Vol. 5 No.02 (2026) | Page: 118-141 | Original Article

Purna Bhandari ¹*

ABSTRACT

Background: Proper nutrition is required for all people to attain optimal physical and mental health. On the contrary, malnutrition affects and kills individuals of all ages globally.

Objective: This study assessed the dietary habits, nutritional status and its associated factors among school going adolescents in Nepalgunj Sub-Metropolitan City, Banke.

Methods: The study was a school based cross-sectional descriptive study using a quantitative method in all 10 randomly selected schools of Nepalgunj city. Where 297 school going adolescents within the respected area were taken as a study unit. Simple random sampling technique was adopted for sample estimation; Data was collected using a semi structure questionnaire and anthropometric instruments.

Results:  The study shows the significant association between nutritional status and different variable like family type, sweets, sugar, chocolate, sweeten drinks consumption, Vitamin A rich vegetables and tubers consumption, Legumes, Nuts and Seeds consumption and individual dietary diversity with p-value (<0.05) which showed the moderate level of association.

Conclusion: In conclusion, the study reveals that most of the respondents ate four or five main meals a day, either skip breakfast or eat in-between meals. The high DDS of the respondents ensures balanced nutrition.

Keywords: malnutrition, overweight, undernutrition, Nepal

Key points:

1. Which dietary habits and sociodemographic factors are associated with nutritional status among school-going adolescents in Nepalgunj, Nepal?
2. Nutritional status is moderately associated with family type, dietary diversity, and consumption of selected foods and sugary products.

3. Promoting diverse, balanced diets and healthier food choices may help improve nutritional status among school-going adolescents.

1. INTRODUCTION

Proper nutrition is required for all persons to attain optimal physical and mental health. On the contrary, malnutrition affects and kills individuals of all ages globally, particularly the impoverished and vulnerable. It continues to be a major cause of illness and impairment in children in poor countries, accounting for half of the 10.4 million yearly child fatalities [1]. Adolescence is defined as the period between the ages of 10 and 19, and it marks the shift from dependent childhood to independent adulthood. Adolescents account for 20% of the global population, with around 80% of them living in poor nations. This age is a stage of development in the lifespan that requires appropriate and proper quality diet to meet the nutrient requirements for their physical, mental, and developmental progress, as well as reproductive maturity [2]. Adolescence is a stage of rapid growth and maturation in human development that necessitates additional nutrients and energy to support growth. Focusing on the nutrition of adolescents, particularly girls, presents a unique chance to break the intergenerational cycle of malnutrition [2]. Adolescence, in other terms, is a period of strong anabolism during which the body requires more of all nutrients. Adolescence is the time when a person reaches 20% of their adult height, 50% of their adult weight, and 45% of their adult bone mass. Healthy eating habits during childhood and adolescence support the growth, development, and health at all stages of childhood and help to ward off health issues later in life [3]. Undernutrition (in terms of stunting and wasting), overweight, and obesity are the main nutritional issues facing adolescent populations around the world. During this time, there are new public health issues. Around the world, 2-3% of adolescents are obese and 10% of adolescents are overweight. The prevalence, which varies from 10% in Africa and Asia to more than 20% in the USA and Europe, is reflected in the global averages [4]. Malnutrition is a hidden emergency that is one of the leading causes of morbidity and mortality in children and adolescents worldwide. The nutrition and epidemiologic shift has its own impact on changes in food and exercise habits, resulting in the establishment of a double burden of malnutrition. Changes in dietary consumption, combined with increasingly sedentary lifestyles as a result of the food market, globalization, and expanding urbanization, have resulted in the emergence of chronic disease as a major new health issue [4]. Adolescents in Nepal cover 23.45 percent of the total population that is nearly a quarter of population [5]. According to Global Nutrition Reports 2018, one in three individuals face malnutrition, one in twenty children report feeling hungry, and one in five global deaths are linked to inadequate food. DBM is more common in LMICs (low- and middle-income nations), with a larger prevalence in the poorer LMICs [6]. According to the most recent global Demographic and Health Survey data for non-pregnant adolescent girls (15-19 years), the prevalence of thinness ranges from 2% in Europe and Central Asia (ECA) to 7% in South Asia (SA). The East Asia and Pacific (EAP) region, on the other hand, has a 4% incidence of overweight and obesity, compared to a 40% prevalence in the Middle East and North Africa (MENA) region. Anemia prevalence has remained high, affecting about 26% of adolescent girls in East and Central Africa (ECA) and 52% in West and Central Africa (WCA) [7]. According to a study conducted in Mekelle, Northern Ethiopia, the total prevalence of obesity, overweight, normal, and thinness among adolescents was 0.4, 2, 60.40, and 37.8%. Similarly, in research conducted in the Eastern Arsi Zone of the Oromia Region, stunting and thinness were found to be 20.2 and 14.8%, respectively [8]. In a newly released study, Shamim and colleagues found that more than 60% of pregnant women aged ≥19 had poor or medium dietary diversity (a score of less than 5 out of a possible 8) [9]. According to a recent study, 10% of the world’s school-aged children have extra body fat; of these, 25% are obese, with a considerable risk of acquiring type 2 diabetes or heart disease in adulthood [10]. In south Asia 11% of adolescent girls aged 15-19 years old are too shorts, 39% are under weight and 55% are anemic [11].  Adolescent stunting is 32% in India, 36% in Bangladesh, and 47% in Nepal, while having a low body mass index (BMI) is 53% in India, 50% in Bangladesh, and 36% in Nepal. In Bangladesh, 25-27% of teenage females are anemic (hemoglobin 12 g/dL) and 30% are iron deficient (serum transferrin saturation [TS] 15%). Half of all school-aged youngsters (47-54%) are vitamin A deficient [12]. Study conducted on rural adolescence of India shows that the prevalence of underweight is higher in boys i.e. (53.1%) that in girls (39.5%). The extent of stunting was higher (42.7%) among adolescents [13]. An adolescent’s nutrition study done in Nepal in 2014 found that 71% of male adolescents and 59% of female adolescents were malnourished more than 43% married adolescents and 65% of unmarried adolescents were malnourished [1]. A community-based study in rural and urban areas of Morang District shows that the overall prevalence of anemia among adolescents (male, female, urban, and rural combined) was found to be very high, at 65.6% female adolescents outnumber males by more than 25% (78.3%). The distinction between rural and urban areas is significantly difference [14]. A study conducted in Dang District shows that the nutritional status of the adolescents among 510 adolescents almost three fourth (74.3%) had normal weight. Similarly, 21.8% were underweight followed by overweight and obesity that is 3.1% and 0.8% respectively [15].  A survey conducted in semi-urban community in Dukuchhap Village of Lalitpur Nepal shows that the prevalence of stunting was found out to be 36.28% more males (16.51%) than female (12.60%) was severely stunted and 21.70% of male and 22.14% of female were moderately stunted. Among total respondents, 14.4% were severely stunted and 21.9% were moderately stunted. More number of male (38.2%) were stunted than female (34.7%) [16]. A study conducted on Dang district Nepal shows that the prevalence of Overweight and Obesity was 4.25% and 2.25% respectively [17]. NDHS 2016 reports show that, half of the households in Nepal are food insecure (52%) and do not have access to food around where 20% are mildly food insecure, 22% are moderately food insecure, and 10% are severely food insecure. Province 7 has severely food insecure percentage of 13% which is second highest after province 6 [18]. This study assessed the nutritional status and its associated factor of the respondents.

2. MATERIALS AND METHODS

A school based cross-sectional descriptive study design was used to assess the nutritional status and its associated factors among high school adolescents. Data was collected in a single shot with selected participants in a selected school. The study period was for Six months starting from Chaitra 2^nd week to Asoj 1^st week. And data collection started from 1^st week of Ashadh and was remain for 2 weeks. Individual school adolescents of class 9 and 10 of Nepalgunj sub-Metropolitan city was the sampling unit of the respective study area. The formula below was used to determine the sample size.

n=Z²×

Were,

n= the desired sample size

Z= the standard normal deviation at required confidence level in this case, i.e. 1.96

p= the proportion of the target population estimated to have characteristics being measured i.e. proportion of the Underweight among adolescent age (14-17 years) from Dang district i.e. 21.8% [5].

q= 1-p

e= the level of accuracy of the statistics being measured i.e. 0.05

Now,

n=Z²×  =  = 261.96≈ 262

For finite population,

N =883

Sample size (

n= 202.31≈202 students

Now, adding 10% non-response

n=202*0.1+202

=222

Hence, the sample size (n) was n= 224. For the selection of required sample size, appropriate probability sampling technique was used.

Table 01: sample estimation of each selected school

SN.	Name of school	Total students		Selected grade	Sample size
1	Sun beam English medium boarding school	Grade 9	29
		Grade 10	33	10	33
2	Nepalgunj model academy	Grade 9	40	9	40
		Grade 10	46
3	Hope international school	Grade 9	36	9	36
		Grade 10	45
4	Pasupati English medium boarding school	Grade 9	54	9 “B”	26
		Grade 10	79
5	Manakamana English medium boarding school	Grade 9	20
		Grade 10	20	10	20
6	St. Thomas English medium boarding school	Grade 9	42
		Grade 10	41	10	41
7	United education academy	Grade 9	46
		Grade 10	44	10	44
8	Sagarmatha boarding school	Grade 9	42	9	42
		Grade 10	32
9	Ideal public school	Grade 9	44	9	44
		Grade 10	52
10	Aadarsh mabi school	Grade 9	75
		Grade 10	63	10 “A”	32
Grand total		883			358

For the Data collection tools self-administered questionnaire was used on dietary practice of adolescence, anthropometric instrument was adapted to measure weight and height. Questionnaire was developed through the reviewing of different literature and consultant with respective Supervisor.Table 02: Data collection Tools and instruments

Tools and Instruments	Uses
Questionnaire	A well-designed and pretested set of questionnaires was used to collect information on different variables of the school going adolescents. Questionnaire was included: Part I: Sociodemographic section Part II: Environmental section Part III: Lifestyle and behaviors related characteristics Part IV: Food habit related characteristics Individual dietary Diversity Part V: Anthropometric measurement
Stature meter	To measure the height of participants
Weighing Scale	A digital weighing Machine measuring the weight of participants.

The technique for data collection was a self-administered questionnaire and anthropometric measurement. Firstly, students with inclusion criteria were participate, and inform consent was taken. Then all the required information was obtained through a self-administered questionnaire and anthropometric measurement. Semi structured questionnaire was used for data collection on following variables;

• Socio Demographic characteristics
• Lifestyle-behavior and environmental related characteristics
• Food habit related characteristics
• Individual dietary diversity
• Anthropometric measurement

Standard questionnaire was used for the data collection on the minimum dietary diversity through following steps:

• Students were asked to recall the consumption of food through 24 hr. dietary recall.
• The food was categorized based on 16 standard food groups of individuals dietary diversity for students, which include [28,29].
• Total number of food groups was summed up and categorized based on following standards

 Table 03: Classification of individual dietary diversity for students

Number of food group consumed in last 24 hours	Classification of dietary diversity
≤3 food groups	Low dietary diversity
4-5 food groups	Medium dietary diversity
≥6 food groups	High dietary diversity

For reliability, data was pretested on 10% of the sample size in Janaki rural municipality, which was the representative study population other than the sample. For the purpose of knowing about the problem related to sequence, meaning, components and understanding of the questions in a different section than the study area including validity of anthropometric instruments After pretesting all confusion, inaccurate and wrong interpretation of questions was removed and data was analyzed and necessary modifications was taken. The Questionnaires and Anthropometrics instruments was pretesting in a small group of students living in the similar context of study. Self-design questionnaire or standard questionnaire adapted from the literature was converted design in the English language and then translated into simple and clear Nepali language by one person and after finalization, it was retranslated into the English language by another person for maintaining its validity and reliability without changing its standard. All the data was export from Epi-Data to SPSS. After correction, the collected data was arranged, entered, analyzed, and organized in SPSS version 22 using Descriptive statistics (frequency, proportion, mean, standard deviation) and Inferential statistics (chi-square test) and the findings was presented in the form of percentages, graphs, charts and tables according to the variables.

3.RESULTS & DISCUSSION

Table 04: Distribution of respondents by Socio-Demographic Characteristics  

Variables	Frequency (n)	Percentage (%)
Age group 13-15 16-19 Median (IQR)=15 (1)	238 59	80.1 19.9
Sex Male Female	156 141	52.5 47.5
Religion Hindu Buddhist Christian Islam	271 9 7 10	91.2 3.1 2.4 3.3
Ethnicity Dalit Janjati Madhesi Muslim Brahmin Chettri Others (Thakuri)	27 48 18 8 63 106 27	9.1 16.2 6.1 2.7 21.2 35.7 9.1
Family Type Nuclear Joint Extended	172 107 18	57.9 36.0 6.1
Family Member Less than 4 More than 4	144 153	48.5 51.5
Number of Siblings No siblings One Two Three More than three	32 152 65 27 21	10.8 51.2 21.9 9.1 7.1
Father’s Education Level Illiterate Literate Primary level (1-5) Lower Secondary level (6-8) Secondary level (9-12) Bachelors Masters	8 19 14 41 141 43 31	2.7 6.4 4.7 13.8 47.5 14.5 10.4
Mother’s Education Level Illiterate Literate Primary level (1-5) Lower Secondary level (6-8) Secondary level (9-12) Bachelors Masters	12 18 28 55 138 28 18	4 6.1 9.4 18.5 46.5 9.4 6.1
Occupation of Mother Agriculture Government service Business Teachers Private Job Housewife Others	20 14 55 28 16 159 5	6.7 4.7 18.5 9.4 5.4 53.5 1.7
Birth Order in Family First Second Third Fourth	135 112 30 20	45.5 37.7 10.1 6.7
Monthly Income of Family Less than 20,000 20,000 to 50,000 More than 50,000	24 159 114	8.1 53.5 38.4

 Table 05: Distribution of respondents by Lifestyle and Behavior related Characteristics

Variables	Frequency (n)	Percentage (%)
Physically active in a week Daily Less than 4 days a week More than 5 days a week	197 76 24	66.3 25.6 8.1
Physical Activities* Walking Running Playing games Others	219 67 92 35	53 16.2 22.2 8.5
How do you used to go school Walking Public Vehicles Private Vehicles School Bus	211 16 46 24	71 5.4 15.5 8.1
Consumption Tobacco product or Smoking No Yes	293 4	98.7 1.3
If yes, frequency of consumption tobacco or smoking Occasionally Rarely	1 3	0.3 1
Alcohol consumption Yes No	9 288	3 97
If yes, frequency of consumption Daily Occasionally Rarely	1 4 4	0.3 1.3 1.3
Item used for hand washing Hand wash Soap Water only	96 194 7	32.3 65.3 2.4
When do you wash your hand* After going toilet After going Shed After coming from field After coming from work Before the meal After the meal	295 276 275 276 291 293	99.7 93.2 92.9 93.2 98.3 99
Frequency of hand wash per day Less than 4 times More than 4 times	50 247	16.8 83.2
Time spends on social media Less than 2 hours More than 2 hours Unknown	159 55 83	53.5 18.5 27.9
Time spends on TV/Laptop/Mobile Less than 2 hour per day More than 2 hour per day	186 111	62.6 37.4

 Table 06: Distribution of respondents by Food Habits related characteristics    

Variables	Frequency (n)	Percentage (%)
Main diet at home Rice/Dal Wheat Maize	286 7 4	96.3 2.4 3.3
vegetarian/non vegetarian Vegetarian Eggetarian Non vegetarian	21 4 272	7.1 1.3 91.6
If non vegetarian, frequency of meat consumption (n=272) Daily Once a week Twice a week Once a month Twice a month Others	45 109 100 8 9 5	16.3 39.5 36.2 2.9 3.3 1.8
Consumption of Vegetable Yes No	289 8	97.3 2.7
If yes, frequency of vegetable consumption (n=289) Once a week Less than 3 day a week More than 3 day a week	41 37 211	14.2 12.8 73
Consumption of fruits Yes No	291 6	98 2
If yes, frequency of fruits consumption (n=291) Once a week Less than 3 day a week More than 3 day a week	72 61 158	24.7 21 54.3
Consumption of milk and milk product Yes No	259 38	87.2 12.8
If yes, frequency of milk and milk product consumption (n=259) Once a week Less than 3 day a week More than 3 day a week	63 45 151	24.3 17.4 58.3
Consumption of eggs Yes No	272 25	91.6 8.4
If yes, frequency of eggs consumption (n=272) Once a week Less than 3 day a week More than 3 day a week	106 66 100	39 24.3 36.8
Consumption of fish Yes No	218 79	73.4 26.6
If yes, frequency of fish consumption (n=218) Once a week Less than 3 day a week More than 3 day a week	158 30 30	72.4 13.8 13.8
Consumption of Lentils, beans, peas or nuts Yes No	283 14	95.3 4.7
If yes, frequency of Lentils, beans, peas or nuts consumption (n=283) Once a week Less than 3 day a week More than 3 day a week	118 69 96	41.8 24.5 33.7
Consumption of sugar, sweets, chocolates or sweetened drinks Yes No	289 8	97.3 2.7
If yes, frequency of sugar, sweets, chocolates or sweetened drinks Consumption (n=289) Once a week Less than 3 day a week More than 3 day a week	84 83 122	29.2 28.8 42
Presence of Canteen at school Yes No	276 21	92.9 7.1
Frequency of taking lunch at school Once a week Less than 3 day a week More than 3 day a week	130 55 112	43.8 18.5 37.7
Prefer for lunch if not preferred in school canteen Homemade food Junk food/packed or processed food Food from hotel/restaurants	252 36 9	84.8 12.1 3
Consumption of junk food or processed food Yes No	284 13	95.6 4.4
If yes, frequency of Consumption of junk food or processed food (n=284) Daily Once a week Twice a week Once a month Twice a month Others	101 84 76 13 6 4	35.6 29.6 26.8 4.6 2.1 1.4
Opinion regarding junk food Lacks nutrients Good for health Bad for health Prefer to taste	54 12 120 111	18.2 4 40.4 37.4
Allowed junk food in school Yes No	44 253	14.8 85.2
Number of meals eat per day 2 meals 3 meals 4 meals 5 meals	46 150 88 13	15.5 50.5 29.6 4.4
Skipped any meal in a week Yes No	169 128	56.9 43.1
If yes, which meal you skip (n=169) Breakfast Lunch Day snacks Dinner	64 23 44 38	37.6 13.5 26.5 22.4
Reason for skipping meal Food deficient For weight loss For attractive figure Health conscious No time for meal Others	12 26 8 30 82 11	7.1 15.3 4.7 17.6 48.8 6.5
With whom you eat food at home Alone Whole family Mother /father Brother/sister	33 204 32 28	11.1 68.7 10.8 9.4
Sleep hour per day Less than 6 hours 6-8 hours More than 9 hours	47 219 31	15.8 73.7 10.4
Availability of pocket money Yes No	189 108	63.6 36.4
Weekly pocket money Less than 200 200-400 400-600 More than 600 Mean=357±244	74 47 51 18	38.9 24.7 26.8 9.5

 Table 07: Distribution of respondents by Knowledge related characteristics  

Variables	Frequency (n)	Percentage (%)
Heard about nutrition Yes No	284 13	95.6 4.4
Reason to eat nutritious food* Adequate physical growth Adequate mental growth Immunity power development	277 269 275	97.9 95.1 97.2
Source of information* TV Radio Social media Books Friends Family School Others	79 29 223 115 122 105 116 22	27.8 10.2 78.5 40.5 43 37 40.8 7.7
Self-rated health status Very good Good Average Bad	60 124 103 10	20.2 41.8 34.7 3.4
Self-perceive nutritional status Under weight Normal Over weight Obesity	26 248 18 5	8.8 83.5 6.1 1.6

 Table 08: Distribution of respondents by Environmental related Characteristics

Variables	Frequency (n)	Percentage (%)
Main source of drinking water at home Tap Well Hand pump Jar /bottle	73 7 44 173	24.6 2.3 14.8 58.2
Purification of water Yes No	237 60	79.8 20.2
If yes, method of purification* Boil Filter Add chlorine Sedimentation Others	49 210 10 5 5	20.6 88.2 4.2 2.1 2.1
Toilet at home Yes	297	100
Separate toilet for boys and girls at school Yes	297	100
Soap and water in school toilet Yes No	252 45	84.8 15.2
Kitchen garden at home Yes No	238 59	80.1 19.9
Illness in past 6 months Yes No	94 203	31.6 68.4
If yes, type of illness Fever Head ache Stomach pain Common cold	44 7 12 31	46.8 7.4 12.7 32.9

 Table 09: Distribution of the respondents by Individual Dietary Diversity

Variables	Frequency (n)	Percentage (%)
Cereals Yes No	292 5	98.3 1.7
White roots and tubers Yes No	158 139	53.2 46.8
Vitamin A rich vegetable and tubers Yes No	160 137	53.9 46.1
Dark green leafy vegetables Yes No	176 121	59.3 40.7
Other vegetables Yes No	257 40	86.5 13.5
Vitamin A Rich Fruits Yes No	209 88	70.4 29.6
Other Fruits Yes No	104 193	35 65
Organ Meat Yes No	61 236	20.5 79.5
Flesh Meats Yes No	106 191	35.7 64.3
Eggs Yes No	141 156	47.5 52.5
Fish and Sea foods Yes No	60 237	20.2 79.8
Legumes, Nuts and Seeds Yes No	158 139	53.2 46.8
Milk And Milk Products Yes No	197 100	66.3 33.7
Oils And Fats Yes No	242 55	81.5 18.5
Sweets Yes No	231 66	77.8 22.2
Spices, Condiments, Beverages Yes No	199 98	67 33
Did you eat anything (meal or snack) OUTSIDE the home yesterday? Yes No	166 131	55.9 44.1

 Table 10: Distribution of respondents by Individual Dietary Diversity Score  

Variables	Frequency (n)	Percentage (%)
Low dietary diversity	3	1
Medium dietary diversity	12	4
High dietary diversity	282	95

 Table 11: Nutritional Status (BMI for age) of the Respondents

Variables (Nutritional Status)	Frequency (n)	Percentage (%)
Under weight (Less than 5th percentile)	45	15.2
Normal (5th -85th percentile)	210	70.7
Over weight (85th 95th percentile)	22	7.4
Obesity (more than 95th percentile)	20	6.7

 Table 12: Association between Socio –Demographic and Nutritional Status (BMI for age) of school going adolescence

Socio-Demographic Variables	Nutritional Status		Chi square	P value	Cramer’s V
	Normal n (%)	Malnourished n (%)
Age group 13-15 16-19	174 (73.1) 36 (61)	64 (26.9) 23 (39)	3.338a	0.068
Sex Male Female	109 (69.9) 101 (71.6)	47 (30.1) 40 (28.4)	0.111a	0.739
Grade Nine Ten	116 (75.3) 94 (65.7)	38 (24.7) 49 (34.3)	3.293a	0.070
Ethnicity Un privileged Privileged group	65 (64.4) 145 (74)	36 (35.6) 51 (26)	2.980a	0.084
Religion Hindu Non- Hindu	194 (71.6) 16 (61.5)	77 (28.4) 10 (38.5)	1.156a	0.282
Family type Nuclear Joint	131 (76.2) 79 (63.2)	41 (23.8) 46 (36.8)	5.873a	0.015*	0.141
No of Siblings Less than 3 More than 3	22 (68.8) 155 71.4)	10 (31.3) 62 (28.6)	0.202a	0.904
Education of Father Illiterate Literate	6 (75) 204 (70.6)	2 (25) 85 (29.4)	0.073a	1.000b
Education of Mother Illiterate Literate	8 (66.7) 202 (70.9)	4 (33.3) 83 (29.1)	0.099a	0.752b
Father Occupation Direct Income generating Indirect Income generating	180 (70.6)   30 (71.40	75 (29.4)   12 (28.6)	0.012a	0.912
Mother Occupation Direct Income generating Indirect Income generating	81 (71.7)   129 (70.1)	32 (28.3)   55 (29.9)	0.084a	0.772
Birth order First/Second Third/Fourth	177 (71.7) 33 (66)	70 (28.3) 17 (34)	0.643a	0.423
Monthly Income of family ≥ 50,000 < 50,000	124 (67.8) 86 (75.4)	59 (32.2) 28 (24.6)	2.000a	0.157

 Table 13: Association between Lifestyle and Behavioral related characteristics with Nutritional Status (BMI for age) of school going adolescence

Lifestyle related variables	Nutritional Status		Chi square	P value	Cramer’s V
	Normal n (%)	Malnourished n (%)
Used to go school By walking By vehicle	146 (69.2) 64 (74.4)	65 (30.8) 22 (25.6)	0.805a	0.370
Physical activity in a week Daily Less than 4 days a week More than 4 days a week	135 (68.5) 57 (75)   18 (75)	62 (31.5) 19 (25)   6 (25)	1.341a	0.511
Item used for hand washing Hand wash Soap	69 (71.9) 141 (70.1)	27 (28.1) 60 (29.9)	0.093a	0.760
Smoking Yes No	2 (50) 208 (71)	2 (50) 85 (29)	0.839a	0.583b
Alcohol consumption Yes No	6 (66.7) 204 (70.8)	3 (33.3) 84 (29.2)	0.073a	0.724b
Frequency of hand washing in a day Less than 4 times More than 4 times	32 (64) 178 (72.2)	18 (36) 69 (27.9)	1.306a	0.253
Time spends on social media Less than 2 hours More than 2 hours	80 (69.6) 73 (73.7)	35 (30.4) 26 (26.3)	0.454a	0.500
Time spends on TV/Laptop/Mobile Less than 2 hour per day More than 2 hour per day	126 (67.7) 84 (75.7)	60 (32.3) 27 (24.3)	2.131a	0.146

 Table 14: Association between Food Habits related variable and Nutritional Status (BMI for age) of school going adolescence

Food Habit related variables	Nutritional Status		Chi square	P value	Cramer’s V
	Normal n (%)	Malnourished n (%)
Main diet at home Rice/dal Other than rice/dal	201 (70.3) 8 (800	85 (29.7) 2 (20)	0.440a	0.729b
Vegetarian /non vegetarian Vegetarian Non vegetarian	14 (66.7) 196 (71)	7 (33.3) 80 (29)	0.178a	0.673
Vegetable consumption Once a week Less than 3 days a week More than 3 days a week	27 (65.9) 26 (70.3) 150 (71.1)	14 (34.1) 11 (29.7) 61 (28.9)	0.450a	0.798
Fruits consumption Once a week Less than 3 days a week More than 3 days a week	50 (69.4) 42 (68.9) 114 (72.2)	22 (30.6) 16 (31.1) 44 (27.8)	0.316a	0.854
Milk and milk products consumption Once a week Less than 3 days a week More than 3 days a week	44 (69.8) 32 (71.1) 106 (70.2)	19 (30.2) 13 (28.9) 45 (29.8)	0.021a	0.989
Eggs consumption Once a week Less than 3 days a week More than 3 days a week	79 (74.5) 46 (69.7) 70 (70)	27 (25.5) 20 (30.3) 30(30)	0.691a	0.708
Fish consumption Once a week Less than 3 days a week More than 3 days a week	111 (70.7) 20 (66.7) 23 (76.7)	46 (29.3) 10 (33.3) 7 923.3)	0.748a	0.688
Lentils, beans, peas or nuts consumption Once a week Less than 3 days a week More than 3 days a week	83 (70.3) 46 (66.7) 71 (74.7)	35 (29.7) 23 (33.3) 24 (25.3)	1.296a	0.523
sugar, sweets, chocolate or sweeten drinks consumption Once a week Less than 3 days a week More than 3 days a week	62 (73.8) 51 (61.4) 92 (76)	22 (26.2) 32 (38.6) 29 (24)	5.506a	0.046*	0.138
Lunch in school canteen Once a week Less than 3 days a week More than 3 days a week	94 (72.3) 33 (60) 83 (74.1)	36 (27.7) 22 (400 29 (25.9)	3.830a	0.147
Sleeping hour per day Less than 6 hours More than 6 hours	30 (63.8) 180 (72)	17 (36.2) 70 (28)	1.275a	0.259
Number of hmeals per day 2-3 meals 4-5 meals	34 (73.9) 166 (69.7)	12 (26.1) 72 (30.3)	0.321a	0.571
Meal skip No yes	90 (70.3) 120 (71)	38 (29.7) 49 (29)	0.017a	0.897
Pocket money No yes	80 (74.1) 130 (68.8)	28 (25.9) 59 (31.2)	0.929a	0.335
Consumption of junk food No Yes	8 (61.5) 202 (71.1)	5 (38.5) 82 (28.9)	0.552a	0.458
Vitamin A rich vegetables and tubers consumption No Yes	89 (65) 121 75.6	48 (35) 39 (24.4)	4.050a	0.044*	0.117
Meat consumption No Yes	168 (71.2) 42 (68.9)	68 (28.8) 19 (31.1)	0.127a	0.721
Legumes, Nuts And Seeds consumption No Yes	106 (76.3) 104 (65.8)	33 (23.7) 54 (34.2)	3.888a	0.049*	0.114

 Table 15: Association between Environmental sanitation variable and knowledge related variable with Nutritional Status (BMI for age) of school going adolescence

Knowledge regarding nutrition and Environmental Sanitation related variables	Nutritional Status		Chi square	P value	Cramer’s V
	Normal n (%)	Malnourished n (%)
Source of drinking water at home Tap Well, /hand pump Jar /bottle	55 (75.3) 40 (78.4) 115 (66.5)	18 (24.7) 11 (21.6) 58 (33.5)	3.723a	0.115
Water purification No Yes	42 (70) 168 (70.9)	18 (30) 69 (29.1)	0.018a	0.893
Separate toilet for boys and girls at school No Yes	11 (57.9) 199 (71.6)	8 (42.1) 79 (28.4)	1.609a	0.205
soap and water available at school toilet No Yes	30 (66.7) 180 (71.4)	15 (33.3) 72 (28.6)	0.418a	0.518
History of illness in past 6 months No Yes	141 (69.5) 69 (73.4)	62 (30.5) 25 (26.6)	0.483a	0.487
Kitchen garden at home No Yes	44 (74.6) 166 (69.7)	15 (25.4) 72 (30.3)	0.532a	0.466
Heard about nutrition No Yes	9 (69.2) 201 (70.8)	4 (30.8) 83 (29.2)	0.014a	0.905
Self-rated health status Very good Good Average Bad	40 (66.7) 91 (73.4) 74 (71.8) 5 (50)	20 (33.3) 33 (26.6) 29 (28.2) 5 (500	3.037a	0.386
Self-perceived nutritional status Under nutrition Normal Overweight	16 (61.5) 177 (71.4) 17 (73.9)	10 (38.50 71 (28.6) 6 926.1)	1.222a	0.543

Table 16: Association between Individual Dietary Diversity and Nutritional Status (BMI for age) of school going adolescence

Food groups	Nutritional Status		Chi square	P value	Cramer’s V
	Normal n (%)	Malnourished n (%)
Individual Dietary Diversity Score Low dietary diversity High dietary Diversity	14 (93.3) 196 (69.5)	1 (6.7) 86 (30.5)	3.905a	0.036b*	0.115

4. DISCUSSION

Malnutrition remains among the most devastating problems and nearly 30% of people worldwide are suffering from one or more of the multiple forms of malnutrition. Especially these days, undernutrition among adolescents is a serious public health problem particularly in developing countries [8]. However, previous studies in Nepalgunj sub-metropolitan city didn’t show the nutritional status of adolescents at the school level. So, this study was conducted to determine the magnitude and associated factors of nutritional status among high school adolescents. In the present study the overall prevalence of underweight, normal weight, overweight and obesity is found to be (15.2%), (70.7%), (7.4%) and (6.7%) respectively. This study revealed that prevalence of under-nutrition among adolescent students was 15.2% and this finding is lower than the study in Ambo 27.5%, higher than study conducted in Addis Ababa city (13%). This might be due to the difference in socioeconomic background between the cities. Other studies in Ethiopia indicated that 37.8% were wasted in Tigray region. These findings indicated that under-nutrition is a major public health problem in majority of Ethiopian communities including urban and rural adolescents. These differences in prevalence could be associated with the sociodemographic and economic characteristics of household [2]. A similar study was conducted in southern Nigeria, over two third of the respondent (70.5%) found to be normal which is consistent with this study whereas, (14%) were overweight, (9.5%) were underweight [28]. which are differ from this study this may be due to study setting and different geographical region. Study conducted in school going adolescents in Solukhumbu, Nepal reveal that overweight and obesity is noted to be (7.35%) [32]. study from the 11 countries, the prevalence of overweight and obese girls is nearly 40% or higher, Saudi Arabia (37%), Costa Rica (38%), Uruguay (38%), Egypt (40%), Libya (42%), Kuwait (46%), Oman (42%), Solomon islands (49%), Tonga (53%), Micronesia (61%) and Kirbati (66%), the reason for girls overweight could be the, negative stigma associated with thinness, in some culture thinness is associated with being ill, whereas, obesity is associated with wealth, happiness, and good health.³³ A similar, study conducted in Kaski district of Nepal,  revealed 8.1% prevalence of overweight and obesity of among higher secondary level school adolescents with 5.8% overweight and 2.3% obese. Urban respondents were found significantly more overweight/obese than village respondents (p=0.001, OR=2.360) which is consistent with this study [22]. In this study the prevalence of malnutrition found to be slighted more higher in male than female this could be the majority of male respondents. In this research study family type and nutritional status of the respondents was found to be significantly associated with each other with the p value of 0.015, which is consistent to the study conducted in dang district, showed statistically significant p = 0.001 between type of family and underweight [5]. The study done by Pal, Pari, Sinha, Prakash and Dhara, 2016 in West Bengal state, India found significant association of underweight with family type, however showed different result of that adolescents of nuclear families (family size < 4) were more likely to be under nutrition [34]. In contrast to this study that adolescent living in nuclear family had (23.8%) malnutrition and (36.8%) in joint family. In the present study findings shows that there is no significant association between age, sex, religion, ethnicity group, parent’s education, family income, birth order and number of siblings. Similar study conducted in urban area of Pokhara Nepal indicate that monthly income and religion were found to be significantly associated with the dietary intake of adolescent’s girls of class 9 and 10 with the p value of (<0.05). A study conducted in Germany to determine the socioeconomic association between parental position and health among adolescent found that parental socioeconomic position and educational level were associated with consumption of less energy, dense food, more fruits and vegetables, and more favorable overall dietary behavior.³⁵ Study conducted in Urban Sharkia Governorate, Egypt there was significant relationship between obesity and parental education, as the highest prevalence of obesity was among students with low educated parents as they are responsible for food selection for their children as well as their lifestyle activities. Whereas, most study conducted in developing countries revealed that the highest prevalence of obesity was among students with high educated parents due to parental style with low energy expenditure [21]. This information explain that the level of socioeconomic status of parents of the adolescents could be influence their nutritional status. In the present study, majority (68.5%) of respondents reported that they were regularly physical active. From the study conducted in Kinondoni revealed that the risk of being overweight and obesity was lower in school adolescents who walked to from schools [36].  majority of the respondents in this study were not smoking cigarette and consuming alcohol. However, few of them had ever smoking and taken alcohol occasionally which is consistent to the study conducted in undergraduate students in private university in Southern Nigeria [28]. it shows that habits of taking cigarette and alcohol was not a common practice among adolescent. Similarly, study conducted in school adolescent in Edo state Nigeria conclude physically active days, BMI and fruit plan tree at home were associated with the healthy dietary pattern at p value less than 0.05 [30]. Which was different from the current study. In the current study it was found that (26.3%) of respondent who had screen time of more than 2 hour were malnourished. This is consistent with study from previous, revealed that Children who exceeded the recommended screen time of less than equal to 2 hour a day on weekends were 3 times more likely to be OW/OB than those who met the recommendation. Educated mothers have a higher chance of employment resulting in lesser time to monitor their children’s physical activities or sedentary behaviors like watching TV, which in turn, significantly increases their BMI [24]. In this study there was significant association between nutritional status and food habits related variable like, sugar, sweets, chocolate or sweeten drinks consumption with the p value of (0.046), Vitamin A rich vegetables and tubers consumption with the p value of (0.044), Legumes, Nuts and Seeds consumption with p value of (0.049). A similar study conducted from Pokhara revealed that Fruits consumption per week was found to be significantly associated with nutritional status. Participants who consumed fruits more than 4 days per week were 2.5 times more likely to be normal (OR 2.500; 95%CI 1.194-5.233; P=0.013) [35]. nearly half of the adolescent found to consume legumes as well other protein rich food sources may increase underlying disease burden from undernutrition and micronutrient deficiency. In this study adolescent consuming sweets, sugar and chocolate were very high i.e. (97.3%) which is similar to the study conducted among adolescents in Ghana i.e. 90.2% [37]. The high consumption of sugar drinks and soda may lead to increase in the prevalence of obesity and cardiovascular disease. However, Meat consumption per week, Egg consumption per week, Fish consumption per week, Vegetable consumption per week and Milk and milk product consumption per week has no association with nutritional status. Consumption of junk food was found very high among adolescents in this study among them 35.6% reported to consume it daily. Junk food consumption has been identified as a risk factor for obesity and overweight in adolescent good taste, advertising, easy availability of fast foods, and marketing are found to be associated with consumption of junk food [38].  A study conducted on urban Nepal revealed that Children who consumed processed meat and its products, (such as sausages, ham, roasts) snacks, (such as potato crisps, chips) and confectionaries (such as sweets and ice cream) more than twice a week were Almost 3 times more likely to be overweight or obese than those who consumed less than twice a week [24]. In current study there was no association found between skipping meal and malnutrition. Majority of the respondent skip breakfast and day snacks while minority of them sometime skip dinner and lunch. A similar study conducted in Southwest Nigeria revealed that there was no association between breakfast skipping and being overweight/obese; however, this study demonstrated a significantly higher mean of BMI among those who skipped breakfast compared to those who ate breakfast [19].  the reason for skipping breakfast by adolescence can be because of consumption is less popular among the Nepalese population. Daily pocket money was associated with junk food patterns in the study conducted in Pokhara, Nepal. Adolescents who got to school with higher pocket money can purchase sweets, snacks and soft drinks. Similar study findings were observed from the study of Ghana [39]. the respondent had knowledge about the word nutrition and its importance toward maintaining a healthy life but this is not found interpreted into their nutritional status, knowledge regarding nutrition is important because it has positive impact on healthy food choice and good health. In this study there was significant association between the BMI and individual dietary diversity score of the respondent with the p value of 0.036. A similar study conducted in a private university in southern Nigeria revealed that three hundred and ninety-two (49.0%) of the respondents had a high dietary diversity, 212 (26.5%) had a low dietary diversity and 196 (24.5%) had a medium dietary diversity, overweight and obese respondents were more among those who had a medium dietary diversity, 36 (18.4%) and 16 (8.2%), respectively, however, this finding was not statistically significant (p = 0.057) [28]. in our study majority of the respondent had a higher dietary diversity score which is consistent with this study. The meal pattern of the respondents also shows that majority of them consumed more of foods belonging to the cereals, roots and tubers, fruits, meats, oils and fats groups and less of foods belonging to the vegetables and eggs group. This may affect the availability of the nutrients (i.e., minerals and proteins) inherent in these food groups, to the respondents. The DDS of the respondents shows that more of them ate more than six food groups, which makes available necessary nutrients for optimal health. The dietary diversity of the respondents may be a reflection of better knowledge of basic nutritional values of the different food groups. High dietary diversity includes food from many food groups (≥6) which makes available balanced nutrients for optimal health. The high DDS of the respondents indicates their consumption of wide varieties of food which ensures availability of useful and balanced nutrients. This guarantees optimal nutrition which has a positive impact on their nutritional and health status.

5. CONCLUSION

The research was conducted among 297 school going adolescents in private school of Nepalgunj sub-metropolitan city Banke district, Nepal. The aim of study was to assess the nutritional status and its associated factors among school going adolescents through the anthropometric measurement BMI for age. The anthropometric results show the prevalence of underweight, overweight and obesity. The present study shows the overall prevalence of underweight, normal weight, overweight and obesity is found to be (15.2%), (70.7%), (7.4%) and (6.7%) respectively. The study shows the significant association between nutritional status and different variable like family type, sweets, sugar, chocolate, sweeten drinks consumption, Vitamin A rich vegetables and tubers consumption, Legumes, Nuts and Seeds consumption and individual dietary diversity which showed the moderate level of association. Likewise, age, sex, religion, parent’s education, number of siblings, birth order, pocket money, physically activity, family income, junk food consumption, sleeping hour, screening time and other food consumption were not associated with nutritional status. The finding revealed that there were high consumption of sweets, carbohydrate drinks and junk or processed food among school going adolescents. These food preferences have increased the propensity of influencing the burden of overweight and obesity. The DDS (dietary Diversity Score) of the respondent shows that majority of them ate more than six food groups. In conclusion, the study reveals that most of the respondents ate four or five main meals a day, either skip breakfast or eat in-between meals. The high DDS of the respondents ensures balanced nutrition. BMI of the respondents indicate that majority of them had a normal BMI.

AUTHOR CONTRIBUTION STATEMENT

Purna Bhandari: Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work, Drafting the work or reviewing it critically for important intellectual content; AND Final approval of the version to be published, and Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

ACKNOWLEDGEMENTS: No specific individuals, institutions, or organizations contributed additional support or assistance requiring formal acknowledgement for this study.

DECLARATIONS:

Funding: This research received no specific grant, financial support, or funding from any public, commercial, or non-profit organization.

Conflicts Of Interest: The authors declare that there are no conflicts of interest, financial or otherwise, that could have influenced the research, analysis, or interpretation of the findings presented in this article.

Data Availability: The datasets and information used in this study are publicly available from the sources cited within the article. No proprietary or restricted data were used.

Trial Registration: Trial registration is not applicable to this study, as it does not involve clinical trials, human participants, or experimental interventions.

Generative AI Disclosure: Generative artificial intelligence tools were not used for generating research data, conducting analyses, or producing scientific conclusions in this study. The authors take full responsibility for the content and accuracy of the manuscript.

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