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Research Article

Factors Contributing To Positive Nutritional Deviance in the Growth of Children Aged 6-36 Months in Rural Northern Ghana

Mahama Saaka1*, Asamoah Larbi2, Irmgard Hoeschle-Zeledon3

1University for Development Studies, School of Medicine and Health Sciences P O Box 1883, Tamale-Ghana
2International Institute of Tropical Agriculture (IITA), P O Box 6, Tamale-Ghana
3International Institute of Tropical Agriculture (IITA), PMB 5320, Oyo Road, Ibadan, Nigeria, c/o IITA, 6th Floor, Suite G, Carolyn House

*Corresponding author:  Dr. Mahama Saaka, University for Development Studies, School of Medicine and Health Sciences, P O Box1883, Tamale-Ghana, Tel: 233-0207061136; Email: mmsaaka@gmail.com

 Submitted: 04-04-2014 Accepted: 05-09-2015 Published: 05-00-2015

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Article


Abstract

The main aim of the study was to find out why some children are nutritionally better-off than others although they belong to the same environmental setting. This cross-sectional study conducted in rural Northern Ghana, compared nutritional positive deviant children (that is, neither stunted nor wasted) with children having at least one form of under nutrition with respect to household feeding care practices and other health seeking behaviours. Of the 1,168 children aged 6-36 months, 67.9 % (CI: 64.5 – 71.1) were classified as positive deviant (PD). The prevalence of stunting and wasting was 23.1 (CI: 19.4 -27.3), 12.8 (CI: 10.9 - 14.8) respectively. Multivariable logistic regression adjusted for cluster sampling showed that positive deviant children (that is, neither wasted nor stunted) were 1.9 times more likely to be female children [AOR 1.88; 95% CI (1.32 - 2.67)]. Younger children (6-8 months) were 13.7 times more likely of being positive deviant children [AOR 13.66; 95% CI (5.51 - 33.90)], compared to children aged 24-36 months. Children who were not breastfeeding were more likely to be positive nutritional deviants as compared to their counterparts who were breastfeeding [AOR 2.80; 95% CI (1.62 - 4.82)]. There was little variation in the diets of positive deviants and the rest of the children (that is negative deviants and median growers), an indication that factors other than diet may be contributing to better growth of children in Northern Ghana.

Keywords: IYCF Practices; Nutritional Status; Positive Deviance; Complementary Feeding Northern Ghana
 
Introduction

Child under nutrition continues to be a public health problem in Northern Ghana. A number of interventions have been implemented to address the issue but progress remained slow and this calls for better and improved ways of dealing with the problem. It is generally agreed that the underlying causes of malnutrition among children are household food insecurity, inadequate care and poor access to health services coupled with poor personal and environmental hygiene [1]. However, variability in growth and nutritional status of children exists even when there is no substantial difference in care, health, and food accessibility, meaning that children having similar living conditions such as disposable income and resource access grow adequately, while others fail to do so in the same household [2-4].
 
In particular, it is usually believed that households with high  income level or socioeconomic status will also have the best nutritional status. This has been found not to be true in all cases and there are research findings that support this. For example, a study in Bangladesh showed that the association between income level and child nutritional status was not evident, because there had been instances where children in very poor households did grow better than others with the best socioeconomic status struggle to grow [5]. This suggests that there must be some hidden factors and/or practices that could be yielding these positive as well as negative results. Many experts believe that this phenomenon can be explained by what is being referred to as “nutritional positive deviance”. The term “positive deviance” in nutrition has been used to identify children who ‘grow and develop well in impoverished environments where majority of children are victims of malnutrition and chronic illness, whereas, ‘negative deviants’ grow at the lower end of the growth spectrum and ‘median growers’ grow at or around the median of the growth spectrum [5]. In situations where a child exhibits the best growth under harsh living conditions, then that child is described as positive deviant [6]. A lot can be learnt from positive deviant children providing guidance to design appropriate nutrition programmes in communities to address the problem of malnutrition among children. For example, programmes can be designed to discourage behaviors that are associated with negative deviance, and to promote behaviors that are associated with positive deviance. To do this effectively, we need to have better understanding of the factors that promote positive deviance in child growth. However, there is little systematic investigation on the magnitude and determinants of positive deviance in the growth of children in Northern Ghana and this warrants further research. The International Institute of Tropical Agriculture (IITA)-Ghana in collaboration with the Ghana Health Service (GHS) has initiated a new project which seeks to identify and promote the consumption of locally available micronutrient-rich foods including vegetables, fruits, and animal-source foods (ASF) to improve dietary diversity and nutritional outcomes of children, pregnant and lactating mothers.

In November 2013, a baseline survey was conducted in IITA programme communities. The overall aim of the survey was to collect information on knowledge and practices related to infant and young child feeding (IYCF) practices which will serve as a baseline for future comparison after the implementation of the project. This paper is based on re-analysis of data from the baseline survey to find out why some children are nutritional better-off than others although they belong to the same environmental setting.

Methods and Materials

Survey design, population and sampling

This was a cross-sectional baseline survey carried out November 2013. The study population comprised mothers/primary caregivers and their children aged 6-36 months, selected from 25 programme communities. A sample size of 288 was required to ensure that the estimated prevalence of chronic malnutrition was within plus or minus 5 % of the true prevalence at 95% confidence level. Assuming a correction factor of 2 (the “design effect”) for cluster sampling the sample size was increased to 576. A non response rate of 5 % and other unexpected events (e.g. damaged/incomplete questionnaire) was factored in the sample size determination and so the sample size was adjusted to 600. The same number of children was selected from comparison communities where the interventions were taking place but were located in the same district.

In each cluster, a complete list of all households was compiled and systematic random sampling used in selecting study households. All the households in each cluster were serially numbered. To get the sampling interval, the total number of households in a cluster was divided by the sample size of 24. The first household was then randomly selected by picking any number within the sample interval. Subsequent selections were made by adding the sampling interval to the selected number in order to locate the next household to visit. If the selected household does not have a target respondent, then next household was selected using the systematic sampling procedure. This process continued until the required sample size was obtained. A minimum of 24 mother/child pairs were randomly selected from a cluster giving a total of 600 respondents per study arm.

Data collection

Anthropometric assessment as well as household interviews, using structured questionnaires was undertaken concurrently. During the interview, mothers were asked questions about family demographics, child feeding practices, specific foods consumed by the child, child care practices, healthcare seeking behavior and home management of sick children.

Independent and dependent variables

The main outcome variable for this study was the prevalence of child’s nutritional deviance. The independent variables for this study were infant and child feeding practices, child and household characteristics. A brief description of main independent and dependent variables is as follows:

Assessment of infant and young child feeding (IYCF) practices

Infant and young child feeding indicators including minimum meal frequency, minimum dietary diversity and minimum acceptable diet were estimated by recall of food and liquid consumption during the previous day of the survey as per  WHO/UNICEF guidelines [7]. An adapted version of infant and child-feeding index (ICFI) originally developed by Ruel and Menon [8] included the following dimensions: current breastfeeding status; dietary diversity in the past 24 hours; adequacy of meal frequency in the past 24 hours prior to the study, score for timely initiation of breast feeding, score for whether or not child was fed with prelacteal food, and score for timely introduction of complementary foods.

A dietary diversity score was created by summing consumption of 16 types of food groups: cereals, white roots and tubers, vitamin A rich vegetables and tubers, legumes and nuts, milk and milk products, dark green leafy vegetables, flesh meats, organ meat, fish, eggs, vitamin A-rich fruits, other fruits, other vegetables, oils and fats, sweets, and spices and condiments.

The dietary diversity score ranged from 0-16 with minimum of 0 if none of the food group was consumed to 16 if all the food groups are consumed. From the dietary diversity score, the minimum dietary diversity indicator was constructed using the WHO recommended cut-off point with a value of “1” if the child had consumed four or more groups of foods and “0” if less. Minimum dietary diversity is the proportion of children who ate at least 4 or more varieties of foods from the seven food groups in a 24 hour time period [9, 10]. Minimum meal frequency is the proportion of children who received complementary foods the minimum recommended number of times in 24-hours. For breastfed children, the frequency should be at least 2 times for 6–8 months, and at least 3 times for 9 –23 months of age. For non-breastfed children, it should be at least 4 times in last 24 hours. Minimum acceptable diet is a composite indicator of minimum dietary diversity and minimum meal frequency. When a currently breastfed child meets both the minimum diversity and the minimum meal frequency, the child is considered to have met the WHO recommended minimum acceptable diet.

Determination of educational level

Maternal educational level was based on the highest level attained according to the Ghanaian System where primary education consist of six years of formal education, the Junior High School (JHS) is nine years, Senior High School (SHS) is 13 years. This variable was categorized into three: no education, primary or junior secondary, senior secondary education or higher.

Anthropometric indicators

Anthropometric indicators of height-for-age (HAZ), weightfor-age (WAZ), weight-for-height (WHZ) were determined as recommended by the World Health Organization [11]. In most studies, one growth indicator is often used to define positive or negative nutrition deviance. However, a child who is not stunted may still be wasted or vice versa. Consequently, we defined positive deviant children as having both height - for -age Z-score (HAZ) and weight – for height Z-score (WHZ) ≥-2 (better nutritional status) were compared with the rest of the children (that is, those having their HAZ and/or WHZ <-2 ( worse nutritional status).Negative deviant child was defined as having both HAZ and WHZ <-2. Median deviant child was defined as having either HAZ or WHZ <-2.

Data management and statistical analyses

The Emergency Nutrition Assessment (ENA) software (2013 version) was used for the anthropometric data analysis and reported using WHO 2006 growth reference values. Data analyses were performed using procedures in SPSS complex samples module, version 18.0 for Windows. Design weights were added to each region (that is, total population divided by number of respondents) to perform weighted analysis. This module of SPSS takes into account the complex nature of the cluster sample design.

Before performing the anthropometric calculations for weightfor-height (WH), height-for-age (HA) and weight-for-age (WA), the data was cleaned and outliers removed. In bivariate analyses, the chi-square tests were carried out to test for differences between positive and negative deviant children. Differences between the study groups were considered to be statistically significant if the P value was less than 0.05, or if the range for the 95% confidence interval for the odds ratio (done as part of the analysis) did not include 1.0. We then used logistic regression with adjustment for clustering in SPSS complex sample to identify independent predictors. The risk factors that were statistically significant or close to significant associations in the bivariate analyses were entered into the logistic regression.

Ethics and informed consent

The study was also approved by the School of Medicine and Health Sciences, University for Development Studies. Informed verbal consent was sought through verbal communication with community representatives and on individual household level, with accompanying clarification on purpose and nature of the study. In each household, the survey team supervisor gave a brief orientation to the respondents as to the purpose and intended outcome of the study. He/she read and explained the informed consent statement to the mothers. All mothers approached opted to participate in the survey.

Results

A total 1,200 children aged 6-36 were surveyed but some of them had missing data and were therefore excluded from the analysis.
 
Socio-demographic characteristics of the sample

As shown in Table 1, the mean (standard error) age of children included in the analysis was 18.9± 0.3 months and 48.9 % were male. The mean (standard error) age of the mothers was 28.9±0.15 years. Nearly 71.0 % (CI: 67.5 - 74.0) of the mothers had no formal education.

Table 1. Sample Characteristics

food table 9.1
Household Food Availability, Access and Utilization

The primary source of obtaining food for 92.5 % of households was their own production (e.g. farming). Most households (98.0 %) reported cultivating grains, roots, tubers but less than 5 % grow orange or yellow fruits and vegetables. The cultivation of leafy green vegetables was reported in only 30 % of households (Figure 1).

With respect to household livestock and poultry keeping, 4.9 % of the sampled households did not keep any animal or bird. Fig 2 shows the types of animals and poultry owned by households. Whereas, over 80 % of households keep chickens, ducks, or other birds; for the meat/sale, only 28.2 % do so for their eggs. Livestock such as cows, goats, sheep, or dogs are kept mainly for sale (59.7 %) but 51.1 % of households reported keeping these animals for the sake of meat. Keeping rabbits, guinea pigs, or other small ruminants was practiced by less than 5 % of households. Fish farming was rarely practiced in the study population.
food fig 9.1
Figure 1. Types of crops grown by households.

food fig 9.2
Figure 2. Types of animals raised by households
 
Food Consumption/Utilization

As shown in Figure 3, the types of food that were fed to children in the past 24 hours prior to the study were cereal-based staples, but the consumption of foods known to have a good content of micronutrients and protein was less than satisfactory. For example, only 14.3 % of children were fed on vitamin A rich fruits and vegetables. Consumption of flesh meat was reported in less than 12 %. Legumes consumption was reported in 45.5 % of the households interviewed.

Organ meats and other animal products - dairy and eggs - were consumed quite infrequently. Dark green, leafy vegetables were consumed by 37.9 % of the children. Consumption of fats and oils was modest (56.3 %). The consumption of dried vegetables such as okro, pumpkin, baoba leaves, and wild types in the past 24 hours was reported by 43.2 % of the households.
 
food fig 9.3
 
Figure 3. Types of food fed to children in the past 24 hours
 
 
Dietary Diversity and Food Group Frequency Consumption

The mean dietary diversity score (DDS) from 7 food groups was 2.8±1.7. Of the 765 children aged 6–23 months, 35.0 % met the minimum dietary diversity (≥ 4 food groups), and only 27.2 % had received an acceptable diet.

The results showed that there was no discernible difference between positive deviant children and negative/median growers in terms of dietary intake in the past 24 hours prior to the study, except that a greater proportion of positive deviant children consumed more legumes compared with the rest of the children (66.7 % versus 33.3 %) χ2 = 5.9 p = 0.015 (Table 2).

Table 2. Type of food groups consumption frequency in the past 24 hours.
 
food table 9.2
 
Nutritional Status of Children 6-36 Months

Table 3 shows the prevalence of acute, chronic and underweight in the study sample. The proportion of children suffering from both chronic and acute malnutrition (negative deviants) was 4.2 %. Of the 1,168 children aged 6- 36 months, 67.9 % (CI: 64.5 – 71.1) were classified as positive deviant (PD).

Table 3. Prevalence of malnutrition among children 6-36 months.
 
food table 9.3
 
*Z -scores: weight for age, height for age, weight for height, WHO Standard 2006

*CI: 95 % confidence interval

Predictors of Positive Nutrition Deviance among Children Aged 6-36 Months

Bivariate analysis was done to quantify the crude association between positive nutrition deviance and selected independent variables. A number of variables including household wealth index, timely initiation of breast feeding, timely introduction of complementary foods, minimum meal frequency, minimum dietary diversity, minimum acceptable diet and a composite index of infant and young child (IYCF) practices were tested to find their association with positive deviance. Tables 4a and 4b show the predictors of positive deviance in child growth. A significantly higher proportion of PD children were younger (6–8 months), compared to children aged 24-36 months. Female children were significantly more likely to be positive deviant compared to boys. Children who were not breastfeeding were more likely to be positive deviant children. Positive deviant children were more likely to come from the Upper West and Upper East regions. Mothers of positive deviant children had higher maternal educational attainment. Mothers of positive deviant children were older (at least 35 years). Positive deviant children suffered less often from diarrhoeal infection in the past two weeks prior to the study, compared to their counterparts who were negative deviants.
 
Table 4a. Bivariate analysis of predictors of positive nutrition deviance among children aged 6-36 months.
 
food table 9.4a
* 95 % confidence level (CI)

Table 4b. Bivariate Analysis of predictors of positive nutrition deviance among children aged 6-36 months.
 
food table 9.4b
 
* 95 % confidence level (CI)

Our data showed that breastfed children aged 6-23 months were not getting adequate complementary foods. The dietary diversity score of such children was significantly lower than their counterparts who were not breast feeding (2.8 versus 3.7), F (1,765) = 4.6, p = 0.032. Additionally, the mean meal frequency in the past 24 hours prior to the study for breast feeding children was lower than that of non-breast feeding children (2.5 versus 5.5), F (1,784) = 13.0, p < 0.001.

Multivariable logistic regression analyses showed that being a female child, resident in the Upper West Region, younger children, non-breast breastfeeding children were factors contributing significantly to positive deviance (PD (Table 5). Compared to the Northern Region, children in the Upper West region were 2.5 times more likely of becoming positive deviant (OR= 2.50, CI= 1.67 - 3.74) and children in the Upper East Region were 2.6 times more likely of becoming positive deviant (OR= 2.60, CI= 1.64 - 4.11).

The data showed that children who had no diarrhoea were 1.9 times more likely of being positive deviant [AOR 1.93; 95% CI (1.34 - 2.76)] compared to children who had diarrhoea in the last two weeks prior to study. Female children were significantly more likely to be positive deviant [AOR 1.88; 95% CI (1.32 - 2.67)]. Younger children (6-8 months) were 13.7 times more likely to be positive deviant children [AOR 13.66; 95% CI (5.51 - 33.90)], compared to children aged 24-36 months.

Of all the predictors of positive deviance, age of the child contributed most (Wald = 37.4, p < 0.001) to the variation of positive deviance of growth.

Table 5. Multivariate analysis of the determinants of positive nutrition deviance (Low socio-economic households only).
 
food table 9.5
 
Discussion

This paper presents analysis of positive nutrition deviance aimed at identifying characteristics of young children who, despite economic constraints prevalent in the study area, were able to achieve positive nutritional outcomes.

Socio-economic status as measured by household wealth index was not an important determinant of positive deviance in child growth in our study sample. This gives an indication that economic constraints did not play into the picture of positive deviance. Multivariate analysis was performed on the entire sample and on a separate subset comprising households of low household wealth index. By using households of similar living conditions, it was possible to provide possible answers to the fundamental question of: “What is it that certain households have been able to do, despite low socioeconomic standing that has resulted in normal nutritional status?

A number of variables including child morbidity, timely initiation of breast feeding, timely introduction of complementary foods, minimum meal frequency, minimum dietary diversity, minimum acceptable diet and a composite index of infant and young child (IYCF) practices were tested to find their association with positive deviance. The results showed that these key indicators of infant and young child feeding practices were however, not important predictors of positive deviance in the study population.

In the present study, factors contributing significantly to positive deviance (PD) in rural households of low socioeconomic status were children of younger ages (6–8) months; children of female sex, residence in the Upper West Region, absence of diarrhoeal infection and non-breast feeding status.

Many other factors that associated with positive deviance in bivariate analysis but failed to reach significance level in multivariable regression analyses were institutional delivery, high maternal educational attainment, Christian religion following and older maternal age (at least 35 years).

Though children aged 6-8 months were less likely to meet minimum dietary diversity, they were more likely to become positive deviant. A significantly higher proportion of PD children were younger (6–8 months), compared to children aged 24-36 months.

We found female children more likely to be positive deviants, contrary to what was reported in other countries including Bangladesh, where male children were three times more likely to be positive deviants as compared to girl children [12]. Male children were more likely to be stunted than their counterpart females, a finding that has been reported by earlier studies in other African countries [13-15]. The exact factors contributing to this male vulnerability is unclear but it is unlikely to be the result of gender preference [13, 16]. The male vulnerability to malnutrition may be biological and the fact that male infants are at greater risk of infection because of greater tendency to explore the environment compared to female counterparts. It has been suggested that despite the improvement in medical care, environmental stresses have harsher effects on males than females in early life [17].

From the analysis we found that children who were not breastfeeding were more likely to be positive nutritional deviants as compared to their counterparts who were breastfeeding. This finding may be explained by the fact that, breast milk alone is inadequate to meet the nutritional needs of children aged 6-24 months but rather a combination of breastfeeding and adequate complementary foods is needed [18]. Similarly, in rural Senegal it was reported that current breast-feeding was associated with a significantly lower height-for-age after adjustment for age [19]. It appears that breast feeding children aged 6-23 months are not getting adequate complementary foods. In our study sample, the dietary diversity score of such children was significantly lower than their counterparts who were not breast feeding. Additionally, the mean meal frequency in the past 24 hours prior to the study for breast feeding children was lower than that of non-breast feeding children. All these point to the fact that breast feeding children are at greater risk of being fed on sub-optimal complementary feeding regime and this has great potential of compromising their growth performance. In view of this, we suggest all mothers, especially those that are breast feeding should be targeted for behaviour change communication interventions designed to promote and enhance complementary feeding.

Positive deviant children suffered less often from diarrhoeal infection in the past two weeks prior to the study, compared to their counterparts who were negative deviants. Usually, the incidence of diarrhoeal disease is directly related to the quality of water and sanitation services, as well as behaviors that are embodied in various sanitation and hygiene practices. This therefore means that occurrence of diarrhoea gives an indication of hygiene and sanitation conditions. A significant proportion of the negative deviant children/median growers had suffered from diarrhoea within two weeks prior to the study, compared to positive deviant children. Similar findings had been reported from several countries including Ghana and Bangladesh [12, 20, 21].

Under-nutrition and childhood morbidity have a synergistic relationship. The two conditions act in such a way that illness can suppress appetite precipitating under nutrition of a child while, on the other hand, nutritional deficiencies increase the susceptibility of the child to infectious diseases [22]. Generally, improving dietary intake to recommended levels together with the elimination of diarrhoea and febrile illness at the same time would be necessary to achieve optimal child growth. The implication of this finding is that proper personal and environmental cleanliness is associated with positive deviance and that interventions to reduce morbidity from diarrhoea may benefit children’s growth in this population.

The prevalence of acute under-nutrition was over 10 %, a level considered to be serious according to the World Health Organization (WHO). The overall prevalence of chronic malnutrition was as high as 23.1 %, which indicates a serious malnutrition situation as judged by the WHO criteria [23, 24].

Poor complementary feeding practices contribute to inadequate energy and protein intake and childhood under nutrition [25-27]. Therefore, complementary feeding indicators were also assessed as predictors of nutritional adequacy. Families of positive deviant children reported desirable IYCF behaviors, especially timely initiation of breast feeding. The analysis of data collected on feeding practices showed that only 46.1 % of the children aged 6-23 months met the minimum acceptable diet suggesting over 50 % were on poor diet quality. Surprisingly, none of the WHO recommended complementary feeding indicators (Minimum meal frequency, minimum dietary diversity, and minimum acceptable diet) was associated with positive deviance in growth among children aged 6-23 months. In bivariate analyses, a composite index of infant and child feeding practices was also not significantly different in the two groups of children. The index comprised the elements: current breast feeding status, timely initiation of breast feeding, whether or not the child was given prelacteal food, age at which complementary foods were introduced, adequacy of meal frequency in the past 24 hours and 24 hour dietary diversity score. A study in Senegal also reported that the feeding index was not associated with height-for-age z-score in either bivariate analyses or in general linear models adjusting for a number of variables [19].

The apparent lack of association between child feeding practices and positive deviance may be due to the fact that there was very little variation in the study population with respect to these indicators. There was little variation in the dietary intake of positive deviants and the rest of the children (that is negative deviants and median growers). This finding is consistent with findings from other studies conducted in the Brong Ahafo Region of Ghana where with the exception of dietary zinc intake, dietary variables were generally not significantly associated with child growth [20].

Findings on the relationship between feeding practices and child growth have been mixed. A survey conducted in Mexico found that measures of recommended breastfeeding and complementary feeding practices were not associated with growth when family economics and other factors were included in logistic regression models [28].

An earlier study carried out in Senegal (Sahelian West Africa country), concluded that dietary diversity in the last 24hrs and frequencies of consumption of animal source foods (animal milk, meat, fish/eggs/poultry) over the last week were not associated with growth in height [19].

However, in seven Latin American countries, it was reported that recommended child feeding practices were positively associated with height-for-age z-score with a stronger effect for children of lower socio-economic status [8]. Dietary diversity among 6–23-month-old children was found to be positively associated with height-for-age z-score in seven of 11 countries when other variables were included in the models [29].

A major strength of this paper lies in the fact that it is about the first to identify the main determinants of positive deviance in Northern Ghana. Most studies tend to focus on the prevalence and determinants of malnutrition. However, as pointed out by many scholars, the determinants of ‘positive deviance’ are not necessarily the converse of poor growth. It has been hypothesized that the mechanisms operating to produce ‘positive deviance’ and ‘negative deviance’ are different [30]. A factor that may be associated with ‘negative deviance’ need not be inversely associated with ‘positive deviance’. One other uniqueness of the present study is that it defined positive deviance taking into consideration the absence of both chronic and acute malnutrition.

Conclusions

This paper has identified some child characteristics and key growth promoting behaviors that enable children in Northern Ghana to perform better in terms of growth under conditions which their counterparts failed. One significant modifiable factor contributing to positive deviance is protection of children from diarrhoeal infection but the age of child was a major determinant of positive deviance.

Our analyses showed that children who were not breastfeeding were more likely to be positive nutritional deviants as compared to their counterparts who were breastfeeding. Evidence from our sample suggest that breast feeding children were at greater risk of being fed on sub-optimal complementary feeding regime and this has great potential of compromising their growth performance.

It is difficult however, to make firm inferences about the contribution of feeding behaviors as most of the major feeding indicators were not associated with positive deviance of child growth. We therefore suggest that intervention studies that aim at improving feeding practices among infants and young children in low-income settings would allow for a better assessment of the effect dietary quantity and quality have on positive deviance of child growth.

Limitations of the study

Our design was a cross sectional study and as with all such studies we cannot ascribe causations to the relationships found in the current study, and based on self-report we are not sure whether the respondents may or may not have misreported. However, because the questionnaire was anonymous we have no reason to believe that the respondents may have knowingly misreported in our survey.

Acknowledgements

Financial support from USAID funded IITA-led project on Sustainable Intensification of Cereal-Legume Farming Systems in West Africa is acknowledged. We are thankful to the data collection team members from the Ghana Health Service (GHS) for their hard work and commitment. The data could not have been obtained without the co-operation and support of the programme communities, especially the mothers and caregivers who took time off from their busy schedules to respond to the interviewers. Their involvement and cooperation is highly appreciated.

References

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Cite this article: Saaka M. Factors Contributing To Positive Nutritional Deviance in the Growth of Children Aged 6-36 Months in Rural Northern Ghana. J J FoodNutri. 2015, 2(1): 009.

Figure 3. Types of food fed to children in the past 24 hours

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