Prevalence and factors associated with water, sanitation and hygiene (WASH) facilities deprivation among children in Nigeria

Abstract

Background

Water, sanitation, and hygiene (WASH) remain fundamental public health components for children's survival, growth, and development. In Nigeria, children under 18 years are most deprived of WASH, with about 70 per cent lacking access to facilities. There is paucity of information on factors associated with WASH facilities deprivation in Nigeria, especially in the context of children. Hence, this study examines the household and individual factors related to WASH facility deprivation among children 0–17 years old in Nigeria.

Method

A secondary analysis of the 2021 Nigeria Multiple Indicator Cluster Survey (MICS) was conducted to assess facility deprivations in WASH for children, along with associated determinants. A merged dataset comprising a total of 22,059 weighted observations from both the under-five children and children aged 5–17 years was used for this study. Frequency tables, pie charts and bar graphs were used to examine the prevalence of WASH facility deprivation among children. A Chi-square statistical test was performed to determine associated factors with child WASH facilities deprivation in Nigeria at a p-value of less than 0.05 level of significance.

Results

This study found that at least one-third of children in Nigeria were deprived of either one or more WASH facilities. Specifically, 32% were deprived of water, 40% were deprived of hygiene facilities and 67% were deprived of sanitation facilities. Children aged 5–9 (37.6%) were the most deprived of WASH facilities in Nigeria. Across all regions of the country, more children were deprived of sanitation when compared to water and hygiene. Overall, the wealth index and geopolitical zone significantly influenced access and availability of WASH facilities for children in Nigeria. Specifically, the education of the household head and wealth index are associated with access to sanitation facilities, place of residence is significantly associated with availability of water while access to hygiene facilities is significantly associated with the sex of the household head.

Conclusion

The study concludes that there is a correlation between factors and the increased likelihood of children experiencing WASH facilities deprivation. Although the influence of these factors increases based on determinants and varies by regional dimensions, there are still insufficient implementation practices where deprivation is minimal, and this is influenced by household and other factors.

Background

Water, sanitation, and hygiene (WASH) remain fundamental public health components critical for children’s survival, growth, and development of children [1]. This is further emphasized by their inclusion in the Sustainable Development Goals (SDGs). While significant progress has been made in achieving these goals in certain regions, disparities still exist, highlighting the need for continued efforts to ensure universal access to WASH for all children. In 2019, 71 out of 117 countries recorded more than 75% coverage of basic sanitation services in schools [2]. According to the Joint Monitoring Programme (JMP), over 2 billion people lacked access to safe drinking water, about 50% of the global population did not have safe sanitation, 2 billion lacked access to hand washing facilities with soap and 419 million practiced open defecation [3]. Sub-Saharan African countries contributed significantly to these figures as over 200 million people in the region practiced open defecation [4].

Countries like Nigeria contribute a significant proportion of the population deprived of WASH facilities as 28 per cent of Nigerians lack access to basic drinking water, about 75 per cent lack basic sanitation, two-thirds do not live in premises with a hand washing facility comprising soap and water, while 20 per cent practice open defecation [1, 5–7]. The study also found that the deprived population are more in rural areas and low-income communities.

In Nigeria, children under 18 years are most deprived with about 70 per cent lacking access to WASH facilities [8]. By regions, there is mixed evidence on WASH deprivations by region as the highest deprivation in drinking water and sanitation is observed in the northern region, while the Southwest region has the second highest proportion of open defecation and lack of hand washing facilities after the northern central region [1]. This lack of access to these WASH facilities contributes to the high burden of preventable diseases, hindering child development and survival. Comparatively, by place of residence, rural dwellers are more deprived of WASH services when compared to people resident in urban areas [9].

Amidst the challenges attributable to this menace is the high burden of WASH-related diseases including, but not limited to diarrhoea, skin and respiratory infections, malaria, malnutrition, and mortality [10]. Diarrhea, a major cause of death among children under five, thrives in environments with contaminated water and poor sanitation practices [11]. Studies have shown a strong association between poor WASH and childhood illnesses [12, 13]. A global report also captured that about 3 of every 4 diarrhoea disease burdens in Nigeria are traced to inadequate WASH [3]. In the same vein, Children from households without toilets are five times more likely to have malaria infection [14]. Also in Pakistan, it was specifically noted in a study that there is a significant association between the source of drinking water and male child malnutrition likewise between sanitation facilities and female child malnutrition [15]. In the same vein, WASH has been traced to children’s interest in schooling as children who lack access to water, have a higher tendency to lose interest in pursuing learning opportunities because they are forced to spend more time in search for water during school hours or stay out of school to recover from illness caused by frequent episodes of diarrhoea [16].

Although the inaccessibility of WASH facilities poses a challenge to the population with more burden on the dependent children, studies have relayed the positive influence of accessible WASH programs on key health and social outcomes [17]. A systematic review found that improved sanitation can decrease diarrhoea disease by 28%, with a significant difference in illness reduction based on the type of improved water and sanitation implemented [18]. In Cross River, the result shows that improved WASH facility has a higher tendency to reduce WASH-related health complications [19].

Based on previous works of literature, there have been studies that identified the factors associated with WASH deprivation in developing countries, at individual, household, and community levels (such as age, educational level, wealth status, media exposure, place of residence, and region) [15, 20, 21]. Some have highlighted the household-level determinants and WASH deprivation among slum-dwellers [22]. In addition, another scholar [23] was able to examine WASH deprivation among primary school pupils, while another research was done in the context of rural-dwelling Nigerian children [24–27]. However, there is paucity of information on factors associated with WASH deprivation in Nigeria, especially in the context of children (both at the individual and household level), using nationally representative data, especially the Multiple Indicator Cluster Survey (MICS). Hence, the importance of this study is to examine the factors associated with WASH facilities deprivation among children 0–17 years in Nigeria.

Methodology

Study and sampling design

A secondary analysis of the Nigeria Multiple Indicator Cluster Survey (MICS) 2021 was conducted to assess deprivations in WASH facilities for children, along with associated individual and household determinants. The MICS (2021) dataset utilized a multi-stage stratified cluster sampling methodology, employing an updated 2006 census enumeration areas (EAs) as its sampling frame. Primary sampling units (PSUs) were defined as clusters based on these EAs. A systematic sampling approach was applied, selecting 20 households per state, resulting in 1,850 clusters and 37,000 households across the entire MICS dataset. Data collection for the 2021 MICS employed questionnaires, encompassing five types: household; women; men; children under 5; and children (aged 5–17).

Study population

To derive the dataset for this study, the children (5–17 years) with the under-five child (0–4 years) and household and household member’s datasets were combined. The children and under-five datasets were merged based on a one-to-one merge. Thereafter, the resulting data was merged with a list of household members and household information datasets. All non-matched observations in the dataset were dropped from the analysis. Thus, in this study, a merged dataset comprising a total of 22,059 weighted observations was used for statistical analysis. This comprised slightly more than two-fifths of the national population. The survey provided comprehensive estimates of WASH indicators nationally, regionally, and across urban and rural areas.

Variables and measurements

Outcome variable

The outcome variable in this study is the child’s WASH facilities deprivation measured with three outcomes. Child WASH facilities deprivation was computed as a dichotomous variable (Child not deprived = 0, and Child deprived = 1). Table 1 shows the six key determinants of WASH variables which were selected individually and combined into one variable serving as the child WASH facilities deprivation. In measuring water facilities deprivation, the main source of drinking water (improved water) and the time to get the water were combined. The standard time of collecting water was benchmarked to 30 min on average. A child is considered deprived if he/she lacks access to both the time and source of water. For sanitation, two variables were utilized; the toilet type and the sharing of the toilet facility with members outside the household. The two variables were combined to denote a child deprived of quality sanitation. For hygiene, the availability of washing place, water and soap were all combined to denote hygiene facilities deprivation. Finally, all the individual variables were merged and classified as either deprived or not deprived.

Table 1.

Outcome variable description

WASH	Variable	Variable category	Variable question	Description
Water	Source of Drinking water	Categorical variables categorized as “improved” and” Unimproved”	What is the main source of drinking water used by members of your household?	Improved source of drinking water includes piped water, boreholes-protected dug wells, and packaged water such as table water. While unimproved sources are unprotected dug wells, spring wells, etc.
	Time to get the water from a closet water point	Numerical variables categorized as “Timely” and “Not timely”	How long does it take for members of your household to go there, get water, and come back?	Households able to get water in less than 30 min from a water point were categorized as “Timely” while otherwise which is above 30 min were categorized as “Not Timely”
Sanitation	Toilet facility type	The categorical variable that is categorized as “Availability of improved facility” and “Unavailable improved facility”	What kind of toilet facility do members of your household usually use?	Availability of improved facilities includes modern types of toilets which are water closets, ventilated improved pit latrines, etc. while Unavailability of improved facilities is characterized as unimproved traditional facilities such as pit latrines without slab, no toilet/bush, etc.
	Shared toilet facility	The categorical variable is categorized as “Not shared toilet facility” and “Shared toilet facility”	Do you share this facility with others who are not members of your household?	Indicating Yes connotes sharing toilet facility with members outside their household and otherwise connotes not toilet facility shared with household.
Hygiene	Availability of Water at the household hand-washing facility	The categorical variable that is categorized as “Available” and “Not available”	Observe the presence of water at the place for hand washing	Availability of part of the necessary equipment (water) for the effective functioning of the hand washing facility was termed available while otherwise was termed not available
	Availability of detergents at the household hand washing facility	The categorical variable is categorized as “Available” and “Not available”	Is soap or detergent or ash/mud/sand present at the place for hand washing?	Availability of soap or detergents for hand washing at the household hand washing section connotes availability and otherwise connotes not available.

Source: MICS, 2021

Independent variable

The independent variables for this study are grouped into two (individual level and household level) to examine and validate the extent to which each of the aforementioned factors influences the outcome variables. Individual level variables are; the age and sex of the child. Household-level variables include; house-related information such as place of residence, region of residence, and wealth index. It also includes household members, household size, number of children in the household, sex of household head, educational attainment of household head, and so on. Other mediating variables considered in the study that are important in determining the outcomes of the study include head of household exposure to mass media.

Statistical analysis

This study utilized the Stata 14 statistical software for data analysis, which involved three phases: univariate, bivariate, and multivariate analyses. The socio-demographic characteristics of the respondents were examined to understand the study population's profile and to organize and check the frequency distribution of respondents, weighted as specified. Outcome categorical variables were visually represented using pie charts. Invariable analyses were conducted to explore associations between independent and outcome variables of interest, focusing solely on these variables while disregarding others. The crude association between individual, household, and other factors and the level of child WASH deprivation was assessed using Chi-Square tests of association. Given that utilization measures and child WASH deprivation may be influenced by multiple factors simultaneously, multivariable analyses were performed. Binary Logistic Regression was employed for the multivariable analysis, incorporating variables that demonstrated significance (p < 0.05) at the bivariable level.

Results

Background characteristics of the respondents

A weighted total of 22,059 children ages 0 – 17 was accessed from the 2021 Multiple Indicator Cluster Survey (MICS) where about 37.5% of the children have their ages range from 5–8 years representing the majority. The results in Table 2 show that at least a fifth (20%) of the children were in middle childhood (9–11 years) and early adolescence (12–14 years). About 19.3% of the children were in the late adolescent (15–17 years) and less than 2% were under-five (0–4 years). Furthermore, an equal sex per cent of 50% were males and 50% were females. The majority of them have their household head to be Males (84%) and their ages range from 45–59 (37.3%). Also, the household heads majorly have a secondary level of education (32%) and a household size of about 1–5 members serving as the major (44%) characterizes of the households in which these children stay across all regions in Nigeria. The Northwest and South West regions were the major zones among the 6 geopolitical zones these children belong to (24% and 22% respectively). Additionally, these children’s household wealth index rages between the poorest (which is about 21%) and the richest (which is about 20%) and also reside majorly in rural areas (56%).

Table 2.

Percentage distribution of respondents by socio-demographics of the respondents

Variables	Frequency	Per cent
Childs agea
Under-five (0–4 years)	299	1.4
Early childhood (5–8 years)	8264	37.5
Middle childhood (9–11 years)	4789	21.7
Early adolescent (12–14 years)	4441	20.1
Late adolescent (15–17 years)	4263	19.3
Child sex
Male	11,039	50.1
Female	11,019	49.9
Age of household heada
15–24	207	0.9
25–34	2,265	10.3
35–44	6,567	29.8
45–59	8,222	37.3
60 and above	4,798	21.8
Sex of household head
Male	18,502	83.9
Female	3,557	16.1
Education of household heada
None	6,492	29.4
Primary	4,776	21.7
Secondary	6,951	31.5
Tertiary	3,839	17.4
Number of children
0–3	16,123	73.1
4–6	5,057	22.9
7 and above	879	4.0
Household size
1–5	9,781	44.3
6–9	9,441	42.8
10 and above	2,837	12.9
Wealth Indexa
Poorest	4,577	20.8
Second	4,163	18.9
Middle	4,366	19.8
Fourth	4,491	20.4
Richest	4,461	20.2
Geopolitical zone
North Central	3,302	15.0
North East	2,709	12.3
North West	5,332	24.2
South East	2,531	11.5
South South	3,389	15.4
South West	4,796	21.8
Place of residencea
Urban	9,744	44.2
Rural	12,314	55.8

^aMissing value deleted

Prevalence of WASH facilities deprivation for children in Nigeria

Table 3 shows different types of children’s WASH facilities derivation. In the context of children’s sanitation facilities deprivation, about 23.5% of children lack access to improved toilet facilities while 56.4% lack access to a place where household members most often wash their hands. In the context of water facilities derivation, at least a quarter (25.4%) lack access to the improved main source of drinking water. In terms of time taken (in minutes) to get water and come back, about 78.3% of the children were deprived of water. Furthermore, results on children’s hygiene deprivation revealed that 56.4% lack access to a place where household members most often wash their hands. About a quarter (25.2%) and a third (33.5%) lack access to water at the place for handwashing and soap/detergent at the place for handwashing respectively.

Table 3.

Percentage of types of WASH deprivation among children (0–17 years)

Type	Frequency	Percentage
Water deprivation
Main source of drinking
Not improved	5608	25.4
Improved	16451	74.6
Time (in minutes) to get water and come back
Not deprived	11729	78.3
Deprived	3260	21.7
Sanitation deprivation
Type of toilet facility
Not improved	5191	23.5
Improved	16867	76.5
Place for household members’ hand-washing
Not available	12432	56.4
Available	9627	43.6
Hygiene deprivation
A place for household members most often hand-washing
No	12432	56.4
Yes	9627	43.6
Water is available at a place for hand-washing
No	2426	25.2
Yes	7202	74.8
Soap/detergent present at a place for handwashing
No	3226	33.5
Yes	6401	66.5

Overall, in measuring the extent of water facilities deprivation, results in Fig. 1 revealed that about 33.9% of children were deprived of access to drinkable water in Nigeria. In the context of sanitation, about 63% of the children were deprived of access to improved toilet facilities that help eradicate the occurrence of diseases that are dangerous to their health. Additionally, the prevalence of children exposed to proper hygiene depicts that almost half (40%) were deprived. This further implies that in terms of access to proper sanitation, children between the ages of 0–17 are still at a high risk of being exposed to new and existing diseases that may deter the successful progress of their health.

Fig. 1.

Graphical representation of the percentage of WASH Deprivation among Children of 0–17 years

By combining all three deprivation factors into one variable, results in Fig. 2 show that most children (81.6%) were deprived of either water, sanitation or hygiene. This implies that a significant number of children in Nigeria are experiencing deprivation, especially in terms of access to improved sanitation facilities as well as quality hygiene facilities in their dwellings which may increase their likelihood of experiencing health challenges.

Fig. 2.

Prevalence of child water, sanitation and hygiene deprivation

In addition to this, Fig. 3 shows the percentages of WASH facilities deprivation according to the child’s age. The result revealed that children aged between 5 and 9 years (37.6%) were the most deprived of WASH facilities in Nigeria. This was followed by children aged 9–11 years (21.6%), 12–14 years (20.3%) and 15–17 years (19.4%).

Fig. 3.

Percentage of child's age by WASH facilities deprivation

Bivariable analysis

Individual factors

Table 4 shows that a child’s sex was not significant in determining the deprivation status of a child concerning sanitation, but there was a high proportion of sanitation facilities deprivation experienced by both males and females (70.6% and 71.1%) respectively. Similarly, the proportion of children deprived of water facilities was low (38.2% and 36.8%) among both the males and females respectively. Less than half proportion of the children (46.7% and 45.6%) males and females respectively suffered hygiene facilities deprivation. Overall, even though, a remarkable proportion of the children (73.6% and 73.3%) males and females respectively suffer from WASH facilities deprivation, however, child sex was not significant in determining the deprivation status of a child. The result also reveals a remarkable proportion (61.7%, 72.2%, and 69.1%) of the children in the respective age groups 0–4, 5–11, and 12–17 years respectively, suffered deprivation in terms of access to sanitation, and this deprivation was more in the age group 5–11 years. Significantly, the age of the child determined the deprivation status in terms of sanitation (p < 0.05). A low proportion (37.9%, 38.7%, and 35.6%) of the children in their respective age groups were reported to suffer water facilities deprivation. Similarly, children who suffered hygiene deprivation in the respective age groups were not significantly high (37.9%, 45.5%, and 47.1%) and age was not significant in determining this deprivation. Generally, a significant proportion (69.3%, 74.4%, and 72.0%) of the children in the different age groups suffer WASH facilities deprivation (p < 0.05).

Table 4.

Bivariate analysis of the factors associated with child water and sanitation deprivation

Factors	Sanitation			Water			Hygiene			WASH
	Child not deprived (%)	Child deprived (%)	Chi-square	Child not deprived (%)	Child deprived (%)	Chi-square	Child not deprived (%)	Child deprived (%)	Chi-square	Child not deprived (%)	Child deprived (%)	Chi-square
Individual factors
Child sex			0.56			4.87			1.15			0.25
Male	2,315(29.4)	5,559(70.6)		7,077(61.8)	4,376(38.2)		2,454(53.3)	2,151(46.7)		3,025(26.4)	8,428(73.6)
Female	2,273(28.9)	5,603(71.1)		7,113(63.2)	4,140(36.8)		2,449(54.4)	2,052(45.6)		3,005(26.7)	8,248(73.3)
Childs age			24.34**			21.28**			4.20			19.03*
0–4 years	67(38.3)	108(61.7)		154(62.1)	94(37.9)		49(62.0)	30(38.0)		76(30.7)	172(69.3)
5–11 years	2573(27.8)	6686(72.2)		8228(61.3)	5199(38.7)		2896(54.4)	2427(45.6)		3427(25.5)	10000(74.5)
12–17 years	1948(30.9)	4364(69.1)		5806(64.3)	3221(35.7)		1958(52.9)	1745(47.1)		2527(28.0)	6500(72.0)
Household factors
Age of household head			64.48*			88.51*			13.09*			42.03*
15–24	25(17.7)	116(82.3)		115(51.3)	109(48.7)		35(43.2)	46(56.8)		40(17.9)	184(82.1)
25–34	330(21.3)	1218(78.7)		1345(54.8)	1109(45.2)		431(49.8)	435(50.2)		535(21.8)	1919(78.2)
35–44	1336(29.6)	3181(70.4)		4094(63.3)	2373(36.7)		1405(55.3)	1136(44.7)		1753(27.1)	4714(72.9)
45–59	1804(30.9)	4027(69.1)		5269(63.0)	3099(37.0)		1895(54.6)	1576(45.4)		2290(27.4)	6078(72.6)
60 +	1093(29.4)	2620(70.6)		3367(64.8)	1826(35.2)		1137(52.8)	1010(47.0)		1412(27.2)	3781(72.8)
Sex of household head			4.44			73.20*			0.04			50.41*
Male	3,846(28.8)	9505(71.2)		11668(61.3)	7370(38.7)		4059(53.8)	3486(46.2)		4882(25.6)	14156(74.4)
Female	742(30.9)	1657(69.1)		2522(68.8)	1146(31.2)		844(54.1)	717(45.9)		1148(31.3)	2520(68.7)
Education of household head			0.01			727.71*			343.34*			883.21*
None	627(13.4)	4051(86.6)		3979(52.5)	3600(47.5)		1148(45.7)	1365(54.3)		1431(18.9)	6148(81.1)
Primary	768(23.6)	2491(76.4)		3070(61.1)	1952(38.9)		1003(47.5)	1110(52.5)		1208(24.1)	3814(75.9)
Secondary	1450(30.7)	3268(69.3)		4395(66.9)	2173(33.1)		1460(54.3)	1229(45.7)		1789(27.2)	4779(72,8)
Tertiary	1743(29.1)	1352(43.7)		2746(77.6)	791(22.4)		1292(72.1)	499(27.9)		1602(45.3)	1935(54.7)
Household size			143.73*			189.37*			23.96**			211.30*
1–5	2148(33.0)	4355(67.0)		6398(66.9)	3167(33.1)		2222(56.8)	1691(43.2)		2941(30.7)	6624(69.3)
6–9	1933(28.7)	4813(71.4)		5990(61.1)	3815(38.9)		2010(51.7)	1875(48.3)		2479(25.3)	7326(74.7)
10 +	507(20.3)	1994(79.7)		1802(54.0)	1534(46.0)		671(51.3)	637(48.7)		610(18.3)	2726(81.7)
Number of children			117.39*			73.03*			16.15**			141.25*
0–3	3484(31.6)	7534(68.4)		10353(64.0)	5772(35.8)		3605(55.2)	2931(44.8)		4621(28.7)	11504(71.3)
4–6	947(24.1)	2977(75.9)		3259(58.8)	2284(41.2)		1084(50.4)	1068(49.6)		1238(22.3)	4305(77.7)
7 and above	157(19.4)	651(80.6)		578(55.7)	460(44.3)		214(51.2)	204(48.8)		171(16.5)	867(83.5)
Wealth index			0.01			4.00			817.01*			0.01
Poorest	175(7.7)	2198(92.6)		2015(35.1)	3721(64.9)		605(36.1)	1073(63.9)		935(16.3)	4801(83.7)
Second	275(8.8)	2856(91.2)		2706(52.9)	2412(47.1)		864(45.7)	1027(54.3)		999(19.5)	4119(80.5)
Middle	737(19.9)	2960(80.1)		3414(69.5)	1501(30.5)		962(48.7)	1012(51.3)		1175(23.9)	3740(76.1)
Fourth	1216(33.2)	2446(66.8)		3337(82.9)	688(17.1)		1071(58.3)	765(41.7)		1062(26.4)	2963(73.6)
Richest	2185(75.7)	702(24.3)		2718(93.3)	194(6.7)		1401(81.1)	326(18.9)		1859(63.8)	1053(36.2)
Geopolitical zone			1.20			889.28*			662.60*			0.01
North Central	1102(45.6)	1313(54.4)		2874(61.2)	1821(38.8)		674(56.2)	525(43.8)		1819(38.7)	2876(61.3)
North East	536(16.8)	2656(83,2)		2215(51.8)	2060(48.2)		737(42.1)	1014(57.9)		604(14.1)	3671(85.9)
North West	561(14.8)	3240(85.2)		2708(55.1)	2167(44.5)		1114(57.8)	815(42.2)		682(14.0)	4193(86.0)
South East	808(43.1)	1068(56.9)		1935(69.2)	861(30.8)		811(55.8)	642(44.2)		907(32.4)	1889(67.6)
South South	771(32.4)	1608(67.6)		2012(64.7)	1097(35.3)		636(38.4)	1020(61.6)		802(25.8)	2307(74.2)
South West	810(38.8)	1277(61.2)		2446(82.8)	510(17.2)		931(83.3)	187(16.7)		1216(41.1)	1740(58.9)
Place of residence			635.88*			0.01			295.30*			472.19*
Urban	2565(40.2)	3817(59.8)		5957(85.5)	1013(14.5)		2141(65.9)	1108(34.1)		2518(36.1)	4452(63.9)
Rural	2023(29.1)	7345(78.4)		8233(52.3)	7503(47.7)		2762(47.2)	3095(52.8)		3512(22.3)	12224(77.7)
Other factors
Exposure to media			288.11*			508.34*			114.98*			122.83*
No	108(8.5)	1170(91.5)		1121(42.5)	1516(57.5)		301(36.2)	531(63.8)		464(17.6)	2173(82.4)
Yes	4480(31.0)	9992(69.0)		13,069(65.1)	7000(34.9)		4602(55.6)	3672(44.4)		5566(27.7)	14,503(72.3)

^*p < 0.01

^**p < 0.05

Household factors

The age of the household head was significant in determining the deprivation status of a child relative to sanitation facilities. Children suffer sanitation facilities deprivation (82.2%, 78.6%, 70.4%, 69.0%, and 70.5%) across the different age groups 15–24, 25–34, 35–44, 45–59, and 60 + of the household head but was relatively high in the younger age groups. Also, the household head’ age was significant in determining the facilities deprivation of a child concerning access to water (p < 0.05). Although the proportion (48.6%, 45.1%, 36.6%, 37.0%, and 35.1%) of children deprived access to water was not significantly high as opposed to those not deprived, the children whose household heads were in the younger age groups has a larger share of water facilities deprivation. Furthermore, children whose household heads were in the younger age groups 15–24 and 25–34 had a significant proportion (56.7% and 50.2%) of hygiene facilities deprivation compared to other age groups, and the age of household heads was also significant to determining the deprivation status of a child (p < 0.05). Overall, children suffer WASH facility deprivation in a large proportion (82.1%, 78.2%, 72.8%, 72.6%, and 72.8%) across the different age groups of the household head but with a large proportion in the younger age groups, and household head’ age has a significant hold on the deprivation status of a child (p < 0.05).

The result also shows that children whose household heads were males suffered high (71.1%) sanitation deprivation compared to those headed by females (69.0%), and household head’ sex was significant in determining deprivation status (p < 0.05). Children whose household heads were males experienced more deprivation (38.7%) in terms of access to water significantly compared to those who had female household heads (31.2%) (p < 0.05). Deprivation in terms of hygiene was experienced almost in the same proportion (male – 46.2% and female – 45.9%) by children relative to their household head’s sex. The sex of the household head significantly determines the deprivation status of a child (p < 0.05) and statistically, children whose household heads are males have a higher proportion (74.3%) of being deprived compared to those who are females (68.7%).

The education of the household head significantly determines the sanitation facilities deprivation status of a child. Children whose household head has no education and primary education have a high proportion (86.6% and 76.4%) respectively of deprivation compared to those with secondary and tertiary education (69.2% and 43.6%). Also, the education of the household head significantly determines the water deprivation of a child (p < 0.05). Children with a household head who has no education suffered water deprivation more (47.5%) compared to others. Household head with no education, primary education, and secondary education (54.2%, 52.2%, and 45.7%) respectively exposed their children to hygiene facilities deprivation compared to those with tertiary education (27.8%). Children who suffer deprivation most are those whose household heads have no education and primary education (81.1% and 75.5%) respectively. Howbeit, child deprivation decreases as the education level of the household head increases. This implies that the level of education of the household head significantly determines the deprivation experience of a child (p < 0.05).

The household size is also a significant determinant of child sanitation deprivation (p < 0.05). There was a high proportion (66.9%, 71.3%, and 79.7%) of children deprived of sanitation facilities with a high reported incidence in households whose sizes were 10 and above. More so, the proportion of (33.1%, 38.9%, and 45.9%) children deprived of access to water varied across the classified household sizes (1–5, 6–9, and 10 +) but with more share of deprivation in a household with more than ten individuals. Similarly, children with more than 10 household sizes have a large share (48.7%) of hygiene deprivation compared to (43.2% and 48.2%) of other household sizes. Generally, a significant determinant of child deprivation is the household size and a larger proportion (81.7%) of child deprivation is experienced in households whose size is above 10. This implies that the larger the size of the household, the higher the level of deprivation. Significantly, the number of children that a household has influenced the level of child sanitation facilities deprivation. A high proportion (68.3%, 75.8%, and 80.5%) of children were observed to be deprived of sanitation based on the number of children in the household (0–3, 4–6, and more than 7). Albeit a higher proportion was observed in households with 7 or more children.

Few proportions of children were deprived of water when considered by household size (35.8%, 41.2%, and 44.3%) as opposed to those who were not deprived, however, households with 7 or more children had the highest deprivation. Similarly, children who experienced hygiene deprivation were few (44.84%, 49.6%, and 48.8%) as opposed to those not deprived. Overall, the number of children a household has significantly determines their level of deprivation and this deprivation varied across the different household children size (p < 0.05). Children experienced a high proportion (83.5%) of deprivation in households with children of size 7 and above compared to the proportion (69.2% and 74.7%) of those with children sizes 0–3 and 4–6. This implies that deprivation increases in response to the increase in household children size.

The results show that the household wealth index significantly determines the deprivation status of a child in terms of sanitation facilities (p < 0.05). A high proportion (92.6%, 91.2%, 80.0%, and 66.7%) of children are deprived of sanitation across the different wealth class indexes (poorest, second, middle, and fourth) except the richest which has a low proportion (24.3%) of deprivation. More so, children whose household wealth status index fell in the poorest category experienced a high proportion (64.8%) of water deprivation compared to other household wealth status indexes. A high proportion (63.9%, 54.3%, and 51.2%) of children in the wealth class – poorest, second, and middle experienced hygiene deprivation more compared to the other wealth class – fourth and richest. Largely, the wealth class of a household significantly impact the level of deprivation experienced by the children. More so, a large proportion (83.7%, 80.4%, 76.0%, and 73.6%) of children in the household wealth class of poorest, second, middle, and fourth experienced deprivation more compared to children (36.1%) in the richest class. Significantly, the level of child deprivation decreases as the wealth status of a household increases.

Child sanitation deprivation varied significantly across different geopolitical zones, but a higher proportion (85.2%) was observed in the North West zone (p < 0.05). More so, child water deprivation was reported in a low proportion (38.9%, 48.1%, 44.4%, 30.7%, 35.2%, and 17.2%) across the six geo-political zones, however, the North East zone has a higher incidence of deprivation compared to others. The proportion (57.9% and 61.5%) of children who experienced child hygiene deprivation in North East and South South zones respectively was high compared to other geo-political zones. Generally, the six geo-political zones significantly experience deprivation in all aspects of water, sanitation, and hygiene. Statistically, the North West zone is observed to have a high proportion (86.1%) of deprivation compared to other zones.

The place of residence of a household significantly determines the deprivation of a child in terms of sanitation (p < 0.05). Children who live in rural areas experience a high proportion (78.4%) of sanitation facilities deprivation compared to those in urban areas (59.8%). A low proportion (14.5% and 47.6%) of children in the urban and rural areas respectively experience water facilities deprivation as opposed to those who are not deprived. However, the deprivation was still high in the rural areas. Children in the rural areas have a large proportion (52.8%) of hygiene deprivation compared to those in the urban areas (34.1%). Overall, the place of residence significantly affects the deprivation status of a child. Children who are in rural areas suffer deprivation more (77.6%) compared to those in urban areas (63.8%). This implies that facility deprivation is experienced in both areas, but there is a decline in it when households transit from rural to urban areas.

Other factors

The results reveal that exposure to media has a significant impact on the deprivation status of a child in terms of sanitation (p < 0.05). Children who are not exposed to media have a larger proportion (91.5%) of being deprived of access to sanitation as opposed to those who are exposed to media (69.0%). Similarly, children who are not exposed to media have a large proportion (57.4%) of water deprivation compared to those who are exposed (34.8%). More so, a large proportion (63.8%) of children who suffer hygiene facilities deprivation are not exposed to media compared to those who are exposed to media (44.3%). Largely, exposure to media significantly influences the deprivation status of a child, and children who are not exposed to media have a large proportion (82.4%).

Multivariable analysis

Results in Table 5 show the binary logistic regression analysis of factors influencing WASH facilities deprivation among children in Nigeria. The results showed a statistically significant association between a child’s age and water, sanitation, and hygiene (WASH) facilities deprivation. For example, WASH deprivation was significantly associated positively with children age 5–8 years (AOR = 6.6, [95%CI = 4.3, 10.2]; p < 0.05), 9–11 years (AOR = 6.9, [95%CI = 4.5, 10.7]; p < 0.05), 12–14 years (AOR = 7.9, [95%CI = 5.1, 12.2]; p < 0.05); and 15–17 years (AOR = 7.5, [95%CI = 4.9, 11.6]; p < 0.05) compared with children aged 0–4 years. Concerning the sex of the household head, the result showed that female child has lower odds of water deprivation (AOR = 0.9, [95%CI = 0.8, 0.9]; p < 0.05), hygiene deprivation (AOR = 0.8, [95%CI = 0.7, 0.9]; p < 0.05), and WASH facilities deprivation (AOR = 0.87, [95%CI = 0.8, 1.0]; p < 0.05) compared with male child. Furthermore, the odds ratio of water facilities deprivation is statistically significantly associated with the educational level of the household head. There was a negative relationship between educational level and WASH facilities deprivation. Household heads with tertiary education are less likely to experience WASH facilities deprivation (AOR = 0.7, [95%CI = 0.7, 0.8]; p < 0.05) compared with households with no education. In terms of household size, the odds of WASH facilities deprivation were higher among children in household size 6–9 (AOR = 1.1, [95%CI = 1.0, 1.3]; p < 0.05), and 10 and above (AOR = 1.2, [95%CI = 1.0, 1.5]; p < 0.05) compared with household size 1–5 children. Similarly, the odds of water facilities deprivation were higher among children in household size 6–9 (AOR = 1.2, [95%CI = 1.1, 1.3]; p < 0.05), and 10 and above (AOR = 1.6, [95%CI = 1.4, 1.8]; p < 0.05) compared with household size 1–5 children. Also, water facilities deprivation is negatively associated family with a high number of children. For example, the odds of water facilities deprivation were lower among families with 4–6 children (AOR = 0.9, [95%CI = 0.8, 0.9]; p < 0.05) and 7 and above (AOR = 0.8, [95%CI = 0.6, 0.9]; p < 0.05) compare with family with 0–3 number of children. Also, place of residence was positively significantly associated with place of residence. The odds of water, sanitation and WASH facilities deprivation were higher in the rural areas than in urban areas. Similarly, the odds of water, sanitation, hygiene and WASH facilities deprivation were negatively associated with the wealth index. For instance, richest are less likely to be water deprived (AOR = 0.1, [95%CI = 0.1, 0.1]; p < 0.05), sanitation deprived (AOR = 0.1, [95%CI = 0.8, 0.1]; p < 0.05), hygiene deprived (AOR = 0.14, [95%CI = 0.1, 0.2]; p < 0.05) and WASH deprived (AOR = 0.4, [95%CI = 0.3, 0.4]; p < 0.05). Finally, there was a statistically significant association between geo-political zone and water, sanitation, hygiene and WASH facilities deprivation.

Table 5.

Multivariate analysis of the factors associated with child WASH deprivation in Nigeria

Factors	Water deprivation AOR (95% CI)	Sanitation AOR (95% CI)	Hygiene AOR (95% CI)	WASH AOR (95% CI
Childs Age
0–4 years	1.0 (RC)	(RC)	(RC)	1.0 (RC)
5–8 years	2.78 (2.11, 3.67)***	1.76 (1.29, 2.41)***	3.52 (2.14, 5.80)***	6.60 (4.29, 10.15)***
9–11 years	2.82 (2.13, 3.73)***	1.73 (1.26, 2.37)**	3.69 (2.24, 6.10)***	6.94 (4.49, 10.70)***
12–14 years	2.85 (2.15, 3.77)***	1.91 (1.39, 2.63)***	4.08 (2.47, 6.75)***	7.87 (5.09, 12.17)***
15–17 years	2.89 (2.18, 3.84)***	1.82 (1.32, 2.50)***	3.99 (2.41, 6.61)***	7.51 (4.86, 11.61)***
Child sex
Male	(RC)	(RC)	(RC)	1.0 (RC)
Female	0.95 (0.90, 1.01)	1.02 (0.96, 1.08)	0.95 (0.87, 1.04)	0.97 (4.86, 1.05)
Age of household head
15–24	(RC)	(RC)	(RC)	1.0 (RC)
25–34	1.03 (0.76, 1.40)	1.12 (0.80, 1.57)	0.99 (1.61, 1.61)	1.49 (0.92, 2.42)
35–44	0.89 (0.66, 1.20)	1.03 (0.74, 1.43)	0.91 (0.57, 1.46)	1.18 (0.74, 1.90)
45–59	0.86 (0.64, 1.15)	0.92 (0.66, 1.27)	0.87 (0.54, 1.40)	1.11 (0.69, 1.77)
60 and above	0.78 (0.58, 1.05)	0.87 (0.62, 1.21)	0.84 (0.53, 1.36)	1.07 (0.67, 1.72)
Sex of household head
Male	(RC)	(RC)	(RC)	1.0 (RC)
Female	0.85 (0.78, 0.94)**	0.98 (0.89, 1.07)	0.82 (0.72, 0.93)**	0.87 (0.77, 0.98)**
Education of household head
None	(RC)	(RC)	(RC)	1.0 (RC)
Primary	1.12 (1.03, 1.22)*	0.81 (0.74, 0.89)***	%1.%2 (0.89, 1.16)	0.96 (0.84, 1.11)
Secondary	1.17 (1.07, 1.28)**	0.92 (0.83, 1.01)***	0.93 (0.81, 1.07)	0.97 (0.85, 1.12)
Tertiary	1.20 (1.07, 1.35)**	0.72 (0.64, 0.80)***	0.66 (0.56, 0.78)***	0.67 (0.58, 0.77)***
Number of children
0–3	(RC)	(RC)	(RC)	1.0 (RC)
4–6	0.86 (0.79, 0.94)**	1.0 (0.92, 1.10)	%1.%2 (0.90, 1.17)	1.01 (0.89, 1.14)
7 and Above	0.77 (0.64, 0.92)**	0.92 (0.77, 1.11)	1.03 (0.79, 1.36)	0.89 (0.69, 1.15)
Household size
1–5	(RC)	(RC)	(RC)	1.0 (RC)
6–9	1.16 (1.07, 1.25)***	1.0 (0.93, 1.08)	1.09 (0.97, 1.22)	1.14 (1.03, 1.26)**
10 +	1.61 (1.41, 1.84)***	1.00 (0.88, 1.15)	1.10 (0.89, 1.34)	1.23 (1.02, 1.48)**
Wealth index
Poorest	(RC)	(RC)	(RC)	1.0 (RC)
Second	0.45 (0.42, 0.49)***	0.44 (0.40, 0.49)***	0.60 (0.52, 0.70)***	0.32 (0.26, 0.39)***
Middle	0.26 (0.24, 0.29)***	0.32 (0.30, 0.37)***	0.53 (0.45, 0.62)***	0.21 (0.17, 0.25)***
Fourth’	0.14 (0.13, 0.16)***	0.20 (0.18, 0.23)***	0.37 (0.32, 0.44)***	0.11 (0.89, 0.13)***
Richest	0.06 (0.05, 0.07)***	0.09 (0.82, 0.11)***	0.14 (0.11, 0.17)***	0.04 (0.28, 0.44)***
Geopolitical zone
North Central	(RC)	(RC)	(RC)	1.0 (RC)
North East	1.08 (0.98, 1.19)	0.23 (0.20, 0.25)***	1.16 (0.99, 1.36)	0.45 (0.38, 0.52)***
North West	0.87 (0.79, 0.96)**	0.22 (0.19, 0.24)***	0.60 (0.51, 0.71)***	0.29 (0.25, 0.34)***
South East	0.87 (0.78, 0.98)*	0.32 (0.29, 0.36)***	1.01 (0.85, 1.19)	0.54 (0.46, 0.63)***
South South	1.17 (1.05, 1.30)**	0.28 (0.25, 0.31)***	2.18 (1.84, 2.57)***	0.69 (0.59, 0.80)***
South West	0.64 (0.56, 0.73)***	0.73 (0.64, 0.82)***	0.31 (0.25, 0.39)***	0.54 (0.46, 0.62)***
Place of residence
Urban	(RC)	(RC)	(RC)	1.0 (RC)
Rural	2.08 (1.90, 2.27)***	1.32 (1.22, 1.43)***	0.87 (0.77, 0.98)	1.30 (1.18, 1.44)***

^*p < 0.01

^**p < 0.05

^***p < 0.001

Discussion of findings

In examining water and sanitation dimensions it was revealed that the prevalence of children deprived of quality sanitation was more prominent (63%) followed by hygiene which seems somewhat close to half of the children deprived (40%) amidst the three factors when examined separately. Also, combining the three cogent factors there was a high prevalence of child deprivation at 81.6%. This indicates that many children in Nigeria largely lack access to at least one component of WASH facilities. Contributing factors include exposure to unfavourable environments, adversely affecting child health. Supporting this, the Nigeria Poverty Map indicates that 46.5% of Nigerians are multidimensional poor and lack access to improved sanitation facilities [28]. A study in Lagos found that 18.7% of slums suffer from severe sanitation deprivation, forcing residents to live in unhealthy conditions [29]. Poverty exacerbates this issue, limiting access to quality housing conducive to children's health. The COVID-19 pandemic temporarily improved hygiene awareness [30, 31], but maintaining these practices remains challenging, resulting in continued child deprivation of quality sanitation and hygiene. Previous studies identified several barriers to sanitation improvement: lack of understanding and awareness, insufficient infrastructure, poor waste management, and household poverty [32, 33].

Despite reported improvements in basic hygiene accessibility from 32% in 2010 to 42% in 2018 due to WASH programs [34], children still face significant deprivation. The goal of reducing mortality rates related to poor hygiene and environmental pollution by 2030 remains unmet. In 2022, 46 million Nigerians practised open defecation, leading to approximately 100,000 under-five deaths [35, 36]. Projections suggest that by 2030, basic sanitation and hygiene coverage in sub-Saharan Africa, including Nigeria, might not exceed 38% due to demographic, environmental, and related factors [37, 38].

Considering the objective of this study, which was to understand the association between WASH deprivation and individual and household factors, it was revealed that household factors had a greater significance compared to individual factors. Among individual factors, the child's age was the only significant factor(p < 0.05) at the bivariate level common to most of the dependent variables except for the hygiene behaviour in which none of the individual factors was significant (p > 0.05). The possible reasons for this distinction may be subject to other variables such as the knowledge of the child on hygiene as compared to their age or sex. In alignment with this possibility, [39, 40] mentioned that limited access to knowledge about hygiene is an important determinant of child hygiene behavioural practice.

Household factors play a significant role in determining whether children experience deprivation in WASHWASH, as highlighted in this study. Variables such as the age of the household head, level of education of the household head, household size, and number of children, wealth index, geopolitical zone, and place of residence emerged as significant factors in the bivariate analysis. This finding aligns with [41], who noted that heads of households under 25 years were more likely to have children drinking unimproved water or using unimproved toilet facilities. However, further analysis revealed that when these three dependent variables are combined, the age and education of the household head were not significantly associated with a child experiencing water and sanitation deprivation. This implies that the importance of these factors was limited to the individual context of the three variables and not when combined. Specifically, household heads with primary and secondary education were more likely, respectively, to deprive their children of WASH, whereas those with tertiary education had the lowest percentages of their children being deprived.

Denoting that the significance of the level of education influences the proximity of a child deprived as occasions of this decrease as the education level of the household head increases across the three dependent variables. This may be because individuals with primary education might prioritize sanitation for their children more, believing that disease prevention is cost-effective given their financial constraints. In contrast, those with advanced education might understand the importance of sanitation but may not prioritize it as highly, resulting in a higher likelihood of their children experiencing deprivation. In contrast, a study in Nigeria by [42] found that higher education levels of the household head significantly determined the use of improved toilet facilities. These results suggest that a higher level of education does not necessarily guarantee that a child will be free from water and sanitation deprivation. Future studies may explore these findings when examining the determinants of water and sanitation outcomes.

Notably, household size, number of children, geopolitical zone and residence exhibited consistent associations, indicating that larger households with a greater number of children and households having their residence in rural areas increase the susceptibility of the children to experience WASH deprivation. Interestingly findings from this study revealed that the wealth index had higher percentages of child deprivation but its significance was not consistent in the context of water deprivation. Possibly due to the method by which this variable was measured by the secondary data and which preempts care to be taken while interpreting the result.

Nonetheless, the wealth index remained and most of the household factors remained constantly significant when the three dependent variables were combined. For instance, households between 4–6 and 7 and above children have lower chances of avoiding WASH deprivation compared to those with 1–3 children. Similarly, households classified in the poorest and second wealth quintiles have higher percentages of children experiencing WASH deprivation compared to those in the richest quintile (ranging from 80%-83%). This suggests that higher wealth status enhances the likelihood of children not experiencing WASH deprivation, potentially due to increased resources available for household needs and survival. This corroborates with the findings of a recent study in which having an improved economic status and living condition creates a high propensity for the use of basic WASH facilities hence reducing the level of deprivation accruing to a child [29, 43, 44], Aside from this, having an improved access to the WASH facilities will as well aid in the prevention of diarrhea among children which aligns with the thoughts observed in previous studies [45, 46] Moreover, households with access to media showed 21% lower odds of children experiencing WASH deprivation, further reinforcing the role of information access in mitigating these challenges [44–46]. These findings all accentuate the importance of socioeconomic factors and media exposure in shaping children's WASH outcomes.

Conclusion

This study concludes that there is a correlation between household factors and the increased likelihood of children experiencing WASH deprivation. While households often possess adequate information, their implementation practices may be insufficient, heightening the risk of disease transmission due to poor hygiene. Therefore, raising awareness about simplified sanitation and hygiene practices which are more prevalent in this study could significantly enhance awareness and behavioural patterns that benefit children's well-being.

Furthermore, a higher level of prevalence was observed in the context of sanitation deprivation among children from 0–17 years in all the regions of the country. This underscores the necessity for targeted financial and strategic interventions in these regions to mitigate this significant prevalence. Failure to address these could hinder progress towards national targets and global priorities such as the Sustainable Development Goals (SDGs), potentially exacerbating under-five mortality rates. Thus, addressing all three WASH components in the context of deprivation, especially sanitation among children is crucial not only for reducing child mortality but also for advancing national and global development objectives.

Limitation of study

This study utilized a large, nationally representative MICS dataset (n = 95,044) to assess WASH practices. While the data is subjectively reported and may introduce bias, limitations include reliance on available variables and the cross-sectional design, which prevents causal inferences.

Abbreviations

UNICEF

United Nations Children’s Fund

WASH

Water, Sanitation, and Hygiene

MICS

Multiple Indicator Cluster Survey

SDGs

Sustainable Development Goals

EAs

Enumeration Areas

PSUs

Sampling frame. Primary sampling units

NBS

National Bureau of Statistics

Authors’ contributions

C.V., F.F.O., and J.A.K. conceptualised and designed the study. VOS and CV analysed the data. CV, JAK and FFO draft the manuscript. All authors did discussion of the findings, and critical reviews and approved the manuscript.

Funding

The authors received no funding for this work.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

The study used de-identified MICS data sets. The 2021 Nigeria MICS data sets are publicly available. Thus, the use of the data sets did not require further ethical approval and consent to participate. However, permission to use the MICS datasets was sought and granted by the National Bureau of Statistics (NBS) [Nigeria] and the United Nations Children’s Fund (UNICEF). Details concerning the data, ethical approval and consent to participate are available at: https://mics.unicef.org/tools#survey-design.

Consent for publication

Not applicable because a person’s data is not included.

Competing interests

The authors declare no competing interests.