Introduction. Childhood diarrhoeal diseases and stunting are major health problems in low- and middle-income countries (LMICs). Poor water supply, sanitation services and hygiene, frequently encountered in resource-poor settings, contribute to childhood diarrhoea and stunting. Methods. Data on demographic characteristics, hygiene practices, sanitation and human-animal interactions (predictors) and child height-for-age z-scores (HAZ) (outcome) were collected once, while diarrhoea incidences were collected fortnightly for 24 months (outcome). Results. Drinking water from public taps (OR = 0.51, 95% CI. 0.44 – 0.61; p < 0.001) and open wells (OR = 0.46, 95% CI. 0.39 – 0.54; p < 0.001) and older age of children (OR = 0.43, 95% CI. 0.27 – 0.67; p < 0.001) were protective against diarrhoea. Inappropriate disposal of children’s faeces (OR = 1.15, 95% CI. 1.02 – 1.31; p = 0.025), sharing water sources with animals in the dry season (OR = 1.48, 95% CI. 1.29 – 1.70; p < 0.001), overnight sharing of houses with cats (OR = 1.35, 95% CI. 1.16 – 1.57; p < 0.001) and keeping chickens inside the house overnight regardless of room (OR = 1.39, 95% CI. 1.20 – 1.60; p < 0.001) increased the risk of diarrhoea. The Sukuma language group (p = 0.005), washing hands in running water (p = 0.007), access of chickens to unwashed kitchen utensils (p = 0.030) and overnight sharing of the house with sheep (p = 0.020) were associated with higher HAZ in children. Conclusions. Until a more precise understanding of the key risk factors is available, these findings suggest efforts towards control of diarrhoea and improved linear growth in these areas should be directed to increased access to clean and safe water, handwashing, sanitation, and improved animal husbandry practices.
Iwondo Ward in the Mpwapwa District and Sanza and Majiri Wards in the Manyoni District are situated within the Great Rift Valley in Tanzania. These areas form part of the semi-arid area of the Central Zone, experiencing low, short-lived and often erratic rainfall (approximately 600 mm per annum) in a unimodal pattern, typically from November to April, with reasonably widespread drought occurring approximately one year in four [16]. Low and unpredictable rainfall is associated with chronic food and nutritional insecurity in the study area due to water and pasture shortage, reduced crop production, livestock deaths, and the sale of livestock and crops at suboptimal prices to meet immediate household needs. Village chickens are kept by more than 50% of the households throughout the year, mostly under an extensive production system, and are the livestock least affected by these unpredictable climatic conditions in terms of feed availability [17]. The Nkuku4U project team conducted a census of all households in Sanza Ward in April 2014, Majiri Ward in October 2014, and Iwondo Ward in December 2016, as part of a staggered implementation within the broader study design, giving a total of 1730, 2810 and 2004 households, respectively. The criteria used for inclusion of households in the broader Nkuku4U study were having at least one child less than two years of age, and either currently owning chickens or expressing an intention to keep chickens within two years. Few households were excluded based on the latter criterion. Two-stage sampling was used to reach the study target of 240 households in Sanza Ward, 280 in Majiri Ward and 300 in Iwondo Ward. First, all eligible households with a child under 12 months of age were enrolled, and then random selection through lottery draw using household identification numbers deployed to select additional households with children aged 12-24 months to give a required number of children. In cases where more than one child under two years of age was present in the household, information on diarrhoea and anthropometry was collected for the younger child. Households in the present study are a subset of those participating in the Nkuku4U project: encompassing all households either currently owning chickens or who owned chickens within the six months before administration of the questionnaire in February 2018. A total of 493 out of 711 households participating in the larger project fulfilled this criterion and were included. The number of households participating in this study from each ward was 153, 153 and 187 for Sanza, Majiri and Iwondo Wards, respectively. Information on parental reports of diarrhoea in children was collected twice per month by trained male and female community members (‘Community Assistants’) over 24 months, starting in June 2014, December 2014 and February 2016 in Sanza, Majiri and Iwondo Wards, respectively. Community Assistants visited each household to record the occurrence of diarrhoea within the preceding fortnight, based on information provided by the mother or primary caretaker of the enrolled child. Diarrhoea was defined as the passage of loose or liquid stools three or more times per day [18]. At each household visit, children reported as having diarrhoea for one or more days during the preceding two weeks were documented as a single positive count. A questionnaire that was initially tested and validated using the sub-population from the same study population was administered in February 2018 to 493 mothers or caregivers of enrolled children in participating households by trained male and female enumerators recruited from within each ward. Survey questions were in Swahili, but enumerators were encouraged to make use of the languages of the two predominant language groups (Gogo and Sukuma) where appropriate to aid in communication. Information collected spanned three key areas: socio-demographic characteristics, hygiene practices and human-animal interactions. Anthropometric data were taken at six-monthly intervals during the Nkuku4U project by trained personnel from the Tanzania Food and Nutrition Centre, Ministry of Health and respective district hospitals. Recumbent length was recorded for children up to 24 months of age, and standing height for children aged 24 months of age or above, using UNICEF portable baby/child length-height measuring boards. Measurements were recorded to the nearest 1 mm. The weights of the mother and child were measured to the nearest 0.1 kg using TANITA HD355 digital scales. Mother/caregiver and child were weighed together and maternal weight subtracted from the combined weight to give the weight of the child; this method eliminated the difficulties of handling children alone on a digital scale. The fifth anthropometry data set in May 2016, November 2016 and January 2018 for Sanza, Majiri and Iwondo, respectively, were used in this study (Fig. 1). Anthropometry was recorded for 466 children (out of the total number of 493 children enrolled in this study) as 27 children (12 boys, 15 girls) were not available for measurements, therefore, z-scores were calculated for 466 children, 223 boys and 243 girls. Data collected by Nkuku4U project and this study and selection criteria of the participating households, the months and years indicates the time of collection of respective data set and n indicates the number of households. These particular diarrhoea and anthropometry data sets were selected for analysis because they were collected during the time when all enrolled children were less than five years of age and data collection was the closest to the time of the questionnaire survey conducted in February 2018. HAZ were calculated from children’s measurements using the Emergency Nutrition Assessment for SMART software (http://www.nutrisurvey.net/ena/ena.html) and WHO child growth standards [19]. A HAZ of less than -2 was classified as stunting. Longitudinal diarrhoea data (episodes) were collected fortnightly for 24 months (48 trials) through household visits. The number of successful visits (i.e. household informant present and able to provide information on the occurrence of diarrhoea in the enrolled child) was taken as the binomial event. For each successful visit, the enrolled child was recorded as having (yes) or not having (no) diarrhoea in the previous fortnight. The incidence of diarrhoea was calculated as a proportion i.e. the numbers of positive diarrhoea records divided by number of successful visits. The dependent and independent variables evaluated by this study are described in Table I. Description of the variables evaluated in the study categorised into socio-demographic characteristics, hygiene practices and human-animal interactions. *The utensils used while wet after washing or the washed utensils are rinsed and used while wet Data was first entered into an Excel 2007 spreadsheets and then transferred to STATA® software version 14.2 for analysis [20]. Descriptive statistics were used to characterise the study population and explore differences in explanatory variables among the three study wards. Proportions were used to present categorical variables, and means, range and standard deviations for quantitative variables. Differences between wards and groups were determined by using t-tests and chi-square tests for continuous and categorical variables, respectively, and the variables were considered statistically significant at p ≤ 0.05. Univariable linear regression and logistic regression models were fitted to determine the independent variables unconditionally associated with HAZ and diarrhoea outcome variables, respectively. Independent variables that showed suggestive associations (p ≤ 0.2) were retained for construction of multivariable models. Candidate variables for multivariable models were categorised into three groups associated with: (1) socio-demographic characteristics, (2) hygiene practices and (3) human-animal interactions. The individual multivariable linear regression model (HAZ outcome variable) and logistic regression model (diarrhoea outcome variable) were run to test the association of independent variables significantly and suggestively associated with the outcomes in univariable models from each category and the outcomes variables under this study. The variables that were significant associated with the outcomes in each multivariable model were run in a single model to generate a final multivariable model. Stepwise backward elimination was used to eliminate the variables with p-values higher than 0.05 to reach the final model in each of the three multivariable models and in final combined multivariable models. The models were fitted by R studio software version 3.6.0 using data stored in the STATA® spreadsheets [21]. The study design, protocols and research tools for this program were approved by the National Institute for Medical Research ethics committee (NIMR/HQ/R.8a/Vol.IX/1690) in Tanzania, and The University of Sydney Human Research Ethics Committee (2014/209). Informed consent was obtained from all questionnaire survey respondents via signature or thumb print, with the assurance of confidentiality, anonymity and voluntary participation.
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