Introduction

Child malnutrition is a serious concern in developing countries due to the high mortality and morbidity with which it is associated. Preschool-age children under the age of 5 are particularly susceptible to the adverse effects of malnutrition as they are in a vulnerable growth period with high growth requirements) 1(. Child under-nutrition is estimated to be the largest contributor to global burden of disease, killing millions of children in the developing countries and causing substantial health expenditures            (2-4). It is estimated that 54% of deaths in children under 5 years are associated with malnutrition) 5), and that approximately 5 million children die each year due to causes that are directly or indirectly related to malnutrition )6(. Indicators of malnutrition include wasting, stunting and underweight, which represent different aspects or measurements of malnutrition )7(. Wasting as measured by low weight for- height represents lower than expected body mass (tissue or fat) and is a good indicator of existing nutritional deficits. Stunting, or low height-for-age is an indicator of a reduced linear growth rate and represents a chronic state of malnutrition as it takes longer for impaired skeletal growth to become apparent. Underweight, which is measured by low weight-for-age,represents a combina- tion of both wasting and stunting. A review of the literature has identified infections, diet, child and family demogra- phics, and household characteristics as risk factors for malnutrition in preschool-age children
(8–13). Both stunting (low height-for-age (HAZ)) and underweight (low weight-for-age (WAZ)), in comparison with healthy reference populations, can be used as indicators of malnutrition. Stunting, in particular, is thought to be a good indicator of malnutrition (14) and often represents a state of chronic nutritional stress. It can lead to both short-and long-term adverse events in childhood and adulthood, including effects on health, cognition and educational outcomes (15-19). Although results from these previous analyses are useful as guides to studies in Iran, regional data collection is required to capture factors that may be unique to a specific population. Furthermore, the findings can be used to address such risk factors at nutritional and regional level with the aim of early identification and prevention to reduce the problem of malnutrition. Although substantial developments have taken place in Iran, there are districts where one in four children is malnourished (20), and this situation calls for serious action. Volkmann (21) for example has reported that nearly 11% of Iranian children are still underweight.

Whilst there have been several studies in other cities in Iran (22-24) there are no studies examining the causes of malnutrition in two to five years old children in Mashhad.  Breastfeeding, first food and socio-demographic determinants play an important role in child growth, but the contribution of these factors to malnutrition has not been examined. Analysis of underlying causes including factors thought to influence growth and food intake such as weaning practices or maternal education has not been reported.

Therefore, the objective of the present study was to determine the prevalence of three indicators of malnutrition (wasting, underwe- ight and stunting) using the new WHO Child Growth Standards and associated risk factors in a population of preschool-age children living in Mashhad, Iran.

Methods and Materials

A cross sectional study was conducted to identify the determinants of nutritional status (weight for age, height for age and weight for height)  in 671 children (24-59 months) from selected health centers in Mashhad city, recruited from an urban population, using a stratified-cluster method Mashhad, Iran. Children were measured for weight and height. In addition, the caregivers were interviewed for their socioeconomic, demographic, health characteristics, history of breast feeding information, when first food was introduced and solid food consumption.  Ethics approval for carrying out this research was obtained from the Ethics committee of Mashhad University of Medical Sciences.

The interviewers used in the study were given specific training on interview techniques and the use of the socio-demographic status questionnaire, which enquired about feeding behaviors, and how to make the anthropometric measurements. In order to avoid measurement bias, anthropometry measurement of the children were undertaken by researchers who attended the health clinics every day. In this study care givers of the children were asked to complete the consent form.

Fourteen health centers were chosen from 28 urban health centers by simple random sampling. The sample size was determined based on the fact that the prevalence of underweight children in Iran was estimated as 11% according to UNICEF report (21) and the fact that the rate of obesity and overweight in 5 years old in Iran has been reported to be 20% (25).

Nutritional status was measured using standardized growth indices as general indicators. Indicators of extreme health outcomes such as stunting, wasting and being underweight were used in this analysis. Since, the prevalence of under- nutrition varies in different studies in Iran, the work presented in this study, aimed to identify nutritional problems and the relationship with health and dietary determinants.

Children whose weight for age, height for age and weight for height were less than two standard deviations (SD) below the median are classified as underweight, stunted or wasted, respectively (26). In addition, children whose weight for age, height for age and weight for height were less than one standard deviations (SD) below  the median and higher than -1SD, are classified as mildly underweight, mildly stunted or mildly wasted, respectively, according to NCHS Reference (26). Moreover, children whose weight for age, height for age and weight for height were less than two standard deviations (SD) below 2SD median and higher than -1SD, are classified as normal, according to NCHS Reference (26). Furthermore, children whose weight for age, height for age and weight for height were less than two standard deviations (SD) higher than 2SD median are classified as high, according to NCHS Reference (26).

Statistical Analysis

The method of Green et al. (1997) was used to interpret the magnitude of relationship. The data analysis was done using SPSS (Statistical Package for the Social Sciences) software. In addition, the Z-scores were calculated using the WHO anthropometric software package. P-values less than 0.05 were considered to be statistically significant.

Results

The percentage of male and female children recruited into the study was 51.56% and 48.43%, respectively. Moreover, 87% of the children had birth weight between 2.5-5 Kg. The gestational age for 95.2% of children was 38-42 weeks, and 61% of children were born by normal delivery.

We found that 24.4% of children were mildly underweight (<-1SD), 4.3% of them were underweight (<-2SD) and 1.8% were overweight. In addition, 13% of children were mildly stunted (<-1SD), 3.1% of them were stunted (<-2SD) and 7% were high. Furthermore, 23.6% of children were mildly wasted (<-1SD), 4.3% of them were wasted (<-2SD) and 0.4% of them were overweight (Table 1).

Malnutrition in boys was more severe
than in girls in the age range of 24 to 35 months. But, malnutrition in girls was more severe than in boys in the age range of 36 to 59 months (Table 2).

Table 1: Prevalence of Severity of Malnutrition by age group.

Table 2: Distribution of Mean Z-scores for weight and height, by Gender and Age.

Association of Feeding Determinants with Child Nutritional Status

In their first week of life 98.5% of the children were breast fed, 0.3% was fed on cow’s milk and 1.2% using formula milk. Only 58.9% of the children were breastfed alone. The reasons for stopping breast feeding were their mothers running out of breast milk (14.6%), the child’s refusal to continue with breast feeding (10.2%), pregnancy (7.8%), the mother’s work obligation (3.7%) and other unspecified reasons (4.8%). From the age of 6 months or above children were introduced to their first complementary foods. Almond porridge was consumed by 50.4% of the children. This is usually prepared by straining ground almonds cooked in diluted syrup of water/ milk and sugar), rice flour porridge by 36.5%, soup by 7.5% and other types of foods including yoghurt and some traditional and local foods.

Solids were introduced to complementary foods from 6 months of age for 86.7% of children in the form of soup and puree softened in butter. The consumption percentages of solids at the age of 6 months were as following: 50.7% vegetables, 22.2% fruits, meat 46.9%, egg 35.9%, fish 5.5%, potato 42.2% and rice 28.5% (Table 3).

Pearson’s correlation coefficients between feeding practices and child’s nutritional status were calculated. In this study nutritional status is measured by weight for age Z score (WAZ), height for age Z score (HAZ) and weight for height Z score (WHZ). These are shown in Table 4; the results show the age at the introduction of first solid food had little relationship with WAZ, (r=-0.187). The average amount of milk consumed per day was positively correlated to WAZ (r=0.266), HAZ (r=0.228) and WHZ (r=0.227). Age at which children started eating fruit had negative correlation with HAZ (r=-0.107).  The age at which eggs were consumed was negatively related to WAZ (r=-0.198) and HAZ (r=-0.202). The age at which feeding with meat was started was positively related to WAZ (r=0.200). Age of beginning feeding potato had little negative correlation with HAZ (r=-0.179). A low consumption of milk was one of the major determinants of malnutrition in the children in our sample population. In addition, the age of beginning feeding meat was another important reason for malnutrition.

Table 3: Percentage of Children who wereIntroduced to Complementary Foods by the specified age.

Table 4: Pearson Correlation Coefficient between Feeding Practices and Child Nutritional Status.

Association of Socio-demographic and Health Factors with child’s Nutritional Status

Pearson’s correlation coefficients between socio-demographic, health factors and
child’s nutritional status were calculated. There was a negative correlation between child’s age in months and HAZ (r=-0.341) (P<0.01) (Table 5).

Table 5: Pearson Correlation Coefficient between Socio-demographic factors and Child Nutritional Status.