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  <front>
    <journal-meta><journal-id journal-id-type="publisher">DWES</journal-id><journal-title-group>
    <journal-title>Drinking Water Engineering and Science</journal-title>
    <abbrev-journal-title abbrev-type="publisher">DWES</abbrev-journal-title><abbrev-journal-title abbrev-type="nlm-ta">Drink. Water Eng. Sci.</abbrev-journal-title>
  </journal-title-group><issn pub-type="epub">1996-9465</issn><publisher>
    <publisher-name>Copernicus Publications</publisher-name>
    <publisher-loc>Göttingen, Germany</publisher-loc>
  </publisher></journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.5194/dwes-13-43-2020</article-id><title-group><article-title>Consumption of safe drinking water in Pakistan:<?xmltex \hack{\break}?> its dimensions and
determinants</article-title><alt-title>Consumption of safe drinking water in Pakistan</alt-title>
      </title-group><?xmltex \runningtitle{Consumption of safe drinking water in Pakistan}?><?xmltex \runningauthor{N. Akram}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes">
          <name><surname>Akram</surname><given-names>Naeem</given-names></name>
          <email>naeem378@yahoo.com</email>
        <ext-link>https://orcid.org/0000-0002-9314-8164</ext-link></contrib>
        <aff id="aff1"><institution>Ministry of Economic Affairs, Islamabad, Pakistan</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Naeem Akram (naeem378@yahoo.com)</corresp></author-notes><pub-date><day>25</day><month>September</month><year>2020</year></pub-date>
      
      <volume>13</volume>
      <issue>2</issue>
      <fpage>43</fpage><lpage>50</lpage>
      <history>
        <date date-type="received"><day>21</day><month>February</month><year>2020</year></date>
           <date date-type="rev-request"><day>17</day><month>March</month><year>2020</year></date>
           <date date-type="rev-recd"><day>9</day><month>June</month><year>2020</year></date>
           <date date-type="accepted"><day>14</day><month>August</month><year>2020</year></date>
      </history>
      <permissions>
        <copyright-statement>Copyright: © 2020 Naeem Akram</copyright-statement>
        <copyright-year>2020</copyright-year>
      <license license-type="open-access"><license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p></license></permissions><self-uri xlink:href="https://dwes.copernicus.org/articles/13/43/2020/dwes-13-43-2020.html">This article is available from https://dwes.copernicus.org/articles/13/43/2020/dwes-13-43-2020.html</self-uri><self-uri xlink:href="https://dwes.copernicus.org/articles/13/43/2020/dwes-13-43-2020.pdf">The full text article is available as a PDF file from https://dwes.copernicus.org/articles/13/43/2020/dwes-13-43-2020.pdf</self-uri>
      <abstract><title>Abstract</title>
    <p id="d1e79">Safe drinking water is one of the basic human needs. Poor quality of
drinking water is directly associated with various waterborne diseases. The
present study has attempted to analyze the household preferences for
drinking water sources and the adoption of household water treatment (HWT)
in Pakistan by using the household data of Pakistan Demographic and Health
Survey 2017–2018 (PDHS, 2018). This study found that people living in rural areas, those with older heads of household and those with large family sizes are significantly less likely
to use water from bottled or filtered water. Households with media
exposure, education, women's empowerment in household purchases and high incomes are more likely to use bottled or filtered
water. Similarly, households are more likely to adopt HWT in urban areas, when there is a higher level of awareness (through education and media), higher incomes, women enjoy a higher level of empowerment, and piped water is already used. However, households that use water from wells and have higher family sizes are less likely to adopt water purifying methods at home.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <label>1</label><title>Introduction</title>
      <p id="d1e91">Access to clean and safe drinking water is a basic human right. However
utilization of contaminated water is increasing (particularly in developing
countries). Approximately 12 % of the world population lacks access to
safe drinking water (World Economic Forum, 2019). It has been estimated that
approximately 785 million people worldwide are drinking water from
unimproved sources; 207 million people have to spend at least 30 min to
reach water source, and 144 million people get drinking water from rivers,
streams or lakes (WHO/UNICEF, 2019).</p>
      <p id="d1e94">Consequently, unsafe water leads to chronic diseases like typhoid, diarrhea,
cholera and parasites (Curry, 2010). It has been estimated that due to diarrhea,
around 1.3 million people die annually; among them 88 % are children (IHME,
2015). Consumption of safe drinking water can prevent the fatal cases of
diarrhea (Fewtrell et al., 2005). This is supported by the fact that during
1870–1930 due to the provision of piped water in the urban areas of the USA,
mortality rates had declined rapidly (Cutler and Miller, 2005). However,
Brick et al. (2004) and Checkley et al. (2004) were of the view that to
achieve the maximum health benefits by using clean water, there is a need for
sanitation and hygiene conditions to also be improved.</p>
      <p id="d1e97">Pakistan ranks ninth on the list of top 10 countries without access to
safe drinking water. In Pakistan, having a population of 207 million in
2018, 21 million people did not have access to safe drinking water (Water
Aid, 2018). Similarly, the Pakistan Council of Research in Water Resources
(PCRWR, 2012) concluded that the quality of water has deteriorated over the
years because of the contamination of chemical pollutants and human waste.</p>
      <p id="d1e100">Provision of clean water to the households can be achieved in two ways: by
supplying treated water at the point of collection and household water
treatment (HWT). In the first approach, studies found that significant
re-contamination can occur during the process of transportation and storage
of the water, and even storage material and duration affects the water
quality (Checkley et al., 2004; Brick et al., 2004). Brick et al. (2004) and
Fewtrell et al. (2005) argued that HWT is the more effective method for the
provision of safe drinking water as compared to supplying treated water at
the point of collection. Examples of HWT are boiling (Mintz et al.,<?pagebreak page44?> 1995), chemical
treatment (Quick et al.,1999) and chlorination (Clasen et al., 2015).
However, various studies concluded that despite having positive impacts
adoptability of HWT is very limited (Brown and Clasen, 2012).</p>
      <p id="d1e104">Consumer behavior regarding the adoption of HWT is affected by numerous
factors. Past studies have found that income (Bruce and Gnedenko, 1998),
education (Dasgupta, 2001; McConnell and Rosado, 2000), education of
female household members (Jyotsna et al., 2003), age of household head (Mintz
et al., 2001), household size (Sattar and Ahmad, 2007), level of awareness
(Quick et al., 1999; Jalan et al., 2009), cost of HWT methods (Jalan
and Somanathan, 2008), wealth of the household (Fotue et al., 2012),
locality of residence (Bruce and Gnedenko, 1998), type of water source
(Daniel et al., 2019), and perception about water quality and usefulness of HWT
(Daniel et al., 2018) are the key factors in determining the adoption of
HWT.</p>
      <p id="d1e107">Very limited studies are being conducted on determinants of a household's
preference for drinking water sources. In this regard, Abrahams et al. (2000) found that perceived risk of using tap water, age, income and race
are important factors in the usage of bottled water. Haq et al. (2007)
found that education of household head and quality of available water play
a significant role in determining the demand of improved water sources in
Pakistan. Rauf et al. (2015) found that family size and distance of the house
from the water source have a negative impact on the consumption of safe drinking
water sources. Zulfiqar et al. (2016) concluded that living in urban areas
has a positive effect, while age of household head and the incidence of water-borne
disease to any household member have a negative impact on the use of drinking
water from improved sources.</p>
      <p id="d1e110">The present study is an attempt to analyze the household preferences and the
impacts of different socioeconomic factors on drinking water sources and
adoption of HWT in Pakistan.</p>
</sec>
<sec id="Ch1.S2">
  <label>2</label><title>Methodology</title>
      <p id="d1e121">The data of Pakistan Demographic and Health Survey (PDHS) 2017–2018 were
used. In PDHS 2017–2018, 15 068 households were selected. The data on the
source of household drinking water as well as the treatment measures adopted
by households to clean the water were used.</p>
      <p id="d1e124">To examine the role of different socioeconomic factors in determining the
water source, the multinomial logit (MNL) model was used. That was because
the dependent variable is multi-categories. By using MNL, we examined the
preference for different drinking water sources by using
bottled/filtered water as the base category. Similarly, logit model was
applied to analyze whether a household applies any measure to clean the
water at home or not. In this regard, a binary variable was created that
takes the value of 1 if the household adopts any water treatment method and
0 for not adopting any HWT. Both models were estimated by using
STATA 13.0. A brief description of the variables that are used in the
analysis is summarized below.</p>
<sec id="Ch1.S2.SS1">
  <label>2.1</label><title>Dependent variables</title>
<sec id="Ch1.S2.SS1.SSS1">
  <label>2.1.1</label><title>Source of drinking water</title>
      <p id="d1e141">In the survey, there are 17 different water sources. However, depending upon
the nature of these sources we had grouped them into six different water
sources. These are (1) bottled/filtered water, (2) piped water, (3) protected
well, (4) unprotected well, (5) surface water and (6) bought water from commercial entities.</p>
</sec>
<sec id="Ch1.S2.SS1.SSS2">
  <label>2.1.2</label><title>Adoption of any purifying method to clean the water</title>
      <p id="d1e152">We had created a binary variable to represent purifying methods used by the
households. It takes the value of 1 if the household adopts any type of
purifying method at home and 0 if the household does not adopt any purifying
method.</p>
</sec>
</sec>
<sec id="Ch1.S2.SS2">
  <label>2.2</label><title>Independent variables</title>
<sec id="Ch1.S2.SS2.SSS1">
  <label>2.2.1</label><title>Age of household head</title>
      <p id="d1e171">It is hypothesized that households with older heads are less likely
to use safe drinking water and adopt modern purifying methods. The following age categories were used: 15–25, 25–39, 40–59 and 60 or more years of age.</p>
</sec>
<sec id="Ch1.S2.SS2.SSS2">
  <label>2.2.2</label><title>Level of education of household head</title>
      <p id="d1e182">In the dataset, education is divided into four categories: none,
primary, secondary and higher education. We hypothesize that education will
positively affect the choice of safe drinking water sources and the use of
purifying methods.</p>
</sec>
<sec id="Ch1.S2.SS2.SSS3">
  <label>2.2.3</label><title>Household size</title>
      <p id="d1e193">It is hypothesized that household size will reduce the chances of using
bottled/filtered water as well as of adopting HWT. This variable is categorized
as the family size of 1–5, 6–10, 11–15 and 16 or more members.</p>
</sec>
<sec id="Ch1.S2.SS2.SSS4">
  <label>2.2.4</label><title>Wealth of household</title>
      <p id="d1e204">The wealth index was used to describe the wealth of the household. The
wealth index is calculated in PDHS by using the principal component analysis
of around 40 different asset variables including the housing facilities,
assets and other material. The wealth index can take values from 1 to 5, where
1 indicates the poorest and 5 the richest household. It is hypothesized
that wealth will increase the chances of using bottled/filtered water and
of adopting HWT.</p><?xmltex \hack{\newpage}?>
</sec>
<?pagebreak page45?><sec id="Ch1.S2.SS2.SSS5">
  <label>2.2.5</label><title>Exposure to media</title>
      <p id="d1e217">We constructed a binary variable named exposure of media (reading the newspaper,
watching TV or listening to the radio). It takes the value of 1 if a
household either reads the newspaper, watches TV or listens to the radio,
indicating that the household has exposure to media. This study hypothesizes that
media exposure will increase the likelihood of using bottled/filtered water
and of adopting HWT.</p>
</sec>
<sec id="Ch1.S2.SS2.SSS6">
  <label>2.2.6</label><title>Women's empowerment</title>
      <p id="d1e228">There are several aspects of women's empowerment. These include control over
resources, involvement in household decision-making, and economic
contribution in the household, freedom of movement, sense of self-worth,
appreciation in the household, time use, knowledge, division in household
work etc. (Akram, 2018). Keeping in mind the nature of the present study, we
used only female autonomy in household purchases as an indicator of
empowerment. In the dataset, the question has five responses: (1) respondent
alone, (2) respondent and husband/partner, (3) husband/partner alone, (4) family
elders and (5) others. To make binary variables in the study, the first two
responses are assigned the value of 1, describing that a woman has autonomy, and
0 for the rest of the three options, indicating that she had no autonomy. It is
hypothesized that women's empowerment will increase the likelihood of using
bottled/filtered water and of adopting HWT.</p>
</sec>
<sec id="Ch1.S2.SS2.SSS7">
  <label>2.2.7</label><title>Distance to the water source</title>
      <p id="d1e239">To measure the relative distance to the water source, we utilized the
information of walking distance (round trip) to get to the water source. The
variable has three options: (1) water is available at home, (2) it takes
up to 15 min to reach water source, and (3) it takes more than 15 min to
reach a water source. We hypothesize that more distance to water will reduce
the chances of using bottled/filtered water and of adopting HWT.</p>
</sec>
<sec id="Ch1.S2.SS2.SSS8">
  <label>2.2.8</label><title>Location</title>
      <p id="d1e250">Rural and urban areas are two bifurcations of the location. In this regard,
a binary variable has been constructed assigning a value of 1 for rural
households and 0 for urban households. It is hypothesized that households
in urban areas are more likely to use bottled/filtered water and
to adopt HWT.</p>
</sec>
</sec>
</sec>
<sec id="Ch1.S3">
  <label>3</label><title>Results and discussions</title>
      <p id="d1e263">Descriptive statistics of variables are presented in Table 1. It shows that
48 % of the surveyed households were living in urban areas, while around
52 % of the sampled households were living in rural areas.</p>

<?xmltex \floatpos{p}?><table-wrap id="Ch1.T1"><?xmltex \currentcnt{1}?><label>Table 1</label><caption><p id="d1e269">Descriptive statistics of explanatory variables.</p></caption><oasis:table frame="topbot"><?xmltex \begin{scaleboxenv}{.97}[.97]?><oasis:tgroup cols="4">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="right"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:colspec colnum="4" colname="col4" align="right"/>
     <oasis:thead>
       <oasis:row>
         <oasis:entry colname="col1">Variable</oasis:entry>
         <oasis:entry colname="col2">Proportion</oasis:entry>
         <oasis:entry colname="col3">Mean</oasis:entry>
         <oasis:entry colname="col4">Standard</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3"/>
         <oasis:entry colname="col4">deviation</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Location</oasis:entry>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3">0.48</oasis:entry>
         <oasis:entry colname="col4">0.50</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Urban</oasis:entry>
         <oasis:entry colname="col2">48.1 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Rural</oasis:entry>
         <oasis:entry colname="col2">51.9 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Water source</oasis:entry>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3">2.81</oasis:entry>
         <oasis:entry colname="col4">0.99</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Bottled/filtered water</oasis:entry>
         <oasis:entry colname="col2">5.5 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"> Piped water</oasis:entry>
         <oasis:entry colname="col2">32.0 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"> Protected well</oasis:entry>
         <oasis:entry colname="col2">46.7 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"> Unprotected well</oasis:entry>
         <oasis:entry colname="col2">10.5 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Surface water</oasis:entry>
         <oasis:entry colname="col2">2.3 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Bought water from</oasis:entry>
         <oasis:entry colname="col2">3.0 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">commercial entities</oasis:entry>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3"/>
         <oasis:entry colname="col4"/>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Adoption of HWT</oasis:entry>
         <oasis:entry colname="col2">–</oasis:entry>
         <oasis:entry colname="col3">0.10</oasis:entry>
         <oasis:entry colname="col4">0.30</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">No</oasis:entry>
         <oasis:entry colname="col2">89.8 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Yes</oasis:entry>
         <oasis:entry colname="col2">10.2 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Distance to water source</oasis:entry>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3">0.37</oasis:entry>
         <oasis:entry colname="col4">0.70</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">At home</oasis:entry>
         <oasis:entry colname="col2">76.2 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Up to 15 min</oasis:entry>
         <oasis:entry colname="col2">10.8 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Above 15 min</oasis:entry>
         <oasis:entry colname="col2">13.0 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Age of household head</oasis:entry>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3">47.78</oasis:entry>
         <oasis:entry colname="col4">14.02</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">15–25</oasis:entry>
         <oasis:entry colname="col2">2.4 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">25–39</oasis:entry>
         <oasis:entry colname="col2">28.5 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">40–59</oasis:entry>
         <oasis:entry colname="col2">46.3 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">60<inline-formula><mml:math id="M1" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col2">22.8 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Household size</oasis:entry>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3">8.43</oasis:entry>
         <oasis:entry colname="col4">4.61</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">1–5</oasis:entry>
         <oasis:entry colname="col2">26.4 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">6–10</oasis:entry>
         <oasis:entry colname="col2">50.0 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">11–15</oasis:entry>
         <oasis:entry colname="col2">16.5 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">16<inline-formula><mml:math id="M2" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col2">7.1 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Education</oasis:entry>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3">0.99</oasis:entry>
         <oasis:entry colname="col4">1.14</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">No education</oasis:entry>
         <oasis:entry colname="col2">50.6 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Primary education</oasis:entry>
         <oasis:entry colname="col2">14.0 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Secondary education</oasis:entry>
         <oasis:entry colname="col2">20.8 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Higher education</oasis:entry>
         <oasis:entry colname="col2">14.6 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Wealth</oasis:entry>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3">2.79</oasis:entry>
         <oasis:entry colname="col4">1.43</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Poorest</oasis:entry>
         <oasis:entry colname="col2">25.3 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Poorer</oasis:entry>
         <oasis:entry colname="col2">21.4 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Middle</oasis:entry>
         <oasis:entry colname="col2">19.0 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Richer</oasis:entry>
         <oasis:entry colname="col2">17.1 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Richest</oasis:entry>
         <oasis:entry colname="col2">17.2 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Media exposure</oasis:entry>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3">0.64</oasis:entry>
         <oasis:entry colname="col4">0.48</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">No</oasis:entry>
         <oasis:entry colname="col2">35.7 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Yes</oasis:entry>
         <oasis:entry colname="col2">64.3 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Women's empowerment in</oasis:entry>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3">0.40</oasis:entry>
         <oasis:entry colname="col4">0.49</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">household purchases</oasis:entry>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3"/>
         <oasis:entry colname="col4"/>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">No</oasis:entry>
         <oasis:entry colname="col2">60.1 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Yes</oasis:entry>
         <oasis:entry colname="col2">39.9 %</oasis:entry>
         <oasis:entry colname="col3">–</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup><?xmltex \end{scaleboxenv}?></oasis:table></table-wrap>

      <?pagebreak page46?><p id="d1e1013"><?xmltex \hack{\newpage}?>The majority of the households were drinking water from protected wells
(47 %), followed by piped water (32 %), unprotected wells (11 %),
bottled/filtered water (6 %) and other sources (4 %). Similarly, 90 %
of households are not adopting any household water purifying method. The
majority of households (i.e., 76 %) have drinking water at home, 11 %
of households have to travel for less than 15 min to reach a water
source and 13 % of households are getting water from sources where they
have to travel for 15 min or more (round trip). The minimum age of
the household head emerged as 15 years, while the maximum age was 95 years, with the average age of the household head being 48 years. It is also pertinent to
mention that the majority of household heads belong to the age bracket of 40–59 years. The average family size is eight persons; however, the maximum family
size of the surveyed households was 44 persons, and the minimum family size
is only 1 family member. A total of 50 % of the households have a family size
of 6–10 persons. Table 1 also indicates that 51 % of surveyed households
were uneducated, and only 35 % of the households have a secondary
level or higher education. In terms of wealth, 47 % of the households were
poor, 19 % are among middle and 34 % were classified as rich. Table 1
also reveals that 64 % of the surveyed households have exposure to
the media. Similarly, about 40 % of the households' women have empowerment
in household purchases.</p>
      <p id="d1e1018">The study is focused on the determinants of household drinking water
sources. For estimation, the MNL model has been applied. In
the MNL model, we had used bottled/filtered water as the base category.
The results are summarized in Table 2 below.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T2" specific-use="star"><?xmltex \currentcnt{2}?><label>Table 2</label><caption><p id="d1e1024">Estimation results of multinomial logit (MNL) model of determinants
of drinking water source.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="7">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="right"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:colspec colnum="4" colname="col4" align="right"/>
     <oasis:colspec colnum="5" colname="col5" align="right"/>
     <oasis:colspec colnum="6" colname="col6" align="right"/>
     <oasis:colspec colnum="7" colname="col7" align="right"/>
     <oasis:thead>
       <oasis:row>
         <oasis:entry colname="col1">Variables</oasis:entry>
         <oasis:entry rowsep="1" namest="col2" nameend="col7" align="center">Water sources </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">Bottled/filtered</oasis:entry>
         <oasis:entry colname="col3">Piped</oasis:entry>
         <oasis:entry colname="col4">Protected</oasis:entry>
         <oasis:entry colname="col5">Unprotected</oasis:entry>
         <oasis:entry colname="col6">Surface</oasis:entry>
         <oasis:entry colname="col7">Bought water from</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">water</oasis:entry>
         <oasis:entry colname="col3">water</oasis:entry>
         <oasis:entry colname="col4">well</oasis:entry>
         <oasis:entry colname="col5">well</oasis:entry>
         <oasis:entry colname="col6">water</oasis:entry>
         <oasis:entry colname="col7">commercial entities</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">Location (living in rural areas)</oasis:entry>
         <oasis:entry colname="col2">1</oasis:entry>
         <oasis:entry colname="col3">1.0094<inline-formula><mml:math id="M5" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">1.1269<inline-formula><mml:math id="M6" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5">1.0584<inline-formula><mml:math id="M7" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">0.6082<inline-formula><mml:math id="M8" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col7">0.0134</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Age of household head</oasis:entry>
         <oasis:entry colname="col2">1</oasis:entry>
         <oasis:entry colname="col3">1.2826<inline-formula><mml:math id="M9" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">1.1197<inline-formula><mml:math id="M10" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5">1.4915<inline-formula><mml:math id="M11" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">1.0676<inline-formula><mml:math id="M12" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col7">1.1768</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Household size</oasis:entry>
         <oasis:entry colname="col2">1</oasis:entry>
         <oasis:entry colname="col3">1.5281<inline-formula><mml:math id="M13" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">1.5405<inline-formula><mml:math id="M14" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5">1.3387<inline-formula><mml:math id="M15" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">1.8129<inline-formula><mml:math id="M16" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col7">1.9999<inline-formula><mml:math id="M17" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Media exposure</oasis:entry>
         <oasis:entry colname="col2">1</oasis:entry>
         <oasis:entry colname="col3">0.9893<inline-formula><mml:math id="M18" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">1.0989</oasis:entry>
         <oasis:entry colname="col5">0.7319<inline-formula><mml:math id="M19" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">0.8713</oasis:entry>
         <oasis:entry colname="col7">0.6348<inline-formula><mml:math id="M20" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Education</oasis:entry>
         <oasis:entry colname="col2">1</oasis:entry>
         <oasis:entry colname="col3">0.8325<inline-formula><mml:math id="M21" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">0.7136<inline-formula><mml:math id="M22" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5">0.6479<inline-formula><mml:math id="M23" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">0.3625<inline-formula><mml:math id="M24" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col7">0.8397<inline-formula><mml:math id="M25" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Women's empowerment in</oasis:entry>
         <oasis:entry colname="col2">1</oasis:entry>
         <oasis:entry colname="col3">0.6489<inline-formula><mml:math id="M26" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">0.7705<inline-formula><mml:math id="M27" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5">0.6130<inline-formula><mml:math id="M28" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">0.5478<inline-formula><mml:math id="M29" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col7">0.3766<inline-formula><mml:math id="M30" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Household purchases</oasis:entry>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3"/>
         <oasis:entry colname="col4"/>
         <oasis:entry colname="col5"/>
         <oasis:entry colname="col6"/>
         <oasis:entry colname="col7"/>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Wealth</oasis:entry>
         <oasis:entry colname="col2">1</oasis:entry>
         <oasis:entry colname="col3">0.4325<inline-formula><mml:math id="M31" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">0.4625<inline-formula><mml:math id="M32" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5">0.2505<inline-formula><mml:math id="M33" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">0.3936<inline-formula><mml:math id="M34" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col7">0.2192<inline-formula><mml:math id="M35" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Constant</oasis:entry>
         <oasis:entry colname="col2">1</oasis:entry>
         <oasis:entry colname="col3">110.0963<inline-formula><mml:math id="M36" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">283.4138<inline-formula><mml:math id="M37" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5">200.7871<inline-formula><mml:math id="M38" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">10.0194<inline-formula><mml:math id="M39" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col7">112.5794<inline-formula><mml:math id="M40" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">LR chi square</oasis:entry>
         <oasis:entry namest="col2" nameend="col7" align="center">3651.62 </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"><inline-formula><mml:math id="M41" display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula> value of chi square</oasis:entry>
         <oasis:entry namest="col2" nameend="col7" align="center">0.0000 </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Pseudo <inline-formula><mml:math id="M42" display="inline"><mml:mrow><mml:msup><mml:mi>R</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry namest="col2" nameend="col7" align="center">0.1021 </oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table><table-wrap-foot><p id="d1e1027"><inline-formula><mml:math id="M3" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula> <inline-formula><mml:math id="M4" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula>.</p></table-wrap-foot></table-wrap>

      <p id="d1e1685">The results suggest that a household's location influenced the choice of
drinking water in four out of five alternatives. Zulfiqar et al. (2016) also
came to the similar conclusion that living in an urban or rural area plays a
significant role in determining a household's water source. The results
suggest that people living in rural areas were more likely to use water from
protected wells and tube wells compared to the water from other
sources (a possible reason seems to be the cost and availability of services).
Furthermore, results suggested that households in rural areas are less
likely to use drinking surface water (relative risk ratio less than 1), but
they would prefer piped water and also unprotected wells (relative risk ratio
greater than 1).</p>
      <p id="d1e1688">Similar to the findings of Abrahams et al. (2000) and Zulfiqar et al. (2016)
it has been found that the age of household head has a significant
impact on the source of drinking water in all five alternatives. The
results suggested that households with older heads are more likely to
consume water from unprotected wells. This reflects that aged people in
Pakistan are the least health-conscious, and they prefer to use traditional water sources.</p>
      <p id="d1e1691">Household size has a very strong impact, as the results are
significant in all five alternatives. The results are also
supported by the findings of Rauf et al. (2015). Households with a larger
family size prefer to use other water sources. In comparison to the
bottled/filtered water, as in all the alternatives the relative risk ratio is
significantly greater than 1. With an increase in family size, water
consumption increased, so families prefer to use water from those sources
where they can get more water easily.</p>
      <p id="d1e1695">It has been confirmed that households having access to media and education
are more likely to use water from protected wells or bottled/filtered water.
This may be because people have information about the health hazards of unsafe
water. Therefore they would prefer to use safe drinking water sources.
Abrahams et al. (2000), Haq et al. (2007) and Zulfiqar et al. (2016) also
came to a similar conclusion that education and awareness about the
hazards of drinking unsafe water plays a crucial role in determining the
improved drinking water source.</p>
      <p id="d1e1698">In line with the findings of Abrahams et al. (2000) it has been found that
wealthier households prefer to use bottled/filtered water in comparison to
other water sources. The reason may be that wealthier households can afford
better sources of drinking water. Furthermore, rich people are more
health-conscious and willing to spend more money on an improved water
source.</p>
      <p id="d1e1701">It has also been found that households with greater women autonomy in making
household purchases prefer to use bottled/filtered water in comparison to
other water sources. This suggests that women are more health-conscious, and if
they are involved in household spending decision-making, then there is a higher
chance that they would make appropriate adjustments in the expenditures to
allocate more money for using an improved water source.</p>
      <p id="d1e1704">In the next step, the household's adoption of HWT was analyzed. This model
is tested by using the logit model. The results are summarized in Table 3.</p>

<?xmltex \floatpos{p}?><table-wrap id="Ch1.T3"><?xmltex \currentcnt{3}?><label>Table 3</label><caption><p id="d1e1710">Estimation results of logit model of the in-house water treatment to
treat water.</p></caption><oasis:table frame="topbot"><?xmltex \begin{scaleboxenv}{.96}[.96]?><oasis:tgroup cols="3">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="right"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:thead>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Variables</oasis:entry>
         <oasis:entry colname="col2">Odd ratios</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M45" display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula> values</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row rowsep="1">
         <oasis:entry namest="col1" nameend="col3">Location </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Urban</oasis:entry>
         <oasis:entry colname="col2">1</oasis:entry>
         <oasis:entry colname="col3"/>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Rural</oasis:entry>
         <oasis:entry colname="col2">0.8901</oasis:entry>
         <oasis:entry colname="col3">0.0469<inline-formula><mml:math id="M46" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry namest="col1" nameend="col3">Age of household head </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">15–25</oasis:entry>
         <oasis:entry colname="col2">1</oasis:entry>
         <oasis:entry colname="col3"/>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">25–39</oasis:entry>
         <oasis:entry colname="col2">0.8677</oasis:entry>
         <oasis:entry colname="col3">0.459</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">40–59</oasis:entry>
         <oasis:entry colname="col2">0.8805</oasis:entry>
         <oasis:entry colname="col3">0.505</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">60<inline-formula><mml:math id="M47" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col2">0.8846</oasis:entry>
         <oasis:entry colname="col3">0.536</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry namest="col1" nameend="col3">Household size </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">1–5</oasis:entry>
         <oasis:entry colname="col2">1</oasis:entry>
         <oasis:entry colname="col3"/>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">6–10</oasis:entry>
         <oasis:entry colname="col2">0.9519<inline-formula><mml:math id="M48" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">0.047</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">11–15</oasis:entry>
         <oasis:entry colname="col2">0.8922<inline-formula><mml:math id="M49" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">0.008</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">16<inline-formula><mml:math id="M50" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col2">0.8672<inline-formula><mml:math id="M51" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">0.000</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry namest="col1" nameend="col3">Education </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">No education</oasis:entry>
         <oasis:entry colname="col2">1</oasis:entry>
         <oasis:entry colname="col3"/>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Primary education</oasis:entry>
         <oasis:entry colname="col2">1.0702</oasis:entry>
         <oasis:entry colname="col3">0.447</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Secondary education</oasis:entry>
         <oasis:entry colname="col2">1.1308<inline-formula><mml:math id="M52" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">0.041</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Higher education</oasis:entry>
         <oasis:entry colname="col2">1.8081<inline-formula><mml:math id="M53" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">0.000</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry namest="col1" nameend="col3">Wealth </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Poorest</oasis:entry>
         <oasis:entry colname="col2">1</oasis:entry>
         <oasis:entry colname="col3"/>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Poorer</oasis:entry>
         <oasis:entry colname="col2">0.9991</oasis:entry>
         <oasis:entry colname="col3">0.992</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Middle</oasis:entry>
         <oasis:entry colname="col2">0.9005</oasis:entry>
         <oasis:entry colname="col3">0.266</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Richer</oasis:entry>
         <oasis:entry colname="col2">1.0675<inline-formula><mml:math id="M54" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">0.063</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Richest</oasis:entry>
         <oasis:entry colname="col2">1.0844<inline-formula><mml:math id="M55" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">0.032</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry namest="col1" nameend="col3">Media exposure </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">No</oasis:entry>
         <oasis:entry colname="col2">1</oasis:entry>
         <oasis:entry colname="col3"/>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Yes</oasis:entry>
         <oasis:entry colname="col2">1.1904<inline-formula><mml:math id="M56" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">0.017</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry namest="col1" nameend="col3">Distance to water source </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">At home</oasis:entry>
         <oasis:entry colname="col2">1</oasis:entry>
         <oasis:entry colname="col3"/>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Up to 15 min</oasis:entry>
         <oasis:entry colname="col2">1.1270</oasis:entry>
         <oasis:entry colname="col3">0.253</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Above 15 min</oasis:entry>
         <oasis:entry colname="col2">0.9610</oasis:entry>
         <oasis:entry colname="col3">0.722</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry namest="col1" nameend="col3">Women's empowerment in household purchases </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">No</oasis:entry>
         <oasis:entry colname="col2">1</oasis:entry>
         <oasis:entry colname="col3"/>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Yes</oasis:entry>
         <oasis:entry colname="col2">1.2291<inline-formula><mml:math id="M57" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">0.001</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry namest="col1" nameend="col3">Water source </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Bottled water</oasis:entry>
         <oasis:entry colname="col2">1</oasis:entry>
         <oasis:entry colname="col3"/>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Piped water</oasis:entry>
         <oasis:entry colname="col2">1.0991<inline-formula><mml:math id="M58" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">0.000</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Well</oasis:entry>
         <oasis:entry colname="col2">0.5752<inline-formula><mml:math id="M59" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">0.000</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Unprotected well</oasis:entry>
         <oasis:entry colname="col2">0.9641<inline-formula><mml:math id="M60" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">0.000</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Surface water</oasis:entry>
         <oasis:entry colname="col2">0.9984</oasis:entry>
         <oasis:entry colname="col3">0.994</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Bought water from</oasis:entry>
         <oasis:entry colname="col2">0.5640<inline-formula><mml:math id="M61" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">0.017</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">commercial entities</oasis:entry>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3"/>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Constant</oasis:entry>
         <oasis:entry colname="col2">0.1608</oasis:entry>
         <oasis:entry colname="col3">0.000</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">LR <inline-formula><mml:math id="M62" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="italic">χ</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula> (36)</oasis:entry>
         <oasis:entry namest="col2" nameend="col3" align="center">118.72 </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"><inline-formula><mml:math id="M63" display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula> value of <inline-formula><mml:math id="M64" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="italic">χ</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry namest="col2" nameend="col3" align="center">0.000 </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Pseudo <inline-formula><mml:math id="M65" display="inline"><mml:mrow><mml:msup><mml:mi>R</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry namest="col2" nameend="col3" align="center">0.1360 </oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup><?xmltex \end{scaleboxenv}?></oasis:table><table-wrap-foot><p id="d1e1713"><?xmltex \hack{\hspace{0.2cm}}?><inline-formula><mml:math id="M43" display="inline"><mml:msup><mml:mi/><mml:mo>∗</mml:mo></mml:msup></mml:math></inline-formula> <inline-formula><mml:math id="M44" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula>.</p></table-wrap-foot></table-wrap>

      <p id="d1e2419">The results from Table 3 indicate that locality of the household plays a
significant role in adoption of in-house water purifying treatment, and
people who live in urban areas are more likely to adopt HWT (odd ratio for
rural households is significantly below 1). These findings have also been
supported by Bruce and Gnedenko (1998), who found that urban households are more
likely to adopt HWT.</p>
      <p id="d1e2422">Similar to the findings of Sattar and Ahmad (2007), it has also been found
that family size hurts the adoption of water purifying methods as odd
ratios are less than 1. Due to the large family size, more water is required
so it is very difficult for large families to adopt HWT. Rather, they
prefer to use water without any treatment. This reveals the fact that, due to
larger family size, quality and quantity of essential services are
negatively affected.</p>
      <p id="d1e2425">Both education and exposure to the media (the indicators of the level
of awareness) tend to increase the likelihood of adopting HWT. However,
only secondary education and higher education result in increasing the chances of
adopting HWT. These findings are supported by various past<?pagebreak page47?> studies,
including Dasgupta (2001), McConnell and Rosado (2000), Quick et al. (1999) and Jalan et al. (2009).</p>
      <p id="d1e2428">In line with the findings of Bruce and Gnedenko (1998) and Totouomet et
al. (2012), it has been found that wealth of households has a significant
impact on the adoption of water purifying methods. There are
significantly higher odds of a wealthier household to adopt HWT in
comparison to a poor or middle-income household.</p>
      <p id="d1e2431">Women's empowerment also had a significant impact on adoption of HWT.
Households wherein women are empowered in making household purchases are
more likely to use water-purifying methods. These results are supported by
Jyotsna et al. (2003).</p>
      <p id="d1e2434">The drinking water source is also emerged as an important and significant
factor in the adoption of HWT. The results indicate that people might not
trust the water quality coming from the piped water (this has been supported
by Daniel et al., 2018). Therefore, they are more likely to adopt HWT.
Daniel et al. (2019) also came to the similar conclusion that households
using piped water are more likely to adopt HWT. However, households using
water from protected well, unprotected wells and water bought from
commercial sources are significantly less likely to adopt HWT.</p>
      <p id="d1e2438">The present study is unable to find significant impact of age of household head
and distance to water sources on the adoption of HWT in Pakistan. However
past studies have found that the age of the household head (Mintz et al., 2001) plays a significant role in the adoption of HWT.</p>
</sec>
<sec id="Ch1.S4" sec-type="conclusions">
  <label>4</label><title>Conclusions and policy recommendations</title>
      <p id="d1e2449">In developing countries, poor quality of drinking water has been recognized
as a major health issue because many fatal diseases, especially diarrhea and
hepatitis, are linked to the quality of water. The present study was conducted to analyze the role of different socioeconomic characteristics of
households in using different water sources and adoption of HWT. The results
of the study provide insight for policymakers to tackle obstacles in the
consumption of safe drinking water in Pakistan, and it will help them to
develop and adopt better policies that would increase the availability/usage of
better quality drinking water in Pakistan.</p>
      <p id="d1e2452">It has been found that locality of household, family size, age of household
head, wealth of household, level of awareness (education and exposure to
media), and women's empowerment are significant factors in determining the
household consumption of drinking water sources. People living in rural
areas, headed by aged family members, and having large family sizes are significantly less
likely to use improved drinking water sources. However, households with
media exposure, education, women's empowerment in household purchases and
belonging to the rich segment of society are more likely to use a safe
drinking water source.</p>
      <p id="d1e2455">Similarly, locality of household, family size, education, exposure to the
media, women's empowerment, source of drinking water and wealth of household
are significant factors in determining the adoption of HWT. This reveals that
households in urban areas, those with a higher level of awareness
(through education and media), belonging to wealthy families, wherein women
enjoy a higher level of empowerment and households using piped water are
more likely to adopt HWT. However, households using water from protected
well, unprotected wells, water bought from commercial sources and having
higher family size are less likely to adopt water purifying methods at home.
However, the age of household head and distance to water sources do not<?pagebreak page48?> have
a significant impact on the adoption of the water purifying method.</p>
      <p id="d1e2458">On the basis of the findings of the present study, the following is recommended:
<list list-type="custom"><list-item><label>i.</label>
      <p id="d1e2463">Better drinking water facilities must be provided in rural areas so that
differences in urban and rural areas in terms of safe drinking water may be
eliminated.</p></list-item><list-item><label>ii.</label>
      <p id="d1e2467">The study reveals that most Pakistani households get drinking water from
wells. However excessive use of wells and tube wells has resulted in significant
reduction in groundwater levels. There is a need for the
government to launch awareness campaigns in order to promote usage of drinking water
from filters and piped water.</p></list-item><list-item><label>iii.</label>
      <p id="d1e2471">Similarly, households consider the water obtained from wells as safe and do
not adopt HWT. There is a dire need for a comprehensive study to be
conducted in order to analyze the levels of pollution in the drinking water obtained
from wells.</p></list-item><list-item><label>iv.</label>
      <p id="d1e2475">As mentioned earlier, larger families do not adopt HWT, and they try to use
those water sources where they can get a large quantity of water without any
cost. Consequently, as a result, larger families obtain essential services at
compromised quality. Policy makers must take appropriate measures to
control population growth in Pakistan.</p></list-item><list-item><label>v.</label>
      <p id="d1e2479">It is also recommended that policy makers in Pakistan take appropriate
actions to empower women. Women's empowerment will not only uplift the
conditions of women in Pakistan, but it will also have positive impacts on
other social conventions including consumption of safe drinking water.</p></list-item><list-item><label>vi.</label>
      <p id="d1e2483">The study also found that awareness created by media and education play
a significant role in determining the consumption of safe drinking water in
Pakistan. Therefore, it is suggested that the government, along with different
NGOs working in the social sector, launch awareness campaigns regarding
the hazards of consuming unsafe water and adoption of HWT. In this regard it is
also recommended that issues associated with safe drinking water be
included in the curriculum of public as well as private schools.</p></list-item></list></p>
</sec>

      
      </body>
    <back><notes notes-type="dataavailability"><title>Data availability</title>

      <p id="d1e2491">Data from the Pakistan Demographic and Health
Survey 2017–2018 are available online. They can be accessed at
<uri>https://www.nips.org.pk/study_detail.php?detail=MTgw</uri> (PDHS, 2018).</p>
  </notes><notes notes-type="competinginterests"><title>Competing interests</title>

      <p id="d1e2500">The author declares that there is no conflict of interest.</p>
  </notes><ack><title>Acknowledgements</title><p id="d1e2506">The author is extremely thankful to the referees and editors of this paper. Their valuable comments improved the paper to a great extent.</p></ack><notes notes-type="reviewstatement"><title>Review statement</title>

      <p id="d1e2511">This paper was edited by Luuk Rietveld and reviewed by two anonymous referees.</p>
  </notes><ref-list>
    <title>References</title>

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    <!--<article-title-html>Consumption of safe drinking water in Pakistan: its dimensions and determinants</article-title-html>
<abstract-html><p>Safe drinking water is one of the basic human needs. Poor quality of
drinking water is directly associated with various waterborne diseases. The
present study has attempted to analyze the household preferences for
drinking water sources and the adoption of household water treatment (HWT)
in Pakistan by using the household data of Pakistan Demographic and Health
Survey 2017–2018 (PDHS, 2018). This study found that people living in rural areas, those with older heads of household and those with large family sizes are significantly less likely
to use water from bottled or filtered water. Households with media
exposure, education, women's empowerment in household purchases and high incomes are more likely to use bottled or filtered
water. Similarly, households are more likely to adopt HWT in urban areas, when there is a higher level of awareness (through education and media), higher incomes, women enjoy a higher level of empowerment, and piped water is already used. However, households that use water from wells and have higher family sizes are less likely to adopt water purifying methods at home.</p></abstract-html>
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