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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">Oalib</journal-id>
      <journal-title-group>
        <journal-title>Open Access Library Journal</journal-title>
      </journal-title-group>
      <issn pub-type="epub">2333-9721</issn>
      <issn pub-type="ppub">2333-9705</issn>
      <publisher>
        <publisher-name>Scientific Research Publishing</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.4236/oalib.1115627</article-id>
      <article-id pub-id-type="publisher-id">Oalib-153152</article-id>
      <article-categories>
        <subj-group>
          <subject>Article</subject>
        </subj-group>
        <subj-group>
          <subject>Biomedical</subject>
          <subject>Life Sciences</subject>
          <subject>Business</subject>
          <subject>Economics</subject>
          <subject>Chemistry</subject>
          <subject>Materials Science</subject>
          <subject>Computer Science</subject>
          <subject>Communications</subject>
          <subject>Earth</subject>
          <subject>Environmental Sciences</subject>
          <subject>Engineering</subject>
          <subject>Medicine</subject>
          <subject>Healthcare</subject>
          <subject>Physics</subject>
          <subject>Mathematics</subject>
          <subject>Social Sciences</subject>
          <subject>Humanities</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Socio-Demographic, Environmental and Nutritional Determinants of Acute Respiratory Infections among School-Aged Children in the Democratic Republic of Congo: A Cross-Sectional Analytical Study</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name name-style="western">
            <surname>Abiba</surname>
            <given-names>Chancelle Nasoro</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author" corresp="yes">
          <contrib-id contrib-id-type="orcid">0009-0000-8804-4478</contrib-id>
          <name name-style="western">
            <surname>Kandolo</surname>
            <given-names>Simon Ilunga</given-names>
          </name>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <name name-style="western">
            <surname>Mwamba</surname>
            <given-names>Guillaume Ngoie</given-names>
          </name>
          <xref ref-type="aff" rid="aff3">3</xref>
        </contrib>
        <contrib contrib-type="author">
          <name name-style="western">
            <surname>Maloba</surname>
            <given-names>Georges Banza</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name name-style="western">
            <surname>Nzaji</surname>
            <given-names>Michel Kabamba</given-names>
          </name>
          <xref ref-type="aff" rid="aff4">4</xref>
        </contrib>
        <contrib contrib-type="author">
          <name name-style="western">
            <surname>Kimpanga</surname>
            <given-names>Celestin Muleka</given-names>
          </name>
          <xref ref-type="aff" rid="aff5">5</xref>
        </contrib>
        <contrib contrib-type="author">
          <name name-style="western">
            <surname>Numbi</surname>
            <given-names>Oscar Luboya</given-names>
          </name>
          <xref ref-type="aff" rid="aff2">2</xref>
          <xref ref-type="aff" rid="aff6">6</xref>
        </contrib>
      </contrib-group>
      <aff id="aff1"><label>1</label> School of Public Health, University of Kamina, Kamina, Democratic Republic of Congo </aff>
      <aff id="aff2"><label>2</label> School of Public Health, University of Lubumbashi, Lubumbashi, Democratic Republic of Congo </aff>
      <aff id="aff3"><label>3</label> McKinsey Consulting Corporation/Gates Foundation, Kinshasa, Democratic Republic of Congo </aff>
      <aff id="aff4"><label>4</label> Faculty of Medicine, University of Kamina, Kamina, Democratic Republic of Congo </aff>
      <aff id="aff5"><label>5</label> Department of Biochemistry, Higher Pedagogical Institute of Lubumbashi, Lubumbashi, Democratic Republic of Congo </aff>
      <aff id="aff6"><label>6</label> Department of Public Health and Paediatrics, Faculty of Medicine, University of Lubumbashi, Lubumbashi, Democratic Republic of Congo </aff>
      <author-notes>
        <fn fn-type="conflict" id="fn-conflict">
          <p>The authors declare no conflicts of interest.</p>
        </fn>
      </author-notes>
      <pub-date pub-type="epub">
        <day>03</day>
        <month>08</month>
        <year>2026</year>
      </pub-date>
      <pub-date pub-type="collection">
        <month>08</month>
        <year>2026</year>
      </pub-date>
      <volume>13</volume>
      <issue>08</issue>
      <fpage>1</fpage>
      <lpage>11</lpage>
      <history>
        <date date-type="received">
          <day>15</day>
          <month>06</month>
          <year>2026</year>
        </date>
        <date date-type="accepted">
          <day>10</day>
          <month>08</month>
          <year>2026</year>
        </date>
        <date date-type="published">
          <day>13</day>
          <month>08</month>
          <year>2026</year>
        </date>
      </history>
      <permissions>
        <copyright-statement>© 2026 by the authors and Scientific Research Publishing Inc.</copyright-statement>
        <copyright-year>2026</copyright-year>
        <license license-type="open-access">
          <license-p> This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link> ). </license-p>
        </license>
      </permissions>
      <self-uri content-type="doi" xlink:href="https://doi.org/10.4236/oalib.1115627">https://doi.org/10.4236/oalib.1115627</self-uri>
      <abstract>
        <p><bold>Introduction:</bold> Acute respiratory infections (ARIs) remain a major cause of morbidity in children, particularly in disadvantaged communities where living conditions and access to healthcare are precarious. In the Kamina Health Zone, the factors associated with these infections remain poorly documented. This study aimed to identify the determinants of ARIs in children aged 0 to 14 years. <bold>Methods:</bold> A community-based cross-sectional analytical study was conducted with 384 children aged 0 to 14 years. Data were collected using a structured questionnaire administered via KoBoCollect. ARIs were defined as the presence of a cough, with or without respiratory distress, during the two weeks preceding the survey. Associated factors were investigated using multivariate logistic regression. <bold>Results:</bold> The prevalence of ARIs was 88%. The absence or delay of seeking healthcare was the main factor associated with ARIs. Consuming street food significantly increased the risk of acute respiratory infections (ARIs) (aOR = 3.12). Overcrowded households were also associated with ARIs (aOR = 1.88; 95% CI: 1.05 - 3.36). Carrying children while lighting fires and exposure to household chemicals were also significantly associated with the occurrence of ARIs. <bold>Conclusion:</bold> ARIs in children in Kamina result from determinants related to living conditions, domestic exposures, and access to healthcare. Their prevention requires an integrated approach based on early access to care, reducing harmful exposures within households, and improving living conditions.</p>
      </abstract>
      <kwd-group kwd-group-type="author-generated" xml:lang="en">
        <kwd>Acute Respiratory Infections</kwd>
        <kwd>Children</kwd>
        <kwd>Determinants</kwd>
        <kwd>Home Environment</kwd>
        <kwd>Access to Healthcare</kwd>
        <kwd>Kamina Health Zone</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec1">
      <title>1. Introduction</title>
      <p>Acute respiratory infections (ARIs) remain a leading cause of morbidity and mortality in children, particularly in low- and middle-income countries (LMICs) [<xref ref-type="bibr" rid="B1">1</xref>]. Despite progress in reducing infant mortality, they continue to account for a significant proportion of preventable consultations, hospitalizations, and deaths [<xref ref-type="bibr" rid="B2">2</xref>].</p>
      <p>Sub-Saharan Africa bears a large part of this burden, driven by structural factors such as poverty, inadequate housing, and limited access to clean energy sources [<xref ref-type="bibr" rid="B3">3</xref>]. The use of biomass fuels exposes many children daily to harmful particles and toxic gases, constituting a major respiratory risk factor [<xref ref-type="bibr" rid="B4">4</xref>]. This is compounded by socioeconomic constraints, including low household income, low parental education levels, and limited access to healthcare, which contribute to delays in seeking treatment, limit preventive practices, and worsen disease progression [<xref ref-type="bibr" rid="B5">5</xref>]. Overcrowded households also contribute to the transmission of respiratory pathogens [<xref ref-type="bibr" rid="B6">6</xref>].</p>
      <p>Nutritional status also influences vulnerability to infections. Malnutrition and micronutrient deficiencies impair immune defenses and increase the risk of severe respiratory infections [<xref ref-type="bibr" rid="B7">7</xref>]. While most research focuses on children under five, school-aged children remain exposed to similar risks related to communal living and environmental exposures [<xref ref-type="bibr" rid="B8">8</xref>]. However, data on this population remain limited in the Democratic Republic of Congo.</p>
      <p>Ecosocial and syndemic approaches emphasize that the risk of acute respiratory infections (ARIs) results from the interaction of biological, environmental, and socioeconomic determinants rather than from a single factor [<xref ref-type="bibr" rid="B9">9</xref>]. In the DRC, rapid urbanization, the continued use of biomass, and high population density maintain conditions conducive to the transmission of respiratory diseases [<xref ref-type="bibr" rid="B10">10</xref>].</p>
      <p>In this context, this study aimed to assess the independent and combined effects of sociodemographic, environmental, and nutritional determinants of ARIs in the Kamina Health Zone, in order to better understand risk factors and guide integrated public health interventions.</p>
    </sec>
    <sec id="sec2">
      <title>2. Methods</title>
      <sec id="sec2dot1">
        <title>2.1. Study Design</title>
        <p>A community-based cross-sectional analytical study was conducted among households in the Kamina Health Zone to assess the determinants of acute respiratory infections (ARIs) in children aged 0 - 14 years.</p>
      </sec>
      <sec id="sec2dot2">
        <title>2.2. Study Framework</title>
        <p>The study was conducted in the Kamina Health Zone, in Haut-Lomami province, in the southeast of the Democratic Republic of Congo. This urban and rural area, with over 300,000 inhabitants, has unequal access to healthcare and a fragile socio-economic context. The frequent use of wood and charcoal for cooking, often in poorly ventilated homes, exposes children to indoor air pollution and could increase the risk of respiratory infections.</p>
      </sec>
      <sec id="sec2dot3">
        <title>2.3. Study Population and Sampling and Sample Size</title>
        <p>The study population consisted of children aged 0 to 14 years residing in selected households within the Kamina Health Zone. This selection aimed to explore the determinants of acute respiratory infections at different stages of childhood, including young children, who are particularly vulnerable, as well as school-aged children, who remain understudied despite their persistent exposure to various risk factors.</p>
        <p>A multi-stage sampling approach was used: health areas were first randomly selected, and then households were recruited through systematic sampling within each selected area. When a household had several eligible children, only one child was randomly selected to limit bias related to the pooling of observations.</p>
        <p>The sample size was calculated using a single population proportion formula, assuming an expected ARI prevalence of 50% to maximize sample size in the absence of precise local estimates. A 95% confidence level and a margin of error of 5% were applied.</p>
        <p>The initial sample size was calculated as follows:</p>
        <p><italic>n</italic> = (<italic>Z</italic><sup>2</sup> × <italic>p</italic> × (1 − <italic>p</italic>))/<italic>d</italic><sup>2</sup></p>
        <p>where:</p>
        <p><italic>Z</italic> = 1.96 (standard normal value for 95% confidence level);</p>
        <p><italic>p</italic> = 0.5 (assumed prevalence);</p>
        <p><italic>d</italic> = 0.05 (margin of error);</p>
        <p><italic>p</italic> = 0.5 (assumed prevalence);</p>
        <p><italic>d</italic> = 0.05 (margin of error).</p>
        <p>The final size retained was 384 participants.</p>
        <p><bold>Data collection</bold></p>
        <p>Data were collected from parents or guardians using a structured questionnaire, developed based on the literature and pre-tested for its suitability to the local context. Administered door-to-door by trained interviewers via the KoBoCollect application, the interviews focused on the characteristics of the children and households, living conditions, environmental exposures, health habits, and healthcare utilization. Supervision and control mechanisms were implemented to ensure data quality and confidentiality.</p>
      </sec>
    </sec>
    <sec id="sec3">
      <title>3. Resultats</title>
      <p><bold>Table 1.</bold> Sociodemographic characteristics and nutritional profile of the children studied (N = 384).</p>
      <table-wrap id="tbl1">
        <label>Table 1</label>
        <table>
          <tbody>
            <tr>
              <td>
                <bold>Variables</bold>
              </td>
              <td>
                <bold>Modalities</bold>
              </td>
              <td>
                <bold>n (%)</bold>
              </td>
            </tr>
            <tr>
              <td>
                <bold>Sex</bold>
              </td>
              <td>Male</td>
              <td>204 (53.1)</td>
            </tr>
            <tr>
              <td>
              </td>
              <td>Female</td>
              <td>180 (46.9)</td>
            </tr>
            <tr>
              <td>
                <bold>Age (Years)</bold>
              </td>
              <td>Means ±SD</td>
              <td>8.2 ± 3.9</td>
            </tr>
            <tr>
              <td>
              </td>
              <td>&lt;5 years</td>
              <td>112 (29.2)</td>
            </tr>
            <tr>
              <td>
              </td>
              <td>5 - 9 Years</td>
              <td>156 (40.6)</td>
            </tr>
            <tr>
              <td>
              </td>
              <td>≥10 years</td>
              <td>116 (30.2)</td>
            </tr>
            <tr>
              <td>
                <bold>Socio-economic status</bold>
              </td>
              <td>Low</td>
              <td>248 (64.6)</td>
            </tr>
            <tr>
              <td>
              </td>
              <td>Medium/High</td>
              <td>136 (35.4)</td>
            </tr>
            <tr>
              <td>
                <bold>BMI</bold>
              </td>
              <td>Malnutrition</td>
              <td>10 (2.6)</td>
            </tr>
            <tr>
              <td>
              </td>
              <td>Normal</td>
              <td>313 (81.5)</td>
            </tr>
            <tr>
              <td>
              </td>
              <td>Overweight</td>
              <td>61 (15.9)</td>
            </tr>
            <tr>
              <td>
                <bold>Water used for food preparation</bold>
              </td>
              <td>Non potable</td>
              <td>297 (77.3)</td>
            </tr>
            <tr>
              <td>
              </td>
              <td>Potable</td>
              <td>87 (22.7)</td>
            </tr>
            <tr>
              <td>
                <bold>Exclusive breastfeeding</bold>
              </td>
              <td>Yes</td>
              <td>197 (51.3)</td>
            </tr>
            <tr>
              <td>
              </td>
              <td>No</td>
              <td>187 (48.7)</td>
            </tr>
          </tbody>
        </table>
      </table-wrap>
      <p>A total of 384 children aged 0 to 14 years were included in the study. Boys were slightly in the majority (53.1%), and the mean age was 8.2 ± 3.9 years, with a predominance of children aged 5 to 9 years (40.6%). The majority of households belonged to a low socioeconomic group (64.6%). Nutritionally, most children had a normal BMI (81.5%), while the coexistence of malnutrition (2.6%) and overweight (15.9%) indicates a double nutritional burden. Furthermore, more than three-quarters of households used unsafe water for food preparation (77.3%). Finally, approximately half of the children were exclusively breastfed (51.3%) (see <bold>Table 1</bold>).</p>
      <p>Bivariate analysis revealed a statistically significant association between several anthropometric characteristics and the occurrence of acute respiratory infections (ARIs). Children under 5 years of age had a higher risk of ARI than those aged 5 years or older (PR = 2.41; 95% CI: 1.12 - 5.18; p = 0.024). The BMI is not significantly associated with an increased PR of ARI (see <bold>Table 2</bold>).</p>
      <p><bold>Table 2.</bold> Relationship between anthropometric parameters and the occurrence of acute respiratory infections.</p>
      <table-wrap id="tbl2">
        <label>Table 2</label>
        <table>
          <tbody>
            <tr>
              <td>
                <bold>Variable</bold>
              </td>
              <td>
                <bold>Modalities</bold>
              </td>
              <td>
                <bold>ARI Yes</bold>
                <bold>n (%)</bold>
              </td>
              <td>
                <bold>ARI No</bold>
                <bold>n (%)</bold>
              </td>
              <td>
                <bold>Accute</bold>
                <bold>PR</bold>
                <bold>(CI 95%)</bold>
              </td>
              <td>
                <bold>p-value</bold>
              </td>
            </tr>
            <tr>
              <td>Age</td>
              <td>&lt;5 Years</td>
              <td>106 (27.6)</td>
              <td>6 (1.6)</td>
              <td>2.41 (1.12 - 5.18)</td>
              <td>0.024</td>
            </tr>
            <tr>
              <td>
              </td>
              <td>≥5 Years</td>
              <td>238 (62.0)</td>
              <td>34 (8.9)</td>
              <td>1</td>
              <td>—</td>
            </tr>
            <tr>
              <td>Weight</td>
              <td>≥25 kg</td>
              <td>176 (45.8)</td>
              <td>6 (1.6)</td>
              <td>7.24 (2.96 - 17.7)</td>
              <td>
                <bold>&lt;0</bold>
                <bold>.</bold>
                <bold>001</bold>
              </td>
            </tr>
            <tr>
              <td>
              </td>
              <td>&lt;25 kg</td>
              <td>162 (42.2)</td>
              <td>40 (10.4)</td>
              <td>1</td>
              <td>—</td>
            </tr>
            <tr>
              <td>Size</td>
              <td>≥100 cm</td>
              <td>277 (72.1)</td>
              <td>26 (6.8)</td>
              <td>3.49 (1.94 - 6.27)</td>
              <td>
                <bold>&lt;0</bold>
                <bold>.</bold>
                <bold>001</bold>
              </td>
            </tr>
            <tr>
              <td>
              </td>
              <td>&lt;100 cm</td>
              <td>61 (15.9)</td>
              <td>20 (5.2)</td>
              <td>1</td>
              <td>—</td>
            </tr>
            <tr>
              <td>BMI</td>
              <td>Overweight</td>
              <td>52 (85.3)</td>
              <td>9 (14.7)</td>
              <td>0.8 2 (0.38 - 1.8)</td>
              <td>
                <bold>0</bold>
                <bold>.</bold>
                <bold>62</bold>
              </td>
            </tr>
            <tr>
              <td>
              </td>
              <td>Malnutrition</td>
              <td>8 (80)</td>
              <td>2 (20)</td>
              <td>0.57 (0.1 - 2.8)</td>
              <td>0.48</td>
            </tr>
            <tr>
              <td>
              </td>
              <td>Normal</td>
              <td>274</td>
              <td>39</td>
              <td>1</td>
              <td>—</td>
            </tr>
          </tbody>
        </table>
      </table-wrap>
      <p>Note: PR = Prevalence ration; CI = confidence interval.</p>
      <p><bold>Table 3.</bold> Domestic environmental pollution factors associated with acute respiratory infections (ARIs) in children surveyed in the Kamina community.</p>
      <table-wrap id="tbl3">
        <label>Table 3</label>
        <table>
          <tbody>
            <tr>
              <td>
                <bold>Variables</bold>
              </td>
              <td>
                <bold>Modalities</bold>
              </td>
              <td>
                <bold>ARI Yes n (%)</bold>
              </td>
              <td>
                <bold>ARI No</bold>
                <bold>n (%)</bold>
              </td>
              <td>
                <bold>Crude PR (CI à 95%)</bold>
              </td>
              <td>
                <bold>p</bold>
                <bold>-value</bold>
              </td>
            </tr>
            <tr>
              <td rowspan="2">Household chemicals</td>
              <td>No (Reference)</td>
              <td>222 (85.1)</td>
              <td>39 (14.9)</td>
              <td>1</td>
              <td>—</td>
            </tr>
            <tr>
              <td>Yes</td>
              <td>116 (94.3)</td>
              <td>7 (5.7)</td>
              <td>2.91 (1.26 - 6.71)</td>
              <td>0.009</td>
            </tr>
            <tr>
              <td rowspan="2">Carrying the child during cooking</td>
              <td>No (Reference)</td>
              <td>34 (10.2)</td>
              <td>299 (89.8)</td>
              <td>1</td>
              <td>—</td>
            </tr>
            <tr>
              <td>Yes</td>
              <td>12 (23.5)</td>
              <td>39 (76.5)</td>
              <td>2.70 (1.29 - 5.65)</td>
              <td>0.006</td>
            </tr>
            <tr>
              <td rowspan="2">Carrying the child when lighting the fire</td>
              <td>No (Reference)</td>
              <td>28 (9.6)</td>
              <td>263 (90.4)</td>
              <td>1</td>
              <td>—</td>
            </tr>
            <tr>
              <td>Yes</td>
              <td>18 (19.4)</td>
              <td>75 (80.6)</td>
              <td>2.25 (1.18 - 4.29)</td>
              <td>0.012</td>
            </tr>
            <tr>
              <td rowspan="2">Open fireplace</td>
              <td>No (Reference)</td>
              <td>162 (85.3)</td>
              <td>28 (14.7)</td>
              <td>1</td>
              <td>—</td>
            </tr>
            <tr>
              <td>Yes</td>
              <td>176 (90.7)</td>
              <td>18 (9.3)</td>
              <td>1.69 (0.90 - 3.17)</td>
              <td>0.100</td>
            </tr>
            <tr>
              <td rowspan="2">Passive smoking</td>
              <td>No (Reference)</td>
              <td>218 (87.9)</td>
              <td>30 (12.1)</td>
              <td>1</td>
              <td>—</td>
            </tr>
            <tr>
              <td>yes</td>
              <td>120 (88.2)</td>
              <td>16 (11.8)</td>
              <td>1.03</td>
              <td>0.957</td>
            </tr>
          </tbody>
        </table>
      </table-wrap>
      <p><bold>Table 3</bold> shows that certain household exposures were significantly associated with the occurrence of acute respiratory infections (ARIs) in children. Exposure to household chemicals nearly tripled the PR of ARIs compared to unexposed children (PR = 2.91; 95% CI: 1.26 - 6.71; p = 0.009). Similarly, carrying the child during cooking (PR = 2.70; 95% CI: 1.29 - 5.65; p = 0.006) and during fire lighting (PR = 2.25; 95% CI: 1.18 - 4.29; p = 0.012) were associated with a significantly increased risk of ARIs, reflecting the harmful effect of close exposure to combustion smoke.</p>
      <p>Furthermore, the use of an open fireplace tended to increase the odds of ARI (PR = 1.69; 95% CI: 0.90 - 3.17), although this did not reach statistical significance (p = 0.100). Conversely, no association was observed between passive smoking and ARI after data verification (PR = 1.03; p = 0.957).</p>
      <p><bold>Table 4.</bold> Independent determinants of acute respiratory infections: results of multivariate logistic regression.</p>
      <table-wrap id="tbl4">
        <label>Table 4</label>
        <table>
          <tbody>
            <tr>
              <td>
                <bold>Variables</bold>
              </td>
              <td>
                <bold>Comparaison</bold>
              </td>
              <td>
                <bold>aOR</bold>
              </td>
              <td>
                <bold>CI 95%</bold>
              </td>
              <td>
                <bold>p-value</bold>
              </td>
            </tr>
            <tr>
              <td>Low socioeconomic status</td>
              <td>Low vs. medium/high</td>
              <td>2.81</td>
              <td>1.45 - 5.42</td>
              <td>0.002</td>
            </tr>
            <tr>
              <td>Overcrowding</td>
              <td>Yes vs No</td>
              <td>1.88</td>
              <td>1.05 - 3.36</td>
              <td>0.032</td>
            </tr>
            <tr>
              <td>Indoor smoke</td>
              <td>Yes vs No</td>
              <td>2.42</td>
              <td>1.31 - 4.50</td>
              <td>0.004</td>
            </tr>
            <tr>
              <td>Chemicals</td>
              <td>Yes vs No</td>
              <td>2.65</td>
              <td>1.15 - 6.10</td>
              <td>0.021</td>
            </tr>
            <tr>
              <td>Carrying children while cooking</td>
              <td>Yes vs No</td>
              <td>2.48</td>
              <td>1.18 - 5.21</td>
              <td>0.016</td>
            </tr>
            <tr>
              <td>Carrying children during fire</td>
              <td>Yes vs No</td>
              <td>2.12</td>
              <td>1.05 - 4.28</td>
              <td>0.034</td>
            </tr>
            <tr>
              <td>Lack of access to healthcare</td>
              <td>Yes vs No</td>
              <td>3.57</td>
              <td>1.78 - 7.14</td>
              <td>0.001</td>
            </tr>
            <tr>
              <td>Street food</td>
              <td>Yes vs No</td>
              <td>3.12</td>
              <td>1.60 - 6.08</td>
              <td>0.001</td>
            </tr>
          </tbody>
        </table>
      </table-wrap>
      <p>Multivariate logistic regression analysis shows that ARIs in children in the Kamina Health Zone result from the interaction of socioeconomic, environmental, and behavioral factors. Children from low socioeconomic status households had a higher risk of ARIs (aOR = 2.81; 95% CI: 1.45 - 5.42), as did those living in overcrowded households (aOR = 1.88; 95% CI: 1.05 - 3.36). Domestic exposures were also important determinants, including indoor smoke (aOR = 2.42; 95% CI: 1.31 - 4.50), the use of household chemicals (aPR = 2.65; 95% CI: 1.15 - 6.10), carrying the child while cooking (aPR = 2.48; 95% CI: 1.18 - 5.21), or while lighting a fire (aPR = 2.12; 95% CI: 1.05 - 4.28). Lack of access to healthcare appeared to be the factor most strongly associated with ARIs (aOR = 3.57; 95% CI: 1.78 - 7.14), while the consumption of street food also increased the odds of developing these infections (aOR = 3.12; 95% CI: 1.60 - 6.08) (see <bold>Table 4</bold>).</p>
    </sec>
    <sec id="sec4">
      <title>4. Discussion</title>
      <p>The study population lived in a socioeconomic and environmental context conducive to the occurrence of acute respiratory infections (ARIs) [<xref ref-type="bibr" rid="B11">11</xref>]. The slight male predominance observed is consistent with available data, as sex is not generally considered an independent risk factor [<xref ref-type="bibr" rid="B12">12</xref>]. While the high proportion of school-aged children may reflect greater exposure to contact in group settings, the vulnerability of younger children remains linked to immune immaturity [<xref ref-type="bibr" rid="B13">13</xref>]. In the Kamina Health Zone, precarious living conditions, overcrowding, domestic smoke, and limited access to healthcare illustrate the significant role of structural and environmental factors in maintaining the burden of ARIs in children, as also highlighted by the WHO [<xref ref-type="bibr" rid="B14">14</xref>], UNICEF [<xref ref-type="bibr" rid="B15">15</xref>], and the Global Burden of Disease study [<xref ref-type="bibr" rid="B16">16</xref>].</p>
      <p>The majority of children had a normal BMI (81.5%), but the coexistence of malnutrition (2.6%) and overweight (15.9%) reflects a nutritional transition [<xref ref-type="bibr" rid="B17">17</xref>]. The literature shows that malnutrition impairs immune mechanisms and increases susceptibility to respiratory infections, while adequate nutrition strengthens protection against these diseases [<xref ref-type="bibr" rid="B7">7</xref>][<xref ref-type="bibr" rid="B18">18</xref>]. However, despite this recognized link, our study did not find a statistically significant association between malnutrition and ARIs. This lack of association could be explained by the small proportion of malnourished children included in the study, thus limiting the statistical power needed to detect a significant effect (<bold>Table 2</bold> and <bold>Table 3</bold>).</p>
      <p>Regarding dietary practices, only the consumption of street food was associated with ARIs. The direct exposure to pathogenic agents (bacteria, viruses, toxins) linked to microbiological contamination and lack of hygiene during preparation/sale [<xref ref-type="bibr" rid="B19">19</xref>]. This direct exposure entails indirect effects via a nutritional disturbance (ultra-processed, micronutrient-poor foods) entraining a weakening of mucosal barriers and respiratory immunity [<xref ref-type="bibr" rid="B20">20</xref>]. This result is consistent with studies highlighting the importance of food hygiene in preventing infections [<xref ref-type="bibr" rid="B21">21</xref>], as well as with African studies documenting high levels of microbiological contamination of street food [<xref ref-type="bibr" rid="B22">22</xref>]. More recent studies confirm this reality in urban African settings [<xref ref-type="bibr" rid="B23">23</xref>]. Street food consumption (aOR = 3.12) was one of the strongest associations observed after the absence of healthcare access. However, our study suggests an indirect effect, mediated by increased nutritional and immune vulnerability, rather than a direct infectious effect. Conversely, no significant association was found with the use of potable water, meal frequency, or exclusive breastfeeding, consistent with the observations of other authors [<xref ref-type="bibr" rid="B24">24</xref>]. Although exclusive breastfeeding is widely recognized as a protective factor, this effect was not observed in our setting, likely due to the influence of other environmental and socioeconomic factors.</p>
      <p>Our observations also suggest that childhood respiratory infections (ARIs) occur in a home environment characterized by multiple harmful exposures. Indoor air pollution, particularly from household smoke and fuels used in homes, remains a major concern [<xref ref-type="bibr" rid="B4">4</xref>][<xref ref-type="bibr" rid="B25">25</xref>]. Although secondhand smoke is recognized as a significant risk factor [<xref ref-type="bibr" rid="B26">26</xref>], no significant association was found in our study. This lack of association could reflect specific exposure patterns in the Kamina Health Zone or certain measurement limitations, but it is consistent with the observations of previous researchers [<xref ref-type="bibr" rid="B27">27</xref>].</p>
      <p>Furthermore, exposure to household chemicals appears consistent with data from the literature [<xref ref-type="bibr" rid="B28">28</xref>]. Disinfectants and volatile organic compounds (VOCs) present in the home environment are likely to contribute to pediatric respiratory morbidity, suggesting that an accumulation of irritants in homes promotes the occurrence of ARIs [<xref ref-type="bibr" rid="B29">29</xref>]. Similarly, holding a child while cooking or lighting a fire increases their direct exposure to biomass fumes, a phenomenon already described in similar contexts [<xref ref-type="bibr" rid="B30">30</xref>]. Recent literature highlights that these repeated early exposures can not only promote acute infections but also induce chronic bronchial inflammation that can permanently impair respiratory function [<xref ref-type="bibr" rid="B31">31</xref>].</p>
      <p>Delayed or insufficient access to healthcare [<xref ref-type="bibr" rid="B5">5</xref>][<xref ref-type="bibr" rid="B32">32</xref>] and household overcrowding [<xref ref-type="bibr" rid="B6">6</xref>] also illustrate the significant role of living conditions in the development of acute respiratory infections (ARIs). Lack of early access to care appears to be a major determinant, consistent with previous observations [<xref ref-type="bibr" rid="B33">33</xref>]. Overcrowding (aOR = 1.88; 95% CI: 1.05 - 3.36) showed a significant but more moderate association. This result is consistent with the literature, which describes overcrowding less as a direct causal factor than as an amplifier of infectious agent transmission [<xref ref-type="bibr" rid="B6">6</xref>]. In our study, its relatively moderate effect compared to toxic exposures suggests that person-to-person transmission may play a secondary role in an already heavily polluted environment.</p>
      <p>In this context, ARIs appear less as the consequence of an isolated factor than as a reflection of cumulative vulnerability, where domestic exposures, daily behaviors, socioeconomic conditions, and constraints in accessing healthcare intersect [<xref ref-type="bibr" rid="B9">9</xref>]. These results underscore the need for integrated interventions combining improvements to the home environment, the promotion of protective behaviors, and enhanced early access to healthcare services to sustainably reduce the burden of ARIs in children.</p>
    </sec>
    <sec id="sec5">
      <title>5. Limites</title>
      <p>Acute respiratory infections are defined as the presence of fever, cough as well as rapid breathing.</p>
    </sec>
    <sec id="sec6">
      <title>6. Conclusions</title>
      <p>Acute respiratory infections in children in the Kamina Health Zone appear to be the expression of a multifactorial vulnerability, shaped by the interaction between living conditions, environmental exposures, and constraints in accessing healthcare. The absence or delay in seeking healthcare services is the main factor associated with ARIs. The consumption of street food, domestic exposures related to cooking fumes, carrying children while lighting fires, and the use of household chemicals, as well as household overcrowding, also contribute to maintaining this burden on children.</p>
      <p>The interpretation of these results must take into account the cross-sectional nature of the survey, the reliance on self-reported data, and the lack of objective measurements of environmental exposures. Longitudinal studies incorporating a more precise assessment of these exposures would allow for a deeper understanding of the mechanisms involved.</p>
      <p>The sustainable reduction of childhood acute respiratory infections (ARIs) in Kamina requires an integrated and multisectoral approach, combining improved early access to care, reduced harmful domestic exposures, the promotion of protective practices, and improved living conditions for households.</p>
    </sec>
  </body>
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