Under Sustainable Development Goal targets 6.1 and 6.2, every nation is committed to ensure universal and equitable access to water and sanitation to its people and India is no exception. The country has made a considerable progress toward these targets through various policy and programmatic initiatives since 2015. Within an overall improvement at the country level, this paper examines the coverage of key WASH indicators in tribal population of the country. Secondary data pertaining to the WASH indicators were obtained from the NFHS 2015–2016 and NFHS 2019–2021 for 90 tribal-dominated districts of the country and were analyzed. We ranked these tribal districts on the basis of their performance. The analysis showed a distinct improvement in terms of marked fall in open defecation, uptake of improved toilet facilities, accessibility to improved sources of water, and improved behaviors in relation to the handwashing and treatment of drinking water in tribal population with varying levels of coverage, which was captured in WASH ranking of these districts. The districts falling toward the bottom side of the ranking ladder need prioritization and entail more attention of programmatic interventions in order to sustain the overall progress and to reach the SDG targets of 100% WASH coverage.

  • It is the first systematic assessment of the progress that has been made toward the WASH coverage in tribal-dominated districts of India.

  • It is the first attempt to rank the tribal-dominated districts on the basis of their performance on WASH indicators and coverage.

  • It provides insights on districts and WASH indicators that need prioritization and also a means to track the progress that each district is making.

Contaminated water, poor sanitation, and hygiene impair health, expose individuals to many health risks and lead to poor health outcomes. It is a persistent health challenge accounting for 90% of the 2 million global diarrhoeal disease-related deaths, mostly affecting children (UN 2016). Access to safe drinking water, adequate sanitation, and hygiene make a meaningful and substantial contribution toward reducing the global disease burden through preventing and reducing illness (Fewtrell et al. 2005; Cairncross et al. 2010; WHO 2017). The era of Sustainable Development Goals (SDGs), with targets 6.1 and 6.2 pertaining to water, sanitation, and hygiene (WASH) seems to have coincided with significant efforts made to improve access to safe drinking water and sanitation (WHO & UNICEF 2021). Both these SDG targets underscore the importance of WASH in population health and reinforce the need of prioritizing the universal access of WASH services. In 2015, India accounted for 90% of South Asians and 50% of the global population defecating in the open. The Government of India launched some of its flagship programs, such as Swachh Bharat Mission (SBM), Jal Jeevan Mission (JJM), and WASH in schools, demonstrating a renewed commitment to WASH. India, since then has made commendable progress in substantially reducing the proportion of population defecating in the open, which has come down from 29% (in 2015) to 15% (in 2020) (World Bank 2022). Likewise, the share of people having access to safe drinking water source has also increased during these 5 years (GoI 2022a, 2022b). In the context of an overall country level improvement, this paper looks into the coverage of WASH indicators in one of its sub-population category, i.e., tribal population. The country has a substantial proportion of tribal population with a 10.1% share in the overall population (Census 2011). The tribal population in Indian settings is known by different names, such as, adivasi, janjati, girijan, and is referred to as Scheduled Tribes in the Indian constitution. The tribal population largely lives in hilly, forested, or well-defined areas. They vary among themselves in relation to the language they speak, ecological settings wherein they reside, physical features, population size, mode of subsistence, level of acculturation, and social stratification. They are spread across the country with varying population size ranging between lakhs and few in numbers. Though they are mainly concentrated in eastern, central and in the northeastern states of the country, the sizeable tribal population is also found in other states. The tribal population, generally in the country, has a relatively poor track record in many of the development and health indicators, including those pertaining to WASH (GoI 2014, 2017a, 2017b). Accordingly, this paper analyzes coverage of key WASH indicators in tribal-dominated geographies of India, for the time period between 2015 and 2021 with an attempt to score and rank them on their performance.

The paper is based on the data collected under the two rounds of National Family Health Survey (NFHS), namely, NFHS-4 (2015–2016) and NFHS-5 (2019–2021). NFHS surveys, which are conducted under the aegis of the Ministry of Health and Family Welfare, Government of India, are large-scale and periodic surveys of representative samples of households in India. These surveys provide reliable and important data on the population, health and nutrition-related indicators at national, state and district level. Four survey schedules/questionnaires, namely, Household, Woman, Man, and Biomarker, were used in both NFHS-4 and NFHS-5 to collect the data. Each tool captures a set of information. We have concentrated on the household schedule/questionnaire, which essentially captures demographic information, socio-economic characteristics, asset ownership, health insurance coverage, land ownership, etc. The household schedule also captures WASH-related information, such as, different sources of drinking water, various means adopted for the treatment of drinking water, sanitation, open defecation, and hand hygiene amenities, etc. at the household level. The data pertaining to drinking water sources, treatment of drinking water, and sanitation facilities are self-reported, while data related to hand hygiene are observed and then recorded. Under NFHS-4, the WASH-related data were collected from 601,509 households, while in NFHS-5, similar data were collected from 636,699 households. The details pertaining to how these households were sampled and the household tool are available in the reports of both these rounds (IIPS & ICF 2017, 2021). The household level data of these surveys are available in different file formats in DHS (Demographic and Health Surveys) Program. We took the SPSS files for both the rounds of the survey and extracted household level data pertaining to WASH indicators for 90 tribal-dominated districts. Figure 1 shows the location of the tribal-dominated districts in the map of India. A total of 66,412 and 66,425 households were covered in these tribal-dominated districts in NFHS-4 and NFHS-5 round, respectively. The extracted data from these households were analyzed in SPSS (version 22). In order to show the scale and significance of change in WASH indicators between these two time periods, a z-test was used. A composite index has also been developed to rank the districts in relation to their respective performance on WASH indicators. To develop the composite index, all the WASH-related indicators, available in NFHS-4 and NFHS-5, were reviewed with respect to their availability across all the 90 tribal-dominated districts. Accordingly, four indicators were selected, namely, households having access to an improved water source, households practicing treatment of water; households having improved toilet facilities and households where both water and cleansing material was observed and available. The data on these indicators were compiled and the value of each indicator was scaled using the following equation:
formula
Figure 1

Location of tribal-dominated districts.

Figure 1

Location of tribal-dominated districts.

Close modal
Figure 2

Location of ranked districts.

Figure 2

Location of ranked districts.

Close modal

The minimum and maximum values of each indicator were determined from the values of that indicator spread across the districts. The scaled value for each indicator lies between the range of 0–1. Using these scaled values, a composite index score was computed (by taking out mean) using the NFHS-5 data. The composite index score provided the overall performance of each district.

The total number of households covered in the tribal-dominated districts, in each round of the surveys, was close to 66,400 with the majority of the households headed by male member having a median age of 46 and 47 years, respectively. About two-thirds of the head of the households were illiterate, with majority of them having an education till primary and secondary level. A small change (6%) can be seen in the proportion of households having a pucca house between these two rounds of surveys, but the majority of the households (60%) is semi-pucca houses with two third of them having a nuclear family (66%). About 50% of the households belonged to the poorest and poor category of the wealth index (Table 1).

Table 1

Socio-demographic characteristics of the respondents

2015
2021
n%n%
Gender 
 Male 56,766 85.5 54,286 81.7 
 Female 9,646 14.5 12,139 18.3 
 Total 66,412 100.0 66,425 100.0 
Age groups (years) 
 15–24 1,810 2.7 1,441 2.2 
 25–34 11,325 17.1 10,896 16.4 
 35–44 15,854 23.9 15,425 23.2 
 45–54 16,165 24.3 16,259 24.5 
 55 + 21,215 31.9 22,365 33.7 
 Did not report 43 0.1 39 0.1 
 Total 66,412 100.0 66,425 100.0 
Education 
 No education, preschool 25,375 38.2 23,138 34.8 
 Primary 14,084 21.2 13,618 20.5 
 Secondary 23,580 35.5 25,914 39.0 
 Higher 3,092 4.7 3,707 5.6 
 Don't know 281 0.4 48 0.1 
 Total 66,412 100.0 66,425 100.0 
Household type 
 Kachha 8,748 13.7 8,896 13.8 
 Semi-pucca 41,934 65.8 38,797 60.2 
 Pucca 13,071 20.5 16,792 26.0 
 Total 63,753 100.0 64,485 100.0 
Household structure 
 Nuclear 41,994 63.2 43,563 65.6 
 Non-nuclear 24,418 36.8 22,862 34.4 
 Total 66,412 100.0 66,425 100.0 
Wealth Index 
 Poorest 17,510 26.4 20,772 31.3 
 Poorer 15,001 22.6 14,996 22.6 
 Middle 14,776 22.2 12,110 18.2 
 Richer 11,524 17.4 10,133 15.3 
 Richest 7,601 11.4 8,414 12.7 
 Total 66,412 100.0 66,425 100.0 
2015
2021
n%n%
Gender 
 Male 56,766 85.5 54,286 81.7 
 Female 9,646 14.5 12,139 18.3 
 Total 66,412 100.0 66,425 100.0 
Age groups (years) 
 15–24 1,810 2.7 1,441 2.2 
 25–34 11,325 17.1 10,896 16.4 
 35–44 15,854 23.9 15,425 23.2 
 45–54 16,165 24.3 16,259 24.5 
 55 + 21,215 31.9 22,365 33.7 
 Did not report 43 0.1 39 0.1 
 Total 66,412 100.0 66,425 100.0 
Education 
 No education, preschool 25,375 38.2 23,138 34.8 
 Primary 14,084 21.2 13,618 20.5 
 Secondary 23,580 35.5 25,914 39.0 
 Higher 3,092 4.7 3,707 5.6 
 Don't know 281 0.4 48 0.1 
 Total 66,412 100.0 66,425 100.0 
Household type 
 Kachha 8,748 13.7 8,896 13.8 
 Semi-pucca 41,934 65.8 38,797 60.2 
 Pucca 13,071 20.5 16,792 26.0 
 Total 63,753 100.0 64,485 100.0 
Household structure 
 Nuclear 41,994 63.2 43,563 65.6 
 Non-nuclear 24,418 36.8 22,862 34.4 
 Total 66,412 100.0 66,425 100.0 
Wealth Index 
 Poorest 17,510 26.4 20,772 31.3 
 Poorer 15,001 22.6 14,996 22.6 
 Middle 14,776 22.2 12,110 18.2 
 Richer 11,524 17.4 10,133 15.3 
 Richest 7,601 11.4 8,414 12.7 
 Total 66,412 100.0 66,425 100.0 

The improved sources of drinking water included piped water, public taps, standpipes, tube wells, boreholes, protected dug wells and springs, rainwater, and community reverse osmosis plants. Almost 82% of the household in tribal-dominated districts had access to an improved source of drinking water in 2021 as compared to 76% in 2015 (z = −19.45, p < 0.00001). Within the improved sources of drinking water, a substantial increase was observed in piped water supply to the households. The proportion of the households where water is piped into the dwelling or yard or plot increased from 23% (in 2015) to 31% (in 2021), respectively (z = −32.87, p < 0.00001). Accordingly, the percentage of households with access to an unimproved water source has decreased from 22 to 16% during this period. The proportion of households having improved or unimproved water source and engaged in water treatment has shown an increase (z = −40.61, p < 0.00001). Irrespective of the water source, as many as 68% of the household in the year 2021 (in comparison to 57% in 2015) reported about treating the drinking water using one or the other method with majority of them preferring to boil, straining through cloth, and use ceramic sand or other water filter in both the years (Table 2). There is also an increase in the households, with improved drinking water source, engaged in treatment of drinking water (z = −38.19, p < 0.00001) as well as those which did not have an improved drinking water source but engaged in treating water (z = −14.90, p < 0.00001).

Table 2

WASH indicators

2015
2021
Percentage changez-test
n%n%
Drinking water facilities and treatment methods 
Improved sources of drinking water 
Piped into dwelling/yard/plot 15,216 22.9 20,523 30.9 34.9 z = −32.87, p < 0.00001 
Public tap/standpipe 11,564 17.4 10,295 15.5 −11.0 z = 9.33, p < 0.00001 
Tube well or borehole 18,270 27.5 15,935 24.0 −12.8 z = 14.58, p < 0.00001 
Protected dug well 2,832 4.3 3,296 5.0 16.4 z = −6.06, p < 0.00001 
Protected spring 2,198 3.3 2,527 3.8 15.0 z = −4.92, p < 0. 00001 
Rainwater 920 1.4 1,300 2.0 41.3 z = −8.45, p < 0.00001 
Community RO Plant 490 0.7 429 0.6 −12.4 z = 2.26, p < 0.0232 
Unimproved sources of drinking water 
Unprotected dug well 6,957 10.5 4,773 7.2 −31.4 z = 21.17, p < 0.00001 
Unprotected spring 3,414 5.1 2,653 −22.3 z = 9.61, p < 0.00001 
Tanker truck/cart with small tank 359 0.5 343 0.5 −4.5 z = 0, p = 1 
Surface water 3,868 5.8 2,332 3.5 −39.7 z = 19.91, p < 0.00001 
Bottled water 168 0.3 391 0.6 132.7 z = −8.16, p < 0.00001 
Others sources 156 0.2 1,628 2.5 943.6 z = −36.31, p < 0.00001 
N 66,412 100.0 66,425 100.0   
Water treatment done at household 
No 28,620 43.1 21,480 32.3 −24.9 z = 40.61, p < 0.00001 
Yes 37,768 56.9 44,940 67.7 19.0 z = −40.61, p < 0.00001 
N 66,412 100.0 66,425 100.0   
Water treatment and source of drinking water 
Household having improved drinking water source and treat water 28,954 56.2 36,713 67.6 26.8 z = −38.19, p < 0.00001 
Household having unimproved drinking water source and treat water 8,814 59.1 8,227 67.9 −6.7 z = −14.90, p < 0.00001 
Water treatment methods 
Boil 25,004 66.2 30,920 68.8 23.7 z = −7.95, p < 0.00001 
Use alum 382 1.0 699 1.6 83.0 z = −7.51, p < 0.00001 
Add bleach/chlorine 599 1.6 895 49.4 z = −4.28, p < 0.00001 
Strain through cloth 7,078 18.7 10,927 24.3 54.4 z = −19.44, p < 0.00001 
Use ceramic, sand or other water filter 7,774 20.6 8,961 19.9 15.3 z = 2.49, p < 0.01242 
Use electric purifier 742 2.0 680 1.5 −8.4 z = 5.49, p < 0.00001 
Allow water to stand and settle 846 2.2 1,896 4.2 124.1 z = −16.06, p < 0.00001 
Other 1,390 3.7 212 0.5 −84.7  
N 37,768  44,940    
Sanitation facilities 
Improved, not shared facility 
Flush/pour flush to piped sewer system 520 0.8 1,109 1.7 113.3 z = −14.76, p < 0.00001 
Flush/pour flush to septic tank 12,772 19.2 24,143 36.3 89.0 z = −69.59, p < 0.00001 
Flush/pour flush to pit latrine 9,391 14.1 11,482 17.3 22.3 z = −16.02, p < 0.00001 
Ventilated improved pit latrine/biogas latrine 117 0.2 167 0.3 42.7 z = −3.64, p < 0.00026 
Pit latrine with slab 5,990 9.0 6,904 10.4 15.3 z = −8.62 p < 0.00001 
Twin pit, composting toilet 520 0.8 2,721 4.1 423.3 z = −38.89, p < 0.00001 
Shared facility 
Flush/pour flush to piped sewer system 54 0.1 114 0.2 111.1 z = −4.70, p < 0.00001 
Flush/pour flush to septic tank 1,571 2.4 1,584 2.4 0.8 z = 0, p = 1 
Flush/pour flush to pit latrine 1,002 1.5 761 1.1 −24.1 z = 6.43, p < 0.00001 
Ventilated improved pit latrine/biogas latrine 13 0.0 18 0.0 38.5  
Pit latrine with slab 764 1.2 546 0.8 −28.5 z = 7.32, p < 0.00001 
Twin pit, composting toilet 26 211 0.3 711.5 z = −14.12, p < 0.00001 
Unimproved 
Flush/pour flush not to sewer/septic tank/pit latrine 1,040 1.6 577 0.9 −44.5 z = 11.48, p < 0.00001 
Pit latrine without slab/open pit 5,175 7.8 1,862 2.8 −64.0 z = 40.67, p < 0.00001 
Dry toilet 2,008 1,573 2.4 −21.7 z = 6.74, p < 0.00001 
Other 121 0.2 193 0.3 59.5 z = −3.64, p < 0.00026 
No facility/uses open space/field 25,328 38.1 12,460 18.8 −50.8 z = 77.95, p < 0.00001 
N 66,412 100.0 66,425 100.0   
Hand washing facilities 
Presence of water at hand washing place 48,156 75.4 56,596 87.4 17.5 z = −55.34, p < 0.00001 
Soap or detergent available 34,712 54.3 43,854 67.8 26.3 z = −49.65, p < 0.00001 
Ash, mud, sand available 12,429 19.5 13,266 20.5 6.7 z = −4.48, p < 0.00001 
Presence of water and Soap or Detergent 32,213 50.4 41,999 64.9 30.4 z = −52.62, p < 0.00001 
Presence of water and ash/mud/sand available 8,924 14.0 11,396 17.6 27.7 z = −17.69, p < 0.00001 
Presence of water only 9969 15.6 8138 12.6 −18.4 z = 15.46, p < 0.00001 
N (households in which place for hand washing was observed) 63,896 100.0 64,722 100.0   
2015
2021
Percentage changez-test
n%n%
Drinking water facilities and treatment methods 
Improved sources of drinking water 
Piped into dwelling/yard/plot 15,216 22.9 20,523 30.9 34.9 z = −32.87, p < 0.00001 
Public tap/standpipe 11,564 17.4 10,295 15.5 −11.0 z = 9.33, p < 0.00001 
Tube well or borehole 18,270 27.5 15,935 24.0 −12.8 z = 14.58, p < 0.00001 
Protected dug well 2,832 4.3 3,296 5.0 16.4 z = −6.06, p < 0.00001 
Protected spring 2,198 3.3 2,527 3.8 15.0 z = −4.92, p < 0. 00001 
Rainwater 920 1.4 1,300 2.0 41.3 z = −8.45, p < 0.00001 
Community RO Plant 490 0.7 429 0.6 −12.4 z = 2.26, p < 0.0232 
Unimproved sources of drinking water 
Unprotected dug well 6,957 10.5 4,773 7.2 −31.4 z = 21.17, p < 0.00001 
Unprotected spring 3,414 5.1 2,653 −22.3 z = 9.61, p < 0.00001 
Tanker truck/cart with small tank 359 0.5 343 0.5 −4.5 z = 0, p = 1 
Surface water 3,868 5.8 2,332 3.5 −39.7 z = 19.91, p < 0.00001 
Bottled water 168 0.3 391 0.6 132.7 z = −8.16, p < 0.00001 
Others sources 156 0.2 1,628 2.5 943.6 z = −36.31, p < 0.00001 
N 66,412 100.0 66,425 100.0   
Water treatment done at household 
No 28,620 43.1 21,480 32.3 −24.9 z = 40.61, p < 0.00001 
Yes 37,768 56.9 44,940 67.7 19.0 z = −40.61, p < 0.00001 
N 66,412 100.0 66,425 100.0   
Water treatment and source of drinking water 
Household having improved drinking water source and treat water 28,954 56.2 36,713 67.6 26.8 z = −38.19, p < 0.00001 
Household having unimproved drinking water source and treat water 8,814 59.1 8,227 67.9 −6.7 z = −14.90, p < 0.00001 
Water treatment methods 
Boil 25,004 66.2 30,920 68.8 23.7 z = −7.95, p < 0.00001 
Use alum 382 1.0 699 1.6 83.0 z = −7.51, p < 0.00001 
Add bleach/chlorine 599 1.6 895 49.4 z = −4.28, p < 0.00001 
Strain through cloth 7,078 18.7 10,927 24.3 54.4 z = −19.44, p < 0.00001 
Use ceramic, sand or other water filter 7,774 20.6 8,961 19.9 15.3 z = 2.49, p < 0.01242 
Use electric purifier 742 2.0 680 1.5 −8.4 z = 5.49, p < 0.00001 
Allow water to stand and settle 846 2.2 1,896 4.2 124.1 z = −16.06, p < 0.00001 
Other 1,390 3.7 212 0.5 −84.7  
N 37,768  44,940    
Sanitation facilities 
Improved, not shared facility 
Flush/pour flush to piped sewer system 520 0.8 1,109 1.7 113.3 z = −14.76, p < 0.00001 
Flush/pour flush to septic tank 12,772 19.2 24,143 36.3 89.0 z = −69.59, p < 0.00001 
Flush/pour flush to pit latrine 9,391 14.1 11,482 17.3 22.3 z = −16.02, p < 0.00001 
Ventilated improved pit latrine/biogas latrine 117 0.2 167 0.3 42.7 z = −3.64, p < 0.00026 
Pit latrine with slab 5,990 9.0 6,904 10.4 15.3 z = −8.62 p < 0.00001 
Twin pit, composting toilet 520 0.8 2,721 4.1 423.3 z = −38.89, p < 0.00001 
Shared facility 
Flush/pour flush to piped sewer system 54 0.1 114 0.2 111.1 z = −4.70, p < 0.00001 
Flush/pour flush to septic tank 1,571 2.4 1,584 2.4 0.8 z = 0, p = 1 
Flush/pour flush to pit latrine 1,002 1.5 761 1.1 −24.1 z = 6.43, p < 0.00001 
Ventilated improved pit latrine/biogas latrine 13 0.0 18 0.0 38.5  
Pit latrine with slab 764 1.2 546 0.8 −28.5 z = 7.32, p < 0.00001 
Twin pit, composting toilet 26 211 0.3 711.5 z = −14.12, p < 0.00001 
Unimproved 
Flush/pour flush not to sewer/septic tank/pit latrine 1,040 1.6 577 0.9 −44.5 z = 11.48, p < 0.00001 
Pit latrine without slab/open pit 5,175 7.8 1,862 2.8 −64.0 z = 40.67, p < 0.00001 
Dry toilet 2,008 1,573 2.4 −21.7 z = 6.74, p < 0.00001 
Other 121 0.2 193 0.3 59.5 z = −3.64, p < 0.00026 
No facility/uses open space/field 25,328 38.1 12,460 18.8 −50.8 z = 77.95, p < 0.00001 
N 66,412 100.0 66,425 100.0   
Hand washing facilities 
Presence of water at hand washing place 48,156 75.4 56,596 87.4 17.5 z = −55.34, p < 0.00001 
Soap or detergent available 34,712 54.3 43,854 67.8 26.3 z = −49.65, p < 0.00001 
Ash, mud, sand available 12,429 19.5 13,266 20.5 6.7 z = −4.48, p < 0.00001 
Presence of water and Soap or Detergent 32,213 50.4 41,999 64.9 30.4 z = −52.62, p < 0.00001 
Presence of water and ash/mud/sand available 8,924 14.0 11,396 17.6 27.7 z = −17.69, p < 0.00001 
Presence of water only 9969 15.6 8138 12.6 −18.4 z = 15.46, p < 0.00001 
N (households in which place for hand washing was observed) 63,896 100.0 64,722 100.0   

Improved sanitation facilities included toilet that was not shared and ranged from flush/pour flush toilets to piped sewer systems, septic tanks, and pit latrines; ventilated improved pit (VIP)/biogas latrines; pit latrines with slabs; and twin pit/composting toilets. Our analysis points toward an increase of 26% points in the use of improved sanitation facilities in tribal-dominated districts from 44.1% in 2015 to 70% in 2021 (z = −95.35, p < 0.00001) with a two-fold rise in households having a toilet that are flushed/pour flush to septic tank. Accordingly, the proportion of households using unimproved toilet facilities declined from 13% (in 2015) to 6% (in 2021). A remarkable change which was noticed between 2015 and 2021 was the 50% decline in household practicing open defecation (from 38% in 2015 to 19% in 2021) (z = 77.95, p < 0.00001) (Table 2).

With respect to hand hygiene, a substantial change is noticed between 2015 and 2021. Almost 87% of the household had water at the hand washing place which is higher than that of 2015 (z = −55.34, p < 0.00001). A similar increase is also noted in availability of hand washing item (soap or detergent). Likewise, the proportion of households which have both water and hand washing item (soap or detergent) has increased from 50% in 2015 to 65% in 2021 (z = −52.62, p < 0.00001) (Table 2). District-wise disaggregated data on WASH indicators show improvement in most of the districts between 2015 and 2021 but also indicate the large variations across the districts. For instance, there were 28 districts where the coverage of improved sources of drinking water is less than 80%, while in remaining it ranges between 80 and 99%. Likewise, with respect to improved sanitation, the coverage ranged from as low as 27–100% across different districts with 29 districts having less than 60% coverage (Table 3).

Table 3

District-wise distribution of WASH indicators

 
 
 
 

Based on the performance of these indicators in the year 2021, we scored the tribal-dominated districts and ranked them (Figure 2). Eight out of the top 10 performing districts were from the north-eastern region of the country. In the 10 least performing districts, half of them were from the central and eastern regions. In contrast to a significant representation of north-eastern districts in top performing districts, two districts, namely, Papum Pare and Aizwal were found to be in least performing districts (Table 4). In comparison to the top performing districts, the proportion of households in ‘poorest’ and ‘poor’ category of wealth quintile is more in least performing districts barring two districts (Table 5). Contrastingly, the proportion of ‘poorest’ and ‘poor’ wealth quintile households is more in bottom six districts of well-performed category.

Table 4

Ranking of districts based on their performance

Top ten
Bottom ten
DistrictsComposite scoreDistrictsComposite score
East Jantia Hills 0.89 Mayurbhanj 0.35 
Anjaw 0.86 Koraput 0.35 
West Kameng 0.85 Pashchimi Singhbhum 0.33 
Lower Subansiri 0.84 Dhar 0.31 
Phek 0.83 Papum Pare 0.30 
Mamit 0.82 Leh (Ladakh) 0.29 
Kinnaur 0.81 Sundargarh 0.26 
Alirajpur 0.80 Dadra & Nagar Haveli 0.24 
Nicobars 0.80 Lakshadweep 0.05 
Zunheboto 0.79 Aizawl 0.05 
Top ten
Bottom ten
DistrictsComposite scoreDistrictsComposite score
East Jantia Hills 0.89 Mayurbhanj 0.35 
Anjaw 0.86 Koraput 0.35 
West Kameng 0.85 Pashchimi Singhbhum 0.33 
Lower Subansiri 0.84 Dhar 0.31 
Phek 0.83 Papum Pare 0.30 
Mamit 0.82 Leh (Ladakh) 0.29 
Kinnaur 0.81 Sundargarh 0.26 
Alirajpur 0.80 Dadra & Nagar Haveli 0.24 
Nicobars 0.80 Lakshadweep 0.05 
Zunheboto 0.79 Aizawl 0.05 
Table 5

Distribution of households by wealth quintilea in top and least performing districts

Districts% of HH
Districts% of HH
Poorest and poorerMiddleRicher and richestPoorest and poorerMiddleRicher and richest
East Jantia Hills 43% 18% 39% Mayurbhanj 74% 13% 14% 
Anjaw 54% 26% 20% Koraput 65% 16% 20% 
West Kameng 5% 9% 86% Pashchimi Singhbhum 75% 15% 11% 
Lower Subansiri 28% 23% 49% Dhar 44% 15% 40% 
Phek 50% 22% 28% Papum Pare 21% 16% 63% 
Mamit 44% 16% 40% Leh (Ladakh) 20% 20% 60% 
Kinnaur 59% 20% 21% Sundargarh 56% 20% 24% 
Alirajpur 60% 24% 16% Dadra & Nagar Haveli 47% 22% 30% 
Nicobars 56% 24% 20% Lakshadweep 45% 18% 37% 
Zunheboto 40% 28% 31% Aizawl 29% 19% 52% 
Districts% of HH
Districts% of HH
Poorest and poorerMiddleRicher and richestPoorest and poorerMiddleRicher and richest
East Jantia Hills 43% 18% 39% Mayurbhanj 74% 13% 14% 
Anjaw 54% 26% 20% Koraput 65% 16% 20% 
West Kameng 5% 9% 86% Pashchimi Singhbhum 75% 15% 11% 
Lower Subansiri 28% 23% 49% Dhar 44% 15% 40% 
Phek 50% 22% 28% Papum Pare 21% 16% 63% 
Mamit 44% 16% 40% Leh (Ladakh) 20% 20% 60% 
Kinnaur 59% 20% 21% Sundargarh 56% 20% 24% 
Alirajpur 60% 24% 16% Dadra & Nagar Haveli 47% 22% 30% 
Nicobars 56% 24% 20% Lakshadweep 45% 18% 37% 
Zunheboto 40% 28% 31% Aizawl 29% 19% 52% 

aComputed in the NFHS and includes variables like different household assets, flooring material as well as drinking water source and toilet facilities.

All the tribal-dominated districts were also categorized region-wise to show their relative ranking in their respective regions as well as states (Table 6). We also compared the WASH performance of the year 2021 with the base year (2015). The results showed that barring 13 districts, all other tribal-dominated districts have shown an increase in their performance score in compassion to the year 2015. Close to 50% of these 13 districts are located in Mizoram state alone.

Table 6

Region-wise ranking of tribal districts

North-eastern
ArP Anjaw WestKameng Lower Subansiri Tawang Upper Siang Upper Subansiri West Siang Dibang Valley Tirap EastKameng East Siang KurungKumey Papum Pare 
2021 0.86 0.85 0.84 0.76 0.76 0.75 0.74 0.70 0.65 0.64 0.57 0.42 0.30 
2015 0.49 0.49 0.63 0.46 0.53 0.56 0.56 0.53 0.53 0.33 0.51 0.66 0.72 
NL Phek Zunheboto Longleng Peren Mon Tuensang Wokha Kiphire Mokokchung Kohima Dimapur   
2021 0.83 0.79 0.78 0.78 0.75 0.72 0.71 0.67 0.65 0.49 0.36   
2015 0.75 0.60 0.52 0.59 0.64 0.55 0.53 0.56 0.50 0.82 0.75   
MZ Mamit Lawngtlai Champhai Lunglei Saiha Serchhip Kolasib Aizawl      
2021 0.82 0.69 0.59 0.48 0.47 0.45 0.36 0.05      
2015 0.53 0.48 0.95 0.70 0.93 0.85 0.73 0.16      
MEGH East Jantia Hills Ribhoi West Khasi Hills West Jaintia Hills South Garo Hills West Garo Hills East Garo Hills East Khasi Hills      
2021 0.89 0.78 0.77 0.72 0.71 0.68 0.66 0.41      
2015 0.72 0.59 0.75  0.67 0.46 0.37 0.82      
Manipur Senapati Chandel Tamenglong Churachandpur Ukhrul         
2021 0.75 0.66 0.65 0.64 0.63         
2015 0.60 0.56 0.52 0.54 0.53         
Assam Karbi Anglong Dima Hasao            
2021 0.55 0.39            
2015 0.31 0.27            
Tripura Dhalai             
2021 0.54             
2015 0.40             
Central and eastern India
Odisha Gajapati Nabarangapur Malkangiri Kandhamal Rayagada Mayurbhanj Koraput Sundargarh      
2021 0.47 0.47 0.44 0.42 0.42 0.35 0.35 0.26      
2015 0.25 0.30 0.27 0.23 0.24 0.31 0.22 0.37      
CG Uttar Bastar Kanker Jashpur Surguja Dantewada Bastar Narayanpur Bijapur       
2021 0.77 0.62 0.61 0.49 0.49 0.49 0.47       
2015 0.47 0.35 0.32 0.28 0.31 0.29 0.40       
MP Alirajpur Jhabua Barwani Dindori Mandla Dhar        
2021 0.80 0.62 0.59 0.56 0.55 0.31        
2015 0.35 0.35 0.38 0.24 0.25 0.44        
JH Simdega Lohardaga Khunti Gumla PashchimiSinghbhum         
2021 0.61 0.57 0.46 0.46 0.33         
2015 0.23 0.24 0.26 0.22 0.17         
Western region
Gujarat Tapi The Dangs Narmada Dohad Valsad         
2021 0.67 0.64 0.61 0.53 0.44         
2015 0.43 0.32 0.46 0.29 0.22         
RAJ Dungarpur Banswara Pratapgarh           
2021 0.75 0.69 0.56           
2015 0.56 0.49 0.36           
MH Nandurbar             
2021 0.43             
2015 0.35             
D&N D & Diu Dadra & Nagar Haveli             
2021 0.24             
2015 0.11             
Other regions
Ladakh Kargil Leh (Ladakh)            
2021 0.45 0.29            
2015 0.26 0.15            
HP Kinnaur Lahul & Spiti            
2021 0.81 0.65            
2015 0.57 0.48            
LKSDP Lakshadweep             
2021 0.05             
2015 0.04             
A&N Nicobars             
2021 0.80             
2015 0.76             
North-eastern
ArP Anjaw WestKameng Lower Subansiri Tawang Upper Siang Upper Subansiri West Siang Dibang Valley Tirap EastKameng East Siang KurungKumey Papum Pare 
2021 0.86 0.85 0.84 0.76 0.76 0.75 0.74 0.70 0.65 0.64 0.57 0.42 0.30 
2015 0.49 0.49 0.63 0.46 0.53 0.56 0.56 0.53 0.53 0.33 0.51 0.66 0.72 
NL Phek Zunheboto Longleng Peren Mon Tuensang Wokha Kiphire Mokokchung Kohima Dimapur   
2021 0.83 0.79 0.78 0.78 0.75 0.72 0.71 0.67 0.65 0.49 0.36   
2015 0.75 0.60 0.52 0.59 0.64 0.55 0.53 0.56 0.50 0.82 0.75   
MZ Mamit Lawngtlai Champhai Lunglei Saiha Serchhip Kolasib Aizawl      
2021 0.82 0.69 0.59 0.48 0.47 0.45 0.36 0.05      
2015 0.53 0.48 0.95 0.70 0.93 0.85 0.73 0.16      
MEGH East Jantia Hills Ribhoi West Khasi Hills West Jaintia Hills South Garo Hills West Garo Hills East Garo Hills East Khasi Hills      
2021 0.89 0.78 0.77 0.72 0.71 0.68 0.66 0.41      
2015 0.72 0.59 0.75  0.67 0.46 0.37 0.82      
Manipur Senapati Chandel Tamenglong Churachandpur Ukhrul         
2021 0.75 0.66 0.65 0.64 0.63         
2015 0.60 0.56 0.52 0.54 0.53         
Assam Karbi Anglong Dima Hasao            
2021 0.55 0.39            
2015 0.31 0.27            
Tripura Dhalai             
2021 0.54             
2015 0.40             
Central and eastern India
Odisha Gajapati Nabarangapur Malkangiri Kandhamal Rayagada Mayurbhanj Koraput Sundargarh      
2021 0.47 0.47 0.44 0.42 0.42 0.35 0.35 0.26      
2015 0.25 0.30 0.27 0.23 0.24 0.31 0.22 0.37      
CG Uttar Bastar Kanker Jashpur Surguja Dantewada Bastar Narayanpur Bijapur       
2021 0.77 0.62 0.61 0.49 0.49 0.49 0.47       
2015 0.47 0.35 0.32 0.28 0.31 0.29 0.40       
MP Alirajpur Jhabua Barwani Dindori Mandla Dhar        
2021 0.80 0.62 0.59 0.56 0.55 0.31        
2015 0.35 0.35 0.38 0.24 0.25 0.44        
JH Simdega Lohardaga Khunti Gumla PashchimiSinghbhum         
2021 0.61 0.57 0.46 0.46 0.33         
2015 0.23 0.24 0.26 0.22 0.17         
Western region
Gujarat Tapi The Dangs Narmada Dohad Valsad         
2021 0.67 0.64 0.61 0.53 0.44         
2015 0.43 0.32 0.46 0.29 0.22         
RAJ Dungarpur Banswara Pratapgarh           
2021 0.75 0.69 0.56           
2015 0.56 0.49 0.36           
MH Nandurbar             
2021 0.43             
2015 0.35             
D&N D & Diu Dadra & Nagar Haveli             
2021 0.24             
2015 0.11             
Other regions
Ladakh Kargil Leh (Ladakh)            
2021 0.45 0.29            
2015 0.26 0.15            
HP Kinnaur Lahul & Spiti            
2021 0.81 0.65            
2015 0.57 0.48            
LKSDP Lakshadweep             
2021 0.05             
2015 0.04             
A&N Nicobars             
2021 0.80             
2015 0.76             

India, being the second most populous country in the world, holds a unique position in terms of its contribution toward the SDGs, which every nation is striving to achieve. The country has made considerable progress toward SDG targets 6.1 and 6.2, which pertains to WASH, through various policy level and programmatic initiatives. Two key such initiatives are SBM and JJM)=. SBM, which was launched in 2014, aims to achieve an open defecation free India. The SBM, and particularly sub-mission SBM (Grammen), through mass scale behavior change, construction of household-owned and community-owned toilets, incentivization, and establishing mechanisms for monitoring toilet construction and usage, has helped 100 million rural households and 500 million residents in gaining access to toilets across 630,000 villages (Government of India n.d.; Ministry of Drinking Water & Sanitation 2018; Access to toilets n.d.). Reports indicate that 95% households have access to toilet and use them (Access to toilets n.d.; Government of India 2022a, 2022b). The phase-II of the SBM (Grammen) is also noteworthy in that it focuses on sustaining the gains made by providing access to toilet facilities to the newly emerging eligible rural households and solid and liquid waste management in the villages of the country in forthcoming years (2020–2025) (Government of India 2020). Before SBM, programs such as Central Rural Sanitation Program, Total Sanitation Campaign and Nirmal Bharat Abhiyan were in place to improve access to safe sanitation and cleanliness. However, these programs made some improvement at the ground level but fell short to achieve their targets (Report of the Comptroller & Auditor General of India 2015) and could not bring needful impact (Patil et al. 2014). The other initiative JJM, which subsumed the National Rural Drinking Water Program by its launch in 2019, is ensuring potable water in adequate quantity, of prescribed quality, with adequate pressure, on a regular and long-term basis to all rural households and public institutions. Under this mission, till March 2022, 102.3 million rural households (54%) have received the benefit of having tap water connections (Government of India 2022a, 2022b).

Tribal regions of the country have reaped the benefits of these programmatic interventions, which gets reflected in our findings. There were distinct improvements in key WASH indicators in tribal-dominated regions of the country between 2015 and 2021. One of the marked improvements was in terms of 50% fall seen in open defecation in the tribal regions (from 38% in 2015 to 19% in 2021), which is almost twice than the average drop seen in rural areas during the same time (54% in 2015 to 26% in 2021). A concurrent 26% increase in improved toilet facilities (from 44% in 2015 to 70% in 2021) was at par with the improvement seen in rural areas of the country (37% in 2015 to 64% in 2021) and indicated acceptance and usage of improved toilet facilities among tribal population. Though the coverage of improved source of water had further improved in tribal-dominated regions between 2015 and 2021, 70% of households did not have access to piped water supply, particularly to their home, with ramifications ranging from health issues to additional responsibilities which school going children, adolescent girls, and women member of the society need to bear on in terms of fetching water (UNICEF n.d). The WASH-related programmatic interventions equally focused on the behavior change component in their respective implementation strategies, and our findings showed an improvement in behaviors linked to the handwashing and treatment of drinking water. The increase in tribal households (14%) having both water and hand washing items (at hand washing place) was at par with the rural areas (50% in 2015 to 64% in 2021). A similar level of improvement in households practicing the treatment of drinking water was noticeable in the tribal regions. It is pertinent to note that the households having access to improved or unimproved drinking water source were engaged in treatment of drinking water, which is indicative of adoption of improved behavior and practice among the people.

However, improvement in these WASH indicators was not uniform across the tribal-dominated geographies with some districts performing very well while others not so in their coverage in the year 2021, which is evident in the ranking of these districts. There are possibilities that the variance in district performance could be due to the differences in the socio-economic status or the reach of the programmatic interventions. In relation to the socio-economic status, it would be apt to highlight here that close to 54% of the households across these districts fall in poorest or poor categories of the wealth quintile. However, the linkages between the socio-economic status and WASH performance get reflected at least in the case of top most and least performing districts though the pattern is not uniform as there are exceptional cases such as Papum Pare and Leh (among least performing category) and Kinnaur, Alirajpur, Phek, Mamit, and Nicobars (among top performing category). These exceptional cases possibly indicate toward better reach or implementation of the programmatic interventions, which gets further evident from the improved performance of these exceptional districts in comparison to 2015 (except Papum Pare). It is noteworthy that in comparison to 2015, 86% of the districts have shown an improvement over this time period further pointing toward the districts reaping the benefits of the programmatic interventions. The findings also pointed out toward 13 districts slipping in their performance in comparison to 2015. The reasons for the same would be difficult to establish given the limited WASH-related variables which are captured in the NFHS. The district-wise disaggregated analysis also pointed toward the wide range of district performance indicating that there is a still a scope of further improving the water and sanitation situation in the districts. However, the districts falling toward the bottom side of the ranking ladder require more attention and efforts of programmatic interventions.

Our analysis has certain limitations. There is no separate nationally representative comprehensive survey of the WASH situation in the tribal population. In its absence, the comparisons made with rural population may not be very apt. Further, the definition of some WASH indicators (as defined in NFHS) may not be in congruence with the definitions accepted in the international forums and thus needs to be understood with due diligence. For instance, public tap, standpipe, piped water in neighborhood, tanker truck or cart with small tank, are not considered as the improved sources of drinking water in safely managed drinking water services. Similarly, water availability criteria, i.e., continuously or at least 12 h per day or 4 days per week are not captured in the existing survey. With respect to sanitation, the improved facilities which are shared do not fall under the safely managed sanitation services. This points toward the need for incorporating the standardized and universally accepted WASH-related indicators in large-scale surveys that are carried out in the country. These limitations also point toward the scope of having a separate comprehensive survey among tribal population of the country. The inclusive, equitable and subset analysis would further facilitate in monitoring the WASH progress and taking up necessary action to be on track.

Providing and ensuring universal and equitable access to environmentally safe sanitation and affordable drinking water facilities to huge population, more so in tribal-dominated geographies, of the country are a challenging effort. The country has made an extraordinary achievement in the past 5 years and the gains of these achievements are well documented (Government of India 2017a, 2017b; UNICEF 2017; WHO 2018). However, the progress has to be sustained and further reinforced, should we aim to reach the SDG targets of 100% WASH coverage. The WASH ranking of the tribal-dominated districts is a useful tool to assess WASH coverage for prioritizing districts for WASH service coverage and for institution of definitive action. A package of interventions should be designed and implemented for the priority districts through the SBA platform in convergence with the relevant departments of Health, Tribal Affairs, Water and Sanitation, etc., which will set us on the path to achieving SDG WASH targets by 2030.

The authors declare that there is no financial support received.

All relevant data are available from an online repository or repositories: https://dhsprogram.com/dataset/India_Standard-DHS_2020.cfm?flag=0.

The authors declare there is no conflict.

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