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Dietary diversity and anthropometric status and failure among infants and young children in Sri Lanka
Accepted Manuscript Title: Dietary diversity and anthropometric status and failure among infants and young children in Sri Lanka Author: Jessica M. Perkins, Renuka Jayatissa, S.V. Subramanian PII: DOI: Reference:
S0899-9007(18)30179-5 https://doi.org/10.1016/j.nut.2018.03.049 NUT 10182
To appear in:
Nutrition
Received date: Revised date: Accepted date:
4-10-2017 12-3-2018 22-3-2018
Please cite this article as: Jessica M. Perkins, Renuka Jayatissa, S.V. Subramanian, Dietary diversity and anthropometric status and failure among infants and young children in Sri Lanka, Nutrition (2018), https://doi.org/10.1016/j.nut.2018.03.049. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Dietary Diversity and Anthropometric Status and Failure among Infants and Young Children in Sri Lanka Jessica M. Perkins, PhD1, Renuka Jayatissa, MD2, S.V.Subramanian, PhD*3 1
Department of Human and Organizational Development, Peabody College, Vanderbilt University; Vanderbilt Institute of Global Health, Vanderbilt University Medical Center 2
Nutrition Department, Medical Research Institute, Ministry of Health Sri Lanka
3
Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Population Health
*Correspondence Department of Social and Behavioral Sciences Harvard Chan School of Public Health Kresge Building 7th Floor, 716 Boston, Massachusetts 02115-6096 Phone: 6174326299 [email protected] Running Head Dietary diversity and anthropometric status in Sri Lanka Conflict of Interest Statement The authors have no conflicts of interest. Contributor statement: JMP, SVS, and RJ conceptualized the study. JMP and SVS designed the study. JMP wrote the first draft. JMP, SVS, RJ provided critical revisions. SVS provided study oversight. All authors approve the final version of the submitted manuscript.
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Highlights
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ABSTRACT
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Objective: We investigate the association between child dietary diversity and anthropometric status
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and failure in Sri Lanka while accounting for other child and household factors by employing
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multivariable logistic and linear regression analyses.
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Research Methods & Procedures: Using a nationally representative survey of children aged 6-59
47
months, child dietary diversity was based on 24-hour recall of child's food intake across seven food
48
groups. Minimum dietary diversity was a score of four or above. Anthropometric status (height-for-age,
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weight-for-age, and weight-for-height z-scores) and anthropometric failure (stunting, wasting, and
50
underweight) were calculated.
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Results The prevalence of stunting, wasting, and underweight was 15%, 21%, and 26%, respectively.
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The prevalence of inadequate dietary diversity was 9%. Although child dietary diversity was positively
53
associated with height-for-age (b = 0.02, se = 0.01, p-value = 0.04), it was not associated with any
54
indicator of anthropometric failure. However, low birthweight, wealth, and location were strong risk
55
factors for anthropometric status and failure. Analyses stratified by child age indicated that dietary
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diversity was positively associated with anthropometric status for children aged 24+ to 59 months (e.g.,
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for HAZ, b = 0.03, s.e., = 0.01, and p = 0.02). Mixed associations were found for children 6 to 12
58
months old, and there were no associations for children 12+ to 24 months old.
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Conclusions Child dietary diversity predicted anthropometric status among children aged 24+months.
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Interventions addressing both proximal and distal risk factors for anthropometric status may be
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necessary in Sri Lanka to address anthropometric failure among infants and young children.
Anthropometric failure remains in Sri Lanka among infants and young children. Dietary diversity was associated with growth among children aged 24-to-59 months. Mixed associations for ages 6 to 12 months, and none for ages 12 to 24 months. Low birthweight and household wealth predict anthropometric failure. Nutrition + distal interventions are needed to improve child growth in Sri Lanka.
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Keywords: Stunting; Wasting; Underweight; Dietary Diversity; Undernutrition; Complementary
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Feeding; HAZ; WHZ; WAZ
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INTRODUCTION The long-term development, health, and economic consequences of anthropometric failure are
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well known (1-6). Although there are many economic, social, environmental, and illness-related factors
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that lead to anthropometric failure among children (7-11), consumption of sufficient nutritious food is a
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basic critical element to ensure healthy child growth (2, 12). The World Health Organization therefore
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recommends that a diverse diet be provided to ensure adequate intake of necessary energy, minerals,
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vitamins, proteins, and fats when introducing complementary feeding for infants and young children
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six months and older (13, 14).
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Dietary diversity is defined as “the number of different foods or food groups consumed over a
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given reference period” (15). According to the World Health Organization, the typical food groups
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making up a diverse diet are grains/roots/tubers, legumes/nuts, dairy (milk, yogurt, cheese and other
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milk products), flesh foods (meat, fish, poultry and liver/organ meats), eggs, vitamin A rich fruits and
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vegetables, and other fruits and vegetables (14). Consuming foods from less than four of these groups
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in the past 24 hours represents consuming less than the minimum diverse diet, an indicator associated
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with diet quality for both breastfed and non-breastfed children aged 6 months and older (14). Some
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studies on dietary diversity calculate a summary score include fats/oils as an 8th food group (16-18)
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while other studies exclude it.
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Broad evidence from low- and middle-income countries of the extent to which dietary diversity
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impacts child anthropometric status is scant (15), though one study found direct positive associations
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between dietary diversity and standardized height-for-age scores among children aged 6 to 23 months
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in seven low-income countries using Demographic and Health Survey data from 1999-2001 (19). More
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recently a study on children aged 6 to 18 months in Zambia found that dietary diversity was positively
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associated with length-for-age and weight-for-length standardized scores (20). Further, a study among
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Indian children aged 6-59 months found that a low dietary diversity score was one of the main
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predictors of child stunting and underweight (21). 3
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Despite Sri Lanka’s ongoing growth and development in many economic and health sectors
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over the past several decades (22), and the introduction of national campaigns for food and
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micronutrient supplementation for infants and young children (23), anthropometric failure among
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infants and young children in Sri Lanka is still a major public health concern (22, 24, 25). The national
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prevalence of child stunting, wasting, and underweight in 2006-07 was 17%, 14%, and 21%,
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respectively (25). Around the same time period, 29% of children aged 6 to 23 months did not meet
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minimum dietary diversity requirements (26).
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The extent to which dietary diversity is associated with anthropometric status and failure among
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infants and young children up to five years old in Sri Lanka is largely unknown. Understanding the
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independent association between dietary diversity and child anthropometry after accounting for
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potential confounding and mediating factors such as socioeconomic status, household wealth, low birth
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weight, and child health is important for identifying nutrition-related intervention priorities. Thus,
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examining this association among infants and young children in Sri Lanka using recent nationally
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representative data would provide critical information for the development of future interventions and
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national policies targeting child growth. To address this knowledge gap, this study assessed the extent
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to which child dietary diversity is associated with anthropometric status and failure among a nationally
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representative sample of children aged 6-59 months in Sri Lanka while accounting for several other
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potential explanatory factors.
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METHODS
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Data Source
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This study used data from the 2012 National Nutrition and Micronutrient Survey, which took
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place in all 25 districts in Sri Lanka and targeted 7500 households where at least one child aged 6-59
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months resided. A multi-stage cluster sampling procedure was used to identify targeted households. For
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the first stage, 30 divisions per district were identified using a population proportion to sampling
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technique. Thus, there were a total of 750 clusters also known as primary sampling units (PSUs). 4
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Within each PSU, 10 households with at least one age eligible child were randomly selected. A
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household was defined as a group of people who share a common cooking pot. If there was more than
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one child present, then the targeted child was randomly selected for participation. For further
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information on study design, see the 2012 Report (24).
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The mother (or the main guardian) of the child selected as the study participant responded to a
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series of close-ended questions regarding the health and diet of that child as well as to questions about
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household structure, resources, and other factors. In addition, anthropometric measurements and
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biomarker data were collected from the selected child. All data were collected during weekdays. Ten
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percent of the sample was revisited to validate the responses. A total of 7306 children completed
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interviews and measurements with a 97.4% response rate. See the 2012 report for further details on
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sample size (24). The final analytical sample for this study included 7303 children as two children were
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excluded due to mislabeled data, and one child was excluded for having implausible standardized child
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growth values (27).
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Approval for this study was obtained from the Ethical Review Committee of the MRI, Ministry
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of Health. In addition, informed consent was obtained from community representatives, and written
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informed consent was obtained from the mother (or main guardian) of the selected children.
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Outcome variables
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Trained field interview teams obtained measurements of child weight in kilograms and height
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(or recumbent length if child was under 2 years old) in centimeters and collected data on child age. To
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assess anthropometric status, standardized height-for-age (HAZ) scores, weight-for-age (WAZ) sores,
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and weight-for-height (WHZ) scores were calculated according to WHO child growth standards (28).
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There were no missing data. In addition, three binary indicators (stunting, wasting, and underweight) of
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anthropometric failure were calculated (28). A HAZ score below -2 SD from the median of the
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reference population indicates stunting, a condition reflecting the cumulative effect of chronic
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undernutrition. A WHZ score below -2 SD from the median of the reference population indicates 5
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wasting, a condition reflecting the effect of short term undernutrition. Finally, a WAZ score below -2
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SD from the median of the reference population indicates that the child is underweight.
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Main explanatory variables
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Child dietary diversity score was derived from maternal/guardian’s recall of child’s preceding
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24-hour dietary intake. Participants were told "Please describe anything that your child age yesterday
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during the day or night, whether at home or outside the home." They were then asked about intake
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across several food categories. Dietary diversity score was derived from responses indicating
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consumption of food from seven specific food groups (or lack of consumption across these groups)
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(29). These groups included grains/roots/tubers (e.g., bread, rice, other food made from grains, white
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potatoes, white yams, manioc, cassava, any other foods made from roots), legumes/nuts (e.g., beans,
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peas, lentils, nuts, peanuts, coconut), dairy products (e.g., cheese, curd, other milk products, milk
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liquid/powder), flesh foods (e.g., liver, kidney, hearts, other organ meats, chicken, beef, pork, lamb,
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goat, duck, fresh or dried fish, shellfish, seafood), eggs, vitamin A rich foods (e.g., carrots, squash,
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sweet potatoes that are yellow/orange, dark green leafy vegetables, ripe mangos or papayas), and other
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fruits and vegetables (e.g., bananas, grapes, apples, oranges, tomatoes). Consumption of each food
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group is worth one point and zero otherwise with seven as a maximum score. A score less than four
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indicated that a child did not meet the minimum dietary diversity requirements (14). There were no
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missing data.
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Information regarding minimum meal frequency was also collected for children under 24
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months of age as it is considered an important complementary feeding factor representative of diet
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quality for this young age group (14). It is based on child age, the number of times children have eaten
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in the past 24 hours, and whether they are breastfed. The minimum number of times is defined as two
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times for breastfed infants 6-8 months old, three times for breastfed children 9-23 months old, and four
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times for non-breastfed children 6-23 months old. This variable was used in age-stratified analyses only
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(as explained in the statistical analysis section). 6
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Other explanatory factors We included information on several child factors as well as socioeconomic and demographic
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household characteristics that are associated with both dietary diversity and anthropometric status (19,
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30-39). Child sex and child age in months were recorded (with age grouped as 6-12, 13-23, 24-36, 37-
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48, and 49-59 months). A binary low birthweight indicator for children born <2500 grams (2.2%
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missing) was based on data obtained from mandatory child development cards issued by a delivering
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hospital where almost 100% of births take place (40). In addition, data were collected on whether child
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had been breastfed in the last 24 hours (missing < 1%). Two separate binary variables represented
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whether the child had diarrhea in the past two weeks and whether the child had an illness with a cough
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in the past two weeks (missing < 1%). Whether the child had been given deworming treatment in the
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past six months (missing < 1%) was also indicated. A yes/no response was recorded for whether the
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child had ever been given thriposha, which is a fortified food supplement containing a mix of protein,
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carbohydrates, and micronutrients provided as part of a national program on supplementary feeding to
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address undernutrition (41). Finally, presence of anaemia in the child was recorded as having a
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haemoglobin level of less than 11.0 g/dl (3.4% missing). Mothers/guardians reported years of their
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completed education (5.8% missing), the total number of household members, and whether the
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household had received food aid from the government. Household wealth quintile was based on a
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compilation of several household resources using principal components analysis (42). Household
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location was coded as rural vs. urban vs. estate where estate represents households living and working
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on tea estates. (If percent of missing responses is not indicated, then zero responses were missing.)
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Statistical analysis
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We first calculated the percent of children experiencing anthropometric failure as well as the
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average dietary diversity score across sub-categories of child and household factors. We then used
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multivariable multilevel regression models, which accounted for the clustering of observations at the
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PSU level, to estimate the relationship between the continuous child dietary diversity score and the 7
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outcomes. We fit separate linear regression models for the three continuous measures of
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anthropometric status (HAZ, WAZ, and WHZ), and we fit separate logistic regression models for the
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three binary indicators of anthropometric failure (stunting, wasting, and underweight). These models
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also simultaneously adjusted for the additional factors described above in the 'Other explanatory
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variables' section and included dummy variables for districts. We also assessed whether linear
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regression estimates differed when the data were stratified by child age (with sub-groups representing 6
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to 12 months vs. 12+ months to less than 24 months vs. 24 months to less than 60 months) as the
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impact of diverse food consumption may differ across critical growth points. For the first two age
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groups, the minimum meal frequency variable was also included. STATA version 15 was used for
199
analyses (43).
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RESULTS
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Table 1 presents the distribution of children in this study across sociodemographic
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characteristics as well as across measures of anthropometric failure. In this study, 15% of children were
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stunted, 21% were wasted, and 26% were underweight. The prevalence of anthropometric failure was
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greater in poorer households than in wealthier households. For example, the prevalence of stunting,
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wasting, and underweight among the lowest wealth quintile was 19%, 26%, and 35%, respectively,
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whereas it was 10%, 17%, and 18% in the highest wealth quintile, respectively. Among children in
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urban locations, the prevalence of stunting was 10%. In contrast, the prevalence of stunting was 15%
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among rural children and 29% among estate children.
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Table 2 presents the average child dietary diversity score and percent of children not meeting
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the minimum dietary diversity requirement across sociodemographic characteristics. Overall, only 9%
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of children experienced inadequate dietary diversity in the previous 24 hours though 22% of children
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aged 6 to 12 months had inadequate dietary diversity and 20% of children living on estates also
213
suffered from inadequate dietary diversity. The data indicated that child dietary diversity score was
214
inversely correlated with mother's education and household wealth quintile. 8
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Results from the linear regression analyses found that child dietary diversity was positively
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associated with HAZ (b = 0.02, se = 0.01, p-value = 0.04), but not with WHZ or WAZ, while adjusting
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for additional explanatory factors (Table 3). Adjusted odds-ratios from the logistic regression analyses
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indicated no relationships between child dietary diversity and anthropometric failure (Table 4). Having
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been breastfed in the past 24 hours was negatively associated with HAZ and WAZ, but was not
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associated with WHZ nor with the risk of anthropometric failure. Having ever consumed thriposha
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seemed to act as an indicator of anthropometric failure. Although low birthweight was associated with
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each measure of anthropometric status as well as with anthropometric failure, none of the other child
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health factors were associated with child growth with one exception; having been de-wormed in the
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past 6 months was positively associated with HAZ.
225
Several household factors were associated with anthropometric status and failure, however. For
226
example, greater household size was associated with worse outcomes across all six anthropometric
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measures as was household receipt of food aid from the government and living in the estate sector.
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Although higher household wealth quintile was generally associated with a lower risk of being stunted,
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wasted, and underweight, separately, maternal education was not uniformly associated with
230
anthropometric status nor anthropometric failure.
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Regression analyses stratified by child age provided a slightly different set of results. Among
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children aged 6 to 12 months, child dietary diversity score was not associated with HAZ nor WAZ, but
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was negatively associated with WHZ (Table 5). At the same time, meeting the minimum meal
234
frequency was negatively associated with WAZ and WHZ for children in this age category. Separately,
235
among children aged 12+ to 23 months, there were no associations between child dietary diversity and
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anthropometric status nor between minimum meal frequency and anthropometric status. However,
237
child dietary diversity score was positively associated with anthropometric status for children 24
238
months and older (e.g., for HAZ, b = 0.03, s.e., = 0.01, and p = 0.02). Sensitivity analyses assessing
239
the associations between each of the seven individual food groups and anthropometric status in separate 9
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models did not indicate any clear patterns of important food group consumption and most associations
241
were not statistically significant (Supplemental Table 1).
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DISCUSSION
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This study presents initial evidence that child dietary diversity is positively associated with
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anthropometric status for children aged 24 months through 59 months in Sri Lanka even when
245
adjusting for several other child and household factors. As most past studies in this area have solely
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focused on children under two years of age, this novel finding adds to the literature on the potential
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importance of dietary diversity for growth among pre-school aged children. The current finding is
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similar to results from a Cambodian study showing an association between child dietary diversity and
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stunting among 12 to 59 months old children (44) and a study from India indicating that dietary
250
diversity was a strong risk factor for child stunting among infants and young children (21). However,
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these results are in contrast to findings from another Cambodian study indicating no association
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between household dietary diversity and stunting and wasting among children under 5 years old (45).
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Important to note is that results from these other studies were based on a wide age range of infants and
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young children and not just on children aged 2 and older. Any national efforts in Sri Lanka to increase
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dietary diversity for children aged 2 to 5 years may positively impact child growth though further
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research assessing evidence of causality between dietary diversity and child growth is needed.
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The lack of associations between child dietary diversity and anthropometric status and failure
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among children aged 12+ months to less than 24 months in this study supports similar findings from
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past research on Sri Lankan children aged 9-23 months in 2006/07 and Sri Lankan children aged 6 to
260
23 months in 2009 across 13 districts (25). The present results differ, however, from an earlier multi-
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country study finding a positive relationship between child dietary diversity and HAZ among children
262
aged 6-23 months (19), and from a more recent study on 6 to 18 month old children in Zambia where
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child dietary diversity was positively associated with length-for-age z-score (20). Distal risk factors
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may be more important for child growth during this development period as neither dietary diversity nor 10
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minimum meal frequency were associated with anthropometric outcomes for this age group.
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Alternatively, children in this age group who meet the minimum meal frequency may not always
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actually eat sufficient quantities of food. It may be easier for a mother to know how often the child eats
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rather than carefully observe the quantity of food a child eats, particularly if the mother is not fully-
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engaged in encouraging the child to eat the food.
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Finally, the novel findings of a negative association between dietary diversity and WHZ and
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between minimum meal frequency and WAZ and WHZ among children aged 6 to 12 months in Sri
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Lanka deserve further research attention both in-country and also via replication studies in other
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contexts. Interacting dynamics between risk factors may combine to affect child growth in different
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ways among children who are newest to complementary feeding practices. If children in this youngest
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age group are experiencing new reductions in breastfeeding while not consuming sufficient calories via
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complementary foods, then they may experience short-term undernutrition and weight loss.
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When comparing results from this study with prior work, it is important to keep in mind that
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results may differ due to the type of data collected and how data are analysed (e.g., whether household
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or child dietary diversity is measured, what is the recall time frame, which food groups are assessed
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and included in the score, which additional factors are included in regression analyses, which growth
281
outcomes are assessed, and whether analyses are stratified by child age group). Yet, the positive
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association between anthropometric status and dietary diversity among children aged 2 to 5 years in Sri
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Lanka and continued evidence of strong associations between anthropometric status/failure and factors
284
such as birthweight, household wealth, and location among infants and young children in Sri Lanka
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support past work suggesting that a combined approach to addressing growth among infants and young
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children is needed through both poverty alleviation efforts and nutrition interventions (46, 47). At the
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same time, future research should examine the overlapping roles of dietary diversity consumption,
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minimum meal frequency, specific food group consumption, and sufficient energy intake on child
289
anthropometric status and failure in Sri Lanka (48). In addition, long-term nutrient supplementation 11
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studies including quantity and frequency measures are also needed (49) though some recent work has
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shown insignificant impact (50-52). Effects of supplementation may depend on the type and frequency
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of intervention as well as other factors (53-56). Finally, studies assessing how these nutrition-related
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factors interact with child health and disease issues to impact growth are also needed.
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Interpretation of our findings is subject to several limitations. First, causality cannot be assessed
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because the data are cross-sectional. Second, other unmeasured confounding factors could have
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influenced the results (e.g., maternal knowledge of child nutrition and feeding practices (57, 58)).
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Third, no contextual variables were included. For example, some locations may have less access to
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healthcare resources or reduced access to diverse foods. In addition, other measures of dietary diversity
299
(e.g., in the past 30 days) were not available nor were detailed measures of chronic household food
300
insecurity. Finally, future research may want to assess whether the relationship between child dietary
301
diversity and child growth differs for children at different points along the standardized growth
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spectrum (59).
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CONCLUSIONS
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Although child dietary diversity was associated with HAZ scores for children aged 6 to less
305
than 60 months in Sri Lanka, it was not associated with anthropometric failure for this population.
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When the population was stratified by age, child dietary diversity remained positively associated with
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anthropometric status among children aged 2 to 5 years in Sri Lanka. However, it was not associated
308
with anthropometric status among children aged 12 to 24 months and displayed mixed associations
309
with HAZ, WAZ, and WHZ among infants aged 6 to 12 months old. In contrast, several distal factors
310
were strongly associated with various anthropometric indicators for all children. Thus, improving
311
anthropometric status and reducing anthropometric failure may require a combination of proximal
312
interventions (e.g., offering increased long-term accessibility to a diversity of foods especially among
313
children aged two years and older) and distal interventions (e.g., programs to improve household
314
socioeconomic status and programs to reduce risk of low birthweight). In the long-run, continued 12
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economic growth at the national level may help to decrease overall poverty and thus reduce child
316
undernutrition and growth failure for all age groups. However, such change will take decades, during
317
which generations of Sri Lankans may fail to achieve healthy child growth. Thus, programs to assist
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households with young children to access sufficient, high quality, and nutrient-rich food and healthcare
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should continue.
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ACKNOWLEDGEMENTS Conflict of Interest Statement The authors have no conflicts of interest. Funding Statement This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
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Table 1. Distribution of children aged 6 months to < 60 months in Sri Lanka in 2012 across child and household characteristics and anthropometric failure. n % % stunted % wasted % underweight All children 7303 100 15 21 26 Child sex Female 3635 50 14 20 27 Male 3668 50 15 22 26 Child age *** *** *** 6.0-12.0 months 702 10 8 12 13 12.01-23.99 months 1583 22 16 18 24 24.01-36.99 months 1859 25 15 22 27 37.01-48.99 months 1768 24 15 24 30 49.01-59.99 months 1391 19 16 24 30 Child low birthweight *** *** *** No 5834 82 12 17 21 Yes 1310 18 27 36 47 Child had breastfed in past 24 hours * ** *** No 3336 46 16 23 29 Yes 3900 54 14 20 24 Child had diarrhea in past 2 weeks No 6718 92 15 21 26 Yes 572 8 16 24 27 Child had illness in past 2 weeks No 5093 70 14 21 26 Yes 2204 30 15 22 27 Child had been dewormed in past 6 months *** * No 2125 29 14 18 24 Yes 5148 71 15 22 27 Child had ever consumed thriposha *** *** *** No 1331 18 6 7 8 Yes 5972 82 17 24 30 Child was currently anaemic No 5990 85 15 21 26 Yes 1063 15 15 20 25 Mother's education *** *** *** 0-5 years 394 6 25 24 37 6-10 years 1624 24 17 23 30 11-13 years 4540 66 13 21 24 14-16 years 319 5 10 13 17 Household size *** *** 3 members or less 1889 26 12 19 22 4-5 members 4204 58 15 21 27 6+ members 1210 17 17 22 29 Household received food aid *** *** *** No 2632 36 10 16 18 Yes 4671 64 17 24 30 Household wealth quintile *** *** *** Lowest quintile 1461 20 19 26 35 22
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493 494 495 496
2nd 1491 20 17 22 30 3rd 1432 20 15 20 26 4th 1479 20 12 19 21 Highest quintile 1440 20 10 17 18 Household location *** ** *** Estate 145 2 29 21 39 Rural 6290 86 15 22 27 Urban 868 12 10 17 18 * p< .05; ** p< .01; *** p< .001 Note: P-value indicators based on chi-square test of differences in growth failure outcomes across categories within one explanatory variable.
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Table 2. Dietary diversity across child and household characteristics among children aged 6 months to < 60 months in Sri Lanka. Mean child dietary % with inadequate diversity score SD dietary diversity All children 5.2 1.2 9 Child sex Female 5.2 1.2 9 Male 5.3 1.2 8 Child age *** 6.0-12.0 months 4.6 1.2 22 12.01-23.99 months 5.2 1.6 9 24.01-36.99 months 5.4 1.3 7 37.01-48.99 months 5.4 1.1 6 49.01-59.99 months 5.3 1.2 7 Child low birthweight No 5.3 1.2 8 Yes 5.2 1.3 9 Child had breastfed in past 24 hours *** No 5.3 1.2 7 Yes 5.2 1.3 10 Child had diarrhea in past 2 weeks *** No 5.3 1.2 8 Yes 5.0 1.4 15 Child had illness in past 2 weeks No 5.3 1.2 8 Yes 5.2 1.3 10 Child had been dewormed in past 6 months *** No 4.9 1.4 15 Yes 5.4 1.2 6 Child had ever consumed thriposha No 5.2 1.2 8 Yes 5.2 1.2 9 Child was currently anaemic *** No 5.3 1.2 8 Yes 5.1 1.3 11 Mother's Education *** 0-5 years 4.8 1.4 19 6-10 years 5.0 1.3 13 11-13 years 5.3 1.2 6 14+ years 5.7 1.1 3 Household Size 3 members or less 5.3 1.3 9 4-5 members 5.2 1.2 8 6+ members 5.2 1.3 10 Household Received Food Aid No 5.3 1.2 8 24
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499 500 501 502 503 504 505 506
Yes 5.2 1.3 9 Household Wealth Quintile *** Lowest quintile 4.9 1.4 15 2nd 5.1 1.3 11 3rd 5.2 1.2 8 4th 5.4 1.1 5 Highest quintile 5.5 1.1 4 Household Location *** Estate 4.6 1.5 20 Rural 5.2 1.2 9 Urban 5.4 1.2 6 * p< .05; ** p< .01; *** p< .001 Note: P-value indicators based on chi-square test of differences in inadequate dietary diversity prevalence across categories within one explanatory variable.
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509 510
Table 3. Multilevel multivariable linear regression estimates of the association between indicators of anthropometric status and dietary diversity among children aged 6 months to <60 months in Sri Lanka in 2012 (n = 6402). HAZ WAZ WHZ b SE p-value b SE p-value b SE p-value Child Factors Dietary diversity score 0.02 0.01 0.04 0.01 0.01 0.26 -0.002 0.01 0.82 0.02 Breastfed in past 24 hours (vs. not) -0.09 0.03 0.004 -0.07 0.03 -0.03 0.03 0.30 Ever consumed thriposha supplement (vs. not) -0.42 0.04 <.001 -0.62 0.03 <.001 -0.55 0.03 <.001 <.001 Low birthweight (vs. not) -0.52 0.03 -0.60 0.03 <.001 -0.45 0.03 <.001 Diarrhea in past 2 weeks (vs. not) -0.01 0.05 0.86 -0.04 0.05 0.35 -0.06 0.05 0.20 0.49 Ill in past 2 weeks (vs. not) -0.01 0.03 0.71 -0.02 0.03 -0.02 0.03 0.41 0.64 Dewormed in past 6 months (vs. not) 0.08 0.03 0.02 0.01 0.03 -0.03 0.03 0.27 Currently anaemic (vs. not) -0.05 0.04 0.20 -0.03 0.03 0.39 -0.003 0.03 0.92 Male (vs. female) 0.004 0.03 0.89 0.03 0.02 0.18 -0.01 0.02 0.58 Aged 12.01-23.99 months (vs. 6-12 months) -0.51 0.05 <.001 -0.33 0.05 <.001 -0.21 0.05 <.001 <.001 <.001 Aged 24.01-36.99 months (vs. 6-12 months) -0.58 0.06 -0.50 0.05 -0.39 0.05 <.001 <.001 Aged 37.01-48.99 months (vs. 6-12 months) -0.66 0.06 -0.56 0.05 <.001 -0.44 0.06 <.001 <.001 Aged 49.01-59.99 months (vs. 6-12 months) -0.65 0.06 -0.63 0.06 <.001 -0.50 0.06 <.001 Household Factors Maternal education of 6-10 years (vs. 0-5 years) 0.11 0.06 0.07 0.07 0.06 0.19 0.002 0.06 0.97 Maternal education of 11-13 years (vs. 0-5 years) 0.12 0.06 0.04 0.08 0.06 0.13 0.01 0.06 0.80 Maternal education of 14+ years (vs. 0-5 years) 0.22 0.08 0.01 0.22 0.08 0.005 0.14 0.08 0.09 Household had 4-5 members (vs. 3) -0.08 0.03 0.009 -0.10 0.03 0.001 -0.07 0.03 0.008 <.001 Household had 6+ members (vs. 3) -0.15 0.04 <.001 -0.16 0.04 -0.10 0.04 0.007 Received food aid (vs. not) -0.13 0.03 <.001 -0.19 0.03 <.001 -0.17 0.03 <.001 2nd wealth quintile (vs. lowest) 0.08 0.04 0.08 0.09 0.04 0.03 0.07 0.04 0.09 3rd wealth quintile (vs. lowest) 0.12 0.05 0.01 0.12 0.04 0.006 0.09 0.04 0.05 <.001 4th wealth quintile (vs. lowest) 0.21 0.05 <.001 0.19 0.05 0.11 0.05 0.015 Highest wealth quintile (vs. lowest) 0.24 0.05 <.001 0.25 0.05 <.001 0.18 0.05 <.001 <.001 Estate location (vs. urban) -0.45 0.12 <.001 -0.47 0.11 -0.32 0.12 0.006 Rural location (vs. urban) -0.14 0.05 0.003 -0.19 0.05 <.001 -0.17 0.05 <.001 Notes: HAZ = height-for-age z-score; WAZ = weight-for-age z-score; WHZ = weight-for-height z-score. All models included all variables shown above plus district dummy variables. 26
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Table 4. Multivariable multilevel logistic regression estimates of the association between indicators of anthropometric failure and dietary diversity among children aged 6 to <60 months in Sri Lanka in 2012 (n=6402).
Child Factors Dietary diversity score Breastfed in past 24 hours (vs. not) Ever consumed thriposha supplement (vs. not) Low birthweight (vs. not) Diarrhea in past 2 weeks (vs. not) Ill in past 2 weeks (vs. not) Dewormed in past 6 months (vs. not) Currently anaemic (vs. not) Male (vs. female) Aged 12.01-23.99 months (vs. <12 months) Aged 24.01-36.99 months (vs. <12 months) Aged 37.01-48.99 months (vs. <12 months) Aged 49.01-59.99 months (vs. <12 months) Household Factors Maternal education of 6-10 years (vs. 0-5 years) Maternal education of 11-13 years (vs. 0-5 years) Maternal education of 14+ years (vs. 0-5 years) Household had 4-5 members (vs. 3) Household had 6+ members (vs. 3) Received food aid (vs. not) 2nd wealth quintile (vs. lowest) 3rd wealth quintile (vs. lowest) 4th wealth quintile (vs. lowest) Highest wealth quintile (vs. lowest) Estate location (vs. urban) Rural location (vs. urban) 513
AOR
Stunting (95% CI)
0.97 1.03 2.66 2.67 1.00 1.04 0.90 1.06 1.08 2.07 1.78 1.97 1.99
(0.91, 1.03) (0.86, 1.23) (2.01, 3.51) (2.27, 3.14) (0.76, 1.32) (0.88, 1.22) (0.75, 1.08) (0.86, 1.31) (0.93, 1.25) (1.46, 2.91) (1.24, 2.56) (1.35, 2.88) (1.34, 2.95)
0.37 0.77 <.001 <.001 0.97 0.66 0.27 0.59 0.30 <.001 0.002 <.001 0.001
0.99 (0.94, 1.05) 1.05 (0.89, 1.23) 3.40 (2.65, 4.37) 2.67 (2.31, 3.10) 1.16 (0.91, 1.48) 1.06 (0.92, 1.22) 1.10 (0.93, 1.30) 1.04 (0.86, 1.25) 1.15 (1.01, 1.31) 1.31 (0.96, 1.78) 1.82 (1.33, 2.49) 1.95 (1.40, 2.71) 1.99 (1.41, 2.80)
0.74 0.57 <.001 <.001 0.22 0.43 0.29 0.72 0.03 0.09 <.001 <.001 <.001
0.80 0.74 0.72 1.28 1.43 1.31 0.85 0.82 0.74 0.64 2.76 1.32
(0.60, 1.08) (0.55, 1.00) (0.44, 1.18) (1.07, 1.53) (1.13, 1.81) (1.10, 1.56) (0.67, 1.08) (0.64, 1.06) (0.57, 0.97) (0.48, 0.87) (1.58, 4.80) (0.99, 1.76)
0.15 0.047 0.19 0.008 0.003 0.003 0.18 0.13 0.03 0.004 <.001 0.06
1.04 (0.78, 1.39) 1.08 (0.81, 1.43) 0.70 (0.44, 1.12) 1.15 (0.98, 1.34) 1.25 (1.01, 1.53) 1.26 (1.08, 1.47) 0.95 (0.77, 1.19) 0.94 (0.74, 1.18) 0.92 (0.72, 1.17) 0.84 (0.65, 1.09) 1.59 (0.87, 2.89) 1.20 (0.94, 1.54)
0.79 0.61 0.14 0.08 0.04 0.004 0.68 0.59 0.50 0.19 0.13 0.14
p-value
AOR
Wasting (95% CI)
p-value
Underweight (95% CI)
p-value
0.98 1.07 4.05 3.33 0.98 1.09 0.89 1.10 1.01 2.02 2.48 2.86 2.90
(0.93, 1.03) (0.92, 1.25) (3.17, 5.16) (2.88, 3.85) (0.78, 1.25) (0.95, 1.25) (0.76, 1.04) (0.92, 1.32) (0.90, 1.15) (1.50, 2.72) (1.83, 3.34) (2.08, 3.95) (2.08, 4.05)
0.45 0.40 <.001 <.001 0.89 0.21 0.14 0.30 0.84 <.001 <.001 <.001 <.001
0.94 0.92 0.84 1.34 1.45 1.44 0.85 0.83 0.62 0.59 2.99 1.45
(0.71, 1.23) (0.71, 1.21) (0.55, 1.28) (1.15, 1.56) (1.19, 1.78) (1.24, 1.68) (0.69, 1.04) (0.67, 1.04) (0.49, 0.79) (0.46, 0.76) (1.71, 5.24) (1.13, 1.89)
0.62 0.56 0.41 <.001 <.001 <.001 0.12 0.10 <.001 <.001 <.001 0.003
AOR
Notes: AOR = Adjusted Odds-Ratio. All models included all variables shown above plus district dummy variables.
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516 517 518 519 520
Table 5. Multilevel multivariable linear regression estimates of the association between indicators of anthropometric status and dietary diversity among children aged 6 months to <60 months in Sri Lanka in 2012. HAZ WAZ WHZ b SE p-value b SE p-value b SE p-value Children aged 6 to 12 months (n = 600) Dietary diversity score 0.02 0.03 0.63 -0.03 0.03 0.201 -0.07 0.03 0.008 Meets minimum meal frequency -0.04 0.12 0.72 -0.25 0.09 0.007 -0.29 0.09 0.002 Children aged 12+months to <24 months (n=1363) Dietary diversity score 0.003 0.03 0.91 -0.02 0.02 0.61 -0.02 0.02 0.48 Meets minimum meal frequency -0.04 0.07 0.56 -0.05 0.06 0.39 -0.04 0.06 0.48 Children aged 24 months and older (n=4409) Dietary diversity score 0.03 0.01 0.015 0.03 0.01 0.006 0.02 0.01 0.058 Notes: HAZ = height-for-age z-score; WAZ = weight-for-age z-score; WHZ = weight-for-height z-score. All models also included the same factors displayed in Table 3.
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S0899-9007(18)30179-5 https://doi.org/10.1016/j.nut.2018.03.049 NUT 10182
To appear in:
Nutrition
Received date: Revised date: Accepted date:
4-10-2017 12-3-2018 22-3-2018
Please cite this article as: Jessica M. Perkins, Renuka Jayatissa, S.V. Subramanian, Dietary diversity and anthropometric status and failure among infants and young children in Sri Lanka, Nutrition (2018), https://doi.org/10.1016/j.nut.2018.03.049. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Dietary Diversity and Anthropometric Status and Failure among Infants and Young Children in Sri Lanka Jessica M. Perkins, PhD1, Renuka Jayatissa, MD2, S.V.Subramanian, PhD*3 1
Department of Human and Organizational Development, Peabody College, Vanderbilt University; Vanderbilt Institute of Global Health, Vanderbilt University Medical Center 2
Nutrition Department, Medical Research Institute, Ministry of Health Sri Lanka
3
Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Population Health
*Correspondence Department of Social and Behavioral Sciences Harvard Chan School of Public Health Kresge Building 7th Floor, 716 Boston, Massachusetts 02115-6096 Phone: 6174326299 [email protected] Running Head Dietary diversity and anthropometric status in Sri Lanka Conflict of Interest Statement The authors have no conflicts of interest. Contributor statement: JMP, SVS, and RJ conceptualized the study. JMP and SVS designed the study. JMP wrote the first draft. JMP, SVS, RJ provided critical revisions. SVS provided study oversight. All authors approve the final version of the submitted manuscript.
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Highlights
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ABSTRACT
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Objective: We investigate the association between child dietary diversity and anthropometric status
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and failure in Sri Lanka while accounting for other child and household factors by employing
45
multivariable logistic and linear regression analyses.
46
Research Methods & Procedures: Using a nationally representative survey of children aged 6-59
47
months, child dietary diversity was based on 24-hour recall of child's food intake across seven food
48
groups. Minimum dietary diversity was a score of four or above. Anthropometric status (height-for-age,
49
weight-for-age, and weight-for-height z-scores) and anthropometric failure (stunting, wasting, and
50
underweight) were calculated.
51
Results The prevalence of stunting, wasting, and underweight was 15%, 21%, and 26%, respectively.
52
The prevalence of inadequate dietary diversity was 9%. Although child dietary diversity was positively
53
associated with height-for-age (b = 0.02, se = 0.01, p-value = 0.04), it was not associated with any
54
indicator of anthropometric failure. However, low birthweight, wealth, and location were strong risk
55
factors for anthropometric status and failure. Analyses stratified by child age indicated that dietary
56
diversity was positively associated with anthropometric status for children aged 24+ to 59 months (e.g.,
57
for HAZ, b = 0.03, s.e., = 0.01, and p = 0.02). Mixed associations were found for children 6 to 12
58
months old, and there were no associations for children 12+ to 24 months old.
59
Conclusions Child dietary diversity predicted anthropometric status among children aged 24+months.
60
Interventions addressing both proximal and distal risk factors for anthropometric status may be
61
necessary in Sri Lanka to address anthropometric failure among infants and young children.
Anthropometric failure remains in Sri Lanka among infants and young children. Dietary diversity was associated with growth among children aged 24-to-59 months. Mixed associations for ages 6 to 12 months, and none for ages 12 to 24 months. Low birthweight and household wealth predict anthropometric failure. Nutrition + distal interventions are needed to improve child growth in Sri Lanka.
62 63
Keywords: Stunting; Wasting; Underweight; Dietary Diversity; Undernutrition; Complementary
64
Feeding; HAZ; WHZ; WAZ
2
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65 66
INTRODUCTION The long-term development, health, and economic consequences of anthropometric failure are
67
well known (1-6). Although there are many economic, social, environmental, and illness-related factors
68
that lead to anthropometric failure among children (7-11), consumption of sufficient nutritious food is a
69
basic critical element to ensure healthy child growth (2, 12). The World Health Organization therefore
70
recommends that a diverse diet be provided to ensure adequate intake of necessary energy, minerals,
71
vitamins, proteins, and fats when introducing complementary feeding for infants and young children
72
six months and older (13, 14).
73
Dietary diversity is defined as “the number of different foods or food groups consumed over a
74
given reference period” (15). According to the World Health Organization, the typical food groups
75
making up a diverse diet are grains/roots/tubers, legumes/nuts, dairy (milk, yogurt, cheese and other
76
milk products), flesh foods (meat, fish, poultry and liver/organ meats), eggs, vitamin A rich fruits and
77
vegetables, and other fruits and vegetables (14). Consuming foods from less than four of these groups
78
in the past 24 hours represents consuming less than the minimum diverse diet, an indicator associated
79
with diet quality for both breastfed and non-breastfed children aged 6 months and older (14). Some
80
studies on dietary diversity calculate a summary score include fats/oils as an 8th food group (16-18)
81
while other studies exclude it.
82
Broad evidence from low- and middle-income countries of the extent to which dietary diversity
83
impacts child anthropometric status is scant (15), though one study found direct positive associations
84
between dietary diversity and standardized height-for-age scores among children aged 6 to 23 months
85
in seven low-income countries using Demographic and Health Survey data from 1999-2001 (19). More
86
recently a study on children aged 6 to 18 months in Zambia found that dietary diversity was positively
87
associated with length-for-age and weight-for-length standardized scores (20). Further, a study among
88
Indian children aged 6-59 months found that a low dietary diversity score was one of the main
89
predictors of child stunting and underweight (21). 3
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90
Despite Sri Lanka’s ongoing growth and development in many economic and health sectors
91
over the past several decades (22), and the introduction of national campaigns for food and
92
micronutrient supplementation for infants and young children (23), anthropometric failure among
93
infants and young children in Sri Lanka is still a major public health concern (22, 24, 25). The national
94
prevalence of child stunting, wasting, and underweight in 2006-07 was 17%, 14%, and 21%,
95
respectively (25). Around the same time period, 29% of children aged 6 to 23 months did not meet
96
minimum dietary diversity requirements (26).
97
The extent to which dietary diversity is associated with anthropometric status and failure among
98
infants and young children up to five years old in Sri Lanka is largely unknown. Understanding the
99
independent association between dietary diversity and child anthropometry after accounting for
100
potential confounding and mediating factors such as socioeconomic status, household wealth, low birth
101
weight, and child health is important for identifying nutrition-related intervention priorities. Thus,
102
examining this association among infants and young children in Sri Lanka using recent nationally
103
representative data would provide critical information for the development of future interventions and
104
national policies targeting child growth. To address this knowledge gap, this study assessed the extent
105
to which child dietary diversity is associated with anthropometric status and failure among a nationally
106
representative sample of children aged 6-59 months in Sri Lanka while accounting for several other
107
potential explanatory factors.
108
METHODS
109
Data Source
110
This study used data from the 2012 National Nutrition and Micronutrient Survey, which took
111
place in all 25 districts in Sri Lanka and targeted 7500 households where at least one child aged 6-59
112
months resided. A multi-stage cluster sampling procedure was used to identify targeted households. For
113
the first stage, 30 divisions per district were identified using a population proportion to sampling
114
technique. Thus, there were a total of 750 clusters also known as primary sampling units (PSUs). 4
Page 4 of 28
115
Within each PSU, 10 households with at least one age eligible child were randomly selected. A
116
household was defined as a group of people who share a common cooking pot. If there was more than
117
one child present, then the targeted child was randomly selected for participation. For further
118
information on study design, see the 2012 Report (24).
119
The mother (or the main guardian) of the child selected as the study participant responded to a
120
series of close-ended questions regarding the health and diet of that child as well as to questions about
121
household structure, resources, and other factors. In addition, anthropometric measurements and
122
biomarker data were collected from the selected child. All data were collected during weekdays. Ten
123
percent of the sample was revisited to validate the responses. A total of 7306 children completed
124
interviews and measurements with a 97.4% response rate. See the 2012 report for further details on
125
sample size (24). The final analytical sample for this study included 7303 children as two children were
126
excluded due to mislabeled data, and one child was excluded for having implausible standardized child
127
growth values (27).
128
Approval for this study was obtained from the Ethical Review Committee of the MRI, Ministry
129
of Health. In addition, informed consent was obtained from community representatives, and written
130
informed consent was obtained from the mother (or main guardian) of the selected children.
131
Outcome variables
132
Trained field interview teams obtained measurements of child weight in kilograms and height
133
(or recumbent length if child was under 2 years old) in centimeters and collected data on child age. To
134
assess anthropometric status, standardized height-for-age (HAZ) scores, weight-for-age (WAZ) sores,
135
and weight-for-height (WHZ) scores were calculated according to WHO child growth standards (28).
136
There were no missing data. In addition, three binary indicators (stunting, wasting, and underweight) of
137
anthropometric failure were calculated (28). A HAZ score below -2 SD from the median of the
138
reference population indicates stunting, a condition reflecting the cumulative effect of chronic
139
undernutrition. A WHZ score below -2 SD from the median of the reference population indicates 5
Page 5 of 28
140
wasting, a condition reflecting the effect of short term undernutrition. Finally, a WAZ score below -2
141
SD from the median of the reference population indicates that the child is underweight.
142
Main explanatory variables
143
Child dietary diversity score was derived from maternal/guardian’s recall of child’s preceding
144
24-hour dietary intake. Participants were told "Please describe anything that your child age yesterday
145
during the day or night, whether at home or outside the home." They were then asked about intake
146
across several food categories. Dietary diversity score was derived from responses indicating
147
consumption of food from seven specific food groups (or lack of consumption across these groups)
148
(29). These groups included grains/roots/tubers (e.g., bread, rice, other food made from grains, white
149
potatoes, white yams, manioc, cassava, any other foods made from roots), legumes/nuts (e.g., beans,
150
peas, lentils, nuts, peanuts, coconut), dairy products (e.g., cheese, curd, other milk products, milk
151
liquid/powder), flesh foods (e.g., liver, kidney, hearts, other organ meats, chicken, beef, pork, lamb,
152
goat, duck, fresh or dried fish, shellfish, seafood), eggs, vitamin A rich foods (e.g., carrots, squash,
153
sweet potatoes that are yellow/orange, dark green leafy vegetables, ripe mangos or papayas), and other
154
fruits and vegetables (e.g., bananas, grapes, apples, oranges, tomatoes). Consumption of each food
155
group is worth one point and zero otherwise with seven as a maximum score. A score less than four
156
indicated that a child did not meet the minimum dietary diversity requirements (14). There were no
157
missing data.
158
Information regarding minimum meal frequency was also collected for children under 24
159
months of age as it is considered an important complementary feeding factor representative of diet
160
quality for this young age group (14). It is based on child age, the number of times children have eaten
161
in the past 24 hours, and whether they are breastfed. The minimum number of times is defined as two
162
times for breastfed infants 6-8 months old, three times for breastfed children 9-23 months old, and four
163
times for non-breastfed children 6-23 months old. This variable was used in age-stratified analyses only
164
(as explained in the statistical analysis section). 6
Page 6 of 28
165 166
Other explanatory factors We included information on several child factors as well as socioeconomic and demographic
167
household characteristics that are associated with both dietary diversity and anthropometric status (19,
168
30-39). Child sex and child age in months were recorded (with age grouped as 6-12, 13-23, 24-36, 37-
169
48, and 49-59 months). A binary low birthweight indicator for children born <2500 grams (2.2%
170
missing) was based on data obtained from mandatory child development cards issued by a delivering
171
hospital where almost 100% of births take place (40). In addition, data were collected on whether child
172
had been breastfed in the last 24 hours (missing < 1%). Two separate binary variables represented
173
whether the child had diarrhea in the past two weeks and whether the child had an illness with a cough
174
in the past two weeks (missing < 1%). Whether the child had been given deworming treatment in the
175
past six months (missing < 1%) was also indicated. A yes/no response was recorded for whether the
176
child had ever been given thriposha, which is a fortified food supplement containing a mix of protein,
177
carbohydrates, and micronutrients provided as part of a national program on supplementary feeding to
178
address undernutrition (41). Finally, presence of anaemia in the child was recorded as having a
179
haemoglobin level of less than 11.0 g/dl (3.4% missing). Mothers/guardians reported years of their
180
completed education (5.8% missing), the total number of household members, and whether the
181
household had received food aid from the government. Household wealth quintile was based on a
182
compilation of several household resources using principal components analysis (42). Household
183
location was coded as rural vs. urban vs. estate where estate represents households living and working
184
on tea estates. (If percent of missing responses is not indicated, then zero responses were missing.)
185
Statistical analysis
186
We first calculated the percent of children experiencing anthropometric failure as well as the
187
average dietary diversity score across sub-categories of child and household factors. We then used
188
multivariable multilevel regression models, which accounted for the clustering of observations at the
189
PSU level, to estimate the relationship between the continuous child dietary diversity score and the 7
Page 7 of 28
190
outcomes. We fit separate linear regression models for the three continuous measures of
191
anthropometric status (HAZ, WAZ, and WHZ), and we fit separate logistic regression models for the
192
three binary indicators of anthropometric failure (stunting, wasting, and underweight). These models
193
also simultaneously adjusted for the additional factors described above in the 'Other explanatory
194
variables' section and included dummy variables for districts. We also assessed whether linear
195
regression estimates differed when the data were stratified by child age (with sub-groups representing 6
196
to 12 months vs. 12+ months to less than 24 months vs. 24 months to less than 60 months) as the
197
impact of diverse food consumption may differ across critical growth points. For the first two age
198
groups, the minimum meal frequency variable was also included. STATA version 15 was used for
199
analyses (43).
200
RESULTS
201
Table 1 presents the distribution of children in this study across sociodemographic
202
characteristics as well as across measures of anthropometric failure. In this study, 15% of children were
203
stunted, 21% were wasted, and 26% were underweight. The prevalence of anthropometric failure was
204
greater in poorer households than in wealthier households. For example, the prevalence of stunting,
205
wasting, and underweight among the lowest wealth quintile was 19%, 26%, and 35%, respectively,
206
whereas it was 10%, 17%, and 18% in the highest wealth quintile, respectively. Among children in
207
urban locations, the prevalence of stunting was 10%. In contrast, the prevalence of stunting was 15%
208
among rural children and 29% among estate children.
209
Table 2 presents the average child dietary diversity score and percent of children not meeting
210
the minimum dietary diversity requirement across sociodemographic characteristics. Overall, only 9%
211
of children experienced inadequate dietary diversity in the previous 24 hours though 22% of children
212
aged 6 to 12 months had inadequate dietary diversity and 20% of children living on estates also
213
suffered from inadequate dietary diversity. The data indicated that child dietary diversity score was
214
inversely correlated with mother's education and household wealth quintile. 8
Page 8 of 28
215
Results from the linear regression analyses found that child dietary diversity was positively
216
associated with HAZ (b = 0.02, se = 0.01, p-value = 0.04), but not with WHZ or WAZ, while adjusting
217
for additional explanatory factors (Table 3). Adjusted odds-ratios from the logistic regression analyses
218
indicated no relationships between child dietary diversity and anthropometric failure (Table 4). Having
219
been breastfed in the past 24 hours was negatively associated with HAZ and WAZ, but was not
220
associated with WHZ nor with the risk of anthropometric failure. Having ever consumed thriposha
221
seemed to act as an indicator of anthropometric failure. Although low birthweight was associated with
222
each measure of anthropometric status as well as with anthropometric failure, none of the other child
223
health factors were associated with child growth with one exception; having been de-wormed in the
224
past 6 months was positively associated with HAZ.
225
Several household factors were associated with anthropometric status and failure, however. For
226
example, greater household size was associated with worse outcomes across all six anthropometric
227
measures as was household receipt of food aid from the government and living in the estate sector.
228
Although higher household wealth quintile was generally associated with a lower risk of being stunted,
229
wasted, and underweight, separately, maternal education was not uniformly associated with
230
anthropometric status nor anthropometric failure.
231
Regression analyses stratified by child age provided a slightly different set of results. Among
232
children aged 6 to 12 months, child dietary diversity score was not associated with HAZ nor WAZ, but
233
was negatively associated with WHZ (Table 5). At the same time, meeting the minimum meal
234
frequency was negatively associated with WAZ and WHZ for children in this age category. Separately,
235
among children aged 12+ to 23 months, there were no associations between child dietary diversity and
236
anthropometric status nor between minimum meal frequency and anthropometric status. However,
237
child dietary diversity score was positively associated with anthropometric status for children 24
238
months and older (e.g., for HAZ, b = 0.03, s.e., = 0.01, and p = 0.02). Sensitivity analyses assessing
239
the associations between each of the seven individual food groups and anthropometric status in separate 9
Page 9 of 28
240
models did not indicate any clear patterns of important food group consumption and most associations
241
were not statistically significant (Supplemental Table 1).
242
DISCUSSION
243
This study presents initial evidence that child dietary diversity is positively associated with
244
anthropometric status for children aged 24 months through 59 months in Sri Lanka even when
245
adjusting for several other child and household factors. As most past studies in this area have solely
246
focused on children under two years of age, this novel finding adds to the literature on the potential
247
importance of dietary diversity for growth among pre-school aged children. The current finding is
248
similar to results from a Cambodian study showing an association between child dietary diversity and
249
stunting among 12 to 59 months old children (44) and a study from India indicating that dietary
250
diversity was a strong risk factor for child stunting among infants and young children (21). However,
251
these results are in contrast to findings from another Cambodian study indicating no association
252
between household dietary diversity and stunting and wasting among children under 5 years old (45).
253
Important to note is that results from these other studies were based on a wide age range of infants and
254
young children and not just on children aged 2 and older. Any national efforts in Sri Lanka to increase
255
dietary diversity for children aged 2 to 5 years may positively impact child growth though further
256
research assessing evidence of causality between dietary diversity and child growth is needed.
257
The lack of associations between child dietary diversity and anthropometric status and failure
258
among children aged 12+ months to less than 24 months in this study supports similar findings from
259
past research on Sri Lankan children aged 9-23 months in 2006/07 and Sri Lankan children aged 6 to
260
23 months in 2009 across 13 districts (25). The present results differ, however, from an earlier multi-
261
country study finding a positive relationship between child dietary diversity and HAZ among children
262
aged 6-23 months (19), and from a more recent study on 6 to 18 month old children in Zambia where
263
child dietary diversity was positively associated with length-for-age z-score (20). Distal risk factors
264
may be more important for child growth during this development period as neither dietary diversity nor 10
Page 10 of 28
265
minimum meal frequency were associated with anthropometric outcomes for this age group.
266
Alternatively, children in this age group who meet the minimum meal frequency may not always
267
actually eat sufficient quantities of food. It may be easier for a mother to know how often the child eats
268
rather than carefully observe the quantity of food a child eats, particularly if the mother is not fully-
269
engaged in encouraging the child to eat the food.
270
Finally, the novel findings of a negative association between dietary diversity and WHZ and
271
between minimum meal frequency and WAZ and WHZ among children aged 6 to 12 months in Sri
272
Lanka deserve further research attention both in-country and also via replication studies in other
273
contexts. Interacting dynamics between risk factors may combine to affect child growth in different
274
ways among children who are newest to complementary feeding practices. If children in this youngest
275
age group are experiencing new reductions in breastfeeding while not consuming sufficient calories via
276
complementary foods, then they may experience short-term undernutrition and weight loss.
277
When comparing results from this study with prior work, it is important to keep in mind that
278
results may differ due to the type of data collected and how data are analysed (e.g., whether household
279
or child dietary diversity is measured, what is the recall time frame, which food groups are assessed
280
and included in the score, which additional factors are included in regression analyses, which growth
281
outcomes are assessed, and whether analyses are stratified by child age group). Yet, the positive
282
association between anthropometric status and dietary diversity among children aged 2 to 5 years in Sri
283
Lanka and continued evidence of strong associations between anthropometric status/failure and factors
284
such as birthweight, household wealth, and location among infants and young children in Sri Lanka
285
support past work suggesting that a combined approach to addressing growth among infants and young
286
children is needed through both poverty alleviation efforts and nutrition interventions (46, 47). At the
287
same time, future research should examine the overlapping roles of dietary diversity consumption,
288
minimum meal frequency, specific food group consumption, and sufficient energy intake on child
289
anthropometric status and failure in Sri Lanka (48). In addition, long-term nutrient supplementation 11
Page 11 of 28
290
studies including quantity and frequency measures are also needed (49) though some recent work has
291
shown insignificant impact (50-52). Effects of supplementation may depend on the type and frequency
292
of intervention as well as other factors (53-56). Finally, studies assessing how these nutrition-related
293
factors interact with child health and disease issues to impact growth are also needed.
294
Interpretation of our findings is subject to several limitations. First, causality cannot be assessed
295
because the data are cross-sectional. Second, other unmeasured confounding factors could have
296
influenced the results (e.g., maternal knowledge of child nutrition and feeding practices (57, 58)).
297
Third, no contextual variables were included. For example, some locations may have less access to
298
healthcare resources or reduced access to diverse foods. In addition, other measures of dietary diversity
299
(e.g., in the past 30 days) were not available nor were detailed measures of chronic household food
300
insecurity. Finally, future research may want to assess whether the relationship between child dietary
301
diversity and child growth differs for children at different points along the standardized growth
302
spectrum (59).
303
CONCLUSIONS
304
Although child dietary diversity was associated with HAZ scores for children aged 6 to less
305
than 60 months in Sri Lanka, it was not associated with anthropometric failure for this population.
306
When the population was stratified by age, child dietary diversity remained positively associated with
307
anthropometric status among children aged 2 to 5 years in Sri Lanka. However, it was not associated
308
with anthropometric status among children aged 12 to 24 months and displayed mixed associations
309
with HAZ, WAZ, and WHZ among infants aged 6 to 12 months old. In contrast, several distal factors
310
were strongly associated with various anthropometric indicators for all children. Thus, improving
311
anthropometric status and reducing anthropometric failure may require a combination of proximal
312
interventions (e.g., offering increased long-term accessibility to a diversity of foods especially among
313
children aged two years and older) and distal interventions (e.g., programs to improve household
314
socioeconomic status and programs to reduce risk of low birthweight). In the long-run, continued 12
Page 12 of 28
315
economic growth at the national level may help to decrease overall poverty and thus reduce child
316
undernutrition and growth failure for all age groups. However, such change will take decades, during
317
which generations of Sri Lankans may fail to achieve healthy child growth. Thus, programs to assist
318
households with young children to access sufficient, high quality, and nutrient-rich food and healthcare
319
should continue.
13
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320 321 322 323 324 325 326 327
ACKNOWLEDGEMENTS Conflict of Interest Statement The authors have no conflicts of interest. Funding Statement This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
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Table 1. Distribution of children aged 6 months to < 60 months in Sri Lanka in 2012 across child and household characteristics and anthropometric failure. n % % stunted % wasted % underweight All children 7303 100 15 21 26 Child sex Female 3635 50 14 20 27 Male 3668 50 15 22 26 Child age *** *** *** 6.0-12.0 months 702 10 8 12 13 12.01-23.99 months 1583 22 16 18 24 24.01-36.99 months 1859 25 15 22 27 37.01-48.99 months 1768 24 15 24 30 49.01-59.99 months 1391 19 16 24 30 Child low birthweight *** *** *** No 5834 82 12 17 21 Yes 1310 18 27 36 47 Child had breastfed in past 24 hours * ** *** No 3336 46 16 23 29 Yes 3900 54 14 20 24 Child had diarrhea in past 2 weeks No 6718 92 15 21 26 Yes 572 8 16 24 27 Child had illness in past 2 weeks No 5093 70 14 21 26 Yes 2204 30 15 22 27 Child had been dewormed in past 6 months *** * No 2125 29 14 18 24 Yes 5148 71 15 22 27 Child had ever consumed thriposha *** *** *** No 1331 18 6 7 8 Yes 5972 82 17 24 30 Child was currently anaemic No 5990 85 15 21 26 Yes 1063 15 15 20 25 Mother's education *** *** *** 0-5 years 394 6 25 24 37 6-10 years 1624 24 17 23 30 11-13 years 4540 66 13 21 24 14-16 years 319 5 10 13 17 Household size *** *** 3 members or less 1889 26 12 19 22 4-5 members 4204 58 15 21 27 6+ members 1210 17 17 22 29 Household received food aid *** *** *** No 2632 36 10 16 18 Yes 4671 64 17 24 30 Household wealth quintile *** *** *** Lowest quintile 1461 20 19 26 35 22
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493 494 495 496
2nd 1491 20 17 22 30 3rd 1432 20 15 20 26 4th 1479 20 12 19 21 Highest quintile 1440 20 10 17 18 Household location *** ** *** Estate 145 2 29 21 39 Rural 6290 86 15 22 27 Urban 868 12 10 17 18 * p< .05; ** p< .01; *** p< .001 Note: P-value indicators based on chi-square test of differences in growth failure outcomes across categories within one explanatory variable.
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497 498
Table 2. Dietary diversity across child and household characteristics among children aged 6 months to < 60 months in Sri Lanka. Mean child dietary % with inadequate diversity score SD dietary diversity All children 5.2 1.2 9 Child sex Female 5.2 1.2 9 Male 5.3 1.2 8 Child age *** 6.0-12.0 months 4.6 1.2 22 12.01-23.99 months 5.2 1.6 9 24.01-36.99 months 5.4 1.3 7 37.01-48.99 months 5.4 1.1 6 49.01-59.99 months 5.3 1.2 7 Child low birthweight No 5.3 1.2 8 Yes 5.2 1.3 9 Child had breastfed in past 24 hours *** No 5.3 1.2 7 Yes 5.2 1.3 10 Child had diarrhea in past 2 weeks *** No 5.3 1.2 8 Yes 5.0 1.4 15 Child had illness in past 2 weeks No 5.3 1.2 8 Yes 5.2 1.3 10 Child had been dewormed in past 6 months *** No 4.9 1.4 15 Yes 5.4 1.2 6 Child had ever consumed thriposha No 5.2 1.2 8 Yes 5.2 1.2 9 Child was currently anaemic *** No 5.3 1.2 8 Yes 5.1 1.3 11 Mother's Education *** 0-5 years 4.8 1.4 19 6-10 years 5.0 1.3 13 11-13 years 5.3 1.2 6 14+ years 5.7 1.1 3 Household Size 3 members or less 5.3 1.3 9 4-5 members 5.2 1.2 8 6+ members 5.2 1.3 10 Household Received Food Aid No 5.3 1.2 8 24
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499 500 501 502 503 504 505 506
Yes 5.2 1.3 9 Household Wealth Quintile *** Lowest quintile 4.9 1.4 15 2nd 5.1 1.3 11 3rd 5.2 1.2 8 4th 5.4 1.1 5 Highest quintile 5.5 1.1 4 Household Location *** Estate 4.6 1.5 20 Rural 5.2 1.2 9 Urban 5.4 1.2 6 * p< .05; ** p< .01; *** p< .001 Note: P-value indicators based on chi-square test of differences in inadequate dietary diversity prevalence across categories within one explanatory variable.
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507 508
509 510
Table 3. Multilevel multivariable linear regression estimates of the association between indicators of anthropometric status and dietary diversity among children aged 6 months to <60 months in Sri Lanka in 2012 (n = 6402). HAZ WAZ WHZ b SE p-value b SE p-value b SE p-value Child Factors Dietary diversity score 0.02 0.01 0.04 0.01 0.01 0.26 -0.002 0.01 0.82 0.02 Breastfed in past 24 hours (vs. not) -0.09 0.03 0.004 -0.07 0.03 -0.03 0.03 0.30 Ever consumed thriposha supplement (vs. not) -0.42 0.04 <.001 -0.62 0.03 <.001 -0.55 0.03 <.001 <.001 Low birthweight (vs. not) -0.52 0.03 -0.60 0.03 <.001 -0.45 0.03 <.001 Diarrhea in past 2 weeks (vs. not) -0.01 0.05 0.86 -0.04 0.05 0.35 -0.06 0.05 0.20 0.49 Ill in past 2 weeks (vs. not) -0.01 0.03 0.71 -0.02 0.03 -0.02 0.03 0.41 0.64 Dewormed in past 6 months (vs. not) 0.08 0.03 0.02 0.01 0.03 -0.03 0.03 0.27 Currently anaemic (vs. not) -0.05 0.04 0.20 -0.03 0.03 0.39 -0.003 0.03 0.92 Male (vs. female) 0.004 0.03 0.89 0.03 0.02 0.18 -0.01 0.02 0.58 Aged 12.01-23.99 months (vs. 6-12 months) -0.51 0.05 <.001 -0.33 0.05 <.001 -0.21 0.05 <.001 <.001 <.001 Aged 24.01-36.99 months (vs. 6-12 months) -0.58 0.06 -0.50 0.05 -0.39 0.05 <.001 <.001 Aged 37.01-48.99 months (vs. 6-12 months) -0.66 0.06 -0.56 0.05 <.001 -0.44 0.06 <.001 <.001 Aged 49.01-59.99 months (vs. 6-12 months) -0.65 0.06 -0.63 0.06 <.001 -0.50 0.06 <.001 Household Factors Maternal education of 6-10 years (vs. 0-5 years) 0.11 0.06 0.07 0.07 0.06 0.19 0.002 0.06 0.97 Maternal education of 11-13 years (vs. 0-5 years) 0.12 0.06 0.04 0.08 0.06 0.13 0.01 0.06 0.80 Maternal education of 14+ years (vs. 0-5 years) 0.22 0.08 0.01 0.22 0.08 0.005 0.14 0.08 0.09 Household had 4-5 members (vs. 3) -0.08 0.03 0.009 -0.10 0.03 0.001 -0.07 0.03 0.008 <.001 Household had 6+ members (vs. 3) -0.15 0.04 <.001 -0.16 0.04 -0.10 0.04 0.007 Received food aid (vs. not) -0.13 0.03 <.001 -0.19 0.03 <.001 -0.17 0.03 <.001 2nd wealth quintile (vs. lowest) 0.08 0.04 0.08 0.09 0.04 0.03 0.07 0.04 0.09 3rd wealth quintile (vs. lowest) 0.12 0.05 0.01 0.12 0.04 0.006 0.09 0.04 0.05 <.001 4th wealth quintile (vs. lowest) 0.21 0.05 <.001 0.19 0.05 0.11 0.05 0.015 Highest wealth quintile (vs. lowest) 0.24 0.05 <.001 0.25 0.05 <.001 0.18 0.05 <.001 <.001 Estate location (vs. urban) -0.45 0.12 <.001 -0.47 0.11 -0.32 0.12 0.006 Rural location (vs. urban) -0.14 0.05 0.003 -0.19 0.05 <.001 -0.17 0.05 <.001 Notes: HAZ = height-for-age z-score; WAZ = weight-for-age z-score; WHZ = weight-for-height z-score. All models included all variables shown above plus district dummy variables. 26
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511 512
Table 4. Multivariable multilevel logistic regression estimates of the association between indicators of anthropometric failure and dietary diversity among children aged 6 to <60 months in Sri Lanka in 2012 (n=6402).
Child Factors Dietary diversity score Breastfed in past 24 hours (vs. not) Ever consumed thriposha supplement (vs. not) Low birthweight (vs. not) Diarrhea in past 2 weeks (vs. not) Ill in past 2 weeks (vs. not) Dewormed in past 6 months (vs. not) Currently anaemic (vs. not) Male (vs. female) Aged 12.01-23.99 months (vs. <12 months) Aged 24.01-36.99 months (vs. <12 months) Aged 37.01-48.99 months (vs. <12 months) Aged 49.01-59.99 months (vs. <12 months) Household Factors Maternal education of 6-10 years (vs. 0-5 years) Maternal education of 11-13 years (vs. 0-5 years) Maternal education of 14+ years (vs. 0-5 years) Household had 4-5 members (vs. 3) Household had 6+ members (vs. 3) Received food aid (vs. not) 2nd wealth quintile (vs. lowest) 3rd wealth quintile (vs. lowest) 4th wealth quintile (vs. lowest) Highest wealth quintile (vs. lowest) Estate location (vs. urban) Rural location (vs. urban) 513
AOR
Stunting (95% CI)
0.97 1.03 2.66 2.67 1.00 1.04 0.90 1.06 1.08 2.07 1.78 1.97 1.99
(0.91, 1.03) (0.86, 1.23) (2.01, 3.51) (2.27, 3.14) (0.76, 1.32) (0.88, 1.22) (0.75, 1.08) (0.86, 1.31) (0.93, 1.25) (1.46, 2.91) (1.24, 2.56) (1.35, 2.88) (1.34, 2.95)
0.37 0.77 <.001 <.001 0.97 0.66 0.27 0.59 0.30 <.001 0.002 <.001 0.001
0.99 (0.94, 1.05) 1.05 (0.89, 1.23) 3.40 (2.65, 4.37) 2.67 (2.31, 3.10) 1.16 (0.91, 1.48) 1.06 (0.92, 1.22) 1.10 (0.93, 1.30) 1.04 (0.86, 1.25) 1.15 (1.01, 1.31) 1.31 (0.96, 1.78) 1.82 (1.33, 2.49) 1.95 (1.40, 2.71) 1.99 (1.41, 2.80)
0.74 0.57 <.001 <.001 0.22 0.43 0.29 0.72 0.03 0.09 <.001 <.001 <.001
0.80 0.74 0.72 1.28 1.43 1.31 0.85 0.82 0.74 0.64 2.76 1.32
(0.60, 1.08) (0.55, 1.00) (0.44, 1.18) (1.07, 1.53) (1.13, 1.81) (1.10, 1.56) (0.67, 1.08) (0.64, 1.06) (0.57, 0.97) (0.48, 0.87) (1.58, 4.80) (0.99, 1.76)
0.15 0.047 0.19 0.008 0.003 0.003 0.18 0.13 0.03 0.004 <.001 0.06
1.04 (0.78, 1.39) 1.08 (0.81, 1.43) 0.70 (0.44, 1.12) 1.15 (0.98, 1.34) 1.25 (1.01, 1.53) 1.26 (1.08, 1.47) 0.95 (0.77, 1.19) 0.94 (0.74, 1.18) 0.92 (0.72, 1.17) 0.84 (0.65, 1.09) 1.59 (0.87, 2.89) 1.20 (0.94, 1.54)
0.79 0.61 0.14 0.08 0.04 0.004 0.68 0.59 0.50 0.19 0.13 0.14
p-value
AOR
Wasting (95% CI)
p-value
Underweight (95% CI)
p-value
0.98 1.07 4.05 3.33 0.98 1.09 0.89 1.10 1.01 2.02 2.48 2.86 2.90
(0.93, 1.03) (0.92, 1.25) (3.17, 5.16) (2.88, 3.85) (0.78, 1.25) (0.95, 1.25) (0.76, 1.04) (0.92, 1.32) (0.90, 1.15) (1.50, 2.72) (1.83, 3.34) (2.08, 3.95) (2.08, 4.05)
0.45 0.40 <.001 <.001 0.89 0.21 0.14 0.30 0.84 <.001 <.001 <.001 <.001
0.94 0.92 0.84 1.34 1.45 1.44 0.85 0.83 0.62 0.59 2.99 1.45
(0.71, 1.23) (0.71, 1.21) (0.55, 1.28) (1.15, 1.56) (1.19, 1.78) (1.24, 1.68) (0.69, 1.04) (0.67, 1.04) (0.49, 0.79) (0.46, 0.76) (1.71, 5.24) (1.13, 1.89)
0.62 0.56 0.41 <.001 <.001 <.001 0.12 0.10 <.001 <.001 <.001 0.003
AOR
Notes: AOR = Adjusted Odds-Ratio. All models included all variables shown above plus district dummy variables.
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514 515
516 517 518 519 520
Table 5. Multilevel multivariable linear regression estimates of the association between indicators of anthropometric status and dietary diversity among children aged 6 months to <60 months in Sri Lanka in 2012. HAZ WAZ WHZ b SE p-value b SE p-value b SE p-value Children aged 6 to 12 months (n = 600) Dietary diversity score 0.02 0.03 0.63 -0.03 0.03 0.201 -0.07 0.03 0.008 Meets minimum meal frequency -0.04 0.12 0.72 -0.25 0.09 0.007 -0.29 0.09 0.002 Children aged 12+months to <24 months (n=1363) Dietary diversity score 0.003 0.03 0.91 -0.02 0.02 0.61 -0.02 0.02 0.48 Meets minimum meal frequency -0.04 0.07 0.56 -0.05 0.06 0.39 -0.04 0.06 0.48 Children aged 24 months and older (n=4409) Dietary diversity score 0.03 0.01 0.015 0.03 0.01 0.006 0.02 0.01 0.058 Notes: HAZ = height-for-age z-score; WAZ = weight-for-age z-score; WHZ = weight-for-height z-score. All models also included the same factors displayed in Table 3.
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