Dietary Habits and Determinants of Overnutrition Among Secondary and Preparatory School Adolescents: A Multi-Center Unmatched Case-Control Study

Abstract

Background: Overnutrition is characterized by abnormal or excessive fat buildup in the body’s fatty tissue, leading to potential health issues associated with overweight or obesity. These conditions pose significant public health challenges for adolescents and are strong indicators of future obesity, illness, and even death. As a result, this study sought to examine the dietary behaviors and factors contributing to overnutrition in secondary and preparatory school students in Debre Berhan Town, Ethiopia. Methods: An institutional-based unmatched case-control study was conducted among 285 adolescents from March 18 to April 20, 2021. The data collection was carried out using standardized interviewer-administered semi-structured questionnaires, which were adapted from previous studies. A general survey was conducted to identify cases and controls. The cases and controls were selected using simple random sampling methods. Data was entered using Epi-data 4.2 software and exported to SPSS v25. Descriptive statistics were done based on the nature of the data. Bivariable and multivariable logistic regression analysis was performed. World Health Organization AnthroPlus software was used to analyze anthropometric data into body mass index for age with z-score. Adjusted odds ratio with a 95% confidence interval and P-value <.05 was considered statistical significance. Result: In this study, eating habits while reading (AOR = 3.87;95% CI: 1.95-7.686), sedentary behavior, (AOR = 2.52; 95% CI: 1.278-4.97), vigorous type of physical exercise for <75 min per week (AOR = 2.38; 95% CI: (1.149-4.92), <6 sleeping hour per day (AOR = 5.68; 95% CI: 2.08-15.48) and earning an average family income of ≥227 USD (AOR = 2.67; 95% CI: 1.214-5.9) were significantly associated with overnutrition among school adolescents. Conclusion: Overnutrition is a significant emerging public health concern among school adolescents, with various factors contributing to its prevalence. This study underscores the importance of promoting an active lifestyle, reducing sedentary behavior, and fostering healthy eating habits as crucial national public health priorities. Early interventions targeting modifiable risk factors are essential for mitigating the incidence of overnutrition among adolescents. It is recommended that educational programs addressing overnutrition and its associated health implications commence early in school settings to prevent the escalating prevalence of this issue. Public health initiatives aimed at increasing awareness of risk factors for overnutrition among adolescents are warranted to alleviate the future burden of obesity-related chronic non-communicable diseases.

Keywords

determinants overnutrition case-control Debre Berhan Ethiopia

“Adolescents who sleep for <6 h per day were 5.6 times more likely to develop overnutrition than those who sleep greater than or equal to 8 h.”

Introduction

According to the World Health Organization (WHO), Adolescence is the phase of life between childhood and adulthood, from ages 10 to 19.¹ Overnutrition can be defined as abnormal or excessive accumulation of fat in the adipose tissue that may affect the health status of individuals explained by overweight/obesity.²

World Health Organization defines overweight as body mass index (BMI) for age, Z-score between +1 and +2 standard deviation (SD), and obesity as BMI for age and Z-score >+2 SDA.³ Nowadays, overweight and obesity are rapidly growing public health problems that our world is facing. Its prevalence is high not only in the developed world but also in developing countries. In the 21st century, overweight and obesity are the most severe public health problems among adolescents and they are significant predictors of adulthood obesity, morbidity, and mortality.⁴

Globally, there has been a significant increase in the number of overweight children and adolescents. In 2016, over 340 million children and adolescents were considered overweight or obese, which is a substantial rise from previous years. The prevalence of overweight and obesity among children and adolescents aged 5-19 years has increased from 4% in 1975 to over 18% in 2016. This increase has been similar among both boys and girls, with 18% of girls and 19% of boys being overweight in 2016. In 1975, the prevalence of obesity among youngsters and adolescents aged 5-19 was less than 1%, while in 2016, there were 124 million obese children and adolescents, which accounted for 6% of girls and 8% of boys.⁵

Worldwide, overweight/obesity is a significant health concern, especially in children and late adolescents. It is a major risk factor for non-communicable diseases like dyslipidemia, cancer, cardiovascular diseases (CVD), and type II diabetes mellitus.⁶

In many Sub-Saharan African countries, research and investment in health have been mainly focused on infectious diseases and undernutrition. Meanwhile, overweight and obesity are recognized risk factors for chronic non-communicable diseases. A study conducted in 7 African countries on the prevalence of overweight and obesity among school adolescents shows that overweight ranges from 8.7% in Ghana to 31.4% in Egypt. Obesity burdens ranged from 0.6% in Benin to 9.3% in Egypt. The study also suggests the need to explore other potential risk factors for overweight, including socio-economic status.^7,8

In low-income countries like Ethiopia, information about adolescent obesity is scarce. This condition is a major risk factor for various diet-related diseases such as cardiovascular diseases, hypertension, type 2 diabetes, and certain cancers. Globalization, economic growth, urbanization, and changing dietary habits are contributing to the rapid increase in overnutrition in developing countries. Factors such as high-fat, high-sugar, energy-dense foods, and low-intensity activity are leading to dramatic changes in living environments and promoting positive energy balance.^9-11

Sedentary life like prolonged sitting or screen time can lead to reduced energy expenditure and an imbalance between energy intake and expenditure, potentially causing weight gain and obesity. Inadequate sleep can affect appetite regulation and food choices, leading to cravings for high-calorie foods and overeating. Overeating, consuming more calories than the body needs, is a major contributor to obesity. Eating while studying can result in mindless eating and excessive calorie consumption, contributing to weight gain.^12-14

Despite various strategies, studies show that overnutrition among adolescents is still a growing problem. In Ethiopia, the prevalence of overweight/obesity among children and adolescents is 11.3%, indicating an emerging issue.^6,15,16 Despite the growing concern about overnutrition among adolescents, there is a lack of studies investigating the dietary habits and determinants of overnutrition specifically among secondary and preparatory school adolescents in Debre Birhan town. Previous studies have primarily focused on undernutrition or nutrition in general, leaving a knowledge gap in understanding the factors contributing to overnutrition in this age group. The current study aims to examine dietary behaviors and factors contributing to overnutrition in secondary and preparatory school students.

Methods and Materials

Study Area and Period

The study was conducted from March 18 to April 20, 2021, in Debre Berhan town which is the capital city of North Shewa Zone. Debre Berhan is located 130 km northeast of Addis Ababa and 694 km from Bahir Dar.¹⁷ According to the city administration education office report for 2020/2021, there are 2 private and 3 governmental secondary and preparatory schools in Debre Berhan town. The total number of secondary and preparatory school adolescents in Debre Berhan town was 5046 (2115 male and 2931 female). Of all, 3692 adolescents were enrolled in government and 1354 were in private high schools.¹⁸

Study Design and Population Characteristics

This institutional-based unmatched case-control study employed a thoughtful approach to selecting cases and controls. The cases consisted of secondary and preparatory school adolescents with sex and age-specific BMI greater than or equal to +1 z-score, while the controls were adolescents with sex and age-specific BMI between −2 and +1 z-scores. To ensure a focused study population, we established the following inclusion criteria: secondary and preparatory school adolescents aged 15-19 years, and adolescents with sex and age-specific BMI above the 5th percentile. We also set specific exclusion criteria to minimize confounding factors, including female adolescents who are pregnant, and adolescents on medications for known chronic diseases, such as antiepileptic medications and ART medications that may result in weight gain.

These selection criteria were justified by the following reasons. By targeting adolescents aged 15-19 years, we ensured that our study focused on the late adolescent age group, which is the target population of interest. Setting a BMI threshold above the fifth percentile helped identify individuals who are at risk of overnutrition, aligning with the study’s objectives. Meanwhile, excluding pregnant adolescents avoided confounding factors related to pregnancy that could affect weight status. Similarly, excluding adolescents on medications for chronic diseases that may lead to weight gain ensured that our study focused on the general adolescent population without the influence of specific medical conditions or treatments. These clear inclusion and exclusion criteria helped define the study population and ensured that our findings are relevant to the target group of late adolescent school students without potential confounding factors.

Sample Size Determination

Epi info version 7.2.3.1 was used to calculate sample size by 2 population proportions with assumptions of 95% Confidence interval, 80% power, and 2:1 controls to cases ratio, by considering major determinant variables from a previous study which was conducted in southern Ethiopia.¹⁹ Finally, by taking the largest sample (180), adding a 5% non-response rate, and multiplying by 1.5 design effect, the total calculated sample size required for this study was 285 (95 cases and 190 controls).

Sampling Technique and Procedures

First, the 5 schools found in Debre Berhan town were stratified as private and governmental, then 2 schools (1 from private and 1 from governmental) namely, Millennium Secondary and Preparatory and Debr Eba Secondary and Preparatory School) were selected by lottery method respectively. To identify cases and controls, the first mass general screening (general survey) was carried out for all adolescents by measuring the height and weight of each adolescent to know their BMI for age

In private schools there were a total of 859 students, of which 3 students were above 20 years old and 92 students were undernourished, so 764 students were eligible for this study, and from governmental schools, there were 1860 students from those 149 were above 20 years and 256 were undernourished. So, 1455 students were eligible for the study. By considering the total number of eligible adolescents attending each selected school, a proportional allocation of cases and controls was used and cases and controls were selected by a simple random sampling technique using computer-generated random numbers. To get cases and controls unique identification number was given for each adolescent in each section since their list was used in Excel during the survey. For each case, 2 controls were sampled from the same school in which cases were drawn.

Anthropometric Measurement Procedure for Screening

Weight and height were measured using calibrated equipment. Height was measured to the nearest 0.1 cm in a standing position at the Frankfurt plane with the occipital, shoulder, and buttock touching the vertical stand using a Seca 206 height measuring stadiometer (Seca, Germany). Weight (in kilograms) was measured in light clothing and barefoot using a calibrated Omron HBF-400 digital weighing scale (Omron, Japan) to the nearest 0.1 kg. The weight measuring scale was checked by measuring standardized known weights and adjusted to zero level before weighing each adolescent. To ensure accurate measurements, data collectors asked participants to remove their bags, books, exercise books, and other materials and stand in the center without any support until the result was recorded.²⁰

Height and weight measurements were taken 3 times, and if any variation occurred, the average value was recorded to the nearest 0.1 cm and 0.1 kg, respectively. BMI was calculated as the weight divided by height squared (kg/m²) and was computed using the WHO Anthro-Plus software. Based on the Z-score value, obesity was defined as greater than +2SD, overweight as greater than +1SD, and normal weight as between less than +1SD and greater than −2SD.³

The dependent variable of this study is Overnutrition, and the independent variables are socio-demographic and socio-economic variables, Dietary Habit and Food Frequency food-related factors, Physical Activity Level Factors, and Anthropometric Measurements.

Data Collection Tools and Procedures

Prior to data collection, all students underwent anthropometric measurements as part of the screening process to identify cases and controls. Subsequently, the data collection process was conducted using interviewer-administered semi-structured questionnaires adapted from previous studies.^19,21 Our questionnaires were based on 4 established tools: the Food Frequency Questionnaire (FFQ), Dietary Habits Questionnaire (DHQ), Global Physical Activity Questionnaire (GPAQ), and Socio-demographic Questionnaire. These tools were selected for their validity and reliability in assessing dietary habits, physical activity, and socio-demographic characteristics in adolescent populations.

The questionnaire consisted of 4 comprehensive parts. The first part focused on socio-demographic and socio-economic characteristics, utilizing a semi-structured questionnaire to gather information on participants’ age, gender, educational level, and family income. The second and third parts comprised the food frequency questionnaire and dietary habits sections, which were used to assess participants’ dietary patterns, including frequency and portion sizes of food consumption. The fourth part employed the Global Physical Activity Questionnaire (GPAQ) to evaluate the level of physical activity among participants, encompassing various types of activities such as walking, moderate and vigorous intensity activities performed at school, as part of home and yard work, to get from place to place, and in spare time for recreation, exercise, or sport. To enhance accuracy, participants were asked to recall their activities over the last 7 days preceding the interview.²¹ To ensure data quality, the data collection process was carried out by 6 BSc nurses who were trained in questionnaire administration and supervised by 2 MSc Nurses with expertise in adolescent health and nutrition.

Data Quality Assurance

The rigor of our data collection was ensured through a multi-faceted approach in developing and validating our interview guide and questionnaire. The interview guide questions were adapted from previous studies. An expert in Child and Adolescent Nutrition carefully reviewed and validated the guide to ensure its content and structure were appropriate for our research objectives. The questionnaire underwent a thorough process to establish its reliability and validity. A pre-test was conducted to assess the questionnaire’s reliability and identify any potential issues with clarity or flow. Content, construct, and criterion validity were assessed to ensure the questionnaire effectively measured Dietary Habits and Determinants of Overnutrition. Content validity was ensured by comprehensive coverage of relevant aspects, while construct validity was confirmed by its alignment with theoretical constructs. Criterion validity was established by comparing questionnaire results with established standards.

The data collection tool was first prepared in English and then translated into Amharic version for ease of understanding by participants and then it was translated to English version to ensure its consistency with independent language translators. Before data collection, a pre-test was conducted at Basso secondary and preparatory schools with 5% of the intended sample size. This pre-test assessed language clarity, instrument appropriateness, and time estimates, allowing for necessary adjustments. Six data collectors and 2 supervisors received 2 days of comprehensive training in anthropometric measuring techniques, data collection tools, and procedures. Supervisors and investigators closely monitored the data collection process to ensure high-quality data. All collected data was double-checked by supervisors and investigators for accuracy and consistency. A random sample of questionnaires was used to further assess consistency. These rigorous procedures ensured the reliability and validity of our data collection instruments and ultimately contributed to the trustworthiness of our research findings.

Data Processing and Analysis

Before analysis, data were checked for completeness and then each completed questionnaire was assigned a unique code. Data were entered using Epi Data version 4.2 and exported to a Statistical Package for Social Sciences (SPSS) version 25 for analysis. World Health Organization Anthro Plus software was used for computing BMI for age. Socio-demographic profiles of variables frequency distribution, and summary statistics such as mean and standard deviation were computed for cases and control groups.

Descriptive statistics was done based on the nature of the variable using frequencies, percentages, mean, and standard deviation. Bivariable and multivariable logistic regression models were used to identify determinant factors linked to overnutrition. In the bivariable models, independent variables that showed a statistically significant relationship (P-value less than .25) with the outcome variable were considered candidate variables for the multivariable logistic regression models. P-values less than .05 were considered statistically significant in the multivariable regression. Finally, results were presented in the form of texts, tables, and graphs.

The amount of multi-collinearity was tested and fitted using variance inflation factor and tolerance in the final multivariable models, and it was found to be within a tolerable range (all variables of variance inflation factor value were less than 1.26) and tolerance (all variable value greater than 0.78). The assumption was fitted for the data with a P-value of .493 in the ultimate multivariable model’s goodness of fit Hosmer Lemeshow.

Results

Socio-Demographic and Socio-Economic Characteristics

In this study, from a total of 285 sampled adolescents, 279 adolescents (93 cases and 186 controls) participated which made the response rate of 98 % for both cases and controls. The majority of the cases 65 (69.9%) and controls 109 (58.6%) were females.

The mean age of cases and controls were 17.05 ± 1.08 and 17.04 ± 1.1 years with the minimum and maximum ages of 15 and 19 years old respectively. The majority of the participants in both case and control groups 75 (80.6%) and 162 (87.1%), respectively, were orthodox religion followers. Nearly half of the mothers in the case group 50 (53.8%) and 61 (32.8%) in controls attended a higher level of education and 42 (45.2%) of mothers in the case group and 53 (28.5%) in control groups were government employees.

The majority 58 (62.4%) of the case group and 110 (59.1%) of the controls had less than 5 family members and a majority of the participants 77 (82.8%) of the cases and 155 (83.3%) of controls were from urban areas (Table 1).

Table 1.

Socio-Demographic and Socio-Economic Characteristics of Secondary and Preparatory School Adolescents in Debre Berhan Town, 2021 (N = 279).

Variables		Cases	Controls
Variables		(N = 93, n (%))	(N = 186, n (%))
Sex of the participant	Male	28(30.1)	77(41.4)
Sex of the participant	Female	65(69.9)	109(58.6)
Birthplace	Urban	77(82.8)	155(83.3)
Birthplace	Rural	16(17.2)	31(16.7)
Birth order	First	48(51.6)	69(37.1)
	Middle	40(43)	107(57.5)
	Last	5(5.4)	10(5.4)
Religion	Orthodox	75(80.6)	162(87.1)
	Protestant	16(17.2)	16(8.6)
	Muslim	2 (2.2)	8 (4.3)
Adolescents’ educational level	Grade 9	31(33.3)	40(21.5)
	Grade 10	34(36.6)	55(29.6)
	Grade 11	22(23.7)	57(30.6)
	Grade 12	6 (6.5)	34 (18.3)
Family size	<5	58 (62.4)	110 (59.1)
Family size	≥5	35 (37.6)	76 (40.9)
Education of mothers	Higher level	50 (53.8)	61 (32.8)
	Secondary and pre (9-12)	19 (20.4)	62 (33.3)
	Primary school (1-8)	8 (8.6)	26 (14)
	Can read and write	9 (9.7)	25 (13.4)
	Can’t read and write	7 (7.5)	12 (6.5)
Education of fathers	Higher level	63 (67.7)	100 (53.8)
	Secondary and pre (9-12)	13 (14)	44 (23.7)
	Primary school (1-8)	6 (6.5)	17 (9.1)
	Can read and write	7 (7.5)	18 (9.7)
	Can’t read and write	4 (4.3)	7 (3.8)
Occupation of mothers	Housewife	33(35.5)	73(39.2)
	Merchant	14(15.1)	39(21.0)
	Government employee	42(45.2)	53 (28.5)
	Others	4 (4.3)	21 (11.3)
Occupation of fathers	Government employee	44 (47.3)	70 (37.6)
	Merchant	26 (28)	54 (29)
	Farmer	11 (11.8)	21 (11.3)
	Pensioner	2 (2.2)	6 (3.2)
	Others	10 (10.8)	35 (18.8)
Monthly income (USD)	<114	19(20.4)	73(39.2)
	115-226	14(15.1)	36 (19.4)
	≥227	60(64.5)	77(41.4)
Transport type	On foot	78(83.9)	163(87.6)
	Bicycle	5(5.4)	3(1.6)
	Automobile	10 (10.8)	20 (10.8)
Having close friends	Yes	92 (98.9)	183 (98.4)
Having close friends	No	1 (1.1)	3 (1.6)
Living status of the participant	A lone	1 (1.1)	1 (0.5)
	With family	80 (86)	171 (91.9)
	With relatives	12 (12.9)	14 (7.5)

Study Participants Dietary Habit

In both case and control groups, most of the adolescents 74 (79.6%) and 113 (60.8%), respectively, skipped their breakfast 1 to 3 times in the week preceding the survey, and two-thirds of the study participants in both cases and control groups 65 (69.9%) and 128 (68.8%) respectively had meal frequency of 3 times per day. Seventy-one (76.3%) of the cases and 70 (37.6%) of the control groups had a habit of eating while reading and a majority of the cases 79 (84.9%) and 137 (73.7%) of controls had a habit of eating while watching TV (Table 2). Globalization, economic growth, urbanization, and changing dietary habits in developing countries are reported to be responsible for the rapid increase in overnutrition, and foods high in fats, sugars, energy-dense foods, and increasing low-intensity activity are some of the factors contributing to overweight and continue to dramatic changes in living environments, as well as in diets and lifestyles that promote positive energy balance, according to various studies.

Table 2.

Dietary Habits of Secondary and Preparatory School Adolescents in Debre Berhan Town, 2021, (N = 279).

Variables	Cases	Controls
Variables	N = 93, n (%)	N = 186, n (%)
Skipping breakfast/week
Never skip	17 (18.3)	52 (28)
Skipped 1-3 times	74 (79.6)	113 (60.8)
Skipped ≥4 times	2 (2.2)	21 (11.3)
Meal frequency/day
Less than 3 times	3 (3.2)	21 (11.3)
3 times	65 (69.9)	128 (68.8)
≥4 times	25 (26.9)	37 (19.9)
Snack consumption per week
never eat snack	14 (15.1)	32 (17.2)
1-3 times per week	40 (43)	87 (46.8)
4-6 times per week	19 (20.4)	35 (18.8)
everyday	20 (21.5)	32 (17.2)
Eating habits while reading
Yes	71 (76.3)	70 (37.6)
No	22 (23.7)	116 (62.4)
Eating habits while watching TV
Yes	79 (84.9)	137 (73.7)
No	14 (15.1)	49 (26.3)

Food Frequency Pattern

Nearly more than half of the adolescents in both groups¹⁴ controls consumed sweet foods 2-4 times per week. The majority of adolescents 77 (82.8%) in the cases group and 117 (62.9) of controls consumed fast food 2-4 times per week. In both case and control groups, 68 (73.1%) and 94 (50.5) and 69 (74.2%) and (103 (55.4) respectively had vegetable and fruit consumption 2-4 times in a week. A large percentage of the cases group 79 (84.9%) and controls 1 [40 (75.3%)] didn’t eat at all fat and oil in food the last week preceding the survey

Physical Activities and Sedentary Behavior

The majority of the adolescents in both groups [75 (80.6%) in cases and 97 (52.2%) in controls] did not have a habit of doing regular exercise and more than two-thirds of cases 64 (68.8%) and 164 (88.2%) of controls did ≥150 min per week of moderate type of physical activity which meets the WHO recommendation for health. Nearly half of the cases 54 (58.1%) and 45 (24.2%) of controls have a sedentary type of life in which, they have sat for greater than or equal to 480 minutes per day (Table 3).

Table 3.

Physical Activities and the Sedentary Life of Secondary and Preparatory School Adolescents in Debre Berhan Town 2021 (N = 279).

Variables	Cases	Controls
Variables	N = 93, n (%)	N = 186, n (%)
Regular physical exercise
Yes	18 (19.4)	89 (47.8)
No	75 (80.6)	97 (52.2)
The sum of vigorous physical activity in minutes per week
<75	72 (77.4)	89 (47.8)
≥75	21 (22.6)	97 (52.2)
The sum of moderate physical activity in minutes per week
<150	29 (31.2)	22 (11.8)
≥150	64 (68.8)	164 (88.2)
Setting time in minutes per day
<480	39 (41.9)	141 (75.8)
≥480	54 (58.1)	45 (24.2)
Sleeping hours per day
<6 h	41 (44.1)	35 (18.8)
6-8 h	43 (46.2)	84 (45.2)
≥8 h	9 (9.7)	67 (36)

Determinants of Overnutrition

In this study, bivariable logistic regression analysis was carried out to see the relation of each independent variable with the outcome variable. Those variables with P-values less than .25 were included in the multivariable analysis. These variables were the sex of participants, educational level of the mother, days of skipping breakfast, meal frequency per day of the participant, adolescent’s average family income per month, sleeping hour per day, eating habits while reading, the sum of vigorous physical activity in minutes per week, the sum of moderate physical activity in minutes per week, sitting time in minute per day.

Those variables with P-P-value <.25 in the bivariable analysis were fitted to multivariable analysis to control confounders and to test significant association with the outcome variable. Variables having statistically significant association (P-value <.05) in multivariable logistic regression were adolescents’ average family income per month, sleeping hours per day, eating habits while reading, the sum of vigorous physical activity in minutes per week, and sitting time in minutes per day.

The multivariable analysis proved that an odd of adolescents earning an average family income of ≥227 USD were 2.67 times and between 115-226 USD were 3.16 times more likely to develop overnutrition than those adolescents who earn <114 USD with (AOR = 2.67; 95% CI: 1.214-5.9) and (AOR = 3.16; 95% CI: 1.06-9.43) respectively.

Similarly, the odds of adolescents’ eating habits while reading were 4 times more likely to develop overnutrition than those adolescents who did not have eating habits while reading (AOR = 3.87; 95% CI: 1.95-7.686).

Likewise, adolescents who had sedentary behavior, where they sit or recline, for more than ≥480 min per day were 2.5 times more likely to develop overnutrition than their counterparts (AOR = 2.52; 95% CI: 1.278-4.97).

In this study, adolescents who practice a vigorous type of physical exercise for <75 min per week were 2.4 times more likely to develop overnutrition than those who practice for ≥75 min per week (AOR = 2.38; 95% CI: (1.149-4.92).

Furthermore, adolescents who sleep for <6 h per day were 5.7 times more likely to develop overnutrition than those who sleep greater than or equal to 8 hours (AOR = 5.68; 95% CI: 2.08-15.48) (Table 4).

Table 4.

Bivariable and Multivariable Analysis Results for Determinants of Overnutrition Among Secondary and Preparatory School Adolescents in Debre Berhan Town 2021, (N = 279).

Variable	Cases	Controls	COR (95%)	AOR (95% CI)	P-Value
Variable	N = 93, n (%)	N = 186, n (%)	COR (95%)	AOR (95% CI)	P-Value
Sex
Female	65(69.9)	109(58.6)	1.64 (.97-2.787)	1.56 (.77-3.14)	.214
Male	28(30.1)	77(41.4)	1	1
Education of mothers
Higher level	50 (53.8)	61 (32.8)	1.41 (.52-3.84)	.59 (.13-2.63)	.488
Secondary (9-12)	19 (20.4)	62 (33.3)	.53 (.18-1.52)	.38 (.08-1.75)	.212
Primary school (1-8)	8 (8.6)	26 (14)	.53 (.16-1.79)	.27 (.05-1.4)	.118
Can read and write	9 (9.7)	25 (13.4)	.62 (.19-2.06)	.49(.09-2.7	.412
Can’t read and write	7 (7.5)	12 (6.5)	1	1
Monthly income (USD)
<114	19(20.4)	73(39.2)	1	1
115-226	14(15.1)	36 (19.4)	1.49 (.67-3.32)	3.16(1.06-9.43)	.038*
≥227	60(64.5)	77(41.4)	2.99 (1.63-5.5)	2.67(1.21-5.9)	.015*
Skipping breakfast/week
Never skip	17 (18.3)	52 (28)	1	1
Skipped 1-3 times	74 (79.6)	113 (60.8)	2.03 (1.08-3.72)	2.06 (.92-4.57)	.075
Skipped ≥4 times	2 (2.2)	21 (11.3)	.29 (.06-1.37)	.27 (.05-1.46)	.129
Meal frequency/day
Less than 3 times	3 (3.2)	21 (11.3)	1	1
3 times	65 (69.9)	128 (68.8)	3.5 (1.02-12.35)	3.16 (.71-14.77)	.096
≥4 times	25 (26.9)	37 (19.9)	4.7 (1.27-17.56)	3.74 (.8-17.5)	.094
Eating habits while reading
Yes	71 (76.3)	70 (37.6)	5.3 (3.05-9.39)	3.87(1.95-7.69)	<.001*
No	22 (23.7)	116 (62.4)	1	1
Sleeping hours per day
<6 h	41 (44.1)	35 (18.8)	8.7 (3.8-19.9)	5.68(2.08-15.48)	.001*
6-8 h	43 (46.2)	84 (45.2)	3.81 (1.74-8.37)	2.56 (.1-6.6)	.051
≥8 h	9 (9.7)	67 (36)	1	1
The sum of vigorous physical activity in minutes per week
<75	72 (77.4)	89 (47.8)	3.7 (2.124-6.57)	2.38(1.15-4.92)	.020*
≥75	21 (22.6)	97 (52.2)	1	1
The sum of moderate physical activity in minutes per week
<150	29 (31.2)	22 (11.8)	3.3 (1.8-6.31)	2.08 (.91-4.79)	.084
≥150	64 (68.8)	164 (88.2)	1	1
Setting time in minutes per day
≥480	54 (58.1)	45 (24.2)	4.3 (2.55-7.38)	2.52(1.28-4.97)	.008*
<480	39 (41.9)	141 (75.8)	1	1

*Significant at P-value <.05, 1-reference.

Bold values indicate to the factors that are associated with the the dependent/outcome variable

Discussions

This study was conducted to determine Dietary Habits and Determinants of Overnutrition Among Secondary and Preparatory School Adolescents: A Multi-Center Unmatched Case-Control Study. The variable that has a significant association with overnutrition by using multivariable analytic techniques were adolescents’ average family income per month, sleeping hours per day, eating habits while reading, the sum of vigorous physical activity in minutes per week, and sedentary behavior/sitting time in minute per day.

In this study, adolescents’ average family income per month was a significant determinant of overnutrition. The odds of earning an average family income of ≥227 USD was 2.67 times higher develop overnutrition than those who earn <114 USD. The current finding is in line with the findings done in Japan,²² Tanzania,²³ Bangladesh,²⁴ and also in Ethiopia, a case-control study in Hawassa and cross-sectional studies in Bihar Dar^19,25-27 were also consistent with the current result. This might be due to high-income levels having a higher risk of exposure to energy-dense foods and a sedentary way of life and also the change in lifestyle, and dietary pattern associated with increased income. On the contrary, a critical review in the US shows that lower-income households tend to have higher rates of overweight/obesity in the United States and other developed countries that are low-income families are more exposed to junk food and other cheap calories including processed sugars.²⁸

In the current study adolescents who had sedentary behavior, those who sit/recline for ≥480 min per day were 2.52 times more likely to develop overnutrition than those adolescents who sit/recline for <480 min per day. This finding was supported by a case-control study in Bangladesh, sedentary time was a risk factor for overweight/obesity²⁴ and also a study in New Zealand on the association between BMI and sedentary behavior in female adolescents and the relationship between childhood sedentary behavior and biomedical health indicators^29,30 and also another study on sedentary behavior and health outcome in Brazil found that there is strong evidence for a relationship between sedentary behavior and overnutrition.^30,31 This may be due to low energy expenditure during sedentary time.³²

Adolescents who engage in vigorous physical exercise for less than 75 min per week were 2.38 times more likely to develop overnutrition compared to those who engage in 75 min or more per week. This finding aligns with previous studies conducted in Ethiopia on overnutrition in adolescents and its associated factors in Dale district schools^33,34 and Malaysia on socio-demographic, dietary, and physical activity determinants of overweight and obesity in adolescents³⁵ and Nepal where low physical activity was identified as a public health concern among middle and late adolescents aged 15-19 years.³⁶]. Additionally, a study in Kenya on overweight/obesity and physical activity in school children³⁷ and research in Ethiopia, specifically Gondar and Bahir Dar, on overweight/obesity and associated factors among high school students, revealed that students who did not engage in moderate or vigorous sports activities were at a higher risk of being overweight compared to those who did.^25,38 This underscores the importance of regular and sufficient levels of physical activity as a critical factor in energy expenditure, essential for maintaining energy balance and weight control in adolescents.³⁹

In the current study, adolescents who sleep for <6 h per day were 5.6 times more likely to develop overnutrition than those who sleep greater than or equal to 8 h. This finding is in line with the studies in Kuwait on Short Sleep Duration and Its Association with Obesity and Other Metabolic Risk Factors.⁴⁰ Also, it is in line with a USA survey on the relationship between insufficient sleeping time and the body mass index in adolescents and another study in Canada shows that the inadequate sleep duration categories <6 h was associated with the presence of overweight^41,42 besides this, the study which is conducted in China on the association between sleep duration and overweight/obesity in adolescents shows that both short sleep duration and long sleep duration were found as risk factors for overweight/obesity in Chinese adolescents and optimal sleep duration may prevent overweight/obesity.⁴³ This might be due to an increase in snacking or an increase in the number of meals consumed per day and more energy needed to sustain extended wakefulness psychological distress and disrupted meal timing, and increases in sedentary behavior seem to be the most compelling mechanisms linking poor sleep with increased overnutrition risk in adolescents^44-46 and also it might be due to sleep influencing energy metabolism. One of its main functions is to conserve energy and the proposed mechanism that associates insufficient sleep with weight gain is a decrease in energy expenditure. On the other hand, the study in Australia argues that sleep duration was not related to overweight.⁴⁷

Moreover, this study found that the odds of adolescents’ eating habits while reading were 3.87 times more likely to develop overnutrition than those who do not have eating habits while reading. This finding is comparable to the study in Italy on eating habits and lifestyle in students with obesity during the COVID-19 lockdown, which was found with BMI gain.⁴⁸ This may be due to an increase in meal frequency per day and also overeating of foods that might increase our vulnerability to gain weight.

Conclusions and Recommendations

Overnutrition is a significant emerging public health problem and multiple factors are associated with it. According to the findings of this study, the determinants of overnutrition were adolescents’ average family income per month, sleeping hours per day, eating habits while reading, the sum of vigorous physical activity in minutes per week, and sitting time in minutes per day.

This finding suggests that promoting an active lifestyle reduced sedentary behavior and healthy eating habits should be a national public health priority; because early interventions on modifiable risk factors are likely to decrease the rate of adolescent overnutrition. Educational programs about overnutrition and associated health consequences should start early in school to prevent its increasing prevalence in adolescents and public health programs are needed to increase awareness of risk factors for overnutrition among adolescents to reduce the future burden of obesity-associated chronic non-communicable diseases.

Supplemental Material

Supplemental Material - Dietary Habits and Determinants of Overnutrition Among Secondary and Preparatory School Adolescents: A Multi-Center Unmatched Case-Control Study

Supplemental Material for Dietary Habits and Determinants of Overnutrition Among Secondary and Preparatory School Adolescents: A Multi-Center Unmatched Case-Control Study by Eleni Dagnaw Abeje, Shiferaw Birhanu Aynalem, and Hailemariam Mekonnen Workie in American Journal of Lifestyle Medicine.

Footnotes

Acknowledgments

First, special thanks go to the Debre Berhan city administration education office for giving us the information that we needed and we would also like to thank also school directors, data collectors, supervisors, and study participants. We would like to thank Bahir Dar University for giving us the chance to conduct this study.

Author Contributions

All authors made substantial contributions to the conception and design, acquisition of data, or analysis and interpretation of data; took part in drafting the article or revising it critically for important intellectual content; gave final approval of the version to be published; and agreed to be accountable for all aspects of the work.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethical Statement

ORCID iD

Hailemariam Mekonnen Workie

Data Availability Statement

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. The original dataset was not shared in order not to compromise the confidentiality of the participants and to maintain privacy.*

Supplemental Material

Supplemental material for this article is available online.

Appendix

References

World Health Organization . Overview of Adolescent Health. Geneva, Switzerland: World Health Organization; 2024. https://www.who.int/health-topics/adolescent-health#tab=tab_1.

World Health Organization , Nutrition in the WHO African Region. Geneva, Switzerland: World Health Organization; 2017. https://www.afro.who.int/sites/default/files/2017-11/Nutrition_in_the_WHO_African_Region_2017_0.pdf

Onis

Onyango

Borghi

Siyam

Nishida

Siekmann

. Development of a WHO growth reference for school-aged children and adolescents. Bull World Health Organ. 2007;85:660-667.

Sorrie

Yesuf

GebreMichael

. Overweight/obesity and associated factors among preschool children in Gondar city, Northwest Ethiopia: a cross-sectional study. PLoS One. 2017;12(8):e0182511.

World Health Organization . The Double Burden of Malnutrition: Policy Brief. Geneva, Switzerland: World Health Organization; 2016.

Gebrie

Alebel

Zegeye

Tesfaye

Ferede

. Prevalence and associated factors of overweight/obesity among children and adolescents in Ethiopia: a systematic review and meta-analysis. BMC obesity. 2018;5(1):19.

Kyallo

Makokha

Mwangi

. Overweight and obesity among public and private primary school children in Nairobi, Kenya. Health. 2013;5(8):85-90.

Manyanga

El-Sayed

Doku

Randall

. The prevalence of underweight, overweight, obesity and associated risk factors among school-going adolescents in seven African countries. BMC Publ Health. 2014;14(1):887.

World Health Organization . Obesity and Overweight Facesheet Number 311. Geneva, Switzerland: World Health Organization; 2011. https://wwwwhoint/mediacentre/factsheets/fs311/en/indexhtml. Last Accessed on 16 Apr, 2014.

10.

Smetanina

Albaviciute

Babinska

, et al. Prevalence of overweight/obesity in relation to dietary habits and lifestyle among 7–17 years old children and adolescents in Lithuania. BMC Publ Health. 2015;15(1):1-9.

11.

Malik

Willett

. Global obesity: trends, risk factors and policy implications. Nat Rev Endocrinol. 2013;9(1):13-27.

12.

Leitzmann

. Physical activity, sedentary behaviour, and obesity. Obes Rev. 2021;22:e13182.

13.

Papatriantafyllou

Efthymiou

Zoumbaneas

Popescu

Vassilopoulou

. Sleep deprivation: effects on weight loss and weight loss maintenance. Nutrients. 2022;14(8):1549.

14.

Razzoli

Pearson

Crow

Bartolomucci

. Stress, overeating, and obesity: insights from human studies and preclinical models. Neurosci Biobehav Rev. 2017;76(Pt A):154-162.

15.

Johnson

Cao

Czepiel

Mushannen

Nolen

Stanford

. Strategies in the management of adolescent obesity. Current Pediatrics Reports. 2020;8(2):56-65.

16.

Johnson

Cao

Czepiel

, et al. Strategies in the management of adolescent obesity. Curr Pediatr Rep. 2020;8:56–65. doi:10.1007/s40124-020-00214-9.

17.

Aynalem Tesfay

Dejenie Habtewold

. Assessment of prevalence and determinants of occupational exposure to HIV infection among healthcare workers in selected health institutions in Debre Berhan town, North Shoa Zone, Amhara Region, Ethiopia, 2014. AIDS Res and Treat. 2014;2014:731848.

18.

Debere Berhan Town City Adminstration . Education Office Report. Debre Berhan, Ethiopia. 2013.

19.

Bereket

Beyero

Fikadu

Bosha

. Risk factors for overweight and obesity in private high school adolescents in Hawassa city, Southern Ethiopia: a case-control study. Food Publ Health. 2017;7(7):29-34.

20.

Rinaldo

Gualdi

, eds. Anthropometric Techniques. International Course On Health And Immigration; September 2015; Ferrara, Italy. Università di Ferrara.

21.

WHO . Global Physical Activity Questionnaire (GPAQ) (Online). Geneva, Switzerland: World Health Organization; 2021. https://www.who.int/chp/steps/GPAQ_Instrument_and_Analysis_Guide_v2.pdf. Accessed 17/12/2017.

22.

Kachi

Otsuka

Kawada

. Socioeconomic status and overweight: a population-based cross-sectional study of Japanese children and adolescents. J Epidemiol. 2015;25(7):JE20140108.

23.

Shayo

Mugusi

. Prevalence of obesity and associated risk factors among adults in Kinondoni municipal district, Dar es Salaam Tanzania. BMC Publ Health. 2011;11(1):365.

24.

Bhuiyan

Zaman

Ahmed

. Risk factors associated with overweight and obesity among urban school children and adolescents in Bangladesh: a case–control study. BMC Pediatr. 2013;13(1):1-6.

25.

Anteneh

Gedefaw

Tekletsadek

Tsegaye

Alemu

. Risk factors of overweight and obesity among high school students in Bahir Dar city, North West Ethiopia: school based cross-sectional study. Adv in Preventive Med. 2015;2015:294902.

26.

Gebreyohannes

Shiferaw

Demtsu

Bugssa

. Nutritional status of adolescents in selected government and private secondary schools of Addis Ababa, Ethiopia. Adolescence. 2014;10(11):504.

27.

Teshome

Singh

Moges

. Prevalence and associated factors of overweight and obesity among high school adolescents in urban communities of Hawassa, Southern Ethiopia. Current Research in Nutrition and Food Science Journal. 2013;1(1):23-36.

28.

Hruschka

. Do economic constraints on food choice make people fat? A critical review of two hypotheses for the poverty-obesity paradox. Am J Hum Biol. 2012;24(3):277-285.

29.

Tye

Scott

Haszard

Peddie

. Physical activity, sedentary behaviour and sleep, and their association with BMI in a sample of adolescent females in New Zealand. Int J Environ Res Publ Health. 2020;17(17):6346.

30.

van Ekris

Altenburg

Singh

Proper

Heymans

Chinapaw

. An evidence-update on the prospective relationship between childhood sedentary behaviour and biomedical health indicators: a systematic review and meta-analysis. Obes Rev. 2016;17(9):833-849.

31.

De Rezende

LFM

Lopes

Rey-López

Matsudo

VKR

do Carmo Luiz

. Sedentary behavior and health outcomes: an overview of systematic reviews. PLoS One. 2014;9(8):e105620.

32.

Bonn

Rimm

Matthews

, et al. Associations of sedentary time with energy expenditure and anthropometric measures. Med Sci Sports Exerc. 2018;50(12):2575-2583.

33.

Desalegn

Diddana

Daba

Tafese

. Overnutrition in adolescents and its associated factors in Dale district schools in Ethiopia: a cross-sectional study. PeerJ. 2023;11:e16229.

34.

Ali

Kassahun

Wubneh

. Overnutrition and associated factors: a comparative cross-sectional study between government and private primary school students in gondar town, northwest Ethiopia. J of Nut and Met. 2020;2020:3670895.

35.

S-T

Kpb

. Socio-demographic, dietary and physical activity determinants of adolescents overweight and obesity in Kelantan. Health and the Environ J. 2012;3(1):44-53.

36.

Adhikari

Shrestha

Adhikari

Timilsina

Kunwar

. Physical activity and obesity prevalence among middle and late school adolescents of pokhara, Nepal. The J Univ Grants Commiss 5(1):1-7.

37.

Muthuri

Wachira

L-JM

Onywera

Tremblay

. Correlates of objectively measured overweight/obesity and physical activity in Kenyan school children: results from ISCOLE-Kenya. BMC Publ Health. 2014;14(1):1-11.

38.

Gebregergs

Yesuf

Beyen

. Overweight and obesity, and associated factors among high school students in Gondar town, North West Ethiopia. J Obes Wt Loss Ther. 2013;3(2):1-5.

39.

Romieu

Dossus

Barquera

, et al.

Energy balance and obesity: what are the main drivers?

Can Causes Cont: CCC. 2017;28(3):247-258.

40.

Al-Rashed

Sindhu

Al Madhoun

, et al. Short sleep duration and its association with obesity and other metabolic risk factors in Kuwaiti urban adults. Nat Sci Sleep. 2021;13:1225-1241.

41.

Shukla

Orozco

. Does insufficient sleep increase the body mass index in adolescents? Obes Facts. 2020;13(5):534-535.

42.

Chaput

J-P

. Sleep patterns, diet quality and energy balance. Physiol Behav. 2014;134:86-91.

43.

Wang

, et al. Associations between sleep duration and overweight/obesity: results from 66,817 Chinese adolescents. Sci Rep. 2015;5:16686. doi:10.1038/srep16686.

44.

Bartel

Gradisar

Williamson

. Protective and risk factors for adolescent sleep: a meta-analytic review. Sleep Med Rev. 2015;21:72-85.

45.

Markwald

Melanson

Smith

, et al. Impact of insufficient sleep on total daily energy expenditure, food intake, and weight gain. Proc Natl Acad Sci USA. 2013;110(14):5695-5700.

46.

Duraccio

Krietsch

Chardon

Van Dyk

Beebe

. Poor sleep and adolescent obesity risk: a narrative review of potential mechanisms. Adolesc Health Med Therapeut. 2019;10:117-130.

47.

Hayes

Balantekin

Altman

Wilfley

Taylor

Williams

. Sleep patterns and quality are associated with severity of obesity and weight-related behaviors in adolescents with overweight and obesity. Child Obes. 2018;14(1):11-17.

48.

Ipolla

Curatola

Ferretti

Giugno

Condemi

Delogu

, et al. Eating habits and lifestyle in children with obesity during the COVID19 lockdown: a survey in an Italian center. Acta Biomed 2021;92(2):e2021196. doi:10.23750/abm.v92i2.10912

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