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Background: Malnutrition constitutes one of the major public health challenges throughout the developing world. Urban poverty and malnutrition have been on the rise, with an increased rate of morbidity. We herein explore the relationship between infections and nutritional status and the related association with hygienic conditions as risk of infection in children residing in the slums of Nairobi. Methods: Case-control study based on a secondary analysis of quantitative data collected from a cluster randomized trial carried out in two slums of Nairobi. The following information about resident children were selected: babies’ anthropometric measurements, related life conditions, data on infant-feeding practices, food security, hygiene, immunization coverage and morbidity were collected and updated with structured questionnaires until 12 months of life. Prevalence of malnutrition was calculated, then both bivariate and multivariate analysis were used to explore the relationship between malnutrition and its determinants. Results: The study involved a total of 1119 babies registered at birth (51.28% male and 48.03% female infants). Overall the prevalence of malnutrition was high, with 26.3% of the children being stunted, 6.3% wasted and 13.16% underweight. Prevalence of wasting was higher in the first months of life, while in older children more case of stunting and underweight were captured. Wasted infants were significantly associated with common childhood illnesses: with cough and rapid breathing as well as with diarrhea (p-value< 0.05). Stunting was associated with hygienic conditions (p-value< 0.05 in households that did not perform any water treatment and for children that had a toilet within the house compound), immunization program and low-birth-weight. Moreover, regression analysis showed that significant determinants of stunting were sex and feeding practices. Underweight was significantly associated with socio-demographic factors. Conclusions: In the specific environment where the study was conducted acute malnutrition is correlated with acute infections, while chronic malnutrition is more influenced by WASH conditions. Therefore, our findings suggest that one cannot separate infection and its risk factors as determinants of the whole malnutrition burden.
We herein explore the relationship between infections and nutritional status and the related association with hygienic conditions as risk of infection in children residing in above-mentioned slums. The MYICN (Maternal Infant and Young Child Nutrition) Intervention study, a cluster randomized controlled trial, was carried out in two slums of Nairobi, Kenya, i.e. Korogocho and Viwandani; here the African Population and Health Research Center (APHRC) runs the Nairobi Urban Health and Demographic Surveillance System (NUHDSS), covering close to 70,000 residents. The two slums are located about 7 km from each other and are densely populated with 63,318 and 52,583 inhabitants per square kilometer respectively [16]. The NUHDSS involves a systematic quarterly recording of vital demographic events, including births, deaths and migrations occurring among residents of all households in the area since 2003. Other data are also collected and updated regularly [17]. The informal settlements of Viwandani and Korogocho were selected as study sites, since data from available literature showed high malnutrition prevalence in these areas; with 45% of children aged < 5 years stunted and high under-five children mortality (79 deaths/1000 live births) [18] these settlements performed worse than other populations in Kenya, including those residing in rural settings and other areas of Nairobi, considering mortality, rate of infections and life conditions [9]. Case-control study based on a secondary analysis of quantitative data collected by the antecedent MIYCN intervention study. The latter’s protocol has already been published [19, 20] together with the results of the intervention [21]. Therefore we herein only detail methods relevant to the specific research question of this paper. The source population consisted in all pregnant women and their offspring living in the randomized Community Health Units (CUs, defined by the Kenya National Community Health Strategy) in Korogocho and Viwandani slums that fall within the NUHDSS area. The inclusion criteria were as follows: all pregnant women aged between 12 and 49 years and their children,born between December 2012 and July 2014. Exclusion criteria were as follows: women with a disability that made the administration of the questionnaires challenging (e.g. hearing, sight or mental impairment); women of reproductive age who had given birth before the recruitment started; disability in both mother and child that would significantly affect infant feeding (e.g. developmental problems); women who had a miscarriage or a still-birth; women who were lost to follow-up during pregnancy. Recruitment of participants was conducted through routine NUHDSS rounds, whereby pregnancy registration is done for female residents in each household. This was complemented by case finding carried out by Community Health volunteers (CHVs) and informants to ensure high coverage. While the reproductive age in most studies is usually defined as 15 to 49 years, girls aged 12 to 14 years were included because a substantial proportion (close to 10%) of adolescents in the study areas is sexually active before the age of 15 years [22]. Within the design of the MIYCN trial, which had focused on optimal maternal and infant feeding practices (as recommended by the WHO – World Health Organization), the population had been randomly divided into two groups: the intervention group and the control group. Both groups were involved in regular visits by CHVs, according to the specific needs of every age group [21]. In the intervention group, mothers were provided with age specific counseling and support on optimal child feeding and health, including breastfeeding initiation, exclusive breastfeeding (EBF), extended breastfeeding, complementary feeding, maternal nutrition, antenatal care including birth planning, health care seeking for delivery and post-natal services including immunization and general hygiene and child care. They also received information materials on MIYCN. The mothers in the intervention arm were visited at least monthly during pregnancy until gestation week no. 34, after which they were visited every week until they gave birth, and more frequently (as necessary) in the 1st month after giving birth (for support in initiating breastfeeding and sustaining EBF). They were then visited once a month until the 5th month, when they were visited fortnightly (to prepare them for introduction of complementary feeding) and monthly in the subsequent months until one year of age of the child. The control arm received standard care involving CHVs visits providing counselling on antenatal care, postnatal care including immunization and general hygiene in accordance with the guidance set forth by the community health strategy. The frequency of visits was defined by need, but generally about once a month per household, and usually more frequent around the time of birth. No specific schedule was given to them and CHVs in the control arm did not undergo any specific training on child feeding. However, mothers in the control arm also received information materials on MIYCN. In the MIYCN Intervention study, babies’ anthropometric measurements, data on infant feeding practices, household characteristics, demographic factors, food security and hygiene, immunization coverage and morbidity were collected and updated (where relevant) every two months during follow-up visits in both groups (intervention and control). Data were captured using various researcher-administered questionnaires. With regards to the present study specific data have been selected from the data dictionary (where all information had been stored). Malnutrition, indicated by wasted, stunted and underweight children. Anthropometric measurements (weight, length) were taken according to standard procedures [23]. Prevalence of malnutrition in the population was generated and the related prevalence of stunting, underweight and wasting at different ages was also considered. For determination of underweight, stunting, and wasting, we calculated weight-for-age z-scores (WAZ), height-for-age z-scores (HAZ) and weight-for-height z-scores (WHZ), using the WHO 2007 growth standards [23, 24]. Stunting was determined as HAZ < − 2, underweight as WAZ < − 2 and wasting as WHZ < − 2 [25]. Independent variables were categorized into three groups. Concerning child health status, common childhood symptoms of illnesses occurring two weeks before the interview date were considered. These included: fever, cough, cough with rapid breathing, diarrhea and seizures. The five common childhood illnesses’ symptoms were counted as separate variables in the analysis, but also collectively as morbidity (general morbidity), when a child had at least a single episode of illness – regardless of the type – two weeks before the interview date. Household Water, Sanitation and Hygiene (WASH) conditions were measured using data from a structured questionnaire addressing water, food and personal hygiene. One of the considered variables was whether any kind of water treatment had been in use at home; possible answers were: no treatment; filtered water; boiled water; water guard/aquatabs/other chemical treatment; sedimentation; UV rays or solar disinfection; sieved through cloth; others. Variables about habits of washing utensils for feeding babies, hand washing practice with soap (with specified frequency), presence of a toilet facility in or near the household were also investigated. With regards to sanitation, type of toilet facility used during the day and at night was categorized into two groups: own (own flush, traditional pit, Ventilated Improved Pit) and shared (shared flush, traditional pit, shared Ventilated Improved Pit; flush trench toilet; toilet without pit, working flush; no facility or bush and field, or flying toilet, and other toilet facility). Socio-economic and demographic variables: the following were included: sex of the child; mother’s age, parity and occupation; marital status; religion; attained level of mother’s education. Birth Weight (BW): BW was categorized into three groups: Low Birth Weight (LBW, less than 2.5 Kg), normal weight at birth (between 2.5 and 4.2 Kg) and overweight (more than 4.2 Kg at birth). Immunization coverage: The variable on full vaccination among children according to the Kenyan Immunization Program was considered [26]. Exclusive breastfeeding until six months: Data were collected through the interviewer-administered questionnaire to the mother to determine if the child was still breastfeeding, and, if so, whether they had started feeding on other foods or fluids other than breast milk; when they were introduced to the other foods or fluids; and if they stopped breastfeeding, when they stopped [21]. Complementary feeding practices: this focused on complementary feeding practices with regard to WHO recommendations [27]. In the present study we focused only on: timely introduction of solid/semi-solid/soft foods; number of food groups consumed (at least four food groups consumed and less than four); minimum meal babies’ frequency and household food security situation. Household Food Security: Household food security was defined using a modified Household Food Insecurity Access Scale (HFIAS) [28] . The WHO growth reference 2007 for children was used to generate anthropometric indices to assess the nutritional status of children [23, 25, 29]. The indices were expressed as standard deviation units from the median of the WHO child growth standards adopted in 2007. Bivariate analysis was conducted to evaluate the association between dependent and independent variables and to identify determinants of malnutrition in the study population. Odds Ratio (OR) and their 95% confidence intervals (CI) were estimated in order to show the magnitude of the association between independent variables and malnutrition. P-values of less than 0.05 were considered statistically significant. All independent variables were analyzed initially in bivariate models and the variables that were significantly associated with the dependent variable were included in logistic regression models. Subsequent selection of variables fitted into the final models was based on statistical significance of p-value ≤0.25, as proposed by Hosmer and Lameshow [30], upon running univariable logistic regression with all the exploratory variables considered in the study. Adjustment for confounding factors were made for the associations observed between independent variables and dependent variables. Details on data collection procedures and other data collected are published [19]. Data management and analysis were carried out using STATA Version 13.
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