Abstract

In sub-Saharan countries, where a large number of populations depend on unsafe water, household water treatment is the recommended means to reduce diarrhea. However, the practice in the region is very low. The current study is intended to assess the households' water treatment using adequate methods, boiling, adding bleach, filtration and solar disinfection, and associated factors in the region which will be an input to design and implement intervention strategies. The Demographic and Health Survey (DHS) data conducted from 2013 to 2016 in 23 sub-Saharan countries were obtained from the DHS program and weighted using the ‘svy’ command for analysis. The households' reported use of treatment methods and associated factors were analyzed using log-binomial regression. In total, 357,979 households were included in the analysis of which 29% used unimproved water for drinking purposes. Households reportedly treating water in the region were 22% and those who used adequate treatment methods were 18%. The households' reported use of adequate treatment methods was statistically associated with household head education, owning a radio and wealth quintiles. The treatment methods' use is low in the region therefore intervention on wide-scale use should be designed and implemented.

INTRODUCTION

Globally, 663 million people depend on unimproved sources and about 2.1 billion use contaminated water (WHO/UNICEF 2015). In addition, there is a range of studies that show post-collection contamination of water, despite their collection from improved sources (Bain et al. 2014; Shaheed et al. 2014). In sub-Saharan Africa, only 41% of the population uses a water source that is free from contamination and only 24% use safely managed water sources (WHO/UNICEF 2017).

Diarrhea continues to be the leading cause of mortality and morbidity in the world with the highest share in the least developed countries (WHO/UNICEF 2015; Troeger et al. 2018). A recent study shows that it is the eighth leading cause of death for all age groups and the fifth leading cause in children below five years (Troeger et al. 2018). In sub-Saharan countries, where the disease burden is high, the proportion of morbidity in the age group of below five years ranged from 10 to 35% (Bado et al. 2016). Lack of safe water is one of the leading risk factors for diarrhea to occur (Troeger et al. 2018).

Household water treatment coupled with safe storage can reduce the risk of diarrheal disease (WHO 2019). Water treatment at the household level can also minimize the risk of recontamination that even improved water supply can present (Wright et al. 2004). The household treatment methods recommended to be used are different chlorine-based disinfectants, filtration, solar disinfection, and boiling (Sobsey et al. 2008). These treatment methods are characterized as adequate based on their microbiological effectiveness (WHO & UNICEF 2006). Their effectiveness is acknowledged in some sub-Saharan countries (Crump et al. 2004, 2005; Mengistie et al. 2013; Mohamed et al. 2016; Bitew et al. 2018).

In regions like sub-Sahara, where the provision of improved water to all segments of the population is a challenge, the wide-scale use of the treatment methods at the household level is anticipated to reduce the burden of diarrhea associated with unsafe water use (Rosa & Clasen 2010). However, only a small number of households used it, and the consistency in use is dropping over time (Waddington et al. 2009; Brown & Clasen 2012). Only 18.2% of households in Africa treat water at the household level despite the fact that it is a region with the highest number of populations dependent on unimproved water sources (Rosa & Clasen 2010; WHO/UNICEF 2015).

Thus, in the region where nearly 60% of populations and about 24% of the population respectively use improved and safely managed drinking water sources (WHO/UNICEF 2015), facilitating households to use adequate water treatment methods is imperative to reduce the associated health problems. This can be ensured through identifying and addressing factors associated with use. In this regard, a few independent studies using Demographic and Health Survey (DHS) data were conducted to indicate the household treatment practices and associated factors (Wright & Gundry 2009; Geremew et al. 2018b). The current study is, therefore, intended to assess the households' reported use of adequate water treatment methods and associated factors using the DHS data in the region from 2013 to 2016. The findings would help policymakers and other stakeholders to design and implement appropriate strategies for wide-scale use of the treatment options.

METHODS

Data source

We used the data of DHS conducted between 2013 and 2016/17 in 23 countries. Namely, Angola, Benin, Burundi, Chad, Congo Democratic Republic, Ethiopia, Gambia, Ghana, Kenya, Lesotho, Liberia, Malawi, Mozambique, Namibia, Nigeria, Rwanda, Sierra Leon, South Africa, Togo, Tanzania, Uganda, Zambia, and Zimbabwe. DHS are nationally representative, cross-sectional household surveys (DHS 2009). Typically, around 5,000–30,000 households were sampled using a multilevel cluster survey design and mostly information was obtained by individuals' self-report (Corsi et al. 2012). The questionnaires are adapted for different settings but are comparable between countries (Footman et al. 2015). The data were obtained through online registration on the MEASURE DHS program.

Study variables

In the DHS, households were asked about water treatment practices at the household level using the statement ‘Do you do anything to make water cleaner before drinking it?’ Those households responded ‘yes’ to the question were asked about the type of treatment methods they reportedly used. The outcome of this study was, therefore, the households' reported use of adequate water treatment methods. The categorization of households into a reported user of adequate treatment methods or not is based on the response of households to the DHS questions ‘What do you usually do to make the water safer to drink?’ Households reportedly used either bleach, boiling, filtration and solar disinfection (SODIS) or all (WHO & UNICEF 2006) and were considered as a reported user of adequate treatment methods and non-user otherwise. Thus, households in each country reportedly using either or all of the mentioned treatment methods were considered a yes (1) and no otherwise (0 = if the household had used none of them).

Although the factors associated with the use of water, sanitation, and hygiene technologies are various, categorized into contextual, psychosocial, and product-related (Dreibelbis et al. 2013), only contextual factors are available in the DHS data and these were considered for the current analysis. They are education status of household head, presence of children below five years in the house, owning radio and television, wealth categorized into five quintiles (poorest, poorer, middle, higher and highest), type of water source (improved versus unimproved), and residency (urban, rural). The data of associated factors were taken directly as they were in the DHS data set. The method of analysis for variables such as wealth quintiles was based on the PCA using the household assets as indicated elsewhere (Croft et al. 2018). We categorized some variables such as drinking water sources as improved and unimproved following the WHO/UNICEF guide (WHO & UNICEF 2006).

Data analysis

The ‘svy’ command in Stata 14.0 (Stata Corp, College Station, Texas, USA) was used to weight the survey data for the adjustment of cluster sampling design in the merged data set of 23 countries. The weighted data were analyzed descriptively using frequency and percentage. We used the prevalence ratio (log-binomial regression) to determine associated factors with households' reported water treatment as the odds ratio overestimates the factors when the outcome of interest exceeds 10% prevalence (in our case 18%) (Greenland 2004). Bivariate regression was applied to determine the unadjusted effects of each of the variables on household water treatment. We then subsequently included the variables for multivariable regression to assess the independent effect after controlling other variables. The significant association of predictor variables was considered at p-value <0.05. Multicollinearity diagnostic was conducted to check the interaction of factors and exclude using the variance inflation factor of greater than 10.

RESULTS

Household number and survey year

Table 1 indicates the number of households included in the survey and the survey year. The DHS survey year for Congo DR, the Gambia, Liberia, Namibia, Nigeria, Sierra Leone, Togo, and Zambia was 2013. In Chad, Ghana, Kenya, Lesotho, and Rwanda, the survey was in 2014. Similarly, 2015 was the survey year for Angola, Malawi, Mozambique, Tanzania, and Zimbabwe. Lastly, 2016 was a survey year for Benin, Burundi, Ethiopia, South Africa, and Uganda.

Table 1

The number of households included in respective countries and survey year, DHS 2013–2016

Year of survey Country Number of households, n 
2013 Congo (DR) 18,171 
Gambia 6,217 
Liberia 9,333 
Namibia 9,849 
Nigeria 38,522 
Sierra Leone 12,629 
Togo 9,549 
Zambia 15,920 
2014 Chad 17,233 
Ghana 11,835 
Kenya 36,430 
Lesotho 9,402 
Rwanda 12,699 
2015 Angola 16,109 
Malawi 26,361 
Mozambique 7,169 
Tanzania 12,563 
Zimbabwe 10,534 
2016 Benin 14,156 
Burundi 15,977 
Ethiopia 16,650 
South-Africa 11,083 
Uganda 19,588 
 Total 357,979 
Year of survey Country Number of households, n 
2013 Congo (DR) 18,171 
Gambia 6,217 
Liberia 9,333 
Namibia 9,849 
Nigeria 38,522 
Sierra Leone 12,629 
Togo 9,549 
Zambia 15,920 
2014 Chad 17,233 
Ghana 11,835 
Kenya 36,430 
Lesotho 9,402 
Rwanda 12,699 
2015 Angola 16,109 
Malawi 26,361 
Mozambique 7,169 
Tanzania 12,563 
Zimbabwe 10,534 
2016 Benin 14,156 
Burundi 15,977 
Ethiopia 16,650 
South-Africa 11,083 
Uganda 19,588 
 Total 357,979 

Characteristics of households

Table 2 shows the characteristics of households surveyed in the region. More than 60% of households resided in rural areas, 45% of households owned a radio and 29% owned a television. More than a quarter of households of the 23 countries use unimproved drinking water sources and about one-fifth of the households walk for more than 30 minutes to collect water.

Table 2

The characteristics of households in sub-Saharan countries of pooled DHS data surveyed in 2013–2016

Characteristics Category Weighted frequency and percentage 
Household head education status No education 102,735 (28.92) 
Primary 126,848 (35.71) 
Secondary 96,289 (27.11) 
Higher 29,361 (8.27) 
Residency of households Urban 116,023 (37.47) 
Rural 193,652 (62.53) 
Wealth status of households Poorest 70,201 (19.61) 
Poorer 69,964 (19.54) 
Middle 69,912 (19.53) 
Higher 72,583 (20.28) 
Highest 75,320 (21.04) 
Owned radio No 162,952 (45.53) 
Yes 194,982 (54.47) 
Owned television No 253,590 (70.85) 
Yes 104,319 (29.15) 
Water source type Improved 254,782 (71.19) 
Unimproved 103,109 (28.81) 
Water source distance In the premises 69,156 (23.44) 
Within 30 minutes 165,58 (56.14) 
More than 30 minutes 56,236 (19.06) 
Characteristics Category Weighted frequency and percentage 
Household head education status No education 102,735 (28.92) 
Primary 126,848 (35.71) 
Secondary 96,289 (27.11) 
Higher 29,361 (8.27) 
Residency of households Urban 116,023 (37.47) 
Rural 193,652 (62.53) 
Wealth status of households Poorest 70,201 (19.61) 
Poorer 69,964 (19.54) 
Middle 69,912 (19.53) 
Higher 72,583 (20.28) 
Highest 75,320 (21.04) 
Owned radio No 162,952 (45.53) 
Yes 194,982 (54.47) 
Owned television No 253,590 (70.85) 
Yes 104,319 (29.15) 
Water source type Improved 254,782 (71.19) 
Unimproved 103,109 (28.81) 
Water source distance In the premises 69,156 (23.44) 
Within 30 minutes 165,58 (56.14) 
More than 30 minutes 56,236 (19.06) 

Household drinking water sources and treatment practices

Figure 1 shows the drinking water sources and water treatment practices. In total, 103,109 households (29%) used unimproved water sources for drinking purposes. The number of households dependent on unimproved water sources ranged from 8% in South Africa to 51% in the Democratic Republic of the Congo. More than three-fifths of households that used improved water sources for drinking purposes and reportedly treated at household level were located in Kenya, Rwanda, Tanzania, and Uganda. Four countries where three-quarters of improved water source user households reportedly treated using adequate treatment methods were Angola, Kenya, Rwanda, and Uganda. In twelve countries, below one-tenth of households used improved water sources for drinking purpose and reportedly treated water at the household level. Of the twelve countries where the lowest number of households reported treated, the least number was shown in Benin and Burundi.

Figure 1

Households using improved water sources and reportedly treating water at household level in sub-Saharan countries, DHS 2013–2016.

Figure 1

Households using improved water sources and reportedly treating water at household level in sub-Saharan countries, DHS 2013–2016.

Household reported water treatment practices versus drinking water source

The highest number of households that depended on unimproved water and reportedly treated their water at household level was found in the Gambia (68.5%) and Uganda (64.9%). The least number of households that depended on unimproved water sources and reportedly treated water was in the Democratic Republic of the Congo (1.7%). The adequate treatment methods use among households dependent on unimproved water sources was highest in Uganda followed by Kenya and Rwanda, and lowest in the Democratic Republic of the Congo (Table 3).

Table 3

Household drinking water sources versus treatment practices in sub-Saharan countries based on DHS 2013–2016

Country Household water treatment practice
 
Among improved water source
 
Among unimproved water source
 
Reportedly treat, n (%) Reportedly used adequate method, n (%) Reportedly treat, n (%) Reportedly used adequate method, n (%) 
Angola 3,289 (38.57) 3,188 (37.39) 2,008 (26.48) 1,944 (25.64) 
Benin 495 (4.91) 111 (1.10) 604 (14.83) 221 (5.43) 
Burundi 645 (4.87) 463 (3.50) 139 (5.07) 73 (2.66) 
Chad 1,078 (11.32) 915 (9.61) 640 (8.34) 483 (6.30) 
Congo (DR) 546 (6.17) 467 (5.27) 155 (1.67) 112 (1.20) 
Ethiopia 819 (7.59) 653 (6.05) 613 (10.46) 365 (6.24) 
Gambia 582 (10.32) 125 (2.20) 384 (68.54) 42 (7.48) 
Ghana 603 (5.68) 286 (2.69) 185 (15.30) 36 (2.98) 
Kenya 11,974 (46.09) 11,455 (44.09) 4,651 (44.54) 4,347 (41.62) 
Lesotho 1,020 (12.99) 966 (12.29) 174 (11.26) 111 (7.21) 
Liberia 1,127 (16.62) 854 (12.59) 224 (8.76) 128 (5.00) 
Malawi 7,048 (30.67) 5,330 (23.20) 1,164 (34.38) 908 (26.82) 
Mozambique 627 (13.94) 253 (5.63) 159 (5.98) 86 (3.22) 
Namibia 719 (8.40) 668 (7.80) 193 (15.10) 176 (13.79) 
Nigeria 2,594 (10.14) 1,356 (5.30) 1,684 (13.00) 313 (2.41) 
Rwanda 4,391 (47.42) 4,324 (46.70) 1,260 (36.68) 1,231 (35.84) 
Sierra Leon 1,471 (19.21) 1,267 (16.55) 286 (5.74) 190 (3.82) 
South-Africa 801 (7.83) 727 (7.11) 84 (9.83) 73 (8.52) 
Tanzania 3,243 (41.81) 2,051 (26.43) 1,585 (32.98) 884(18.41) 
Togo 645 (9.98) 445 (6.88) 484 (15.75) 180 (5.85) 
Uganda 7,779 (50.62) 7,281 (47.38) 2,695 (63.87) 2,483 (58.86) 
Zambia 3,857 (37.54) 3,748 (36.48) 1,503 (26.77) 1,436 (25.56) 
Zimbabwe 1,141 (13.85) 1,088 (13.21) 388 (16.87) 327 (14.21) 
Total 56,493 (22.18) 48,019 (18. 85) 21,260 (20.62) 16,150 (15.66) 
Country Household water treatment practice
 
Among improved water source
 
Among unimproved water source
 
Reportedly treat, n (%) Reportedly used adequate method, n (%) Reportedly treat, n (%) Reportedly used adequate method, n (%) 
Angola 3,289 (38.57) 3,188 (37.39) 2,008 (26.48) 1,944 (25.64) 
Benin 495 (4.91) 111 (1.10) 604 (14.83) 221 (5.43) 
Burundi 645 (4.87) 463 (3.50) 139 (5.07) 73 (2.66) 
Chad 1,078 (11.32) 915 (9.61) 640 (8.34) 483 (6.30) 
Congo (DR) 546 (6.17) 467 (5.27) 155 (1.67) 112 (1.20) 
Ethiopia 819 (7.59) 653 (6.05) 613 (10.46) 365 (6.24) 
Gambia 582 (10.32) 125 (2.20) 384 (68.54) 42 (7.48) 
Ghana 603 (5.68) 286 (2.69) 185 (15.30) 36 (2.98) 
Kenya 11,974 (46.09) 11,455 (44.09) 4,651 (44.54) 4,347 (41.62) 
Lesotho 1,020 (12.99) 966 (12.29) 174 (11.26) 111 (7.21) 
Liberia 1,127 (16.62) 854 (12.59) 224 (8.76) 128 (5.00) 
Malawi 7,048 (30.67) 5,330 (23.20) 1,164 (34.38) 908 (26.82) 
Mozambique 627 (13.94) 253 (5.63) 159 (5.98) 86 (3.22) 
Namibia 719 (8.40) 668 (7.80) 193 (15.10) 176 (13.79) 
Nigeria 2,594 (10.14) 1,356 (5.30) 1,684 (13.00) 313 (2.41) 
Rwanda 4,391 (47.42) 4,324 (46.70) 1,260 (36.68) 1,231 (35.84) 
Sierra Leon 1,471 (19.21) 1,267 (16.55) 286 (5.74) 190 (3.82) 
South-Africa 801 (7.83) 727 (7.11) 84 (9.83) 73 (8.52) 
Tanzania 3,243 (41.81) 2,051 (26.43) 1,585 (32.98) 884(18.41) 
Togo 645 (9.98) 445 (6.88) 484 (15.75) 180 (5.85) 
Uganda 7,779 (50.62) 7,281 (47.38) 2,695 (63.87) 2,483 (58.86) 
Zambia 3,857 (37.54) 3,748 (36.48) 1,503 (26.77) 1,436 (25.56) 
Zimbabwe 1,141 (13.85) 1,088 (13.21) 388 (16.87) 327 (14.21) 
Total 56,493 (22.18) 48,019 (18. 85) 21,260 (20.62) 16,150 (15.66) 

In total, 56,494 (22%) of households that used improved water sources reportedly treated their water and 48,019 (19%) of households reportedly treated using adequate treatment methods. Of unimproved water source users, 21,260 (21%) reportedly treated and 16,150 (16%) used adequate treatment methods. The overall reported use of treatment methods in the region was 22% and the reported use of adequate treatment methods was 18%. The reported use of adequate treatment use was higher in Kenya, Rwanda, and Uganda compared to others. Below one-tenths of households in twelve countries reportedly treated water at the household level with the lowest number in Benin (2.3%), the Gambia (2.7%) and Ghana (2.7%) (Table 3).

Type of treatment methods reportedly used

The types of treatment methods that the households reportedly used to treat water were boiling, bleach, filter, SODIS, let the water stand and settle, cloth straining, and other methods with the respective percentages of 10.81, 8.64, 0.79, 0.07, 1.25, 1.69, and 1.82%. Boiling shares the highest number (41%) with more than 50% of households reportedly treating water in each of seven countries (Burundi, Lesotho, Namibia, Nigeria, Tanzania, Togo, and Uganda). The highest number of the use of boiling occurred in Lesotho (87%), Uganda (82%), and Rwanda (80%). The lowest number occurred in Benin, Gambia, and Liberia. In nine countries (Angola, Chad, Congo, Liberia, Malawi Sierra Leon, Togo, Zambia, and Zimbabwe), more than half of households reportedly treated water using bleach. The high number of reported use of bleach was indicated in Liberia and the lowest was in Burundi. Of the adequate treatment methods, SODIS is reportedly used by a small number of households and is never used in three countries (Burundi, Lesotho, and Namibia). Let it stand and settle and cloth straining respectively ranked third and fourth for the households in the region (Figure 2).

Figure 2

Type of treatment methods reportedly used by households in sub-Saharan countries, DHS 2013–2016.

Figure 2

Type of treatment methods reportedly used by households in sub-Saharan countries, DHS 2013–2016.

Factors associated with household water treatment using adequate treatment methods

The binary log-binomial regression shows that the proportion of households that used adequate treatment methods was higher among those households that owned a radio, a television, had an educated household head or were in the richer and richest wealth quintile. On the other hand, the ratio of adequate water treatment use between households that depend on improved and unimproved water sources did not vary significantly. In addition, there is no significant difference among households of having children under five years old and dwelling in urban or rural areas in the reported use of adequate treatment methods (Table 4).

Table 4

The binary and multivariable log-binomial regression on factors associated with household water treatment using adequate treatment methods in sub-Saharan countries, DHS 2013–2016

Characteristics Category Households use adequate treatment methods, n (%)
 
CRR, 95% CI ARR, 95% CI 
No Yes 
Owned radio Noa 141,735 21,217 
Yes 152,025 42,958 1.66 (1.37, 2.01) 1.17 (1.01, 1.36) 
Owned television Noa 215,000 38,589 
Yes 78,743 25,575 1.62 (1.07, 2.44) 0.81 (0.55, 1.20) 
Household wealth quintile Pooresta 64,076 6,125 
Poorer 60,829 9,135 1.47 (1.22, 1.77) 1.40 (1.16, 1.69) 
Middle 58,224 11,688 1.91 (1.43, 2.55) 1.86 (1.37, 2.53) 
Richer 57,297 15,285 2.51 (1.80, 3.48) 2.57 (1.77, 3.75) 
Richest 53,371 21,949 3.59 (2.53, 5.10) 3.87 (2.19, 6.84) 
House head education status Noa 94,178 8,557 
Primary 100,877 25,970 2.32 (1.86, 2.89) 2.02 (1.55, 2.63) 
Secondary 76,563 19,726 2.34 (1.59, 3.43) 1.78 (1.28, 2.47) 
Higher 20,104 9,257 3.74 (2.68, 5.20) 2.20 (1.56, 3.10) 
Household residency Urbana 87,235 28,788 
Rural 159,705 33,947 0.69 (0.47, 1.00) 1.14 (0.80, 1.61) 
Children presence in the house Noa 133,647 29,921 
Yes 160,150 34,262 0.98 (0.86, 1.10) 1.10 (0.97, 1.24) 
Water source type Improveda 206,763 48,019 
Unimproved 86,959 16,150 0.86 (0.68, 1.10) 1.31 (0.99, 1.75) 
Characteristics Category Households use adequate treatment methods, n (%)
 
CRR, 95% CI ARR, 95% CI 
No Yes 
Owned radio Noa 141,735 21,217 
Yes 152,025 42,958 1.66 (1.37, 2.01) 1.17 (1.01, 1.36) 
Owned television Noa 215,000 38,589 
Yes 78,743 25,575 1.62 (1.07, 2.44) 0.81 (0.55, 1.20) 
Household wealth quintile Pooresta 64,076 6,125 
Poorer 60,829 9,135 1.47 (1.22, 1.77) 1.40 (1.16, 1.69) 
Middle 58,224 11,688 1.91 (1.43, 2.55) 1.86 (1.37, 2.53) 
Richer 57,297 15,285 2.51 (1.80, 3.48) 2.57 (1.77, 3.75) 
Richest 53,371 21,949 3.59 (2.53, 5.10) 3.87 (2.19, 6.84) 
House head education status Noa 94,178 8,557 
Primary 100,877 25,970 2.32 (1.86, 2.89) 2.02 (1.55, 2.63) 
Secondary 76,563 19,726 2.34 (1.59, 3.43) 1.78 (1.28, 2.47) 
Higher 20,104 9,257 3.74 (2.68, 5.20) 2.20 (1.56, 3.10) 
Household residency Urbana 87,235 28,788 
Rural 159,705 33,947 0.69 (0.47, 1.00) 1.14 (0.80, 1.61) 
Children presence in the house Noa 133,647 29,921 
Yes 160,150 34,262 0.98 (0.86, 1.10) 1.10 (0.97, 1.24) 
Water source type Improveda 206,763 48,019 
Unimproved 86,959 16,150 0.86 (0.68, 1.10) 1.31 (0.99, 1.75) 

aCRR = Crude risk ratio, ARR = adjusted risk ratio, CI = confidence interval.

The multivariable regression indicates that the proportion of households using adequate treatment methods to treat the water at the household level is significantly associated with owning a radio (ARR = 1.17, 95% CI = 1.01, 1.36). The number of households using adequate treatment methods in the richer and richest wealth quintiles is respectively 2.57 (95% CI = 1.77, 3.75) and 3.87 (95% CI = 2.19, 6.84) times higher compared to those households in the poorest wealth quintile (Table 4).

DISCUSSION

The overall reported water treatment at the household level in 23 countries was 22% and the reported water treatment using adequate methods was 18%. Based on the water sources that households depend on, 22 and 21% respectively were the number of improved and unimproved water source users reportedly treating water. Our finding was inconsistent with a prior study that shows that about 29% of households dependent on an improved water source and 27% of households dependent on unimproved water sources reportedly treat their drinking water at the household level (Rosa & Clasen 2010). The reported use of water treatment methods in the region is low despite the preponderance of diarrhea associated with water safety (Troeger et al. 2018). The overall reported use would have been higher to reduce the burden that could be from unimproved water sources, post-collection contamination and the presence of pathogens, even in improved water sources (Bain et al. 2014; Shaheed et al. 2014).

The use of adequate treatment methods did not differ significantly among households living in urban and rural areas although households in the rural area mostly depend on unimproved water sources. The current results did not corroborate a prior study that shows caregivers dwelling in urban areas were more likely to treat their water than those in a rural dwelling (Geremew et al. 2018a). The treatment methods use was lower among households with a non-educated household head, in the poorest wealth quintile that did not own a radio where the suffering from diarrhea is highly likely. The finding complies with two independent studies of DHS data that show household water treatment is high among households with an educated household head and high wealth quintiles (Wright & Gundry 2009; Geremew et al. 2018b).

The reported water treatment did not differ considerably between households using improved and unimproved water sources and unimproved sources. This could be from a low perception about the quality of unimproved water as prior findings indicate that households perceived poor water quality was more likely to treat (Jain et al. 2014; Onjala et al. 2014). In addition, the household reported that the use of adequate treatment methods did not differ among households that had or had no children below the age of five years, despite evidence that diarrheal disease associated with unsafe water in this age group is high (Troeger et al. 2018). The results suggest much work is needed to improve the accessibility of products and behavior interventions for wide-scale use of treatment methods in the region (Figueroa & Kincaid 2010).

The number of households reportedly treating water varies from country to country. Those countries with more than 30% of households reportedly treating water with adequate treatment methods were Angola, Ghana, Nigeria, Togo, and Zambia. Less than one-tenth of households reportedly treat water with adequate treatment methods in twelve countries. When we compare our findings with prior findings on thirteen countries included in the survey, there was a slight increment (Rosa & Clasen 2010).

The reported use of boiling, bleach, filter, and SODIS respectively is 10.81, 8.64, 0.79 and 0.07% despite their reliability and effectiveness as indicated in prior studies (Clasen 2009; Clasen et al. 2015). The current finding also implies that support and promotion by NGOs, international agencies and governments are still remaining (Clasen et al. 2007, 2015). The overall use of adequate treatment methods is higher than a prior report in 22 African countries based on the number of populations that show that 10.6% treat their drinking water at the household level (Rosa & Clasen 2010).

Boiling is a more predominant treatment method with over 41% of households overall reportedly using it. It is commonly used in ten countries and more than 80% of households used boiling in Lesotho, Rwanda, and Uganda. A small number of households reportedly used boiling compared to bleach in Benin, Gambia, and Liberia with only about 1% of households compared to other countries. The preference for boiling compared with other methods complies with prior assessments in some African countries that show that many prefer to use traditional methods, including boiling rather than chemical methods (PATH 2010). In addition, the common use of boiling compared to other adequate treatment options in the region is consistent with previous findings (Rosa & Clasen 2010). The number of households reportedly using bleach as a treatment method accounts for 38% of reportedly treating water. The overall use of the products is about 8% which makes it the second highest next to boiling. Of the 23 countries, 13 were reportedly predominant users of bleach compared to others including boiling. In total, a small number of households' reported use could be because of different factors, mainly taste, accessibility and affordability as indicated elsewhere (Olembo et al. 2004; Luby et al. 2008; DuBois et al. 2010).

SODIS is the least popular treatment method, reportedly used by only 0.3% of households despite preceding studies that reported that SODIS is effective in reducing diarrhea in children (Asiimwe et al. 2013; Bitew et al. 2018). The three countries where SODIS is not reportedly used were Burundi, Lesotho, and Namibia. Of the countries reportedly using SODIS, Liberia is the country with the highest number of reported users. The small number of households reporting the use of SODIS in the region suggests the need for appropriate intervention methods like household promotion in combination with persuasion which was found to be effective in changing the behavior of households to use the treatment in Zimbabwe (Mosler et al. 2013).

STRENGTHS AND LIMITATIONS

The current study has the following strengths: (1) The survey in each country is conducted every five years by taking representative samples, hence, the representativeness of the data is high. In addition, analysis of data after pooling would show the situation of household water treatment practices in the region. The limitations of the study are: (1) We used survey data which is liable to biases and the factors and outcomes fail to show cause and effect relationships. (2) The current findings could not show the actual use of products as it was a self-reported use. (3) Only contextual factors were available in the DHS dataset, therefore it did not comprehensively show all potential factors.

CONCLUSIONS

Below one-fifth of households reportedly treat their water using adequate treatment methods in the region. Boiling and adding bleach are the predominant methods compared to others. The reported use of treatment methods is high among households with educated household heads, which owned a radio, and were in high wealth quintiles. Interventions that take into account the context of the countries should be designed and implemented for wide-scale use of treatment methods.

ETHICS APPROVAL

We followed the principles and procedures of the MEASURE DHS Program. Each of the surveys was conducted after ethical clearance was obtained from the appropriate Ethics Review Committee of the country.

AVAILABILITY OF DATA

The datasets used and/or analyzed during the current study belong to the DHS program.

ACKNOWLEDGEMENTS

We would like to thank Measure DHS for providing the dataset.

REFERENCES

REFERENCES
Bain
R.
,
Cronk
R.
,
Wright
J.
,
Yang
H.
,
Slaymaker
T.
&
Bartram
J.
2014
Fecal contamination of drinking-water in low-and middle-income countries: a systematic review and meta-analysis
.
PLoS Med.
11
(
5
),
e1001644
.
Clasen
T.
2009
Scaling up Household Water Treatment among Low-Income Populations
.
World Health Organization
,
Geneva
.
Clasen
T.
,
Schmidt
W.-P.
,
Rabie
T.
,
Roberts
I.
&
Cairncross
S.
2007
Interventions to improve water quality for preventing diarrhoea: systematic review and meta-analysis
.
Br. Med. J.
334
(
7597
),
782
.
Clasen
T. F.
,
Alexander
K. T.
,
Sinclair
D.
,
Boisson
S.
,
Peletz
R.
,
Chang
H. H.
,
Majorin
F.
&
Cairncross
S.
2015
Interventions to improve water quality for preventing diarrhoea
.
Cochrane Database Syst. Rev.
10
,
1
180
.
Corsi
D. J.
,
Neuman
M.
,
Finlay
J. E.
&
Subramanian
S.
2012
Demographic and Health Surveys: a profile
.
Int. J. Epidemiol.
41
(
6
),
1602
1613
.
Croft
T. N.
,
Marshall
A. M.
&
Allen
C. K.
2018
Guide to DHS Statistics
.
ICF
,
Rockville, Maryland
,
USA
.
DHS
2009
Demographic and Health Surveys, Quality Information to Plan, Monitor, and Improve Population, Health, and Nutrition Programs© 2008 Erberto Zani, Courtesy of Photoshare
.
MEASURE DHS, The DHS Program
. ).
DuBois
A. E.
,
Crump
J. A.
,
Keswick
B. H.
,
Slutsker
L.
,
Quick
R. E.
,
Vulule
J. M.
&
Luby
S. P.
2010
Determinants of use of household-level water chlorination products in rural Kenya, 2003–2005
.
Int. J. Environ. Res. Public Health
7
(
10
),
3842
3852
.
Figueroa
M. E.
&
Kincaid
D. L.
2010
Social, Cultural and Behavioral Correlates of Household Water Treatment and Storage. HCenter Publication HCI 2010-1: Health Communication Insights
.
Johns Hopkins Bloomberg School of Public Health, Center for Communication Programs
,
Baltimore
.
Geremew
A.
,
Mengistie
B.
,
Alemayehu
E.
,
Lantagne
D. S.
,
Mellor
J.
&
Sahilu
G.
2018a
Point-of-use water chlorination among urban and rural households with under-five year children: a comparative study in Kersa Health and Demographic Surveillance Site, Eastern Ethiopia
.
J. Water Sanit. Hyg. Dev.
8
(
3
),
468
480
.
Geremew
A.
,
Mengistie
B.
,
Mellor
J.
,
Lantagne
D. S.
,
Alemayehu
E.
&
Sahilum
G.
2018b
Appropriate household water treatment methods in Ethiopia: household use and associated factors based on 2005, 2011, and 2016 EDHS data
.
Environ. Health Prevent. Med.
23
(
1
),
46
.
Luby
S. P.
,
Mendoza
C.
,
Keswick
B. H.
,
Chiller
T. M.
&
Hoekstra
R. M.
2008
Difficulties in bringing point-of-use water treatment to scale in rural Guatemala
.
Am. J. Trop. Med. Hyg.
78
(
3
),
382
387
.
Mohamed
H.
,
Clasen
T.
,
Njee
R. M.
,
Malebo
H. M.
,
Mbuligwe
S.
&
Brown
J.
2016
Microbiological effectiveness of household water treatment technologies under field use conditions in rural Tanzania
.
Trop. Med. Int. Health
21
(
1
),
33
40
.
Mosler
H.
,
Kraemer
S.
&
Johnston
R.
2013
Achieving long-term use of solar water disinfection in Zimbabwe
.
Public Health
127
(
1
),
92
98
.
Olembo
L.
,
Kaona
F.
,
Tuba
M.
&
Burnham
G.
2004
Safe Water Systems: An Evaluation of the Zambia CLORIN Program (Final Report)
.
Zambia
. ).
Onjala
J.
,
Ndiritu
S. W.
&
Stage
J.
2014
Risk perception, choice of drinking water and water treatment: evidence from Kenyan towns
.
J. Water Sanit. Hyg. Dev.
4
(
2
),
268
280
.
PATH
2010
Market Assessment of Household Water Treatment Products in Eight African Countries, Project Brief
.
Program for Appropriate Technology in Health (PATH)
,
Seattle, Washington, DC
,
USA
.
Shaheed
A.
,
Orgill
J.
,
Ratana
C.
,
Montgomery
M. A.
,
Jeuland
M. A.
&
Brown
J.
2014
Water quality risks of ‘improved'water sources: evidence from Cambodia
.
Trop. Med. Int. Health
19
(
2
),
186
194
.
Troeger
C.
,
Blacker
B. F.
,
Khalil
I. A.
,
Rao
P. C.
,
Cao
S.
,
Zimsen
S. R.
,
Albertson
S. B.
,
Stanaway
J. D.
,
Deshpande
A.
&
Abebe
Z.
2018
Estimates of the global, regional, and national morbidity, mortality, and aetiologies of diarrhoea in 195 countries: a systematic analysis for the Global Burden of Disease Study 2016
.
Lancet Infect. Dis.
18
(
11
),
1211
1228
.
Waddington
H.
,
Snilstveit
B.
,
White
H.
&
Fewtrell
L.
2009
Water, sanitation and hygiene interventions to combat childhood diarrhoea in developing countries
.
Sythn. Rev.
1
,
17
22
.
WHO
2019
Results of Round II of the WHO International Scheme to Evaluate Household Water Treatment Technologies
.
Licence: CC BY-NC-SA 3.0 IGO
.
World Health Organization
,
Geneva
.
WHO & UNICEF
2006
Core Questions on Drinking Water and SANITATIOn for Household Surveys
.
Available from: https://apps.who.int/iris/handle/10665/43489 (cited 7/3/2019
).
WHO/UNICEF
2015
Joint Monitoring Programme for Water Supply and Sanitation (JMP) (2015)
.
Available from: www.unicef.org/publications/index_82419.html (cited 12/5/2016
).
WHO/UNICEF
2017
Safely managed services: Accounting for service levels
.
Progress on Drinking Water, Sanitation and Hygiene: 2017 Update and SDG Baselines
(
Grojec
A.
, ed.).
World Health Organization (WHO) and the United Nations Children's Fund (UNICEF)
,
Geneva
,
Switzerland
.