Lundy and Feldesman ( 1987 ) are widely used in modern and archaeological cases concerning black Africans. However, it should be taken into account that these formulae provide an estimate of the Total skeletal Height (TSH) – i.e., it reconstructs the proportion of the stature that is made up by the skeletal elements. From here, this value should be adjusted to account for soft tissues – for a TSH of less than 153.5 cm, 10 cm is added; for a TSH 153.5 to 163.5 cm, 10.5 cm must be added for a THS of more than 163.5 cm, 11.5 cm is added (Fully 1956 ). More recently, Raxter et al. ( 2006 ) provided new, generic (world-wide) soft tissue correction factors which are commonly in use to convert TSH into living stature. If no correction for the age of an individual is made, living stature = 0,996 x Skeletal height (TSH) + 11.7 (SEE 2:31). Unfortunately, in South Africa, it has been shown that these soft tissue correction factors, and especially that of Lundy & Feldesman ( 1987 ) consistently underestimate stature (e.g., Bidmos and Manger 2012 , Brits et al., 2017 ). The new Bidmos and Manger ( 2012 ) corrections for South African black males have been criticized due to some technical issues (Ruff et al. 2012 ), while that of Brits et al. ( 2017 ) are commonly in use for black females. This does leave a conundrum, because it means that in the South African context, there is no reciprocity between males and females when living stature is reconstructed from TSH using the most recent soft tissue corrections. Until firmly established soft tissue correction factors are established for African males, it is therefore advised that the Raxter et al. ( 2006 ) soft tissue corrections are used in archaeological settings. These are in use world-wide, but are not population-specific and may under-estimate stature in South Africans. A word of caution – for the Trotter and Gleser ( 1952 ) formulae specifically, there is some confusion as to exactly how the tibiae were measured (Jantz et al. 1994 ; Mays 2016 ) – the tibiae can be measured as maximum lengths (with medial malleolus), or physiological length (without the malleolus). The physiological lengths are also reportedly sometimes recorded with callipers rather than an osteometric board. This confusion makes the use of the tibia unpopular, and should tibial formulae be used the exact manner of recording, as used in the publication providing the formulae, should be established. Similarly, some formulae require the use of maximum femur length, whereas others use the physiological / bicondylar femur length. De Villiers, in her 1981 unpublished report on the Broederstroom, Munro and Olifantspoort remains, for example, provides the maximum femur lengths (FeL1), but then goes on to say that the Lundy formulae were used to reconstruct stature – these, however, use physiological / bicondylar length. Reported statures, without providing raw data, are therefore problematical. In general, when several long bones are available, the bone (formulae) with the highest correlation to stature should be used. In most sets of formulae, the femur usually has the highest correlation to actual stature, followed by the tibia. In the upper limb, the radius is usually the best correlated to stature (but less so than the lower limb bones). Pfeiffer and Sealy ( 2006 ) in a paper on body size of Holocene foragers from the Cape ecozone, clearly encountered the same difficulties when having to deal with different methods to reconstruct stature. They used the regression equations proposed by Feldesman and Fountain ( 1996 ), the generic femur:stature ratio of 26.74 proposed by Feldesman et al. ( 1990 ), and the sex-specific equations for black and white individuals developed by Trotter ( 1970 ). These problems with stature estimation are not unique to South Africa and have been debated in several other regions of the world (e.g., Ruff et al. 2012 ; Kinahan 2013 ; Mays 2016 ). This demonstrates the difficulty with obtaining comparable stature data from long bone lengths across populations, especially with varying degrees of preservation of remains. Materials and methods For this study, reported long bone and stature data of southern African Iron Age Bantu-speaker individuals, focusing on individuals from the pre-colonial era, were collected. Only individuals with firm dates were included, or individuals that came from archaeological sites that were firmly dated. Only adult individuals, or late adolescent individuals with complete epiphyseal closure, were included. Individuals were divided by sex. For each individual, depending on the data available, the following were calculated/recorded: Stature based on the Trotter and Gleser ( 1952 ) formulae for black Americans (Terry Collection), as these were sometimes used by De Villiers, also in reports where raw long bone lengths were not provided. Stature based on the Lundy and Feldesman ( 1987 ) formulae for modern black South Africans, using the original (Fully 1956 ) soft tissue correction factors. Stature based on the Lundy and Feldesman ( 1987 ) formulae for modern black South Africans, using the Raxter et al. ( 2006 ) soft tissue correction factors. The general formula, not corrected for age, was used as age estimates were often not available. Stature based on the femur:stature ratio for Africans, using the regression equation of Feldesman and Fountain ( 1996 ) where living stature = 30.285687 + (2.986895 x femur maximum length) Where no long bone data were recorded, but a stature was published, this was included as a “reported stature”. For all cases, only the point estimate (without SEE) was used for purposes of comparison. The statures of individuals, using the various methods, were compared in order to assess for, for example, consistent over- and underestimation. Unfortunately, the actual, living stature is of course not available and therefore these can never be assessed for real accuracy. In order to assess if changes in stature occurred, individuals were divided into Huffman’s ( 2009 ) descriptions of Early, Middle and Late Iron age. While not all archaeologists would agree with this division, it provides a convenient way to compare statures across time periods. Following this, Early Iron Age (EIA) individuals were dated to AD 100–900, Middle Iron Age (MIA) to AD 900–1300 and Late Iron Age (LIA) to AD 1300–1840. Within each of these time periods, the mean statures were calculated – e,g., mean stature of EIA females, mean stature of MIA females, etc. Mean statures across the three time periods, for females and males respectively, were assessed using ANOVA to establish if stature changed significantly. For this purpose, SPSS (Statistical Package for Social Sciences) was used. As these individuals were all dated, or came from dated sites, stature versus date were plotted on a graph to visually assess trends and scatter. For this purpose, the midpoint of the reported AD dates was used for each individual as the raw (before present) dates were often not available. This is of course only a wide approximation of the date of each skeleton, but it assists to graphically assess the available data. Results The raw data, with reported long bone lengths per individual, are shown in the Supplementary material (S1) for future use in similar studies. It also shows the full detail of each skeleton, as well as the reference for each entry (full reference list in S2). The availability of long bone or stature data from the South African Iron Age is disappointing. For the Early Iron Age (as per the definition above), information for only two males and two females could be obtained. For the MIA, data were available for 6 females and 13 males, while the corresponding numbers for the LIA were 17 (female) and 16 (male). This brings the total sample to n = 56 individuals (Table 1 ). Table 1 reflects the reconstructed statures for each individual, using various different methods. Only the point estimates, without SEE’s are included here, for easy comparison. Overall, the formulae of Trotter and Gleser ( 1952 ) provided relatively tall estimates, clearly out of line with other formulae. The Lundy and Feldesman ( 1987 ) formulae with the soft tissue corrections of Raxter et al. ( 2006 ) provided slightly taller estimates than the original soft tissue corrections, as expected. The femur:stature ratio (as per the regression) of Feldesman and Fountain ( 1996 ), in general provided estimates that were slightly taller than the Lundy and Feldesman (with Raxter et al. corrections) formulae (1.4 cm on average; two were taller and the remainder shorter). These ratios still provided statures that were shorter than those using the Trotter and Gleser ( 1952 ) formulae. In each individual case, and for further comparison, a judgement call was made as to which stature estimate was most probably the most accurate for each individual. As the Lundy and Feldesman ( 1987 ) formulae with Raxter et al. ( 2006 ) soft tissue corrections are often criticized because they tend to underestimate (Bidmos and Manger 2012 , Brits et al., 2017 ), the Feldesman and Fountain ( 1996 ) femur:stature ratio was deemed the most accurate (where maximum femur lengths were available), followed by the Lundy and Feldesman ( 1987 ) formulae with the Raxter et al. ( 2006 ) soft tissue corrections (also used for cases where only physiological length of the femur was reported). Estimates using the femur was preferred over that using the tibia, with the radius usually deemed the next best choice. However, in some individuals, only a single long bone such as a fibula or humerus length was available and had to be used. In 14 cases, no raw data (long bone lengths) were recorded and only a reported stature was available – in some cases, e.g., Glennel, the author stated which method was used (Trotter and Gleser in this case), whereas in others (e.g., Eersteling) no information was given as to how the estimate was derived. For the Broederstroom female, in an unpublished report, De Villiers quoted a stature estimate of 150 cm although it was not clear on what it was based – a maximum tibia length was recorded but did not correlate with a 150 cm reconstruction, creating some confusion and the reconstructed stature was retained. Average statures of females were 152.0 cm in the EIA (n = 2), 159.3 in the MIA (n = 6) and 1588 cm (n = 17) in the LIA, with no clear trend visible (p = 0.500). A similarly non-directional, not significantly different (p = 0.645) pattern was seen in males, where average stature was 171.6 cm (n = 2) in the EIA, 166.4 cm (n = 13) in the MIA and 167.1 cm (n = 17) in the LIA. Overall, female stature ranged from 143.2 cm (Newcastle 2007/006) to 179.9 cm (Thulamela, UP 43) with an overall mean of 158.4 cm (n = 23; SD 7.906). For males, the shortest stature was 156.4 cm (from the little-known MIA site of Munro) and the tallest 185.8 cm (from Clarens, an MIA site). The overall mean for males is 167.1 cm (SD 7.101). The data are graphically represented in Fig. 1 , where a wide scatter can be observed. What is once again obvious from Fig. 1 , is that the data from the EIA is very limited, with peaks around the LIA and the K2/Mapungubwe (MIA) period (circa AD 1000 to 1300). As expected, males are generally taller than females, although some overlap is evident. Table 1 Stature reconstruction using various formulae. Stature estimates are shown in cm. Individual Period Sex Reported stature T&G L&F L&F Raxter Fem ratio Final Broederstroom A4143 EIA Female 150.0 163.8 150.0 Mhlopeni PMB 80/2.1b EIA Female 161.4 161.6 162.7 153.9 153.9 Mean 152.0 Happyrest UP1 EIA Male 175.1 170.8 171.4 173.7 173.7 KwaGandaganda PMB001 EIA Male 172.2 167.2 167.8 169.5 169.5 Mean 171.6 K2 A1722 MIA Female 154.8 148.5 149.6 151.6 151.6 K2 A1730 MIA Female 158.9 152.9 154.0 156.9 156.9 Mapungubwe A624 MIA Female 170.6 170.1 170.7 172.2 172.2 Pilanesberg UP51 MIA Female 150.1 151.2 151.2 Glennel 1/1 D35.1.1 MIA Female 160.0 160.0 160.0 Glennel 2/1 MIA Female 164.0 164.0 164.0 Mean 159.3 Clarens A4237/4231 MIA Male 183.7 181.5 181.0 185.8 185.8 K2 A1714 MIA Male 162.0 163.1 163.1 K2 A1732 MIA Male 168.2 161.6 162.7 163.8 163.8 K2 A1734 MIA Male 184.0 173.2 173.8 173.8 K2 A1758 MIA Male 163.7 155.7 156.8 157.5 157.5 K2; KS58 MIA Male 167.0 162.2 162.2 Mapungubwe A619 MIA Male 175.8 173.1 173.6 174.6 174.6 Kon-Stayt UP77 MIA Male 167.7 168.3 168.3 Schroda NAS2AA.3(i).1 MIA Male 169.7 169.7 169.7 Glennel 1/1 A25.1.1 MIA Male 169.5 169.5 169.5 Glennel 1/1 B26.1.1 MIA Male 161.0 161.0 161.0 Mapungubwe UP145 MIA Male 160.6 156.6 157.7 157.7 Munro burial 2 MIA Male 156.4 156.4 Mean 166.4 Askoppies NASB1 LIA Female 155.5 149.8 151.0 152.2 152.4 Champagne C PMB2009/023 LIA Female 157.6 150.7 151.8 155.1 155.1 Cyferkuil UP94 LIA Female 171.9 161.9 163.0 163.0 Eersteling A410c LIA Female 157.8 157.8 Ellerton Mine A414 LIA Female 156.2 156.2 Lindley UCT326 LIA Female 156.0 156.0 156.0 Newcastle 2007/006 LIA Female 149.6 142.1 143.2 143.2 Pilanesberg UP95 LIA Female 161.4 161.4 161.4 Thabazimbi UP132 LIA Female 154.8 144.7 145.9 145.9 Thulamela UP43 LIA Female 176.5 176.3 175.8 179.9 179.9 Wellington Estate A1103 LIA Female 164.2 159.6 160.7 160.7 Wellington Estate A1836 LIA Female 160.3 168.1 168.6 168.6 Wellington Estate A2235 LIA Female 160.7 160.7 Willow Glen UP 72 LIA Female 162.0 157.3 158.4 158.4 Klip River Valley UCT UCT329 LIA Female 160.0 160.0 160.0 Olifantspoort A4221 LIA Female 164.2 159.9 161.0 163.8 163.8 Olifantspoort A2853&2854 LIA Female 162.5 156.2 157.3 157.3 Mean 158.8 Kaybar's Cave A294 LIA Male 172.0 167.0 167.7 169.2 169.2 Kaybar's Cave A295 LIA Male 165.0 159.3 160.4 159.3 159.3 Makapanstad UP LIA Male 160.5 161.6 161.6 Makgope UP48 LIA Male 172.0 167.5 168.1 169.2 169.2 Makgope UP49 LIA Male 168.2 162.7 163.7 163.8 163.8 Modimolle UP92 LIA Male 168.8 163.1 164.2 164.7 164.7 Nwanetsi UP130 LIA Male 168.5 161.7 162.8 - 162.8 Pilanesberg UP139 LIA Male 181.2 178.8 178.3 182.3 182.3 Pilanesberg UP143 LIA Male 166.5 166.5 166.5 Robinson's Shelter A302 LIA Male 174.7 169.9 170.4 173.1 173.1 Skukuza Rock Shelter UP29 LIA Male 172.3 165.4 166.0 166.0 Thulamela UP44 LIA Male 172.3 165.4 166.0 166.0 Welgegund UP12 LIA Male 166.1 166.1 Wellington Estate A1838 LIA Male 162.1 157.8 159.0 159.0 Yellowtree Shelter A299 LIA Male 169.4 164.4 164.9 165.6 165.6 Olifantspoort burial 5 LIA Male 187.8 179.5 179.0 179.0 Mean 167.1 Discussion The availability of long bone data lengths and stature for individuals from the South African Iron Age is disappointing, and the reasons for this – relative to the much more numerous Stone Age data from the southern provinces – can be debated. It possibly reflects the preoccupation of early physical anthropologists with “race” and the San/KhoeSan populations of southern Africa, where excavations focused on cave sites along the coast that yielded large numbers of skeletons. Perhaps it is also related to a general perception that we know much about the relatively recent incoming Iron Age agriculturalists, and that their histories are somehow less interesting. This is most certainly not true as, for example, the recently reported MIA dating of surprisingly tall, robust and craniologically different people from Clarens in the Drakensberg region shows (Landsman et al. 2022 ). Clearly there are much to be learned. However, this lack of data seems to be the case for various southern African regions (e.g., Kinahan 2013 ) and it is clear that research lags behind in some regions of the subcontinent. The majority of larger skeletal assemblages in South Africa results from large scale excavations done in the first half of the 20th century (e.g., from Matjes River, Whitcher’s Cave, Mapungubwe/K2). While these were done in haphazard and unscientific ways (e.g, see Morris 2022 ), they did result in large (but often commingled) assemblages from a specific site. Recent additions of human skeletal remains to skeletal collections are rare and mostly result from inadvertently (often single) discovered graves, which are excavated as part of rescue operations (e.g., the skeletons from Cyferkuil, Modimulle and Nwanetzi included here). Unfortunately, the accompanying archaeological data from these are limited. This is unlikely to change in future, as excavation of human remains are now exceedingly rare. It is therefore important that remains in collections, which are often under-studied, should be reassessed, properly catalogued and analysed. In general, skeletal data from Iron Age Bantu-speaker populations are limited. What is imperative, is that when skeletal reports are published, basic, raw data are recorded and reported. Then at least the most appropriate methods of analysis can be selected or direct comparisons of long bone lengths made. For now, the array of methods used to reconstruct stature is confusing. While the femur:stature ratio seems to provide reliable statures, the problem is that femora, and specifically maximum femur lengths, are not always available. For now, we are probably best off to use either the Feldesman and Fountain ( 1996 ) ratios when they are avialable, or alternatively the formulae of Lundy and Feldesman ( 1987 ) with the Raxter et al. ( 2006 ) soft tissue corrections. No clear trends in stature across the last circa 1500 years could be observed from the available data. From this one may be tempted to propose that the environmental and general nutritional status did not change much, but this is almost certainly an oversimplification, even taking the limited data set into account. If the variation of stature in specific individuals are considered, some interesting patterns are seen. For example, the shortest of the female individuals –Newcastle (2007/006) - shows a 13.3% Khoe-San admixture from her autosomal DNA profile, although other genetic indicators (see Steyn et al. 2019 ) clearly show a West-African, Bantu-speaker origin. Is it conceivable that the limited Khoe-San genetic contributions could have contributed to her short stature? The tall Thulamela female (179.9 cm, UP 43) is also interesting – she was a high-status individual (royal because she was tall, or perhaps came from elsewhere through a marriage arrangement?) (Steyn et al. 1998 ). Her mtDNA tentatively aligned her with eastern African peoples (Bodiba et al. 2019 ), as opposed to the Thulamela male who aligned more with western peoples. The second tallest female (172.2 cm) A624, was also a high-status individual from Mapungubwe Hill. This possible pattern of taller statures for high-status individuals have been described before (Haviland 1967 ; Brødholt et al. 2023 ) although the patterns are complex and not always clear-cut (e.g., Robb et al. 2001 ) Of the males, the Clarens individual A4237/4231, was the tallest (185.8 cm) – as mentioned before, the early date, coupled with a very robust-looking group of individuals, makes these individuals interesting. Craniologically they did not align with any of the Howell’s groups of African individuals included in Fordisc (Jantz and Ousley 2005 ), and their origins are not currently clear (Landsman et al. 2022 ). The EIA Happy Rest male (UP 1), and the high status Mapungubwe hill male (A 619) were among the taller males, as was UP 139 from Pilanesberg and A 2857 from Olifantspoort. It is clear that adult statures are thus the products of gene flow, social status and general health. More data are needed. Tobias ( 1972 ) reported on the stature of various African groups – mostly from people in the first half of the 20th century. Unfortunately, mostly male data are included for Bantu-speakers. South African black groups with known statures mostly fell in the “medium” stature group, described by Tobias as having mean statures between 160 and 170 cm. This correlates well with the mean stature of 167.1 cm reported here, tentatively suggesting no significant changes from the Iron Age through to the early 20th century. Tobias does provide mean statures for Venda and Zulu females only, which are in the range of 150 to 160 cm – also similar to the 158.4 cm reported for females in this study, although their means were actually somewhat less and ranged between 154.0 and 156.4 cm. For now, we can thus not comment on changes in stature throughout the IA, and also into the early 20th century, but hopefully this data will stand as a possible reference source for future studies. It may also help in the interpretation of stature estimates in individual cases, as it provides a baseline against which statures can be interpreted. Overall, this paper also demonstrated the confusion that can arrive with the use of different formulae, but we will have to continue to use stature estimates (as opposed to femur lengths alone) as they can include remains of varying preservation. However, this is not without its problems and methods should be clearly described and raw data provided. Conclusion This paper assessed the practices used to estimate stature in Iron Age Bantu-speaker populations from South Africa, and assessed the available data on remains from this time period. Overall, methods used were inconsistent, poorly reported and unclear. There is an overall paucity of long bone data and stature estimates, making the assessment of overall trends and interpretations difficult. With the availability of data, no clear trends could be observed and statures seem to be on a par with that reported for early 20th century individuals. All currently available stature data are reported here and can form the base for future similar studies. Declarations Ethical Approval This research forms part of a larger study to sample skeletal remains for aDNA and dating, for which approval has been obtained from the Raymond A. Dart Archaeological Human Remains Collection committee at the University of the Witwatersrand. All other information was obtained from published sources. Funding No funding was received for this research. Availability of data and materials All data used for this study are available in the supplementary material. To access the remains, individual curators will need to be approached. References Allen JA (1877) The influence of physical conditions in the genesis of species. Radical Review 1:108-140 Bidmos MA, Manger PR (2012) New soft tissue correction factors for stature estimation: results from magnetic resonance imaging. Forensic Sci Int 214:212.e1-212.e7 Bodiba M, Steyn M, Bloomer P, Mosothwane MN, Rühli F, Bouwman A (2019) Ancient DNA Analysis of the Thulamela Remains: Deciphering the Migratory Patterns of a Southern African Population. J Afr Archaeol 17:161-172 Bogin B, Kapell M, Silva MIV, Orden AB, Smith PK, Loucky J. (2001) How genetic are human body proportions? In: Dasgupta P, Hauspie R (eds) Perspectives in Human Growth, Development and Maturation. Springer, Dordrecht, pp 205-221 Brits D, Manger PR, Bidmos MA (2017) The accuracy of the anatomical method for stature estimation in Black South African females. For Sci Int 278:409.e1-409.e10 Brødholt ET, Gautvik KM, Benedictow OJ, Günther CC, Sjøvold T, Holck P (2023) Female skeletal health and socioeconomic status in medieval Norway (11th–16th centuries AD): Analysis of bone mineral density and stature. Int J Osteoarch 33(1):83-93 De Villiers H (1972) Skeletal remains from Iron Age sites in the Orange Free State. S Afr J Sci 68:268-274 De Villiers H (1973) The Welgegund human skeleton: physical description. S Afr Archaeol Bull 72:163 Dupertuis CW, Hadden JA (1951) On the reconstruction of stature from long bones. Am J Phys Anthropol 9:15-54 Feldesman MR, Kleckner JG, Lundy JK (1990) The femur/stature ratio and estimates of stature in mid- and late-Pleistocene fossil hominids. Am J Phys Anthropol 83:359-372 Fully G (1956) Une nouvelle méthode de determination de la taille. Annales de Médicine Légale 36:266-273 Gustafsson A, Werdelin L, Tullberg BS, Lindenfors P (2007) Stature and sexual stature dimorphism in Sweden, from the 10th to the end of the 20th century. Am J Hum Biol 19:861-870 Haviland WA (1967) Stature at Tikal, Guatemala: implications for ancient Maya demography and social organization. Am Antiq 32:316-325 Huffman TN (2009) Mapungubwe and Great Zimbabwe: The origin and spread of social complexity in southern Africa. J Anthropol Archaeol 28:37–54 Feldesman MR, Fountain RL (1996) “Race” specificity and the femur/stature Ratio. Am J Phys Anthropol 100:207-224 İşcan MY, Steyn M (2013) The Human Skeleton in Forensic Medicine. Charles C Thomas, Springfield Jantz RL, Hunt DR, Meadows L (1994). Maximum length of the tibia: how did Trotter measure it? Am J Phys Anthropol 93:525–528 Jantz R, Ousley SD (2005) FORDISC 3.1. Computerized Forensic Discriminant Functions. Version 3.1. The University of Tennessee: Knoxville, TN Kinahan J (2013) The use of skeletal and complementary evidence to estimate human stature and identify the presence of women in the recent archaeological record of the Namib desert. S Afr Archaeol Bull 68:72-78 Komlos J (1994) Stature, living standards and economic development. The University of Chicago Press Kurki HK, Ginter JK, Stock JT, Pfeiffer S (2010) Body size estimation of small-bodied humans: applicability of current methods. Am J Phys Anthropol 141:169-180 Kurki HK, Pfeiffer S, Stynder DD (2012) Allometry of head and body size in Holocene foragers in the South African Cape. Am J Phys Anthropol 147:462-471 Landsman C, Meyer A, Steyn M (2022) A bioarchaeological analysis of skeletal remains from Van Zyl’s farm. Clarens, Free State, South Africa. Southern Afr Field Archaeol 1:1-18 Lundy JK, Feldesman M (1987) Revised equations for estimating living stature from the long bones of the South African Negro. South Afr J Sci 40:758-761 Mays S (2016) Estimation of stature in archaeological human skeletal remains from Britain. Am J Phys Anthropol 161:646-655 Morris AG (2022) Bones and Bodies: How South African Scientists Studied Race. Witwatersrand University Press, Johannesburg Pfeiffer S (2012) Conditions for evolution of small adult body size in southern Africa. Curr Anthropol 53:S383-S394 Pfeiffer S, Sealy J (2006) Body size among Holocene foragers of the Cape Ecozone, southern Africa. Am J Phys Anthropol 129:1–11 Pfeiffer S, Harrington L (2011) Bioarchaeological evidence for the basis of small adult stature in southern Africa. Curr Anthropol 52(3):449-461 Raxter MH, Auerbach BM, Ruff CB (2006) Revision of the Fully technique for estimating statures. Am J Phys Anthropol 130:374-384 Robb J, Bigazzi R, Lazzarini L, Scarsini C, Sonego F (2001) Social “status” and biological “status”: A comparison of grave goods and skeletal indicators from Pontecagnano. Am J Phys Anthropol 115:213-222 Ross AH, Konigsberg LW (2002) New formulae for estimating stature in the Balkans. J For Sci 47:165-167 Ruff CB (1993) Climatic adaptation and hominid evolution: the thermoregulatory imperative. Evol Anthropol: Issues, News, and Reviews 2(2):53-60 Ruff CB, Holt BM, Niskanen M, Sladek, V, Berner M, Garofalo E, Tompkins D (2012) Stature and body mass estimation from skeletal remains in the European Holocene. Am J Phys Anthropol 148, 601–607 Ruff C, Raxter M, Auerbach B (2012) Comment on Bidmos and Manger, "New soft tissue correction factors for stature estimation: results from magnetic resonance imaging" [Forensic Sci. Int. 214 (2012) 212.e1-212.e7]. Forensic Sci Int 222(1-3):e42-3 Sealy J (2006) Diet, mobility and settlement pattern among Holocene hunter-gatherers in southernmost Africa. Curr Anthropol 47:569-595 Sealy J, Pfeiffer S (2000) Diet, body size, and landscape use among Holocene people in the Southern Cape, South Africa. Curr Anthropol 4:642-655 Sjovold T (2000) Stature estimation from the skeleton. In: Encyclopaedia of Forensic Sciences. Siegel JA, Saukko PJ, Knupfer GC (eds). Academic Press, London, pp 276-284. Steckel RH (1995) Stature and the standard of living. J Econ Lit 33:1903-1940 Steyn M, Miller S, Nienaber WC, Loots M (1998) Late Iron Age gold burials from Thulamela (Pafuri Region, Kruger National Park). S Afr Archaeol Bull 53:73-85 Steyn M, Whitelaw G, Botha D, Vicente M, Schlebusch CM, Lombard M (2019) Four Iron Age women from KwaZulu-Natal: biological anthropology, genetics and archaeological context. Southern Afr Hum 32:23–56 Stock JT, Pfeiffer SK (2004) Long bone robusticity and subsistence behaviour among Later Stone Age foragers of the forest and fynbos biomes of South Africa. J Archaeol Sci 31:999-1013 Tanner JM (1994) Introduction: Growth in height as a mirror of the standard of living. In: Komlos J, Stature, living standards and economic development. The University of Chicago Press, pp 1-8 Tobias PV (1972) Growth and stature in Southern African populations. In: Vorster DJM (ed) Human Biology of Environmental Change. International Biological Programme. London, pp 96-104 Trotter M (1970) Estimation of stature from intact long limb bones. In: Stewart TD (ed) Personal Identification in Mass Disasters.: Smithsonian Institute, Washington, DC, pp 71–83 Trotter M, Gleser GC (1952) Estimation of stature from long bones of American Whites and Negroes. Am J Phys Anthropol 10(4):463-514 Vercellotti G, Piperata BA, Agnew AM, Wilson WM, Dufour DL, Reina JC, Boano R, Justus HM, Larsen CS, Stout SD, Sciulli PW (2014) Exploring the multidimensionality of stature variation in the past through comparisons of archaeological and living populations. Am J Phys Anthropol 155:229-242 Wells LH (1935) Remains from a grave in Klein Letaba district. S Afr J Sci 32:625-632 Additional Declarations No competing interests reported. Supplementary Files S1SteynStatureinIronAgepopulations.xlsx S2SteynStatureinIronAgepopulations.docx Cite Share Download PDF Status: Published Journal Publication published 22 Nov, 2023 Read the published version in Archaeological and Anthropological Sciences → Version 1 posted Editorial decision: Revision requested 01 Nov, 2023 Reviews received at journal 02 Sep, 2023 Reviewers agreed at journal 01 Sep, 2023 Reviewers invited by journal 29 Aug, 2023 Editor assigned by journal 28 Aug, 2023 Submission checks completed at journal 24 Aug, 2023 First submitted to journal 21 Aug, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3282701","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":228550596,"identity":"e4d37b52-fd09-4235-b440-fd3f28ba7df1","order_by":0,"name":"Maryna Steyn","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAklEQVRIiWNgGAWjYNCDDwwSJKjmAWLGGQwSJOgBaWEGEoS16LaffSZdUMNgb8/eY/bYts2iTr6B+eEHhj92OLWYnUk3k55xjCGxh+eMuXFum4SEwQE2YwkGnmTcWg6ksUnzsDEk8EjkmEnnbgNqAQoC3ceMW8v5Z0At/xjseeTfmElbArXIN7B/Y2AwqMet5QbQFt42BsYeCR4zaUagFoYDPEBbEg7j0fKM2Zq3TyKx50xamWTvPwnJDYd5iiUSDhzH47A0xts832zs2dsPb5P4caaOX769feOHD3+qcWoBAhYJSGxwGED4II8n4NMAVPIBQrM/wK9uFIyCUTAKRiwAACNQQzz8Il5tAAAAAElFTkSuQmCC","orcid":"","institution":"University of the Witwatersrand","correspondingAuthor":true,"prefix":"","firstName":"Maryna","middleName":"","lastName":"Steyn","suffix":""}],"badges":[],"createdAt":"2023-08-21 13:44:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3282701/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3282701/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s12520-023-01900-7","type":"published","date":"2023-11-22T15:00:58+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":42266985,"identity":"efcc1b30-7a20-4886-8afe-9c3b8a1fc6bb","added_by":"auto","created_at":"2023-08-28 20:15:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":127643,"visible":true,"origin":"","legend":"\u003cp\u003eStature of males and females across the Iron Age\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-3282701/v1/5585aad4babd345276f98d20.png"},{"id":47146282,"identity":"a4157554-d9a7-4787-a190-e6173ef9aa86","added_by":"auto","created_at":"2023-11-27 15:07:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":420748,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3282701/v1/3b1c886b-03e4-4e4a-8f6f-f6f4e3fca0d0.pdf"},{"id":42266206,"identity":"5f925b75-0dce-4a75-80a5-e90a7a6017ed","added_by":"auto","created_at":"2023-08-28 20:07:28","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":13109,"visible":true,"origin":"","legend":"","description":"","filename":"S1SteynStatureinIronAgepopulations.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3282701/v1/babdae4873e891e4d0fca517.xlsx"},{"id":42266207,"identity":"2a75880b-c6e0-4478-8150-609dcd5bebde","added_by":"auto","created_at":"2023-08-28 20:07:28","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":15982,"visible":true,"origin":"","legend":"","description":"","filename":"S2SteynStatureinIronAgepopulations.docx","url":"https://assets-eu.researchsquare.com/files/rs-3282701/v1/864530fc2b4676ea839f307c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessment of stature in Iron Age populations of South Africa","fulltext":[{"header":"Introduction","content":"\u003cp\u003eStature, and changes in stature, are often used to gain information on health and well-being of past and present populations (e.g., Komlos \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Tanner \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Steckel \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Vercelotti et al. 2014; Mays \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). It should, however, be kept in mind that final adult stature is the result of many factors, the most important of which is genetics (e.g, Tanner \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Bogin et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Tobias (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1972\u003c/span\u003e) was one of the first researchers to provide general information on stature of historic South Africans. Much more research has since been added on stature in past populations, with studies by Sealy and Pfeiffer (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) and others (e.g., Kurki et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Pfeiffer and Harrington \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Kinahan \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), particularly in Stone Age groups in southern Africa, providing examples of how growth and stature in autochtonous groups can help us to understand the influence of environmental and other factors on body size.\u003c/p\u003e \u003cp\u003eIn their paper, Sealy and Pfeiffer (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) provide maximum femur lengths and femoral head diameters, with dates, for a large number of Stone Age Holocene individuals from the Southern Cape, South Africa. Amongst other things, they found a pattern of stability among already-small San people, with a noteworthy increase in diversity and decline in mean body size from ca. 3 300 to 2 000 BP. Before 2 000 BP, the people of smallest stature were often also those who ate mostly terrestrial foods. After this date, this pattern no longer holds true. Very small people, all apparently women, occurred from 4 000 to 2 000 BP.\u003c/p\u003e \u003cp\u003eThis was followed by several other studies with similar themes (e.g., Sealy \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Pfeiffer and Sealy \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Pfeiffer \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) which reflected on the relationship between small body size and population density, food availability and types (through isotopic analysis), trauma, possible sexual selection etc. Other themes explored aspects of body size (Kurki et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Kurki et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), child growth (Pfeiffer and Harrington \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) and activity patters (Stock and Pfeiffer \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThese papers, mainly focusing on Stone Age hunter- and gatherer populations, show the value of looking at body size and stature, as well as trends in stature across time, as it reflects the general adaptation and well-being of populations as well as possible environmental changes. Stature is of course dependent on both environmental and genetic factors. In the changing landscape of southern Africa, with its continuous migrations and diffusion of populations, it is hard to separate genetic influences (e.g., the short stature of the Khoe-San) with changes that may have been brought on by environmental stressors or the absence thereof.\u003c/p\u003e \u003cp\u003eUnfortunately, much less research of this nature has been done on Iron Age Bantu-speaker populations of South Africa, with stature reconstructions usually mentioned in passing as part of individual skeletal reports. In most older publications of the early 20th century dealing with human skeletal remains, unfortunately, the focus was on the identification of racial characteristics of skulls (see Morris \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) with hardly any emphasis on anything related to the postcranial skeleton. Most of these early papers do not report on the long bones at all and do not make any attempt to reconstruct stature.\u003c/p\u003e \u003cp\u003eThese practices changed somewhat by the 1970\u0026rsquo;s, with physical anthropologists such as De Villiers (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1972\u003c/span\u003e; \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1973\u003c/span\u003e) including stature reconstructions in her reports, sometimes (but rarely) with attempts to bring it into a greater context. Unfortunately, De Villiers and others (e.g., Wells \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e1935\u003c/span\u003e) mostly do not report raw measurements, but rather provided reconstructed statures. At the time, population-specific stature reconstruction formulae were not available, and formulae developed by Trotter and Gleser (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1952\u003c/span\u003e) developed for North American populations were often employed in earlier publications. More recently other methods (e.g., Lundy and Feldesman \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1987\u003c/span\u003e; Feldesman and Fountain \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1996\u003c/span\u003e) became available and were used in skeletal reports. It is not clear from the literature exactly which methods are the most appropriate for the reconstruction of stature in South Africans, and particularly in Iron Age Bantu-speaker individuals.\u003c/p\u003e \u003cp\u003eThe aim of this paper is to assess the availability of long bone and stature data relating to Iron Age Bantu-speaker remains in South Africa, and to investigate which methods were used to reconstruct stature. An overview of available methods will be provided for practitioners not so familiar with the topic, as a guideline to use in such estimations \u0026ndash; this will include recommendations of what to use for South Africans and in this case particularly for the skeletal remains of Iron Age Bantu-speakers. All long bone and stature data from the literature, as well as unpublished reports, will be collated in order to assess for trends in stature in the past 2000 years, in an attempt to add information on the health and well-being (and perhaps possible genetic influences) of these individuals.\u003c/p\u003e\n\u003ch3\u003eStature reconstruction in archaeological populations\u003c/h3\u003e\n\u003cp\u003eIt is widely accepted in the forensic anthropological context that population-specific formulae should be used to reconstruct stature (e.g., Ross and Konigsberg \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; İşcan and Steyn \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). This, of course, is problematic when it comes to past populations and if ancestry / population is not known. It has conclusively been demonstrated that long bone lengths versus overall stature varies in different populations, and this is most probably related to the well-known associations between climate and body proportion (Allen \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1877\u003c/span\u003e; Ruff \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Feldesman and Fountain \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). Generally speaking, individuals in warmer climates have longer limbs relative to their overall heights, as a heat adaptation. The opposite is true for people living in colder climates. Of course, this picture becomes confounded in modern populations where people no longer live in their ancestral lands.\u003c/p\u003e \u003cp\u003eOne of the oldest methods of stature estimation is the use of a femur:stature ratio, as it was found that there is a relatively constant relationship between femur and overall stature in various populations across the world (Dupertius and Hadden 1951; Sjovold \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). The femur:stature ratio of various groups worldwide was assessed in detail by Feldesman and Fountain (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1996\u003c/span\u003e) using a large and diverse sample of individuals from various regions of the world \u0026ndash; from Eskimos to pygmee populations. The femur:stature ratio of Black African population groups was shown to be different from the generally observed value of 3.74 \u0026ndash; i.e., where maximum femur length multiplied by 3.74 provides a stature estimate (Feldesman \u0026amp; Fountain \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Sjovold \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). According to Feldesman and Fountain (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1996\u003c/span\u003e), the femur length constitutes approximately 26.75% of the stature across all ancestry groups (translating to the ratio of 3.74) but 27.13% in individuals of African descent and 26.48% in individuals of European decent \u0026ndash; demonstrating the somewhat longer limbs in Africans. While there are slight differences between males and females, they advise one generic formula \u0026ndash; in the case of individuals of African descent, the formula:\u003c/p\u003e \u003cp\u003eStature\u0026thinsp;=\u0026thinsp;30.285687 + (2.986895 x femur)\u003c/p\u003e \u003cp\u003eshould be used, as this regression formula gives a slightly better result than using the ratio itself. It should be noted that the femur length to be used in this formula is the maximum femur length, recorded in cm (in standard reports, both maximum and physiological length are usually recorded, with the physiological length being shorter than the maximum length). An advantage of this method is that it provides an estimate of the living stature, and it is not necessary to add a soft tissue correction factor (as is necessary for method based on Total Skeletal Height, TSH, introduced by Fully \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1956\u003c/span\u003e). A disadvantage is that the ratio does not provide an estimate of the uncertainty around this point estimate \u0026ndash; other traditional formulae usually provide an SEE (Standard Error of Estimate) that allows one to provide a stature estimate with a 95% confidence interval. The largest disadvantage of using femur:stature ratios in archaeological populations, as opposed to other methods to assess stature, however, is the fact that the femora may not be complete or not preserved at all and that maximum femur length is therefore not avialable. Other long bones and measurements are therefore often used to estimate the stature.\u003c/p\u003e \u003cp\u003eIn South Africa, the formulae of Lundy and Feldesman (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1987\u003c/span\u003e) are widely used in modern and archaeological cases concerning black Africans. However, it should be taken into account that these formulae provide an estimate of the Total skeletal Height (TSH) \u0026ndash; i.e., it reconstructs the proportion of the stature that is made up by the skeletal elements. From here, this value should be adjusted to account for soft tissues \u0026ndash; for a TSH of less than 153.5 cm, 10 cm is added; for a TSH 153.5 to 163.5 cm, 10.5 cm must be added for a THS of more than 163.5 cm, 11.5 cm is added (Fully \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1956\u003c/span\u003e). More recently, Raxter et al. (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) provided new, generic (world-wide) soft tissue correction factors which are commonly in use to convert TSH into living stature. If no correction for the age of an individual is made, living stature\u0026thinsp;=\u0026thinsp;0,996 x Skeletal height (TSH)\u0026thinsp;+\u0026thinsp;11.7 (SEE 2:31).\u003c/p\u003e \u003cp\u003eUnfortunately, in South Africa, it has been shown that these soft tissue correction factors, and especially that of Lundy \u0026amp; Feldesman (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1987\u003c/span\u003e) consistently underestimate stature (e.g., Bidmos and Manger \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2012\u003c/span\u003e, Brits et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The new Bidmos and Manger (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) corrections for South African black males have been criticized due to some technical issues (Ruff et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), while that of Brits et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) are commonly in use for black females. This does leave a conundrum, because it means that in the South African context, there is no reciprocity between males and females when living stature is reconstructed from TSH using the most recent soft tissue corrections. Until firmly established soft tissue correction factors are established for African males, it is therefore advised that the Raxter et al. (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) soft tissue corrections are used in archaeological settings. These are in use world-wide, but are not population-specific and may under-estimate stature in South Africans.\u003c/p\u003e \u003cp\u003eA word of caution \u0026ndash; for the Trotter and Gleser (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1952\u003c/span\u003e) formulae specifically, there is some confusion as to exactly how the tibiae were measured (Jantz et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Mays \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) \u0026ndash; the tibiae can be measured as maximum lengths (with medial malleolus), or physiological length (without the malleolus). The physiological lengths are also reportedly sometimes recorded with callipers rather than an osteometric board. This confusion makes the use of the tibia unpopular, and should tibial formulae be used the exact manner of recording, as used in the publication providing the formulae, should be established. Similarly, some formulae require the use of maximum femur length, whereas others use the physiological / bicondylar femur length. De Villiers, in her 1981 unpublished report on the Broederstroom, Munro and Olifantspoort remains, for example, provides the maximum femur lengths (FeL1), but then goes on to say that the Lundy formulae were used to reconstruct stature \u0026ndash; these, however, use physiological / bicondylar length. Reported statures, without providing raw data, are therefore problematical.\u003c/p\u003e \u003cp\u003eIn general, when several long bones are available, the bone (formulae) with the highest correlation to stature should be used. In most sets of formulae, the femur usually has the highest correlation to actual stature, followed by the tibia. In the upper limb, the radius is usually the best correlated to stature (but less so than the lower limb bones).\u003c/p\u003e \u003cp\u003ePfeiffer and Sealy (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) in a paper on body size of Holocene foragers from the Cape ecozone, clearly encountered the same difficulties when having to deal with different methods to reconstruct stature. They used the regression equations proposed by Feldesman and Fountain (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1996\u003c/span\u003e), the generic femur:stature ratio of 26.74 proposed by Feldesman et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1990\u003c/span\u003e), and the sex-specific equations for black and white individuals developed by Trotter (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1970\u003c/span\u003e). These problems with stature estimation are not unique to South Africa and have been debated in several other regions of the world (e.g., Ruff et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Kinahan \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Mays \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). This demonstrates the difficulty with obtaining comparable stature data from long bone lengths across populations, especially with varying degrees of preservation of remains.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eFor this study, reported long bone and stature data of southern African Iron Age Bantu-speaker individuals, focusing on individuals from the pre-colonial era, were collected. Only individuals with firm dates were included, or individuals that came from archaeological sites that were firmly dated. Only adult individuals, or late adolescent individuals with complete epiphyseal closure, were included. Individuals were divided by sex.\u003c/p\u003e \u003cp\u003eFor each individual, depending on the data available, the following were calculated/recorded:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eStature based on the Trotter and Gleser (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1952\u003c/span\u003e) formulae for black Americans (Terry Collection), as these were sometimes used by De Villiers, also in reports where raw long bone lengths were not provided.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eStature based on the Lundy and Feldesman (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1987\u003c/span\u003e) formulae for modern black South Africans, using the original (Fully \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1956\u003c/span\u003e) soft tissue correction factors.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eStature based on the Lundy and Feldesman (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1987\u003c/span\u003e) formulae for modern black South Africans, using the Raxter et al. (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) soft tissue correction factors. The general formula, not corrected for age, was used as age estimates were often not available.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eStature based on the femur:stature ratio for Africans, using the regression equation of Feldesman and Fountain (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1996\u003c/span\u003e) where living stature\u0026thinsp;=\u0026thinsp;30.285687 + (2.986895 x femur maximum length)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eWhere no long bone data were recorded, but a stature was published, this was included as a \u0026ldquo;reported stature\u0026rdquo;.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eFor all cases, only the point estimate (without SEE) was used for purposes of comparison. The statures of individuals, using the various methods, were compared in order to assess for, for example, consistent over- and underestimation. Unfortunately, the actual, living stature is of course not available and therefore these can never be assessed for real accuracy.\u003c/p\u003e \u003cp\u003eIn order to assess if changes in stature occurred, individuals were divided into Huffman\u0026rsquo;s (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) descriptions of Early, Middle and Late Iron age. While not all archaeologists would agree with this division, it provides a convenient way to compare statures across time periods. Following this, Early Iron Age (EIA) individuals were dated to AD 100\u0026ndash;900, Middle Iron Age (MIA) to AD 900\u0026ndash;1300 and Late Iron Age (LIA) to AD 1300\u0026ndash;1840. Within each of these time periods, the mean statures were calculated \u0026ndash; e,g., mean stature of EIA females, mean stature of MIA females, etc. Mean statures across the three time periods, for females and males respectively, were assessed using ANOVA to establish if stature changed significantly. For this purpose, SPSS (Statistical Package for Social Sciences) was used.\u003c/p\u003e \u003cp\u003eAs these individuals were all dated, or came from dated sites, stature versus date were plotted on a graph to visually assess trends and scatter. For this purpose, the midpoint of the reported AD dates was used for each individual as the raw (before present) dates were often not available. This is of course only a wide approximation of the date of each skeleton, but it assists to graphically assess the available data.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe raw data, with reported long bone lengths per individual, are shown in the Supplementary material (S1) for future use in similar studies. It also shows the full detail of each skeleton, as well as the reference for each entry (full reference list in S2).\u003c/p\u003e \u003cp\u003eThe availability of long bone or stature data from the South African Iron Age is disappointing. For the Early Iron Age (as per the definition above), information for only two males and two females could be obtained. For the MIA, data were available for 6 females and 13 males, while the corresponding numbers for the LIA were 17 (female) and 16 (male). This brings the total sample to n\u0026thinsp;=\u0026thinsp;56 individuals (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e reflects the reconstructed statures for each individual, using various different methods. Only the point estimates, without SEE\u0026rsquo;s are included here, for easy comparison. Overall, the formulae of Trotter and Gleser (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1952\u003c/span\u003e) provided relatively tall estimates, clearly out of line with other formulae. The Lundy and Feldesman (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1987\u003c/span\u003e) formulae with the soft tissue corrections of Raxter et al. (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) provided slightly taller estimates than the original soft tissue corrections, as expected. The femur:stature ratio (as per the regression) of Feldesman and Fountain (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1996\u003c/span\u003e), in general provided estimates that were slightly taller than the Lundy and Feldesman (with Raxter et al. corrections) formulae (1.4 cm on average; two were taller and the remainder shorter). These ratios still provided statures that were shorter than those using the Trotter and Gleser (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1952\u003c/span\u003e) formulae.\u003c/p\u003e \u003cp\u003eIn each individual case, and for further comparison, a judgement call was made as to which stature estimate was most probably the most accurate for each individual. As the Lundy and Feldesman (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1987\u003c/span\u003e) formulae with Raxter et al. (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) soft tissue corrections are often criticized because they tend to underestimate (Bidmos and Manger \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2012\u003c/span\u003e, Brits et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), the Feldesman and Fountain (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1996\u003c/span\u003e) femur:stature ratio was deemed the most accurate (where maximum femur lengths were available), followed by the Lundy and Feldesman (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1987\u003c/span\u003e) formulae with the Raxter et al. (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) soft tissue corrections (also used for cases where only physiological length of the femur was reported). Estimates using the femur was preferred over that using the tibia, with the radius usually deemed the next best choice. However, in some individuals, only a single long bone such as a fibula or humerus length was available and had to be used. In 14 cases, no raw data (long bone lengths) were recorded and only a reported stature was available \u0026ndash; in some cases, e.g., Glennel, the author stated which method was used (Trotter and Gleser in this case), whereas in others (e.g., Eersteling) no information was given as to how the estimate was derived. For the Broederstroom female, in an unpublished report, De Villiers quoted a stature estimate of 150 cm although it was not clear on what it was based \u0026ndash; a maximum tibia length was recorded but did not correlate with a 150 cm reconstruction, creating some confusion and the reconstructed stature was retained.\u003c/p\u003e \u003cp\u003eAverage statures of females were 152.0 cm in the EIA (n\u0026thinsp;=\u0026thinsp;2), 159.3 in the MIA (n\u0026thinsp;=\u0026thinsp;6) and 1588 cm (n\u0026thinsp;=\u0026thinsp;17) in the LIA, with no clear trend visible (p\u0026thinsp;=\u0026thinsp;0.500). A similarly non-directional, not significantly different (p\u0026thinsp;=\u0026thinsp;0.645) pattern was seen in males, where average stature was 171.6 cm (n\u0026thinsp;=\u0026thinsp;2) in the EIA, 166.4 cm (n\u0026thinsp;=\u0026thinsp;13) in the MIA and 167.1 cm (n\u0026thinsp;=\u0026thinsp;17) in the LIA. Overall, female stature ranged from 143.2 cm (Newcastle 2007/006) to 179.9 cm (Thulamela, UP 43) with an overall mean of 158.4 cm (n\u0026thinsp;=\u0026thinsp;23; SD 7.906). For males, the shortest stature was 156.4 cm (from the little-known MIA site of Munro) and the tallest 185.8 cm (from Clarens, an MIA site). The overall mean for males is 167.1 cm (SD 7.101).\u003c/p\u003e \u003cp\u003eThe data are graphically represented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, where a wide scatter can be observed. What is once again obvious from Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, is that the data from the EIA is very limited, with peaks around the LIA and the K2/Mapungubwe (MIA) period (circa AD 1000 to 1300). As expected, males are generally taller than females, although some overlap is evident.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStature reconstruction using various formulae. Stature estimates are shown in cm.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndividual\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePeriod\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReported\u003c/p\u003e \u003cp\u003estature\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eT\u0026amp;G\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eL\u0026amp;F\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eL\u0026amp;F Raxter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eFem ratio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eFinal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBroederstroom A4143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e150.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e163.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e150.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMhlopeni PMB 80/2.1b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e161.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e161.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e162.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e153.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e153.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eMean\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e152.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHappyrest UP1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e175.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e170.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e171.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e173.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e173.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKwaGandaganda PMB001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e172.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e167.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e167.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e169.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e169.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eMean\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e171.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK2 A1722\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e154.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e148.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e149.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e151.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e151.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK2 A1730\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e158.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e152.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e154.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e156.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e156.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMapungubwe A624\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e170.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e170.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e170.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e172.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e172.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePilanesberg UP51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e150.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e151.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e151.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlennel 1/1 D35.1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e160.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e160.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e160.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlennel 2/1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e164.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e164.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e164.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eMean\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e159.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClarens A4237/4231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e183.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e181.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e181.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e185.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e185.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK2 A1714\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e162.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e163.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e163.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK2 A1732\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e168.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e161.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e162.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e163.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e163.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK2 A1734\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e184.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e173.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e173.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e173.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK2 A1758\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e163.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e155.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e156.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e157.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e157.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK2; KS58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e167.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e162.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e162.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMapungubwe A619\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e175.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e173.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e173.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e174.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e174.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKon-Stayt UP77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e167.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e168.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e168.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSchroda NAS2AA.3(i).1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e169.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e169.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e169.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlennel 1/1 A25.1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e169.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e169.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e169.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlennel 1/1 B26.1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e161.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e161.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e161.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMapungubwe UP145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e160.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e156.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e157.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e157.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMunro burial 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e156.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e156.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eMean\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e166.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAskoppies NASB1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e155.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e149.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e151.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e152.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e152.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChampagne C PMB2009/023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e157.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e150.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e151.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e155.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e155.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCyferkuil UP94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e171.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e161.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e163.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e163.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEersteling A410c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e157.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e157.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEllerton Mine A414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e156.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e156.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLindley UCT326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e156.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e156.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e156.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNewcastle 2007/006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e149.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e142.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e143.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e143.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePilanesberg UP95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e161.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e161.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e161.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThabazimbi UP132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e154.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e144.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e145.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e145.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThulamela UP43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e176.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e176.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e175.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e179.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e179.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWellington Estate A1103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e164.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e159.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e160.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e160.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWellington Estate A1836\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e160.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e168.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e168.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e168.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWellington Estate A2235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e160.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e160.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWillow Glen UP 72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e162.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e157.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e158.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e158.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKlip River Valley UCT UCT329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e160.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e160.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e160.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOlifantspoort A4221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e164.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e159.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e161.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e163.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e163.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOlifantspoort A2853\u0026amp;2854\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e162.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e156.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e157.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e157.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eMean\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e158.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKaybar's Cave A294\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e172.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e167.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e167.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e169.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e169.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKaybar's Cave A295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e165.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e159.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e160.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e159.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e159.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMakapanstad UP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e160.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e161.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e161.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMakgope UP48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e172.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e167.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e168.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e169.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e169.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMakgope UP49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e168.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e162.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e163.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e163.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e163.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModimolle UP92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e168.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e163.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e164.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e164.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e164.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNwanetsi UP130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e168.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e161.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e162.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e162.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePilanesberg UP139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e181.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e178.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e178.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e182.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e182.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePilanesberg UP143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e166.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e166.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e166.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRobinson's Shelter A302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e174.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e169.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e170.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e173.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e173.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSkukuza Rock Shelter UP29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e172.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e165.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e166.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e166.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThulamela UP44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e172.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e165.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e166.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e166.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWelgegund UP12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e166.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e166.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWellington Estate A1838\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e162.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e157.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e159.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e159.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYellowtree Shelter A299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e169.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e164.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e164.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e165.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e165.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOlifantspoort burial 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e187.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e179.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e179.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e179.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eMean\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e167.1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe availability of long bone data lengths and stature for individuals from the South African Iron Age is disappointing, and the reasons for this \u0026ndash; relative to the much more numerous Stone Age data from the southern provinces \u0026ndash; can be debated. It possibly reflects the preoccupation of early physical anthropologists with \u0026ldquo;race\u0026rdquo; and the San/KhoeSan populations of southern Africa, where excavations focused on cave sites along the coast that yielded large numbers of skeletons. Perhaps it is also related to a general perception that we know much about the relatively recent incoming Iron Age agriculturalists, and that their histories are somehow less interesting. This is most certainly not true as, for example, the recently reported MIA dating of surprisingly tall, robust and craniologically different people from Clarens in the Drakensberg region shows (Landsman et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Clearly there are much to be learned. However, this lack of data seems to be the case for various southern African regions (e.g., Kinahan \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and it is clear that research lags behind in some regions of the subcontinent.\u003c/p\u003e \u003cp\u003eThe majority of larger skeletal assemblages in South Africa results from large scale excavations done in the first half of the 20th century (e.g., from Matjes River, Whitcher\u0026rsquo;s Cave, Mapungubwe/K2). While these were done in haphazard and unscientific ways (e.g, see Morris \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), they did result in large (but often commingled) assemblages from a specific site. Recent additions of human skeletal remains to skeletal collections are rare and mostly result from inadvertently (often single) discovered graves, which are excavated as part of rescue operations (e.g., the skeletons from Cyferkuil, Modimulle and Nwanetzi included here). Unfortunately, the accompanying archaeological data from these are limited. This is unlikely to change in future, as excavation of human remains are now exceedingly rare. It is therefore important that remains in collections, which are often under-studied, should be reassessed, properly catalogued and analysed.\u003c/p\u003e \u003cp\u003eIn general, skeletal data from Iron Age Bantu-speaker populations are limited. What is imperative, is that when skeletal reports are published, basic, raw data are recorded and reported. Then at least the most appropriate methods of analysis can be selected or direct comparisons of long bone lengths made. For now, the array of methods used to reconstruct stature is confusing. While the femur:stature ratio seems to provide reliable statures, the problem is that femora, and specifically maximum femur lengths, are not always available. For now, we are probably best off to use either the Feldesman and Fountain (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1996\u003c/span\u003e) ratios when they are avialable, or alternatively the formulae of Lundy and Feldesman (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1987\u003c/span\u003e) with the Raxter et al. (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) soft tissue corrections.\u003c/p\u003e \u003cp\u003eNo clear trends in stature across the last circa 1500 years could be observed from the available data. From this one may be tempted to propose that the environmental and general nutritional status did not change much, but this is almost certainly an oversimplification, even taking the limited data set into account. If the variation of stature in specific individuals are considered, some interesting patterns are seen. For example, the shortest of the female individuals \u0026ndash;Newcastle (2007/006) - shows a 13.3% Khoe-San admixture from her autosomal DNA profile, although other genetic indicators (see Steyn et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) clearly show a West-African, Bantu-speaker origin. Is it conceivable that the limited Khoe-San genetic contributions could have contributed to her short stature? The tall Thulamela female (179.9 cm, UP 43) is also interesting \u0026ndash; she was a high-status individual (royal because she was tall, or perhaps came from elsewhere through a marriage arrangement?) (Steyn et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Her mtDNA tentatively aligned her with eastern African peoples (Bodiba et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), as opposed to the Thulamela male who aligned more with western peoples. The second tallest female (172.2 cm) A624, was also a high-status individual from Mapungubwe Hill. This possible pattern of taller statures for high-status individuals have been described before (Haviland \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1967\u003c/span\u003e; Br\u0026oslash;dholt et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) although the patterns are complex and not always clear-cut (e.g., Robb et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2001\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eOf the males, the Clarens individual A4237/4231, was the tallest (185.8 cm) \u0026ndash; as mentioned before, the early date, coupled with a very robust-looking group of individuals, makes these individuals interesting. Craniologically they did not align with any of the Howell\u0026rsquo;s groups of African individuals included in Fordisc (Jantz and Ousley \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), and their origins are not currently clear (Landsman et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The EIA Happy Rest male (UP 1), and the high status Mapungubwe hill male (A 619) were among the taller males, as was UP 139 from Pilanesberg and A 2857 from Olifantspoort. It is clear that adult statures are thus the products of gene flow, social status and general health. More data are needed.\u003c/p\u003e \u003cp\u003eTobias (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1972\u003c/span\u003e) reported on the stature of various African groups \u0026ndash; mostly from people in the first half of the 20th century. Unfortunately, mostly male data are included for Bantu-speakers. South African black groups with known statures mostly fell in the \u0026ldquo;medium\u0026rdquo; stature group, described by Tobias as having mean statures between 160 and 170 cm. This correlates well with the mean stature of 167.1 cm reported here, tentatively suggesting no significant changes from the Iron Age through to the early 20th century. Tobias does provide mean statures for Venda and Zulu females only, which are in the range of 150 to 160 cm \u0026ndash; also similar to the 158.4 cm reported for females in this study, although their means were actually somewhat less and ranged between 154.0 and 156.4 cm.\u003c/p\u003e \u003cp\u003eFor now, we can thus not comment on changes in stature throughout the IA, and also into the early 20th century, but hopefully this data will stand as a possible reference source for future studies. It may also help in the interpretation of stature estimates in individual cases, as it provides a baseline against which statures can be interpreted. Overall, this paper also demonstrated the confusion that can arrive with the use of different formulae, but we will have to continue to use stature estimates (as opposed to femur lengths alone) as they can include remains of varying preservation. However, this is not without its problems and methods should be clearly described and raw data provided.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis paper assessed the practices used to estimate stature in Iron Age Bantu-speaker populations from South Africa, and assessed the available data on remains from this time period. Overall, methods used were inconsistent, poorly reported and unclear. There is an overall paucity of long bone data and stature estimates, making the assessment of overall trends and interpretations difficult. With the availability of data, no clear trends could be observed and statures seem to be on a par with that reported for early 20th century individuals. All currently available stature data are reported here and can form the base for future similar studies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research forms part of a larger study to sample skeletal remains for aDNA and dating, for which approval has been obtained from the Raymond A. Dart Archaeological Human Remains Collection committee at the University of the Witwatersrand. All other information was obtained from published sources.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received for this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data used for this study are available in the supplementary material. To access the remains, individual curators will need to be approached.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAllen JA (1877) The influence of physical conditions in the genesis of species. Radical Review 1:108-140\u003c/li\u003e\n \u003cli\u003eBidmos MA, Manger PR (2012) New soft tissue correction factors for stature estimation: results from magnetic resonance imaging. Forensic Sci Int 214:212.e1-212.e7\u003c/li\u003e\n \u003cli\u003eBodiba M, Steyn M, Bloomer P, Mosothwane MN, R\u0026uuml;hli F, Bouwman A (2019) Ancient DNA Analysis of the Thulamela Remains: Deciphering the Migratory Patterns of a Southern African Population. J Afr Archaeol 17:161-172\u003c/li\u003e\n \u003cli\u003eBogin B, Kapell M, Silva MIV, Orden AB, Smith PK, Loucky J. (2001) How genetic are human body proportions? In: Dasgupta P, Hauspie R (eds) Perspectives in Human Growth, Development and Maturation. Springer, Dordrecht, pp 205-221\u003c/li\u003e\n \u003cli\u003eBrits D, Manger PR, Bidmos MA (2017) The accuracy of the anatomical method for stature estimation in Black South African females. For Sci Int 278:409.e1-409.e10\u003c/li\u003e\n \u003cli\u003eBr\u0026oslash;dholt ET, Gautvik KM, Benedictow OJ, G\u0026uuml;nther CC, Sj\u0026oslash;vold T, Holck P (2023) Female skeletal health and socioeconomic status in medieval Norway (11th\u0026ndash;16th centuries AD): Analysis of bone mineral density and stature. Int J Osteoarch 33(1):83-93\u003c/li\u003e\n \u003cli\u003eDe Villiers H (1972) Skeletal remains from Iron Age sites in the Orange Free State. S Afr J Sci 68:268-274\u003c/li\u003e\n \u003cli\u003eDe Villiers H (1973) The Welgegund human skeleton: physical description. S Afr Archaeol Bull 72:163\u003c/li\u003e\n \u003cli\u003eDupertuis CW, Hadden JA (1951) On the reconstruction of stature from long bones. Am J Phys Anthropol 9:15-54\u003c/li\u003e\n \u003cli\u003eFeldesman MR, Kleckner JG, Lundy JK (1990) The femur/stature ratio and estimates of stature in mid- and late-Pleistocene fossil hominids. Am J Phys Anthropol 83:359-372\u003c/li\u003e\n \u003cli\u003eFully G (1956) Une nouvelle m\u0026eacute;thode de determination de la taille. Annales de M\u0026eacute;dicine L\u0026eacute;gale 36:266-273\u003c/li\u003e\n \u003cli\u003eGustafsson A, Werdelin L, Tullberg BS, Lindenfors P (2007) Stature and sexual stature dimorphism in Sweden, from the 10th to the end of the 20th century. Am J Hum Biol 19:861-870\u003c/li\u003e\n \u003cli\u003eHaviland WA (1967) Stature at Tikal, Guatemala: implications for ancient Maya demography and social organization. Am Antiq 32:316-325\u003c/li\u003e\n \u003cli\u003eHuffman TN (2009) Mapungubwe and Great Zimbabwe: The origin and spread of social complexity in southern Africa. J Anthropol Archaeol 28:37\u0026ndash;54\u003c/li\u003e\n \u003cli\u003eFeldesman MR, Fountain RL (1996) \u0026ldquo;Race\u0026rdquo; specificity and the femur/stature Ratio. Am J Phys Anthropol 100:207-224\u003c/li\u003e\n \u003cli\u003eİşcan\u0026nbsp;MY, Steyn M (2013) The Human Skeleton in Forensic Medicine. Charles C Thomas, Springfield\u003c/li\u003e\n \u003cli\u003eJantz RL, Hunt DR, Meadows L (1994). Maximum length of the tibia: how did Trotter measure it? Am J Phys Anthropol 93:525\u0026ndash;528\u003c/li\u003e\n \u003cli\u003eJantz R, Ousley SD (2005) FORDISC 3.1. Computerized Forensic Discriminant Functions. Version 3.1. The University of Tennessee: Knoxville, TN\u003c/li\u003e\n \u003cli\u003eKinahan J (2013) The use of skeletal and complementary evidence to estimate human stature and identify the presence of women in the recent archaeological record of the Namib desert. S Afr Archaeol Bull 68:72-78\u003c/li\u003e\n \u003cli\u003eKomlos J (1994) Stature, living standards and economic development. The University of Chicago Press\u003c/li\u003e\n \u003cli\u003eKurki HK, Ginter JK, Stock JT, Pfeiffer S (2010) Body size estimation of small-bodied humans: applicability of current methods. Am J Phys Anthropol 141:169-180\u003c/li\u003e\n \u003cli\u003eKurki HK, Pfeiffer S, Stynder DD (2012) Allometry of head and body size in Holocene foragers in the South African Cape. Am J Phys Anthropol 147:462-471\u003c/li\u003e\n \u003cli\u003eLandsman C, Meyer A, Steyn M (2022) A bioarchaeological analysis of skeletal remains from Van Zyl\u0026rsquo;s farm. Clarens, Free State, South Africa. Southern Afr Field Archaeol 1:1-18\u003c/li\u003e\n \u003cli\u003eLundy JK, Feldesman M (1987) Revised equations for estimating living stature from the long bones of the South African Negro. South Afr J Sci 40:758-761\u003c/li\u003e\n \u003cli\u003eMays S (2016) Estimation of stature in archaeological human skeletal remains from Britain. Am J Phys Anthropol 161:646-655\u003c/li\u003e\n \u003cli\u003eMorris AG (2022) Bones and Bodies: How South African Scientists Studied Race. Witwatersrand University Press, Johannesburg\u003c/li\u003e\n \u003cli\u003ePfeiffer S (2012) Conditions for evolution of small adult body size in southern Africa. Curr Anthropol 53:S383-S394\u003c/li\u003e\n \u003cli\u003ePfeiffer S, Sealy J (2006) Body size among Holocene foragers of the Cape Ecozone, southern Africa. Am J Phys Anthropol 129:1\u0026ndash;11\u003c/li\u003e\n \u003cli\u003ePfeiffer S, Harrington L (2011) Bioarchaeological evidence for the basis of small adult stature in southern Africa. Curr Anthropol 52(3):449-461\u003c/li\u003e\n \u003cli\u003eRaxter MH, Auerbach BM, Ruff CB (2006) Revision of the Fully technique for estimating statures. Am J Phys Anthropol 130:374-384\u003c/li\u003e\n \u003cli\u003eRobb J, Bigazzi R, Lazzarini L, Scarsini C, Sonego F (2001) Social \u0026ldquo;status\u0026rdquo; and biological \u0026ldquo;status\u0026rdquo;: A comparison of grave goods and skeletal indicators from Pontecagnano. Am J Phys Anthropol 115:213-222\u003c/li\u003e\n \u003cli\u003eRoss AH, Konigsberg LW (2002) New formulae for estimating stature in the Balkans. J For Sci 47:165-167\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eRuff CB (1993) Climatic adaptation and hominid evolution: the thermoregulatory imperative. Evol Anthropol: Issues, News, and Reviews 2(2):53-60\u003c/li\u003e\n \u003cli\u003eRuff CB, Holt BM, Niskanen M, Sladek, V, Berner M, Garofalo E, Tompkins D (2012) Stature and body mass estimation from skeletal remains in the European Holocene. Am J Phys Anthropol 148, 601\u0026ndash;607\u003c/li\u003e\n \u003cli\u003eRuff C, Raxter M, Auerbach B (2012) Comment on Bidmos and Manger, \u0026quot;New soft tissue correction factors for stature estimation: results from magnetic resonance imaging\u0026quot; [Forensic Sci. Int. 214 (2012) 212.e1-212.e7]. Forensic Sci Int 222(1-3):e42-3\u003c/li\u003e\n \u003cli\u003eSealy J (2006) Diet, mobility and settlement pattern among Holocene hunter-gatherers in southernmost Africa. Curr Anthropol 47:569-595\u003c/li\u003e\n \u003cli\u003eSealy J, Pfeiffer S (2000) Diet, body size, and landscape use among Holocene people in the Southern Cape, South Africa. Curr Anthropol 4:642-655\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSjovold T (2000) Stature estimation from the skeleton. In: Encyclopaedia of Forensic Sciences. Siegel JA, Saukko PJ, Knupfer GC (eds). Academic Press, London, pp 276-284.\u003c/li\u003e\n \u003cli\u003eSteckel RH (1995) Stature and the standard of living. J Econ Lit 33:1903-1940\u003c/li\u003e\n \u003cli\u003eSteyn M, Miller S, Nienaber WC, Loots M (1998) Late Iron Age gold burials from Thulamela (Pafuri Region, Kruger National Park). S Afr Archaeol Bull 53:73-85\u003c/li\u003e\n \u003cli\u003eSteyn M, Whitelaw G, Botha D, Vicente M, Schlebusch CM, Lombard M (2019) Four Iron Age women from KwaZulu-Natal: biological anthropology, genetics and archaeological context. Southern Afr Hum 32:23\u0026ndash;56\u003c/li\u003e\n \u003cli\u003eStock JT, Pfeiffer SK (2004) Long bone robusticity and subsistence behaviour among Later Stone Age foragers of the forest and fynbos biomes of South Africa. J Archaeol Sci 31:999-1013 \u0026nbsp;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eTanner JM (1994) Introduction: Growth in height as a mirror of the standard of living. In: Komlos J, Stature, living standards and economic development. The University of Chicago Press, pp 1-8\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eTobias PV (1972) Growth and stature in Southern African populations. In: Vorster DJM (ed) Human Biology of Environmental Change. International Biological Programme. London, pp 96-104\u003c/li\u003e\n \u003cli\u003eTrotter M (1970) Estimation of stature from intact long limb bones. In: Stewart TD (ed) \u0026nbsp;Personal Identification in Mass Disasters.: Smithsonian Institute, Washington, DC, pp 71\u0026ndash;83\u003c/li\u003e\n \u003cli\u003eTrotter M, Gleser GC (1952) Estimation of stature from long bones of American Whites and Negroes. Am J Phys Anthropol 10(4):463-514\u003c/li\u003e\n \u003cli\u003eVercellotti G, Piperata BA, Agnew AM, Wilson WM, Dufour DL, Reina JC, Boano R, Justus HM, Larsen CS, Stout SD, Sciulli PW (2014) Exploring the multidimensionality of stature variation in the past through comparisons of archaeological and living populations. Am J Phys Anthropol 155:229-242\u003c/li\u003e\n \u003cli\u003eWells LH (1935) Remains from a grave in Klein Letaba district. S Afr J Sci 32:625-632\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"archaeological-and-anthropological-sciences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aasc","sideBox":"Learn more about [Archaeological and Anthropological Sciences](http://link.springer.com/journal/12517)","snPcode":"12520","submissionUrl":"https://submission.nature.com/new-submission/12520/3","title":"Archaeological and Anthropological Sciences","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"long bones, regression equations, femur:stature ratio, stature reconstruction","lastPublishedDoi":"10.21203/rs.3.rs-3282701/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3282701/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWorldwide and in South African Stone Age contexts, much research has been done on the relationship between stature of past populations and general well-being, as well as trends and patterns in stature through time. This research aimed at collating and assessing all available stature and long bone data for Bantu-speaker individuals living in the South African Iron Age. Data for only 25 female and 32 male individuals, dating from circa AD 550 to AD 1823, could be found. In general, methods used to reconstruct stature were inconsistent and data were poorly reported. From the available data, no clear trends or patterns in stature through time could be observed and stature seems to be on a par relative to those of early 20th century individuals. Recommendations are made as to which methods to use in stature estimations in this context. The data provided in this research can serve as reference material for future similar studies and can assist in interpreting individual stature estimations from bioarchaeological research in the region.\u003c/p\u003e","manuscriptTitle":"Assessment of stature in Iron Age populations of South Africa","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-08-28 20:07:23","doi":"10.21203/rs.3.rs-3282701/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2023-11-01T19:14:46+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-09-02T13:46:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"d60ca00e-9529-4f27-93c0-a7fdd917bfcf","date":"2023-09-01T12:15:40+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-08-29T09:17:09+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-08-28T14:08:12+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-08-24T06:21:07+00:00","index":"","fulltext":""},{"type":"submitted","content":"Archaeological and Anthropological Sciences","date":"2023-08-21T13:37:18+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"archaeological-and-anthropological-sciences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aasc","sideBox":"Learn more about [Archaeological and Anthropological Sciences](http://link.springer.com/journal/12517)","snPcode":"12520","submissionUrl":"https://submission.nature.com/new-submission/12520/3","title":"Archaeological and Anthropological Sciences","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"8de23b6e-18f9-4607-a995-be7cfdb27662","owner":[],"postedDate":"August 28th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-11-27T15:03:08+00:00","versionOfRecord":{"articleIdentity":"rs-3282701","link":"https://doi.org/10.1007/s12520-023-01900-7","journal":{"identity":"archaeological-and-anthropological-sciences","isVorOnly":false,"title":"Archaeological and Anthropological Sciences"},"publishedOn":"2023-11-22 15:00:58","publishedOnDateReadable":"November 22nd, 2023"},"versionCreatedAt":"2023-08-28 20:07:23","video":"","vorDoi":"10.1007/s12520-023-01900-7","vorDoiUrl":"https://doi.org/10.1007/s12520-023-01900-7","workflowStages":[]},"version":"v1","identity":"rs-3282701","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3282701","identity":"rs-3282701","version":["v1"]},"buildId":"J0_U0BvcaRcwD8yVFaRlm","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}