Finger ridge-count variation among various Subsaharan African groups

AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 57:311-321(1982)

Finger Ridge-Count Variation Among Various Subsaharan African Groups

R.L. JANTZ, C.H. HAWKINSON, H. BREHME, AND H.W. HITZEROTH Department of Anthropology, University of Tennessee, Knoxville, Tennessee 37996 (RLJ., CJIH.); Institute of Human Genetics and Anthropology, University of Freiburg, 7800 Freiburg, West Germany ( H B J ; and Africa Institute of South Africa, P.O. Box 630, Pretoria, South Africa (H.W.H.)

KEY WORDS components

Dermatoglyphics, Ridge counts, Africa, Principal

ABSTRACT This paper addresses the question of the extent to which finger ridge-count data are useful features with which to study population variation in Subsaharan Africa. Each subject was represented by a vector of 20 ridge-counts, a radial and an ulnar count for each digit. Such data were available from 11 African groups, nine of which were indigenous Africans, and two, the South African Colored and South African Indians, contained a portion of non-African ancestory. The ridge-counts were first transformed to principal component scores and these were subjected to multivariate analysis of variance and distance analysis to elucidate intergroup variation. The primary findings were that ridge- counts provide a good reflection of variation on a t least two levels, that of African versus non-African, and variation among Africans. Also, the principal components that reveal variation at these two levels are very different. We conclude that ridge-counts can only be useful in population studies if full account is taken of their multicomponent nature.

If dermatoglyphics are to achieve their proper position in population studies, there must be a much greater appreciation of the nature and meaning of population variation than generally exists at the moment. That such an appreciation does not exist is partly methodological and is rooted in the historic emphasis on highly polygenic summary features such as total finger ridge-count, absolute ridge-count or, overall frequency of arch-loop- whorl patterns. The tendency to ignore certain aspects of variation persists, many reports con- tinuing to provide only the summary features and to base analyses upon them. Use of such summary features necessarily involves the as- sumption that they reflect the primary axes of human variation, which may not be war- ranted.

To date dermatoglyphics has a rather dismal record in providing insight into genetic variation between populations on the microevo- lutionary level. In nearly all instances where dermatoglyphics have been included with other biological data, such as anthropometrics

or sero-genetic data, they produce a different picture of interpopulation relationships, one which is not readily interpretable in terms of known or inferred historical relationships between groups (Nee1 et al., 1974; Friedlander, 1975; Chai, 1972; Rothhammer et al., 1979). The last authors reach the conclusion, using South American data, that dermatoglyphics do not accurately reflect genetic relationships at the tribal level and do not become useful until one wishes to ascertain relationships between geographical races. However, Froehlich and Giles (1981) obtained clear-cut intergroup differences among New Guinea populations and argue that finger prints may offer insights into population history unobtainable with serological or metrical traits. One suspects that methodology may have a great deal to do with the nature of the results obtained from an analysis (e.g., Jantz, 1974; Jantz and Hawkinson, 1980, and for an up-to-date review of the whole issue, Meier, 1980).

Received March 26, 1981; accepted November 9, 1981

0002-948318215703-031 1$03.50 0 1982 ALAN R. LISS. INC.

312 R.L. JANTZ, C.H. HAWKINSON. H. BREHME, AND H.W. HITZEROTH

It has recently been argued that finger ridge- counts should be analyzed by retaining both the radial and ulnar counts for each digit. Sev- eral analyses of structure using principal components support this notion (Roberts and Coope, 1975; Roberts, 1979; Jantz and Owsley, 1977; Reed et al., 1978). Jantz and Hawkinson (1980) applied the radial-ulnar concept to White-Black comparisons using principal component scores to obtain a numerical rep- resentation of the component structure. They showed that considerable additional information resulted from this approach.

The purpose of this paper is to extend this approach to the extensive data now available from African samples. These data permit us to examine the all important question of differentiation within a geographical area where traditional approaches have often failed to produce meaningful results. We are also able to examine relationships of genetically distinct groups living in South Africa to Black Afri- cans, providing relative environmental ho- mogeneity against which to assess the presumed genetic variation in ridge-counts.

MATERIALS AND METHODS

The samples and sample sizes are shown in Table 1. The dermatoglyphics of all the African groups except the South African Colored have been previously described, the four Angolan by Brehme (1972a,b), the four South African groups by Brehme and Hitzeroth (1979), the Yoruba by Jantz and Brehme (19781, and the South African Indians by Hitzeroth and Brehme (1974). Linguistically, all of the Black African samples represent groups belonging to the Niger-Congo family; the Yoruba belonging to the Kwa subfamily and the remaining eight Bantu-speaking groups belonging to the Benue-Congo subfamily (Greenberg, 1970). Of the South African Bantu groups, the Tswana and Pedi speak a Sotho language, the Shan- gana belong to the Tsonga-speakers, while the Venda speak a language of their own, associ- ating them with the Shona of Zimbabwe (cf. Brehme and Hitzeroth, 1979). In Angola the Chokwe and Luimba belong to the Lunda cluster of languages, the Bieno to Ovimbundu and Ginga to Kimbundu (Rosing, 1977).

The South African Indians represent des- cendents of immigrants coming to South Africa in the latter part of the 19th century. Most of these immigrants remained in Natal where they had disembarked, but certain groups moved on to other provinces. The present sample represents Indians who began coming to

TABLE 1 . Groups, sample sues, and locations ofthe samples employed in the analysis

Sample Males Females Location

Tawana Shangana Pedi Venda YoNba Ginga Chokwe Luimba Bieno South African Colored South African Indiana Germans

92 87 92 80 85 92 66 66 120 55 94 94 89 90 86 75 74 90 94 90 103 103 154 151

South Africa South Africa South Africa South Africa Nigeria Angola Angola Angola Angola South Africa South Africa SW Germany

the Transvaal around 1880, the 1970 population numbers about 81,000 (Hitzeroth and Brehme, 1974). Originally, the immigrants were drawn from three areas in India; south- eastern (Madras), eastern (Calcutta), and northwestern (Bombay) (Hitzeroth and Brehme, 1975). Specific ethnic affinities in South Africa are no longer identifiable. In ad- dition to the original ethnic heterogenity, South African Indians have also undergone a certain degree of admixture with local populations, principally Negroes. This admixture resulted from an excess of males among the early migrants (Hitzeroth and Brehme, 1974). The extent of the admixture is unknown; Jen- kins et al. (1970) estimated Negro admixture in Natal Indians, using Gm makers, at only 1%. The Transvaal Indians however, display dermatoglyphic differences when compared to those of Natal (Hitzeroth and Brehme, 19751, and this difference may be due to a larger Ne- gro component.

The South African Colored are composed of at least four elements: European, Khoisan, Asian, and Black African. There have been various attempts to estimate parental contri- butions to the Colored population. Jenkins et al. (1970) estimated the composition of the Jo- hannesburg Coloreds, using Gm markers, as follows: 50% European, 36% Khoisan, with the remainder presumably consisting of Asian. Other lines of evidence have produced somewhat different results, particularly regarding the European component. Using geneologies Heese (1971) estimated the composition as about one-third indigenous South African (i.e., Negro and Khoisan), one-third European, and one-third Asian, and Botha (1972) using ABO and Rh blood groups estimated the same components as 36%, 34%, and 30%, respectively.

AFRICAN FINGER RIDGE-COUNTS 313

The Coloreds of Pretoria lived for a time in close proximity to Negroes, Indians, and Chinese, but many have moved to the more or less closed residential area of Eersterust. The present sample consists of school children from this community. A report detailing the dermatoglyphic features of this sample is in prep- aration.

The German sample represents the parents of a large family series assembled by Brehme. They are from Freiburg and surrounding lo- calities.

All ridge-counts were carried out by a single

investigator (H. Brehme) using standard methods (Brodhage and Wendt, 1951; Cum- mins and Midlo, 1961).

Our statistical methods have been outlined with justification in Jantz and Hawkinson (1980) so we provide only a brief summary here (see also Roberts and Coope, 1975). First, a covariance matrix is obtained for each group by sex. These are then pooled to yield a within- groups covariance matrix, which is converted to a correlation matrix. The Germans were not included in the correlation matrix. The within- groups correlation matrix, which contains

TABLE 2. Mean radial and ulnar ridge-counts for each of the African samples and the within-groups standard deviations

V IV 111 I1 I

R U R U R U R U R U

Tswana (MI

Tswana (F)

Shangana (M)

Shangana (F)

Pedi (MI

Pedi (F)

Venda (MI

Venda (F)

Yoruba (M)

Yoruba (F)

Ginga (M)

Ginga (F)

Chokwe (M)

Chokwe (F)

Luimbe (MI

Luimbe (F)

Bieno (M)

Bieno (F)

Indians (M)

Indiana (F)

Colored (MI

Colored (F)

S.D.

L R L R L R L R L R L R L R L R L R L R L R L R L R L R L R L R L R L R L R L R L R L R L R

12.02 12.28 9.63

10.26 12.21 12.16 10.81 11.43 12.19 12.73 11.20 11.17 13.76 13.47 11.73 12.09 13.43 13.73 11.84 12.05 12.38 12.66 11.70 12.14 13.58 13.57 11.91 12.79 12.98 13.56 12.16 12.11 12.53 13.12 11.50 12.70 14.05 14.19 13.76 13.40 14.25 14.43 11.58 12.42 4.82 4.93

0.78 1.39 0.90 0.63 0.98 0.96 0.68 0.66 1.34 0.91 1.03 0.49 0.27 0.86 0.74 0.47 0.93 0.88 1.00 0.67 1.29 1.49 0.95 0.66 1.25 1.49 1.48 1.16 1.53 1.59 0.93 0.51 1.55 1.23 0.80 0.84 1.74 1.46 1.71 1.17 1.71 1.91 0.65 0.65 3.27 3.08

15.28 15.48 11.74 13.06 13.32 13.62 13.50 13.87 14.27 14.72 13.08 13.36 16.33 17.02 14.39 15.18 15.35 15.74 14.00 15.20 14.81 14.53 14.62 15.57 15.38 15.55 14.83 15.69 14.52 15.24 14.56 15.45 14.41 15.92 13.24 15.18 16.65 16.24 16.33 16.84 16.39 16.62 15.22 15.32 5.96 5.86

4.95 5.60 4.15 3.85 3.76 4.78 3.69 3.42 4.55 4.23 3.41 3.80 5.20 7.38 3.67 3.62 5.07 6.32 3.20 3.80 4.31 5.49 3.72 4.09 5.08 4.55 4.38 3.50 4.26 5.50 5.31 4.41 4.87 6.18 2.91 2.35 6.54 8.35 8.00 8.56 5.66 6.34 5.33 4.79 6.78 6.72

12.55 12.53 9.71

10.06 9.61 9.86

10.14 10.66 11.05 10.96 9.45

10.17 13.58 12.44 9.82

10.56 11.40 10.61 10.49 10.15 11.91 11.22 11.00 11.45 11.96 11.66 11.58 11.93 11.57 11.38 11.63 11.65 12.46 11.89 10.36 10.60 14.02 13.45 12.92 13.37 12.71 13.04 11.27 12.10 5.75 5.16

3.79 3.91 2.60 1.70 2.62 2.76 2.13 1.28 2.81 1.81 2.70 1.55 5.21 4.91 2.76 1.39 4.13 3.63 3.11 2.62 2.83 2.77 2.64 2.06 3.34 2.69 2.77 1.33 2.30 1.81 2.65 1.91 2.97 3.31 1.86 0.96 4.53 3.93 3.28 3.04 4.17 3.84 3.98 2.38 6.41 5.78

9.27 9.11 7.89 8.90 8.30 8.91 7.88 9.67 8.94 9.81 7.82 8.70

11.71 10.85 7.83 9.26 8.51 8.74 7.84 8.31 8.36 9.07 8.64 9.79 9.36 9.52 9.09 9.44 9.13 9.19 8.45 9.64 9.04 9.88 6.99 8.94

10.39 11.64 9.50

10.87 9.80

10.37 8.32

10.04 6.08 5.89

5.65 6.71 2.64 3.67 5.86 6.32 5.96 4.69 4.16 4.14 4.34 3.92 8.17 8.55 5.70 4.09 5.76 6.28 5.58 5.82 4.37 5.44 4.37 3.93 5.10 4.60 3.68 2.89 4.52 4.55 5.75 4.16 4.96 4.73 4.58 3.28 7.09 7.89 7.31 6.50 7.69 7.45 7.19 5.59 7.28 7.20

12.96 14.37 10.11 11.90 11.72 12.58 10.84 12.81 13.62 16.06 11.08 12.63 15.11 15.82 11.77 13.35 12.75 15.00 10.24 11.71 13.35 15.00 13.19 14.18 15.27 16.42 12.93 14.34 14.37 15.47 11.89 12.99 14.00 14.92 12.48 13.90 17.15 18.90 14.36 16.97 16.75 18.88 13.66 16.00 6.84 6.79

6.02 7.48 5.23 4.13 6.52 6.77 6.07 4.69 6.19 6.67 7.00 6.32 6.61 7.56 6.09 5.97 6.92 8.00 5.11 4.89 5.72 7.15 7.54 7.87 8.26 9.62 6.47 7.61 6.87 7.03 8.67 7.48 8.09 8.65 7.30 7.36 5.59 7.62 6.40 6.36 6.43 7.38 6.49 5.32 8.27 8.39

314 R.L. JANTZ. C.H. HAWKINSON. H. BREHME, AND H.W. HITZEROTH

1851 degrees of freedom, is submitted to the PA1 option of the SPSS subroutine FACTOR and all 20 latent roots and vectors obtained. FACTOR also produces a factor score coefficient matrix to obtain principal component scores. Before obtaining principal component scores, the raw data matrix is converted to Z scores, centered on the grand mean and standardized by the within-groups standard deviation. The result- ing principal component scores are standard scores with a grand mean of zero and unit variance.

Eigenvalues were tested for significance using Bartlett's criterion (Lawley and Maxwell, 1963). This is a test of the hypothesis that eigenvalues remaining after removal of the first k are equal. If the hypothesis is accepted and the m-k eigenvalues are considered equal, no further variance maximizing rotation is re- quired.

The principal component scores can then be used as variables for further analysis. We used the following procedures to elucidate the nature of intergroup variation: Two-way multivariate analysis of variance (MANOVA) was carried out by means of the GLM procedure in the SAS package, using sex and group as treatments. Although we are primarily interested in group variation, it is important to evaluate the magnitude of sex variation. MANOVA per- mits the simultaneous evaluation of the two effects, as well as their interaction. The pro- gram also gives the ANOVA results for each of the individual components.

Since the principal components are orthogonal variables with unit variance, pairwise Mahalanobis D2 can be calculated as the sum of the squared differences of principal component means between each pair of groups. It was at this stage that the Germans were introduced to provide an additional comparative dimen- sion. This was accomplished by first getting their principal component scores using the score coefficients from the within-groups analysis, and then getting their D2 values from the other 11 samples. The distances were displayed on orthogonal axes as described by Gower (1972).

Group means and within-group standard deviations for the 20 variables are given in Table 2.

Principal components Table 3 gives the eigenvalues of the within-

groups correlation matrix, the percent of variation accounted for, and the Bartlett's x2 value after removing the first k eigenvalues. Table

TABLE 3. Eigenualues of within-groups correlation matrir, proportion of uariance accounted for, and x2 test of

significance ___ ~ ~

x2 after l k hk hk/20 removing X I - k D.F.

1 8.93 2 1.90 3 1.49 4 1.24 5 0.96 6 0.75 7 0.63 8 0.56 9 0.53

10 0.45 11 0.42 12 0.34 13 0.31 14 0.26 15 0.26 16 0.23 17 0.22 18 0.19 19 0.17 20 0.15

,447 ,095 ,075 .062 .048 ,038 ,031 ,028 ,026 ,022 ,021 ,017 ,015 ,013 ,013 ,012 ,011 ,010 ,008 ,008

9997.57* 7688.64' 5882.83* 4316.01* 3222.38* 2515.93* 2018.23* 1579.76* 1135.11* 830.60' 525.66' 375.45* 255.99' 202.36*

77.42* 75.81* 23.93%

5.27 - -

189 170 152 135 119 104 90 77 65 54 44 35 27 20 14 9 5 2

*p < ,001

3 shows that after removing 18 eigenvalues it is no longer possible to achieve a variance maximizing rotation; therefore, the first 18 eigenvalues may be considered significant. Lawley and Maxwell (1963) point out that the X2 distribution is only approximate when the correlation matrix rather than the covariance matrix is used. However, even the X2 with 17 eigenvalues removed is highly significant, so it is reasonable to accept all 18 eigenvalues as reliably estimated. Later eigenvalues account for a very small proportion of the variance and therefore cannot express much meaningful information. Since the correlation matrix is not singular we examine all 20 components in the analysis of variance which follows, and include all of them in the distance computations.

Loadings for the first 10 principal components are shown in Table 4. The first five or six components may be given morphological interpretations similar to those described in Roberts and Coope (1975) and Jantz and Hawkinson (19801, and even components after six are interpretable to some extent. Morphol- ogical interpretations of the components will be referred to as needed later in the paper.

MANOVA-Full model We used group, sex, and group-sex inter-

action as treatments for the multivariate analysis of the component scores. The SAS GLM


TABLE 4 . Loadings of the first ten principal components

Digit 1 2 3 4 5 6 7 8 9 10

-0.19 -0.04 -0.17 0.42 0.10 0.00 -0.02 0.21 -0.16 0.45 0.43 0.34 0.24 0.18 0.27 -0.20 -0.00 0.18

-0.23 0.02 -0.27 0.16 -0.04 -0.11 -0.02 -0.14 0.15 0.36 0.25 0.04 -0.04 -0.16 -0.29 -0.32 -0.07 -0.17

0.79 -0.25 0.19 -0.14 -0.16 -0.11 0.05 0.07 -0.13 0.19 L3 ; 0.65 0.45 -0.08 -0.14 -0.22 -0.03 -0.04 -0.09 0.35 0.16

-0.21 0.31 0.05 -0.18 -0.19 0.14 0.33 0.06 -0.19 0.26 -0.37 -0.23 -0.19 0.15 0.30 -0.26 -0.15 -0.14

-0.32 -0.15 0.41 -0.19 0.35 -0.13 -0.04 0.04 0.01 0.09 -0.47 0.39 0.17 -0.37 0.06 -0.10 0.02 0.07

-0.21 -0.06 -0.18 0.43 0.12 0.02 -0.00 0.20 -0.13 0.48 0.34 0.28 0.25 0.20 0.07 0.30 -0.16 -0.01

-0.26 0.01 -0.25 0.21 0.01 -0.06 -0.05 -0.10 0.18 R4 ; 8:;; 0.31 0.19 -0.01 -0.06 -0.08 -0.40 0.03 -0.16 -0.20

-0.28 0.24 -0.08 -0.17 -0.05 0.07 -0.06 -0.14 0.20 0.46 -0.12 -0.19 -0.20 0.07 -0.12 0.25 0.28 0.16

-0.24 0.35 0.14 -0.22 -0.22 0.28 -0.11 0.20 -0.17 0.25 -0.36 -0.26 -0.14 0.18 0.21 0.15 -0.22 -0.14

-0.38 -0.15 0.44 -0.20 0.34 -0.14 -0.03 0.02 -0.01 0.07 -0.48 0.35 0.15 -0.31 0.02 0.17 -0.08 0.04

L4 ; 8:;;

L2 ; ;:;; L1 ; g; R5 ; 8::;

R3 8::; R2 8:;; R1 ; 8::;

procedure gives MANOVA results for each variable, and a type I and type IV sum of squares (SS) for each treatment. The former SS represents the sequential decomposition of the model SS, the latter the SS for each effect conditioned on the others. In unbalanced de- signs the two may differ, markedly if the de- sign is highly unbalanced. Our data are ap- proximately balanced and the two types of SS are very similar; in no case is there disagree- ment between them as to the level of significance of a treatment. We therefore use the type I SS for tests of significance and for additional analysis later in the paper.

Table 5 gives the analysis of variance results for each of the 20 component scores. Ten of them exhibit variation significant at 5% or less; three (Nos. 4, 18, 19) show only group effects, one (No. 17) shows sex alone, one group and group-sex interaction (No. 5), one (No. 6) sex, group, and sex-group interaction, and the remainder (Nos. 1, 7, 8, 10, 13) both sex and group effects. The overall multivariate tests were carried out by the F conversion of Wilks' lambda. Significant group effects (F = 2.56,P < 0.0001) and sex (F = 7.78; P < 0.0001) effects were found, but the overall interaction is not significant (F = 0.97; P 0.60). The two components which show a significant interaction are only marginally sigificant at 5%, and out of 20 tests we would expect one by chance. We can therefore reject the hypothesis of sex-group interaction.

The most interesting observation we can

TABLE 5. Analysis of variance of the 20 principal components scores using sex, group, and sex-group

interaction as treatments

Component Overall F Treatment

2 3 4 5 6 7 8 9

10 11 12 13

1.46 ns 1.38 ns 2.65*** G*** 3.32*** G***, I* 5.92*** , , S*** G*** I* 2.18** s** G** 3.08*** S***, G** 1.20 ns 2.95*** 0.96 ns 0.52 ns 1.84**

14 1.0 ns 15 1.03 ns 16 1.42 ns 17 1.69' S*** 18 1.86** G*** 19 1.76** G** 20 1.34 ns

S = sex; G = group; I = sex-group interaction. *p < .05; **p < .01; ***p < ,001; ns, nonsignificant.

make concerning these results is that significant intergroup variation exists over the whole range of components, even though the later ones are associated with very small eigenvalues. Even components 17, 18 and 19, which collectively account for 2.9% of the variation, exhibit significant sex or intergroup variation. It would therefore appear unwise to limit the

316 R.L. JANTZ, C.H. HAWKINSON, H. BREHME, AND H.W. HITZEROTH

* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * + ~ - - 4 m w ~ o - 4 ~ - w w m ~ ~ z z ~ z z z ~ ~ ~

* * * * * * * I * * * * * * * I * * F * * * * * * * * * * m c - a w t - m w w ~ m w 23f?Yz!rS 2:

* * * * * * * * * * 4 - m ~ w r n - 4 - w ~ 'YTY 4?'y?9?'E- 3 0 0 0 0000-04

number of components to those with eigenvalues greater than some specified value, unless one is primarily interested in structural inter- pretation of the components.

Distance analysis In this part of the analysis we include the

sample of Germans to provide a genetically distinct group living in a different environ- ment. Mahalanobis distances (D2) were calculated from the component score means and are shown in Table 6, males in the lower di- agonal, females in the upper. The distances between South African Colored-South African Indian groups and the Black Africans are greater than those between individual Black African groups and are for the most part sta- tistically significant. There does not appear any tendency for the South African Colored- South African Indian distances to be smaller for the South African Bantu speakers, the An- golan Bantu speakers, or the Yoruba.

A better impression of the main relationships can be obtained by scaling the distances onto orthogonal axes, or principal coordinates (Gower, 1972). The 12 groups are shown plot- ted by sex on the first two principal coordinates in Figure 1. The first axis accounts for 27.7 and 33.7% of intergroup variation in males and females, respectively, and the corresponding values for the second axis are 23.9 and 20.5%. Clearly the first axis serves to separate the Black Africans from S.A. Colored, S.A. Indi- ans, and Germans, the picture being approxi- mately the same in both sexes. The most not- able feature of the three last mentioned groups is that the Colored group does not exhibit any close relationship with the Black Africans, and indeed in females is farther removed from the general cluster of Black Africans than even the Germans.

The second axis separates Black African groups from one another. There is a tendency, most pronounced in females, for the Angolan and South African Blacks to form geographic clusters. In both sexes the Yoruba are not differentiated, and appear to show a preference for the South Africans.

Variation among Black Africans The ANOVA results previously given refer

to heterogeneity among all 11 groups, and the D2 results present pairwise distances utilizing all components. Deeper insight into intergroup variation can be gained by determining whether variation among Black Africans cor-

AFRICAN FINGER RIDGE-COUNTS

0 -

1 -

-2

-3

*Ormpll

- -

*SA I d m .Gw

Rdi . .l"*

1 1 1 1 1 1 1 1 1 1 1 1 1 1 ~ l 1

4 - 8 - 7 d - S + - 3 - 2 - 1 0 1 2 3 4 s a

I

-5 -4 i .€kkrl

L ~ " ~ ' " ' ' ~ " ' ' f ~ 4 -8 -7 -8 -5 -4 -3 -2 -1 0 I 1 3 4 5 8

317

Fig. 1. Mahalanobis distances shown on the first two principal coordinates. The first two axes account for 51.6 and 54.2% of the intergroup variation.

318 R.L. JANTZ, C.H. HAWKINSON. H. BREHME. AND H.W. HITZEROTH

TABLE 7 . Group sums of squares for all eleven African groups and for nine Black African groups only

All groups Black Africans only

Component GroupSS F GroupSS F ~

1 57.87 2 21.62 3 16.15 4 42.98 5 49.11 6 66.54 7 26.41 8 22.83 9 14.36

10 46.67 11 10.42 12 7.86 13 22.53 14 12.56 15 13.86 16 17.15 17 13.75 18 30.88 19 23.63 20 10.85

5.79** 2.16* 1.61 4.30** 4.91** 6.65** 2.64** 2.28' 1.44 4.67** 1.04 0.79 2.25* 1.26 1.39 1.72 1.38 3.09** 2.36** 1.08

14.55 18.16 8.26

41.25 32.67

4.65 13.07 7.43 7.90

35.18 5.12 6.12 9.35

10.49 12.70 16.80 7.17

22.74 15.61 6.23

1.82 2.27* 1.03 5.16** 4.08** 0.58 1.63 0.93 0.99 4.40** 0.64 0.76 1.17 1.31 1.59 2.10* 0.90 2.84** 1.95* 0.78

*P < .05; **P < .01

responds to that between S.A. Colored or S.A. Indians and the Black Africans. This can readily be seen by taking the group SS when all 11 groups are included and removing that portion due to S.A. Colored and S.A. Indians. The remainder will represent variation among Black African groups only.

Table 7 shows the group SS and associated F ratio for all 11 groups and then for Black Africans only. The first column of Table 6 shows that components 6 and 1 have the highest SS, followed by 5, 10 and 4, respectively. After removing the SS due to S.A. Colored and S.A. Indian, components 1 and 6 are markedly reduced while 4, 5, and 10 are only minimally effected. It is evident from these results that S.A. Colored and S.A. Indians differ from Black Africans primarily along components 1 and 6, while Black Africans differ from each other along components 4, 5 and 10.

Component 2, it should be noted, is significant in Table 7, but not in Table 5 , where both group and sex effects were considered. Nearly all of the SS is due to group, so when group is considered alone, component two becomes significant. As an intergroup discriminator it re- mains comparatively unimportant.

DISCUSSION

To the extent that the components can be interpreted in terms of the original variables, it is possible to state more explicitly the nature

of intergroup variation. Component 1 is general size and correlates well with absolute ridge-count, as has been previously empha- sized by Roberts and Coope (1975). S.A. Col- ored and S.A. Indians differ from African Blacks in having significantly larger ridge- counts, but African Blacks do not differ among themselves in overall size. The importance of this finding scarcely requires additional emphasis; it has been accepted as an article of faith that summary features, such as absolute and total ridge-counts, represent the important axes of intergroup variation. Yet we see that the size component is important in the present context only in differentiating groups of African descent from those whose ancestory is non-African, or contains a substantial component thereof.

Component 6, which involves radial-ulnar finger contrasts on the radial side of the hand, i.e., thumb and forefinger, is also seen to be of little consequence for discerning variation among Black Africans. The results shown here provide strong confirmation of the findings of Jantz and Hawkinson (19801, who found that component 6 was the primary source of variation between American White and African and American Blacks.

Component 4 is a thumb component, but with some involvement of the radial count of digit V as well. Component 5 takes the form of a radial count gradient across the hand, starting with strong positive loadings on digit V and ending in negative loadings on the thumb. On Component 10 the highest loadings are found on the central counts, i.e., from radial IV to ulnar 11, and involve negative loadings on ulnar IV, and radial I1 and ulnar 11, and positive loadings on radial IV and radial and ulnar 111. Therefore, this component may be taken as a whole finger contrast between digits I1 and 111, since radial and ulnar counts of each have the loadings in the same direction, and at the same time a radial ulnar contrast on digit IV.

The variation among Black African populations is therefore seen to involve various in- teractions between digits, although it is not the simple 11, I11 versus IV, V contrast (found by Jantz and Hawkinson, 1979), using the larger of two counts per digit. It is interesting to inquire whether by using only the three best components, we can obtain a better resolution of the groups. Figure 2 shows the nine Black African groups clustered using components 4, 5 and 10. Clustering was done by means of the SAS subroutine CLUSTER. Females present a


Females

Tswana

I------ Shangana

Venda

Pedi

L Yoruba

Ginga

Chokwe

Bieno

1 I Luimbe

Males

P- Venda

i Shangana Lr-

I Y o r u b a

f- Ginga Pedi

i 1 rChokwe

I Bieno

Fig. 2. Cluster diagram of intergroup relationships of Black Africans, using the three principal components showing the greatest heterogeneity among groups.

satisfying picture in terms of geography, South African tribes forming a unified cluster, so do the Angolans, with the Yoruba separate but joining with the South Africa cluster. Males are similar, although the Pedi cluster with the Angolans and the Yoruba fall in with the South Africa groups.

It is evident that finger ridge-counts are capable of organizing the ll African groups on two and possibly three levels of genetic relationships. On the highest level, those groups with substantial non-African ancestory are clearly differentiated from indigenous African groups. The Colored group presents a problem in that they are somewhat closer to the Ger- mans than we might expect on the basis of their presumed genetic composition. Their similarity to the Germans (who might be taken as an approximation of the Dutch ancestory in the Colored) might mean that this sample is predominately of European origin, or it could indicate dominance in the genes responsible for ridge-count variation, as has previously been suggested (Singh, 1979; Spence et al., 1977). This problem cannot be resolved until data from groups approximating the ancestory of the Coloreds become available.

The second level of genetic variation per- tains to relationships between different Black African groups. Here it is historically reasonable to postulate that the South African Bantu speakers would be differentiated from those in Angola, and the Yoruba should be rather distinct from both Bantu speaking groups. It is well known that the major Bantu speaking groups of Southern African came into close contact with the Khoisan people (Hitzeroth, 1972) and the degree of admixture has been estimated (Jenkins et al., 1970). Using Khoisan marker Gm’313, the degree of admixture has been estimated between 15 and 38%, for the groups considered here. Gm’.13 is vir- tually absent from the Bantu groups in Angola (Jenkins et al., 1970).

Distances derived from the finger ridge- count data do, in general, differentiate the South African and Angolan Bantu speakers. The Yoruba, however, are consistently placed with the South African Bantu speakers (see Figs. 1 and 2). That it occurs in both sexes may be taken as evidence of a biological reality.

While the relationship of the Yoruba to the South African Bantu speakers was a t first un- expected, at least on geographical grounds, it

320 R.L. JANTZ, C.H. HAWKINSON, H. BREHME, AND H.W. HITZEROTH

is not inconsistent with other lines of evidence. Ojikutu et al. (1977) reported a frequency of the acid phosphatase allele p’ in the Yoruba similar to that found in Bantu speaking populations of Southern Africa. The p’ allele has always been considered a Khoisan marker, and its presence in Southern African Bantu speakers has been attributed to admixture with Khoisan populations. Finding it in the Yoruba makes it plausible to suggest common ancestory for its occurrence in West Central and Southern Africa. Ojikutu et al. (1977) conclude their analysis as follows: “It would therefore appear that some at least of the Negro peoples of Southern Africa are likely to have diverged from a common stock with the Yoruba comparatively recently, and that though some of the differences are almost certainly due to Khoisan admixture in the more southerly peoples, the majority could as well be due to the operation of random genetic drift.“ Our dermatoglyphic results are consistent with this conclusion.

Among similar lines, De Villiers (1968) observed that the Ibo (also Kwa speakers) were craniometrically closer to South African Ne- groes than any of a wide variety of other Af- rican groups. It is not unreasonable, therefore, to draw the preliminary conclusion that a t least some Southern African Bantu speakers share a recent common ancestory with some of the West Central African populations, with serological, dermatoglyphic, and craniometric corroboration on this point. Linguistically, Greenberg (1970) notes that there may be in- adequate justification for separating the two groups into subfamilies.

A third level of variation concerns the relationships among groups within South Africa and within Angola. The intra-Angolan distances are all nonsignificant, so we obviously cannot attach a great deal of meaning to them. Baing’s (1977) anthropometric study of An- golan groups, which included the four samples used here, showed the Bieno and Luimbe to be especially close, but the other groups were about equidistant from one another. There is no evidence for the close Bieno-Luimbe relationship in either Figures 1 and 2 or Table 4, nor for any other systematic relationship that might be meaningful.

The intra-South African distances are also nonsignificant for females, but the males display a reasonable level of differentiation. The most prominent feature to be noted from Fig- ure 1 and Table 6, but not Figure 2, is the differentiation of the Venda. Hitzeroth (1981)

and Hitzeroth et al. (1981) have observed a similar differentiation of the Venda using red cell enzyme data, as has Rightmire (1976) using craniometry. The red cell enzyme data also showed a consistent tendency for the Shangana to separate from the Tswana and Pedi, a tendency not observable in the dermatoglyphic results. Any conclusions concerning similari- ties between sero-genetic and dermatoglyphic distances are clearly premature, but there appear to be grounds for optimism that dermatoglyphic data may be capable of reflecting biological variation on a local level.

Our findings show that finger dermatoglyphics, once their multicomponent nature is rec- ognized, are capable of producing interpretable results a t the tribal level, as well as on the level of geographic races. Our results further show that summary features, represented in the present instance by an overall size component, are nearly useless for inferring relationships on the tribal level. Even representing individuals as ten ridge-counts, omitting the smaller, is likely to result in considerable information loss. It is evident that nearly all the components involve radial-ulnar contrasts of some sort, and this information is disregarded in the traditional approach. It is likely that De Villiers’ (1980) failure to find significant in- tertribal variation among 16 Southern Africa population results from using the larger count only. We are therefore unable to agree with her conclusions that “in the context of population studies, especially in the search for tribal origins, dermatoglyphic studies would appear to have limited application.” On the contrary, in the present context, finger ridge- counts appear to hold considerable promise. However, it is absolutely necessary, if one is to extract useful information from dermatoglyphics, to take full cognizance of the variety of directions the variation may take in mul- tidimensional space.

ACKNOWLEDGMENTS

The authors acknowledge the use of The University of Tennessee Computing Center, Knoxville, in obtaining the results shown here.

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Finger ridge-count variation among various Subsaharan African groups