Dot plot illustrating the amount (ng/ml) of ECP in genital lavage (a) and in urine (b) and of EPX in genital lavage (c)) and urine (d) classified by pathology category 1–5 (see table 1).

<p>The plus and minus following “NoFGS” in group 4 and 5 refer to the <i>S. haematobium</i> egg status. The median is indicated with a horizontal bar and interquartile ranges shown. Only significant p values are shown on the graphs. For ECP in urine two extreme outlies were excluded (b). Note that the ordinate axis is on logarithmic scale.</p

Diet and hygiene practices influence morbidity in schoolchildren living in Schistosomiasis endemic areas along Lake Victoria in Kenya and Tanzania—A cross-sectional study

<div><p>Background</p><p>Since 2011, cohorts of schoolchildren in regions bordering Lake Victoria in Kenya and Tanzania have been investigated for morbidity caused by <i>Schistosoma mansoni</i> infection. Despite being neighbouring countries with similar lifestyles and ecological environments, Tanzanian schoolchildren had lower <i>S</i>. <i>mansoni</i> prevalence and intensity and they were taller and heavier, fewer were wasted and anaemic, and more were physical fit compared to their Kenyan peers. The aim of the present study was to evaluate whether diet and school-related markers of socioeconomic status (SES) could explain differences in morbidity beyond the effect of infection levels.</p><p>Methods and principal findings</p><p>Parasitological and morbidity data from surveys in 2013–2014 were compared with information on diet and school-related markers of SES collected in 2015 using questionnaires. A total of 490 schoolchildren (163 Kenyans and 327 Tanzanians) aged 9–11 years provided data. A higher proportion of Tanzanian pupils (69.4%, 95% CI: 64.3–74.5) knew where to wash hands after toilet visits compared to Kenyan pupils (48.5%, 95% CI: 40.9–56.1; <i>P</i><0.0005). Similar proportions of children in the two countries ate breakfast, lunch and dinner, but the content of the meals differed. At all three meals, a higher proportion (95% CI) of Tanzanian pupils consumed animal proteins (mostly fish proteins) compared to their Kenyan peers (35.0% (28.3–41.7) vs. 0%; <i>P</i><0.0005 at breakfast; 69.0% (63.9–74.1) vs. 43.6% (35.8–51.4); <i>P</i><0.0005 at lunch; and 67.2% (62.1–72.3) vs. 53.4% (45.8–61.0); <i>P</i> = 0.003 at dinner). Multivariable analyses investigating risk factors for important morbidity markers among individuals revealed that after controlling for schistosome and malaria infections, eating animal proteins (fish) and knowing where to wash hands after toilet visits were significant predictors for both haemoglobin levels and physical fitness (measured as VO₂ max).</p><p>Conclusions</p><p>These results suggest that the differences in morbidity may be affected by factors other than <i>S</i>. <i>mansoni</i> infection alone. Diet and hygiene practice differences were associated with health status of schoolchildren along Lake Victoria in Kenya and Tanzania.</p><p>Trial registration</p><p>Trials Registration numbers: <a href="https://clinicaltrials.gov/ct2/show/ISRCT 16755535" target="_blank">ISRCT 16755535</a> (Kenya), <a href="https://clinicaltrials.gov/ct2/show/ISRCT 95819193" target="_blank">ISRCT 95819193</a> (Tanzania).</p></div

FGS diagnostic categories used for data analysis.

<p><b>√</b>: At least one manifestation of the pathology type in question.</p><p><b>?</b>: The pathology can be present.</p><p><b>-</b> : No manifestations of the given type.</p><p>Below the category number in brackets are the terms used in the text and on <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0002974#pntd-0002974-g001" target="_blank">figure 1</a> for each grouping.</p

Regression coefficients (<i>B</i>), 95% confidence intervals (95% CI) and corresponding <i>P</i> values of variable found to be significant predictors of physical fitness, VO₂ max (mL/kg/min) in children in Kenya and Tanzania in a multivariable linear regression model ^*.

<p>Regression coefficients (<i>B</i>), 95% confidence intervals (95% CI) and corresponding <i>P</i> values of variable found to be significant predictors of physical fitness, VO₂ max (mL/kg/min) in children in Kenya and Tanzania in a multivariable linear regression model ^{<a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0006373#t006fn001" target="_blank">*</a>}.</p

Year 3 cross-sectional measurements of parasitological, demographic, anthropometric, haematological and physical parameters in schoolchildren in Kenya and Tanzania *.

<p>Year 3 cross-sectional measurements of parasitological, demographic, anthropometric, haematological and physical parameters in schoolchildren in Kenya and Tanzania *.</p

Summary of questionnaire results from the schoolchildren in Kenya and Tanzania.

<p>Summary of questionnaire results from the schoolchildren in Kenya and Tanzania.</p

The two-armed cohort study (arms in bold) was nested in a larger cross-sectional study.

<p>The cohort study investigated the effects of the most intense level of treatment (arm 1) and the less intense treatment strategy (arm 6) on subtle morbidity. Arm 1 represents the community-wide treatment (CWT) and arm 6 represents biannual school-based treatment. Holiday means that no PC was provided that year. Arrows indicate years where morbidity assessments were performed and the bold arrow indicates when the parasitological and morbidity data used for this study were collected. Questionnaire data was collected 1½ years (Kenya) and ½ year (Tanzania) after collection of parasitological and morbidity data.</p

Univariable association of demographic, anthropometric, parasitological (including treatment history), and diet and school-related markers of socioeconomic status with haemoglobin (Hb) level (g/L; adjusted for altitude) of the schoolchildren ^*.

<p>Univariable association of demographic, anthropometric, parasitological (including treatment history), and diet and school-related markers of socioeconomic status with haemoglobin (Hb) level (g/L; adjusted for altitude) of the schoolchildren ^{<a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0006373#t003fn007" target="_blank">*</a>}.</p

Venn diagram showing the overlap between positive findings in the four diagnostic indicators.

<p>The four diagnostic indicators were: (1) Urine microscopy, (2) Schistosoma PCR in cervico-vaginal lavagae, (3) sandy patches identified using clinical photocolposcopic examination or by computerised colourimetric image analysis and (4) self-reported urogenital symptoms: abnormal discharge colour, abnormal discharge smell, burning sensation in the genitals, bloody discharge, genital ulcer, red urine, pain on urination, stress incontinence and urge incontinence).</p

Cross tabulation of frequencies of negative and positive results for urine microscopy of <i>S</i>. <i>haematobium</i> compared to a pseudo-gold standard, with empirical sensitivities, specificities, positive and negative predictive values and 95% confidence intervals (CIs).

<p>Cross tabulation of frequencies of negative and positive results for urine microscopy of <i>S</i>. <i>haematobium</i> compared to a pseudo-gold standard, with empirical sensitivities, specificities, positive and negative predictive values and 95% confidence intervals (CIs).</p