into that knowledge to come up with some disaggregated patterns that more fully describe and explain the high levels of mortality of tribal children.

The analysis undertaken for this paper is part of an ongoing program<sup>3</sup> that looks at social exclusion and the differential outcomes for excluded groups like Dalit and Adivasis along a range of development parameters. The characteristics of Scheduled Tribes and Scheduled Castes and manner in which exclusion manifests itself is discussed in greater detail in the reports from that program. In this paper we disaggregate tribal child mortality patterns to build on the robust understanding that tribals do worse than others.

Tribal groups have historically had more equal gender relations and women’s status in tribal societies has been higher. This has manifested itself in later than average age at marriage, higher participation of women in the labor force and lower restrictions on the mobility of women (see Das and Desai, 2003). Until the late 20<sup>th</sup> century, child mortality and fertility rates for tribals were lower than those for non-tribals (Maharatna, 1998). Dreze and Gazdar (1997) and Maharatna (1998; 2000) however point to a disturbing trend in tribal societies – that gender equality and their lower fertility and mortality patterns seem to be gradually eroding, as they get more integrated into non-tribal society and as their traditionally sustainable livelihoods are encroached upon. Migration of tribals is also seen to be associated with wearing down their sustainable lifestyles (see for instance Maharatna on Santhal fertility, 2005). This is consistent with findings from other countries on the experience of indigenous populations. In their examination of health of Mexican immigrants in the USA, James (1993) and Vega and Amaro (1994) find a similar pattern of ‘acculturation’ resulting in behaviors or lifestyles that adversely impact health (e.g. decreased fiber consumption, decreased breast feeding, increased use of cigarettes and alcohol especially by young women).

Tribal groups however are very heterogeneous and there are large differences by state and even by districts within states, and certainly across tribes. The Government of India identifies 533 tribes with 62 of them located in the state of Orissa.<sup>4</sup> The national data do not allow for disaggregation by tribe, so some of these patterns may not hold true for individual tribes. There is an additional issue of heterogeneity. The most disadvantaged tribal groups are those where the Fifth Schedule of the Constitution applies. States in North-Eastern India, particularly those covered by the Sixth Schedule<sup>5</sup> have a large proportion of Scheduled Tribes but many also have much better human development indicators. Often the better indicators in these states raise average human development outcomes, so a state-wise disaggregation becomes really important.

The contribution of this paper lies in the fact that it disaggregates childhood mortality into neonatal, post-neonatal, infant and child mortality and analyzes the correlates of each. Most analyses have lumped child mortality<sup>6</sup> into “under-five” mortality or have analyzed only infant

> 3 India Poverty Assessment Report and India Social Exclusion Report (forthcoming, 2010).  We also draw heavily from the India chapter (Das, Hall, Kapoor and Nikitin, 2010) of a forthcoming volume on indigenous people (Hall and Patrinos, eds, 2010)

> 4 http://www.tribal.nic.in/index1.html

> **5** Assam, Meghalaya, Tripura and Mizoram

> 6 Mortality indicators are in 'deaths per 1000 births'. Neonatal mortality (NN)- probability of dying in the first month of life; Post-neonatal mortality (PNN) - probability of dying after the first month of life, but before the first birthday;

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