Prevalence and Correlates of Undernutrition in Young Children Living in Urban Slums of Mumbai, India: A Cross Sectional Study

Huey, Samantha L; Finkelstein, Julia L.; Venkatramanan, Sudha; Udipi, Shobha; Ghugre, Padmini; Thakker, Varsha; Thorat, Aparna; Potdar, Ramesh; Chopra, Harsha; Kurpad, Anura V; Haas, Jere D.; Mehta, Saurabh

doi:10.3389/fpubh.2019.00191

Cited by 30 publications

(36 citation statements)

References 66 publications

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“…In fact, we know that the growth outcome measurement obtained every month for 3 years exhibits 40% of the children had poor growth in the slum area, Vellore. Similar nding of high proportion of children had poor growth in their young age were observed in urban slum in India [11,29,[33][34][35][36][37]. The research nding with the growth data is similar to the existing literature in identifying the subgroup pattern such as "large, catch up, stunting, faltering and average" for the growth outcomes of height, weight, and head circumference.…”

Section: Discussionsupporting

confidence: 74%

Identifying longitudinal child growth curve pattern using Functional Principal Component Analysis from birth cohort study in South India

Karuppusami¹,

Antonisamy²,

Premkumar³

2021

Preprint

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Background: Human growth studies has long been of interest to researchers and health authorities. Predominantly, the study of physical growth in children is a challenging and complex issue. The goal of a variety of studies from across the world is to develop overall health and well-being in children. It is therefore important that we need to identify an accurate and reliable approach for characterising growth trajectories to distinguish between children who have healthy growth and those growth is poor. Many statistical approaches are available to assess the longitudinal growth data and which are difficult to recognize the pattern. The purpose of this study is to identify the longitudinal child growth trajectory pattern and factors association on the growth function using an advanced statistical technique. Methods: This longitudinal birth cohort study (n=290) was conducted in three nearby urban slums communities in Vellore, South India. Pregnant women were identified during a survey conducted in 2002 and infants were recruited from birth between the period of March 2002 and August 2003 following written informed consent from the mother. Growth outcomes of height and weight measurements were recorded for each child continuously in first 36 months. Functional Principal Component Analysis was used to classify the longitudinal child growth trajectory pattern. Functional linear model was used to assess the factors association with the growth functions. Results: We have obtained four functional principal components explained by 86.5%, 3.9%, 3.1% and 2.2% of the variation respectively for the height functions. 38% of the children’s had poor growth trajectories in height. Similarly, we have obtained three functional principal components explained 76.2%, 8.8%, and 4.7% respectively for the weight functions. 44% of the children’s had poor growth in their weight trajectories. The study shows that gender, socio-economic status, parent’s education, breast feeding, and gravida are associated and, influence the growth pattern in children. Conclusions: The advanced FPC approach deals with subjects’ dynamics of growth and not with specific values at given times. FPCA may be a better alternative approach in the sense of both dimension reduction and pattern detection. FPCA may be used to offer greater insight for classification.

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Section: Discussionsupporting

confidence: 74%

Identifying longitudinal child growth curve pattern using Functional Principal Component Analysis from birth cohort study in South India

Karuppusami¹,

Antonisamy²,

Premkumar³

2021

Preprint

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“…When stratified by sex, these associations were present only in male children. Poor growth outcomes in male children compared to female children have been previously observed (67)(68)(69)(70). Earlier studies in undernourished infants and their microbiota have found lower microbial diversity with stunting (71), underweight and wasting (57), or severe acute malnutrition (30).…”

Section: Discussionmentioning

confidence: 98%

“…Participants were children between 10 and 18 completed months of age living in urban slums of Mumbai, India (including the eastern wards of Khar, Santacruz, and Bandra) who provided informed caregiver consent to be screened for enrollment into the parent study, a randomized controlled nutrition intervention trial (Clinicaltrials.gov ID: NCT02233764) ( 93 ). This exploratory cross-sectional study examined a subset of participants at screening, prior to enrollment ( 67 ).…”

Section: Methodsmentioning

confidence: 99%

Nutrition and the Gut Microbiota in 10- to 18-Month-Old Children Living in Urban Slums of Mumbai, India

Huey

Jiang

Fedarko

et al. 2020

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In this cross-sectional study, we describe the composition and diversity of the gut microbiota among undernourished children living in urban slums of Mumbai, India, and determine how nutritional status, including anthropometric measurements, dietary intakes from complementary foods, feeding practices, and micronutrient concentrations, is associated with their gut microbiota. We collected rectal swabs from children aged 10 to 18 months living in urban slums of Mumbai participating in a randomized controlled feeding trial and conducted 16S rRNA sequencing to determine the composition of the gut microbiota. Across the study cohort, Proteobacteria dominated the gut microbiota at over 80% relative abundance, with Actinobacteria representation at <4%, suggesting immaturity of the gut. Increased microbial α-diversity was associated with current breastfeeding, greater head circumference, higher fat intake, and lower hemoglobin concentration and weight-for-length Z-score. In redundancy analyses, 47% of the variation in Faith’s phylogenetic diversity (Faith’s PD) could be accounted for by age and by iron and polyunsaturated fatty acid intakes. Differences in community structure (β-diversity) of the microbiota were observed among those consuming fats and oils the previous day compared to those not consuming fats and oils the previous day. Our findings suggest that growth, diet, and feeding practices are associated with gut microbiota metrics in undernourished children, whose gut microbiota were comprised mainly of Proteobacteria, a phylum containing many potentially pathogenic taxa. IMPORTANCE The impact of comprehensive nutritional status, defined as growth, nutritional blood biomarkers, dietary intakes, and feeding practices, on the gut microbiome in children living in low-resource settings has remained underreported in microbiome research. Among undernourished children living in urban slums of Mumbai, India, we observed a high relative abundance of Proteobacteria, a phylum including many potentially pathogenic species similar to the composition in preterm infants, suggesting immaturity of the gut, or potentially a high inflammatory burden. We found head circumference, fat and iron intake, and current breastfeeding were positively associated with microbial diversity, while hemoglobin and weight for length were associated with lower diversity. Findings suggest that examining comprehensive nutrition is critical to gain more understanding of how nutrition and the gut microbiota are linked, particularly in vulnerable populations such as children in urban slum settings.

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“…This finding is consistent with other studies that have found children born later to be susceptible to poorer nutrition and health outcomes. [56][57][58] One explanation for this could be that increasing numbers of children within a household puts strain on food and household resources, impacting the level of care and nutrition provided. 59 These findings emphasise the importance of family planning and reproductive health services that enable women to control when and how many children they have.…”

Section: Child Characteristicsmentioning

confidence: 99%

Factors influencing undernutrition among children under 5 years from cocoa-growing communities in Bougainville

et al. 2020

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Half the children under the age of 5 years in Papua New Guinea (PNG) are undernourished, more than double the global average with rural areas disproportionately affected. This study examines factors associated with stunting, wasting and underweight in cocoa growers’ children (<5 years) in the Autonomous Region of Bougainville (ARoB), using data from a comprehensive 2017 cross-sectional livelihoods survey. Sixteen independent predictors for stunting, wasting and underweight were selected based on the UNICEF Conceptual Framework of Determinants of Undernutrition. We used multilevel logistic mixed regression models to measure the association of the explanatory variables with stunting, wasting and underweight. At the household level, the adjusted OR (aOR) of stunting (aOR=1.71,95% CI 1.14 to 2.55) and underweight (aOR=2.11, 95% CI 1.16 to 3.82) increased significantly among children from households with unimproved toilet facilities. The aOR for underweight also increased among children from households without access to clean drinking water (aOR=1.97, 95% CI 1.19 to 3.29). Short maternal stature was significantly associated with child stunting, the odds increased as maternal height decreased (from 150 to <155 cm, aOR=1.52, 95% CI 1.02 to 2.26) (<150 cm, aOR=2.37, 95% CI 1.29 to 4.35). At the individual level, the odds of a child being underweight increased with birth order (second born, aOR=1.92, 95% CI 1.09 to 3.36; third born, aOR=6.77, 95% CI 2.00 to 22.82). Compared with children less than 6 months, children aged 6–23 months and 24–59 months had a higher odds of being stunted (aOR=3.27, 95% CI 1.57 to 6.78 and aOR=2.82, 95% CI 1.40 to 5.67) and underweight (aOR=4.83, 95% CI 1.36 to 17.24 and aOR=4.59, 95% CI 1.29 to 16.26). No variables were found to be significant for wasting. Interventions that simultaneously target key life stages for women and children and the underlying social and environmental determinants are required for sustained improvements to undernutrition.

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Prevalence and Correlates of Undernutrition in Young Children Living in Urban Slums of Mumbai, India: A Cross Sectional Study

Cited by 30 publications

References 66 publications

Identifying longitudinal child growth curve pattern using Functional Principal Component Analysis from birth cohort study in South India

Identifying longitudinal child growth curve pattern using Functional Principal Component Analysis from birth cohort study in South India

Nutrition and the Gut Microbiota in 10- to 18-Month-Old Children Living in Urban Slums of Mumbai, India

Factors influencing undernutrition among children under 5 years from cocoa-growing communities in Bougainville

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