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Household survey data from 27 sites in 22 countries were collected in 2017–2018 in order to construct and validate a cross-cultural household-level water insecurity scale. The resultant Household Water Insecurity Experiences (HWISE) scale presents a useful tool for monitoring and evaluating water interventions as a complement to traditional metrics used by the development community. It can also help track progress toward achievement of Sustainable Development Goal 6 ‘clean water and sanitation for all’. We present HWISE scale scores from 27 sites as comparative data for future studies using the HWISE scale in low- and middle-income contexts. Site-level mean scores for HWISE-12 (scored 0–36) ranged from 1.64 (SD 4.22) in Pune, India, to 20.90 (7.50) in Cartagena, Colombia, while site-level mean scores for HWISE-4 (scored 0–12) ranged from 0.51 (1.50) in Pune, India, to 8.21 (2.55) in Punjab, Pakistan. Scores tended to be higher in the dry season as expected. Data from this first implementation of the HWISE scale demonstrate the diversity of water insecurity within and across communities and can help to situate findings from future applications of this tool. HIGHLIGHTS We present comparison scores of the Household Water Insecurity Experiences (HWISE) scale, a novel household water insecurity index validated for use in low- and middle-income countries.; These scores can aid interpretation of future implementation of the HWISE scale.; The HWISE scale should still be evaluated in new contexts, such as high-income settings.;
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Short Communication
The Household Water Insecurity Experiences (HWISE) Scale: comparison scores from
27 sites in 22 countries
Justin Stoler a,*, Joshua D. Miller b, Ellis A. Adams c, Farooq Ahmed d, Mallika Alexandere, Gershim Asikif,
Mobolanle Balogun g, Michael J. Boivinh, Alexandra Brewis i, Genny Carrilloj, Kelly Chapman k,
Stroma Cole l, Shalean M. Collinsm, Jorge Escobar-Vargasn, Hassan Eini-Zinabo, Matthew C. Freeman p,
Monet Ghorbanii, Ashley Hagaman q, Nicola Hawleyq, Zeina Jamaluddine r, Wendy E. Jepson j,
Divya Krishnakumars, Kenneth Maest, Jyoti Mathad u, Jonathan Maupin i, Patrick Mbullo Owuorv,
Milton Marin Moralesw, Javier Morán-Martínez x, Nasrin Omidvar o, Amber L. Pearson h, Sabrina Rasheedy,
Asher Y. Rosinger z, Luisa Samayoa-Figueroaaa, Ernesto C. Sánchez-Rodríguez ab, Marianne V. Santoso v,
Roseanne C. Schuster i, Mahdieh Sheikhio, Sonali Srivastavas, Chad Staddon ac, Andrea Sullivan a,
Yihenew Tesfaye ad, Alex Trowell ae, Desire Tshala-Katumbayaf, Raymond Tutuag, Cassandra L. Workman ah,
Amber Wutich i, Sera L. Young vand The Household Water Insecurity Experiences Research Coordination
Network (HWISE-RCN)
a
University of Miami, Coral Gables, FL 33146, USA
b
University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
c
University of Notre Dame, South Bend, IN, USA
d
Quaid-i-Azam University Islamabad, Islamabad, Pakistan
e
Johns Hopkins University-Byramjee Jeejeebhoy Medical College Clinical Trials Unit, Pune, India
f
African Population and Health Research Center, Nairobi, Kenya
g
College of Medicine of the University of Lagos, Lagos, Nigeria
h
Michigan State University, East Lansing, MI, USA
i
Arizona State University, Tempe, AZ, USA
j
Texas A&M University, College Station, TX, USA
k
University of Florida, Gainesville, FL, USA
l
University of Westminster, London, UK
m
Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
n
Ponticia Universidad Javeriana, Bogotá, Colombia
o
Shahid Beheshti University of Medical Sciences, Tehran, Iran
p
Emory University, Atlanta, GA, USA
q
Yale School of Public Health, New Haven, CT, USA
r
London School of Tropical Medicine and Hygiene, London, UK
s
Anode Governance Lab, Bengaluru, India
t
Oregon State University, Corvallis, OR, USA
u
Weill Cornell Medicine, New York, NY, USA
v
Northwestern University, Evanston, IL, USA
w
Universidad Autónoma del Beni José Ballivián, Trinidad, Bolivia
x
Autonomous University of Coahuila, Coahuila, Mexico
y
International Centre for Diarrhoeal Disease Research Bangladesh, Dhaka, Bangladesh
z
Pennsylvania State University, State College, PA, USA
aa
McGill University, Ste-Anne-de-Bellevue, Quebec, Canada
ab
Hospital Agustin OHoran, Mérida, Yucatan, Mexico
ac
University of the West of England, Bristol, UK
ad
Bahir Dar University, Bahir Dar, Ethiopia
ae
University of Amsterdam, Amsterdam, The Netherlands
af
Oregon Health & Science University, Portland, OR, USA
ag
Delaware State University, Dover, DE, USA
ah
University of North Carolina at Greensboro, Greensboro, NC, USA
*Corresponding author. E-mail: stoler@miami.edu
JS, 0000-0001-8435-7012; JDM, 0000-0002-2171-856X; EAA, 0000-0003-3783-9005; FA, 0000-0002-4668-2882; MB, 0000-0001-8147-2111;
AB, 0000-0003-3769-4205; KC, 0000-0002-5417-9400; SC, 0000-0002-9135-9339; MCF, 0000-0002-1517-2572; AH, 0000-0002-8016-1036;
ZJ, 0000-0003-2074-9329; WEJ, 0000-0002-7693-1376; JM, 0000-0001-9487-7775; JM, 0000-0003-2610-2737; JM, 0000-0002-6514-238X;
NO, 0000-0002-4061-0562; ALP, 0000-0002-8848-1798; AYR, 0000-0001-9587-1447; ECS, 0000-0001-8650-2092; MVS, 0000-0001-6302-9116;
RCS, 0000-0002-3747-5267; CS, 0000-0002-2063-8525; AS, 0000-0002-4486-4228;YT,0000-0003-0824-7756;AT,0000-0001-6060-2503;
CLW, 0000-0003-0021-6541;AW,0000-0003-4164-1632;SLY,0000-0002-1763-1218
This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY-NC-ND 4.0), which permits copying and
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ABSTRACT
Household survey data from 27 sites in 22 countries were collected in 20172018 in order to construct and validate a cross-cultural house-
hold-level water insecurity scale. The resultant Household Water Insecurity Experiences (HWISE) scale presents a useful tool for monitoring
and evaluating water interventions as a complement to traditional metrics used by the development community. It can also help track pro-
gress toward achievement of Sustainable Development Goal 6 clean water and sanitation for all. We present HWISE scale scores from 27
sites as comparative data for future studies using the HWISE scale in low- and middle-income contexts. Site-level mean scores for HWISE-12
(scored 036) ranged from 1.64 (SD 4.22) in Pune, India, to 20.90 (7.50) in Cartagena, Colombia, while site-level mean scores for HWISE-4
(scored 012) ranged from 0.51 (1.50) in Pune, India, to 8.21 (2.55) in Punjab, Pakistan. Scores tended to be higher in the dry season as
expected. Data from this rst implementation of the HWISE scale demonstrate the diversity of water insecurity within and across commu-
nities and can help to situate ndings from future applications of this tool.
Key words: global health, measurement, metrics, water insecurity
HIGHLIGHTS
We present comparison scores of the Household Water Insecurity Experiences (HWISE) scale, a novel household water insecurity index
validated for use in low- and middle-income countries.
These scores can aid interpretation of future implementation of the HWISE scale.
The HWISE scale should still be evaluated in new contexts, such as high-income settings.
INTRODUCTION
Household-level water insecurity the inability to access and benet from adequate, reliable, and safe water for well-being
and a healthy life affects billions of people globally, but until recently, there were few metrics that could facilitate its house-
hold-level monitoring and evaluation (Jepson et al. 2017;Wutich et al. 2017). Freshwater availability has traditionally been
reported at the community, watershed, or national level using resource-based metrics, but advances in water insecurity
measurement have led to the creation of at least 13 different scales that measure household water experiences with avail-
ability, accessibility, reliability, and use, in contrast with at least 67 resource-based metrics that assess freshwater
availability at larger geographic scales (Octavianti & Staddon 2021). These experiential metrics are particularly crucial for
understanding human adaptation to natural resource stressors associated with climate change (Maja & Ayano 2021).
The Household Water Insecurity Experiences Research Coordination Network (HWISE-RCN; www.hwise-rcn.org) was
formed in 2018 to promote scholarship and practice related to mitigating household-level water insecurity. Investigators col-
lected data from 27 sites in low- and middle-income countries between 2017 and 2018 as part of a larger project that created
and validated a cross-culturally comparable household water insecurity scale (Young et al. 2019b). This 12-item experiential
scale, known as the HWISE scale or HWISE-12 (Young et al. 2019a), has received interest throughout the international
development communities as a monitoring and evaluation tool that can complement the household-level metrics produced
by the World Health Organizations (WHO) Joint Monitoring Programme for Water Supply, Sanitation and Hygiene (JMP)
(Slaymaker et al. 2020). A shortened 4-item version of the scale (the HWISE-4) was recently validated to facilitate rapid
deployment in eld survey settings with constrained resources (Young et al. 2021).
Several HWISE-RCN-afliated studies have focused on how these new metrics are associated with water governance
(Miller et al. 2020), water sharing (Rosinger et al. 2020), nancial expenditures on water (Stoler et al. 2020), injuries
(Venkataramanan et al. 2020), and self-reported health (Jepson et al. 2021). Research on the measurement of water insecur-
ity, however, has not fully considered how the HWISE scale varies within and across sites. For instance, while studies have
demonstrated the validity of the HWISE scale and its relationship with economic, health, and social outcomes, none have
provided site-level scores. This brief provides a site-wise summary of the different HWISE scale scores as points of compari-
son for future research that uses these metrics to study household water insecurity and better understand these scalesutility
in diverse global settings.
METHODS
Cross-sectional survey data were collected from 7,709 households in 27 sites across 22 countries in two waves. Sites were
selected through existing professional networks to maximize variation in local climate, water infrastructure, and typical
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water problems (Young et al. 2019b). Most sites targeted approximately 250 households and used simple random sampling to
select households, with four exceptions (purposive sampling in Singida, Tanzania; Kampala, Uganda; and Upolu, Samoa; par-
allel assignment in Pune, India) for ongoing studies that required different sampling strategies to achieve their research
objectives. Adults were eligible respondents if they reported being knowledgeable about their households water situation
(Young et al. 2019a). The HWISE survey provided a much more detailed view of household water insecurity than other stan-
dard household surveys, such as Demographic and Health Surveys or Multiple Indicator Cluster Surveys, because it also
probed experiences that demonstrate the consequences of inadequate, unreliable, or unsafe water. All participants provided
verbal or written informed consent in the respective local language, and all study activities were reviewed and approved by
the appropriate ethical review boards (Young et al. 2019b).
Enumerators used paper- and tablet-based surveys to collect data on sociodemographic characteristics and experiences
with water availability, accessibility, reliability, and use, which are core components of household water insecurity (Jepson
et al. 2017). Table 1 presents the composition of the HWISE-12, HWISE-11, and HWISE-4 scales with the full wording of
each item. Each item reects an experience related to water adequacy (having sufcient quantity for drinking and household
consumption), reliability (the availability of water when needed), safety (water that is t-for-use, such as drinking or bathing),
or psychosocial experiences related to these problems.
Each survey item elicited the frequency of household experiences related to water in 4 weeks prior to the survey and cate-
gorized responses as: never (0 times) scored as 0,rarely (12 times) scored as 1,sometimes (310 times) scored as 2, and
often (1120 times) or always (more than 20 times) which were combined and scored as 3. The HWISE-12 is calculated by
summing the scores of 12 items, yielding a range of 036 (Young et al. 2019a), and the HWISE-4 is the sum of four items from
Table 1 |Item composition of the HWISE-12, HWISE-11, and HWISE-4 scales
Label Survey item HWISE-12 HWISE-11 HWISE-4
Worry In the last 4 weeks, how frequently did you or anyone in your household worry you would not
have enough water for all of your household needs?
XXX
Hands In the last 4 weeks, how frequently have you or anyone in your household had to go without
washing hands after dirty activities (e.g., defecating or changing diapers, cleaning animal dung)
because of problems with water?
XXX
Plans In the last 4 weeks, how frequently has you or anyone in your household had to change schedules/
plans due to problems with your water situation, such as problems getting or distributing water
within the household? (Activities that may have been interrupted include caring for others and
doing household chores)
XXX
Drink In the last 4 weeks, how frequently has there not been as much water to drink as you would like
for you or anyone in your household?
XXX
Interrupt In the last 4 weeks, how frequently has your household water supply from your main water source
been interrupted or limited (e.g., water pressure, less water than expected)?
XX
Clothes In the last 4 weeks, how frequently has there not been enough water in the household to wash
clothes?
XX
Food In the last 4 weeks, how frequently have you or anyone in your household had to change what was
being eaten because there were problems with water (e.g., for washing foods and cooking)?
XX
Bathe In the last 4 weeks, how frequently have you or anyone in your household had to go without
washing their body because of problems with water (e.g., not enough water, dirty, and unsafe)?
XX
Angry In the last 4 weeks, how frequently did you or anyone in your household feel angry about your
water situation?
XX
Sleep In the last 4 weeks, how frequently have you or anyone in your household gone to sleep thirsty
because there was not any water to drink?
XX
None In the last 4 weeks, how frequently has there been no useable or drinkable water whatsoever in
your household?
XX
Shame In the last 4 weeks, how frequently have problems with water caused you or anyone in your
household to feel ashamed/excluded/stigmatized?
X
Note: Items classied as never (0 times), rarely (12 times), sometimes (310 times), and often/always (11 times or more); score ranges are 036 for HWISE-12, 033 for HWISE-11, and
012 for HWISE-4.
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the HWISE-12 with a range of 012 (Young et al. 2021). One HWISE-12 item, related to experiencing shame about ones
water situation, was introduced in late-2017 during the second wave of data collection. As a result, the HWISE scale in
study sites surveyed during the rst wave has typically been represented as the HWISE-11 without the shame item (range
033); the HWISE-11 accounted for 99.3% of the variation in HWISE-12 scores with minimal additional error (Stoler
et al. 2020).
This research brief presents the mean, standard deviation, and additional descriptive information of 27 sites for (1)
HWISE-12 (where available), (2) HWISE-11, (3) HWISE-4, and (4) the Household Food Insecurity Access Scale (HFIAS,
range 027) (Coates et al. 2007). We provide HFIAS scores for additional context given the wide availability of HFIAS refer-
ence data globally and its cross-cultural applicability, and because HFIAS and HWISE scores have been associated with each
other in prior studies (Young et al. 2019a;Stoler et al. 2020).
RESULTS AND DISCUSSION
Table 2 presents the four indicators as well as season (wet, dry, both, or neither) and sample size information. There were
3,293 households from 13 sites with complete HWISE-12 data (i.e., the 11 sites used to derive HWISE-12 in Pune, India,
and Dhaka and Chakaria, Bangladesh), yielding an aggregate mean score of 9.32 (standard deviation [SD] ¼8.81). Site-
level mean HWISE-12 scores ranged from 1.64 (SD ¼4.22) in Pune, India, to 20.90 (SD ¼7.50) in Cartagena, Colombia.
HWISE-12 can offer a more nuanced view of water insecurity than WHO JMP measures of drinking water service level,
which do not consider sufciency for all household uses. For instance, the HWISE-12 identied water insecurity even
among households with basicwater services, as classied by the JMP drinking water service ladder (Young et al. 2019a).
Because we could only compute HWISE-12 for 13 sites, Table 1 also contains HWISE-11 estimates for all 27 sites. Among
6,484 households, the aggregated mean HWISE-11 score was 6.95 (SD ¼7.50). Site-mean HWISE-11 scores ranged from 1.54
(3.78) in Pune, India, to 19.56 (5.65) in Punjab, Pakistan.
HWISE-4 scores could be computed for 7,351 households across the 27 sites, yielding an aggregate mean score of 2.84
(SD ¼3.08). Site-mean HWISE-4 scores ranged from 0.51 (SD ¼1.50) in Pune, India, to 8.21 (SD ¼2.55) in Punjab, Pakistan.
We present a bubble plot of the mean site scores in Figure 1, and the frequency of afrmation for each item (never, rarely,
sometimes, or often) by site in Supplementary Figure 1, to aid interpretation of the variation within and between sites that is
summarized by the means and standard deviations in Table 2. HWISE scale scores exhibited greater variation in sites sur-
veyed during the rainy season, perhaps because household-level characteristics (e.g., differences in wealth and nancial
access to water storage technologies) modied householdsability to take advantage of relatively higher water availability.
Sites surveyed during the dry season tended to have higher HWISE scale scores as expected, and less variability, indicating
that seasonal decreases in water availability may have affected households more uniformly. Although the sites with the ve
highest scores across all HWISE measures were surveyed in dry conditions, household water insecurity is shaped by local
context as well. For example, the marginalized community where the survey was implemented in Cartagena was, in 2018,
awaiting a long-delayed piped water service expansion by the municipal water authority. The bar chart for Cartagena in Sup-
plementary Figure 1 reveals the frustration that characterized this communitys water insecurity: nearly 75% of respondents
reported worryor angerabout their water situation often or always, by far the highest prevalence of these experiences
among all sites.
Finally, we computed HFIAS scores for 7,077 households across 26 sites (HFIAS was not implemented in Upolu, Samoa),
yielding an aggregate mean score of 6.10 (SD ¼6.58). Site-mean HFIAS scores ranged from 1.03 (SD ¼2.55) in Kathmandu,
Nepal, to 16.08 (SD ¼8.06) in Gressier, Haiti. The overall range was typical of HFIAS scores observed in similar low- and
middle-income settings (e.g., De Cock et al. 2013;Roba et al. 2019).
CONCLUSION
This research brief presents site-level HWISE-12, HWISE-11, HWISE-4, and HFIAS scores for 27 study sites across 22
countries. Overall, there was substantial variability within and between sites, as well as by season, reecting the many
ways in which households or communities experience and adapt to water insecurity (Jepson et al. 2017). These scores provide
comparison data for future studies that use, adapt, or improve these metrics for novel contexts. We hope that future deploy-
ment of the HWISE scale will establish testretest or interrater reliability, attempt to validate a version for high-income
countries, or assess its utility in dynamic scenarios such as disaster recovery. The scale is limited in that it does not illuminate
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Table 2 |Mean and standard deviation (SD) of the HWISE-12, HWISE-11, HWISE-4, and HFIAS indicators by site with season (wet, dry, both, or neither), sample size(n), and the
number of missing cases
HWISE-12 (range: 036) HWISE-11 (range: 033) HWISE-4 (range: 012) HFIAS (range: 027)
Site Season Mean SD nMissing Mean SD nMissing Mean SD nMissing Mean SD nMissing
Africa
Ethiopia (Bahir Dar) Rainy 4.10 6.03 10 249 2.02 2.27 253 6 2.67 3.53 259 0
Ghana (Accra) Rainy 5.50 6.25 221 8 1.98 2.33 227 2 6.70 6.24 225 4
Kenya (Kisumu) Neither 11.60 5.73 245 2 4.44 2.17 247 0 12.65 4.92 239 8
Malawi (Lilongwe) Neither 5.83 5.23 290 12 2.13 2.12 297 5 7.93 6.47 302 0
Nigeria (Lagos) Rainy 2.49 3.33 227 12 0.99 1.48 235 4 2.70 3.81 234 5
Tanzania (Morogoro) Rainy 4.18 4.78 256 44 4.11 4.62 256 44 1.40 2.02 269 31 6.50 5.89 274 26
Tanzania (Singida) Dry 1.57 3.15 561 3 0.71 1.38 563 1 4.69 5.06 562 2
Uganda (Arua) Rainy 11.89 8.02 227 23 4.71 3.22 242 8 11.90 5.58 239 11
Uganda (Kampala) Dry 6.91 5.46 215 31 2.43 2.06 236 10 8.15 6.20 195 51
East Asia and Pacic
Indonesia (Labuan Bajo) Dry 13.80 7.68 268 11 13.46 7.32 268 11 5.01 2.86 273 6 5.03 5.07 273 6
Samoa (Upolu) Both 1.58 4.45 171 113 0.69 2.01 174 110 0 284
Europe and Central Asia
Tajikistan (Dushanbe) Dry 5.84 5.13 220 5 2.23 2.22 222 3 3.01 3.35 222 3
Latin America and the Caribbean
Bolivia (San Borja) Dry 17.51 7.89 171 76 15.99 7.35 177 70 5.82 2.93 202 45 7.14 5.60 175 72
Brazil (Ceará) Neither 2.22 3.40 187 67 1.03 1.57 201 53 3.46 5.36 239 15
Colombia (Cartagena) Dry 20.90 7.50 218 48 19.47 6.95 224 42 7.58 2.98 256 10 11.86 6.57 246 20
Guatemala (Acatenango) Dry 3.98 6.57 93 8 1.67 2.53 95 6 4.68 6.61 82 19
Guatemala (Chiquimula) Dry 5.21 5.28 286 28 5.13 5.20 287 27 2.32 2.50 311 3 7.54 5.63 311 3
Haiti (Gressier) Dry 9.82 9.10 280 12 9.24 8.37 281 11 3.62 3.36 290 2 16.08 8.06 272 20
Mexico (Mérida) Dry 3.20 4.36 234 16 1.52 1.80 247 3 3.82 3.71 241 9
Mexico (Torreón) Dry 8.56 8.37 239 10 8.34 8.09 239 10 2.89 2.93 246 3 3.11 4.82 248 1
Middle East and North Africa
Iran (Sistan & Balochistan) Rainy 6.03 6.51 132 174 5.74 6.01 133 173 2.87 2.56 305 1 5.50 5.61 303 3
Lebanon (Beirut) Rainy 7.13 7.02 544 30 6.76 6.60 544 30 2.54 2.77 560 14 5.85 7.49 545 29
(Continued.)
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Table 2 |Continued
HWISE-12 (range: 036) HWISE-11 (range: 033) HWISE-4 (range: 012) HFIAS (range: 027)
Site Season Mean SD nMissing Mean SD nMissing Mean SD nMissing Mean SD nMissing
South Asia
Bangladesh (Dhaka & Chakaria) Both 6.89 7.98 473 33 5.95 7.60 502 4 2.30 2.93 506 0 4.35 5.84 506 0
India (Pune) Both 1.64 4.22 171 9 1.54 3.78 171 9 0.51 1.50 176 4 1.04 2.47 159 21
India (Rajasthan) Dry 13.94 7.41 208 40 12.72 6.71 209 39 5.08 2.93 235 13 4.43 6.17 244 4
Nepal (Kathmandu) Rainy 5.49 4.61 244 19 2.29 1.81 259 4 1.03 2.55 263 0
Pakistan (Punjab) Dry 20.36 5.92 47 188 19.56 5.65 48 187 8.21 2.55 224 11 7.63 5.87 219 16
Aggregate (all sites) 9.32 8.81 3,293 703 6.95 7.50 6,484 1,225 2.84 3.08 7,351 358 6.10 6.58 7,077 632
Note: Sites are ordered by the World Bank region.
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Figure 1 |Bubble plots of site-mean scores for (a) HWISE-12, (b) HWISE-11, and (c) HWISE-4, with linear trend line. Bubble size is propor-
tionate to site sample size. Bold-outlined bubbles indicate sites surveyed exclusively in the dry season.
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differences in the underlying causes of water insecurity, which may be individual in nature (e.g., the elderly being unable to lift
large containers of water) or structural (e.g., exclusion due to gender or ethnic discrimination) (Slaymaker et al. 2020), or
convey the degree of household disruption from a given water insecurity experience. Because the HWISE-12 and the
HWISE-4 were intended to represent universal, but not comprehensive, experiences of household water insecurity, studies
may benet from including additional complementary metrics of water insecurity sub-domains that are not necessarily appli-
cable to all households in a given community, such as experiences with water conict, effects on children, or water used for
agricultural livelihoods. Nonetheless, the ability to rapidly screen communities cross-culturally makes the HWISE scale an
important tool that can help public health practitioners track progress toward achievement of Sustainable Development
Goal 6 clean water and sanitation for all.
ACKNOWLEDGEMENTS
We acknowledge the support of the Household Water Insecurity Experiences Research Coordination Network (HWISE-
RCN) funded by the National Science Foundation under grant no. BCS-1759972. We also thank Hala Ghattas, Hugo
Melgar-Quiñonez, and Nathaly Triviño for additional support of this project. The HWISE study was funded with the Com-
petitive Research Grants to Develop Innovative Methods and Metrics for Agriculture and Nutrition Actions (IMMANA).
IMMANA is funded with UK Aid from the UK government. This project was also supported by the Buffett Institute for
Global Studies and the Center for Water Research at Northwestern University; Arizona State Universitys Center for
Global Health at the School of Human Evolution and Social Change and Decision Center for a Desert City (National Science
Foundation, No. SES-1462086); and the Ofce of the Vice Provost for Research of the University of Miami. S.L.Y. was sup-
ported by the National Institutes of Health (Nos NIMH R21 MH108444 and NIMH K01 MH098902). W.E.J. was supported
by the National Science Foundation (No. BCS-1560962) and the Texas A&M University-CONACYT Research Collaborative
Grant. C.S. was supported by the Lloyds Register Foundation. M.C.F. was supported by the World Bank Strategic Impact
Evaluation Fund (Award No. 7175829). Funders of the study had no role in study design, data collection, data analysis,
data interpretation, or writing of the report.
AUTHOR CONTRIBUTIONS
J.S. is involved in the conceptualization, formal analysis, investigation, writing original draft, and writing review & editing.
J.D.M. is involved in formal analysis, investigation, and writing review & editing. All other authors are involved in the inves-
tigation and writing review & editing.
CONFLICT OF INTEREST
This research does not contain any conict of interest.
DATA AVAILABILITY STATEMENT
Data cannot be made publicly available; readers should contact the corresponding author for details.
REFERENCES
Coates, J., Swindale, A. & Bilinsky, P. 2007 Household Food Insecurity Access Scale (HFIAS) for Measurement of Food Access: Indicator
Guide. Food and Nutrition Technical Assistance III Project (FANTA) (ed.), FHI 360/FANTA, Washington, DC.
De Cock, N., DHaese, M., Vink, N., van Rooyen, C. J., Staelens, L., Schönfeldt, H. C. & DHaese, L. 2013 Food security in rural areas of
Limpopo province, South Africa.Food Security 5(2), 269282.
Jepson, W. E., Wutich, A., Colllins, S. M., Boateng, G. O. & Young, S. L. 2017 Progress in household water insecurity metrics: a cross-
disciplinary approach.WIREs Water 4(3), e1214.
Jepson, W. E., Stoler, J., Baek, J., Morán Martínez, J., Uribe Salas, F. J. & Carrillo, G. 2021 Cross-sectional study to measure household water
insecurity and its health outcomes in urban Mexico.BMJ Open 11 (3), e040825.
Maja, M. M. & Ayano, S. F. 2021 The impact of population growth on natural resources and farmerscapacity to adapt to climate change in
low-income countries.Earth Systems and Environment 5(2), 271283.
Miller, J. D., Vonk, J., Staddon, C. & Young, S. L. 2020 Is household water insecurity a link between water governance and well-being?
A multi-site analysis. Journal of Water, Sanitation and Hygiene for Development.
Octavianti, T. & Staddon, C. 2021 A review of 80 assessment tools measuring water security.WIREs Water 8(3), e1516.
Journal of Water, Sanitation and Hygiene for Development Vol 00 No 0, 8
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Downloaded from http://iwaponline.com/washdev/article-pdf/doi/10.2166/washdev.2021.108/941253/washdev2021108.pdf
by guest
on 29 September 2021
Roba, K. T., OConnor, T. P., OBrien, N. M., Aweke, C. S., Kahsay, Z. A., Chisholm, N. & Lahiff, E. 2019 Seasonal variations in household
food insecurity and dietary diversity and their association with maternal and child nutritional status in rural Ethiopia.Food Security
11 (3), 651664.
Rosinger, A. Y., Brewis, A., Wutich, A., Jepson, W., Staddon, C., Stoler, J., Young, S. L. & RCN, H. W. I. S. E. 2020 Water borrowing is
consistently practiced globally and is associated with water-related system failures across diverse environments.Global Environmental
Change 64, 102148.
Slaymaker, T., Johnston, R., Young, S., Miller, J. & Staddon, C. 2020 WaSH Policy Research Digest Issue #15: Measuring Water Insecurity.
University of North Carolina, Chapel Hill, NC.
Stoler, J., Pearson, A. L., Staddon, C., Wutich, A., Mack, E., Brewis, A., Rosinger, A. Y. & RCN, H. W. I. S. E. 2020 Cash water expenditures
are associated with household water insecurity, food insecurity, and perceived stress in study sites across 20 low- and middle-income
countries.Science of the Total Environment 716, 135881.
Venkataramanan, V., Geere, J. A., Thomae, B., Stoler, J., Hunter, P. R., Young, S. L. & RCN, H. W. I. S. E. 2020 In pursuit of safewater: the
burden of personal injury from water-fetching in 21 low- and middle-income countries.BMJ Global Health 5, e003328.
Wutich, A., Budds, J., Eichelberger, L., Geere, J., Harris L, M., Horney J, A., Jepson, W., Norman, E., OReilly, K., Pearson, A. L., Shah S, H.,
Shinn, J., Simpson, K., Staddon, C., Stoler, J., Teodoro, M. P. & Young S, L. 2017 Advancing methods for research on household water
insecurity: studying entitlements and capabilities, socio-cultural dynamics, and political processes, institutions and governance.Water
Security 2,110.
Young, S., Boateng, G., Jamaluddine, Z., Miller, J., Frongillo, E., Neilands, T., Collins, S., Wutich, A., Jepson, W. & Stoler, J. & HWISE-RCN
2019a The Household Water InSecurity Experiences (HWISE) Scale: development and validation of a household water insecurity
measure for low- and middle-income countries.BMJ Global Health 4(5), e001750.
Young, S. L., Collins, S. M., Boateng, G. O., Neilands, T. B., Jamaluddine, Z., Miller, J. D., Brewis, A. A., Frongillo, E. A., Jepson, W. E.,
Melgar-Quiñonez, H., Schuster, R. C., Stoler, J. B. & Wutich, A. & HWISE-RCN 2019b Development and validation protocol for an
instrument to measure household water insecurity across cultures and ecologies: the Household Water InSecurity Experiences (HWISE)
Scale.BMJ Open 9(1), e023558.
Young, S. L., Miller, J. D., Frongillo, E. A., Boateng, G. O., Jamaluddine, Z. & Neilands, T. B. 2021 Validity of a four-item Household Water
Insecurity Experiences Scale for assessing water issues related to health and well-being.The American Journal of Tropical Medicine and
Hygiene 104 (1), 391394.
First received 24 June 2021; accepted in revised form 12 September 2021. Available online 28 September 2021
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... Only 2% of households had scores of ≥12, defined previously as the provisional threshold for water insecurity (Young et al., 2019a). A number of sites where HWISE has been implemented had low mean site scores similar to Tsimane' (Stoler et al., 2021). For example, households in the Pune, India site had a mean score of 1.6 for the HWISE 12, while still demonstrating accuracy, validity, and reliability of the scale . ...
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