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<article xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" article-type="research-article" xml:lang="en">
<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">JAMBA</journal-id>
<journal-title-group>
<journal-title>J&#x00E0;mb&#x00E1; - Journal of Disaster Risk Studies</journal-title>
</journal-title-group>
<issn pub-type="ppub">2072-845X</issn>
<issn pub-type="epub">1996-1421</issn>
<publisher>
<publisher-name>AOSIS</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">JAMBA-16-1645</article-id>
<article-id pub-id-type="doi">10.4102/jamba.v16i1.1645</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Original Research</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Role of <italic>Kader Siaga Bencana</italic> in the flood management of selected <italic>Kampung Siaga Bencana</italic></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-2763-0219</contrib-id>
<name>
<surname>Fatmah</surname>
<given-names>Fatmah</given-names>
</name>
<xref ref-type="aff" rid="AF0001">1</xref>
</contrib>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">https://orcid.org/0009-0004-9744-6830</contrib-id>
<name>
<surname>Purwana</surname>
<given-names>Rachmadhi</given-names>
</name>
<xref ref-type="aff" rid="AF0001">1</xref>
</contrib>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-9831-5729</contrib-id>
<name>
<surname>Bisri</surname>
<given-names>Mizan F.</given-names>
</name>
<xref ref-type="aff" rid="AF0002">2</xref>
</contrib>
<aff id="AF0001"><label>1</label>Disaster Management Program, School of Environmental Science, University of Indonesia, Jakarta, Indonesia</aff>
<aff id="AF0002"><label>2</label>Graduate School of International Cooperation Studies, Kobe University, Kobe, Japan</aff>
</contrib-group>
<author-notes>
<corresp id="cor1"><bold>Corresponding author:</bold> Fatmah Fatmah, <email xlink:href="ffatmah@ui.ac.id">ffatmah@ui.ac.id</email></corresp>
</author-notes>
<pub-date pub-type="epub"><day>31</day><month>07</month><year>2024</year></pub-date>
<pub-date pub-type="collection"><year>2024</year></pub-date>
<volume>16</volume>
<issue>1</issue>
<elocation-id>1645</elocation-id>
<history>
<date date-type="received"><day>01</day><month>12</month><year>2023</year></date>
<date date-type="accepted"><day>24</day><month>06</month><year>2024</year></date>
</history>
<permissions>
<copyright-statement>&#x00A9; 2024. The Authors</copyright-statement>
<copyright-year>2024</copyright-year>
<license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/">
<license-p>Licensee: AOSIS. This work is licensed under the Creative Commons Attribution License.</license-p>
</license>
</permissions>
<abstract>
<p>Health cadres and community leaders&#x2019; empowerment to become flood disaster preparedness cadres (<italic>Kader Siaga Bencana,</italic> KSB) still needs to be improved. The study aimed to assess flood management practices among families with disaster-vulnerable groups, as well as KSB candidates (<italic>posyandu</italic>/health cadres, community leaders) in flood management initiatives in flood-prone areas. The study used a cross-sectional design of 100 families with flood-prone groups and 100 health cadres and community leaders. They were selected using simple random sampling in five selected villages of Jakarta city affected by floods and Disaster Alert Villages (<italic>Kasmpung Siaga Bencana,</italic> DAV). Most family respondents had a low knowledge level of DAV, and inadequate knowledge of flood warning system, emergency response plan, and flood management practices, despite having good family support. Health cadres and community leaders as KSB candidates were assessed using four parameters of knowledge on KSB &#x2013; flood early warning system, emergency response plan, natural hazards and flood knowledge, and flood management practice. With their sound understanding of natural hazards and floods, health cadres and community leaders were 4.52 times more likely to have good flood management practices compared to those with inadequate knowledge. Both elements of the community have the potential to be KSB because of good disaster knowledge and the presence of the flood early warning system in the community. Intervention studies to increase the knowledge and practical ability of KSB in disaster management are also needed.</p>
<sec id="st1">
<title>Contribution</title>
<p>The research assessed the initial readiness of health cadres and community leaders to become disaster preparedness cadres in flood management. It is necessary to provide training to develop their expertise as KSB.</p>
</sec>
</abstract>
<kwd-group>
<kwd>flood management</kwd>
<kwd><italic>posyandu cadres</italic></kwd>
<kwd>disaster preparedness cadres</kwd>
<kwd>disaster alert villages</kwd>
<kwd>knowledge</kwd>
<kwd>practice</kwd>
</kwd-group>
<funding-group>
<funding-statement><bold>Funding information</bold> The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Universitas Indonesia through the PUTI Q2 Scopus Grant Year 2023. The grant number is NKB-841/UN2.RST/HKP.05.00/2023.</funding-statement>
</funding-group>
</article-meta>
</front>
<body>
<sec id="s0001">
<title>Introduction</title>
<p>Flooding is one of the most common natural hazards, with particularly destructive effects in low-income countries. More than 90&#x0025; of the developing countries addressed frequent floods in their reports. In 2011, severe floods were reported in Mozambique, Namibia, South Africa, and Uganda in Africa; Brazil, Colombia, and Mexico in South America, and Cambodia, China, India, Korea, Pakistan, the Philippines, and Thailand in Asia. There were over 1000 people killed in the</p>
<p>Philippines and Colombia caused by causing significant material damage, particularly in the above-mentioned developed countries (Kundzewicz et al. <xref ref-type="bibr" rid="CIT0019">2005</xref>).</p>
<p>The occurrence of flood disasters are common in Indonesia because it has a tropical climate with two seasons: the dry season and the rainy season, characterized by extreme weather changes, temperature, and wind direction (Chan et al. <xref ref-type="bibr" rid="CIT0006">2016</xref>). These extreme changes affect humans negatively through the occurrence of hydrometeorological disasters such as floods, landslides, forest fires, and droughts. From January to October 2023, there have been 3056 disasters, with floods (893 cases) and extreme weather (861 cases) being the most common (Annur <xref ref-type="bibr" rid="CIT0002">2023</xref>). Because of its location on the northwest coast of Java Island, as well as the fact that DKI Jakarta Province, which is also the capital of Indonesia, is home to the mouth of the Ciliwung River in Jakarta Bay, the province becomes a disaster-critical or disaster-prone area, particularly on account of floods. The average elevation of the area in Jakarta is 8 m above sea level. Climate change and Jakarta&#x2019;s rapidly developing urban areas have contributed significantly to the frequency of floods in this province. Almost 17&#x0025; of the total land area of Jakarta is predicted to be submerged by 2030, and most of the areas of Jakarta are under the threat of sinking by 2050 (Kulp &#x0026; Benjamin <xref ref-type="bibr" rid="CIT0018">2019</xref>).</p>
<p>Natural hazards caused by climate change affect older people to a greater extent. It&#x2019;s essential to understand how aware and prepared they are to deal with disasters. Several studies have indicated that older people may be less aware of and less prepared for disasters than the general population. However, it has been found that Canadian older people&#x2019;s perceptions of risk are often associated with specific risks related to their geographic location (Bogdan et al. <xref ref-type="bibr" rid="CIT0005">2024</xref>). A significant proportion of older individuals residing in flood-prone areas of Bangkok have never participated in community-based flood preparedness and management training programs (Sawangnate, Benjawan &#x0026; Suthirat 2023). Hence, it is imperative to increase awareness of flood preparedness among older people, one of the vulnerable groups inordinately affected by natural hazards.</p>
<p>One of the promotive and preventive actions that can be carried out comprehensively and collaboratively across sectors to minimize the impact of flooding on older people is to have Disaster Preparedness Cadres (<italic>Kader Siaga Bencana,</italic> KSB). These cadres are the community groups that improve the community&#x2019;s disaster preparedness, prevention, and mitigation, and play an important role in quick responses to health issues. Although these cadres have not been officially included in Indonesia&#x2019;s disaster emergency management plans, there is evidence that they are indeed involved in disaster responses in Indonesia, illustrating their crucial role in disaster management in society. Therefore, it is essential to improve disaster information literacy and skills related to disaster preparedness and flood management among cadres for flood-prone groups in urban areas. This includes pre-disaster mitigation and preparedness, emergency response during floods, and post-disaster recovery. Cadres are selected as the community group studied in this study because they are at the forefront of disaster management and can transfer disaster management knowledge to disaster-prone communities (Gustina <xref ref-type="bibr" rid="CIT0012">2020</xref>).</p>
<p>Cadre empowerment is one of the principles of disaster management under the Community-Based Disaster Management (CBDM) approach. This approach encourages grassroots communities to manage local disaster risks, helping the community to organize themselves to be self-sufficient in dealing with disasters before, during, and after disasters. The CBDM includes community activities such as disaster simulation, training, community-based disaster risk reduction education, and training on Basic Living Assistance (BHD) as the first steps of emergency relief (Herianto, Nulhaqim &#x0026; Rachim <xref ref-type="bibr" rid="CIT0013">2015</xref>). Several studies in Indonesia have elaborated the role of cadres in disaster emergency responses to minimize the impact of the disaster on the victims, facilitate coordination, make reporting and coordination easier at the village and sub-district levels, and cadres&#x2019; quick responses in the event of a disaster (Maharani <xref ref-type="bibr" rid="CIT0021">2021</xref>; Puspitasari, Depi &#x0026; Rismayanti <xref ref-type="bibr" rid="CIT0027">2021</xref>; Tiffany &#x0026; Clarita <xref ref-type="bibr" rid="CIT0033">2021</xref>; Ulfa &#x0026; Azizah <xref ref-type="bibr" rid="CIT0034">2021</xref>; Zuliani &#x0026; Suhendi <xref ref-type="bibr" rid="CIT0038">2021</xref>). <italic>Kader Siaga Bencana</italic> is a Safe Community organization that supports the achievement of safe and healthy conditions in the community through the active roles played by community groups, including the private sector and professionals, which work in synergy with the government in emergency responses and disaster management. The essence of <italic>Safe Community</italic> is efforts by the community, from the community, and for the community, under the government&#x2019;s support as a facilitator towards creating healthy and safe conditions (Zuliani &#x0026; Suhendi <xref ref-type="bibr" rid="CIT0038">2021</xref>). Studies on KSB&#x2019;s role in disaster prevention in DKI Jakarta Province have never been conducted despite their significant role they play in reducing flood risk, especially for flood-vulnerable groups. Thus, a study that assesses the knowledge and practice of families with group(s) vulnerable to disasters and cadres of integrated health posts [<italic>Pos Pelayanan Terpadu, posyandu</italic>] in urban areas of DKI Jakarta regarding disaster management is essential before preparing for the establishment of KSB in the future. This study aimed to assess the knowledge and practice of flood management among families with groups vulnerable to flood, health cadres, religious leaders, and community leaders in the selected flood-prone areas of Jakarta city.</p>
</sec>
<sec id="s0002">
<title>Research methods and design</title>
<sec id="s20003">
<title>Study design</title>
<p>This cross-sectional study was conducted among 200 respondents living in the five selected villages of Rawa Buaya (West Jakarta), South Pengadegan (South Jakarta), Cawang (East Jakarta), Karet Tengsin (Central Jakarta), and Pejagalan (North Jakarta) in August 2023. These five villages were selected because they were among the 25 flood-prone villages in the province in 2023 (Azzahra <xref ref-type="bibr" rid="CIT0004">2023</xref>).</p>
</sec>
<sec id="s20004">
<title>Population and sample</title>
<p>The study population comprised the entire population of Rawa Buaya (West Jakarta), South Pengadegan (South Jakarta), Cawang (East Jakarta), Karet Tengsin (Central Jakarta), and Pejagalan (North Jakarta) villages, with a high Flood Risk Index of 21.03 in 2023 (National Board for Disaster Management [BNPB] <xref ref-type="bibr" rid="CIT0022">2021</xref>). The inclusion criteria for this study were people who had experienced flooding both inside and outside the home for at least the last 3 years and who had at least one family group that was categorized as one of the vulnerable groups (infant, toddler, child, pregnant woman, nursing mother, older people, and person with disability), a cadre of <italic>posyandu</italic> for under-five children, a cadre of <italic>posbindu</italic> for older people, and a local community/religious leader. The sampling technique was performed using the simple random sampling from the neighbourhoods (Rukun Warga, RW) affected by floods, at least in 2020. A total of 100 respondents from families with groups vulnerable to flood and 100 respondents from cadres from <italic>posyandu</italic> for under-five children, cadres for <italic>posbindu</italic> for older people, and local community/religious leaders participated in this study. The sample size was estimated using Slovin&#x2019;s formula to get a representative sample of respondents (Jerri &#x0026; Joyce <xref ref-type="bibr" rid="CIT0015">2012</xref>). Slovin&#x2019;s formula estimated the sample size to be 100 individuals for each type of respondent: families with flood-prone groups and health cadres and community leaders.
<disp-formula id="FD1"><alternatives><mml:math display="block" id="M1"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mfrac><mml:mi>N</mml:mi><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:mtext>N</mml:mtext><mml:msup><mml:mrow><mml:mtext>.e</mml:mtext></mml:mrow><mml:mn>2</mml:mn></mml:msup></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mfrac></mml:mrow></mml:math><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="JAMBA-16-1645-e001.tif"/></alternatives></disp-formula></p>
<p>The sample size, <italic>N</italic> is the total population affected by the flood at five selected villages (250 336 people) and e refers to the error margin at 10&#x0025;.</p>
</sec>
<sec id="s20005">
<title>Study location</title>
<p>The study was conducted in the five flood-prone villages in DKI Jakarta Province: Rawa Buaya (West Jakarta), South Pengadegan (South Jakarta), Kampung Melayu (East Jakarta), Pejagalan (North Jakarta), and Karet Tengsin (Central Jakarta). These villages had been established as Disaster Alert Villages (Kampung Siaga Bencana, KSB). Kampung Melayu Village is one of the villages on the banks of the Ciliwung River. It has been partially evicted and relocated to West Jatinegara because of the normalization of the Ciliwung River (<xref ref-type="fig" rid="F0001">Figure 1</xref>). Nearly 920 households in Kampung Melayu have been evicted because of this program (Karima, Purwantiasning &#x0026; Prayodi <xref ref-type="bibr" rid="CIT0016">2018</xref>).</p>
<fig id="F0001">
<label>FIGURE 1</label>
<caption><p>Flood hazard map of Kampung Melayu Urban Village.</p></caption>
<graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="JAMBA-16-1645-g001.tif"/>
</fig>
<p>Karet Tengsin Village is situated on a relatively flat terrain and is flanked by two rivers: the West Flood Canal and the Krukut River. These two rivers make the village susceptible to flooding, particularly during severe floods every 5 years. The densely populated settlement in this area is located along the Krukut Riverbank: a low plateau that can potentially be affected by flooding when there is an overflow of river water (<xref ref-type="fig" rid="F0002">Figure 2</xref>). Rawa Buaya Village is located in an area surrounded by three streams: Mookevart River, Anak Kali Angke, and Sanggrahan River (<xref ref-type="fig" rid="F0003">Figure 3</xref>). The region is dominated by housing and industrial estates, which has reduced the catchment area. The causes of flooding in this area include poorly organized water and drainage systems, cut drainage channels, narrowing and silting of river bodies, and damage to water pumps. Additionally, reservoirs do not function properly because of silt and garbage deposits (Putro <xref ref-type="bibr" rid="CIT0028">2010</xref>). Pengadegan Village is located on the bank of the Ciliwung River, which makes it vulnerable to flooding. Lubang Kampong, situated in a lowland area below the river surface, is also at risk. The flooding affects around 3 hectares of RW 01 and RW 02 (<xref ref-type="fig" rid="F0004">Figure 4</xref>). Pejagalan Village is another flood-prone area because of its proximity to the Angke River (<xref ref-type="fig" rid="F0005">Figure 5</xref>).</p>
<fig id="F0002">
<label>FIGURE 2</label>
<caption><p>Flood hazard map of Karet Tengsin Urban Village.</p></caption>
<graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="JAMBA-16-1645-g002.tif"/>
</fig>
<fig id="F0003">
<label>FIGURE 3</label>
<caption><p>Flood hazard map of Rawa Buaya Urban Village.</p></caption>
<graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="JAMBA-16-1645-g003.tif"/>
</fig>
<fig id="F0004">
<label>FIGURE 4</label>
<caption><p>Flood hazard map of South Pengadegan Urban Village.</p></caption>
<graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="JAMBA-16-1645-g004.tif"/>
</fig>
<fig id="F0005">
<label>FIGURE 5</label>
<caption><p>Flood hazard map of Pejagalan Urban Village.</p></caption>
<graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="JAMBA-16-1645-g005.tif"/>
</fig>
</sec>
<sec id="s20006">
<title>Study framework</title>
<p>This study applied the flood disaster management framework through an assessment of socio-demographic characteristics (marital status, age, final education, employment, number of people living in the house, number of biological children, total income, and size or number of family groups); knowledge of the Disaster Preparedness Village (definition, tasks); knowledge of natural hazards and floods (definitions, types of natural hazards, causes, impacts, groups prone to natural hazards, need for disaster-prone groups to prepare for floods); family practices in flood management (before, during, and after disaster); disaster warning systems (sources of information, efforts made when hearing information about floods); support for families with groups vulnerable to flood (forms of support and assistance provided); and emergency response plan parameters (division of tasks in self-rescue actions during floods; self-evacuation during floods; availability of a map, place, route, and meeting point for family evacuation and shelter in the event of flooding; relatives or family groups who provide temporary shelter during floods; availability of first-aid box or essential medicines for first aid during floods; self-rescue initial measures in the event of flood; family groups who had received training on first aid and flood evacuation; the presence or absence of evacuation routes during floods; flood emergency preparation; knowledge on whether or not evacuation routes are available; availability of family communication equipment [cell phone or radio or Handy Talky] during flooding; availability of family lighting equipment for flood emergency [flashlight or emergency lamp or generator]; the availability of disaster preparedness bags; owning essential numbers that can be contacted in an emergency [hospital, police, fire department]; and whether or not to get flood preparedness education and materials).</p>
</sec>
<sec id="s20007">
<title>Data analysis</title>
<p>Univariate analysis of socio-demographic characteristics (gender, marital status, age, late education, employment, number of people living in the house, number of biological children, total income, and size or number of family groups) was presented in the frequency distribution table. Knowledge of KSB, natural hazards, and flood, as well as the emergency response plan parameters and flood management practices (before the disaster, during emergency response, and after the disaster), were displayed in the +standard deviation (s.d.) mean and frequency distribution. Bivariate analysis was used to assess differences in flood management practices (pre, during, and post) in two categories of inadequate and reasonable based on the socio-demographic characteristics, knowledge of KSB, understanding of natural hazards and floods, flood warning systems, and emergency response plan parameters by applying the Chi-Square test with a significance level of <italic>p</italic> &#x003C; 0.05. Multiple logistics multivariate analysis was used to assess the determinant independent variables that determine the practices of families with groups vulnerable to flood, health cadres ([<italic>posyandu/posbindu</italic>] of older people or mosquito larva monitoring [<italic>jumantik</italic>], and community leaders in flood management).</p>
</sec>
<sec id="s20008">
<title>Ethical considerations</title>
<p>An application for full ethical approval was made to the Ethics Commission for Health Research and Development (KEPPK) of the Sint Carolus School of Health Sciences and ethics consent was received on 20 July 2023. The ethics approval number is 112/KEPPKSTIKSC/VII/2023.</p>
</sec>
</sec>
<sec id="s0009">
<title>Results</title>
<sec id="s20010">
<title>Families with groups vulnerable to flood</title>
<p>The socio-demographic characteristics of families with groups belonging to one of the vulnerable groups to flood are presented in <xref ref-type="table" rid="T0001">Table 1</xref> (gender, marital status, age group, education level, occupation, income, number of family groups living in the house, and number of biological children living in the house). Married women comprised of the majority of respondents. Most respondents were between the age of 20 and 34 years, with a mean age of 40.9 &#x00B1; 15.5. Most had at least a high school education, worked informally, and had a monthly income of 1&#x2013;3 million. Living with a husband, children, and other family groups is the respondents&#x2019; most common living arrangement. Most respondents had 1&#x2013;2 biological children. Most respondents had a low level of knowledge about KSB, inadequate flood warning system and emergency response plan parameters, and inadequate flood disaster management practices, yet they had good family support (<xref ref-type="table" rid="T0002">Table 2</xref>).</p>
<table-wrap id="T0001">
<label>TABLE 1</label>
<caption><p>Sociodemographic characteristic.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="top" align="left">Variable</th>
<th valign="top" align="center">Number of participants (<italic>n</italic>)</th>
<th valign="top" align="center">Percentage (&#x0025;)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" colspan="3"><bold>Sex</bold></td>
</tr>
<tr>
<td align="left">Male</td>
<td align="center">39</td>
<td align="center">39.0</td>
</tr>
<tr>
<td align="left">Female</td>
<td align="center">61</td>
<td align="center">61.0</td>
</tr>
<tr>
<td align="left" colspan="3"><bold>Marital status</bold></td>
</tr>
<tr>
<td align="left">Single or widow or widower</td>
<td align="center">25</td>
<td align="center">25.0</td>
</tr>
<tr>
<td align="left">Married</td>
<td align="center">75</td>
<td align="center">75.0</td>
</tr>
<tr>
<td align="left" colspan="3"><bold>Age group (in years)</bold></td>
</tr>
<tr>
<td align="left">20&#x2013;34</td>
<td align="center">43</td>
<td align="center">43.0</td>
</tr>
<tr>
<td align="left">35&#x2013;49</td>
<td align="center">30</td>
<td align="center">30.0</td>
</tr>
<tr>
<td align="left">&#x003E; 49</td>
<td align="center">27</td>
<td align="center">27.0</td>
</tr>
<tr>
<td align="left" colspan="3"><bold>Final education</bold></td>
</tr>
<tr>
<td align="left">Graduated from junior high school or below</td>
<td align="center">46</td>
<td align="center">46.0</td>
</tr>
<tr>
<td align="left">Graduated from senior high school or above</td>
<td align="center">54</td>
<td align="center">54.0</td>
</tr>
<tr>
<td align="left" colspan="3"><bold>Job status</bold></td>
</tr>
<tr>
<td align="left">Work irregularly</td>
<td align="center">56</td>
<td align="center">56.0</td>
</tr>
<tr>
<td align="left">Work regularly</td>
<td align="center">44</td>
<td align="center">44.0</td>
</tr>
<tr>
<td align="left" colspan="3"><bold>Live at the same house with</bold></td>
</tr>
<tr>
<td align="left">Husband or wife or children and other family</td>
<td align="center">55</td>
<td align="center">55.0</td>
</tr>
<tr>
<td align="left">Husband or wife or children</td>
<td align="center">45</td>
<td align="center">45.0</td>
</tr>
<tr>
<td align="left" colspan="3"><bold>Number of owned children (person)</bold></td>
</tr>
<tr>
<td align="left">&#x003E; 2</td>
<td align="center">45</td>
<td align="center">45.0</td>
</tr>
<tr>
<td align="left">1&#x2013;2</td>
<td align="center">55</td>
<td align="center">55.0</td>
</tr>
<tr>
<td align="left" colspan="3"><bold>Monthly income (IDR)</bold></td>
</tr>
<tr>
<td align="left">&#x003C; 1 million</td>
<td align="center">23</td>
<td align="center">23.0</td>
</tr>
<tr>
<td align="left">1&#x2013;3 million</td>
<td align="center">45</td>
<td align="center">45.0</td>
</tr>
<tr>
<td align="left">&#x003E; 3 million</td>
<td align="center">32</td>
<td align="center">32.0</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p>Note: Age group mean is 41.0; standard deviation is 15.0. The minimum to maximum is 20.0&#x2013;78.0.</p></fn>
<fn><p>IDR, income-driven repayment.</p></fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="T0002">
<label>TABLE 2</label>
<caption><p>Preparedness parameter and flood management practice of respondents with flood-prone group.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="top" align="left" rowspan="2">Variable (number of questions, value range)</th>
<th valign="top" align="center" rowspan="2">Mean</th>
<th valign="top" align="center" rowspan="2">Median</th>
<th valign="top" align="center" rowspan="2">Min&#x2013;Max</th>
<th valign="top" align="center" rowspan="2">s.d.</th>
<th valign="top" align="center" colspan="2">Poor<hr/></th>
<th valign="top" align="center" colspan="2">Good<hr/></th>
</tr>
<tr>
<th valign="top" align="center"><italic>n</italic></th>
<th valign="top" align="center">&#x0025;</th>
<th valign="top" align="center"><italic>n</italic></th>
<th valign="top" align="center">&#x0025;</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left">Knowledge of <italic>Kampung Siaga Bencana</italic> (7 items, 0&#x2013;100)</td>
<td align="center">19.0</td>
<td align="center">0.0</td>
<td align="center">0.0&#x2013;86.0</td>
<td align="center">26.0</td>
<td align="center">66</td>
<td align="center">66</td>
<td align="center">34</td>
<td align="center">34</td>
</tr>
<tr>
<td align="left">Flood early warning system (12 items, 0&#x2013;100)</td>
<td align="center">30.0</td>
<td align="center">25.0</td>
<td align="center">0.0&#x2013;75.0</td>
<td align="center">17.0</td>
<td align="center">51</td>
<td align="center">51</td>
<td align="center">49</td>
<td align="center">49</td>
</tr>
<tr>
<td align="left">Emergency response plan (15 items, 0&#x2013;100)</td>
<td align="center">56.0</td>
<td align="center">53.0</td>
<td align="center">13.3&#x2013;100.0</td>
<td align="center">13.0</td>
<td align="center">54</td>
<td align="center">54</td>
<td align="center">45</td>
<td align="center">45</td>
</tr>
<tr>
<td align="left">Knowledge on natural hazard and flood (39 items, 0&#x2013;100)</td>
<td align="center">33.0</td>
<td align="center">31.0</td>
<td align="center">7.7&#x2013;74.0</td>
<td align="center">12.0</td>
<td align="center">54</td>
<td align="center">54</td>
<td align="center">46</td>
<td align="center">46</td>
</tr>
<tr>
<td align="left">Family support (4 items, 0&#x2013;100)</td>
<td align="center">19.0</td>
<td align="center">25.0</td>
<td align="center">0.0&#x2013;75.0</td>
<td align="center">19.0</td>
<td align="center">40</td>
<td align="center">40</td>
<td align="center">60</td>
<td align="center">60</td>
</tr>
<tr>
<td align="left">Practice before flood (18 items, 0&#x2013;100)</td>
<td align="center">31.0</td>
<td align="center">29.0</td>
<td align="center">5.6&#x2013;72.0</td>
<td align="center">13.0</td>
<td align="center">58</td>
<td align="center">58</td>
<td align="center">42</td>
<td align="center">42</td>
</tr>
<tr>
<td align="left">Practice during flood (31 items, 0&#x2013;100)</td>
<td align="center">34.0</td>
<td align="center">32.0</td>
<td align="center">12.9&#x2013;77.0</td>
<td align="center">11.0</td>
<td align="center">58</td>
<td align="center">58</td>
<td align="center">42</td>
<td align="center">42</td>
</tr>
<tr>
<td align="left">Practice after flood (8 items, (0&#x2013;100)</td>
<td align="center">31.0</td>
<td align="center">25.0</td>
<td align="center">0.0&#x2013;100.0</td>
<td align="center">19.0</td>
<td align="center">60</td>
<td align="center">60</td>
<td align="center">40</td>
<td align="center">40</td>
</tr>
<tr>
<td align="left">Flood management practice (57 item, 0&#x2013;100)</td>
<td align="center">32.0</td>
<td align="center">30.0</td>
<td align="center">10.5&#x2013;79.0</td>
<td align="center">13.0</td>
<td align="center">60</td>
<td align="center">60</td>
<td align="center">40</td>
<td align="center">40</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p>s.d., standard deviation.</p></fn>
</table-wrap-foot>
</table-wrap>
<p><xref ref-type="table" rid="T0003">Table 3</xref> illustrates differences in pre-flood practices by age group, education, number of biological children, knowledge of natural hazards and floods, flood warning system, and family support. Flood response practices differ based on age group, education, number of biological children, income, knowledge of natural hazards and floods, flood warning system, family support, and emergency response plan parameters. Differences based on post-flood practices were found in variables such as age group, marital status, final education, employment status, income, knowledge of natural hazards and floods, and family support. Respondents&#x2019; flood management practices differed by age group, employment status, final education, knowledge of natural hazards and floods, flood warning system, and family support. Results of the multivariate analysis of logistic regression on practices before flood demonstrated that the availability of a good flood warning system would support good pre-flood practices by 6.36 times, compared to an inadequate flood warning system. A good flood warning system was 6.57 times more likely to support good flood response practices. A good level of knowledge of natural hazards and floods had a probability of good after-flood practices of 4.3 times higher compared to an inadequate level of knowledge of natural hazards and floods. A good flood warning system was 11.15 times more likely to lead to good flood management practices than an inadequate flood warning system (<xref ref-type="table" rid="T0004">Table 4</xref>).</p>
<table-wrap id="T0003">
<label>TABLE 3a</label>
<caption><p>Differences in flood management practices based on socio-demographic characteristics, disaster knowledge, flood early warning systems, family support, and emergency response plans in families with members of flood-prone group.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="top" align="left" rowspan="3">Variable</th>
<th valign="top" align="center" colspan="4">Before flood<hr/></th>
<th valign="top" align="center" rowspan="3"><italic>p</italic></th>
<th valign="top" align="center" rowspan="3">OR</th>
<th valign="top" align="center" rowspan="3">95&#x0025; CI OR</th>
<th valign="top" align="center" colspan="4">During flood<hr/></th>
<th valign="top" align="center" rowspan="3"><italic>p</italic></th>
<th valign="top" align="center" rowspan="3">OR</th>
<th valign="top" align="center" rowspan="3">95&#x0025; CI OR</th>
</tr>
<tr>
<th valign="top" align="center" colspan="2">Poor<hr/></th>
<th valign="top" align="center" colspan="2">Good<hr/></th>
<th valign="top" align="center" colspan="2">Poor<hr/></th>
<th valign="top" align="center" colspan="2">Good<hr/></th>
</tr>
<tr>
<th valign="top" align="center"><italic>n</italic></th>
<th valign="top" align="center">&#x0025;</th>
<th valign="top" align="center"><italic>n</italic></th>
<th valign="top" align="center">&#x0025;</th>
<th valign="top" align="center"><italic>n</italic></th>
<th valign="top" align="center">&#x0025;</th>
<th valign="top" align="center"><italic>n</italic></th>
<th valign="top" align="center">&#x0025;</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" colspan="15"><bold>Sex</bold></td>
</tr>
<tr>
<td align="left">Male</td>
<td align="center">24</td>
<td align="center">61.0</td>
<td align="center">15</td>
<td align="center">38.0</td>
<td align="center">0.566</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">26</td>
<td align="center">67.0</td>
<td align="center">13</td>
<td align="center">33.0</td>
<td align="center">0.160</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Female</td>
<td align="center">34</td>
<td align="center">56.0</td>
<td align="center">27</td>
<td align="center">44.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">1.0&#x2013;4.0</td>
<td align="center">32</td>
<td align="center">52.0</td>
<td align="center">29</td>
<td align="center">47.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">0.8&#x2013;4.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Marital status</bold></td>
</tr>
<tr>
<td align="left">Married</td>
<td align="center">47</td>
<td align="center">63.0</td>
<td align="center">28</td>
<td align="center">37.0</td>
<td align="center">0.101</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">44</td>
<td align="center">59.0</td>
<td align="center">31</td>
<td align="center">41.0</td>
<td align="center">0.815</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Single or widow or widower</td>
<td align="center">11</td>
<td align="center">44.0</td>
<td align="center">14</td>
<td align="center">56.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;5.0</td>
<td align="center">14</td>
<td align="center">56.0</td>
<td align="center">11</td>
<td align="center">44.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.4&#x2013;3.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Age group (in years)</bold></td>
</tr>
<tr>
<td align="left">&#x003E; 49</td>
<td align="center">21</td>
<td align="center">78.0</td>
<td align="center">6</td>
<td align="center">22.0</td>
<td align="center">0.035</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">24</td>
<td align="center">89.0</td>
<td align="center">3</td>
<td align="center">11.0</td>
<td align="center">0.001</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">35&#x2013;49</td>
<td align="center">17</td>
<td align="center">57.0</td>
<td align="center">13</td>
<td align="center">43.0</td>
<td align="center">-</td>
<td align="center">3.0</td>
<td align="center">1.0&#x2013;8.0</td>
<td align="center">17</td>
<td align="center">57.0</td>
<td align="center">13</td>
<td align="center">43.0</td>
<td align="center">-</td>
<td align="center">6.0</td>
<td align="center">1.0&#x2013;24.9</td>
</tr>
<tr>
<td align="left">20&#x2013;34</td>
<td align="center">20</td>
<td align="center">46.0</td>
<td align="center">23</td>
<td align="center">53.0</td>
<td align="center">-</td>
<td align="center">4.0</td>
<td align="center">1.0&#x2013;12.0</td>
<td align="center">17</td>
<td align="center">39.0</td>
<td align="center">26</td>
<td align="center">60.0</td>
<td align="center">-</td>
<td align="center">12.0</td>
<td align="center">3.0&#x2013;47.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Final education</bold></td>
</tr>
<tr>
<td align="left">Graduated from junior high school or below</td>
<td align="center">33</td>
<td align="center">72.0</td>
<td align="center">13</td>
<td align="center">28.0</td>
<td align="center">0.010</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">38</td>
<td align="center">83.0</td>
<td align="center">8</td>
<td align="center">17.0</td>
<td align="center">0.001</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Graduated from senior high school or above</td>
<td align="center">25</td>
<td align="center">46.0</td>
<td align="center">29</td>
<td align="center">54.0</td>
<td align="center">-</td>
<td align="center">3.0</td>
<td align="center">1.0&#x2013;7.0</td>
<td align="center">20</td>
<td align="center">37.0</td>
<td align="center">34</td>
<td align="center">63.0</td>
<td align="center">-</td>
<td align="center">8.0</td>
<td align="center">3.0&#x2013;21.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Working status</bold></td>
</tr>
<tr>
<td align="left">Irregularly work</td>
<td align="center">36</td>
<td align="center">64.0</td>
<td align="center">20</td>
<td align="center">36.0</td>
<td align="center">0.151</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">36</td>
<td align="center">64.0</td>
<td align="center">20</td>
<td align="center">36.0</td>
<td align="center">0.151</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Regularly work</td>
<td align="center">22</td>
<td align="center">50.0</td>
<td align="center">22</td>
<td align="center">50.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.8&#x2013;4.0</td>
<td align="center">22</td>
<td align="center">50.0</td>
<td align="center">22</td>
<td align="center">50.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">0.8&#x2013;4.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Live in the house with</bold></td>
</tr>
<tr>
<td align="left">Husband or wife or children, other family</td>
<td align="center">31</td>
<td align="center">56.0</td>
<td align="center">24</td>
<td align="center">44.0</td>
<td align="center">0.714</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">31</td>
<td align="center">56.0</td>
<td align="center">24</td>
<td align="center">44.0</td>
<td align="center">0.714</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Husband or wife or children</td>
<td align="center">27</td>
<td align="center">60.0</td>
<td align="center">18</td>
<td align="center">40.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.4&#x2013;2.0</td>
<td align="center">27</td>
<td align="center">60.0</td>
<td align="center">18</td>
<td align="center">40.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.4&#x2013;2.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Number of owned children (person)</bold></td>
</tr>
<tr>
<td align="left">&#x003E; 2</td>
<td align="center">31</td>
<td align="center">69.0</td>
<td align="center">14</td>
<td align="center">31.0</td>
<td align="center">0.046</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">31</td>
<td align="center">69.0</td>
<td align="center">14</td>
<td align="center">31.0</td>
<td align="center">0.046</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">1&#x2013;2</td>
<td align="center">27</td>
<td align="center">49.0</td>
<td align="center">28</td>
<td align="center">51.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;5.0</td>
<td align="center">27</td>
<td align="center">49.0</td>
<td align="center">28</td>
<td align="center">51.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;5.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Monthly income (IDR)</bold></td>
</tr>
<tr>
<td align="left">&#x003C; 1 million</td>
<td align="center">15</td>
<td align="center">65.0</td>
<td align="center">8</td>
<td align="center">35.0</td>
<td align="center">0.725</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">17</td>
<td align="center">74.0</td>
<td align="center">6</td>
<td align="center">26.0</td>
<td align="center">0.013</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">1&#x2013;3 million</td>
<td align="center">25</td>
<td align="center">56.0</td>
<td align="center">20</td>
<td align="center">44.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.5&#x2013;4.0</td>
<td align="center">29</td>
<td align="center">64.0</td>
<td align="center">16</td>
<td align="center">36.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">0.5&#x2013;5.0</td>
</tr>
<tr>
<td align="left">&#x003E; 3 million</td>
<td align="center">18</td>
<td align="center">56.0</td>
<td align="center">14</td>
<td align="center">44.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.5&#x2013;4.0</td>
<td align="center">12</td>
<td align="center">37.0</td>
<td align="center">20</td>
<td align="center">62.0</td>
<td align="center">-</td>
<td align="center">5.0</td>
<td align="center">1.0&#x2013;15.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Knowledge on <italic>Kampung Siaga Bencana</italic></bold></td>
</tr>
<tr>
<td align="left">Poor</td>
<td align="center">38</td>
<td align="center">57.6</td>
<td align="center">28</td>
<td align="center">42.0</td>
<td align="center">0.905</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">39</td>
<td align="center">59.0</td>
<td align="center">27</td>
<td align="center">41.0</td>
<td align="center">0.758</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Good</td>
<td align="center">20</td>
<td align="center">58.8</td>
<td align="center">14</td>
<td align="center">41.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.4&#x2013;2.0</td>
<td align="center">19</td>
<td align="center">56.0</td>
<td align="center">15</td>
<td align="center">44.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.5&#x2013;3.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Knowledge on natural hazard and flood</bold></td>
</tr>
<tr>
<td align="left">Poor</td>
<td align="center">39</td>
<td align="center">72.2</td>
<td align="center">15</td>
<td align="center">28.0</td>
<td align="center">0.002</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">43</td>
<td align="center">80.0</td>
<td align="center">11</td>
<td align="center">20.0</td>
<td align="center">0.001</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Good</td>
<td align="center">19</td>
<td align="center">41.3</td>
<td align="center">27</td>
<td align="center">59.0</td>
<td align="center">-</td>
<td align="center">4.0</td>
<td align="center">2.0&#x2013;8.0</td>
<td align="center">15</td>
<td align="center">33.0</td>
<td align="center">31</td>
<td align="center">67.0</td>
<td align="center">-</td>
<td align="center">8.0</td>
<td align="center">3.0&#x2013;20.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Flood early warning system</bold></td>
</tr>
<tr>
<td align="left">Poor</td>
<td align="center">37</td>
<td align="center">72.5</td>
<td align="center">14</td>
<td align="center">27.0</td>
<td align="center">0.003</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">37</td>
<td align="center">72.0</td>
<td align="center">14</td>
<td align="center">27.0</td>
<td align="center">0.003</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Good</td>
<td align="center">21</td>
<td align="center">42.9</td>
<td align="center">28</td>
<td align="center">57.0</td>
<td align="center">-</td>
<td align="center">3.0</td>
<td align="center">1.0&#x2013;8.0</td>
<td align="center">21</td>
<td align="center">43.0</td>
<td align="center">28</td>
<td align="center">57.0</td>
<td align="center">-</td>
<td align="center">3.0</td>
<td align="center">1.0&#x2013;8.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Family support</bold></td>
</tr>
<tr>
<td align="left">Poor</td>
<td align="center">31</td>
<td align="center">77.5</td>
<td align="center">9</td>
<td align="center">22.0</td>
<td align="center">0.001</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">33</td>
<td align="center">82.0</td>
<td align="center">7</td>
<td align="center">17.0</td>
<td align="center">0.001</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Good</td>
<td align="center">27</td>
<td align="center">45.0</td>
<td align="center">33</td>
<td align="center">55.0</td>
<td align="center">-</td>
<td align="center">4.0</td>
<td align="center">2.0&#x2013;10.0</td>
<td align="center">25</td>
<td align="center">42.0</td>
<td align="center">35</td>
<td align="center">58.0</td>
<td align="center">-</td>
<td align="center">7.0</td>
<td align="center">2.0&#x2013;17.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Emergency response plan</bold></td>
</tr>
<tr>
<td align="left">Poor</td>
<td align="center">32</td>
<td align="center">61.5</td>
<td align="center">20</td>
<td align="center">38.0</td>
<td align="center">0.456</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">37</td>
<td align="center">71.0</td>
<td align="center">15</td>
<td align="center">29.0</td>
<td align="center">0.006</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Good</td>
<td align="center">26</td>
<td align="center">54.2</td>
<td align="center">22</td>
<td align="center">46.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">1.0&#x2013;3.0</td>
<td align="center">21</td>
<td align="center">44.0</td>
<td align="center">27</td>
<td align="center">56.0</td>
<td align="center">-</td>
<td align="center">3.0</td>
<td align="center">1.0&#x2013;7.0</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p>CI, confidence interval; OR, odd ratio; s.d., standard deviation.</p></fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="T0003a">
<label>TABLE 3b</label>
<caption><p>Differences in flood management practices based on socio-demographic characteristics, disaster knowledge, flood early warning systems, family support, and emergency response plans in families with members of flood-prone group.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="top" align="left" rowspan="3">Variable</th>
<th valign="top" align="center" colspan="4">After flood<hr/></th>
<th valign="top" align="center" rowspan="3"><italic>p</italic></th>
<th valign="top" align="center" rowspan="3">OR</th>
<th valign="top" align="center" rowspan="3">95&#x0025; CI OR</th>
<th valign="top" align="center" colspan="4">Flood management<hr/></th>
<th valign="top" align="center" rowspan="3"><italic>p</italic></th>
<th valign="top" align="center" rowspan="3">OR</th>
<th valign="top" align="center" rowspan="3">95&#x0025; CI OR</th>
</tr>
<tr>
<th valign="top" align="center" colspan="2">Poor<hr/></th>
<th valign="top" align="center" colspan="2">Good<hr/></th>
<th valign="top" align="center" colspan="2">Poor<hr/></th>
<th valign="top" align="center" colspan="2">Good<hr/></th>
</tr>
<tr>
<th valign="top" align="center"><italic>n</italic></th>
<th valign="top" align="center">&#x0025;</th>
<th valign="top" align="center"><italic>n</italic></th>
<th valign="top" align="center">&#x0025;</th>
<th valign="top" align="center"><italic>n</italic></th>
<th valign="top" align="center">&#x0025;</th>
<th valign="top" align="center"><italic>n</italic></th>
<th valign="top" align="center">&#x0025;</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" colspan="15"><bold>Sex</bold></td>
</tr>
<tr>
<td align="left">Male</td>
<td align="center">22</td>
<td align="center">56.0</td>
<td align="center">17</td>
<td align="center">43.0</td>
<td align="center">0.947</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">25</td>
<td align="center">64.1</td>
<td align="center">14</td>
<td align="center">36.0</td>
<td align="center">0.503</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Female</td>
<td align="center">34</td>
<td align="center">56.0</td>
<td align="center">27</td>
<td align="center">44.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.5&#x2013;2.0</td>
<td align="center">35</td>
<td align="center">57.4</td>
<td align="center">26</td>
<td align="center">43.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.0 &#x2013; 3.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Marital status</bold></td>
</tr>
<tr>
<td align="left">Married</td>
<td align="center">46</td>
<td align="center">61.0</td>
<td align="center">29</td>
<td align="center">39.0</td>
<td align="center">0.063</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">12</td>
<td align="center">48.0</td>
<td align="center">13</td>
<td align="center">52.0</td>
<td align="center">0.157</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Single or widow or widower</td>
<td align="center">10</td>
<td align="center">40.0</td>
<td align="center">15</td>
<td align="center">60.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;6.0</td>
<td align="center">48</td>
<td align="center">64.0</td>
<td align="center">27</td>
<td align="center">36.0</td>
<td align="left"></td>
<td align="center">2.0</td>
<td align="center">1.0 &#x2013; 5.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Age group (in years)</bold></td>
</tr>
<tr>
<td align="left">&#x003E; 49</td>
<td align="center">21</td>
<td align="center">78.0</td>
<td align="center">6</td>
<td align="center">22.0</td>
<td align="center">0.013</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">24</td>
<td align="center">88.9</td>
<td align="center">3</td>
<td align="center">11.0</td>
<td align="center">0.001</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">35&#x2013;49</td>
<td align="center">17</td>
<td align="center">57.0</td>
<td align="center">13</td>
<td align="center">43.0</td>
<td align="center">-</td>
<td align="center">3.8</td>
<td align="center">1.0&#x2013;8.0</td>
<td align="center">18</td>
<td align="center">60.0</td>
<td align="center">12</td>
<td align="center">40.0</td>
<td align="center">-</td>
<td align="center">5.0</td>
<td align="center">1.0 &#x2013; 22.0</td>
</tr>
<tr>
<td align="left">20&#x2013;34</td>
<td align="center">18</td>
<td align="center">42.0</td>
<td align="center">25</td>
<td align="center">58.0</td>
<td align="center">-</td>
<td align="center">5.0</td>
<td align="center">2.0&#x2013;14.0</td>
<td align="center">18</td>
<td align="center">41.9</td>
<td align="center">25</td>
<td align="center">58.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">3.0 &#x2013; 43.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Final education</bold></td>
</tr>
<tr>
<td align="left">Graduated from junior high school or below</td>
<td align="center">34</td>
<td align="center">74.0</td>
<td align="center">12</td>
<td align="center">26.0</td>
<td align="center">0.001</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">38</td>
<td align="center">82.6</td>
<td align="center">8</td>
<td align="center">17.0</td>
<td align="center">0.001</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Graduated from senior high school or above</td>
<td align="center">22</td>
<td align="center">41.0</td>
<td align="center">32</td>
<td align="center">59.0</td>
<td align="center">-</td>
<td align="center">4.0</td>
<td align="center">2.0&#x2013;10.0</td>
<td align="center">22</td>
<td align="center">40.7</td>
<td align="center">32</td>
<td align="center">59.0</td>
<td align="center">-</td>
<td align="center">7.0</td>
<td align="center">3.0 &#x2013; 18.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Working status</bold></td>
</tr>
<tr>
<td align="left">Irregularly work</td>
<td align="center">37</td>
<td align="center">66.0</td>
<td align="center">19</td>
<td align="center">34.0</td>
<td align="center">0.022</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">40</td>
<td align="center">71.4</td>
<td align="center">16</td>
<td align="center">29.0</td>
<td align="center">0.008</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Regularly work</td>
<td align="center">19</td>
<td align="center">43.0</td>
<td align="center">25</td>
<td align="center">57.0</td>
<td align="center">-</td>
<td align="center">3.0</td>
<td align="center">1.0&#x2013;9.0</td>
<td align="center">20</td>
<td align="center">45.5</td>
<td align="center">24</td>
<td align="center">54.0</td>
<td align="center">-</td>
<td align="center">3.0</td>
<td align="center">1.0 &#x2013; 7.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Live in the house with</bold></td>
</tr>
<tr>
<td align="left">Husband or wife or children, other family</td>
<td align="center">28</td>
<td align="center">51.0</td>
<td align="center">27</td>
<td align="center">49.0</td>
<td align="center">0.257</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">32</td>
<td align="center">58.2</td>
<td align="center">23</td>
<td align="center">42.0</td>
<td align="center">0.682</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Husband or wife or children</td>
<td align="center">28</td>
<td align="center">62.0</td>
<td align="center">17</td>
<td align="center">38.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.3&#x2013;1.0</td>
<td align="center">28</td>
<td align="center">62.2</td>
<td align="center">17</td>
<td align="center">38.0</td>
<td align="center">-</td>
<td align="center">0.8</td>
<td align="center">0.4 &#x2013; 2.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Number of owned children (person)</bold></td>
</tr>
<tr>
<td align="left">&#x003E; 2</td>
<td align="center">27</td>
<td align="center">60.0</td>
<td align="center">18</td>
<td align="center">40.0</td>
<td align="center">0.466</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">31</td>
<td align="center">68.9</td>
<td align="center">14</td>
<td align="center">31.0</td>
<td align="center">0.101</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">1&#x2013;2</td>
<td align="center">29</td>
<td align="center">53.0</td>
<td align="center">26</td>
<td align="center">47.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">1.0 &#x2013; 3.0</td>
<td align="center">29</td>
<td align="center">52.7</td>
<td align="center">26</td>
<td align="center">47.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0 &#x2013; 4.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Monthly income (IDR)</bold></td>
</tr>
<tr>
<td align="left">&#x003C; 1 million</td>
<td align="center">17</td>
<td align="center">74.0</td>
<td align="center">6</td>
<td align="center">26.0</td>
<td align="center">0.021</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">17</td>
<td align="center">73.9</td>
<td align="center">6</td>
<td align="center">26.0</td>
<td align="center">0.120</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">1&#x2013;3 million</td>
<td align="center">27</td>
<td align="center">60.0</td>
<td align="center">18</td>
<td align="center">40.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0 &#x2013; 6.0</td>
<td align="center">28</td>
<td align="center">62.2</td>
<td align="center">17</td>
<td align="center">38.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">0.6 &#x2013; 5.0</td>
</tr>
<tr>
<td align="left">&#x003E; 3 million</td>
<td align="center">12</td>
<td align="center">37.0</td>
<td align="center">20</td>
<td align="center">62.0</td>
<td align="center">-</td>
<td align="center">8.0</td>
<td align="center">1.0&#x2013;15.0</td>
<td align="center">15</td>
<td align="center">46.9</td>
<td align="center">17</td>
<td align="center">53.0</td>
<td align="center">-</td>
<td align="center">3. 0</td>
<td align="center">1.0 &#x2013; 10.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Knowledge on <italic>Kampung Siaga Bencana</italic></bold></td>
</tr>
<tr>
<td align="left">Poor</td>
<td align="center">38</td>
<td align="center">58.0</td>
<td align="center">28</td>
<td align="center">42.0</td>
<td align="center">0.658</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">39</td>
<td align="center">59,1</td>
<td align="center">27</td>
<td align="center">41.0</td>
<td align="center">0.796</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Good</td>
<td align="center">18</td>
<td align="center">53.0</td>
<td align="center">16</td>
<td align="center">47.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.5&#x2013;3.0</td>
<td align="center">21</td>
<td align="center">61,8</td>
<td align="center">13</td>
<td align="center">38.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.4 &#x2013; 2.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Knowledge on natural hazard and flood</bold></td>
</tr>
<tr>
<td align="left">Poor</td>
<td align="center">39</td>
<td align="center">72.0</td>
<td align="center">15</td>
<td align="center">28.0</td>
<td align="center">0.001</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">44</td>
<td align="center">81.5</td>
<td align="center">10</td>
<td align="center">18.0</td>
<td align="center">0.001</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Good</td>
<td align="center">17</td>
<td align="center">37.0</td>
<td align="center">29</td>
<td align="center">63.0</td>
<td align="center">-</td>
<td align="center">4.0</td>
<td align="center">3.0&#x2013;10.0</td>
<td align="center">16</td>
<td align="center">34.8</td>
<td align="center">30</td>
<td align="center">65.0</td>
<td align="center">-</td>
<td align="center">8.0</td>
<td align="center">3.0 &#x2013; 22.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Flood early warning system</bold></td>
</tr>
<tr>
<td align="left">Poor</td>
<td align="center">32</td>
<td align="center">63.0</td>
<td align="center">19</td>
<td align="center">37.0</td>
<td align="center">0.166</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">38</td>
<td align="center">74.5</td>
<td align="center">13</td>
<td align="center">25.0</td>
<td align="center">0.003</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Good</td>
<td align="center">24</td>
<td align="center">49.0</td>
<td align="center">25</td>
<td align="center">51.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;4.0</td>
<td align="center">22</td>
<td align="center">44.9</td>
<td align="center">27</td>
<td align="center">55.0</td>
<td align="center">-</td>
<td align="center">4.0</td>
<td align="center">1.0 &#x2013; 8.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Family support</bold></td>
</tr>
<tr>
<td align="left">Poor</td>
<td align="center">29</td>
<td align="center">72.0</td>
<td align="center">11</td>
<td align="center">27.0</td>
<td align="center">0.007</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">34</td>
<td align="center">85.0</td>
<td align="center">6</td>
<td align="center">15.0</td>
<td align="center">0.001</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Good</td>
<td align="center">27</td>
<td align="center">45.0</td>
<td align="center">33</td>
<td align="center">55.0</td>
<td align="center">-</td>
<td align="center">3.0</td>
<td align="center">1.0 &#x2013; 8.0</td>
<td align="center">26</td>
<td align="center">43.3</td>
<td align="center">34</td>
<td align="center">57.0</td>
<td align="center">-</td>
<td align="center">7.0</td>
<td align="center">3.0 &#x2013; 21.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Emergency response plan</bold></td>
</tr>
<tr>
<td align="left">Poor</td>
<td align="center">33</td>
<td align="center">63.0</td>
<td align="center">19</td>
<td align="center">36.0</td>
<td align="center">0.118</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">36</td>
<td align="center">69.2</td>
<td align="center">16</td>
<td align="center">31.0</td>
<td align="center">0.050</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Good</td>
<td align="center">23</td>
<td align="center">48.0</td>
<td align="center">25</td>
<td align="center">52.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0 &#x2013; 4.0</td>
<td align="center">24</td>
<td align="center">50.0</td>
<td align="center">24</td>
<td align="center">50.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0 &#x2013; 5.0</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p>CI, confidence interval; OR, odd ratio; s.d., standard deviation.</p></fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="T0004">
<label>TABLE 4</label>
<caption><p>Multivariate analysis of the flood management practices dominant variable in families with flood-vulnerable members.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="top" align="left" rowspan="2">Variable</th>
<th valign="top" align="center" rowspan="2">Logistic coefficients (B)</th>
<th valign="top" align="center" rowspan="2">Standard error (s.e.)</th>
<th valign="top" align="center" rowspan="2">Wald</th>
<th valign="top" align="center" rowspan="2">db</th>
<th valign="top" align="center" rowspan="2"><italic>p</italic></th>
<th valign="top" align="center" rowspan="2">OR</th>
<th valign="top" align="center" colspan="2">95&#x0025; CI OR<hr/></th>
</tr>
<tr>
<th valign="top" align="center">BB</th>
<th valign="top" align="center">BA</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" colspan="9"><bold>Before flood</bold></td>
</tr>
<tr>
<td align="left">Marital status <italic>(Single or widow or widower vs. married)</italic></td>
<td align="center">1.44</td>
<td align="center">0.58</td>
<td align="center">6.17</td>
<td align="center">1</td>
<td align="center">0.013</td>
<td align="center">4.24</td>
<td align="center">1.36</td>
<td align="center">13.26</td>
</tr>
<tr>
<td align="left">Flood early warning system <italic>(Good vs. Poor)</italic></td>
<td align="center">1.83</td>
<td align="center">0.52</td>
<td align="center">12.38</td>
<td align="center">1</td>
<td align="center">0.000</td>
<td align="center">6.26</td>
<td align="center">2.25</td>
<td align="center">17.41</td>
</tr>
<tr>
<td align="left">Family support before flood <italic>(Good vs. Poor)</italic></td>
<td align="center">1.75</td>
<td align="center">0.52</td>
<td align="center">11.45</td>
<td align="center">1</td>
<td align="center">0.001</td>
<td align="center">5.77</td>
<td align="center">2.09</td>
<td align="center">15.92</td>
</tr>
<tr>
<td align="left">Constant</td>
<td align="center">&#x2212;2.75</td>
<td align="center">0.61</td>
<td align="center">20.31</td>
<td align="center">1</td>
<td align="center">0.000</td>
<td align="center">0.06</td>
<td align="center">-</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left" colspan="9"><italic>-2LL=107.8, Cox and Snell R Square = 0.23, Nagelkerke R Square = 0.33, Omnibus Test Model = 28.285, p = 0.001</italic></td>
</tr>
<tr>
<td align="left" colspan="9"><bold>During flood</bold></td>
</tr>
<tr>
<td align="left">Final education <italic>(Graduated from senior high school or above vs. Graduated from junior high school or below)</italic></td>
<td align="center">1.41</td>
<td align="center">0.58</td>
<td align="center">5.86</td>
<td align="center">1</td>
<td align="center">0.016</td>
<td align="center">4.10</td>
<td align="center">1.31</td>
<td align="center">12.83</td>
</tr>
<tr>
<td align="left">Knowledge on natural hazard and flood <italic>(Good vs. Poor)</italic></td>
<td align="center">1.73</td>
<td align="center">0.61</td>
<td align="center">8.04</td>
<td align="center">1</td>
<td align="center">0.005</td>
<td align="center">5.64</td>
<td align="center">1.71</td>
<td align="center">18.68</td>
</tr>
<tr>
<td align="left">Flood early warning system <italic>(Good vs. Poor)</italic></td>
<td align="center">1.88</td>
<td align="center">0.59</td>
<td align="center">10.04</td>
<td align="center">1</td>
<td align="center">0.002</td>
<td align="center">6.57</td>
<td align="center">2.05</td>
<td align="center">21.05</td>
</tr>
<tr>
<td align="left">Family support before flood <italic>(Good vs. Poor)</italic></td>
<td align="center">1.27</td>
<td align="center">0.63</td>
<td align="center">4.11</td>
<td align="center">1</td>
<td align="center">0.043</td>
<td align="center">3.56</td>
<td align="center">1.04</td>
<td align="center">12.16</td>
</tr>
<tr>
<td align="left">Constant</td>
<td align="center">&#x2212;3.82</td>
<td align="center">0.77</td>
<td align="center">24.75</td>
<td align="center">1</td>
<td align="center">0.000</td>
<td align="center">0.02</td>
<td align="center">-</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left" colspan="9"><italic>-2LL = 86.0, Cox and Snell R Square = 0.39, Nagelkerke R Square = 0.53, Omnibus Test Model = 50.05, p = 0.001</italic></td>
</tr>
<tr>
<td align="left" colspan="9"><bold>After flood</bold></td>
</tr>
<tr>
<td align="left">Working status <italic>(Regularly vs. Irregularly)</italic></td>
<td align="center">0.89</td>
<td align="center">0.44</td>
<td align="center">4.05</td>
<td align="center">1</td>
<td align="center">0.044</td>
<td align="center">2.43</td>
<td align="center">1.02</td>
<td align="center">5.79</td>
</tr>
<tr>
<td align="left">Knowledge on natural hazard and flood <italic>(Good vs. Poor)</italic></td>
<td align="center">1.46</td>
<td align="center">0.44</td>
<td align="center">10.95</td>
<td align="center">1</td>
<td align="center">0.001</td>
<td align="center">4.30</td>
<td align="center">1.81</td>
<td align="center">10.18</td>
</tr>
<tr>
<td align="left">Constant</td>
<td align="center">&#x2212;1.34</td>
<td align="center">0.38</td>
<td align="center">12.78</td>
<td align="center">1</td>
<td align="center">0.000</td>
<td align="center">0.26</td>
<td align="center">-</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left" colspan="9"><italic>-2LL = 120.28 Cox and Snell R Square = 0.16, Nagelkerke R Square=0.21, Omnibus Test Model=16.9, p = 0.001</italic></td>
</tr>
<tr>
<td align="left" colspan="9"><bold>Flood management</bold></td>
</tr>
<tr>
<td align="left">Working status <italic>(Regularly vs. Irregularly)</italic></td>
<td align="center">1.66</td>
<td align="center">0,60</td>
<td align="center">7.56</td>
<td align="center">1</td>
<td align="center">0.006</td>
<td align="center">5.26</td>
<td align="center">1.61</td>
<td align="center">17.16</td>
</tr>
<tr>
<td align="left">Knowledge on natural hazard and flood <italic>(Good vs. Poor)</italic></td>
<td align="center">2.15</td>
<td align="center">0.62</td>
<td align="center">11.95</td>
<td align="center">1</td>
<td align="center">0.001</td>
<td align="center">8.59</td>
<td align="center">2.54</td>
<td align="center">29.10</td>
</tr>
<tr>
<td align="left">Flood early warning system <italic>(Good vs. Poor)</italic></td>
<td align="center">2.41</td>
<td align="center">0.66</td>
<td align="center">13.34</td>
<td align="center">1</td>
<td align="center">0.000</td>
<td align="center">11.15</td>
<td align="center">3.06</td>
<td align="center">40.69</td>
</tr>
<tr>
<td align="left">Family support before flood <italic>(Good vs. Poor)</italic></td>
<td align="center">1.67</td>
<td align="center">0.64</td>
<td align="center">6.80</td>
<td align="center">1</td>
<td align="center">0.009</td>
<td align="center">5.32</td>
<td align="center">1.51</td>
<td align="center">18.69</td>
</tr>
<tr>
<td align="left">Constant</td>
<td align="center">&#x2212;4.53</td>
<td align="center">0.87</td>
<td align="center">26.86</td>
<td align="center">1</td>
<td align="center">0.000</td>
<td align="center">0.01</td>
<td align="center">-</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left" colspan="9"><italic>-2LL = 81.02 Cox and Snell R Square = 0.42, Nagelkerke R Square = 0.56, Omnibus Test Model = 53.59, p = 0.001</italic></td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p>CI, confidence interval; OR, odd ratio.</p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s20011">
<title>Cadres and community leaders</title>
<p>Most respondents have <italic>dasawisma/posyandu/jumantik</italic> cadre positions with equal gender proportion between males and females. The percentage of married respondents was almost five times higher than those who were not married (single, widow/widower). The majority of respondents were over the age of 50 years, with a mean of 46.9 years, and at least graduated from senior high school. Most respondents worked as <italic>RT</italic> (neighborhood association)<italic>/RW</italic> (citizen association) staff, volunteers, cadres, and community leaders. Respondents generally lived with their nuclear family, which consisted of the husband/wife and their children. Most respondents had 1&#x2013;2 biological children with a monthly income of 1&#x2013;3m (<xref ref-type="table" rid="T0005">Table 5</xref>). The levels of knowledge of natural hazards and floods, flood warning systems, emergency response parameters, and pre-flood practices were classified as suitable for most respondents, except for knowledge of natural hazards and floods. The comparison between good flood management practices and after-flood practices was similar to inadequate practices (<xref ref-type="table" rid="T0006">Table 6</xref>).</p>
<table-wrap id="T0005">
<label>TABLE 5</label>
<caption><p>Sociodemographic characteristic of health cadres and community leaders.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="top" align="left">Variable</th>
<th valign="top" align="center">Number of participants (<italic>n</italic>)</th>
<th valign="top" align="center">Percentage (&#x0025;)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" colspan="3"><bold>Position in the community</bold></td>
</tr>
<tr>
<td align="left">Chairman or staff of <italic>RT or RW</italic></td>
<td align="center">38</td>
<td align="center">38.0</td>
</tr>
<tr>
<td align="left">Youth organization or community leaders</td>
<td align="center">23</td>
<td align="center">23.0</td>
</tr>
<tr>
<td align="left"><italic>Dasawisma or posyandu</italic> cadres</td>
<td align="center">39</td>
<td align="center">39.0</td>
</tr>
<tr>
<td align="left" colspan="3"><bold>Sex</bold></td>
</tr>
<tr>
<td align="left">Male</td>
<td align="center">50</td>
<td align="center">50.0</td>
</tr>
<tr>
<td align="left">Female</td>
<td align="center">50</td>
<td align="center">50.0</td>
</tr>
<tr>
<td align="left" colspan="3"><bold>Marital status</bold></td>
</tr>
<tr>
<td align="left">Single or widow or widower</td>
<td align="center">17</td>
<td align="center">17.0</td>
</tr>
<tr>
<td align="left">Married</td>
<td align="center">83</td>
<td align="center">83.0</td>
</tr>
<tr>
<td align="left" colspan="3"><bold>Age group (in years)</bold></td>
</tr>
<tr>
<td align="left">20&#x2013;40</td>
<td align="center">28</td>
<td align="center">28.0</td>
</tr>
<tr>
<td align="left">41&#x2013;50</td>
<td align="center">35</td>
<td align="center">35.0</td>
</tr>
<tr>
<td align="left">&#x003E; 50</td>
<td align="center">37</td>
<td align="center">37.0</td>
</tr>
<tr>
<td align="left" colspan="3"><bold>Final education</bold></td>
</tr>
<tr>
<td align="left">Graduated from junior high school or below</td>
<td align="center">33</td>
<td align="center">33.0</td>
</tr>
<tr>
<td align="left">Graduated from senior high school or above</td>
<td align="center">67</td>
<td align="center">67.0</td>
</tr>
<tr>
<td align="left" colspan="3"><bold>Working status</bold></td>
</tr>
<tr>
<td align="left">Irregularly work</td>
<td align="center">44</td>
<td align="center">44.0</td>
</tr>
<tr>
<td align="left">Regularly work</td>
<td align="center">35</td>
<td align="center">35.0</td>
</tr>
<tr>
<td align="left">Staf RW or RT or volunteer or health cadres or community leader</td>
<td align="center">21</td>
<td align="center">21.0</td>
</tr>
<tr>
<td align="left" colspan="3"><bold>Live in the same house with</bold></td>
</tr>
<tr>
<td align="left">Husband or wife or children with other family</td>
<td align="center">41</td>
<td align="center">41.0</td>
</tr>
<tr>
<td align="left">Husband or wife or children with other</td>
<td align="center">59</td>
<td align="center">59.0</td>
</tr>
<tr>
<td align="left" colspan="3"><bold>Number of owned children</bold></td>
</tr>
<tr>
<td align="left">&#x003E; 2</td>
<td align="center">36</td>
<td align="center">36.0</td>
</tr>
<tr>
<td align="left">1&#x2013;2</td>
<td align="center">64</td>
<td align="center">64.0</td>
</tr>
<tr>
<td align="left" colspan="3"><bold>Monthly income (IDR)</bold></td>
</tr>
<tr>
<td align="left">1&#x2013;3 million</td>
<td align="center">60</td>
<td align="center">60.0</td>
</tr>
<tr>
<td align="left">&#x003E; 3 million</td>
<td align="center">40</td>
<td align="center">40.0</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p>Note: Age group (in years) Mean is 47.0; standard deviation is 11.0; Min-Max is 19.0&#x2013;70.0.</p></fn>
<fn><p>s.d., standard deviation; RT, neighborhood association; RW, citizens association; IDR, income-driven repayment.</p></fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="T0006">
<label>TABLE 6</label>
<caption><p>Preparedness parameter and flood management practice of health cadres and community leaders.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="top" align="left" rowspan="2">Variable (number of questions, value range)</th>
<th valign="top" align="center" rowspan="2">Mean</th>
<th valign="top" align="center" rowspan="2">Median</th>
<th valign="top" align="center" rowspan="2">Min-Max</th>
<th valign="top" align="center" rowspan="2">s.d.</th>
<th valign="top" align="center" colspan="2">Poor<hr/></th>
<th valign="top" align="center" colspan="2">Good<hr/></th>
</tr>
<tr>
<th valign="top" align="center"><italic>n</italic></th>
<th valign="top" align="center">&#x0025;</th>
<th valign="top" align="center"><italic>n</italic></th>
<th valign="top" align="center">&#x0025;</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left">Knowledge of KSB (13 items, 0&#x2013;100)</td>
<td align="center">28.0</td>
<td align="center">31.0</td>
<td align="center">0.0&#x2013;69.0</td>
<td align="center">19.0</td>
<td align="center">42</td>
<td align="center">42</td>
<td align="center">58</td>
<td align="center">58</td>
</tr>
<tr>
<td align="left">Food early warning system (12 items, 0&#x2013;100)</td>
<td align="center">34.0</td>
<td align="center">33.0</td>
<td align="center">0.0&#x2013;92.0</td>
<td align="center">17.0</td>
<td align="center">39</td>
<td align="center">39</td>
<td align="center">61</td>
<td align="center">61</td>
</tr>
<tr>
<td align="left">Emergency response plan (15 items, 0&#x2013;100)</td>
<td align="center">70.0</td>
<td align="center">73.0</td>
<td align="center">47.0&#x2013;93.0</td>
<td align="center">11.0</td>
<td align="center">49</td>
<td align="center">49</td>
<td align="center">51</td>
<td align="center">51</td>
</tr>
<tr>
<td align="left">Knowledge on natural disaster and flood (37 items, 0&#x2013;100)</td>
<td align="center">42.0</td>
<td align="center">43.0</td>
<td align="center">19.0&#x2013;78.0</td>
<td align="center">11.0</td>
<td align="center">45</td>
<td align="center">45</td>
<td align="center">55</td>
<td align="center">55</td>
</tr>
<tr>
<td align="left">Practice before flood (15 items, 0&#x2013;100)</td>
<td align="center">44.0</td>
<td align="center">47.0</td>
<td align="center">13.0&#x2013;87.0</td>
<td align="center">14.0</td>
<td align="center">49</td>
<td align="center">49</td>
<td align="center">51</td>
<td align="center">51</td>
</tr>
<tr>
<td align="left">Practice during flood (30 items, 0&#x2013;100)</td>
<td align="center">30.0</td>
<td align="center">27.0</td>
<td align="center">13.0&#x2013;70.0</td>
<td align="center">10.0</td>
<td align="center">48</td>
<td align="center">48</td>
<td align="center">52</td>
<td align="center">52</td>
</tr>
<tr>
<td align="left">Practice after flood (9 items, 0&#x2013;100)</td>
<td align="center">37.0</td>
<td align="center">35.0</td>
<td align="center">11.0&#x2013;67.0</td>
<td align="center">15.0</td>
<td align="center">50</td>
<td align="center">50</td>
<td align="center">50</td>
<td align="center">50</td>
</tr>
<tr>
<td align="left">Flood management practice (54 items, 0&#x2013;100)</td>
<td align="center">40.0</td>
<td align="center">35.0</td>
<td align="center">11.0&#x2013;67.0</td>
<td align="center">11.0</td>
<td align="center">50</td>
<td align="center">50</td>
<td align="center">50</td>
<td align="center">50</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p>s.d., standard deviation.</p></fn>
</table-wrap-foot>
</table-wrap>
<p>Most respondents took several measures to protect residents with vulnerable family groups from floods. These measures included providing verbal explanations on self-evacuation steps, maps, and plans and disseminating and educating residents on flood control programs. Respondents mostly facilitated the self-evacuation of flood-prone groups to safer places during floods. In addition, almost all respondents prioritized rescuing children, pregnant women, nursing mothers, the elderly, and persons with disabilities during floods. This was because these groups had limited movement, could not help themselves, and were more susceptible to sickness. Post-flood respondents mainly focused on ensuring the health condition of flood-prone groups. However, providing nutritious food, medicine, and vitamins was the least frequently done effort by respondents after the flood (<xref ref-type="table" rid="T0007">Table 7</xref>).</p>
<table-wrap id="T0007">
<label>TABLE 7</label>
<caption><p>Distribution of frequency of flood management practices, participation in disaster training, efforts to increase community preparedness, willingness to become KSB among health cadres and community leaders.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="top" align="left">Variable</th>
<th valign="top" align="center">Number of participants (<italic>n</italic>)</th>
<th valign="top" align="center">Percentage (&#x0025;)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" colspan="3"><bold>Before flood (<italic>multiple answer</italic>)</bold></td>
</tr>
<tr>
<td align="left">Explain verbally the steps/map/plan for self-evacuation</td>
<td align="center">47</td>
<td align="center">47</td>
</tr>
<tr>
<td align="left">Practice self-evacuation plans/steps</td>
<td align="center">26</td>
<td align="center">26</td>
</tr>
<tr>
<td align="left">Education and socialisation of flood prevention behaviour</td>
<td align="center">50</td>
<td align="center">50</td>
</tr>
<tr>
<td align="left" colspan="3"><bold>During flood (<italic>multiple answer</italic>)</bold></td>
</tr>
<tr>
<td align="left">Evacuate himself/herself via the evacuation route to a safe place</td>
<td align="center">68</td>
<td align="center">68</td>
</tr>
<tr>
<td align="left">Prioritise residents vulnerable to flooding for evacuation</td>
<td align="center">98</td>
<td align="center">98</td>
</tr>
<tr>
<td align="left" colspan="3"><bold>After flood (<italic>multiple answer</italic>)</bold></td>
</tr>
<tr>
<td align="left">Ensure the health status is in good condition</td>
<td align="center">65</td>
<td align="center">65</td>
</tr>
<tr>
<td align="left">Give the medicine and food if necessary</td>
<td align="center">32</td>
<td align="center">32</td>
</tr>
<tr>
<td align="left">Give nutritious food and safe water</td>
<td align="center">-</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Efforts are made when hearing danger signs for groups vulnerable to flooding (<italic>multiple answer</italic>)</td>
<td align="center">-</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Help evacuate flood-prone communities to safe places</td>
<td align="center">37</td>
<td align="center">37</td>
</tr>
<tr>
<td align="left" colspan="3"><bold>Readiness becomes KSB (<italic>single answer</italic>):</bold></td>
</tr>
<tr>
<td align="left">Participation in the disaster training</td>
<td align="center">-</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Yes</td>
<td align="center">42</td>
<td align="center">42</td>
</tr>
<tr>
<td align="left">No</td>
<td align="center">58</td>
<td align="center">58</td>
</tr>
<tr>
<td align="left" colspan="3"><bold>Type of disaster training attended before (<italic>multiple answer</italic>)</bold></td>
</tr>
<tr>
<td align="left">Disaster mitigation</td>
<td align="center">34</td>
<td align="center">34</td>
</tr>
<tr>
<td align="left">Handling assistance to injured victims</td>
<td align="center">10</td>
<td align="center">10</td>
</tr>
<tr>
<td align="left">Flood evacuation simulation</td>
<td align="center">10</td>
<td align="center">10</td>
</tr>
<tr>
<td align="left">Basic Life Support (BLS)</td>
<td align="center">4</td>
<td align="center">4</td>
</tr>
<tr>
<td align="left" colspan="3"><bold>Readiness becomes KSB (<italic>single answer</italic>)</bold></td>
</tr>
<tr>
<td align="left">Yes</td>
<td align="center">72</td>
<td align="center">72</td>
</tr>
<tr>
<td align="left">No</td>
<td align="center">28</td>
<td align="center">28</td>
</tr>
<tr>
<td align="left" colspan="3"><bold>The reasons for being willing to become a KSB (<italic>single answer</italic>)</bold></td>
</tr>
<tr>
<td align="left">Helping community</td>
<td align="center">25</td>
<td align="center">25</td>
</tr>
<tr>
<td align="left">Participate in facing flood</td>
<td align="center">50</td>
<td align="center">50</td>
</tr>
<tr>
<td align="left">A form of social activity in society</td>
<td align="center">15</td>
<td align="center">15</td>
</tr>
<tr>
<td align="left">A form of social responsibility activity in society</td>
<td align="center">10</td>
<td align="center">10</td>
</tr>
<tr>
<td align="left" colspan="3"><bold>Willing to take part in KSB skills improvement training (<italic>single answer</italic>)</bold></td>
</tr>
<tr>
<td align="left">Yes</td>
<td align="center">69</td>
<td align="center">69</td>
</tr>
<tr>
<td align="left">No</td>
<td align="center">31</td>
<td align="center">31</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>Almost half of all respondents had attended flood preparedness training held in the local village office, with most attending the training in 2018. Most training providers were from the DKI Jakarta Fire Brigade, Jakarta City of Regional Disaster Management Agency (<italic>BPBD</italic>), the local village government, and Wahana Visi NGO. The types of training attended were flood and earthquake evacuation simulations, first aid, injury management, and flood mitigation. Respondents made several efforts to improve community preparedness in their environment, including appeals not to litter carelessly, information sharing on self-evacuation during floods, community service practices, flood mitigation simulations, and information on drug preparation. When asked about their willingness to become KSB, most expressed their desire to join because it is a good cause to help residents and participate in managing floods. The KSB is also seen as a social cause for the community and a form of responsibility towards the community. Most respondents were willing to participate in disaster training to be more skilled in flood management and improve their knowledge (<xref ref-type="table" rid="T0007">Table 7</xref>).</p>
<p>Flood management practices differ significantly based on knowledge of KSB, understanding of natural hazards and floods, flood warning systems, and emergency response plans (<xref ref-type="table" rid="T0008">Table 8</xref>). The multivariate analysis showed that communities with a good flood early warning system were 6.33 times more likely to have pre-flood practices than communities with inadequate flood early warning systems. Variables significantly associated with flood emergency response practices were knowledge of KSB, understanding of natural hazards and floods, and emergency response plan parameters. The most dominant variable was knowledge of natural hazards and floods at 8.15. Understanding natural hazards and floods also dominated post-flood practices at 8.16 and flood management practices at 4.52 (<xref ref-type="table" rid="T0009">Table 9</xref>).</p>
<table-wrap id="T0008">
<label>TABLE 8a</label>
<caption><p>Differences in flood management practices based on socio-demographic characteristics, <italic>Kampung Siaga Bencana</italic> knowledge, disaster knowledge, flood EWS, a demergency response plans for heat cadres and comm. leaders.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="top" align="left" rowspan="3">Variable</th>
<th valign="top" align="center" colspan="4">Before flood<hr/></th>
<th valign="top" align="center" rowspan="3"><italic>p</italic></th>
<th valign="top" align="center" rowspan="3">OR</th>
<th valign="top" align="center" rowspan="3">95&#x0025; CI OR</th>
<th valign="top" align="center" colspan="4">During flood<hr/></th>
<th valign="top" align="center" rowspan="3"><italic>p</italic></th>
<th valign="top" align="center" rowspan="3">OR</th>
<th valign="top" align="center" rowspan="3">95&#x0025; CI OR</th>
</tr>
<tr>
<th valign="top" align="center" colspan="2">Poor<hr/></th>
<th valign="top" align="center" colspan="2">Good<hr/></th>
<th valign="top" align="center" colspan="2">Poor<hr/></th>
<th valign="top" align="center" colspan="2">Good<hr/></th>
</tr>
<tr>
<th valign="top" align="center"><italic>n</italic></th>
<th valign="top" align="center">&#x0025;</th>
<th valign="top" align="center"><italic>n</italic></th>
<th valign="top" align="center">&#x0025;</th>
<th valign="top" align="center"><italic>n</italic></th>
<th valign="top" align="center">&#x0025;</th>
<th valign="top" align="center"><italic>n</italic></th>
<th valign="top" align="center">&#x0025;</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" colspan="15"><bold>Position in the community</bold></td>
</tr>
<tr>
<td align="left">Chairman or staff of <italic>RT</italic> or <italic>RW</italic></td>
<td align="center">23</td>
<td align="center">60.0</td>
<td align="center">15</td>
<td align="center">39.5</td>
<td align="center">0.152</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">21</td>
<td align="center">55.0</td>
<td align="center">17</td>
<td align="center">45.0</td>
<td align="center">0.369</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Youth organization or comm. leaders</td>
<td align="center">11</td>
<td align="center">48.0</td>
<td align="center">12</td>
<td align="center">52.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;5.0</td>
<td align="center">9</td>
<td align="center">39.0</td>
<td align="center">14</td>
<td align="center">61.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;5.0</td>
</tr>
<tr>
<td align="left">Health cadres</td>
<td align="center">15</td>
<td align="center">38.0</td>
<td align="center">24</td>
<td align="center">61.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;6.0</td>
<td align="center">22</td>
<td align="center">56.0</td>
<td align="center">17</td>
<td align="center">44.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.4&#x2013;2.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Sex</bold></td>
</tr>
<tr>
<td align="left">Male</td>
<td align="center">28</td>
<td align="center">56.0</td>
<td align="center">22</td>
<td align="center">44.0</td>
<td align="center">0.161</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">27</td>
<td align="center">54.0</td>
<td align="center">23</td>
<td align="center">46.0</td>
<td align="center">0.689</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Female</td>
<td align="center">21</td>
<td align="center">42.0</td>
<td align="center">29</td>
<td align="center">58.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;4.0</td>
<td align="center">25</td>
<td align="center">50.0</td>
<td align="center">25</td>
<td align="center">50.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.5&#x2013;3.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Marital status</bold></td>
</tr>
<tr>
<td align="left">Single or widow or widower</td>
<td align="center">12</td>
<td align="center">71.0</td>
<td align="center">5</td>
<td align="center">29.0</td>
<td align="center">0.051</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">12</td>
<td align="center">71.0</td>
<td align="center">5</td>
<td align="center">30.0</td>
<td align="center">0.092</td>
<td align="center">1</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Married</td>
<td align="center">37</td>
<td align="center">45.0</td>
<td align="center">46</td>
<td align="center">55.0</td>
<td align="center">-</td>
<td align="center">3.0</td>
<td align="center">1.0&#x2013;9.0</td>
<td align="center">40</td>
<td align="center">48.0</td>
<td align="center">43</td>
<td align="center">52.0</td>
<td align="center">-</td>
<td align="center">3.0</td>
<td align="center">1.0&#x2013;8.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Age group (years old)</bold></td>
</tr>
<tr>
<td align="left">20&#x2013;40</td>
<td align="center">17</td>
<td align="center">61.0</td>
<td align="center">11</td>
<td align="center">39.0</td>
<td align="center">0.263</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">18</td>
<td align="center">64.0</td>
<td align="center">10</td>
<td align="center">36.0</td>
<td align="center">0.238</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">&#x003E;50</td>
<td align="center">18</td>
<td align="center">49.0</td>
<td align="center">19</td>
<td align="center">51.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;4.0</td>
<td align="center">19</td>
<td align="center">51.0</td>
<td align="center">18</td>
<td align="center">49.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;5.0</td>
</tr>
<tr>
<td align="left">41&#x2013;50</td>
<td align="center">14</td>
<td align="center">40.0</td>
<td align="center">21</td>
<td align="center">60.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;6.0</td>
<td align="center">15</td>
<td align="center">43.0</td>
<td align="center">20</td>
<td align="center">57.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;7.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Final education</bold></td>
</tr>
<tr>
<td align="left">Graduated from junior high school or below</td>
<td align="center">20</td>
<td align="center">61.0</td>
<td align="center">13</td>
<td align="center">39.0</td>
<td align="center">0.103</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">18</td>
<td align="center">54.0</td>
<td align="center">15</td>
<td align="center">45.0</td>
<td align="center">0.721</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Graduated from senior high school or above</td>
<td align="center">29</td>
<td align="center">43.0</td>
<td align="center">38</td>
<td align="center">57.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;5.0</td>
<td align="center">34</td>
<td align="center">51.0</td>
<td align="center">33</td>
<td align="center">49.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.5&#x2013;3.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Working status</bold></td>
</tr>
<tr>
<td align="left">Irregularly work</td>
<td align="center">24</td>
<td align="center">54.0</td>
<td align="center">20</td>
<td align="center">45.0</td>
<td align="center">0.462</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">27</td>
<td align="center">62.0</td>
<td align="center">17</td>
<td align="center">38.0</td>
<td align="center">0.189</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Regularly work</td>
<td align="center">17</td>
<td align="center">49.0</td>
<td align="center">18</td>
<td align="center">51.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.5&#x2013;3.0</td>
<td align="center">17</td>
<td align="center">49.0</td>
<td align="center">18</td>
<td align="center">51.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;4.0</td>
</tr>
<tr>
<td align="left">Staff of <italic>RW</italic> or <italic>RT</italic> or <italic>cadres</italic> or comm. leaders</td>
<td align="center">8</td>
<td align="center">38.0</td>
<td align="center">13</td>
<td align="center">62.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">0.7&#x2013;6.0</td>
<td align="center">8</td>
<td align="center">38.0</td>
<td align="center">13</td>
<td align="center">61.0</td>
<td align="center">-</td>
<td align="center">3.0</td>
<td align="center">1.0&#x2013;7.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Live in the same house with</bold></td>
</tr>
<tr>
<td align="left">Husband or wife or children or other family</td>
<td align="center">24</td>
<td align="center">58.0</td>
<td align="center">17</td>
<td align="center">41.0</td>
<td align="center">0.112</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">22</td>
<td align="center">54.0</td>
<td align="center">19</td>
<td align="center">46.0</td>
<td align="center">0.782</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Husband or wife or children or other family</td>
<td align="center">25</td>
<td align="center">42.0</td>
<td align="center">34</td>
<td align="center">58.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;4.0</td>
<td align="center">30</td>
<td align="center">51.0</td>
<td align="center">29</td>
<td align="center">49.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.5&#x2013;2.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Number of owned children (person)</bold></td>
</tr>
<tr>
<td align="left">&#x003E; 2</td>
<td align="center">21</td>
<td align="center">58.0</td>
<td align="center">15</td>
<td align="center">42.0</td>
<td align="center">0.161</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">15</td>
<td align="center">42.0</td>
<td align="center">21</td>
<td align="center">58.0</td>
<td align="center">0.121</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">1&#x2013;2</td>
<td align="center">28</td>
<td align="center">44.0</td>
<td align="center">36</td>
<td align="center">56.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;4.0</td>
<td align="center">37</td>
<td align="center">58.0</td>
<td align="center">27</td>
<td align="center">42.0</td>
<td align="center">-</td>
<td align="center">0.5</td>
<td align="center">0.2&#x2013;1.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Monthly income (IDR)</bold></td>
</tr>
<tr>
<td align="left">1-3 million</td>
<td align="center">31</td>
<td align="center">52.0</td>
<td align="center">29</td>
<td align="center">48.0</td>
<td align="center">0.514</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">34</td>
<td align="center">57.0</td>
<td align="center">26</td>
<td align="center">43.0</td>
<td align="center">0.253</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">&#x003E; 3 million</td>
<td align="center">18</td>
<td align="center">45.0</td>
<td align="center">22</td>
<td align="center">55.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">1.0&#x2013;3.0</td>
<td align="center">18</td>
<td align="center">45.0</td>
<td align="center">22</td>
<td align="center">55.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;4.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Knowledge on KSB</bold></td>
</tr>
<tr>
<td align="left">Poor</td>
<td align="center">27</td>
<td align="center">64.0</td>
<td align="center">15</td>
<td align="center">36.0</td>
<td align="center">0.009</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">32</td>
<td align="center">76.0</td>
<td align="center">10</td>
<td align="center">24.0</td>
<td align="center">0.001</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Good</td>
<td align="center">22</td>
<td align="center">38.0</td>
<td align="center">36</td>
<td align="center">62.1</td>
<td align="center">-</td>
<td align="center">3.0</td>
<td align="center">1.0&#x2013;7.0</td>
<td align="center">20</td>
<td align="center">34.0</td>
<td align="center">38</td>
<td align="center">65.0</td>
<td align="center">-</td>
<td align="center">6.0</td>
<td align="center">2.0&#x2013;15.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Knowledge on natural disaster and flood</bold></td>
</tr>
<tr>
<td align="left">Poor</td>
<td align="center">33</td>
<td align="center">60.0</td>
<td align="center">22</td>
<td align="center">40.0</td>
<td align="center">0.015</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">42</td>
<td align="center">76.0</td>
<td align="center">13</td>
<td align="center">24.0</td>
<td align="center">0.001</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Good</td>
<td align="center">16</td>
<td align="center">36.0</td>
<td align="center">29</td>
<td align="center">64.0</td>
<td align="center">-</td>
<td align="center">3.0</td>
<td align="center">1.0&#x2013;6.0</td>
<td align="center">10</td>
<td align="center">22.0</td>
<td align="center">35</td>
<td align="center">78.0</td>
<td align="center">-</td>
<td align="center">11.0</td>
<td align="center">4.0&#x2013;29.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Flood early warning system</bold></td>
</tr>
<tr>
<td align="left">Poor</td>
<td align="center">28</td>
<td align="center">72.0</td>
<td align="center">11</td>
<td align="center">28.0</td>
<td align="center">0.001</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">29</td>
<td align="center">74.0</td>
<td align="center">10</td>
<td align="center">26.0</td>
<td align="center">0.001</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Good</td>
<td align="center">21</td>
<td align="center">34.0</td>
<td align="center">40</td>
<td align="center">66.0</td>
<td align="center">-</td>
<td align="center">5.0</td>
<td align="center">2.0&#x2013;12.0</td>
<td align="center">23</td>
<td align="center">38.0</td>
<td align="center">38</td>
<td align="center">62.0</td>
<td align="center">-</td>
<td align="center">5.0</td>
<td align="center">2.0&#x2013;12.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Emergency response plan</bold></td>
</tr>
<tr>
<td align="left">Poor</td>
<td align="center">25</td>
<td align="center">51.0</td>
<td align="center">24</td>
<td align="center">49.0</td>
<td align="center">0.692</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">32</td>
<td align="center">65.0</td>
<td align="center">17</td>
<td align="center">35.0</td>
<td align="center">0.009</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Good</td>
<td align="center">24</td>
<td align="center">47.0</td>
<td align="center">27</td>
<td align="center">53.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.5&#x2013;3.0</td>
<td align="center">20</td>
<td align="center">39.0</td>
<td align="center">31</td>
<td align="center">61.0</td>
<td align="center">-</td>
<td align="center">3.0</td>
<td align="center">1.0&#x2013;7.0</td>
</tr>
</tbody>
</table>
</table-wrap>
<table-wrap id="T0008a">
<label>TABLE 8b</label>
<caption><p>Differences in flood management practices based on socio-demographic characteristics, <italic>Kampung Siaga Bencana</italic> knowledge, disaster knowledge, flood EWS, a demergency response plans for heat cadres and comm. leaders.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="top" align="left" rowspan="3">Variable</th>
<th valign="top" align="center" colspan="4">After flood<hr/></th>
<th valign="top" align="center" rowspan="3"><italic>p</italic></th>
<th valign="top" align="center" rowspan="3">OR</th>
<th valign="top" align="center" rowspan="3">95&#x0025; CI OR</th>
<th valign="top" align="center" colspan="4">Flood management<hr/></th>
<th valign="top" align="center" rowspan="3"><italic>p</italic></th>
<th valign="top" align="center" rowspan="3">OR</th>
<th valign="top" align="center" rowspan="3">95&#x0025; CI OR</th>
</tr>
<tr>
<th valign="top" align="center" colspan="2">Poor<hr/></th>
<th valign="top" align="center" colspan="2">Good<hr/></th>
<th valign="top" align="center" colspan="2">Poor<hr/></th>
<th valign="top" align="center" colspan="2">Good<hr/></th>
</tr>
<tr>
<th valign="top" align="center"><italic>n</italic></th>
<th valign="top" align="center">&#x0025;</th>
<th valign="top" align="center"><italic>n</italic></th>
<th valign="top" align="center">&#x0025;</th>
<th valign="top" align="center"><italic>n</italic></th>
<th valign="top" align="center">&#x0025;</th>
<th valign="top" align="center"><italic>n</italic></th>
<th valign="top" align="center">&#x0025;</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" colspan="15"><bold>Position in the community</bold></td>
</tr>
<tr>
<td align="left">Chairman or staff of <italic>RT</italic> or <italic>RW</italic></td>
<td align="center">24</td>
<td align="center">63.0</td>
<td align="center">14</td>
<td align="center">37.0</td>
<td align="center">0.611</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">22</td>
<td align="center">58.0</td>
<td align="center">16</td>
<td align="center">42.0</td>
<td align="center">0.325</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Youth organization or comm. leaders</td>
<td align="center">12</td>
<td align="center">52.0</td>
<td align="center">11</td>
<td align="center">48.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;4.0</td>
<td align="center">12</td>
<td align="center">52.0</td>
<td align="center">11</td>
<td align="center">48.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.4&#x2013;4.0</td>
</tr>
<tr>
<td align="left">Health cadres</td>
<td align="center">25</td>
<td align="center">64.0</td>
<td align="center">14</td>
<td align="center">36.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">1.0&#x2013;2.0</td>
<td align="center">16</td>
<td align="center">41.0</td>
<td align="center">23</td>
<td align="center">59.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;5.0</td>
</tr>
<tr>
<td align="left"><bold>Sex</bold></td>
<td align="left"></td>
<td align="left"></td>
<td align="left"></td>
<td align="left"></td>
<td align="left"></td>
<td align="left"></td>
<td align="center">-</td>
<td align="left"></td>
<td align="left"></td>
<td align="left"></td>
<td align="left"></td>
<td align="left"></td>
<td align="left"></td>
<td align="left"></td>
</tr>
<tr>
<td align="left">Male</td>
<td align="center">31</td>
<td align="center">62.0</td>
<td align="center">19</td>
<td align="center">38.0</td>
<td align="center">0.838</td>
<td align="center">1.0</td>
<td align="left"></td>
<td align="center">28</td>
<td align="center">56.0</td>
<td align="center">22</td>
<td align="center">44.0</td>
<td align="center">0.230</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Female</td>
<td align="center">30</td>
<td align="center">60.0</td>
<td align="center">20</td>
<td align="center">40.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.5&#x2013;2.0</td>
<td align="center">22</td>
<td align="center">44.0</td>
<td align="center">28</td>
<td align="center">56.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;4.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Marital status</bold></td>
</tr>
<tr>
<td align="left">Single or widow or widower</td>
<td align="center">14</td>
<td align="center">82.0</td>
<td align="center">3</td>
<td align="center">18.0</td>
<td align="center">0.048</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">12</td>
<td align="center">71.0</td>
<td align="center">5</td>
<td align="center">29.0</td>
<td align="center">0.062</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Married</td>
<td align="center">47</td>
<td align="center">53.0</td>
<td align="center">36</td>
<td align="center">43.0</td>
<td align="center">-</td>
<td align="center">4.0</td>
<td align="center">1.0&#x2013;13.0</td>
<td align="center">38</td>
<td align="center">46.0</td>
<td align="center">45</td>
<td align="center">54.0</td>
<td align="center">-</td>
<td align="center">3.0</td>
<td align="center">1.0&#x2013;9.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Age group (years old)</bold></td>
</tr>
<tr>
<td align="left">20&#x2013;40</td>
<td align="center">20</td>
<td align="center">71.0</td>
<td align="center">8</td>
<td align="center">29.0</td>
<td align="center">0.266</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">18</td>
<td align="center">64.0</td>
<td align="center">10</td>
<td align="center">36.0</td>
<td align="center">0.156</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">&#x003E;50</td>
<td align="center">23</td>
<td align="center">62.0</td>
<td align="center">14</td>
<td align="center">38.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">1.0.&#x2013;4.0</td>
<td align="center">18</td>
<td align="center">49.0</td>
<td align="center">19</td>
<td align="center">51.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;5.0</td>
</tr>
<tr>
<td align="left">41&#x2013;50</td>
<td align="center">18</td>
<td align="center">51.0</td>
<td align="center">17</td>
<td align="center">49.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;7.0</td>
<td align="center">14</td>
<td align="center">40.0</td>
<td align="center">21</td>
<td align="center">60.0</td>
<td align="center">-</td>
<td align="center">3.0</td>
<td align="center">1.0&#x2013;7.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Final education</bold></td>
</tr>
<tr>
<td align="left">Graduated from junior high school or below</td>
<td align="center">23</td>
<td align="center">70.0</td>
<td align="center">10</td>
<td align="center">30.0</td>
<td align="center">0.211</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">20</td>
<td align="center">61.0</td>
<td align="center">13</td>
<td align="center">39.0</td>
<td align="center">0.137</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Graduated from senior high school or above</td>
<td align="center">38</td>
<td align="center">57.0</td>
<td align="center">29</td>
<td align="center">43.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;4.0</td>
<td align="center">30</td>
<td align="center">45.0</td>
<td align="center">37</td>
<td align="center">55.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;4.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Working status</bold></td>
</tr>
<tr>
<td align="left">Irregularly work</td>
<td align="center">28</td>
<td align="center">64.0</td>
<td align="center">16</td>
<td align="center">36.0</td>
<td align="center">0.872</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">23</td>
<td align="center">52.0</td>
<td align="center">21</td>
<td align="center">48.0</td>
<td align="center">0.208</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Regularly work</td>
<td align="center">21</td>
<td align="center">60.0</td>
<td align="center">14</td>
<td align="center">40.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.5&#x2013;3.0</td>
<td align="center">20</td>
<td align="center">57.0</td>
<td align="center">15</td>
<td align="center">43.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.3&#x2013;2.0</td>
</tr>
<tr>
<td align="left">Staff of <italic>RW or RT or cadres or</italic> comm. leaders</td>
<td align="center">12</td>
<td align="center">57.0</td>
<td align="center">9</td>
<td align="center">43.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.5&#x2013;4.0</td>
<td align="center">7</td>
<td align="center">33.0</td>
<td align="center">14</td>
<td align="center">67.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;6.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Live in the same house with</bold></td>
</tr>
<tr>
<td align="left">Husband/wife/children/other family</td>
<td align="center">25</td>
<td align="center">61.0</td>
<td align="center">16</td>
<td align="center">39.0</td>
<td align="center">0.997</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">22</td>
<td align="center">54.0</td>
<td align="center">19</td>
<td align="center">46.0</td>
<td align="center">0.542</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Husband or wife or children or other family</td>
<td align="center">36</td>
<td align="center">61.0</td>
<td align="center">23</td>
<td align="center">39.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.4&#x2013;2.0</td>
<td align="center">28</td>
<td align="center">47.0</td>
<td align="center">31</td>
<td align="center">52.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">1.0&#x2013;3.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Number of owned children (person)</bold></td>
</tr>
<tr>
<td align="left">&#x003E; 2</td>
<td align="center">21</td>
<td align="center">58.0</td>
<td align="center">15</td>
<td align="center">42.0</td>
<td align="center">0.682</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">19</td>
<td align="center">53.0</td>
<td align="center">17</td>
<td align="center">47.0</td>
<td align="center">0.677</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">1&#x2013;2</td>
<td align="center">40</td>
<td align="center">62.0</td>
<td align="center">24</td>
<td align="center">37.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.4&#x2013;2.0</td>
<td align="center">31</td>
<td align="center">48.0</td>
<td align="center">33</td>
<td align="center">52.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.5&#x2013;3.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Monthly income (IDR)</bold></td>
</tr>
<tr>
<td align="left">1-3 million</td>
<td align="center">38</td>
<td align="center">63.0</td>
<td align="center">22</td>
<td align="center">37.0</td>
<td align="center">0.558</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">30</td>
<td align="center">50.0</td>
<td align="center">30</td>
<td align="center">50.0</td>
<td align="center">1.000</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">&#x003E; 3 million</td>
<td align="center">23</td>
<td align="center">57.0</td>
<td align="center">17</td>
<td align="center">42.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">1.0&#x2013;3.0</td>
<td align="center">20</td>
<td align="center">50.0</td>
<td align="center">20</td>
<td align="center">50.0</td>
<td align="center">-</td>
<td align="center">1.0</td>
<td align="center">0.5&#x2013;2.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Knowledge on KSB</bold></td>
</tr>
<tr>
<td align="left">Poor</td>
<td align="center">32</td>
<td align="center">76.0</td>
<td align="center">10</td>
<td align="center">24.0</td>
<td align="center">0.008</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">30</td>
<td align="center">71.0</td>
<td align="center">12</td>
<td align="center">29.0</td>
<td align="center">0.001</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Good</td>
<td align="center">29</td>
<td align="center">50.0</td>
<td align="center">29</td>
<td align="center">50.0</td>
<td align="center">-</td>
<td align="center">3.0</td>
<td align="center">1.0&#x2013;8.0</td>
<td align="center">20</td>
<td align="center">34.0</td>
<td align="center">38</td>
<td align="center">65.0</td>
<td align="center">-</td>
<td align="center">5.0</td>
<td align="center">2.0&#x2013;11.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Knowledge on natural disaster and flood</bold></td>
</tr>
<tr>
<td align="left">Poor</td>
<td align="center">45</td>
<td align="center">82.0</td>
<td align="center">10</td>
<td align="center">18.0</td>
<td align="center">0.001</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">38</td>
<td align="center">69.0</td>
<td align="center">17</td>
<td align="center">31.0</td>
<td align="center">0.001</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Good</td>
<td align="center">16</td>
<td align="center">36.0</td>
<td align="center">29</td>
<td align="center">64.0</td>
<td align="center">-</td>
<td align="center">8.0</td>
<td align="center">3.0&#x2013;20.0</td>
<td align="center">12</td>
<td align="center">27.0</td>
<td align="center">33</td>
<td align="center">73.0</td>
<td align="center">-</td>
<td align="center">6.0</td>
<td align="center">3.0&#x2013;15.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Flood early warning system</bold></td>
</tr>
<tr>
<td align="left">Poor</td>
<td align="center">31</td>
<td align="center">79.0</td>
<td align="center">8</td>
<td align="center">20.0</td>
<td align="center">0.002</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">26</td>
<td align="center">67.0</td>
<td align="center">13</td>
<td align="center">33.0</td>
<td align="center">0.008</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Good</td>
<td align="center">30</td>
<td align="center">49.0</td>
<td align="center">31</td>
<td align="center">51.0</td>
<td align="center">-</td>
<td align="center">4.0</td>
<td align="center">2.0&#x2013;10.0</td>
<td align="center">24</td>
<td align="center">39.0</td>
<td align="center">37</td>
<td align="center">61.0</td>
<td align="center">-</td>
<td align="center">3.0</td>
<td align="center">1.0&#x2013;7.0</td>
</tr>
<tr>
<td align="left" colspan="15"><bold>Emergency response plan</bold></td>
</tr>
<tr>
<td align="left">Poor</td>
<td align="center">34</td>
<td align="center">69.0</td>
<td align="center">15</td>
<td align="center">31.0</td>
<td align="center">0.092</td>
<td align="center">1.0</td>
<td align="center">-</td>
<td align="center">29</td>
<td align="center">59.0</td>
<td align="center">20</td>
<td align="center">41.0</td>
<td align="center">0.072</td>
<td align="center">1.0</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Good</td>
<td align="center">27</td>
<td align="center">53.9</td>
<td align="center">24</td>
<td align="center">47.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;5.0</td>
<td align="center">21</td>
<td align="center">41.0</td>
<td align="center">30</td>
<td align="center">59.0</td>
<td align="center">-</td>
<td align="center">2.0</td>
<td align="center">1.0&#x2013;5.0</td>
</tr>
</tbody>
</table>
</table-wrap>
<table-wrap id="T0009">
<label>TABLE 9</label>
<caption><p>Multivariate analysis of the dominant variable of flood management practices among health cadres and community leaders.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="top" align="left" rowspan="2">Variable</th>
<th valign="top" align="center" rowspan="2">Logistic coefficients (B)</th>
<th valign="top" align="center" rowspan="2">Standard error (s.e.)</th>
<th valign="top" align="center" rowspan="2">Wald</th>
<th valign="top" align="center" rowspan="2">db</th>
<th valign="top" align="center" rowspan="2"><italic>p</italic></th>
<th valign="top" align="center" rowspan="2">OR</th>
<th valign="top" align="center" colspan="2">95&#x0025; CI OR<hr/></th>
</tr>
<tr>
<th valign="top" align="center">BB</th>
<th valign="top" align="center">BA</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" colspan="9"><bold>Before flood</bold></td>
</tr>
<tr>
<td align="left">Position at community</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">6.62</td>
<td align="center">2</td>
<td align="center">0.037</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">Position at community (youth organization, community leaders, vs. staff of RW/RT)</td>
<td align="center">0.74</td>
<td align="center">0.65</td>
<td align="center">1.32</td>
<td align="center">1</td>
<td align="center">0.251</td>
<td align="center">2.10</td>
<td align="center">0.59</td>
<td align="center">7.46</td>
</tr>
<tr>
<td align="left">Position at community (health cadre vs. staff of RW/RT)</td>
<td align="center">1.43</td>
<td align="center">0.56</td>
<td align="center">6.61</td>
<td align="center">1</td>
<td align="center">0.010</td>
<td align="center">4.18</td>
<td align="center">1.40</td>
<td align="center">12.43</td>
</tr>
<tr>
<td align="left">Marital status (married vs. single or widow or widower)</td>
<td align="center">1.35</td>
<td align="center">0.69</td>
<td align="center">3.86</td>
<td align="center">1</td>
<td align="center">0.050</td>
<td align="center">3.86</td>
<td align="center">1.00</td>
<td align="center">14.85</td>
</tr>
<tr>
<td align="left">Final education (graduated from senior high school or above vs. graduated from junior high school or below)</td>
<td align="center">1.38</td>
<td align="center">0.54</td>
<td align="center">6.48</td>
<td align="center">1</td>
<td align="center">0.011</td>
<td align="center">3.98</td>
<td align="center">1.37</td>
<td align="center">11.52</td>
</tr>
<tr>
<td align="left">Flood early warning system (good vs. poor)</td>
<td align="center">1.84</td>
<td align="center">0.51</td>
<td align="center">13.10</td>
<td align="center">1</td>
<td align="center">0.000</td>
<td align="center">6.33</td>
<td align="center">2.33</td>
<td align="center">17.18</td>
</tr>
<tr>
<td align="left">Constant</td>
<td align="center">&#x2212;3.90</td>
<td align="center">1.02</td>
<td align="center">14.58</td>
<td align="center">1</td>
<td align="center">0.000</td>
<td align="center">0.02</td>
<td align="center">-</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left" colspan="9"><italic>-2LL = 110.0, Cox and Snell R Square = 0.25, Nagelkerke R Square = 0.33, Omnibus Test Model = 28.6, p = 0.001</italic></td>
</tr>
<tr>
<td align="left" colspan="9"><bold>During flood</bold></td>
</tr>
<tr>
<td align="left">Knowledge of health cadres or community leaders on KSB (good vs. poor)</td>
<td align="center">1.42</td>
<td align="center">0.53</td>
<td align="center">7.02</td>
<td align="center">1</td>
<td align="center">0.008</td>
<td align="center">4.12</td>
<td align="center">1.45</td>
<td align="center">11.74</td>
</tr>
<tr>
<td align="left">Knowledge of health cadres or community leaders on natural disaster and flood (good vs. poor)</td>
<td align="center">2.10</td>
<td align="center">0.51</td>
<td align="center">16.86</td>
<td align="center">1</td>
<td align="center">0.000</td>
<td align="center">8.15</td>
<td align="center">2.99</td>
<td align="center">22.19</td>
</tr>
<tr>
<td align="left">Emergency response plan (good vs. poor)</td>
<td align="center">1.05</td>
<td align="center">0.51</td>
<td align="center">4.16</td>
<td align="center">1</td>
<td align="center">0.041</td>
<td align="center">2.86</td>
<td align="center">1.04</td>
<td align="center">7.83</td>
</tr>
<tr>
<td align="left">Constant</td>
<td align="center">&#x2212;2.45</td>
<td align="center">0.58</td>
<td align="center">17.60</td>
<td align="center">1</td>
<td align="center">0.000</td>
<td align="center">0.09</td>
<td align="center">-</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left" colspan="9"><italic>-2LL = 96.2. Cox and Snell R Square = 0.36, Nagelkerke R Square = 0.46, Omnibus Test Model = 42.2, p = 0.001</italic></td>
</tr>
<tr>
<td align="left" colspan="9"><bold>After flood</bold></td>
</tr>
<tr>
<td align="left">Knowledge of health cadres or community leaders on natural disaster and flood (good vs. poor)</td>
<td align="center">2.10</td>
<td align="center">0.47</td>
<td align="center">20.09</td>
<td align="center">1</td>
<td align="center">0.000</td>
<td align="center">8.16</td>
<td align="center">3.26</td>
<td align="center">20.42</td>
</tr>
<tr>
<td align="left">Constant</td>
<td align="center">&#x2212;1.50</td>
<td align="center">0.35</td>
<td align="center">18.51</td>
<td align="center">1</td>
<td align="center">0.000</td>
<td align="center">0.22</td>
<td align="center">-</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left" colspan="9"><italic>-2LL = 110.7. Cox and Snell R Square = 0.21, Nagelkerke R Square = 0.28, Omnibus Test Model = 23.0, p = 0.001</italic></td>
</tr>
<tr>
<td align="left" colspan="9"><bold>Flood management</bold></td>
</tr>
<tr>
<td align="left">Knowledge of health cadres or community leaders on KSB (good vs. poor)</td>
<td align="center">1.16</td>
<td align="center">0.47</td>
<td align="center">5.97</td>
<td align="center">1</td>
<td align="center">0.015</td>
<td align="center">3.18</td>
<td align="center">1.26</td>
<td align="center">8.03</td>
</tr>
<tr>
<td align="left">Knowledge of health cadres or community leaders on natural disaster and flood (good vs. poor)</td>
<td align="center">1.51</td>
<td align="center">0.47</td>
<td align="center">10.39</td>
<td align="center">1</td>
<td align="center">0.001</td>
<td align="center">4.52</td>
<td align="center">1.81</td>
<td align="center">11.30</td>
</tr>
<tr>
<td align="left">Constant</td>
<td align="center">&#x2212;1.35</td>
<td align="center">0.39</td>
<td align="center">11.94</td>
<td align="center">1</td>
<td align="center">0.001</td>
<td align="center">0.26</td>
<td align="center">-</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left" colspan="9"><italic>-2LL = 114.2, Cox and Snell R Square = 0.22, Nagelkerke R Square = 0.29, Omnibus Test Model = 24.5, p = 0.001</italic></td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p>CI, confidence interval; OR, odd ratio.</p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
</sec>
<sec id="s0012">
<title>Discussion</title>
<p>Families with disaster-vulnerable groups had a low level of knowledge about KSB, inadequate flood warning system and emergency response plan parameters, and inadequate flood management practices compared to <italic>posyandu</italic> cadres and community leaders; yet, they need better family support. Health cadres and community leaders are community groups who are tasked with supporting the health programs at the <italic>RT</italic> and <italic>RW</italic> levels. A community leader is a person who is a role model for the community in a particular region. Cadres are agents of change in health and nutrition programs at the <italic>posyandu</italic> for under-five children and <italic>posbindu</italic> for older people (Yulidar et al. <xref ref-type="bibr" rid="CIT0037">2020</xref>). Health cadres and community leaders are crucial in improving the preparedness, emergency response, and post-flood practices of communities living in flood-prone areas to enable them to act as quickly and effectively as possible. Therefore, these two groups must know more about KSB, natural hazards, and floods than the general population. All locations in this study already have KSB established by the Ministry of Social Affairs of the Republic of Indonesia based on the Regulation of the Minister of Social Affairs of the Republic of Indonesia No. 128 of 2011 (Audit Board of the Republic of Indonesia (BPK) <xref ref-type="bibr" rid="CIT0003">2011</xref>). The purpose of establishing KSB is to create public understanding and awareness of disaster hazards; establish a community-based disaster preparedness network and strengthen social interaction of community groups; organize trained disaster preparedness communities; ensure the implementation of sustainable community-based disaster preparedness; and optimize potentials and resources for disaster management. Disaster Alert Villages are established in disaster-prone areas, including those prone to floods, and have a high level of community participation. Almost all respondents from the cadre and community leader group joined the KSB so that they know KSB, know of natural hazards and floods, flood early warning systems, and have good emergency response plans (BPK <xref ref-type="bibr" rid="CIT0003">2011</xref>).</p>
<p>Family support in flood management practices is already good in terms of providing information on equipment and actions that need to be taken before the event of a flood, reminding older people constantly to activate their communication devices to make it easier for them to contact others during emergency conditions, and preparing vehicles to evacuate family groups who are vulnerable to flood to a safe location in an emergency. Family support is an attitude, an act of acceptance towards family groups, in the form of giving informational, assessment, instrumental, and emotional support. There are four types of family support: informational, physiological, instrumental, and emotional support (Friedman <xref ref-type="bibr" rid="CIT0011">2010</xref>). Informational, instrumental, and emotional supports are provided in this study. This is in line with earlier studies conducted on the effect of family support on older people&#x2019;s preparedness (Djaafar et al. <xref ref-type="bibr" rid="CIT0008">2021</xref>; Nurhidayati <xref ref-type="bibr" rid="CIT0025">2018</xref>). Families and groups vulnerable to flood are the main stakeholders in disaster management.</p>
<p>Early warning systems are crucial in disaster management, consisting of knowledge of risk, monitoring and warning services, dissemination and communication, and countermeasure capabilities. Flood early warning systems are the most critical variable that determines the practice of families with groups vulnerable to floods, such as children, pregnant women, nursing mothers, persons with disabilities, and older people, before and during flood emergency response. Respondents use various flood early warning systems, including WhatsApp Group (WAG), mosque/<italic>musholla</italic> speaker announcements, sirens from village offices, and flood detection early warning system (DEWS) tools (<xref ref-type="fig" rid="F0006">Figure 6</xref>). The DEWS tool is a remote loudspeaker/speaker in the form of a pole with loudspeakers on all four sides pointing in various directions to announce information to the community in flood-prone areas. This tool is activated when the river floodgates begin to enter alert level 3, alert level 2, and alert level 1. The BPBD of DKI Jakarta Province activates the DEWS tool directly using VHF digital radio technology (Aji <xref ref-type="bibr" rid="CIT0001">2020</xref>; Wibowo <xref ref-type="bibr" rid="CIT0035">2023</xref>). In Rawa Buaya Village, local people have developed a simple way of early detection of floods through marks on concrete pillars of the railway bridge. Green, yellow, and red marks are water level markers, with yellow indicating alert and red indicating danger or flood alert. Early warning systems are a crucial component of disaster management. They encompass a range of activities, including risk assessment, monitoring and warning services, communication and dissemination, and countermeasure capabilities (International Strategy for Disaster Reduction [ISDR] <xref ref-type="bibr" rid="CIT0014">2006</xref>).</p>
<fig id="F0006">
<label>FIGURE 6</label>
<caption><p>Disaster early warning system (DEWS) for a flood at Rawa Buaya Urban Village.</p></caption>
<graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="JAMBA-16-1645-g006.tif"/>
</fig>
<p>Early warning of the flood is a significant factor in reducing flood risk because the community can respond accordingly to conduct rescues, avoid casualties, and reduce the impact of the disaster. Early flood warnings help warn residents of the potential for floods through communication devices or by directly using sirens and warning lights so that rescue measures can be taken immediately. A complete, adequate, and community-centered flood early warning requires four elements of knowledge of disaster risk, monitoring, and warning services through the establishment of hazard monitoring and early warning services, dissemination and communication of risk and early warning information, and community capabilities (Sagay &#x0026; Pangemanan <xref ref-type="bibr" rid="CIT0029">2023</xref>). The findings of this study demonstrated that the majority of respondents when they hear the sound of sirens or <italic>kentongan</italic> (a traditional slit drum usually used as a communication tool in the village) signalling the possibility of flood, will immediately evacuate to a safe location. In addition, respondents immediately helped the flood-vulnerable groups reach safe meeting points.</p>
<p>Knowledge of natural hazards and floods is the primary determinant of flood management practices by families with groups vulnerable to flood. The same applies to the <italic>posyandu cadres</italic> and community leaders who participated in this study. Experience provides knowledge about floods hitting the area and will affect the attitude and awareness of the community to be ready to anticipate floods. The community&#x2019;s knowledge of disasters can affect their awareness and preparedness when flooding strikes flood-prone areas (Kim &#x0026; Kim <xref ref-type="bibr" rid="CIT0017">2022</xref>; Noor et al. <xref ref-type="bibr" rid="CIT0024">2022</xref>; Oktari et al., <xref ref-type="bibr" rid="CIT0026">2020</xref>; Shanableh et al. <xref ref-type="bibr" rid="CIT0031">2023</xref>). This study&#x2019;s findings align with several studies conducted on community knowledge and flood preparedness (Nekada, Herawati &#x0026; Rahil <xref ref-type="bibr" rid="CIT0023">2023</xref>; Yatnikasari, Asnan &#x0026; Agustuna 2021). A community&#x2019;s knowledge about disasters will affect household attitudes and awareness to be ready and prepared to anticipate disasters to minimize the follow-up impacts of disasters (LIPI-UNESCO/ISDR <xref ref-type="bibr" rid="CIT0020">2006</xref>). The emergency response plan also plays a role in flood management practices as shown in this study. Emergency response plans include plans to respond to emergencies, evacuate, provide first aid, rescue, safety and security, fulfilment of basic needs, equipment and tools, essential facilities, and simulation or exercises (Firmansyah <xref ref-type="bibr" rid="CIT0010">2014</xref>; Taryana, Mahmudi &#x0026; Bekti <xref ref-type="bibr" rid="CIT0032">2022</xref>). This study&#x2019;s findings are supported by a survey carried out in Pacitan District stating that an emergency response plan is a learning process to improve the community&#x2019;s ability to deal with disasters (Faturahman <xref ref-type="bibr" rid="CIT0009">2018</xref>).</p>
<p>A flood preparedness framework is needed to assess the extent of community preparedness in an area facing natural hazards. The first parameter is knowledge, which is the main factor and is critical to readiness, including the practice of being ready and prepared before a flood, especially for people living in flood-prone areas. The second parameter is an emergency response plan linked to self-evacuation to safe meeting points, evacuation routes, first aid, and self-rescue during flooding. Flood early warning systems include warning signs and distribution of information about the occurrence of disasters. The community can significantly take appropriate actions through disaster warnings to reduce casualties. For this reason, training and simulation are needed to familiarize people with what to do when hearing warnings and where and how to save themselves within a specific time frame according to where the people are during the disaster warning. Human resource mobilization is performed through family and community participation in flood preparedness training, and first aid training, among others (Deni <xref ref-type="bibr" rid="CIT0007">2008</xref>).</p>
<p>Health cadres and community leaders already have good flood management practices before, during, and after floods. This condition is based on sound knowledge of natural hazards and floods and KSB, along with the presence of flood early warning systems and emergency response plans. Based on these three disaster preparedness parameters, it is necessary to establish flood KSBs in the five study locations that have already become Disaster Alert Villages. The strengthening of KSB is facilitated by family support for the family groups who belong to the flood-vulnerable groups, establishing a Disaster Alert Village, and the willingness and readiness of health cadres and community leaders to become KSB. For families with groups vulnerable to flood, efforts need to be made to increase preparedness, including providing disaster knowledge education on flood mitigation and preparedness strategies, emergency response plans, and resource mobilization. To support KSB skills, it is necessary to do simulations or exercises and management training on floods and other disasters with BPBD DKI Jakarta Province, the Ministry of Social Affairs, non-governmental organizations (NGOs), and related parties.</p>
<p>The study has some limitations. Firstly, the cross-sectional design of this study cannot assess the causal and influence relationships between independent variables, such as socio-demographic characteristics, family support, disaster knowledge, flood early warning system, and emergency response plan, with the dependent variable of flood management practices. Secondly, the flood-vulnerable groups studied are not specific to one type of vulnerable group, such as children, pregnant women, nursing mothers, older people, and persons with disabilities. As a result, the identified flood management practices (before, during, and after) are general. Thirdly, the study locations were chosen by purposive sampling based on data from BPBD DKI Jakarta province that cannot be generalized to the DKI Jakarta Provincial level. Fourthly, this study uses a quantitative approach with quantitative methods. It is necessary to use a mixed quantitative and qualitative method to explore why and how both types of respondents (families and prospective KSB) perform good flood management practices.</p>
</sec>
<sec id="s0013">
<title>Conclusion</title>
<p>Generally, the four community preparedness parameters, namely disaster knowledge, emergency response plan, flood early warning system, and human resource mobilization still need to be improved. Only family support is found to be good in this respondent group. The KSB candidates, including health cadres and community leaders, have four suitable preparedness parameters, especially in disaster knowledge, which plays a significant role in flood management practices. Disaster education from KSB in simulations, exercise, and training needs to be provided more intensively to families with groups vulnerable to flood to improve preparedness parameters. The role and tasks of the Disaster Preparedness Village need to be intensified to strengthen the role of KSB as an agent of change to improve community preparedness in flood management.</p>
</sec>
</body>
<back>
<ack>
<title>Acknowledgements</title>
<sec id="s20014" sec-type="COI-statement">
<title>Competing interests</title>
<p>The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.</p>
</sec>
<sec id="s20015">
<title>Authors&#x2019; contributions</title>
<p>F.F. contributed to study preparation; data collection; analysis the results; writing the draft article, and finishing the article. R.P. contributed to writing the draft article. M.B. reviewed the draft and the final article.</p>
</sec>
<sec id="s20016" sec-type="data-availability">
<title>Data availability</title>
<p>Data sharing does not apply to this article as no new data were created or analyzed in this study.</p>
</sec>
<sec id="s20017">
<title>Disclaimer</title>
<p>The views and opinions expressed in this article are those of the authors and are the product of professional research. They do not necessarily reflect the official policy or position of any affiliated institution, funder, agency, or that of the publisher. The authors are responsible for this article&#x2019;s results, findings, and content.</p>
</sec>
</ack>
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<fn><p><bold>How to cite this article:</bold> Fatmah, F., Purwana, R. &#x0026; Bisri, M.F., 2024, &#x2018;Role of <italic>Kader Siaga Bencana</italic> in the flood management of selected <italic>Kampung Siaga Bencana</italic>&#x2019;, <italic>J&#x00E0;mb&#x00E1;: Journal of Disaster Risk Studies</italic> 16(1), a1645. <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.4102/jamba.v16i1.1645">https://doi.org/10.4102/jamba.v16i1.1645</ext-link></p></fn>
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