NUTRITIONAL STATUS OF THE SCHOOL CHILDREN OF DHAKA CITY

INTRODUCTION

Nutritional status of children is a manifestation of a host of factors consisting of care for child, access and distribution of food in household and most importantly parental knowledge about nutrition. Bangladesh is a third world country with a very large population. The nutritional status of this population is a matter of great importance as it effects the whole country’s growth.  Children are the future of this nation. Often while discussing the nutritional status of the children of this country it is said that the children are under nourished. But recent studies show that obesity is also prevalent in case of school going children. And it is known that the nutritional status of the children is largely dependent on the parents as they are the decision makers of the family.

Nutritional knowledge of parents is associated with nutritional status of children. Positive results have been reported in Asia¹, Sub-Saharan Africa², Latin America³, as well as in the United States of America⁴. Widely cited is the example of the World Bank’s first community nutrition loan to Indonesia in the 1970s which significantly improved the nutritional status of 40 percent of target children through nutrition education.⁵

Under nutrition is a problem more commonly found in developing and under developed countries. This is due to the fact that in developed countries the government takes important measures to ensure proper care of the child is given at homes. So under nutrition is a problem rarely seen in developed countries. But that is not the case for the rest of the world. The incidence of underweight children has been consistently reported at about 45%, which compares with an average incidence of underweight children in Sub Saharan Africa in the 90’s of 33%.(World Bank, 2000)Similarly, surveys in Ethiopia have consistently found more than half the children under five stunted, with stunting rates most often attaining more than 60%.⁶ By way of comparison, during the mid 90’s, the average prevalence of children stunted for 19 Sub Saharan African countries is 39%.⁷

The other side of malnutrition is obesity. The World Health Organization⁸ has identified an increase in childhood obesity in developed countries and a high prevalence of childhood obesity has been reported in developing regions such as in Latin America.⁹In the United States of America (USA), the average rates for overweight and obesity among children have been reported to be 22% and 11% respectively, while in the state of Carolina, it was 32.4% and 16.4% respectively. ¹⁰Figures for overweight and obesity for Spain and Italy were 40%, and for Canada 25.3%. ^11-13  In developed and developing countries obesity in children prevails over under nutrition unlike their under developed counterparts. Some Middle East and Asian countries have documented a significant increasing rate in the past decade.^{14-19 In the Islamic Republic of Iran it has been reported that the prevalence of overweight has been increasing in the country.20}

Nutritional studies on primary school children in Malaysia show that, children aged 6-12 years old from five rural communities found the prevalence of underweight among boys and girls to be 29.1% and 26.1% respectively (Khor & Tee, 1997). In these communities, an average of 34.4% boys and 24.9% girls were stunted. However, the prevalence of wasting among these children (boys = 8.2%; girls = 6.2%) was much lower compared to the other two nutritional status indicators.²¹ In Malaysia, the reported prevalence of overweight  children in Kuala Lumpur ranged from 5.8% to 17.8%.^21-23

In Afghanistan National Nutrition Survey in 2004-05 found over half (54%) of children below five years are chronically undernourished and 39% low weight for their age. ²⁴Sri-Lanka has experienced marked improvements in the nutritional status of young children. Underweight rates declined by almost 25% in that time period from “very high” levels to “high” levels, according to WHO classification.  Stunting rates, a measure of long term under-nutrition, declined even more, by about 75% to a “low” level classification from that of “high”. As a result, Sri Lanka has the lowest prevalence of underweight in South Asia.²⁴

In Nepal, a study showed that 61% of the students were found to be malnourished. The students were more stunted (21.5%) than wasted (10.4%). Only 5.4 % of the students were found to be both wasted and stunted.²⁵In Pakistan 38% and 40% of children under five years old reported to be underweight and stunted, respectively.²⁴In India, The Third National Family Health Survey (NFHS) in 2005 found 46% and 38% of children below the age of 3 years to be underweight and stunted, respectively. Child malnutrition in rural areas is much higher than in urban areas. In rural area 51% stunting and 46% underweight and in urban area 40% of children are stunted and 33 % are underweight.²⁴

Like other counties in the South Asia region, the levels of child under nutrition in Bangladesh are among the highest in the world. Stunting is most common in poorest households where more than 50% of the children are too short for their age, compared to only 26% in the wealthiest households. Stunting is also more prevalent in rural areas (45%) than in urban areas (36%), and among uneducated mothers as opposed to those with higher education.²⁴Recent study in primary school children in Dhaka city had showed the prevalence of obesity was 52% and overweight 13%.²⁶

The nutritional status of children is of vital importance. But in a family it is the parents who make decisions towards the family’s lifestyle. So parents determine what food is given to the children. The nutritional status of the children is highly dependent on the type or amount of the food given by their parents. And the parental knowledge on food and nutrition is the main factor that contributes to the decision making in case of food. And that food proves vital In case of shaping a child’s nutritional status.  So parental knowledge and children nutritional status are factors extremely coherent to each others. Few studies have explored whether or how nutrition knowledge interacts with education when or whether they act as substitutes or complements.  Exceptions include research in Nicaragua, ²⁷ and Myanmar ²⁸that show that maternal education and certain types of nutrition knowledge are significantly but independently associated with child outcomes.  Similarly, another study²⁹ found that maternal knowledge (rather than schooling) in Morocco is a strong contributor to child height-for-age. Another study also reports that maternal schooling in the United States has a strong impact on children’s diets.³⁰ In another study in Malaysia shows that,  most parents (62.3%) felt their child had normal weight, 22.1% felt that their child was underweight, 14.7% felt that their child was overweight and only 1% felt that their child was obese. The accuracy varied widely across the actual weight status. Parents were found to underestimate their child weight status with 78 (38.2%) of the parents inaccurate in their perception.³¹

In a study undertaken in North America to find the status of parents misinterpretation of child’s nutritional status showed that 16%, 55%, and 77% of normal weight, under weight and overweight or obese children were perceived inaccurately, respectively.³²

The more access parents get to source of knowledge the better they can decide what is right for their children. And sometimes the educational level of a parent can cause change in perception towards children’s nutrition. Thus socio demographic status of a population acts as a driving factor in case of parental knowledge about nutrition.

Knowledge and practice of the parents can affect the nutritional status of the children. For example parental knowledge can lead to inappropriate preventive health measures such as unhealthy dietary habits, lifestyle etc which can be risk factors for malnutrition of the children. Parents serve as role models for eating behavior and their support is needed to make changes in children’s eating behavior.

A very few studies have been done on knowledge regarding nutrition and nutritional status of children. No published information is available on parental knowledge regarding nutritional status of children in Bangladesh. This study aims to assess parental knowledge on nutrition and its effect on nutritional status of children. And its findings will be used to create an appropriate strategy that can address malnutrition and help plan to combat the malnutrition problem among Bangladeshi primary school children.

Literature Review

Nutritional knowledge is greatly about interpretation of child’s growth by parents. So the perception of growth and nutritional knowledge form a base in constructing the actual nutritional status of child.

Sometimes misperception is a major cause of malnutrition. Many studies especially in United Kingdom, United States and Australia have demonstrated that parents tend to underestimate their child’s weight status. Around 32%to 89.5% of parents had an inaccurate perception of their child’s weight status.^33-36 The parental inaccuracy of their child’s weight status was associated with parents of low education and parents with female, older and higher BMI children.^{33, 35} Other factors which might affect parental misperception were cultural difference in the acceptance of large body habitus and inadequate understanding on overweight and its health implications.^{35, 37}

The condition of health of a person that is influenced by the intake and utilization of nutrients is called nutritional status.³⁸

The worldwide size of this group is estimated at 2 billion people. The increasing rates are a result of changing lifestyles and industrialization with the associated increasing rate of television viewing and playing with computer games, consumption of high calorie and high fat foods coupled with low levels of energy expenditure in the form of low physical activity.³⁹

The incidence of underweight children has been consistently reported at about 45%, which compares with an average incidence of underweight children in Sub Saharan Africa in the 90’s of 33%.(World Bank, 2000) Similarly, surveys in Ethiopia have consistently found more than half the children under five stunted, with stunting rates most often attaining more than 60%.⁶ By way of comparison, during the mid 90’s, the average prevalence of children stunted for 19 Sub Saharan African countries is 39%.⁷

In the United States of America (USA), the average rates for overweight and obesity among children have been reported to be 22% and 11% respectively, while in the state of Carolina, it was 32.4% and 16.4% respectively. ¹⁰ Figures for overweight and obesity for Spain and Italy were 40%, and for Canada 25.3%. ^11-13

This epidemic of childhood overweight is worldwide; in particular some Middle East and Asian countries have documented a significant increasing rate in the past decade.^{14-19 In the Islamic Republic of Iran it has been reported that the prevalence of overweight has been increasing in the country.20}

Nutritional status of children in South- East Asia:

In Malaysia, the reported prevalence of overweight children in Kuala Lumpur ranged from 5.8% to 17.8%.^{21, 23}

South Asia has experienced high economic growth during the last decade. South Asia, however, still has both the highest rates and the largest numbers of undernourished children in the world. While poverty is often the underlying cause of child under nutrition, the high economic growth experienced by South Asian countries has not made an impact on the nutritional status of South Asian children. Addressing the causes of under nutrition is particularly important as it impedes productivity, economic growth, and poverty reduction. A child undernourished during its first two years of life is less likely to complete school and will earn, on average, a 10-17% lower income than well nourished children. There is an urgent need to build a strong, healthy and well-nourished population that can make the most of education and employment opportunities available in today’s rapidly globalizing world.²⁴

Afghanistan:

Afghanistan has made considerable improvements in some health indicators over the past 5 years. The indicators for child and maternal under nutrition remain low and are among the highest in the world. National Nutrition Survey in 2004-05 found over half (54%) of children below five years are chronically undernourished and 39% low weight for their age.²⁴

Sri-Lanka:

Sri-Lanka has experienced marked improvements in the nutritional status of young children over the past 2 decades, with underweight and stunting rates declining significantly between 1987 and 2000 .  Underweight rates declined by almost 25% in that time period from “very high” levels to “high” levels, according to WHO classification.  Stunting rates, a measure of long term under-nutrition, declined even more, by about 75% to a “low” level classification from that of “high”. As a result, Sri Lanka has the lowest prevalence of underweight in South Asia.  The aggregate trends (1993-2000) in underweight rates suggested that Sri Lanka was likely to achieve its Millennium Development Goal target of 19% prevalence of underweight in 2015. ²⁴

Nepal:

The 2006 Nepal Demographic and Health Survey (NDHS) survey found 45% and 43% of children below the age of 5 years to be underweight and stunted, respectively.

Almost 54% of children under five years old from household in the poorest quintile were found to be underweight compared to around 24% in the wealthiest quintile (NDHS 2006). Only 37% of children from the Eastern region of Nepal were underweight compared to 53% from the Mid-western region.

In a study 61% of the students were found to be malnourished. The students were more stunted (21.5%) than wasted (10.4%). Only 5.4 % of the students were found to be both wasted and stunted. ²⁴

Pakistan:

Although the problem of malnutrition has been recognized in Pakistan for several decades as underlying much of infant and under-5 mortality, the country still suffers from high rates of childhood malnutrition and has made little progress in the past 20 years to address the issue. With about 38% and 40% of children under five years old reported to be underweight and stunted, respectively, the burden of child malnutrition is lower than some countries in South Asia (India, Bangladesh and Nepal) but still much higher than most countries in Sub-Sahara Africa. ²⁴

India:

Whilst India celebrates its booming economy and GDP growth, the country remains one of the most malnourished in the world today. The Third National Family Health Survey (NFHS) in 2005 found 46% and 38% of children below the age of 3 years to be underweight and stunted, respectively.

The rates are highest amongst scheduled tribes and scheduled castes, with 54% being stunted. Child malnutrition in rural areas is also much higher (51% stunting and 46% underweight) than in urban areas (40% of children are stunted and 33 % are underweight) and also among the poorest income quintiles (60% stunting) compared with the middle quintiles (50% stunting). Similarly while 60% children from the poorest quintiles are stunted, 50% of children in the middle income quintiles are stunted. However, contrary to expectations in the South Asia region, the data from the NHFS survey found no disparities in under nutrition between boys and girls, and hence both groups were about equally likely to be undernourished.   Moreover, several studies have also concluded that it is unlikely that the MDG target of halving the prevalence of underweight to 27% by 2015 will be met. ²⁴

Nutritional status of children in Bangladesh:

Like other counties in the South Asia region, the levels of child under nutrition in Bangladesh are among the highest in the world. While the country made significant progress reducing all anthropometric measures of nutrition in the 1990s, stunting, underweight, and wasting, progress slowed markedly after 2000.  Stunting continued to fall reflecting the gains of the 1990s but child underweight rates barely changed, falling just 2 percentage points to 46% in the 7 years up to 2007 (Figure 1 Source: Bangladesh Demographic Health Surveys 2004 and 2007).  The most alarming trend is that the level of wasting has increased by more than 50% in the same 7 years, from 10 % in 2000 to 16% in 2007.  To date there has been little recognition of this and no policy response despite it being above the emergency threshold of 15%, constituting a crisis situation according to the WHO classification. ²⁴

Stunting is most common in poorest households where more than 50% of the children are too short for their age, compared to only 26% in the wealthiest households. Stunting is also more prevalent in rural areas (45%) than in urban areas (36%), and among uneducated mothers as opposed to those with higher education.

Deficiencies in some key micronutrients that have important adverse effects remain widespread among children and adults in Bangladesh. A recent study by the Institute of Public Health and Nutrition (IPHN) reported a high prevalence of anemia across all vulnerable groups – 46% among pregnant women, 64% among 6-23 months old children and 42% among 24-59 months old children. Of concern is that location specific studies indicate that iron deficiency anemia showed no improvement from 1996/97 to 2006/7 despite reductions in poverty. Iodine deficiency is also of public health concern throughout the country, with about 34% of children 6-12 years old and 39% among the 15-44 years age group suffering from subclinical Iodine Deficiency Disorders according to a national nutrition intervention.

Recent study in primary school children in Dhaka city had showed the prevalence of obesity was 52% and overweight 13%.²⁶Obese children had been shown to have a higher tendency to become obese adults and carry long term health consequences.⁴⁰  Early intervention is therefore required in these overweight and obese children. The treatment for overweight and obese children involves cooperation of both the children themselves and parents or caregivers. Parents are the vital promoter of healthy eating and lifestyle for their children.

In case of obese children the parental influences can come in varying forms. Such as encouragement to sports and outdoor activities can contribute a lot in motivating children to burn calories while having fun. But the correct perception of obesity is a must for parents. This again exudes the importance of parental knowledge of nutrition for the greater good of children’s nutritional status. On the other hand under nourishment can be fought when parents can interpret balanced diet in an apt way. That way the child will not run the risk of obesity and also be able to fight challenges associated with under nutrition.

Malnutrition:

When there is a lack or excess intake of one or more nutrients and/or faulty utilization of nutrients in our body, it leads to the state of imbalance in the body. This condition is known as malnutrition.

There are two types of malnutrition. The condition of health of a person that results due to the lack of one or more nutrients is called under nutrition. However, when there is an excess intake of nutrients, it results in over nutrition.

Acute malnutrition is a devastating public health problem of epidemic proportions. Worldwide, some 55 million children under the age of five suffer from acute malnutrition and 19 million of these from the most serious type – severe acute malnutrition. Every year, 5 million children die of malnutrition.

The World Health Organization cites malnutrition as the gravest single threat to the world’s public health.

Two type of Malnutrition:

Under nutrition:

Primary malnutrition -occurs in parts of the world wherein most of its population is undernourished because of famine, poverty and limited crop production. Primary malnutrition affects mostly children in underdeveloped countries. Kwashiorkor is a common type of primary malnutrition that is caused by a diet that is low in protein and certain other nutrients but contains adequate calories, which are derived mainly from carbohydrates. Kwashiorkor is common in areas with famine and people with low level of education, which can lead to inadequate knowledge of proper diet. Another form of primary malnutrition is Marasmus result from a diet that is low in both protein and calories. It is characterized by energy deficiency. The weight of the child with marasmus may reduce to less than 80% of the normal weight for that height. Marasmus occurrence increases before the child reaches the age of 1, whereas Kwaskiorkor occurrence increases after 18 months.

• Symptoms of Marasmus: Emaciation (is a condition wherein a human loses substantial amounts of much needed fat and muscle tissue, which makes the person very thin) and Diarrhea
• Symptoms of Kwaskiorkor: Edema or swelling due to water retention, stunned growth, skin rashes, lightening of hair color and apathy.

Secondary malnutrition is the result of an underlying disease which includes: eating disorder like anorexia nervosa or bulimia, cancer and certain digestive system disorders can eventually cause malnutrition because the affected person may not be able to swallow or digest food or absorb the nutrients derived from food. People who have an alcohol or drug addiction may lose interest in food, which can lead to severe malnutrition.

Some diseases that can lead to secondary malnutrition are beriberi (lack of vitamin B1), pellagra (vitamin disease caused by lack of niacin and protein), rickets (disease caused by lack of vitamin D causing soft bone) and scurvy (vitamin deficiency diseases), anemia and endemic goiter (mineral deficiency diseases).

Malnutrition is the condition that results from taking an unbalanced diet in which certain nutrients are lacking, in excess (too high an intake), or in the wrong proportions.^{41, 42}

There are three types of protein-energy malnutrition in children:

Acute malnutrition or Wasting or thinness: Acute inadequate nutrition leading to rapid weight loss or failure to gain weight normally.

Chronic malnutrition or Stunting or shortness: Inadequate nutrition over long period of time leading to failure of linear growth.

Acute and chronic malnutrition or Underweight: A combination measure, therefore, it could occur as a result of wasting, stunting, or both.

These forms of protein-energy malnutrition in children can be pictured like this:

Wasting and stunting are very different forms of malnutrition. Stunting is chronic and its causative factors are poorly understood. Stunting usually does not pose an immediate threat to life and is relatively common in many populations in less-developed countries. This is not to say that it is unimportant, just less important than wasting in humanitarian emergencies. Wasting results from an acute shortage of food, is reversible with re-feeding, and has a relatively high mortality rate. For these reasons, wasting is the highest priority form of malnutrition in humanitarian emergencies.

Micronutrient deficiencies may also be important in an emergency-affected population. In fact, they can cause a large proportion of deaths in children and adults in populations after the acute phase of the emergency when infectious diseases and acute malnutrition are under relative control.

Many outbreaks of otherwise rare micronutrient deficiencies, such as scurvy (vitamin C deficiency), pellagra (niacin deficiency), beriberi (thiamine deficiency), and others, have occurred in such populations.

Deficiencies of iron, vitamin A and zinc are ranked among the World Health Organization’s (WHO) top 10 leading causes of death through disease in developing countries:

Iron deficiency is the most prevalent form of malnutrition worldwide, affecting millions of people. Iron forms the molecules that carry oxygen in the blood, so symptoms of a deficiency include tiredness and lethargy. Lack of iron in large segments of the population severely damages a country’s productivity. Iron deficiency also impedes cognitive development, affecting 40-60 percent of children aged 6-24 months in developing countries.⁴³

Vitamin A deficiency weakens the immune systems of a large proportion of under-fives in poor countries, increasing their vulnerability to disease. A deficiency in vitamin A, for example, increases the risk of dying from diarrhoea, measles and malaria by 20-24 percent. Affecting 140 million preschool children in 118 countries and more than seven million pregnant women, it is also a leading cause of child blindness across developing countries.⁴⁴

Iodine deficiency affects 780 million people worldwide. The clearest symptom is a swelling of the thyroid gland called a  goitre. But the most serious impact is on the brain, which cannot develop properly without iodine. According to UN research, some 20 million children⁴⁵ are born mentally impaired because their mothers did not consume enough iodine. The worst-hit suffer cretinism, associated with severe mental retardation and physical stunting.

Zinc deficiency contributes to growth failure and weakened immunity in young children. It is linked to a higher risk of diarrhoea and pneumonia, resulting in nearly 800,000 deaths per year.

Over-nutrition

We have just explored one side of malnutrition; however often in we only hear one side of the story. Over-nutrition is one of the biggest problems now facing the developed world and in some parts of the developing world. In countries with growing affluence there has been a shift away from traditional foods to processed foods. Over-nutrition occurs when the body absorbs to many nutrients. This form of malnutrition mainly occurs in first world countries where food (especially processed) is readily available.

Over-nutrition can be caused by:

• Changing metabolism
• Unbalanced diet
• Overeating
• Micronutrient poisoning (excess micronutrient intake)

Parents are responsible for the reasonable upbringing of their children. Their educational status and occupational fields affect their view on nutrition and child care. Besides a family’s income is highly dependent on their occupation, and the income pulls the strings of the type of food given in household. Education, occupation, outlook contribute to parental knowledge of nutrition, which later influences child’s nutritional status. Children’s gender and age have also been proved important in case of their nutrition. As often primary school age children are victims of unruly situations which change their food habits. Besides gender disparity often comes into act and creates nutritional problems in different cases. The habitat in which the children grow up also contributes largely in the child’s nutrition as it determines what types of food a child has easy access to.

Objectives

• To assess parental knowledge on healthy diet and nutrition.
• To assess the nutrition status among primary school children.
• To assess the association between parental knowledge vs socio-demographic factors.
• To assess the association between parental knowledge vs nutritional status of primary school children.

Methodology

Study design: 

A school based cross-sectional study was conducted in urban primary school in Dhaka city. 3 schools named Udayan Higher Secondary School, Govt. Laboratory High School and College and Azimpur Girl’s High School and College was selected for this study. The study aimed to assess the parental knowledge on nutrition and its effect on their children nutritional status by interview with the respondents.

Study area:

Udayan Higher Secondary School, is a non- government, co-education school, Govt. Laboratory High School and College, is a government, boys school and Azimpur Girl’s High School and College , is a government, girls school.

Study population:

Study populations were 5-10 years old children from selected schools in Dhaka city.

Inclusion criteria:

• Parents willing to participate.
• Children of primary school age 5-10 years of the selected school.

Exclusion criteria:

• Parents willing to participate.
• Children from other than selected primary school. 

Study Period:

The study period was six months duration from January’11 to June ’11. The study was started with protocol presentation and finished with submission of final report. Data collection was started from April’11 to May’11.

Sample size:

Parents were found to underestimate their child weight status with 78 (38.2%) of the parents inaccurate in their perception.³¹ 

Here, Z= 95% CI = 1.96 P= 38.2% = 0.382 q = (1-p) = (1-0.382) = 0.618 d = 70% = 0.07

Calculation:

Z2 p q

 

d2

n =

(1.96)2×0.382×0.618

 

(0.07)2

=

= 185

Data collection technique and instrument:

In a self-administered questionnaire, parents (either mother or father) gave information on the socio-demographic profiles and rated their perception of child’s weight as “underweight”, “normal”, “overweight”, “pre obese” and “obese”. Additional questions were on nutrition and obesity which include the definition of a balance diet, identifying CHO rich foods, Protein rich foods, Fat rich foods, Vitamin and Mineral rich foods, practice to reduce fat in food, obesity complications and practice to reduce weight, EPI schedule etc.

The correct responses were given one mark and the wrong or “do not know” answers were given a zero mark. The parental knowledge score was calculated from the percentage of correct answers. The children weight and height were measured using a weighing machine with an attached height scale. Body mass index (BMI) of the children was calculated using the formula of weight in kilograms divided by height in meters squared. And Z score will be calculated also for analyze the nutritional status.

Collected data will be analyzed by using appropriate statistical technique. All statistical analysis will be performed with the software SPSS 11.5 for windows.

Conceptual Framework:

Data Analysis

The main objective of this study was to assess the parental knowledge on nutrition and its effect on nutritional status of the children. This was a cross-sectional study. My study area were selected schools; Udayan Higher Secondary School, Govt. Laboratory High School and College, and Azimpur Girl’s High School and College. Total 150 parents were interviewed.

Socio-demographic characteristics 

Child’s age in month:

Total 150 children were studied.Table-1.1 shows the distribution of the children age. The distribution pattern is age group each of 12 months. However age 109 to 120 months showed maximum number of 49 children (32.7%). Their median age is 99 months. Their mean age was 97.95 months with standard deviation of 14.845 months.

Table 1.1: Distribution of child’s age in month

 

Age in month	No (%)
61 to 72	4.0
73 to 84	10.0
85 to 96	29.3
97 to 108	24.0
109 to 120	32.7
(Mean ±Std. Deviation)	97.95 ±14.845
Total	100.0

Child’s sex:

Figure- 1.1 shows the distribution of the children by sex. Out of 150 children 82 (54.7%) were males and 68 (45.3%) were female.

Child’s religion:

Among the 150 children 137 (91.3%) were Muslims, 12 (8%) were Hindus and 1 (0.7%) were Christian (Figure-1.2).

Child’s education:

Table-1.2 shows distribution of the children by their level of education. 15.3% are from class I, 22.7% are from class II, 29.3% are from class III, and 32.7% are from class IV.

Table 1.2: Distribution of child by educational level

Education	No (%)
Class I	15.3
Class II	22.7
Class III	29.3
Class IV	32.7
Total	100.0

Parents’ education:

Table -1.3 shows distribution of the parents by their education level. Most of the parents, 77 (51.3%) mothers and 134 (89.3%) fathers are graduate and above. On the other hand, 1 (0.7%) and 1 (0.7%) mother had no formal education and primary level education, respectively. But there was no one amongst the fathers below secondary level education.

Table 1.3: Distribution of parents by educational level

Mother’s education	No (%)
No formal education	.7
Primary	.7
Secondary	2.0
S.S.C.	4.7
H.S.C.	40.7
Graduate & above	51.3
Father’s education	No (%)
Secondary	.7
S.S.C.	2.0
H.S.C.	8.0
Graduate & above	89.3

Parent’s occupation:

Majority of the mothers i.e. 115 out of 150 (76.67%) were housewife and majority of the fathers 81 (54%) were businessman. 22% mothers and 26% fathers were service holders. On the other hand, 2 mothers out of 150 (1.33%) were businessman. The fathers under the other category were 33 (20%) included media personnel, working abroad. (Table-1.4)

Table 1.4: Distribution of parents by occupation

Mother’s occupation	No (%)
Service	22
Business	1.33
Housewife	76.67
Father’s occupation	No (%)
Service	26.0
Business	54.0
Others	20.0

 Monthly income of the family:

The mean monthly family income of the children was 58396.67 taka per month with standard deviation of 33890.828 taka per month. Their median monthly income was Tk 50000 (range Tk. 10,000 – Tk. 1, 60,000) per month. (Table-1.5)

Table 1.5: Distribution of the child’s family by monthly income

Monthly income	No (%)
Below 20000	4.7
20000 to 50000	55.3
50000 to 80000	26.0
80000 to 100000	4.0
Above 100000	10.0
(Mean ±Std. Deviation)	58396.67 Tk/ month ±33890.828 Tk/ month
Total	100.0

Family size:

Figure- 1.3 shows out of 150 children 85 (56.7%) had below 4 family members, 54 (36%) had 4 to 6 family members and 11 (7.3%) had above 6 family members.

Knowledge about BMI, health and diet

Table -2.1 shows the parents knowledge about BMI, healthy diet and nutrition and whether they get information or not about nutrition. 117 (78%) out of 150 parents don’t know about BMI and 33 (22%) parents know about BMI. 6% of them don’t gets information about healthy diet and nutrition and 94% gets information about healthy diet and nutrition. 91.3% of the parents get all those information from proper sources such as, educational background, books, media etc and 8.7% don’t get information from proper sources.

Table 2.1: Knowledge about BMI and nutrition and healthy diet

Parameters	No (%)
Knowledge about BMI
Incorrect or Don’t know	78.0
Correct	22.0
Get information about nutrition and healthy diet
No	6.0
Yes	94.0
Gets information about nutrition and healthy diet from whom & where
No	8.7
Yes	91.3

Knowledge about exclusive breast feeding, colosrtum feeding and complimentary feeding:

Table-3.1 shows the parents knowledge about exclusive breast feeding, colostrums and complimentary feeding. Out of 150 parents 100% had knowledge about exclusive breast feeding and colostrums feeding. But 0.7% doesn’t know about complimentary feeding and rest of them i.e. 99.3% had knowledge about complimentary feeding.

Table 3.1: Distribution of knowledge about exclusive breast feeding, Colostrum and complimentary feeding

Variables	Yes	No
Exclusive breast feeding	150 (100.0%)	0 (0%)
Knowledge about Colostrum	150 (100.0%)	0 (0%)
Complimentary feeding	149 (99.3%)	1 (0.7%)

Knowledge about timing of exclusive breast feeding:

Table-3.2 shows the distribution of the knowledge on timing of exclusive breast feeding. 97.3% out of 150 parents’ knowledge about timing of exclusive breast feeding is correct, that is up to 6 months.

Table 3.2: Distribution of knowledge about timing of exclusive breast feeding

Timing of exclusive breast feeding	No (%)
	Yes	No	Don’t know
Up to 2 months	3.3	96	0.7
Up to 6 months	97.3	2.7	00
Up to 12 months	10.7	83.3	6

Knowledge regarding life style of the family

Out of 150 parents 99.3% of them feed their children family food during diarrhoea and 0.7% doesn’t give their children family foods. 100% parents used iodized salt. And 20% of the children had wrong meal frequency such as more than 5 times or less than 3 times and 80% children had correct habit of meal frequency within 3 to 5 times. (Table-4.1)

Table 4.1: Distribution of knowledge regarding life style of the family

Parameters	No (%)
Feed family food to children during diarrhoea
Incorrect or Don’t know	.7
Correct	99.3
Use iodized salt
No	0
Yes	100.0
Frequency of taking meal of the child
Incorrect or Don’t know	20.0
Correct	80.0

Table-4.2 shows the knowledge about healthy lifestyle. 88%, 90%, 99.3%, 99.3%, 64.7% and 90% parents about Chips, Somucha, Burger, French fries, Ice cream and Singara are Fast food is correct, respectively.  And 37.3% parents said Cake is Fast food, which is incorrect.

100% parents said that remove excess oil from cooked food is a way of reduce fat form food, which is correct. Most of them,96%, 58%, 36.7% parents knowledge is remove fat in meat before cooking, remove skin of a chicken before cooking, boil or steam fish are the way of reducing fat from food, respectively, whcich are correct answers.

99.3%, 92.7%, 98.7%, 97.8% parents answer were exercise/ Playing, avoid overeating, eat at regular time every day, eat more fruits and vegetables, respectively correct. But 98% and 99.3% parents said skip meal, lunch or dinner and over eat in order to finish and not to waste food are the steps of reduce child’s weight, which are incorrect answers.

Table 4.2: Distribution of knowledge regarding life style of the family

Parameters	No (%)
Knowledge about fast food	Yes	No	Don’t know
Cake	37.3	60	2.7
Chips	88	12	00
Biscuit	8.7	91.3	00
Somucha	90.7	9.3	00
Burger	99.3	0.7	00
French fries	99.3	0.7	00
Bread	5.3	92	2.7
Ice cream	64.7	30.7	4.7
Singara	90	10	00
Reduce fat from food	Yes	No	Don’t know
To remove skin of a chicken before cooking	58	5.3	36.7
To remove fat in meat before cooking	96	2	2
To remove excess oil from cooked food	100	00	00
To dip fry food in sugar	2	42	56
To dip fry chicken	1.3	43.3	55.3
To boil or steam fish	36.7	10	53.3
To grill or bake fish	0.7	16.7	82.7
To remove fat layer from forzen food	0.7	3.3	96
Life style of the child to reduce weight	Yes	No	Don’t know
Exercise/ Playing	99.3	0.7	00
Avoid overeating	92.7	7.3	00
To skip meal, lunch or dinner	98	1.3	0.7
Eat at regular time everyday	98.7	1.3	00
Over eat in order to finish and not to waste food	99.3	0.7	00
Eat more fruits and vegetables	97.3	1.3	1.3

Mother takes post partum vitamin A supplementation (PPVAS):

 22 (14.7%) parents among 150 parents didn’t take post partum vitamin A supplementation and 128 (85.3%) parents took PPVAS. (Figure-4.3)

Knowledge regarding health and nutrition

Knowledge about 1^st class protein and 2^nd class protein:

Table-5.1 shows the parental knowledge about 1^st class protein and 2^nd class protein. Daal is a 2^nd class protein, but 44.7% parents said this is a 1^st class protein. And 40.7% parents said this is 2^nd class protein and 14.7% don’t know about it. Egg is 1^st class protein, 84.7% said this is 1^st class and 2% said 2^nd class and 13.3% don’t know about it. Milk is 1^st class protein and 85.3% said 1^st class, 1.3% said 2^nd class and 13.3% don’t know. Wheat is 2^nd class protein 68.7% said 2^nd class, 9.3% said 1^st class and 22% don’t know. Meat is 1^st class protein and 75.3% said 1^st class, 9.3% said 2^nd class and 15.3% don’t know. Nuts and Beans are 2^nd class protein, 16% and 16.7% said 2^nd class, respectively. Fish, Yogurt, Chicken are 1^st class protein and 83.3%, 44.7%, 80.7% said 1^st class, respectively.

Table 5.1: Distribution of knowledge on 1^st class and 2^nd class protein

Food name	No (%)
	1st class	2nd class	Don’t know
Daal	44.7	40.7	14.7
Egg	84.7	2.0	13.3
Milk	85.3	1.3	13.3
Wheat	9.3	68.7	22.0
Meat	75.3	9.3	15.3
Nuts	53.3	16.0	30.7
Fish	83.3	3.3	13.3
Yogurt	44.7	21.3	34.0
Chicken	80.7	4.0	15.3
Beans	41.3	16.7	42.0

Knowledge about different type of deficiency disorders:

Table-5.2 shows knowledge about Vitamin A deficiency disorder. Night blindness is vitamin A deficiency disorder, 96.7% parents said it correctly. But 6.7%, 26%, 10% said Scurvy, Anemia and Beriberi as vitamin A deficiency disorder, respectively, which is incorrect.

Delayed physical development, Goiter, Hypothyroidism are iodine deficiency disorders. 80%, 100% and 10% parents said these are iodine deficiency disorders. But 87.3% don’t know about Hypothyroidism.

Anemia is iron deficiency disorder, and 61.3% parents give the correct answer.

Table 5.2: Distribution of knowledge about different types of deficiency disorders

Parameter	No (%)
Vitamin A deficiency disorder	Yes	No	Don’t know
Scurvy	6.7	92	1.3
Anemia	26	44	30
Night blindness	96.7	3.3	00
Beriberi	10	46.7	43.3
Iodine deficiency disorder	Yes	No	Don’t know
Night blindness	5.3	142	00
Delayed physical development	80	15.3	4.7
Goiter	100	00	00
Hypothyroidism	10	2.7	87.3
Anemia	18	36.7	75.3
Iron deficiency disorders	Yes	No	Don’t know
Goiter	10	85.3	4.7
Anemia	61.3	4	34.7
Night blindness	23.3	63.3	13.3
Hypothyroidism	8.7	4.7	86.7

Distribution of knowledge about reducing iodine deficiency:

Table-5.3 shows the distribution of the parental knowledge for reducing iodine deficiency disorders. 100% parents knowledge is correct about using iodized salt. But 11.3%, 85, 3.3% and 2.7% parents said rice, chicken, mango and bread can reduce iodine deficiency disorder, respectively.

Table 5.3: Distribution of knowledge about reducing iodine deficiency

Foods	No (%)
	Yes	No	Don’t know
Chicken	8	89.3	2.7
Using iodized salt	100	00	00
Rice	11.3	84	4.7
Mango	3.3	96	0.7
Bread	2.7	91.3	6

Distribution of knowledge about disease related with obesity:

Table-5.4 shows 100% parents know that diarrhea is not obesity related disease. But 27.3%, 82.7% and 10% parents said ARI, Kidney disease and Jaundice is obesity related disease, respectively; which is wrong.

Table 5.4: Distribution of knowledge about disease related with obesity 

Disease related to obesity	No (%)
	Yes	No	Don’t know
Diarrhoea	.0	100	.0
Cardiovascular disease	98	2	.0
ARI	27.3	17.3	55.3
Diabetes mellitus	95.3	4.7	.0
Kidney disease	82.7	12	5.3
Jaundice	10	82.7	7.3
UTI	6.7	26	67.3

Nutritional status of the children

Nutritional status by BMI (z score) of the child:

Table 6.1 shows nutritional status of the children by BMI (z score). Out of 150 children 5.3% children were severely thin (z score <-3), 82.7% were normal (z score -2 to +1), 10.7% were overweight (z score +1.01 to +2) and 1.3% were obese (z score >+2). Mean BMI of the children was 16.2095 and standard deviation is 3.05131. Their median BMI was 15.2662 (range 11.97 to 29.96).

Table 6.1: Distribution of nutritional status by BMI (z score) of the child

Nutritional status		No (%)
<-3	Severe thinness	5.3
-2 to +1	Normal	82.7
+1.01 to +2	Overweight	10.7
>+2	Obesity	1.3
(Mean ±Std. Deviation)	16.2095 ±3.05131

Nutritional status by weight for height (z score) of the child:

6% out of 150 children were moderately wasted (z score -3 to -2), 88% of them were normal (z score -2.01 to +2), 4% were overweight (z score +2.01 to +3) and 2% were obese (z score >+3). Mean z score by weight for height of the children was -0.3618 and standard deviation was 1.24260. Range of the z score was -2.50 to 4.85 with the median of -0.6714 z score of weight for height.(Table 6.2)

Table 6.2: Distribution of nutritional status by weight for height (z score) of the child

Nutritional status		No (%)
-3 to -2	Moderate wasting	6.0
-2.01 to +2	Normal	88.0
+2.01 to +3	Overweight	4.0
>+3	Obese	2.0
(Mean ±Std. Deviation)	-0.3618 ±1.24260

Nutritional status by height for age (z score) of the child:

Table 6.3 shows the nutritional status of the children by height for age (z score). 0.7% children were moderately stunted (z score -3 to -2), 87.3% were normal (z score -2.01 to +2), 8.7% were tall (z score +2.01 to +3) and 3.3% were very tall (z score >+3).

Table 6.3: Distribution of nutritional status by height for age (z score) of the child

Nutritional status		No (%)
-3 to -2	Moderate stunting	.7
-2.01 to +2	Normal	87.3
+2.01 to +3	Tall	8.7
>+3	Very tall	3.3

Nutritional status by weight for age (z score) of the child:

93.3% out of 150 children were normal (z score -2.01 to +2), 4.7% of them were overweight (z score +2.01 to +3) and 2% were obese (z score >+3). Mean z score by weight for age of the children was 0.1704 and standard deviation was 1.27238. Range of the z score was -1.71 to 6.17 with the median of -0.0769 z score of weight for height. (Table 6.4)

Table 6.4: Distribution of nutritional status by weight for age (z score) of the child

Nutritional status		No (%)
-2.01 to +2	Normal	93.3
+2.01 to +3	Overweight	4.7
>+3	Obese	2.0
(Mean ±Std. Deviation)	0.1704 ±1.27238

Nutritional status of the male and female child separately:

 Nutritional status by BMI (z score) of the male and female child separately:

Table-7.1 shows nutritional status of the children by BMI (z score). Out of 82 male children 4.9% children were severely thin (z score <-3), 85.4% were normal (z score -2 to +1), 8.5% were overweight (z score +1.01 to +2) and 1.2% were obese (z score >+2). Mean BMI of the male children was 15.9419 and standard deviation is 2.81397.

Out of 68 female children 5.9% children were severely thin (z score <-3), 79.4% were normal (z score -2 to +1), 13.2% were overweight (z score +1.01 to +2) and 1.5% were obese (z score >+2). Mean BMI of the male children was 16.5323 and standard deviation is 3.30741.

Table 7.1: Distribution of nutritional status by BMI (z score) of the male and female child separately

Nutritional status (Male)		No (%)
<-3	Severe thinness	4.9
-2 to +1	Normal	85.4
+1.01 to +2	Overweight	8.5
>+2	Obesity	1.2
(Mean ±Std. Deviation)	15.9419 ±2.81397
Nutritional status (Female)		No (%)
<-3	Severe thinness	5.9
-2 to +1	Normal	79.4
+1.01 to +2	Overweight	13.2
>+2	Obesity	1.5
(Mean ±Std. Deviation)	16.5323 ±3.30741

Nutritional status by weight fog height (z score) of the male and female child separately:

6.1% out of 82 male children were moderately wasted (z score -3 to -2), 90.2% of them were normal (z score -2.01 to +2), 1.2% were overweight (z score +2.01 to +3) and 2.4% were obese (z score >+3). Mean z score by weight for height of the children was -0.4919 and standard deviation was 1.12990.

5.9% out of 68 female children were moderately wasted (z score -3 to -2), 85.3% of them were normal (z score -2.01 to +2), 7.4% were overweight (z score +2.01 to +3) and 1.5% were obese (z score >+3). Mean z score by weight for height of the children was -0.2048 and standard deviation was 1.35817. (Table 7.2) 

Table 7.2: Distribution of nutritional status by weight for height (z score) of the male and female child separately

Nutritional status (Male)		No (%)
-3 to -2	Moderate wasting	6.1
-2.01 to +2	Normal	90.2
+2.01 to +3	Overweight	1.2
>+3	Obese	2.4
(Mean ±Std. Deviation)	-0.4919 ±1.12990
Nutritional status (Female)		No (%)
-3 to -2	Moderate wasting	5.9
-2.01 to +2	Normal	85.3
+2.01 to +3	Overweight	7.4
>+3	Obese	1.5
(Mean ±Std. Deviation)	-0.2048 ±1.35817

Nutritional status by height for age (z score) of the male and female child separately:

Table-7.3 shows the nutritional status of the children by height for age (z score). 1.2% male children were moderately stunted (z score -3 to -2), 86.6% were normal (z score -2.01 to +2), 8.5% were tall (z score +2.01 to +3) and 3.7% were very tall (z score >+3).

88.2% female children were normal (z score -2.01 to +2), 8.8% were tall (z score +2.01 to +3) and 2.9% were very tall (z score >+3).

Table 7.3: Distribution of nutritional status by height for age (z score) of the male and female child separately

Nutritional status (Male)		No (%)
-3 to -2	Moderate stunting	1.2
-2.01 to +2	Normal	86.6
+2.01 to +3	Tall	8.5
>+3	Very tall	3.7
Nutritional status (Female)		No (%)
-2.01 to +2	Normal	88.2
+2.01 to +3	Tall	8.8
>+3	Very tall	2.9

Nutritional status by weight for age (z score) of the male and female child separately:

91.5% out of 82 male children were normal (z score -2.01 to +2), 7.3% of them were overweight (z score +2.01 to +3) and 1.2% were obese (z score >+3). Mean z score by weight for age of the children was 0.0202 and standard deviation was 1.26969.

95.6% out of 68 female children were normal (z score -2.01 to +2), 1.5% of them were overweight (z score +2.01 to +3) and 2.9% were obese (z score >+3). Mean z score by weight for age of the children was 0.3515 and standard deviation was 1.26115. (Table 7.4)

Table 7.4: Distribution of nutritional status by weight for age (z score) of the male and female child separately

Nutritional status (Male)		No (%)
-2.01 to +2	Normal	91.5
+2.01 to +3	Overweight	7.3
>+3	Obese	1.2
(Mean ±Std. Deviation)	0.0202 ±1.26969
Nutritional status (Female)		No (%)
-2.01 to +2	Normal	95.6
+2.01 to +3	Overweight	1.5
>+3	Obese	2.9
(Mean ±Std. Deviation)	0.3515 ±1.26115

Association between Socio-Demographic Indicators & parental knowledge on nutrition

Association between parental knowledge and mothers’ education:

Table 8.1 shows the association between parental knowledge and mothers’ education. It shows there is strong association (p<0.05) between parental knowledge and mothers’ education. Parents having Graduate and above (54.1%) have good knowledge compare to Secondary, S.S.C. and H.S.C. group which are (2.5%), (2.5%) and (41%) respectively.

Table 8.1: Association between parental knowledge and mothers’ education

Parental knowledge	Education of the mother						Total	Level of significance
	No formal education	Primary	Secondary	S.S.C.	H.S.C.	Graduate & above
Poor	0 (.0%)	0 (.0%)	0 (.0%)	0 (.0%)	2 (40%)	3 (60%)	5 (100%)	p<0.05 (.012)
Average	1 (4.3%)	1 (4.3%)	0 (.0%)	4 (17.4%)	9 (39.1%)	8 (34.8%)	23 (100.0%)
Good	0 (.0%)	0 (.0%)	3 (2.5%)	3 (2.5%)	50 (41%)	66 (54.1%)	122 (100%)

Ns= Significant                                                            c2 value = 22.719; df = 10

Association between parental knowledge and fathers’ education:

Table 8.2 shows the association between parental knowledge and fathers’ education. It shows there is strong association (p<0.05) between parental knowledge and mothers’ education. Parents having Graduate and above (91.8%) have good knowledge compare to S.S.C. and H.S.C. group which are (1.6%) and (6.6%) respectively.

Table 8.2: Association between parental knowledge and fathers’ education

Parental knowledge	Education of the father						Total	Level of significance
	No formal education	Primary	Secondary	S.S.C.	H.S.C.	Graduate & above
Poor	0 (.0%)	0 (.0%)	0 (.0%)	0 (.0%)	2 (40%)	3 (60%)	5 (100%)	p<0.05 (.033)
Average	0 (.0%)	0 (.0%)	1 (4.3%)	1 (4.3%)	2 (8.7%)	19 (82.6%)	23 (100%)
Good	0 (.0%)	0 (.0%)	0 (.0%)	2 (1.6%)	8 (6.6%)	112 (91.8%)	122 (100%)

Ns= Significant                                                            c2 value = 13.748; df = 6

Association between parental knowledge and family income:

Table 8.3 shows the association between income level and parental knowledge. The table shows there is no association (p>0.05) between income and parental knowledge.

Table 8.3: Association between parental knowledge and family income

Parental knowledge	Family income					Total	Level of significance
	<20000	20000-50000	50000-80000	80000-100000	>100000
Poor	1 (20%)	1 (20%)	1 (20%)	1 (20%)	1 (20%)	5 (100%)	p>0.05 (.183)
Average	2 (8.7%)	12 (52.2%)	8 (34.8%)	0 (.0%)	1 (4.3%)	23 (100%)
Good	4 (3.3%)	70 (57.4%)	30 (24.6%)	5 (4.1%)	13 (10.7%)	122 (100%)

Ns= Not significant                                                            c2 value = 11.399; df = 8

Total knowledge score and Nutritional status of the children

Relationship between Total knowledge score and Nutritional status of the children:

Table-9.1 shows the relationship between total knowledge score and nutritional status. There is no significant relationship between parental knowledge and nutritional status of the children.

Table 9.1: Relationship between Total knowledge score and Nutritional status of the children

Correlation		BMI (z-score)	Weight for height (z score)	Weight for age (z score)
Total score	Pearson Correlation	-.018	-.029	-.043
	Sig. (2-tailed)	.827	.723	.605

Relation between BMI (z-score) and total knowledge score and nutritional status (Weight for height z-score and weight for age z-score) of the children:

There is significant relationship between BMI (z-score) and nutritional status (Weight for height z-score and weight for age z-score). That means BMI (z score) is positively correlated with weight for height (z score) (r = 0.900, p value= 0.000) and weight for age (z score) (r = 0.799, p value= 0.000). (Table-9.2)

Table 9.2: Relation between BMI (z-score) and total knowledge score and nutritional status (Weight for height z-score and weight for age z-score) of the children

Correlation		Total score	Weight for height (z score)	Weight for age (z score)
BMI (z-score)	Pearson Correlation	-.018	.900**	.799**
	Sig. (2-tailed)	.827	.000	.000

Relation between Weight for height z-score and total knowledge score and nutritional status (BMI z-score and weight for age z-score) of the children:

Table 15.3 shows weight for height (z score) is positively correlated with BMI (z score) (r = 0.900, p value= 0.000) and weight for age (z score) (r = 0.651, p value= 0.000). (Table-9.3)

Table 9.3: Relation between Weight for height z-score and total knowledge score and nutritional status (BMI z-score and weight for age z-score) of the children

Correlation		Total score	BMI (z-score)	Weight for age (z score)
Weight for height (z score)	Pearson Correlation	-.029	.900**	.651**
	Sig. (2-tailed)	.723	.000	.000

Relation between Weight for age z-score and total knowledge score and nutritional status (Weight for height z-score and BMI z-score) of the children:

Table 15.3 shows weight for age (z score) is positively correlated with BMI (z score) (r = 0.799, p value= 0.000) and weight for height (z score) (r = 0.651, p value= 0.000). (Table-9.3)

Table 9.4: Relation between Weight for age z-score and total knowledge score and nutritional status (Weight for height z-score and BMI z-score) of the children

Correlation		Total score	BMI (z-score)	Weight for height (z score)
Weight for age (z score)	Pearson Correlation	-.043	.799**	.651**
	Sig. (2-tailed)	.605	.000	.000

Association between parental knowledge and Nutritional status

Association between parental knowledge and Nutritional status by BMI (z score):

Table 10.1 shows association between parental knowledge and nutritional status by BMI (z score). It shows there is no association (p>0.05) between parental knowledge and nutritional status by BMI (z score).

Table 10.1: Association between parental knowledge and Nutritional status by BMI (z score)

Parental knowledge	Nutritional status by BMI (z score)				Total	Level of significance
	Severe thinness (<-3)	Normal (-2 to +1)	Overweight (+1.01 to +2)	Obese (>+2)
Poor	0 (.0%)	5 (100.0%)	0 (.0%)	0 (.0%)	5 (100.0%)	p>0.05 (.812)
Average	1 (4.3%)	21 (91.3%)	1 (4.3%)	0 (.0%)	23 (100.0%)
Good	7 (5.7%)	98 (80.3%)	15 (12.3%)	2 (1.6%)	122 (100.0%)

Ns= Not significant                                                            c2 value = 2.973; df = 6

Association between parental knowledge and Nutritional status weight for height (z score):

Table 10.2 shows association between parental knowledge and nutritional status by weight for height (z score). It shows there is no association (p>0.05) between parental knowledge and nutritional status by weight for height (z score).

Table 10.2: Association between parental knowledge and Nutritional status weight for height (z score):

Parental knowledge	Nutritional status by weight for height (z score)				Total	Level of significance
	Moderate wasting (-3 to -2)	Normal (-2.01 to +2)	Overweight (+2.01 to +3)	Obese (>+3)
Poor	0 (.0%)	5 (100.0%)	0 (.0%)	0 (.0%)	5 (100.0%)	p>0.05 (.835)
Average	2 (8.7%)	21 (91.3%)	0 (.0%)	0 (.0%)	23 (100.0%)
Good	7 (5.7%)	106 (86.9%)	6 (4.9%)	3 (2.5%)	122 (100.0%)

Ns= Not significant                                                            c2 value = 2.786; df = 6

Association between parental knowledge and Nutritional status weight for age(z score):

Table 10.3 shows association between parental knowledge and nutritional status by weight for age (z score). It shows there is no association (p>0.05) between parental knowledge and nutritional status by weight for age (z score).

Table 10.3: Association between parental knowledge and Nutritional status weight for age (z score):

Parental knowledge	Nutritional status by weight for age (z score)			Total	Level of significance
	Normal (-2.01 to +2)	Overweight (+2.01 to +3)	Obese (>+3)
Poor	4 (80.0%)	1 (20.0%)	0 (.0%)	5 (100.0%)	p>0.05 (.339)
Average	22 (95.7%)	0 (.0%)	1 (4.3%)	23 (100.0%)
Good	114 (93.4%)	6 (4.9%)	2 (1.6%)	122 (100.0%)

Ns= Not significant                                                            c2 value = 4.531; df = 4

Association between parental knowledge and Nutritional status height for age (z score):

Table 10.3 shows association between parental knowledge and nutritional status by height for age (z score). It shows there is no association (p>0.05) between parental knowledge and nutritional status by height for age (z score).

Table 10.4: Association between parental knowledge and Nutritional status height for age (z score):

Parental knowledge	Nutritional status by weight for height (z score)				Total	Level of significance
	Moderate stunting (-3 to -2)	Normal (-2.01 to +2)	Tall (+2.01 to +3)	very tall (>+3)
Poor	0 (.0%)	3 (60.0%)	2 (40.0%)	0 (.0%)	5 (100.0%)	p>0.05 (.338)
Average	0 (.0%)	20 (87.0%)	2 (8.7%)	1 (4.3%)	23 (100.0%)
Good	1 (.8%)	108 (88.5%)	9 (7.4%)	4 (3.3%)	122 (100.0%)

Ns= Not significant                                                            c2 value = 6.814; df = 6

Total parental knowledge on nutrition:

Figure-11 shows the distribution of parents total knowledge score. Knowledge about nutrition was scored. Knowledge score is good 122(81.3%), have good knowledge about nutrition. 16% parents have average knowledge about nutrition. Only 3.3% have poor knowledge regarding nutrition.

Parental perception about their child’s weight status:

Figure-12 shows the parental perception about their child’s nutritional status. Out of 150 parents 97 (64.7%) are incorrect about their child’s weight status and only 53 (35.3%) are correct. And 80 (53.3%) are incorrect about their child’s height status and 70 (46.7%) are correct.

Major Findings:

Socio-demographic characteristics:

• Total 150 children were studied. The distribution pattern is age group each of 12 months. However age 109 to 120 months showed maximum number of 49 children (32.7%).
• The distribution of the children out of 150 children 82 (54.7%) were males and 68 (45.3%) were female.
• Among the 150 children 137 (91.3%) were Muslims, 12 (8%) were Hindus and 1 (0.7%) were Christian.
• 15.3% are from class I, 22.7% are from class II, 29.3% are from class III, and 32.7% are from class IV.

• Most of the parents, 77 (51.3%) mothers and 134 (89.3%) fathers are graduate and above. On the other hand, 1 (0.7%) and 1 (0.7%) mother had no formal education and primary level education, respectively. But there was no one amongst the fathers below secondary level education.

• 115 out of 150 (76.67%) were housewife and majority of the fathers 81 (54%) were businessman. 22% mothers and 26% fathers were service holders. On the other hand, 2 mothers out of 150 (1.33%) were businessman. The fathers under the other category were 33 (20%) included media personnel, working abroad.
• 55.3% family income is 20000 to 50000 taka per month.  And the range of their monthly income is 10000 to 16000 taka per month.
• Out of 150 children 85 (56.7%) had below 4 family members, 54 (36%) had 4 to 6 family members and 11 (7.3%) had above 6 family members.

Parental knowledge about nutrition:

• Few studies have explored whether or how nutrition knowledge interacts with education when or whether they act as substitutes or complements.  Exceptions include research in Nicaragua, ²⁷ and Myanmar ²⁸that show that maternal education and certain types of nutrition knowledge are significantly but independently associated with child outcomes.  Similarly, another study²⁹ found that maternal knowledge (rather than schooling) in Morocco is a strong contributor to child height-for-age.

• In this study, 81.3% have good knowledge about nutrition. 16% parents have average knowledge and only 3.3% have poor knowledge regarding nutrition.
• In this study parental knowledge and mothers’ education have strong association (p<0.05).Mothers having Graduate and above (54.1%) have good knowledge compare to Secondary, S.S.C. and H.S.C. group which are (2.5%), (2.5%) and (41%) respectively.

• The association between parental knowledge and fathers’ education have strong association (p<0.05). Fathers having Graduate and above (91.8%) have good knowledge compare to S.S.C. and H.S.C. group which are (1.6%) and (6.6%) respectively.

Parental knowledge about nutritional status of their children:

• In another study in Malaysia shows that, most parents (62.3%) felt their child had normal weight, 22.1% felt that their child was underweight, 14.7% felt that their child was overweight and only 1% felt that their child was obese. The accuracy varied widely across the actual weight status. Parents were found to underestimate their child weight status with 78 (38.2%) of the parents inaccurate in their perception.³¹
• In this study Out of 150 parents 97 (64.7%) are incorrect about their child’s weight status and only 53 (35.3%) are correct. And 80 (53.3%) are incorrect about their child’s height status and 70 (46.7%) are correct.

Nutritional status of primary school children:

Nutritional studies on primary school children in Malaysia show that, children aged 6-12 years old from five rural communities found the prevalence of underweight among boys and girls to be 29.1% and 26.1% respectively (Khor & Tee, 1997). In these communities, an average of 34.4% boys and 24.9% girls were stunted. However, the prevalence of wasting among these children (boys = 8.2%; girls = 6.2%) was much lower compared to the other two nutritional status indicators.²¹ In Malaysia, the reported prevalence of overweight  children in Kuala Lumpur ranged from 5.8% to 17.8%.^21-23

In this study, Out of 150 children 5.3% children were severely thin (z score <-3), 82.7% were normal (z score -2 to +1), 10.7% were overweight (z score +1.01 to +2) and 1.3% were obese (z score >+2). 6% children were moderately wasted (z score -3 to -2), 88% of them were normal (z score -2.01 to +2), 4% were overweight (z score +2.01 to +3) and 2% were obese (z score >+3). 0.7% children were moderately stunted (z score -3 to -2), 87.3% were normal (z score -2.01 to +2), 8.7% were tall (z score +2.01 to +3) and 3.3% were very tall (z score >+3). 93.3% children were normal (z score -2.01 to +2), 4.7% of them were overweight (z score +2.01 to +3) and 2% were obese (z score >+3).

Separately, out of 82 male children 4.9% children were severely thin (z score <-3), 85.4% were normal (z score -2 to +1), 8.5% were overweight (z score +1.01 to +2) and 1.2% were obese (z score >+2). 6.1% male children were moderately wasted (z score -3 to -2), 90.2% of them were normal (z score -2.01 to +2), 1.2% were overweight (z score +2.01 to +3) and 2.4% were obese (z score >+3). 1.2% male children were moderately stunted (z score -3 to -2), 86.6% were normal (z score -2.01 to +2), 8.5% were tall (z score +2.01 to +3) and 3.7% were very tall (z score >+3). 91.5% male children were normal (z score -2.01 to +2), 7.3% of them were overweight (z score +2.01 to +3) and 1.2% were obese (z score >+3).

And out of 68 female children, 5.9% children were severely thin (z score <-3), 79.4% were normal (z score -2 to +1), 13.2% were overweight (z score +1.01 to +2) and 1.5% were obese (z score >+2). 5.9% female children were moderately wasted (z score -3 to -2), 85.3% of them were normal (z score -2.01 to +2), 7.4% were overweight (z score +2.01 to +3) and 1.5% were obese (z score >+3). 88.2% female children were normal (z score -2.01 to +2), 8.8% were tall (z score +2.01 to +3) and 2.9% were very tall (z score >+3). 95.6% female children were normal (z score -2.01 to +2), 1.5% of them were overweight (z score +2.01 to +3) and 2.9% were obese (z score >+3).

Association between parental knowledge and nutritional status of the children:

Nutritional knowledge of parents is associated with nutritional status of children. Positive results have been reported in Asia¹, Sub-Saharan Africa², Latin America³, as well as in the United States of America⁴. Widely cited is the example of the World Bank’s first community nutrition loan to Indonesia in the 1970s which significantly improved the nutritional status of 40 percent of target children through nutrition education.⁵

In this study there is no association found between parental knowledge and nutritional status of their children.  That does not mean that there is no association. A good score on nutrition and obesity questions does not mean good knowledge in all domains of the questions. Any imbalances in knowledge domains are a potential source of problems in food habit. In this study only 40.7% parents know that daal is a 2^nd class protein and 53.3% think that nuts are 1^st class protein.

37.3% parents think Cake is a fast food and 30.7% parents think that Ice cream is not a fast food. 98% parents think that skipping meal is a step to reduce child weight. 20% parents don’t know the correct meal frequency for the child but 80% had correct knowledge about it. Parents should replace the traditional fatty cooking methods with lower fat cooking methods instead.

87.3% parents don’t know about Hypothyroidism is an Iodine deficiency disorder. But 100% parents know about using iodized salt to reduce iodine deficiency disorders.

100% parents know that diarrhea is not obesity related disease. But 27.3%, 82.7% and 10% parents said ARI, Kidney disease and Jaundice is obesity related disease, respectively; which is wrong.

In this study many of the parents failed to recognize the overweight and obesity in their own children. One of the possible reasons for this poor parental perception of their child weight status is that parents may be in denial and refused to admit of having the problem.

In one study of 1098 parents conducted in California showed that parent’s weight perception of their own children’s was not the same as in determining the weight status of unrelated children. Parents were found to have better perception on the weight status of their own children.⁴⁶

Recommendation

Parents, especially mothers should be made more aware about their child’s nutrition and their nutritional status. The GOB and NGO’s can do this by creating more and more programmes.

More programmes should be created with effective monitoring and evaluation about appropriate nutrition. Seminars should be held on regularly. Media broadcasting can play a vital role about it. Not only mothers, but also almost all the family members, especially the fathers should be aware of the child nutrition. Working mothers have to face great problem about this concern. The family members can help the mother to give healthy diet to the child.

Health education and promotion should be given to the parents. This is an effective way to improve the knowledge on nutrition of the parents. The government can arrange many health programmes regularly. They can telecast many related programmes through the media, such as- television, radio etc. These can be done by both at government and non-government level.

Conclusion

In conclusion, overall, parents showed a good knowledge on nutrition. Unfortunately, such a good knowledge was found insufficient to make them recognize the nutritional status of their children.

In addition, this parental knowledge on nutrition is very important for maintaining their children good health and nutritional status.

This parental knowledge also needs to be improved with regard to the food pyramid and methods of preparing balanced diet for their children.

There is a need for the improvement of the methods and content of nutritional educational packages as well as efforts to improve parents’ recognition of their child nutritional status.

Parents need to improve their knowledge about malnutrition related complications. They need to know the consequences of under nutrition and over nutrition also.

They need an improvement of their knowledge about healthy life style and selection of healthy foods for their children.