Abstract
There is widespread concern about the socio-economic inequities that disadvantage certain households in rural India. This article focuses on inequities in the context of the shortage of household sanitation. Lack of proper sanitation is a major environmental risk to children’s health and an inconvenience, particularly for women.
We undertake a comparative analysis of three states, namely Gujarat, Madhya Pradesh and the Punjab. These three states are chosen because they differ significantly in terms of the Human Development Index. We compare the overall shortage of household sanitation in their rural areas and the likelihood of sanitation-related inequities. Empirical analyses, with data for 2007–08, showed that, in respect of both sanitation and sanitation-related inequities, Madhya Pradesh was in the third position, Gujarat did rather better, while Punjab had the best performance. The results could have some useful policy implications.
Introduction
Socio-economic inequities in matters of health have been of considerable concern in India. Baru et al. (2010) analysed inequities in access to health services. Katrak (2012) pointed to inequities in household sanitation as between the rural and urban areas. Sampat (2007) reports that even within the rural areas there are significant inequities between households.
Inequities in access to proper sanitation are of particular concern as the affect children and women. Lack of proper sanitation is a major cause of children’s diarrhoea and so of infant mortality. 1 This is of some concern for, as Ram et al. (2008) observe, there is a marked lack of training in the proper treatment of diarrhoea. Radkar and Parasuraman (2007) explain that lack of household sanitation poses a further problem for women: they have to defecate in open fields and that encroaches on their privacy.
This article compares sanitation-related inequities in three states, Gujarat, Madhya Pradesh and Punjab. These three states are selected as they differ from each other in respect of certain important indicators. Mehrotra and Gandhi (2012) reported their findings for the overall Human Development Index and also for the more detailed Health Index and Education Index. They noted that, in respect of each of these indicators, Madhya Pradesh had a poorer performance than the two other states while Punjab had the best performance.
We will examine whether these three states also differ in respect of household sanitation and sanitation-related inequities. Inequities could arise because, within each state, households differ in terms of certain characteristics, namely income, women’s literacy and/or caste. We will first consider these characteristics separately and then jointly.
The rest of the article is arranged as follows. The second section has a brief background about the sanitation scenario and socio-economic inequities in rural India. The third section outlines the procedures to compare differences between states and also within states. The fourth section gives details of the data to be used for the empirical analysis and the fifth section reports the results of the analysis. Sixth section discusses the implications and limitations of the findings. The appendices explain the procedures for the empirical analysis.
The Background Scenario
The shortage of proper sanitation in rural India has been partly due to the limitations of governments’ policies. Earlier policies suffered from a top-down and supply-oriented approach; this often led to underachievement of targets and poor maintenance of sanitation units. Subsequent recognition of these problems led to a shift towards a de-centralised and demand-driven approach with community participation and performance-related awards.
Gupta and Pal (2008) found that this demand-oriented approach has helped to increase sanitation coverage in some areas. However, many rural districts still have shortages. This continuing problem could be because of: (a) insufficient government funding and/or poor utilisation of those funds and (b) constraints on household demand.
Concern with the funding problem has spurred the government to announce a further initiative in 2012. The resources allocated for rural sanitation are to be increased twofold in the 12th Five Year Plan. The major contribution is to be made by the centre and state governments and a small contribution will be required from households. 2
Increased funding may, however, not be sufficient. What is also required is proper monitoring of the use of those funds. This is important particularly as George (2011) has documented some cases of under utilisation and inefficient utilisation in certain states.
Constraints on households’ demand can be due to, at least, two factors. Low-income households may not be able to afford the contribution for their sanitation programme and/or may lack sufficient information about the link between lack of sanitation and risks to health. Pattanayak et al. (2009) recognise the role of both of these factors: they suggest the need for sanitation subsidies and also for health education programmes.
Socio-economic inequities, within a state, can arise can arise if, for instance, there is a shortage of resources for sanitation. For instance, in cases of limited resources, the sanitation providing agencies may give priority to certain households; the remaining households would then have little (or nil) likelihood of getting sanitation. Such an outcome may be called ‘supply side’ inequities.
The priority households could be those with relatively higher incomes and/or with literate women. The low-priority groups would then be those with low incomes and/or illiterate women; some of these could also be Scheduled Caste (SC) and Scheduled Tribe (ST) households. 3 These households would have a low (or nil) likelihood of getting sanitation.
Recognition of these supply-side inequities has led the government to promote village-level committees. The National Rural Health Mission (NRHM) has allocated funds for the setting up and functioning of Health and Sanitation Committees (HSC).
The HSC are expected to have a high representation of the disadvantaged households, including those with illiterate women, low incomes and the Scheduled Castes and Scheduled Tribes. 4 These groups will also be considered in our analysis of socio-economic inequities.
The Procedures for the Empirical Analyses
The first step will be an overall analysis of the data. We will examine inter-state differences in: (a) the lack of sanitation and (b) the presence of the disadvantaged groups of households.
The main purpose of the overall analysis will be to examine whether the state with the highest (lowest) percentage of households without sanitation also has the highest (lowest) per cent of the disadvantaged groups of households.
The next exercise will examine whether most of the households that lack sanitation are also disadvantaged in some other respects. Households may be disadvantaged if, say, their women are illiterate. In view of this possibility, we will check whether the majority of households that lack sanitation are also those where women are illiterate. The procedure to calculate the percentage of such households is detailed in Appendix A-I.
The third exercise will concern the socio-economic inequities, within each state. We will calculate the likelihood that some low priority households would not be provided with sanitation facilities. A distinction will be made between two low-priority groups: (a) those whose women are literate and have low incomes and (b) the SC and ST households. 5 Both groups would be of interest to the HSC.
The likelihood of not getting sanitation will be measured on a scale from zero to one. The calculations of the likelihood will take account of the overall shortage of sanitation, in each state. The underlying procedure is explained in Appendix A-II.
The Data
The required data was taken mainly from the District Level Household and Facility Survey (DLHS-3). These are periodic state-level surveys; the most recent data is for the years 2007–08. Details are reported separately for the rural and urban areas.
Our interest is in the percentage of rural households with each of the following characteristics:
lack access to a toilet facility; currently married women who have not had 10 or more years of schooling; are positioned in the lowest and in the highest wealth quintiles.
The data for each of these items has certain features that need to be discussed.
First, the data about access to toilets does not distinguish between private toilets and shared, or communal toilets. This could conceal inequities between households; shared toilets could raise problems of queuing and/or proper maintenance and functioning. However, for practical convenience, we will use the terms ‘toilets’ and ‘sanitation’ interchangeably.
Second, the data on women’s illiteracy is being used as an indicator of those households that are likely to neglect women’s needs. In this respect, it would be desirable to also have data about households where women are not income earners. However, employment data matching the coverage of the DLHS-3 is not available.
Third, the data on wealth quintiles distinguishes only between households in the lowest quintile and those in the highest quintile. However, there are a rather large percentage of households in between those quintiles; these may be called the ‘in-between’ quintiles. The percentage of households in those quintiles need also be taken into account.
We will use this data to form two groups of households: a ‘low-income’ and a ‘high-income’ group. The former group will be defined as the households that are in the lowest wealth quintile plus one-half of those that are in the in-between quintiles.
The DLHS-3 also reports the percentage of villages that have HSC. In using these village-level percentages along with the above household percentages, we will need to assume that the number of households per village is the same for all villages, in each state.
The data for the SC and ST households is reported by the Office of the Registrar General and Census Commissioner. 6 The latest data is for the year 2011. The percentage of illiterate women in these households is higher than in other households but the gap has been closing over the preceding years.
One other point about the data should be mentioned. The DLHS-3 data on sanitation is not the most recent available. The Census 2011 is more recent. Nevertheless we use the DLHS-3 because it provides information about the HSC on a comparable basis, as the sanitation data.
The Empirical Analysis
Table 1 gives an overview of the data. The main observations are: (a) the marked differences between the three states and (b) within each state the differences between the various household characteristics. Details are as follows.
First, as between states, Madhya Pradesh has the poorest record on most counts: it has the highest percentage of households with lack of sanitation and also the highest percentage for households with illiterate women, low incomes and the SC and ST households. Gujarat does somewhat better while Punjab has the best outcomes.
Inter-state Differences in Household and Village Characteristics1
1. The numbers in first four columns are the percentage of households that have the mentioned characteristics, while those in the fifth column pertain to the percentage of villages.
2. Lack sanitation denotes lack of sanitation or of toilets.
3. SC and ST denote Schedule Caste and Schedule Tribe, respectively.
4. HSC denotes Health and Sanitation Committees.
5. This is short for Madhya Pradesh.
Second, these inter-state differences are much greater for lack of sanitation than for the three other characteristics. For example, in Gujarat, the percentage of households that lack sanitation is more than twice greater than that for Punjab but, in comparison, the percentage of households with illiterate women in the former state is only about one-fifth higher than in the latter.
Third, within each state, the highest percentages are for women’s illiteracy while the lowest is for the SC and ST households. For instance, in Gujarat, the figure for women’s illiteracy is as high as 87 per cent while that for the SC and ST is only 22 per cent.
Fourth, the low-income groups are on average about 42 per cent of all households. This figure is rather similar to the all-India percentage of rural households living below the official poverty line. 7
The final column shows the percentage of villages that have an HSC. We see that, in all three states, these percentages are lower than for the households that lack sanitation (shown in the first column). This is particularly so in Madhya Pradesh: the percentage for the HSC is only about two-fifths of that for the households that lack sanitation.
These results could be due to the influence of two factors. First, in all three states, there may be a shortage of government funding for the HSC. Second, even those committees that have been formed may have little impact in inducing households to have sanitation.
Table 2 focuses on lack sanitation in two groups of households. The first column pertains to those households where women are not literate while the second column is for those where women are illiterate. The details are as follows.
First, we found that there are marked differences between the two groups of households. Lack of sanitation is a problem very largely in the households where women are not literate. The average of the three states showed that more than one-half of all households lacked sanitation and the women were not literate, while less than 10 per cent of households lacked sanitation and had literate women. (The remaining households were those that had sanitation.)
Second, we found marked differences between the three states. Here again Madhya Pradesh had the poorest record: as many as 86 per cent of the households lacked sanitation and their women were not literate.
Lack of Sanitation in Two Groups of Households
These inter-household differences are now further considered in the context of supply-side constraints. These constraints could arise, for instance, in districts (or villages) where the sanitation providing agencies give low priority to some households. The low priority households could include those with illiterate women, low incomes and/or the SC and ST households.
Likelihood That Some Households Will Not Have Sanitation
The greater is the percentage of the privileged households that are given priority the lower will be the likelihood that the disadvantaged households will not get sanitation. This likelihood will be measured on a scale ranging from zero to one.
Table 3 shows two alternative scenarios. The first column assumes that the low-priority households are all those that have illiterate women and low incomes. The second column considers a smaller group that has only the SC and ST households. These differences between the two groups arise in all three states.
We find that the likelihood of not having sanitation could be quite high for both groups. For instance, in the Punjab, the likelihood for the larger group could be as high as 0.62 while that for the smaller group could even reach the maximum possible, that is, 1.0. The latter figure would mean a nil likelihood of getting sanitation.
Implications and Questions for Further Research
The results of this article, though limited to three states, have an important implication for India’s poor record in sanitation for rural households. We need to understand why there are such marked differences between states and also marked inequities within states.
Our results provide, at least, a part of the answer. A major factor could be women’s illiteracy. Inter-state comparisons showed that the state that had the highest (lowest) percentage of households without sanitation were also those that had the highest (lowest) incidence of women’s illiteracy. Moreover, within each state, the lack of sanitation was found mainly in those households whose women were illiterate.
The results also point to the need for some further research. There are, at least, two important questions to be considered. These pertain to the HSC and the validity of our results for more recent periods.
First, have the HSCs helped to reduce some socio-economic inequities? For instance are the committees set up mainly in those districts (or villages) that had a relatively high shortage of sanitation and/or a high incidence of women’s illiteracy?
Second, would our results, obtained with data for the year 2007–08, be valid for, say, 2012–13. Would the state that had the worst (best) record in the earlier period continue to have the worst (best) performance in the latter period? In particular, would Gujarat, with its rapid economic growth in recent years, now have become the best performer in matters of sanitation and/or women’s literacy?
Footnotes
Appendix A-I
This appendix explains the procedure used to calculate the percentage of those households that lack sanitation and whose women are not literate. The procedure is illustrated with the data for Madhya Pradesh.
The households that lack sanitation account for 89.9 per cent of the total while those whose women are not literate are 95.3 per cent. So the households that have both these characteristics would be (0.899) (0.953) (100) = 85.7 per cent of the total.
Appendix A-II
This appendix deals with the supply-side inequities. Priority for sanitation is given to those households that are in the upper-income group and whose women are literate. The procedure is illustrated with the data for Gujarat.
The upper-income households are 51.9 per cent of the total, the households with illiterate women account for 13.1 per cent and so the priority households would be (0.519) (0.131) (100) = 6.8 per cent of the total. The non-priority households would then be as many as (100–6.8) = 93.2 per cent.
Sanitation is reported in 28.3 per cent of all households. So if all priority households were provided with sanitation facilities the facilities left for the non-priority group would be available in only (28.3–6.8) = 21.5 per cent of all households.
Consequently the likelihood that any one of the non-priority households would have sanitation would be only (21.5/93.2) = 0.231 and so the likelihood of not having sanitation would be as high as (1.00–0.231) = 0.769.