Spatial patterns of anthropometric variation in India with reference to geographic, climatic, ethnic and linguistic backgrounds

被引:12
作者
Bharati, S
Demarchi, DA
Mukherji, D
Vasulu, TS
Bharati, P
机构
[1] Indian Stat Inst, Biol Anthropol Unit, Kolkata 700108, India
[2] Univ Nacl Cordoba, Museo Antropol FFyH, RA-5000 Cordoba, Argentina
[3] Inst Ecol & Dev Studies, Howrah, India
关键词
spatial; autocorrelation; geographical climes; caste hierarchy; population structure;
D O I
10.1080/03014460500097443
中图分类号
Q98 [人类学];
学科分类号
030303 ;
摘要
Background: Anthropometric variation can be fruitfully utilized to investigate microevolutionary processes. Anthropometric variations in the Indian subcontinent based on stature and three indices ( Cephalic Index, Nasal Index, and Total Facial Index) are highly variable and discriminative among populations across geographical regions. Aims: Anthropometric variation in stature, Cephalic Index (CI), Nasal Index ( NI) and Total Facial Index (TFI) were investigated with respect to ethnic, linguistic, geographical and climatic affiliation, across the Indian subcontinent. Subjects and methods: Published data on anthropometric variations of 531 populations from the Indian subcontinent were analysed using discriminant analysis and spatial autocorrelation analysis. Results: Discriminant analysis of the four anthropometric variables shows that stature and NI are good discriminators for populations of different languages. Stature, NI and CI discriminate well among populations of diverse ethnic origin and climatic conditions in different regions. TFI is not a good discriminator for populations of diverse ethnic, linguistic and climatic attributes. Spatial autocorrelation analysis showed significant departure from randomness, suggesting geographic structuring. The Moran's I estimate is positive and statistically significant for the four variables at low distances but exhibits significant negative association at higher values. Conclusion: The results suggest geographical clines for the four anthropometric variables and indicate the influence of population structure on the studied variables.
引用
收藏
页码:407 / 444
页数:38
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