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  • Open Access
  • Open Peer Review

Achieving optimal technology and behavioral uptake of single and combined interventions of water, sanitation hygiene and nutrition, in an efficacy trial (WASH benefits) in rural Bangladesh

  • 1Email author,
  • 1,
  • 1,
  • 1,
  • 2,
  • 3,
  • 4,
  • 1,
  • 1,
  • 5,
  • 5 and
  • 6
Trials201819:358

https://doi.org/10.1186/s13063-018-2710-8

  • Received: 4 April 2017
  • Accepted: 25 May 2018
  • Published:
Open Peer Review reports

Abstract

Background

Uptake matters for evaluating the health impact of water, sanitation and hygiene (WASH) interventions. Many large-scale WASH interventions have been plagued by low uptake. For the WASH Benefits Bangladesh efficacy trial, high uptake was a prerequisite. We assessed the degree of technology and behavioral uptake among participants in the trial, as part of a three-paper series on WASH Benefits Intervention Delivery and Performance.

Methods

This study is a cluster randomized trial comprised of geographically matched clusters among four districts in rural Bangladesh. We randomly allocated 720 clusters of 5551 pregnant women to individual or combined water, sanitation, handwashing, and nutrition interventions, or a control group. Behavioral objectives included; drinking chlorine-treated, safely stored water; use of a hygienic latrine and safe feces disposal at the compound level; handwashing with soap at key times; and age-appropriate nutrition behaviors (pregnancy to 24 months) including a lipid-based nutrition supplement (LNS). Enabling technologies and behavior change were promoted by trained local community health workers through periodic household visits. To monitor technology and behavioral uptake, we conducted surveys and spot checks in 30–35 households per intervention arm per month, over a 20-month period, and structured observations in 324 intervention and 108 control households, approximately 15 months after interventions commenced.

Results

In the sanitation arms, observed adult use of a hygienic latrine was high (94–97% of events) while child sanitation practices were moderate (37–54%). In the handwashing arms, handwashing with soap was more common after toilet use (67–74%) than nonintervention arms (18–40%), and after cleaning a child’s anus (61–72%), but was still low before food handling. In the water intervention arms, more than 65% of mothers and index children were observed drinking chlorine-treated water from a safe container. Reported LNS feeding was > 80% in nutrition arms. There was little difference in uptake between single and combined intervention arms.

Conclusions

Rigorous implementation of interventions deployed at large scale in the context of an efficacy trial achieved high levels of technology and behavioral uptake in individual and combined WASH and nutrition intervention households. Further work should assess how to achieve similar uptake levels under programmatic conditions.

Trial registration

WASH Benefits Bangladesh: ClinicalTrials.gov, identifier: NCT01590095. Registered on April 30, 2012.

Keywords

  • WASH benefits
  • Intervention uptake
  • Behavior change
  • Water quality
  • Sanitation
  • Handwashing
  • Child nutrition
  • Efficacy
  • Cluster randomized controlled trial
  • Bangladesh

Background

Uptake of technologies and behaviors in WASH efficacy, effectiveness, and implementation studies

Water, sanitation and hygiene (WASH) interventions have been implemented for many years, and are commonly viewed as an essential part in health and development interventions supported by governments, donor organizations, and development banks. Currently, the specific impact of WASH interventions on disease transmission [13], environmental enteric dysfunction, and nutrition and child development outcomes [46] is a priority area of research. However it has been difficult to attain sufficient uptake of WASH interventions in effectiveness trials and routine programs implemented at scale [79], to replicate the impacts seen in small, well-controlled studies [10, 11].

Efficacy research examines the impact of interventions under ideal or optimal conditions where providers are adequately trained, closely monitored and the respondents are often homogenous. In contrast, effectiveness research examine whether the interventions produce results under near real-world conditions among heterogeneous populations [12]; while implementation research promote the uptake of specific study findings into routine practice [13]. There are questions concerning uptake of WASH technologies (latrines, handwashing stations, water treatments) and WASH behaviors (latrine maintenance and use, handwashing with soap at key times, water treatment and safe storage) for all three kinds of studies. In WASH efficacy studies, researchers ask whether adequate uptake of technologies and behaviors was achieved for the study to qualify as a true efficacy study [14]. Uptake targets are set at a very high level, such as 80% or 90%, and interventions are intensive and carefully monitored [15].

Effect of WASH combined interventions on uptake

Even under optimal conditions for WASH intervention delivery, there are questions concerning the effects of combined interventions, in comparison to individual interventions, on the quality of work by field workers installing technology and promoting behavior change at the household level, to achieve uptake. Combined interventions are potentially more efficient than individual-component interventions but there is a concern that more intervention messages will dilute effectiveness and thwart uptake levels. Practicing multiple behaviors is more difficult and this may limit the potential for sustained adoption of the behaviors [16, 17]. In addition, and importantly from a behavior change perspective, water, sanitation, handwashing, and nutrition behaviors are quite distinct, with respect to factors such as cues, complexity, timing, and relevant individuals in the household and could require distinct tailor-made promotional strategies.

Objectives

The WASH Benefits Bangladesh trial examines the impact of WASH and nutrition interventions alone and in combination on outcomes including reported diarrhea and linear child growth [18, 19]. The current analysis aimed to assess the degree of technology and behavioral uptake among participants in the trial, as part of a three-paper series on WASH Benefits Bangladesh Intervention Delivery and Performance.

Implementation quality affects intervention uptake [20]. It is influenced by the standards of the intervention delivery system [21] and the degree of implementation fidelity, which is an important fundamental tool for assessing the implementation process [2224] and can help to explain the association between intervention and outcomes [25].We describe the WASH Benefits intervention delivery system in the first paper of this series [14] and the system for monitoring implementation fidelity in the second paper in this series [15]. This paper examines whether the study team was able to attain the ambitious targets for uptake of WASH technologies and behaviors required for intervention delivery under ideal conditions, atypical of routine programs.

Methods

Study setting and population

The WASH Benefits Bangladesh trial was conducted in four rural districts (Gazipur, Kishorgonj, Mymensingh, Tangail) in central Bangladesh (ClinicalTrials.gov, NCT01590095). These areas were selected based on low iron and arsenic levels in the drinking water (to avoid interference with the chlorine-based water treatment) and absence of major water, sanitation, or focused nutrition programs delivered by the government or nongovernmental organizations (NGOs). Tubewells are the primary source of drinking water and found near most household compounds, and supply groundwater that is generally much less contaminated than surface water, but still commonly contaminated [26]. Handwashing with soap is an existing but erratic practice [2729]; around 25% of residents washed their hands with soap after defecation and cleaning a child’s anus and less than 1% practiced before preparing food [7]. Open defecation is not extensively practiced by adults [30, 31]; around 11% found ever practiced during baseline. However, only about half the population has access to improved sanitation facilities that hygienically separate human excreta from human contact [32]. Malnutrition in Bangladesh is still high and estimated that approximately 36% of children under 5 are stunted [33]. The subject population was households or compounds with pregnant women and their children who were born within approximately 6 months of the trial’s baseline survey.

The study protocol was approved by the Ethical Review Committee at The International Centre for Diarrhoeal Disease Research, Bangladesh (PR-11063), the Committee for the Protection of Human Subjects at the University of California, Berkeley (2011–09-3652), and the Institutional Review Board at Stanford University (25863).

WASH benefits intervention design

The WASH Benefits study design and rationale are described in detail elsewhere [18]. In Bangladesh enrolment began in May 2012 during which we identified six to eight closest pregnant women in their second and third trimester to form a cluster. A buffer zone of a minimum of 1 km or 15 min walking distance was enforced before enrolling the next cluster, to minimize spillover between enrolled clusters that might have reduced the risk of disease transmission and reduced the possibility of coping chance among the control clusters from intervention [34]. Eight geographically proximate clusters were grouped together to form a trial block. The trial enrolled 5551 households in 90 blocks (720 clusters). We randomly allocated the clusters of each trial block to one of six intervention arms and retained two clusters as controls. The six interventions were drinking water treatment and safe storage, sanitation, handwashing, and child nutrition, in individual and combined arms, and included free provision of enabling technologies and supplies integrated with parallel behavior change promotion. The water technologies comprised household-level chlorination with sodium dichloroisocyanurate tablets (Aquatabs™ Medentech, Wexford, Ireland) coupled with 10 L safe storage in a covered, narrow-mouth container, based on successful previous trial in rural Bangladesh [26]. The sanitation intervention targeted all households of the index child’s compounds in the sanitation arm, and combined arms (WSH and Nutrition+WSH); these compounds contained a shared courtyard. This compound-based intervention aimed to improve sanitary condition of the shared environment. The sanitation intervention included provision of concrete ring-based double pit pour-flush latrines that had a slab, water seal, and a superstructure for privacy; a potty for young children and a sani-scoop for removal of child feces from the environment. The handwashing intervention households received two handwashing stations, one for the latrine (40 L water reservoir) and one for the kitchen (16 L water reservoir) area; soapy water bottle was provided with a regular supply of detergent sachets to make soapy water. This prototype was tested in our previous study in a similar setting [35, 36]. The nutrition intervention was designed for index children (6–24 months) only with monthly supply of lipid-based nutrient supplement (LNS; Nutriset, France).

Behavioral recommendations were developed based on theory and evidence-based behavioral framework, the Integrated Behavioral Model for Water, Sanitation, and Hygiene (IBM-WASH) model [37]. This framework ensured that we explicitly considered the multiple dimensions (contextual, psychosocial, and technical) and the multiple aggregate levels (societal, communal, interpersonal, individual, and habitual) of determinants of WASH-related behaviors; targeted to the index mother and children. The behavior change messages focused on treatment and safe storage of drinking water for children aged < 36 months, use of latrines for defecation, and the removal of human and animal feces from the compound, handwashing with soap at critical times around food preparation, defecation, and contact with feces, and use of LNS for children aged 6–24 months and age-appropriate nutrition behaviors (pregnancy to 24 months).

The WASH Benefits final intervention design was developed through formative research to account for local context and preferences followed by piloting and repeated iterations. Locally recruited female CHWs who were residents of the study villages received extensive training to deliver and promote the interventions during regular home visits. The intervention approach was not primarily focused on message delivery, but rather emphasized the promoters closely working with the mothers to overcome to targeted behaviors.

The interventions theory of change was based on the importance of an enabling environment created by the various WASH technologies offered and the CHWs’ frequent visits of motivational counseling and problem-solving, to allow behavior change to occur at the household level, provide the stable context needed for habit formation at the sub-individual (habitual) level, change WASH-related social norms at the compound level, and enable nurture toward the children to be expressed at its fullest by the caregiver. These behavioral determinants are summarized in a conceptual framework, IBM-WASH, developed by the same team, based on prior formative research, a multi-level ecological model that specifically identifies the importance of technological determinants out of the general contextual factors in influencing behavior change at all levels of the model. The CHWs received and tried out the technologies and behaviors first, in their own homes. They were thus able to model them and point out their benefits to the mothers, based on personal experience. This draws on key elements for the promotion of self-efficacy: modeling of behaviors, repetition, and practice [38]. The benefits promoted included ease and convenience, attractiveness, recommendation by a well-respected health organization, and health and safety for their baby because of improved hygiene.

CHWs received extensive training at the beginning along with quarterly refreshers to deliver and promote the interventions during regular home visits. Shortly after the training, a community meeting was convened to introduce the intervention and present the promoters and their roles to the community and mothers. Each of the visits was structured with specific objectives and guidelines; the activities included training hardware maintenance, discussion, storytelling, songs in different visits. They engaged in dialogue with the caregivers, rather than conducting on-way message delivery. They observed the WASH situation in the home and compound, listened to the problems faced by the mother, and offered their best advice. Behavioral recommendations were explained by CHWs during home visits, when they also verified that people followed behavioral recommendations, and intervened/problem solved when they did not follow the recommendations.

Each CHW was responsible for one cluster of one intervention arm; there were no promoters in the control communities. The CHWs were instructed to visit the intervention households at least once weekly in the first 6 months and then once in every 2 weeks throughout the study period. They have visited more than that and did have a large presence in the community; which may affect the uptake. However, CHWs did not collect any outcome measures; this was a separate team and the outcome measures were objective and assessed on unannounced follow-up visits, which is why the collected outcome measures were not prone to courtesy bias. These CHWs received a stipend equivalent to USD 20 per month provided by the project, a compensation that is similar to the 5 days of local agricultural labor.

In order to accumulate sufficient intervention-specific promoters to support an efficient training session, up to 3 months elapsed between the baseline assessment and the initiation of intervention hardware distribution. For single intervention, the hardware and household visits were conducted shortly after training. For combined intervention, the sanitation intervention was introduced first followed by handwashing, water treatment, and nutrition. The intervention was implemented along a timeline so that the index child born in an intervention household would be born into a household with the intervention in place.

Problem-solving related to behavioral adoption, and the high CHW to household ratio (1:8) was a defining feature of the theory of change. Since the WASH Benefits Bangladesh was an efficacy study, CHWs did not simply deliver the intervention components and leave it up to the householder to judge whether to adopt the behavioral recommendations or not. The high CHW to household ratio allowed the CHWs to return at frequent interventions, and identify and address the barriers to behavior change through ongoing dialogue with the caregivers. This obviously would not be feasible under routine programmatic conditions. However the trial aimed to assess the impact of adoption of the behavioral recommendations under optimal conditions.

The WASH Benefits efficacy trial intended to achieve optimal intervention uptake including uptake of both the technology and adoption of targeted behaviors. Technology uptake implies “sustained adoption and usage of hardware that was distributed by CHWs”. We defined behavioral uptake as the sustained practice of key behaviors promoted by CHWs.

Data collection

We assessed uptake from two data sources – monthly fidelity implementation assessments and structured observations; both assessments were unannounced prior to the individual household visits. We designed the data collection tools based on a priori fidelity indicators developed through substantial feedback, comments, and discussions with national and international experts. Monthly fidelity assessment includes spot checks and survey that captured reported behaviors of interest, as well as the presence, functionality, condition, and signs of use of the delivered hardware. Structured observations consisted of the spot checks of technologies plus direct observation of the behavioral practices of interest. No intervention was conducted in control clusters, therefore, those households were not part of the fidelity assessments but were included in the structured observations.

Implementation fidelity assessment

Implementation fidelity is defined as the degree to which an intervention is delivered as intended. Health interventions often fail to have an impact because they are not delivered with fidelity [39, 40]. For the current efficacy trial, intervention fidelity was important to ensure that the outcomes could be attributable to the respective intervention. Therefore, the field team conducted unannounced monthly fidelity assessments in a random subset of intervention households. These fidelity assessment included spot checks and surveys over 20 months, from November 2012, 2 months after commencement of intervention delivery, until October 2014. Fidelity assessments were coordinated based on timing of intervention delivery. We surveyed a subset of households based on random selection on a monthly basis.

Structured observation

The field workers conducted 5 h of structured observation visits after approximately 15 months of intervention delivery, from February to July 2014. Six (6) trial blocks were randomly selected from each of nine (9) successive implementation phases. From each selected trial block, one (1) household was randomly selected per cluster totaling 324 households from intervention arms (6 blocks*9 phases*6 households) and 108 (6*9*2) households from double-sized control arms. Each observation was approximately 5 h during one of three different time slots (6 am–11 am, 9 am–2 pm and 12 pm–5 pm) to capture activities performed throughout a whole day. The observation times were culturally acceptable for visitors and realistic to observe daily behaviors.

Analysis

Technology uptake was measured as spot-check indicators (e.g., observed hygienic latrine, presence of residual chlorine in study-provided container). Behavioral uptake, behavior change and use of delivered technology, was reported for some indicators (e.g., LNS feeding) or directly observed for others (e.g. handwashing at key times during structured observation). Contextual spot-check indicators served as proxies for technology and behavioral uptake (e.g., feces presence in the courtyard as an indicator of sani-scoop use and safe feces disposal).

We report intervention uptake and compare rates to the index child’s age to track the proportion of time that the index child in the household was receiving the intervention. To analyze survey and spot check data, we calculated proportions for each indicator and compared uptake in households who received individual versus households who received combined interventions. We compared proportions using the chi-square test adjusted for clustering [41]; the unit of clustering was the geographical cluster. We compared the number of monthly CHW visits in individual versus combined intervention arms using a cluster adjusted t-test, with the same unit of clustering.

To analyze structured observation data, we calculated proportions of each observed behavior across intervention arms. To measure the difference between each intervention and the control arm or between individual and combined interventions, risk difference (RD), 95% confidence interval (CI) and p value were calculated using generalized linear models (GLM). We used a clustered sandwich estimator for cluster adjustment; the unit of clustering for this analysis was the repeated events in each observed household.

Results

There was little difference in social and demographic characteristics between the intervention and control households at baseline (Table 1). The reported number of CHW visits per household per month was high, 5–7 per month (Fig. 1). Each CHW was instructed to visit the assigned intervention households at least once weekly for the first 6 months, then once every 2 weeks.
Table 1

Baseline characteristics of WASH Benefits participants in control and intervention arms, rural Bangladesh, 2012

Characteristics

n (%) or mean ± SD

Control

Water

Sanitation

Handwashing

Nutrition

WSHa

Nutrition+WSHb

Education of mother of the youngest child

N = 1382

N = 698

N = 696

N = 688

N = 698

N = 703

N = 686

 No education

206 (15)

115 (17)

115 (17)

101 (15)

116 (17)

100 (14)

116 (17)

 Up-to primary

440 (32)

206 (30)

218 (31)

221 (32)

209 (30)

223 (32)

225 (33)

 Above primary

736 (53)

377 (54)

363 (52)

366 (53)

373 (53)

380 (54)

345 (50)

Education of father of the youngest child

N = 1378

N = 697

N = 695

N = 687

N = 697

N = 700

N = 685

 No education

406 (30)

201 (29)

209 (30)

221 (32)

211 (30)

221 (32)

203 (30)

 Up to primary

412 (30)

220 (32)

204 (29)

211 (31)

211 (30)

198 (28)

228 (33)

 Above primary

560 (41)

276 (40)

282 (41)

255 (37)

275 (40)

281 (40)

254 (37)

Monthly household income (USD)

133 ± 2.8

140 ± 4.2

131 ± 3.8

127 ± 3.6

132 ± 3.7

140 ± 4.2

137 ± 4.1

People/household

4.7 ± .06

4.7 ± .08

4.7 ± .08

4.7 ± .08

4.7 ± .08

4.7 ± .08

4.7 ± .08

Children <3 years/household

0.2 ± .01

0.2 ± .02

0.2 ± .02

0.2 ± .02

0.2 ± .02

0.2 ± .02

0.2 ± .02

Children <3 years/compound

0.7 ± .02

0.6 ± .03

0.6 ± .03

0.7 ± .03

0.7 ± .03

0.7 ± .03

0.7 ± .03

Own home

1357 (98)

688 (98)

691 (99)

676 (98)

686 (98)

686 (98)

670 (98)

Hectares of owned homestead land (mean ± SD)

.059 ± .002

.058 ± .003

.057 ± .003

.057 ± .003

.063 ± .004

.061 ± .003

.052 ± .002

Hectares of owned agricultural land (mean ± SD)

.427 ± .025

.395 ± .046

.407 ± .029

.411 ± .030

.425 ± .031

.420 ± .028

.459 ± .054

Household have own: n (%)

N = 1382

N = 698

N = 696

N = 688

N = 698

N = 703

N = 686

 Electricity

784 (57)

422 (61)

408 (59)

405 (59)

409 (59)

426 (61)

412 (60)

 Refrigerator

116 (8.4)

52 (7.5)

57 (8.2)

50 (7.3)

56 (8.0)

54 (7.7)

52 (7.6)

 Mobile phone

1188 (86)

605 (87)

591 (85)

582 (85)

589 (84)

600 (85)

593 (86)

 Television

416 (30)

215 (31)

225 (32)

210 (31)

205 (29)

187 (27)

203 (30)

 Motor cycle

100 (7.2)

46 (6.6)

47 (6.8)

35 (5.1)

49 (7.0)

53 (7.5)

32 (4.7)

Observed presence of water and soap in primary handwashing station

289/1256 (23)

149/630 (24)

155/631 (25)

133/622 (21)

149/644 (23)

151/646 (23)

146/640 (23)

Observed presence of water and soap in secondary handwashing station

33/147 (23)

11/78 (14)

15/75 (20)

10/75(13)

11/48 (23)

12/68 (18)

10/72(14)

Reported always handwashing with soap

N = 1382

N = 698

N = 696

N = 688

N = 698

N = 703

N = 686

 After defecation

590 (43)

288 (41)

298 (43)

271 (39)

289 (41)

334 (48)

287 (42)

 After cleaning child’s anus

39 (2.8)

14 (2.0)

24 (3.5)

21 (3.1)

18 (2.6)

28 (4.0)

19 (2.8)

 Before food preparation

17 (1.2)

9 (1.3)

6 (0.9)

8 (1.2)

7 (1.0)

11 (1.6)

10 (1.5)

Household owned a toilet

1321 (96)

680 (97)

664 (95)

656 (95)

661 (95)

670 (95)

662 (97)

Observed presence of functional water seal

358 (26)

183 (26)

177 (25)

162 (24)

183 (26)

152 (22)

155 (23)

Observed presence of hygienic latrine

243 (18)

140 (20)

127 (18)

123 (18)

134 (19)

101 (14)

106 (15)

Reported always use of toilet by male

1146 (83)

596 (85)

580 (83)

556 (81)

583 (84)

576 (82)

580 (85)

Reported always use of toilet by female

1283 (93)

665 (95)

649 (93)

625 (91)

648 (93)

651 (93)

647 (94)

Reported last child defecation (<3 years) in potty or toilet

32/272 (12)

16/128 (13)

9/132(6.8)

17/141 (12)

15/131 (11)

16/145 (11)

6/137 (4.4)

Reported safe disposal of <3 years child’s last open defecated feces

14/193 (7.3)

4/92 (4.5)

7/96 (7.3)

5/100 (5.0)

5/90 (5.6)

7/106 (6.6)

8/102 (7.8)

Primary source of drinking water

N = 1382

N = 698

N = 696

N = 688

N = 698

N = 703

N = 686

 Tubewell

1336 (97)

666 (95)

674 (97)

662 (96)

676 (97)

688 (98)

664 (97)

 Piped water

42 (3.0)

31 (4.4)

21 (3.0)

24 (3.5)

20 (2.9)

13 (1.9)

21 (3.1)

 Borewell, river, pond, etc.

4 (0.3)

1 (0.1)

1 (0.1)

2 (0.3)

2 (0.3)

2 (0.3)

1 (0.2)

Walking minutes to primary water source (mean ± SD)

.71 ± .04

.71 ± .06

.77 ± .08

.76 ± .07

.70 ± .07

.77 ± .05

.70 ± .07

Reported storage of drinking water

441 (30)

235 (35)

206 (30)

223 (32)

190 (27)

198 (28)

206 (30)

Reported ever treatment of drinking water

10 (0.7)

2 (0.3)

1 (0.1)

2 (0.3)

2 (0.3)

0 (0)

4 (0.6)

aWSH: in combination of water quality, sanitation and handwashing interventions

bNutrition+WSH: in combination of water quality, sanitation, handwashing and nutrition intervention

Fig. 1
Fig. 1

Reported mean number of CHW visits per month by WASH Benefits study arm

Sanitation uptake

Among compounds that received the sanitation interventions fieldworkers observed high uptake for presence of hygienic latrine (functional water seal, stool visible on slab/floor), during monthly spot checks (Fig. 2); however, the uptake was slightly lower in the first couple of months. Information on the rapid response triggered by low uptake and resulting improvements in implementation fidelity are reported elsewhere [15]. Uptake was higher among intervention compared to control households for the same indicators (water seal: intervention households: 95–98%, control: 23%, p < 0.001; stool visible on slab/floor: intervention households 24–38%, control: 62%, p < 0.01; hygienic latrine: intervention households: 60–72%, control: 14%, p < 0.001) detected in spot checks during structured observations (Table 2). During structured observation, adults from the sanitation intervention arms more commonly used a hygienic latrine (94–97% of events, p < 0.001) compared to adults in the other intervention arms (Table 3). The field workers found moderate use of child potty during child defecation and low use of sani-scoop for cleaning human and animal feces (Fig. 2 and Table 3). Observed safe disposal of human feces was moderate (30–38% of events, p > 0.05) (Table 3). Human feces were less commonly observed at the compound (13–26%) among the sanitation intervention households than households in other arms (p = 0.01 to 0.57). However, the fieldworkers observed animal feces in the majority of compounds (range 85–96%, p > 0.05) across all arms (Table 2).
Fig. 2
Fig. 2

Monthly technology and behavioral uptake measurements over 20 months of intervention delivery, rural Bangladesh, 2012–2014

Table 2

Spot checks of sanitation and handwashing facilities during structured observations, rural Bangladesh, 2014

Indicators

(%)

n

Control

Water

Sanitation

Handwashing

Nutrition

WSH

Nutrition+WSH

(%) N = 108

(%)

N = 54

RDa (95%CI) p value

(%) N = 55

RD

(95% CI)

p value

(%) N = 53

RD

(95% CI)

p value

(%)

N = 54

RD

(95% CI) p value

(%) N = 53

RD

(95% CI)

p value

(%) N = 55

RD

(95% CI)

p value

Sanitation observation

 Presence of functional water seal in latrine

(23) 25

(30) 16

6 (−8, 21) 0.38

(95) 52

71 (61, 81) < .001

(32) 17

9 (−6,24), 0.24

(28) 15

5 (−9,19) 0.52

(98) 52

75 (66,84) < .001

(95) 52

71 (61,81) < .001

 Stool visible on slab or floor or outside

(62) 67

(69) 37

6 (−9,-22) 0.41

(38) 21

−24 (−39,-8) 0.003

(55) 29

−7 (− 23,9) 0.38

(56) 30

−6 (− 22,-9) 0.43

(26) 14

−35 (−50,-20) < .001

(24) 13

−38 (−52,-24) < .001

 Presence of hygienic latrineb

(14) 15

(17) 9

3 (− 9,14) .64

(60) 33

46 (30,60) < .001

(19) 10

5 (− 7,17) .43

(19) 10

4 (− 7,17) .46

(72) 38

58 (44,71) < .001

(71) 39

57 (43,70) < 0.001

 Human feces observed in the surrounding compound

(30) 32

(19) 10

−11 (−24,2) 0.10

(21) 12

− 8 (− 21,6) 0.27

(32) 17

2 (−12,18) 0.75

(39) 21

9 (− 6,25) 0.24

(13) 7

− 16 (−29,−4) 0.01

(26) 14

-4 (− 18,10) 0.57

 Animal feces observed in the compound

(92) 99

(93) 50

1.0 (−8,10) 0.84

(85) 47

−6.2 (−17,4) 0.25

(96) 51

4.6 (− 3,12) 0.22

(94) 51

2.8 (− 5,11) 0.50

(85) 45

−6.8 (− 18,4) 0.23

(89) 49

− 2.6 (− 12,7) 0.61

Handwashing observation

 Handwashing station near the kitchen

  Presence of handwashing station

(83) 90

(85) 46

2 (−10,13) 0.76

(84) 46

.3 (− 11,12) 0.96

(89) 47

5 (−5,16) 0.34

(87) 47

4 (−7,15) 0.50

(89) 47

5 (−5,-16) 0.35

(87) 48

4 (− 7,15) 0.50

  Presence of water

(82) 89

(85) 46

3 (−9,14) 0.64

(84) 46

1 (−10,13) 0.84

(75) 40

−12 (−27,1) 0.08

(87) 47

4 (− 7,16) 0.80

(81) 43

−1 (− 14,11) 0.84

(75) 41

−8 (− 21,05) 0.25

  Presence of soap/soapy water

(19) 21

(15) 8

−4 (− 16,7) 0.45

(18) 10

−1 (− 14,11) 0.84

(74) 39

52 (38,66) < .001

(26) 14

7 (− 7,2) 0.36

(81) 43

61 (49,74) < .001

(76) 42

57 (43,70) < .001

  Presence of water and soap

(19) 21

(15) 8

− 4 (− 16,7) 0.45

(18) 10

− 1 (− 14,11) 0.84

(64) 34

43 (23,58) < .001

(26) 14

6 (− 7,20) 0.36

(76) 40

56 (42,70) < .001

(69) 38

49 (35,64) < 0.001

 Handwashing station near the latrine

  Presence of handwashing station

(19) 20

(13) 7

−5 (−17,6) 0.35

(5.5) 3

− 13 (− 22,-3) 0.007

(89) 47

71 (59,81) < .001

(7.4) 4

− 11 (− 21,-1) 0.03

(93) 49

74 (63,84) < .001

(91) 50

72 (62,83) < 0.001

  Presence of water

(17) 18

(13) 7

−4 (− 15,7) 0.52

(5.5) 3

− 11 (− 20,-2) 0.01

(74) 39

57 (43,70) < .001

(7.4) 4

−9 (− 19,0) 0.07

(83) 44

66 (54,78) 0.001

(78) 43

61 (48,74) < 0.001

  Presence of soap/soapy water

(5.6) 6

(9.3) 5

4 (− 5,12) 0.41

(0) 0

−5 (− 10,-1) 0.01

(79) 42

73 (62,85) < .001

(2.0) 1

−4 (− 9,2) 0.19

(87) 46

81 (71,93) < .001

(82) 45

76 (65,87) < 0.001

  Presence of water and soap

(4.6) 5

(9.3) 5

4 (− 4,13) 0.30

(0) 0

− 4 (− 8,-.7) 0.02

(66) 35

61 (48,74) < .001

(2.01) 1

− 3 (− 8,2) 0.31

(77) 41

72 (6,84) < .001

(73) 40

68 (56,80) < 0.001

  Presence of water and soap in at least one handwashing station

(21) 23

(22.2) 12

0.9 (−12,14) 0.13

(18) 10

− 3 (− 16,10) 0.63

(77) 41

54 (40,68) < .001

(28) 15

6 (−7,21) 0.37

(85) 45

64 (51,76) < .001

(85) 47

64 (52,76) < .001

aRD (risk difference), confidence interval (CI), and p value calculated using generalized linear models (GLM) to measure the differences between each intervention arm and the control arms. Clustered sandwich estimator used for cluster adjustment; the unit of clustering was the repeated events in each observed household

bHygienic latrine defined as presence of functional water seal and no visible feces on slab or floor inside

Table 3

Structured observation for sanitation, handwashing, water treatment and lipid-based nutrient supplementation (LNS) feeding practices

Indicators n/N (%)

Control

Water

Sanitation

Handwashing

Nutrition

WSH

Nutrition+WSH

(%) n/N

(%) n/N

RDa (CI)

p value

(%) n/N

RD (CI) p value

(%) n/N

RD (CI

p value

(%) n/N

RD (CI) p value

(%) n/N

RD (CI)

p value

(%) n/N

RD (CI)

p value

Sanitation practices

 Observed adult use of hygienic latrineb

(40) 38/94c

(44) 16/36

4 (− 31, 39) 0.82

(94) 32/34

54 (28, 79 < .001

(27) 8/30

−14 (− 49,21) 0.44

(31) 13/42

− 9 (− 41,23) 0.56

(97) 37/38

57 (32,82) < .001

(95) 35/37

54 (29,80) < .001

 Observed child defecation in potty or hygienic latrine

(32) 22/69

(29) 9/31

−3 (− 49,44) 0.90

(54) 21/39

22 (−18,61) 0.28

(9.1) 2/22

−23 (− 61,-15) 0.24

(5.9) 2/34

− 26 (− 63,11) 0.17

(37) 13/35

5 (− 38,48) 0.81

(40) 16/40

8 (− 31,47) 0.70

 Safe disposal of human feces

(16) 12/76

(13) 4/30

−2 (− 32,27) 0.87

(36) 14/39

20 (− 11,51) 0.

(3.2) 1/31

− 13 (− 39,-14) 0.40

(5.3) 2/38

−.11 (− 38,17) 0.45

(38) 13/34

.22 (− 11,56) 0.19

(30) 14/47

.14 (− 16,44) 0.25

 Use of sani-scoop for human feces handling

(27) 6/22

(25) 5/20

(38)11/29

 Use of sani-scoop for animal feces handling

(15) 16/105

(21) 24/116

(12) 12/102

Handwashing practices

 Handwashing with soap

  After toilet use

(29) 25/87

(18) 6/34

−11 (−35,13) 0.37

(30) 10/33

2 (−24,27) 0.90

(67) 18/27

38 (11,64) < .005

(40) 16/40

11 (−15,38) 0.41

(74) 26/35

46 (19,72) < .001

(67) 20/30

38 (10,65) < .007

  After cleaning child’s anus

(26) 18/69

(39) 12/31

13 (− 7,.32) 0.21

(34) 14/41

.8 (−12,28) 0.43

(61) 14/23

35 (12,58) 0.003

(37) 13/35

11 (− 13,35) 0.36

(69) 24/35

42 (6,78) < .020

(72) 28/39

46 (26,66) < .001

  Before infant feeding

(1.8) 6/343

(4.0) 9/227

2 (−2,6) 0.27

(1.9) 3/160

.1 (−2,2) 0.92

(16) 26/161

14 (2,27) 0.02

(2.9) 5/174

1 (−2,4) 0.44

(9.0) 14/155

7 (2,13) 0.008

(5.3) 10/190

4 (−.1,7) 0.06

  Before eating

(0.7) 4/546

(.3) 1/296

−.3 (−1,1) .42

(1.5) 4/262

0.7 (−.8,2) .34

(6.9) 21/306

6 (3,9) < .001

(1.7) 5/297

1 (− 1,3) .30

(11) 34/300

11 (5,16) < .001

(5.1) 16/317

4 (1,7) 0.007

  Before food preparation

(.5) 1/186

(1.9) 2/104

1 (−2,4) 0.35

(0) 0/106

−.5 (−.1,.5) 0.32

(5.0) 6/121

4 (.4,8.0) 0.03

(0) 0/118

− 5 (−1,.5) 0.31

(8.7) 9/104

8 (2,14) 0.005

(5.0) 6/119

5 (−1,10) 0.11

  After cutting vegetables to be cooked

(0.6) 1/161

(3.0) 2/67

2 (−3,8) 0.41

(0) 0/88

−.6 (−1,.6) 0.31

(5.0) 4/80

4 (−.3,9) 0.07

(1.0) 1/100

4 (− 2,3) 0.75

(5.8) 5/86

5 (.1,10) 0.03

(4.2) 4/95

4 (− 1,9) 0.15

  After handling raw meat/fish

(6.0) 4/67

(0) 0/23

−6 (−11,-.3) 0.04

(8.6) 3/35

3 (−8,13) 0.63

(44) 8/18

38 (7,70) 0.01

(3.9) 1/26

−2 (− 11,7) 0.65

(18) 3/17

12 (− 9,30) 0.27

(32) 12/38

25 (12,39) < .001

  All food handling events

(1.0) 10/960

(1.0) 5/490

−.02 (−1,1) 0.97

(1.4) 7/491

.4 (− 1,2) 0.60

(7.4) 39/525

6 (3,9) < .001

(1.3) 7/541

.3 (− 1,2) 0.72

(10.1)51/507

9 (6,12) < .001

(6.7) 38/569

6 (3,8) < .001

Water practices

 Water treatment-related events

  Proportion of households observed to store water

(51) 55/108

(48) 26/54

−3 (−19,13) 0.74

(49) 27/55

−2 (− 18,14) 0.83

(51) 27/53

.01 (− 16,16) 0.99

(48) 26/54

− 3 (− 19,13) 0.74

(53) 28/53

.02 (− 14,18) 0.82

(62) 34/55

10 (−5,27) 0.18

  Storage container fully covered

(18) 13/74

(77) 27/35

60 (41,78) < .001

(38) 16/42

20 (−.3,41) 0.05

(31) 13/42

13 (−9,35) 0.23

(19) 7/37

1 (−16,18) 0.88

(55) 21/38

38 (19,57) < .001

(62) 31/50

44 (24,65) < .001

  Water stored with residual chlorination detectedd

0/70 (0)

(70) 23/33

69 (54,85) < .001

0/41 (0)

0 (− 0,0) 1

0/42 (0)

0 (− 0,0) 1

0/37 (0)

0 (− 0,0) 1

(50) 18/36

50 (33,66) < .001

(65) 30/46

65 (51,80) < .001

  Drinking stored water; index child or its mother

(81) 208/258

(97) 167/172

16 (10,23) < .001

(81.3) 113/139

.7 (−8,9) 0.88

(83) 96/116

2 (− 9,12) 0.70

(85)126/148

5 (−5,14) 0.34

(97) 109/113

16 (10,22) < .001

(97) 113/117

16 (10,22) < .001

  Drinking stored water; other household members

(87) 222/256

(90) 146/162

3 (−6,12) 0.46

(78.4) 105/134

−8 (−18,2) 0.10

(83) 134/162

−4 (−16,.8) 0.51

(89) 122/137

2 (− 6,10) 0.58

(96) 141/147

9 (3,16) 0.004

(83) 144/173

−3 (−18,12) 0.65

Water collection and storage practices

  Rinsed container with water

(42) 31/74

(60) 21/35

18 (5,42) 0.13

(43) 18/42

1 (−23,25) 0.94

(33) 14/42

−9 (−31,14) 0.46

(41) 15/37

−1 (− 26,26) 0.91

(58) 22/38

16 (−8,40) 0.10

(34) 17/50

− 8 (− 29,14) 0.47

  Washed hands with only water

(27) 20/74

(34) 12/35

7 (−14,29) 0.51

(41) 17/42

13 (−11,37) 0.27

(14) 6/42

−13 (− 29,4) 0.13

(24) 9/37

−3 (−23,17) 0.79

(40) 15/38

12 (− 11,36) 0.31

(16) 8/50

− 11 (− 29,7) 0.22

  Washed hands with water and soap

(1.4) 1/74

(14) 5/35

13 (.3,26) 0.04

(0) 0/42

−1 (−4,1) 0.31

(0) 0/42

−1 (−4,1) 0.31

(0) 0/37

− 1 (− 4,1) 0.31

(7.9) 3/38

7 (−2,16) 0.16

(0) 0/50

− 1 (− 4,1) 0.31

Serving stored drinking water

  Rinsed glass with drinking water

(15) 76/514

(7.8) 26/334

−7 (−13,-1) 0.02

(20) 55/273

5 (−.4,14) 0.24

(11) 30/278

−4 (−10,2) 0.21

(14) 40/285

−.8 (− 7,6) 0.83

(8.1) 21/260

− 7 (− 13,-1) 0.03

(7.6) 22/290

− 7 (− 13,-2) 0.01

  Washed hands with only water

(5.5) 28/514

(4.5) 15/334

− 1 (−5,3) 0.65

(4.4) 12/273

−1 (−6,4) 0.69

(3.2) 9/278

−2 (−6,2) 0.29

(3.2) 9/285

−2 (− 6,2) 0.24

(3.5) 9/260

− 2 (− 6,2) 0.31

(1.4) 4/290

− 4 (− 7,-1) 0.01

Drinking water stored in the study provided container (topaz); index child or its mother

(74) 128/172

(66) 74/113

(68)80/118

Drinking water stored in the study provided container (topaz); other household members

(40) 65/162

(57) 84/147

(42) 72/173

Nutrition practices

 LNS events

  Observed LNS serving (at least 1)

(56) 30/54

(59) 32/54

  Consumption (index child)

             

  Consumed 1 full sachet

(65) 26/40

(97) 31/32

  Consumed 2 full sachet

(0) 0/40

(0) 0/32

  Partially from left over sachet

(13) 5/40

(0) 0/32

  Partially eaten and stored

(18) 7/40

(0) 0/32

  Partially eaten and thrown away

(5) 2/40

(3.1) 1/32

  Mother’s hands washed with soap before feeding LNS

(13) 5/40

(31) 10/32

aRD (risk difference), confidence interval (CI), and p value calculated using generalized linear models (GLM) to measure the difference between each intervention arm and the control arms. Clustered sandwich estimator used for cluster adjustment; the unit of clustering was the repeated events in individual household

bHygienic latrine defined as presence of functional water seal and no visible feces on slab or floor inside

cDenominator was total number of defecation and urination events observed in the HHs which included use of hygienic, non-hygienic latrine and open defecation

dResidual chlorine > 0.2 mg/L with the HUCH method

Handwashing uptake

Among households that received the handwashing intervention, the proportion of households with handwashing stations observed to be stocked with water and soap or soapy water near the kitchen and latrine was high across intervention arms (Fig. 2). Somewhat higher uptake was noted in the first few months of fidelity assessments (Fig. 2). Similarly, during structured observation, field workers observed high uptake in the kitchen (range 64–76%, p < 0.001) and latrine area (range 66–77%, p < 0.001) (Table 2). Observed handwashing with soap was more common after toilet use (range: 67%–74% of events, p < 0.05) and after cleaning a child’s anus (range: 61%–72%, p < 0.05) compared to other intervention (range 34–39%) and control households (range 26–29%). However, the field workers observed only 5–11% of participants washing their hands with soap before eating and before food preparation across the handwashing arms (p = 0.001 to 0.11) (Table 3).

Water treatment and safe storage uptake

Observed drinking water stored in study-provided containers and self-reported water treatment with Aquatabs were somewhat lower in the first few months but high later on (Fig. 2). Detectable residual chlorine was lower than self-reported Aquatab treatment but sizeable (Fig. 2). In households that received the water intervention, more than 65% (range 66–74%) of mothers or index children drank treated water from the study-provided containers (Table 3).

LNS uptake

Among mothers of children aged between 6 to 20 months of age, more than 80% reported LNS feeding (1 or 2 sachets per day) across the nutrition intervention arms (Fig. 2). During structured observation, 56% of index children were observed to consume at least one LNS sachet in the individual nutrition intervention arm and 59% in the combined Nutrition+WSH intervention arm (Table 3).

Comparison of uptake among individual and combined interventions

Some small differences were detected in the overall uptake between individual and combined interventions in the uptake measurements over 20 months (Table 4).
Table 4

Differences in the uptake across individual and combined intervention arms over 20 months

Indicators

Water, % (mean)

Sanitation, % (mean)

Handwashing, % (mean)

Nutrition, % (mean)

WSH, % (mean) p valuea

Nutrition+WSH, % (mean) p valuea

Observed latrine with a functional water seal

89

91 0.54

90 0.80

Absence of visible feces observed on slab or floor of latrine

73

73 0.98

75 0.59

Observed hygienic latrine

70

70 0.97

72 0.63

Proportion of children 6–36 months living in the compound who are reported to always defecate in the potty

48

50 0.69

47 0.75

Reported use of sani-scoop for cleaning child/human feces

20

21 0.71

20 0.90

Mean CHW visits per month in Sanitation arms

(6.4)

(6.3) 0.68

(6.6) 0.35

Observed proportion of households have handwashing station near the kitchen stocked with water and soap

94

86 0.005

87 0.003

Observed proportion of households have handwashing station near the latrine stocked with water and soap

93

85 0.002

87 0.008

Mean CHW visits per month in handwashing arms

(6.2)

(6.3) 0.56

(6.6) 0.052

Observed drinking water storage in project provided container

88

81 0.013

81 0.027

Self-reported water treatment with Aquatab

84

78 0.046

77 0.03

Detectable residual chlorine > 0.2 mg/L in stored water

76

68 0.034

67 0.016

Mother’s report of index child drinking water stored in project provided container

58

54 0.48

51 0.20

Mean CHW visits per month in water arms

(5.6)

(6.3) 0.007

(6.6) 0.000

Self- reported feeding LNS to child (6–20 months)

84

84 0.95

Mean CHW visits per month in Nutrition arms

(5.8)

(6.6) .002

CHW community health worker; LNS lipid-based nutrient supplementation; WSH water quality, sanitation, handwashing

aCluster adjusted chi-square test for proportion and cluster adjusted t test for mean

All sanitation uptake indicators were similar and did not differ significantly for the individual compared to the two combined interventions (p = 0.63 to 0.97). In the individual handwashing intervention, the majority (93–94%) of households had water and soap in both handwashing stations (near the kitchen and near the latrine), and this proportion was somewhat higher compared to households that received combined handwashing interventions (range 85–87%, p < 0.01). The proportion of self-reported water treatment with Aquatabs (84%) was somewhat higher for those who received the individual water intervention than the combined interventions (range 77–78%, p < 0.05). Similarly, detectable chlorine residual (76%) was more common in the individual intervention compared to combined intervention households (range 67–68%, p < 0.05). However, mothers’ reports of index children drinking water from the study-provided container were similar across the water intervention arms (range 51–58%, p > 0.05) (Table 4).

Discussion

The assessment of the technology and behavioral uptake in the WASH Benefits efficacy trial demonstrated moderate to high level uptake of desired technologies and behaviors in both individual and combined intervention arms. In some individual arms, we found somewhat higher uptake compared to combined intervention arms for a subset of indicators (fully stocked handwashing stations, water storage in study-provided containers, and self-reported water treatment); however, these uptake differences were small.

Sanitation uptake

We identified higher proportions of hygienic latrines, absence of visible feces on the latrine slab or floor, presence of functional water seal, and targeted behavioral uptake in the sanitation intervention households compared to households that did not receive any sanitation intervention. However, we found comparatively lower levels of technology and behavioral uptake in child sanitation practices in all sanitation intervention arms. Nonetheless, child sanitation practices in these arms were higher compared to the child sanitation practices achieved in other studies [7, 8, 42, 43] and during the WASH Benefits baseline.

Open defecation among children under the age of five in Bangladesh and elsewhere is common [4447]. It is possible that the existing open defecation practice among children was so common and accepted that it acted as a barrier to the uptake of potty use, especially since this requires potty training, which can be time-consuming for mothers [48, 49]. Similarly, unsafe child feces disposal is highly prevalent in rural Bangladesh even when a household has latrine access [50]. Unsafe feces disposal decreases if a potty is available in the household, but it is very common for a child under the age of 3 to defecate in a nappy or on the ground [50]. Even when a potty was available and promoted actively in this study, observed use was not very high, and possibly linked to unsafe feces disposal practices. Further research might identify approaches to improve the promotion of child sanitation practices in this and similar settings. Adapting toilets to be child-friendly might improve safe feces management of preadolescent children.

Handwashing uptake

Earlier studies from Bangladesh reported low uptake of handwashing behaviors at key times [7, 29, 5154]. Our study identified higher uptake of handwashing stations at designated places, which likely contributed to the improved handwashing practices noted in the structured observation. These findings highlight the importance of a convenient location for acquiring the habit of washing hands [29, 55]. Households were able to maintain the study-provided handwashing station. However, improved but still low behavioral uptake was found before food preparation and infant feeding, consistent with other studies in similar settings [29, 51]. We provided a designated handwashing station near the kitchen, which could have had an impact on the frequency of handwashing [56], though the presence of a handwashing station was not a sufficient condition for achieving behavior change. Further research on how handwashing can be promoted in the absence of intense interpersonal communication and without free provision of supplies is a priority area for handwashing research. The popularity of soapy water suggests it may be a promising component [57].

Water treatment uptake

The technology and behavioral uptake of the water treatment was similar to another intervention trial in Bangladesh that used the same approach [26]. That study also reported that safe storage alone markedly improved microbiological quality of stored water and subsequently reduced diarrhea. While intervention households commonly treated water with Aquatabs, reported practice was higher than detected free chlorine; higher concentration of iron in water from some tubewells may have reacted with Aquatabs and thereby reducing detectable chlorine [58]. However, supplying Aquatabs at scale would require further research to gauge demand and willingness to pay. Safe water storage alone might be sufficient to improve water quality in some settings [26].

Nutrition uptake

The high LNS uptake in nutrition interventions was consistent with similar previously implemented interventions [5963]. Using formative research to develop nutrition intervention messages [64] that were culturally sensitive likely influenced high levels of adoption [65]. This confirms that LNS is highly acceptable in this setting, however nutrition programs will need to determine ways to fund product purchase and distribution.

Comparison of uptake among individual and combined intervention

Combined interventions showed high technology and behavioral uptake, even though other research has suggested that too many behavior change communication (BCC) interventions risk overwhelming the target audience [16, 17, 66, 67]. Our intensive intervention delivery system, highly trained CHWs, as well as using a phased intervention roll out rather than introducing multiple interventions together in the households [14], may have contributed. Specifically for nutrition and child sanitation practices, where delivery aligned as the children’s cohort aged. The training for children on potty use was age-appropriate. Routine programs, by contrast, have to concurrently serve children of diverse ages and developmental stages, and therefore diverse programmatic needs, requiring the CHWs’ concurrent dissemination of interventions targeted to multiple age groups at once. Future research could explore approaches to deliver complex interventions to larger numbers of children of diverse ages.

CHWs were the cornerstone of intervention delivery where uptake was a primary requirement. The importance of the capacity of health workers to promote complex interventions has been highlighted elsewhere [68]. A common concern has been that increasing health promoters’ workload can result in diluted messages, and receivers of these messages can be overwhelmed [67, 69]. However, in this assessment, we found somewhat lower uptake in combined intervention households, and only for handwashing and water treatment behaviors; this relatively lower uptake level was modest. Mothers in low-income settings setting have time constraints that can limit their time to integrate additional responsibilities into their daily routines [70, 71]; likely to prioritize convenient behavior options. In fact, when it comes to adopting new behaviors, when given a choice, there is evidence that people tend to choose convenience over effectiveness [72]. It is possible that, when multiple behaviors promoted in combination, the amount of attention/effort/time dedicated to these inconvenient and time-consuming behaviors had to be limited and overall uptake of multiple behaviors fell compared to the uptake when these behaviors were promoted individually.

First and foremost, the CHW to population ratio (1:8) was very high; hence the CHWs could demonstrate the enabling technologies and behavioral recommendations in their own homes and the homes of the study participants, thus promoting an in-depth familiarity that likely increased their own self-efficacy to promote the behavioral recommendations. In addition, they received extensive trainings, and close supervision, and conducted repeated household visits that included problem-solving and behavior reinforcement [14].

It is possible that individual and combined interventions were received equally well by the study participants because they were all linked within the common theme of child health and well-being. The multiple messages were all complementary not conflicting/contradictory. Earlier research shows that thinking about a behavioral outcome can occur easily if multiple behaviors are thematically linked [73].

The study has some limitations. Some of the uptake indicators were reported and not directly observed, potentially overestimating uptake. In addition, the presence of an observer might alter practices during the observation period [74] and, therefore, overestimate uptake. We attempted to reduce the limitations of questions on reported behaviors by adding spot checks and residual chlorine measurements. We attempted to reduce the impact of the observer by arriving unannounced and extending the observation into 5 h, which likely minimized the reactivity [75]. In addition, observers had no connection with the intervention to reduce reactivity. In the case of LNS consumption, the 5-hour period may have been too short to observe a feeding event, hence the discrepancy between reported and observed uptake. A limitation of efficacy trials is that the intervention delivered under optimal conditions, and so these findings do not readily generalize to routine programs.

Conclusions

The WASH Benefits efficacy trial demonstrates that with a carefully designed intervention, explicitly based on a broad behavior change theory and formative research, implemented by well-trained and supervised CHWs, high uptake of water, sanitation, hygiene, and nutrition-related behaviors could be achieved within low-income rural communities. Adapting techniques that were effective in this well-resourced efficacy study, to large-scale programmatic interventions would require a focused research effort and iterative learning, but the high uptakes achieved suggest that such an effort may be worth the investment.

Abbreviations

BCC: 

Behavior change communication

CHW: 

Community health worker

IBM-WASH: 

Integrated Behavioral Model for Water, Sanitation, and Hygiene

LNS: 

Lipid-based nutrient supplementation

NGO: 

Nongovernmental organization

WASH: 

Water, Sanitation, and Hygiene

Declarations

Acknowledgements

The authors acknowledge the WASH Benefits study collaborators and acknowledge the cooperation of the study households and communities that were visited several times for intervention delivery and data collection.

Funding

This research study was funded by the Bill & Melinda Gates Foundation grant OPPGD759 through the University of California Berkeley. icddr,b acknowledges with gratitude the commitment of the Bill & Melinda Gates Foundation to its research efforts. icddr,b is also grateful to the Governments of Bangladesh, Canada, Sweden, and the UK for providing core/unrestricted support.

Availability of data and materials

Data can be made available through the authors.

Authors’ contributions

SMP conducted data analysis and interpretation of the results and drafted the manuscript as primary author with the listed co-authors. SPL provided conceptual guidance for data analysis and manuscript development. RA provided support for field data collection and data analysis. MR, LU, PKR, ANT, CS, KJ, MJR, EL, and PJW provided support during tools development design and the development of data analysis. All authors provided feedback and read and approved the manuscript.

Ethics approval and consent to participate

All households provided written informed consent at enrollment. The protocol was reviewed and approved by human subjects review committees at the icddr,b and at the University of California, Berkeley.

Consent for publication

All co-authors have reviewed this version of the manuscript and provided consent for manuscript submission.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Environmental Intervention Unit, Enteric and Respiratory Infections Program, Infectious Diseases Division, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr.b), Dhaka, Bangladesh
(2)
School of Public Health and Health Professions, University of Buffalo, Buffalo, NY, USA
(3)
Rollins School of Public Health, Emory University, Atlanta, GA, USA
(4)
Department of Nutrition, University of California, Davis, CA, USA
(5)
Department of International Health, Social and Behavioral Interventions Program, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA
(6)
Division of Infectious Diseases and Geographic Medicine, Stanford University, Stanford, CA, USA

References

  1. Schmidt WP. The elusive effect of water and sanitation on the global burden of disease. Tropical Med Int Health. 2014;19:522–7.View ArticleGoogle Scholar
  2. Mbuya MN, Humphrey JH. Preventing environmental enteric dysfunction through improved water, sanitation and hygiene: an opportunity for stunting reduction in developing countries. Matern Child Nutr. 2016;12(Suppl 1):106–205.View ArticlePubMedGoogle Scholar
  3. Ngure FM, Reid BM, Humphrey JH, Mbuya MN, Pelto G, Stoltzfus RJ. Water, sanitation, and hygiene (WASH), environmental enteropathy, nutrition, and early child development: making the links. Ann N Y Acad Sci. 2014;1308:118–28.View ArticlePubMedGoogle Scholar
  4. Humphrey JH. Child undernutrition, tropical enteropathy, toilets, and handwashing. Lancet. 2009;374:1032–5.View ArticlePubMedGoogle Scholar
  5. Dangour AD, Watson L, Cumming O, Boisson S, Che Y, Velleman Y, Cavill S, Allen E, Uauy R. Interventions to improve water quality and supply, sanitation and hygiene practices, and their effects on the nutritional status of children. Cochrane Database Syst Rev. 2013;1(8):CD009382.Google Scholar
  6. Cumming O, Cairncross S. Can water, sanitation and hygiene help eliminate stunting? Current evidence and policy implications. Matern Child Nutr. 2016;12:91–105.View ArticlePubMedPubMed CentralGoogle Scholar
  7. Huda TMN, Unicomb L, Johnston RB, Halder AK, Sharker MAY, Luby SP. Interim evaluation of a large scale sanitation, hygiene and water improvement programme on childhood diarrhea and respiratory disease in rural Bangladesh. Soc Sci Med. 2012;75:604–11.View ArticlePubMedGoogle Scholar
  8. Patil SR, Arnold BF, Salvatore AL, Briceno B, Ganguly S, Colford JM Jr, Gertler PJ. The effect of India's total sanitation campaign on defecation behaviors and child health in rural Madhya Pradesh: a cluster randomized controlled trial. PLoS Med. 2014;11(8):e1001709.View ArticlePubMedPubMed CentralGoogle Scholar
  9. Boisson S, Sosai P, Ray S, Routray P, Torondel B, Schmidt W-P, Bhanja B, Clasen T. Promoting latrine construction and use in rural villages practicing open defecation: process evaluation in connection with a randomised controlled trial in Orissa, India. BMC Res Notes. 2014;7:486.View ArticlePubMedPubMed CentralGoogle Scholar
  10. Christensen G, Dentz HN, Pickering AJ, Bourdier T, Arnold BF, Colford JM Jr, Null C. Pilot cluster randomized controlled trials to evaluate adoption of water, sanitation, and hygiene interventions and their combination in rural western Kenya. Am J Trop Med Hygiene. 2015;92:437–47.View ArticleGoogle Scholar
  11. Biran A, Schmidt W-P, Varadharajan KS, Rajaraman D, Kumar R, Greenland K, Gopalan B, Aunger R, Curtis V. Effect of a behaviour-change intervention on handwashing with soap in India (SuperAmma): a cluster-randomised trial. Lancet Glob Health. 2014;2:e145–54.View ArticlePubMedGoogle Scholar
  12. Glasgow RE, Lichtenstein E, Marcus AC. Why don’t we see more translation of health promotion research to practice? Rethinking the efficacy-to-effectiveness transition. Am J Public Health. 2003;93:1261–7.View ArticlePubMedPubMed CentralGoogle Scholar
  13. Bhattacharyya O, Reeves S, Zwarenstein M. What is implementation research? Rationale, concepts, and practices. Res Soc Work Pract. 2009;19:491–502.View ArticleGoogle Scholar
  14. Unicomb L, Begum F, Leontsini E, Rahman M, Ashraf S, Naser AM, Nizame FA, Jannat K, Hussain F, Parvez SM, et al. WASH benefits Bangladesh trial: management structure for achieving high coverage in an efficacy trial. Trials. 2018 (accepted).Google Scholar
  15. Rahman M, Ashraf S, Unicomb L, Mainuddin AKM, Parvez SM, Begum F, Das KK, Naser AM, Hussain F, Clasen T, et al. Implementation fidelity for a water, sanitation, hand washing and nutrition randomized controlled trial in rural Bangladesh identified latrine modification practices. Trials. 2018 (accepted).Google Scholar
  16. Dalton AN, Spiller SA. Too much of a good thing: the benefits of implementation intentions depend on the number of goals. J Consum Res. 2012;39:600–14.View ArticleGoogle Scholar
  17. Soman D, Zhao M. The fewer the better: number of goals and savings behavior. J Mark Res. 2011;48(6):944–57.View ArticleGoogle Scholar
  18. Arnold BF, Null C, Luby SP, Unicomb L, Stewart CP, Dewey KG, Ahmed T, Ashraf S, Christensen G, Clasen T, et al. Cluster-randomised controlled trials of individual and combined water, sanitation, hygiene and nutritional interventions in rural Bangladesh and Kenya: the WASH benefits study design and rationale. BMJ Open. 2013;3:e003476.View ArticlePubMedPubMed CentralGoogle Scholar
  19. Luby SP, Rahman M, Arnold BF, Unicomb L, Ashraf S, Winch PJ, Stewart CP, Begum F, Hussain F, Benjamin-Chung J. Effects of water quality, sanitation, handwashing, and nutritional interventions on diarrhoea and child growth in rural Bangladesh: a cluster randomised controlled trial. Lancet Glob Health. 2018;6(3):e302–15.View ArticlePubMedPubMed CentralGoogle Scholar
  20. Proctor E, Silmere H, Raghavan R, Hovmand P, Aarons G, Bunger A, Griffey R, Hensley M. Outcomes for implementation research: conceptual distinctions, measurement challenges, and research agenda. Adm Policy Ment Health Ment Health Serv Res. 2011;38:65–76.View ArticleGoogle Scholar
  21. Curran GM, Bauer M, Mittman B, Pyne JM, Stetler C. Effectiveness-implementation hybrid designs: combining elements of clinical effectiveness and implementation research to enhance public health impact. Med Care. 2012;50:217.View ArticlePubMedPubMed CentralGoogle Scholar
  22. Breitenstein SM, Fogg L, Garvey C, Hill C, Resnick B, Gross D. Measuring implementation fidelity in a community-based parenting intervention. Nurs Res. 2010;59:158.View ArticlePubMedPubMed CentralGoogle Scholar
  23. Cross W, West J. Examining implementer fidelity: Conceptualising and measuring adherence and competence. J Children’s Serv. 2011;6:18–33.View ArticleGoogle Scholar
  24. Durlak JA, DuPre EP. Implementation matters: a review of research on the influence of implementation on program outcomes and the factors affecting implementation. Am J Community Psychol. 2008;41:327–50.View ArticlePubMedGoogle Scholar
  25. Carroll C, Patterson M, Wood S, Booth A, Rick J, Balain S. A conceptual framework for implementation fidelity. Implement Sci. 2007;2:1–9.View ArticleGoogle Scholar
  26. Ercumen A, Naser AM, Unicomb L, Arnold BF, Colford JM Jr, Luby SP. Effects of source-versus household contamination of tubewell water on child diarrhea in rural Bangladesh: a randomized controlled trial. PLoS One. 2015;10:e0121907.View ArticlePubMedPubMed CentralGoogle Scholar
  27. Luby SP, Halder AK, Tronchet C, Akhter S, Bhuiya A, Johnston RB. Household characteristics associated with Handwashing with soap in rural Bangladesh. Am J Trop Med Hyg. 2009;81:882–7.View ArticlePubMedGoogle Scholar
  28. Curtis VA, Danquah LO, Aunger RV. Planned, motivated and habitual hygiene behaviour: an eleven country review. Health Educ Res. 2009;24:655–73.View ArticlePubMedPubMed CentralGoogle Scholar
  29. Halder AK, Tronchet C, Akhter S, Bhuiya A, Johnston R, Luby SP. Observed hand cleanliness and other measures of handwashing behavior in rural Bangladesh. BMC Public Health. 2010;10:545.View ArticlePubMedPubMed CentralGoogle Scholar
  30. Hanchett S: Sanitation in Bangladesh: revolution, evolution, and new challenges. 2016.Google Scholar
  31. icddr b, UNICEF: SHEWA-B Health Impact Survey Report. 2014.Google Scholar
  32. Organization WH, Supply WUJW, Programme SM. Progress on sanitation and drinking water: 2015 update and MDG assessment. Geneva: World Health Organization; 2015.Google Scholar
  33. National Institute of Population Research and Training (NIPORT) MaA, and ICF International. Bangladesh Demographic and Health Survey 2014. Dhaka, Bangladesh, and Rockville, Maryland, USA: NIPORT, Mitra and Associates, and ICF International; 2016.Google Scholar
  34. Benjamin-Chung J, Amin N, Ercumen A, Arnold BF, Hubbard AE, Unicomb L, Rahman M, Luby SP, Colford JM. A randomized controlled trial to measure spillover effects of a combined water, sanitation, and Handwashing intervention in rural Bangladesh. Am J Epidemiol. 2018; https://doi.org/10.1093/aje/kwy046. [Epub ahead of print]
  35. Hulland KR, Leontsini E, Dreibelbis R, Unicomb L, Afroz A, Dutta NC, Nizame FA, Luby SP, Ram PK, Winch PJ. Designing a handwashing station for infrastructure-restricted communities in Bangladesh using the integrated behavioural model for water, sanitation and hygiene interventions (IBM-WASH). BMC Public Health. 2013;13:877.View ArticlePubMedPubMed CentralGoogle Scholar
  36. Ashraf S, Nizame FA, Islam M, Dutta NC, Yeasmin D, Akhter S, Abedin J, Winch PJ, Ram PK, Unicomb L. Nonrandomized trial of feasibility and acceptability of strategies for promotion of soapy water as a Handwashing agent in rural Bangladesh. Am J Trop Med Hygiene. 2017;96:421–9.View ArticleGoogle Scholar
  37. Dreibelbis R, Winch PJ, Leontsini E, Hulland KRS, Ram PK, Unicomb L, Luby SP. The integrated Behavioural model for water, sanitation, and hygiene: a systematic review of behavioural models and a framework for designing and evaluating behaviour change interventions in infrastructure-restricted settings. BMC Public Health. 2013;13:1015.View ArticlePubMedPubMed CentralGoogle Scholar
  38. Bandura A. Social cognitive theory: an agentic perspective. Annu Rev Psychol. 2001;52:1–26.View ArticlePubMedGoogle Scholar
  39. Mihalic S. The importance of implementation fidelity. Emot Behav Disord Youth. 2004;4:83–105.Google Scholar
  40. Fixsen DL, Naoom SF, Blase KA, Friedman RM. Implementation research: a synthesis of the literature. Tampa: The National Implementation Research Network; 2005.Google Scholar
  41. Donner A, Klar N. Design and analysis of cluster randomization trials in health research. London: Arnold; 2000.Google Scholar
  42. LGRD: Bangladesh country paper: sanitation in Bangladesh. Goverment of the People’s Republic of Bangladesh. 2008.Google Scholar
  43. Gil A, Lanata C, Kleinau E, Penny M. Children’s feces disposal practices in developing countries and interventions to prevent diarrheal diseases. A literature review. Arlington: Environmental Health Project at USAID; 2004.Google Scholar
  44. Sultana R, Mondal UK, Rimi NA, Unicomb L, Winch PJ, Nahar N, Luby SP. An improved tool for household faeces management in rural Bangladeshi communities. Tropical Med Int Health. 2013;18:854–60.View ArticleGoogle Scholar
  45. Curtis V, Kanki B, Mertens T, Traore E, Diallo I, Tall F, Cousens S. Potties, pits and pipes: explaining hygiene behaviour in Burkina Faso. Soc Sci Med. 1995;41:383–93.View ArticlePubMedGoogle Scholar
  46. Traore E, Cousens S, Curtis V, Mertens T, Tall F, Traore A, Kanki B, Diallo I, Rochereau A, Chiron J. Child defecation behaviour, stool disposal practices, and childhood diarrhoea in Burkina Faso: results from a case-control study. J Epidemiol Community Health. 1994;48:270–5.View ArticlePubMedPubMed CentralGoogle Scholar
  47. Alam N, Wojtyniak B, Henry FJ, Rahaman MM. Mothers’ personal and domestic hygiene and diarrhoea incidence in young children in rural Bangladesh. Int J Epidemiol. 1989;18:242–7.View ArticlePubMedGoogle Scholar
  48. Yeager BA, Huttly SR, Bartolini R, Rojas M, Lanata CF. Defecation practices of young children in a Peruvian shanty town. Soc Sci Med. 1999;49:531–41.View ArticlePubMedGoogle Scholar
  49. Hussain F, Clasen T, Akter S, Bawel V, Luby SP, Leontsini E, Unicomb L, Barua MK, Thomas B, Winch PJ. Advantages and limitations for users of double pit pour-flush latrines: a qualitative study in rural Bangladesh. BMC Public Health. 2017;17:515.View ArticlePubMedPubMed CentralGoogle Scholar
  50. Islam M, Ercumen A, Ashraf S, Das KK, Kafi MAH, Luby S, Unicomb L: Impact of unsafe feces disposal of <3 years child among households with latrine access in rural Bangladesh. Water & Health Conference: Where Science Meet Policy 2015.Google Scholar
  51. Nizame FA, Unicomb L, Sanghvi T, Roy S, Nuruzzaman M, Ghosh PK, Winch PJ, Luby SP. Handwashing before food preparation and child feeding: a missed opportunity for hygiene promotion. Am J Trop Med Hygiene. 2013;89:1179–85.View ArticleGoogle Scholar
  52. Luby SP, Halder AK, Huda T, Unicomb L, Johnston RB. The effect of handwashing at recommended times with water alone and with soap on child diarrhea in rural Bangladesh: an observational study. PLoS Med. 2011;8:798.View ArticleGoogle Scholar
  53. Galiani S, Gertler PJ, Orsola-Vidal A. Promoting handwashing behavior in Peru: the effect of large-scale mass-media and community level interventions. World Bank Policy Research Working Paper No. 6257. World Bank, Washington, DC. © World Bank. 2012. https://openknowledge.worldbank.org/handle/10986/19928.
  54. Chase C, Do Q-T. Handwashing behavior change at scale: evidence from a randomized evaluation in Vietnam. Policy Research Working Paper; No. 6207. World Bank, Washington, DC. © World Bank. 2012. https://openknowledge.worldbank.org/handle/10986/12056.
  55. Grover E, Hossain MK, Uddin S, Venkatesh M, Ram PK, Dreibelbis R. Comparing the behavioural impact of a nudge-based handwashing intervention to high-intensity hygiene education: a cluster-randomised trial in rural Bangladesh. Tropical Med Int Health. 2018;23:10–25.View ArticleGoogle Scholar
  56. Cairncross S. More water: better health. People Planet. 1997;6:10–1.PubMedGoogle Scholar
  57. Biswas D, Nizame FA, Sanghvi T, Roy S, Luby SP, Unicomb LE. Provision versus promotion to develop a handwashing station: the effect on desired handwashing behavior. BMC Public Health. 2017;17:390.View ArticlePubMedPubMed CentralGoogle Scholar
  58. Lippy EC. Chlorination to prevent and control waterborne diseases. J Am Water Works Assoc. 1986;78(1):49–52.Google Scholar
  59. Abbeddou S, Hess SY, Yakes Jimenez E, Somé JW, Vosti SA, Guissou RM, Ouédraogo JB, Brown KH. Comparison of methods to assess adherence to small-quantity lipid-based nutrient supplements (SQ-LNS) and dispersible tablets among young Burkinabé children participating in a community-based intervention trial. Matern Child Nutr. 2015;11:90–104.View ArticlePubMedGoogle Scholar
  60. Harding KL, Matias SL, Mridha MK, Moniruzzaman M, Vosti SA, Hussain S, Dewey KG, Stewart CP. Adherence to recommendations on lipid-based nutrient supplement and iron and folic acid tablet consumption among pregnant and lactating women participating in a community health programme in Northwest Bangladesh. Matern Child Nutr. 2017;13(1). https://doi.org/10.1111/mcn.12252.
  61. Christian P, Shaikh S, Shamim AA, Mehra S, Wu L, Mitra M, Ali H, Merrill RD, Choudhury N, Parveen M. Effect of fortified complementary food supplementation on child growth in rural Bangladesh: a cluster-randomized trial. Int J Epidemiol. 2015;44(6):1862–76.View ArticlePubMedPubMed CentralGoogle Scholar
  62. Ashorn U, Alho L, Arimond M, Dewey KG, Maleta K, Phiri N, Phuka J, Vosti SA, Zeilani M, Ashorn P. Malawian mothers consider lipid-based nutrient supplements acceptable for children throughout a 1-year intervention, but deviation from user recommendations is common. J Nutr. 2015;145:1588–95.View ArticlePubMedGoogle Scholar
  63. Tondeur M, Salse U, Wilkinson C, Spiegel P, Seal A. Rapid acceptability and adherence testing of a lipid-based nutrient supplement and a micronutrient powder among refugee children and pregnant and lactating women in Algeria. Public Health Nutr. 2016;19:1852–61.View ArticlePubMedGoogle Scholar
  64. Vazir S, Engle P, Balakrishna N, Griffiths PL, Johnson SL, Creed-Kanashiro H, Fernandez Rao S, Shroff MR, Bentley ME. Cluster-randomized trial on complementary and responsive feeding education to caregivers found improved dietary intake, growth and development among rural Indian toddlers. Matern Child Nutr. 2013;9:99–117.View ArticlePubMedGoogle Scholar
  65. Dewey KG, Adu-Afarwuah S. Systematic review of the efficacy and effectiveness of complementary feeding interventions in developing countries. Matern Child Nutr. 2008;4:24–85.View ArticlePubMedGoogle Scholar
  66. Loevinsohn BP. Health education interventions in developing countries: a methodological review of published articles. Int J Epidemiol. 1990;19:788–94.View ArticlePubMedGoogle Scholar
  67. Black MM, Pérez-Escamilla R, Rao SF. Integrating nutrition and child development interventions: scientific basis, evidence of impact, and implementation considerations. Adv Nutr: Int Rev J. 2015;6:852–9.View ArticleGoogle Scholar
  68. Yousafzai AK, Rasheed MA, Rizvi A, Armstrong R, Bhutta ZA. Effect of integrated responsive stimulation and nutrition interventions in the lady health worker programme in Pakistan on child development, growth, and health outcomes: a cluster-randomised factorial effectiveness trial. Lancet. 2014;384:1282–93.View ArticlePubMedGoogle Scholar
  69. DiGirolamo AM, Stansbery P, Lung'aho M. Advantages and challenges of integration: opportunities for integrating early childhood development and nutrition programming. Ann N Y Acad Sci. 2014;1308:46–53.View ArticlePubMedGoogle Scholar
  70. Blackden CM, Wodon Q. Gender, time use, and poverty in sub-Saharan Africa. Washington DC: World Bank Publications; 2006.View ArticleGoogle Scholar
  71. Fontana M, Natali L. Gendered patterns of time use in Tanzania: public investment in infrastructure can help. In: IFPRI Project on ‘Evaluating the Long-Term Impact of Gender-focused Policy Interventions. New York: IFPRI; 2008.Google Scholar
  72. Arvai J, Post K. Risk Management in a Developing Country Context: improving decisions about point-of-use water treatment among the rural poor in Africa. Risk Anal. 2012;32:67–80.View ArticlePubMedGoogle Scholar
  73. Kruglanski AW, Shah JY, Fishbach A, Friedman R, Chun WY, Sleeth-Keppler D. A theory of goal systems. Adv Exp Soc Psychol. 2002;34:331–78.View ArticleGoogle Scholar
  74. Ram PK, Halder AK, Granger SP, Jones T, Hall P, Hitchcock D, Wright R, Nygren B, Islam MS, Molyneaux JW. Is structured observation a valid technique to measure handwashing behavior? Use of acceleration sensors embedded in soap to assess reactivity to structured observation. Am J Trop Med Hygiene. 2010;83:1070–6.View ArticleGoogle Scholar
  75. Cousens S, Kanki B, Toure S, Diallo I, Curtis V. Reactivity and repeatability of hygiene behaviour: structured observations from Burkina Faso. Soc Sci Med. 1996;43:1299–308.View ArticlePubMedGoogle Scholar

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