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Obesity and Associated Factors in Jimma Town, Ethiopia
Journal of Pediatric Nursing 35 (2017) 98–104
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Journal of Pediatric Nursing
The Emerging Nutritional Problems of School Adolescents: Overweight/ Obesity and Associated Factors in Jimma Town, Ethiopia Nurezeman Gali, MSc b, Dessalegn Tamiru, MSc a,⁎, Meseret Tamrat, MSc a a b
College of Health Science, Jimma University, Ethiopia Nursing Department, Jimma University Specialized Hospital, Ethiopia
a r t i c l e
i n f o
Article history: Received 5 December 2016 Revised 12 March 2017 Accepted 13 March 2017 Available online xxxx Keywords: Overweight Obesity Adolescents Jimma Town
a b s t r a c t Background: Globally, overweight is rapidly becoming one of the most important medical and public health problems. Adolescent obesity is a multisystem disease with potentially devastating consequences that persist into adulthood. However, there is a paucity of available information regarding the adolescent overweight and obesity in Ethiopia, particularly in the study area. Methods: A school-based cross-sectional study was conducted from March to April/2015 among 546 adolescents. Study participants were selected using a multi-stage, stratified random sampling method. An interviewer administered questionnaire was used to collect data. Multivariable logistic regression analysis was used to identify independent predictors of overweight and obesity at 95% confidence intervals. Results: The mean dietary diversity score of school adolescents was 6.97 ± 1.15. Cereal based diets (99.6%) and vegetables (73.9%) are the two common foods of adolescents. The prevalence of overweight/obesity was 13.3%. Overweight/Obesity was significantly associated with being a female (AOR = 3.57 [95% CI:1.28–9.9]), attending private schools (AOR = 7.53 [2.51–22.3]), lack of paternal education (AOR = 5.57 [95% CI:1.53–20.26]), wealthy households (AOR = 3 [95% CI:1.09–8.26]) and not being a vegetarian (AOR = 9.23 [95% CI:1.68–50.8]). Adolescents who are physically inactive (AOR = 3.7 [95% CI:1.06–13.02]) and those with sedentary lifestyles (AOR = 3.64 [95% CI:1.39–9.5]) were more obese compared to their counter peers. Conclusions: The proportion of overweight/obesity among school adolescent was considerably high. Being a female, learning in private school, high household economic status, not being a vegetarian and having a sedentary life were significantly associated with overweight/obesity. Practice implications: Findings of this study can be used to guide the development of programs aimed at preventing overweight/obesity in Ethiopia by informing policymakers and other stakeholders about this emerging nutrition-related problem among school adolescents. © 2017 Elsevier Inc. All rights reserved.
Background United Nations Population Fund (UNFPA) reported that adolescents account about one fourth of the total world's population in which the majority of them live in developing countries (UNFPA, 2014). World Health Organizations (WHO) defined adolescence as a pivotal period of development which represents the age between 10 and 19 years (WHO, 2013). During this critical period, dietary patterns play an important role in the nutritional status of adolescents, as well as lifelong health. However, adolescents face serious nutritional challenges which could affect their rapid growth spurt as well as their health status. In developing countries like Ethiopia, the main nutritional problems affecting both young children and adolescents are under-nutrition. Under⁎ Corresponding author. E-mail addresses: [email protected] (N. Gali), [email protected] (D. Tamiru), [email protected] (M. Tamrat).
http://dx.doi.org/10.1016/j.pedn.2017.03.002 0882-5963/© 2017 Elsevier Inc. All rights reserved.
nutrition and infections play major roles in determining morbidity and mortality in low-income countries and limit the wellness and productivity of young children and adolescents. However, the problem of over-nutrition is increasing significantly, becoming one of the emerging public health problems in developing countries like Ethiopia (FDRE, 2013; PRB, 2013; UNFPA, 2014; WHO, 2013). Overweight and obesity are both chronic conditions that are the result of an energy imbalance over a period of time. An energy imbalance arises when the number of calories consumed is not equal to the number of calories used by the body. The cause of this energy imbalance can be due to a combination of several different factors and varies from one person to another (WHO, 2013). Globally, overweight is rapidly becoming one of the most important medical and public health problems of our times with the worrisome rise in the magnitude among the young population. According to recent statistics, the worldwide rates of overweight and obesity among children aged 5–17 years were 10% and 2–3.5% respectively (UNFPA, 2014; WHO, 2013, 2014). In Africa,
N. Gali et al. / Journal of Pediatric Nursing 35 (2017) 98–104
despite deep-rooted under-nutrition, a study conducted in seven countries reported that 8.5% of children were overweight or obese, and this incidence is projected to reach 12.7% by 2020. In Ethiopia, there are no national level data, but a study conducted in Addis Ababa showed that 8.6% of adolescents were overweight (Alemu, Atnafu, Yitayal, & Yimam, 2014; Onis, Blossner, & Borghi, 2010). Obesity is assigned as the fifth leading risk for deaths globally. It accounts for nearly three million deaths and 35.8 million of global disability adjusted life years (DALYs). Likewise, 44% of the diabetes, 23% of the ischemic heart disease and 7% to 41% of certain cancers worldwide were attributed to nutrition related non-communicable disease (EU, 2014; WHO, 2003, 2011). Adolescent obesity is a multisystem disease with potentially devastating consequences that persist into adulthood. Additionally, the care of overweight is associated with increased health care costs to the society. The impact also extends to psychological well-being, and is associated with decreased self-esteem, lower educational attainment and higher rates of poverty (EU, 2014; Onis et al., 2010; WHO, 2003). Adolescent health and nutrition are important in the overall social and economic development of a country, as adolescents are tomorrow's workforce and leaders. Studies evaluating under-nutrition have identified it as the most common public health problem. However, for some time the nutritional status of adolescents has been largely overlooked, as they were considered to be less vulnerable to malnutrition. Various studies in different countries showed that there is a high increment of overweight and obesity among young children and adolescents. Studies also showed that urban dwellers are more obese than those in rural areas due to relatively lower physical activity and more sedentary lifestyles in urban (Creber, Smeeth, Gilman, & Miranda, 2010; EU, 2014; Onis et al., 2010; WHO, 2003). Without early intervention, adolescent obesity can persist into adulthood and increase the risk of chronic disease. Findings from several studies also showed that the most effective ways to prevent the adverse consequences of obesity are the identification of predisposing factors and management of obesity, especially during the early life stages (FDRE, 2013; WHO, 2003, 2013). To address this evolving health concern, the problem of overweight/obesity was incorporated into the national nutrition program, and an initiative to encourage physical activity was launched in Ethiopia (EU, 2014; FDRE, 2013; WHO, 2011, 2013). However, these efforts are not specifically targeted to adolescents. Additionally, studies were conducted using growth reference that used formula fed children from a single ethnic group as a global standard. These references were inaccurate in estimating the magnitude of the problem and were of limited value in planning effective intervention strategies (FDRE, 2013). Therefore, this study was conducted to determine the magnitude and predictors of obesity and overweight among Jimma town school adolescents. It is envisioned that data from this study can be used to inform policy makers, educators and other stakeholders in designing early prevention of nutrition-related problems among school adolescents. Methods Study Area and Period This study was conducted in Jimma town's schools from March 8 to April 1, 2015. Jimma town is located at 357 km to the south west of Addis Ababa. Jimma town is the fifth largest city in Ethiopia with an estimated population of about 195,228. According to the 2014 Jimma town education bureau report, the town has 16 governmental and 12 private schools. The total number of adolescent students attending schools is 20,886, of which 10.985 were female. Sampling and Source Population A school based cross-sectional study was conducted with adolescents attending school in Jimma town. The sample size was calculated
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by using a single population formula with 5% margin of error, 95% confidence interval and the proportion adolescent girls who were reported to be overweight (20.2%) in Hawassa town (Teshome, Singh, & Moges, 2013). By adding a 10% non-response rate and considering the design effect the total sample size projected for 546. A multistage stage stratified random sampling technique was employed to select the study subjects. The schools were stratified into governmental and private schools according to their ownerships. At the first stage a total of eight schools, five government and three private schools, were selected by lottery from each. Secondly, one section per grade was selected by using a lottery method from each selected school. Then, the sample size was proportionally allocated for male and females. Finally, participants were selected by using computer generated simple random sampling techniques. Data Collection and Analysis Methods Interviewer-administered questionnaires were used to collect data. A qualitative food frequency questionnaire modified from WHO-STEP wise approach was used to gather information on the frequency of consumption of different food groups from each participant. This technique was considered to obtain qualitative descriptive data on typical consumption of foods and food groups over extended periods of time. Finally, data were collected to categorize participants based on detailed information regarding food choices and dietary diversity (WHO, 2003). The Global Physical Activity Questionnaire (GPAQ) developed by WHO for physical activity surveillance was used to assess the physical activity pattern among school adolescents in three domains, including activity at work, travel to and from places, recreational activities and sedentary behavior through face-to-face interviews with the respondents. The activity level of the study participants was evaluated according to the WHO total physical activity. Vigorous exercise was defined as activity that causes large increases in respiratory or heart rate, such as carrying or lifting heavy loads, digging or construction work, running or jogging, high-intensity aerobic classes, and competitive full-field sports (soccer) or basketball (Bull, Maslin, & Armstrong, 2009). The weight of each student was measured using the UNICEF Seca digital weighing scale (Germany) with light clothing and recorded to the nearest 0.1 kg. Height was measured using a portable Stadiometer (Seca, Germany) and recorded to the nearest 0.1 cm. During height measurement shoes, bulky clothing, pins and braids from the hair that could affect the measurement were removed. Height was measured with the head of participants at the Frankfurt plane, knees straight and the heels buttocks and the shoulder blades touching the vertical surface of the stadiometer. Data were collected by fluent speaker of local languages (Afan Oromo and Amharic) after training them. Mock interviews and practical field exercise were practiced with data collectors to ensure the quality of the field operation. During data collection, the supervisors followed data collectors and performed quality checks with the principal investigator. The questionnaire was prepared in English and translated to Amharic and Afan Oromo, then back translated to English to ensure the consistency of the questions. The data entry was done using Epi-Data version 3.1. The data were checked for missing values, outliers and analysed using SPSS version 20 and WHO Anthro-Plus (version 1.0.4.0). Descriptive statistics were used to examine the frequency distributions of selected study variables. Principal component analysis was used to assess household wealth status and components were developed using items with Eigen values greater than one. Finally, household wealth status was ranked as low, medium and high based up on variable factor scores. Overweight and obesity were determined using the WHO's age and gender specific growth reference for children aged 5–19 years (WHO, 2003). To allow for comparisons with other studies, overweight and obesity were also re-analysed using both CDC 2000 and IOTF criteria. A general chi-square for independence was used to investigate the association between
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overweight/obesity and nominal explanatory variables. Chi-square test for trends were used to measure the association between overweight/ obesity and ordinal scale independent variables. First, bivariate analysis was conducted to identify those variables with p-values ≤ 0.2. Before the inclusion of predictors in the final model, multi co-linearity was checked using the cut-off point VIF b10. Then, multivariable logistic regression was carried out to isolate independent predictors of obesity and overweight. The goodness of fit of the final logistic model was tested by using Hosmer and Lemeshow's test at a p-value of N 0.05 and Omnibus test p-value b 0.05. Both crude odds ratio and adjusted odds ratio with 95% confidence interval were reported. Data qualities were ensured during tool development, data collection, cleaning, entry and analysis. The data collectors were trained for one day on data collection methods and the tool was pretested. The principal investigator conducted on the spot checking and reviewed all the completed questionnaires to ensure completeness and consistency of collected information. Anthropometric measurements were taken using standardized and calibrated equipment in triplicates for each participant. Weighing scales were checked and zero after weighing every participant and regularly calibrated with an object of known weight.
Dietary Intake of Adolescents The mean dietary diversity score of school adolescents was 6.97 ± 1.15. Three hundred ninety-six non-obese students (88%) had a high dietary diversity score (DDS ≥ 5). Almost all (99.6%) students had consumed cereal-based foods with varying frequency per week. Three hundred thirty students (64.7%) had consumed fruits, and 480 (94.12%) of them had vegetables recently. More than three fourths (78%) of adolescents consumed legumes at least once per week. More than half of the students, 281 (55.1%) ate a snack daily. Nearly half, 275 (53.9%) of the students did not eat fast foods in a typical week. One-fourth (25.9%) of the adolescents did not eat their breakfast regularly. Four hundred nine students, 409 (80.2%) did not eat their meal outside of the home (Table 2). Physical Activity and Sedentary Life More than half, 269 (52.7%) of the respondents were engaged in certain household activities besides their education. Four hundred twenty seven students (83.7%) walk to school on foot, and most of them (62.7%) were involved in moderate to vigorous sport activities. The mean sedentary time was 3.78 ± 1.6 h per day (Table 3).
Results Nutritional Status of Adolescents Socio-demographic Characteristics This study aimed to assess the emerging nutritional problems and its association with dietary intake among school adolescents in Jimma town. Out of 546 sampled adolescents, 93.4% provided complete responses. The mean age of respondents was 15.37 ± 1.88 years. Nearly two thirds (67.6%) of the respondents were from government schools (Table 1).
The mean BAZ and BMI of the students were − 0.19 ± 1.19 and 20.05 ± 3.23 respectively. Females and private school adolescents had the highest BAZ and BMI than their counter peers (Table 4). A small number of study participants (11.1%) were underweight and 385 (75.5%) were within normal range. The prevalence of overweight and obesity was 60 (11.8%) and 8 (1.6%) respectively. The gender specific distribution of BMI status showed that the prevalence of overweight
Table 1 Socio-demographic characteristics of adolescents in Jimma town, Ethiopia, 2015. Variables
Categories
Gender
Female Male Single In a relation Private Government Protestant Orthodox Muslim Primary school Secondary school No formal education Primary school Secondary school Tertiary school No formal education Primary school Secondary school Tertiary school Merchant Government employee NGO Daily laborer Others$ Merchant Government employee House wife Others$ Low Medium High
Marital status School type Religion
Participant education Maternal education
Father education
Paternal occupation
Maternal occupation
Household wealth status
$
Daily laborer, farmer, no job.
Overweight/obese
p-Value
No (%)
Yes (%)
250 (82.5) 192 (92.8) 435 (86.5) 7 (100) 122 (73.9) 320 (92.8) 74 (91.4) 159 (77.9) 209 (92.9) 183 (89.7) 259 (84.6) 57 (81.4) 132 (86.8) 183 (85.5) 70 (94.5) 61 (76.25) 90 (85.7) 140 (89.2) 151 (89.9) 133 (86.9) 157 (88.2) 42 (67.7) 78 (94.1) 32 (94.4) 126 (86.9) 133 (95.7) 165 (83.8) 18 (62.1) 254 (91.4) 80 (84.2) 108 (78.8)
53 (17.5) 15 (7.2) 68 (13.5) – 43 (26.1) 25 (7.2) 7 (8.6) 45 (22.1) 16 (7.1) 21 (10.3) 47 (15.4) 13 (18.6) 20 (13.2) 31 (14.5) 4 (5.4) 19 (23.8) 15 (14.35) 17 (10.8) 17 (10.1) 20 (13.1) 21 (11.8) 20 (32.3) 5 (6) 2 (5.9) 19 (13.1) 6 (4.3) 32 (16.2) 11 (37.9) 24 (8.6) 15 (15.8) 68 (13.3)
b0.001 0.602 b0.001 0.430
0.111 0.290
0.013
0.470
0.310
0.001
N. Gali et al. / Journal of Pediatric Nursing 35 (2017) 98–104 Table 2 Dietary intake characteristics of school adolescents in Jimma town, Ethiopia, 2015. Variables (n = 510)
DDS category Cereal
Vegetables
Fruit
Animal source
Dairy product
Legumes and nuts
Sweet food
Oil and fats Snacking Fast food
Skipping breakfast
Eating out side
Categories
Low (DDS b 5) High (DDS ≥ 5) 1–2×/wk. 3–4×/wk. 5–7×/wk. None 1–2×/wk. 3–4×/wk. 5–7×/wk. None 1–2×/wk. 3–4×/wk. 5–7×/wk. None 1–2×/wk. 3–4×/wk. 5–7×/wk. None 1–2×/wk. 3–4×/wk. 5–7×/wk. None 1–2×/wk. 3–4×/wk. 5–7×/wk. None 1–2×/wk. 3–4×/wk. 5–7×/wk. 3–4 5–7×/wk. 3-6 x/wk. 7x/wk. None 1–2×/wk. 3–4×/wk. 5–7×/wk. None 1–2×/wk. 3–4×/wk. 5–7×/wk. No Yes
Overweight/obese No (%)
Yes (%)
46 (75.4) 396 (88.2) 36 (79.1) 29 (87.9) 377 (87.7) 18 (60.0) 82 (79.6) 168 (86.6) 174 (95.1) 157 (87.2) 16 (61.5) 104 (81.9) 165 (93.2) 189 (93.6) 143 (87.2) 59 (79.7) 51 (72.9) 226 (89.0) 119 (84.4) 47 (83.9) 50 (84.7) 5 (83.3) 67 (82.7) 171 (90.5) 199 (85.0) 97 (86.6) 238 (88.8) 81 (88.0) 26 (68.4) 17 (85.0) 425 (86.7) 202 (88.2) 240 (85.4) 250 (90.9) 165 (87.8) 9 (52.9) 18 (60.0) 332 (87.8) 78 (87.6) 15 (65.2) 17 (85) 349 (85.3) 93 (92.1)
15 (24.6) 53 (11.8) 9 (20.9) 4 (12.1) 55 (12.7) 12 (40) 21 (20.4) 25 (13.4) 10 (4.9) 23 (12.8) 10 (38.5) 23 (18.1) 12 (6.8) 13 (6.4) 21 (12.8) 15 (20.3) 19 (27.1) 28 (11.0) 22 (15.6) 9 (16.1) 9 (15.3) 1 (16.7) 14 (17.3) 18 (9.5) 35 (15.0) 15 (13.4) 30 (12.2) 11 (12) 12 (31.6) 3 (15.0) 65 (13.3) 27 (11.8) 41 (14.6) 25 (9.1) 23 (12.2) 8 (47.1) 12 (40.0) 46 (12.2) 11 (12.4) 8 (34.8) 3 (12.4) 60 (14.7) 8 (7.9)
p-Value
101
Table 3 Physical activity characteristics of adolescents in Jimma town, Ethiopia, 2015. Variables (n = 510)
Categories
0.014
House-working
0.358
Vigorous intensity activities
b0.001
Moderate intensity activities
0.029
Walking/using bicycle
b0.001
Vigorous sport activities
0.213
Moderate sport activities
0.761
Physical activities
Sedentary behavior 0.206 Mode of transportation
No Yes None 1–2 3–5 None 1–2 3–4 5–7 None 1–2 3–4 5–7 None 1–2 3–4 5–7 None 1–2 3–4 5–7 High Medium Low b3 h ≥3 h Vehicle On foot
Overweight/obesity
p-Value
No (%)
Yes (%)
196 (81.3) 246 (91.4) 378 (86.3) 24 (75.0) 40 (100.0) 217 (83.5) 28 (82.4) 74 (89.2) 123 (92.5) 56 (59.6) 46 (97.9) 27 (79.4) 309 (93.4) 196 (78.7) 84 (95.5) 85 (93.4) 77 (93.9) 274 (83.0) 79 (91.9) 51 (96.2) 38 (92.7) 191 (91.8) 192 (94.1) 59 (60.2) 239 (94.5) 203 (79.0) 45 (54.2) 397 (93.0)
45 (18.7) 23 (8.8) 60 (13.7) 8 (25.0) – 43 (16.5) 6 (17.6) 9 (10.8) 10 (7.50 38 (40.4) 1 (2.1) 7 (20.6) 22 (6.6) 53 (21.3) 4 (4.5) 6 (6.6) 5 (6.1) 56 (17.0) 7 (8.1) 2 (3.8) 3 (7.3) 17 (8.2) 12 (5.9) 39 (39.8) 14 (5.5) 54 (21.0) 38 (45.8) 30 (7.0)
0.001 0.060
0.040
b0.001
b0.001
0.007
b0.001
b0.001 b0.001
0.831 0.120 b0.001
0.317
0.214
×/wk.: frequency of consumption per week.
was 5.3% (11 students) for males and 16.2% (49 students) for females, whereas the obesity rates among students from private versus government schools were 22.6% and 6.7% respectively. Results were analysed according to IOTF and CDC criteria and compared with findings from some selected countries and worldwide data. Based on the IOTF criteria, the prevalence of overweight and obesity among school adolescents in Jimma town was 7.1% and 1% respectively. These percentages increased to 9.2% and 3.1% respectively when the CDC 2000 overweight/obesity definitions were utilized (Fig. 1). Factors Associated With Overweight/Obesity A multivariable logistic regression analysis showed that gender, school type, paternal education, household wealth status, fruit and vegetable and animal source food consumption, physical activity and sedentary behaviours are independently associated with overweight/ obesity among school adolescents. Girls are more than three times at risk of being overweight or obese compared to boys (AOR = 3.57 [95% CI: 1.28–9.9]. Adolescents attending private schools were greater than seven times (AOR = 7. 53 [95% CI: 2.51–22.3]) more at risk for becoming overweight or obese than government school adolescents. Adolescents whose father did not attend
formal education were more at risk of being obese (AOR = 5.57 [95% CI: 1.53–20.26]) compared to whose fathers attended college and above. Adolescents from a high wealth households were 3 times more likely to be overweight or obese (AOR = 3 [95% CI: 1.094–8.26]) than those from low wealth households. Adolescents who did not consume vegetables were nine times more likely to become overweight or obese (AOR = 9.23 [1.68–50.8]) than adolescents who consumed vegetables regularly. Similarly, adolescents who ate vegetables once or twice a week were five times more likely to be overweight or obese than those who consumed vegetables regularly. Those who ate no fruits were at 5 times greater risk of overweight/obesity than those who consumed fruits on a regular basis (AOR = 5.08 [1.57–16.38]). Physically inactive adolescents were almost four times more likely to be obese/overweight (AOR = 3.7 [1.06–13.02]) than active adolescents. Adolescents who were not involved in different physical activities for N 3 h per day were 3.64 times more at risk of being obese and/overweight than their counter peers (AOR = 3.64 [1.39– 9.5]) (Table 5). Discussion Nutrition related problems early in life have an impact on the psychosocial well-being and quality of life of adolescents. They can have far-reaching impacts on the country's economic growth, both in terms of lost productivity and increased burden of disease (FDRE, 2013; WHO, 2003, 2011, 2013). Studies have shown that in Ethiopia the Table 4 The anthropometric measurements of school adolescents in Jimma town, Ethiopia/2015. Variables (n = 510)
Weight Height BAZ BMI
Sex
Type of school
Female
Male
Private
Government
52.8 159.5 0.01 20.69
50.9 162.3 −0.49 19.13
55.7 162.1 0.09 21.14
50.2 159.9 −0.33 19.54
Total
52 kg 160.6 cm −0.19 20.05 kg/m2
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Fig. 1. Prevalence of overweight/obesity using various diagnostic criteria among adolescents in Jimma town, Ethiopia, 2015.
problem of nutrition-related, non-communicable disease is increasing significantly over time. Nutrition-related, non-communicable disease, namely overweight/obesity, is becoming increasingly recognized as a public health problem, in contrast to previous policies which focused primarily on the problem of under-nutrition. Therefore, the findings of this study have meaningful input in addressing the problem of nutrition-related issues especially among school adolescents. Findings of this study showed that the overall prevalence of overweight/obesity according to WHO 2007 definition was 13.4%, which is relatively low when compared to findings from Hawassa where 15.6% of adolescents were obese/overweight (Teshome et al., 2013). However, it is relatively high when compared to findings from Gonder where only 5.9% of
adolescents were obese/overweight (Gebregergs, Yesu, & Beyen, 2013). This difference might be due to differences in socioeconomic backgrounds and the availability of recreational facilities. The findings of this study indicated that adolescent overweight/obesity was significantly associated with school type. Students who attended private school were likely to be obese than those who attended government school. This finding is consistent with a study from India (Jagadesan et al., 2014), Saudi Arabia (El-Hazmi & Warsy, 2002), Yemen (Hussein Badi, García Triana, & Suárez Martínez, 2013), Burkina Faso (Daboné, Delisle, & Receveur, 2011) and Kenya (Kyallo, Makokha, & Mwangi, 2013). This similarity might be due to the fact that these adolescents usually come from families with a higher
Table 5 Multivariable logistic regression analysis of predictors of overweight/obesity among. Variables (n = 510)
Categories
Yes (%)
No (%)
COR
AOR (95 CI)
Gender
Female Male Private Government No education Primary Secondary Tertiary Low Medium High None 1–2×/wk. 3–4×/wk. 5–7×/wk. None 1–2×/wk. 3–4×/wk. 5–7×/wk. None 1–2×/wk. 3–4×/wk. 5–7 ×/wk. Inactive Active b3 h ≥3 h
53 (17.5) 15 (7.2) 43 (26.1) 25 (7.2) 19 (23.8) 15 (14.35) 17 (10.8) 17 (10.1) 24 (8.6) 15 (15.8) 68 (13.3) 12 (40.0) 21 (20.4) 26 (13.4) 9 (4.9) 23 (12.8) 10 (38.5) 23 (18.1) 12 (6.8) 13(6.4) 21 (12.8) 15 (20.3) 19 (27.1) 40 (56.3) 28 (6.4) 14 (5.5) 54 (21)
250 (82.5) 192 (92.8) 122 (73.9) 320 (92.8) 61 (76.25) 90 (85.7) 140 (89.2) 151 (89.9) 254 (91.4) 80 (84.2) 108 (78.8) 18 (60.0) 82 (79.6) 168 (86.6) 174 (95.1) 157 (87.2) 16 (61.5) 104 (81.9) 165 (93.2) 189 (93.6) 143 (87.2) 59 (79.7) 51 (72.9) 31 (43.7) 411 (93.6) 239 (94.5) 203 (79.0)
2.7⁎ 1 4.51⁎⁎ 1 2.76⁎ 1.48 1.079 1 1 1.98 2.84⁎ 12.88⁎⁎ 4.95 2.99 1 2.01⁎
3.57 (1.28–9.91)⁎⁎ 1 7.53 (2.51–22.3)⁎
School type Father education
Wealth status
Vegetables consumption
Fruit consumption
Animal source intake
Physical activity Sedentary behavior
Jimma town adolescents in February/2015. COR: crude odd ratio, AOR: adjusted odd ratio. ⁎ Significant at b0.05. ⁎⁎ Significant at ≤0.001.
8.59 3.04 1 0.185⁎⁎ 0.39⁎ 0.68⁎ 1 18.94⁎⁎ 1 1 0.22
1 5.57 (1.53–20.26)⁎ 3.7 (1.01–13.76)⁎ 0.73 (0.19–2.82) 1 1 2.25 (0.73–6.93) 3 (1.09–8.26)⁎ 9.23 (1.68–50.8)⁎ 8 (1.93–33.9)⁎ 3.13 (0.99–9.98) 1 5.08 (1.57–16.38)⁎ 4.17 (0.56–30.85) 2.87 (0.77–10.65) 1 0.04 (0.01–0.24)⁎⁎ 0.20 (0.05–0.78)⁎ 0.37 (0.87–1.66) 1 3.7 (1.06–13.02)⁎ 1 1 3.64 (1.39–9.5)⁎
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economic status, which likely exposes them to highly-processed, energy-dense foods and a more motorized lifestyle as compared to those attending government schools. Overweight/obesity was not significantly associated with the adolescent's age, which is inconsistent with the findings of studies from Saudi Arabia (El-Hazmi & Warsy, 2002), Turkey (Jagadesan et al., 2014) and Iran (Hajian-Tilaki & Heidari, 2007). This difference could be accredited to innate genetic differences, environmental factors and overall health status, factors which are not addressed by this particular study. Girls are at greater risk of being overweight or obese than males. These results are comparable to those found in Nigeria (Mustapha & Sanusi, 2013) and Bahrain (Al-Sendi, Shetty, Musaiger, & Myatt, 2003). This can be attributed to hormonal changes at puberty resulting in fat accumulation, as well as negative attitudes toward girls' participation in outdoor activities due to certain cultural and religious restrictions. The association between family affluence and overweight/obesity has been debated and this study also found that there was a statistically significant association between overweight/obesity among adolescents from households with high economic status compared to those from households with lower economic status. This is consistent with results from the Hawassa town study (Teshome et al., 2013). This can be explained by the association of wealth with a more motorized, less-active lifestyle, as well as consumption of unhealthy foods, such as those foods which are energy dense, high in saturated fats and those with a high glycemic index. Lack of paternal education was also associated with being overweight, which is consistent with reports from Saudi Arabia (ElHazmi & Warsy, 2002) and Yemen (Nasreddine et al., 2014). This similarity may be partly explained by the hypothesis that high educational level will lead to more healthy food choices and increased physical activity. The dietary patterns of school adolescents played a significant role, as students who consumed fruit and vegetable were less overweight. Studies from Hawassa also showed that adolescents who consumed fewer fruits were more obese than adolescents who daily consumed fruits (Teshome et al., 2013). However, in Gondar town (Gebregergs et al., 2013), no association was found between fruit consumption and the incidence of overweight/obesity. Findings of this study showed that there was no statistically significant association between fast food intake and overweight/obesity. However, results from Lebanon (Nasreddine et al., 2014) reported a positive association between fast food consumption and overweight/obesity. This difference might be due to less accessibility of fast foods in Ethiopia. This study also documented the significant relationship between physical activity and overweight/obesity which is consistent with the results from Addis Ababa showing a significant association between sedentary behavior and overweight/obesity (Alemu et al., 2014). Study Limitation Although this study addressed very important issues, significant limitations were identified. Other factors which might impact rates of overweight/obesity, such as genetic influences, parental BMI and the health condition of participants were not addressed. Recall bias may influence results as the participants could forget what he or she consumed, but intensive training was given for data collectors on how to probe caregivers. Additionally, the use of BMI data may erroneously identify muscular individuals as being overweight/obese. Finally, as dietary intake and physical activity were self-reported data, over- or underreporting may be a significant concern. Practice Implications The findings of this study can be used to strengthen the health promotion activities of pediatric nurses and other health professionals in the prevention of overweight/obesity. Despite the fact that under-nutrition has been identified as the most common public health problem,
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researchers can use the result of this study as a baseline to conduct further studies on the negative consequences of over-nutrition in developing countries. Additionally, the result of this study can be also used to inform policy makers and other stakeholders about an emerging nutrition related problems among adolescents. Conclusions Our results showed that the prevalence of overweight and obesity among school adolescents in Jimma town is considerably high compared to certain previous studies done in Ethiopia. Overweight/obesity is significantly associated with being a female, attending private school, higher household economic status, dietary patterns and lifestyle. Policymakers and school communities should focus on the promotion of healthy lifestyles and proper eating habits among school adolescents. Conflict of Interests The authors declare that they have no competing. Ethics Approval and Consent to Participate Ethical clearance was obtained from the Institutional Review Board of Jimma University. Letter of support was also obtained from Population and Family Health department and submitted to the school director. Permission was also obtained from the Jimma town Education Office. Informed verbal consent was also obtained from study participants and they were also briefed about the purpose of the study, including how the study will be beneficial to them and for the whole country. Authors' Contribution The first (NG) and the second (DT) authors had equal contribution. All authors had designed and supervised the study. NG and DT had the primary responsibility for the content and finally submitted paper for publication. Acknowledgment We would like to express our sincere gratitude to Jimma University and Ethiopian Public Health Institute for their cooperation in the provision of necessary materials and study participants for their commitment and time for this study. References Alemu, E., Atnafu, A., Yitayal, M., & Yimam, K. (2014). Nutrition & food prevalence of overweight and/or obesity and associated factors among. Nutrition & Food Sciences, 4(2), 10–14. Al-Sendi, A. M., Shetty, P., Musaiger, A. O., & Myatt, M. (2003). Relationship between body composition and blood pressure in Bahraini adolescents. British Journal of Nutrition, 90(4), 837–844. Bull, F. C., Maslin, T. S., & Armstrong, T. (2009). Global physical activity questionnaire (GPAQ): Nine country reliability and validity study. Journal of Physical Activity & Health, 6(6), 790–804. Creber, R. M. M., Smeeth, L., Gilman, R. H., & Miranda, J. J. (2010). Physical activity and cardiovascular risk factors among rural and urban groups and rural-to-urban migrants in Peru: A cross-sectional study. Revista Panamericana de Salud Pública, 28(1), 1–8. Daboné, C., Delisle, H. F., & Receveur, O. (2011). Poor nutritional status of schoolchildren in urban and peri-urban areas of Ouagadougou (Burkina Faso). Nutrition Journal, 10(1), 34. El-Hazmi, M. A., & Warsy, A. S. (2002). A comparative study of prevalence of overweight and obesity in children in different provinces of Saudi Arabia. Journal of Tropical Pediatrics, 48(3), 172–177. EU (2014). EU action plan on childhood obesity 2014–2020. Nutrition and physical activity from childhood to old age: Challenges and opportunities. (February). Retrieved from http://ec.europa.eu/health/nutrition_physical_activity/docs/childhoodobesity_ actionplan_2014_2020_en.pdf FDRE (2013). National Nutrition Programme Republic of Ethiopia. Retrieved from www. unicef.org/ethiopia/National_Nutrition_Programme.pdf (2013) Gebregergs, G., Yesu, M., & Beyen, T. (2013). Overweight and obesity, and associated factors among high school. J Obes Wt Loss, 3(165), 2–6.
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Hajian-Tilaki, K. O., & Heidari, B. (2007). Prevalence of obesity, central obesity and the associated factors in urban population aged 20–70 years, in the north of Iran: A population-based study and regression approach. Obesity Reviews, 8(1), 3–10. Hussein Badi, M. A., García Triana, B. E., & Suárez Martínez, R. (2013). Overweight/obesity and socioeconomic status in children from Aden governorate, Yemen, 2009. Rev. habanera Cienc.méd, 12(3), 364–373. Jagadesan, S., Harish, R., Miranda, P., Unnikrishnan, R., Anjana, R. M., & Mohan, V. (2014). Prevalence of overweight and obesity among school children and adolescents in Chennai. Indian Pediatrics, 51(7), 544–549. Kyallo, F., Makokha, A., & Mwangi, A. M. (2013). Overweight and obesity among public and private primary school children in Nairobi, Kenya. Health, 5(8), 85–90. Mustapha, R. A., & Sanusi, R. A. (2013). Overweight and obesity among in-school adolescents in Ondo state, Southwest Nigeria. African Journal of Biomedical Research, 16(3), 205–210. Nasreddine, L., Naja, F., Akl, C., Chamieh, M. C., Karam, S., Sibai, A. M., & Hwalla, N. (2014). Dietary, lifestyle and socio-economic correlates of overweight, obesity and central adiposity in lebanese children and adolescents. Nutrients, 6(3), 1038–1062. Onis, M., Blossner, M., & Borghi, E. (2010). Global prevalence and trends of overweight and obesity among preschool children. American Journal of Clinical Nutrition, 92(C), 1257–1264 http://doi.org/10.3945/ajcn.2010.29786.
PRB (2013). The world's youth 2013 data sheet. Retrieved from www.prb.org/pdf13/ youth-data-sheet-2013.pdf Teshome, T., Singh, P., & Moges, D. (2013). 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, 1(1), 23–36. UNFPA (2014). The power of adolescents, youth and the transformation of the future state. Retrieved from www.unfpa.org/swop-2014 WHO (2003). The WHO STEPwise approach to surveillance of noncommunicable diseases (STEPS). Retrieved from www.who.int/ncd_surveillance/en/steps_framework_ dec03.pdf WHO (2011). Chapter 1: Burden: Mortality, morbidity and risk factors. Global status report on non-communicable diseases 2010 (http://doi.org/ISBN 978 92 4 068645 8). WHO (2013). WHO Media Centre. Obesity and overweight. Fact sheet No.311. Obesity and oveweight fact sheet. Retrieved from http://www.who.int/mediacentre/ factsheets/fs311/en/ WHO (2014). World Health Organization - Noncommunicable diseases (NCD) country profiles, 2014 Retrieved from http://www.who.int/nmh/publications/ncd-profiles2014/en/
Contents lists available at ScienceDirect
Journal of Pediatric Nursing
The Emerging Nutritional Problems of School Adolescents: Overweight/ Obesity and Associated Factors in Jimma Town, Ethiopia Nurezeman Gali, MSc b, Dessalegn Tamiru, MSc a,⁎, Meseret Tamrat, MSc a a b
College of Health Science, Jimma University, Ethiopia Nursing Department, Jimma University Specialized Hospital, Ethiopia
a r t i c l e
i n f o
Article history: Received 5 December 2016 Revised 12 March 2017 Accepted 13 March 2017 Available online xxxx Keywords: Overweight Obesity Adolescents Jimma Town
a b s t r a c t Background: Globally, overweight is rapidly becoming one of the most important medical and public health problems. Adolescent obesity is a multisystem disease with potentially devastating consequences that persist into adulthood. However, there is a paucity of available information regarding the adolescent overweight and obesity in Ethiopia, particularly in the study area. Methods: A school-based cross-sectional study was conducted from March to April/2015 among 546 adolescents. Study participants were selected using a multi-stage, stratified random sampling method. An interviewer administered questionnaire was used to collect data. Multivariable logistic regression analysis was used to identify independent predictors of overweight and obesity at 95% confidence intervals. Results: The mean dietary diversity score of school adolescents was 6.97 ± 1.15. Cereal based diets (99.6%) and vegetables (73.9%) are the two common foods of adolescents. The prevalence of overweight/obesity was 13.3%. Overweight/Obesity was significantly associated with being a female (AOR = 3.57 [95% CI:1.28–9.9]), attending private schools (AOR = 7.53 [2.51–22.3]), lack of paternal education (AOR = 5.57 [95% CI:1.53–20.26]), wealthy households (AOR = 3 [95% CI:1.09–8.26]) and not being a vegetarian (AOR = 9.23 [95% CI:1.68–50.8]). Adolescents who are physically inactive (AOR = 3.7 [95% CI:1.06–13.02]) and those with sedentary lifestyles (AOR = 3.64 [95% CI:1.39–9.5]) were more obese compared to their counter peers. Conclusions: The proportion of overweight/obesity among school adolescent was considerably high. Being a female, learning in private school, high household economic status, not being a vegetarian and having a sedentary life were significantly associated with overweight/obesity. Practice implications: Findings of this study can be used to guide the development of programs aimed at preventing overweight/obesity in Ethiopia by informing policymakers and other stakeholders about this emerging nutrition-related problem among school adolescents. © 2017 Elsevier Inc. All rights reserved.
Background United Nations Population Fund (UNFPA) reported that adolescents account about one fourth of the total world's population in which the majority of them live in developing countries (UNFPA, 2014). World Health Organizations (WHO) defined adolescence as a pivotal period of development which represents the age between 10 and 19 years (WHO, 2013). During this critical period, dietary patterns play an important role in the nutritional status of adolescents, as well as lifelong health. However, adolescents face serious nutritional challenges which could affect their rapid growth spurt as well as their health status. In developing countries like Ethiopia, the main nutritional problems affecting both young children and adolescents are under-nutrition. Under⁎ Corresponding author. E-mail addresses: [email protected] (N. Gali), [email protected] (D. Tamiru), [email protected] (M. Tamrat).
http://dx.doi.org/10.1016/j.pedn.2017.03.002 0882-5963/© 2017 Elsevier Inc. All rights reserved.
nutrition and infections play major roles in determining morbidity and mortality in low-income countries and limit the wellness and productivity of young children and adolescents. However, the problem of over-nutrition is increasing significantly, becoming one of the emerging public health problems in developing countries like Ethiopia (FDRE, 2013; PRB, 2013; UNFPA, 2014; WHO, 2013). Overweight and obesity are both chronic conditions that are the result of an energy imbalance over a period of time. An energy imbalance arises when the number of calories consumed is not equal to the number of calories used by the body. The cause of this energy imbalance can be due to a combination of several different factors and varies from one person to another (WHO, 2013). Globally, overweight is rapidly becoming one of the most important medical and public health problems of our times with the worrisome rise in the magnitude among the young population. According to recent statistics, the worldwide rates of overweight and obesity among children aged 5–17 years were 10% and 2–3.5% respectively (UNFPA, 2014; WHO, 2013, 2014). In Africa,
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despite deep-rooted under-nutrition, a study conducted in seven countries reported that 8.5% of children were overweight or obese, and this incidence is projected to reach 12.7% by 2020. In Ethiopia, there are no national level data, but a study conducted in Addis Ababa showed that 8.6% of adolescents were overweight (Alemu, Atnafu, Yitayal, & Yimam, 2014; Onis, Blossner, & Borghi, 2010). Obesity is assigned as the fifth leading risk for deaths globally. It accounts for nearly three million deaths and 35.8 million of global disability adjusted life years (DALYs). Likewise, 44% of the diabetes, 23% of the ischemic heart disease and 7% to 41% of certain cancers worldwide were attributed to nutrition related non-communicable disease (EU, 2014; WHO, 2003, 2011). Adolescent obesity is a multisystem disease with potentially devastating consequences that persist into adulthood. Additionally, the care of overweight is associated with increased health care costs to the society. The impact also extends to psychological well-being, and is associated with decreased self-esteem, lower educational attainment and higher rates of poverty (EU, 2014; Onis et al., 2010; WHO, 2003). Adolescent health and nutrition are important in the overall social and economic development of a country, as adolescents are tomorrow's workforce and leaders. Studies evaluating under-nutrition have identified it as the most common public health problem. However, for some time the nutritional status of adolescents has been largely overlooked, as they were considered to be less vulnerable to malnutrition. Various studies in different countries showed that there is a high increment of overweight and obesity among young children and adolescents. Studies also showed that urban dwellers are more obese than those in rural areas due to relatively lower physical activity and more sedentary lifestyles in urban (Creber, Smeeth, Gilman, & Miranda, 2010; EU, 2014; Onis et al., 2010; WHO, 2003). Without early intervention, adolescent obesity can persist into adulthood and increase the risk of chronic disease. Findings from several studies also showed that the most effective ways to prevent the adverse consequences of obesity are the identification of predisposing factors and management of obesity, especially during the early life stages (FDRE, 2013; WHO, 2003, 2013). To address this evolving health concern, the problem of overweight/obesity was incorporated into the national nutrition program, and an initiative to encourage physical activity was launched in Ethiopia (EU, 2014; FDRE, 2013; WHO, 2011, 2013). However, these efforts are not specifically targeted to adolescents. Additionally, studies were conducted using growth reference that used formula fed children from a single ethnic group as a global standard. These references were inaccurate in estimating the magnitude of the problem and were of limited value in planning effective intervention strategies (FDRE, 2013). Therefore, this study was conducted to determine the magnitude and predictors of obesity and overweight among Jimma town school adolescents. It is envisioned that data from this study can be used to inform policy makers, educators and other stakeholders in designing early prevention of nutrition-related problems among school adolescents. Methods Study Area and Period This study was conducted in Jimma town's schools from March 8 to April 1, 2015. Jimma town is located at 357 km to the south west of Addis Ababa. Jimma town is the fifth largest city in Ethiopia with an estimated population of about 195,228. According to the 2014 Jimma town education bureau report, the town has 16 governmental and 12 private schools. The total number of adolescent students attending schools is 20,886, of which 10.985 were female. Sampling and Source Population A school based cross-sectional study was conducted with adolescents attending school in Jimma town. The sample size was calculated
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by using a single population formula with 5% margin of error, 95% confidence interval and the proportion adolescent girls who were reported to be overweight (20.2%) in Hawassa town (Teshome, Singh, & Moges, 2013). By adding a 10% non-response rate and considering the design effect the total sample size projected for 546. A multistage stage stratified random sampling technique was employed to select the study subjects. The schools were stratified into governmental and private schools according to their ownerships. At the first stage a total of eight schools, five government and three private schools, were selected by lottery from each. Secondly, one section per grade was selected by using a lottery method from each selected school. Then, the sample size was proportionally allocated for male and females. Finally, participants were selected by using computer generated simple random sampling techniques. Data Collection and Analysis Methods Interviewer-administered questionnaires were used to collect data. A qualitative food frequency questionnaire modified from WHO-STEP wise approach was used to gather information on the frequency of consumption of different food groups from each participant. This technique was considered to obtain qualitative descriptive data on typical consumption of foods and food groups over extended periods of time. Finally, data were collected to categorize participants based on detailed information regarding food choices and dietary diversity (WHO, 2003). The Global Physical Activity Questionnaire (GPAQ) developed by WHO for physical activity surveillance was used to assess the physical activity pattern among school adolescents in three domains, including activity at work, travel to and from places, recreational activities and sedentary behavior through face-to-face interviews with the respondents. The activity level of the study participants was evaluated according to the WHO total physical activity. Vigorous exercise was defined as activity that causes large increases in respiratory or heart rate, such as carrying or lifting heavy loads, digging or construction work, running or jogging, high-intensity aerobic classes, and competitive full-field sports (soccer) or basketball (Bull, Maslin, & Armstrong, 2009). The weight of each student was measured using the UNICEF Seca digital weighing scale (Germany) with light clothing and recorded to the nearest 0.1 kg. Height was measured using a portable Stadiometer (Seca, Germany) and recorded to the nearest 0.1 cm. During height measurement shoes, bulky clothing, pins and braids from the hair that could affect the measurement were removed. Height was measured with the head of participants at the Frankfurt plane, knees straight and the heels buttocks and the shoulder blades touching the vertical surface of the stadiometer. Data were collected by fluent speaker of local languages (Afan Oromo and Amharic) after training them. Mock interviews and practical field exercise were practiced with data collectors to ensure the quality of the field operation. During data collection, the supervisors followed data collectors and performed quality checks with the principal investigator. The questionnaire was prepared in English and translated to Amharic and Afan Oromo, then back translated to English to ensure the consistency of the questions. The data entry was done using Epi-Data version 3.1. The data were checked for missing values, outliers and analysed using SPSS version 20 and WHO Anthro-Plus (version 1.0.4.0). Descriptive statistics were used to examine the frequency distributions of selected study variables. Principal component analysis was used to assess household wealth status and components were developed using items with Eigen values greater than one. Finally, household wealth status was ranked as low, medium and high based up on variable factor scores. Overweight and obesity were determined using the WHO's age and gender specific growth reference for children aged 5–19 years (WHO, 2003). To allow for comparisons with other studies, overweight and obesity were also re-analysed using both CDC 2000 and IOTF criteria. A general chi-square for independence was used to investigate the association between
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overweight/obesity and nominal explanatory variables. Chi-square test for trends were used to measure the association between overweight/ obesity and ordinal scale independent variables. First, bivariate analysis was conducted to identify those variables with p-values ≤ 0.2. Before the inclusion of predictors in the final model, multi co-linearity was checked using the cut-off point VIF b10. Then, multivariable logistic regression was carried out to isolate independent predictors of obesity and overweight. The goodness of fit of the final logistic model was tested by using Hosmer and Lemeshow's test at a p-value of N 0.05 and Omnibus test p-value b 0.05. Both crude odds ratio and adjusted odds ratio with 95% confidence interval were reported. Data qualities were ensured during tool development, data collection, cleaning, entry and analysis. The data collectors were trained for one day on data collection methods and the tool was pretested. The principal investigator conducted on the spot checking and reviewed all the completed questionnaires to ensure completeness and consistency of collected information. Anthropometric measurements were taken using standardized and calibrated equipment in triplicates for each participant. Weighing scales were checked and zero after weighing every participant and regularly calibrated with an object of known weight.
Dietary Intake of Adolescents The mean dietary diversity score of school adolescents was 6.97 ± 1.15. Three hundred ninety-six non-obese students (88%) had a high dietary diversity score (DDS ≥ 5). Almost all (99.6%) students had consumed cereal-based foods with varying frequency per week. Three hundred thirty students (64.7%) had consumed fruits, and 480 (94.12%) of them had vegetables recently. More than three fourths (78%) of adolescents consumed legumes at least once per week. More than half of the students, 281 (55.1%) ate a snack daily. Nearly half, 275 (53.9%) of the students did not eat fast foods in a typical week. One-fourth (25.9%) of the adolescents did not eat their breakfast regularly. Four hundred nine students, 409 (80.2%) did not eat their meal outside of the home (Table 2). Physical Activity and Sedentary Life More than half, 269 (52.7%) of the respondents were engaged in certain household activities besides their education. Four hundred twenty seven students (83.7%) walk to school on foot, and most of them (62.7%) were involved in moderate to vigorous sport activities. The mean sedentary time was 3.78 ± 1.6 h per day (Table 3).
Results Nutritional Status of Adolescents Socio-demographic Characteristics This study aimed to assess the emerging nutritional problems and its association with dietary intake among school adolescents in Jimma town. Out of 546 sampled adolescents, 93.4% provided complete responses. The mean age of respondents was 15.37 ± 1.88 years. Nearly two thirds (67.6%) of the respondents were from government schools (Table 1).
The mean BAZ and BMI of the students were − 0.19 ± 1.19 and 20.05 ± 3.23 respectively. Females and private school adolescents had the highest BAZ and BMI than their counter peers (Table 4). A small number of study participants (11.1%) were underweight and 385 (75.5%) were within normal range. The prevalence of overweight and obesity was 60 (11.8%) and 8 (1.6%) respectively. The gender specific distribution of BMI status showed that the prevalence of overweight
Table 1 Socio-demographic characteristics of adolescents in Jimma town, Ethiopia, 2015. Variables
Categories
Gender
Female Male Single In a relation Private Government Protestant Orthodox Muslim Primary school Secondary school No formal education Primary school Secondary school Tertiary school No formal education Primary school Secondary school Tertiary school Merchant Government employee NGO Daily laborer Others$ Merchant Government employee House wife Others$ Low Medium High
Marital status School type Religion
Participant education Maternal education
Father education
Paternal occupation
Maternal occupation
Household wealth status
$
Daily laborer, farmer, no job.
Overweight/obese
p-Value
No (%)
Yes (%)
250 (82.5) 192 (92.8) 435 (86.5) 7 (100) 122 (73.9) 320 (92.8) 74 (91.4) 159 (77.9) 209 (92.9) 183 (89.7) 259 (84.6) 57 (81.4) 132 (86.8) 183 (85.5) 70 (94.5) 61 (76.25) 90 (85.7) 140 (89.2) 151 (89.9) 133 (86.9) 157 (88.2) 42 (67.7) 78 (94.1) 32 (94.4) 126 (86.9) 133 (95.7) 165 (83.8) 18 (62.1) 254 (91.4) 80 (84.2) 108 (78.8)
53 (17.5) 15 (7.2) 68 (13.5) – 43 (26.1) 25 (7.2) 7 (8.6) 45 (22.1) 16 (7.1) 21 (10.3) 47 (15.4) 13 (18.6) 20 (13.2) 31 (14.5) 4 (5.4) 19 (23.8) 15 (14.35) 17 (10.8) 17 (10.1) 20 (13.1) 21 (11.8) 20 (32.3) 5 (6) 2 (5.9) 19 (13.1) 6 (4.3) 32 (16.2) 11 (37.9) 24 (8.6) 15 (15.8) 68 (13.3)
b0.001 0.602 b0.001 0.430
0.111 0.290
0.013
0.470
0.310
0.001
N. Gali et al. / Journal of Pediatric Nursing 35 (2017) 98–104 Table 2 Dietary intake characteristics of school adolescents in Jimma town, Ethiopia, 2015. Variables (n = 510)
DDS category Cereal
Vegetables
Fruit
Animal source
Dairy product
Legumes and nuts
Sweet food
Oil and fats Snacking Fast food
Skipping breakfast
Eating out side
Categories
Low (DDS b 5) High (DDS ≥ 5) 1–2×/wk. 3–4×/wk. 5–7×/wk. None 1–2×/wk. 3–4×/wk. 5–7×/wk. None 1–2×/wk. 3–4×/wk. 5–7×/wk. None 1–2×/wk. 3–4×/wk. 5–7×/wk. None 1–2×/wk. 3–4×/wk. 5–7×/wk. None 1–2×/wk. 3–4×/wk. 5–7×/wk. None 1–2×/wk. 3–4×/wk. 5–7×/wk. 3–4 5–7×/wk. 3-6 x/wk. 7x/wk. None 1–2×/wk. 3–4×/wk. 5–7×/wk. None 1–2×/wk. 3–4×/wk. 5–7×/wk. No Yes
Overweight/obese No (%)
Yes (%)
46 (75.4) 396 (88.2) 36 (79.1) 29 (87.9) 377 (87.7) 18 (60.0) 82 (79.6) 168 (86.6) 174 (95.1) 157 (87.2) 16 (61.5) 104 (81.9) 165 (93.2) 189 (93.6) 143 (87.2) 59 (79.7) 51 (72.9) 226 (89.0) 119 (84.4) 47 (83.9) 50 (84.7) 5 (83.3) 67 (82.7) 171 (90.5) 199 (85.0) 97 (86.6) 238 (88.8) 81 (88.0) 26 (68.4) 17 (85.0) 425 (86.7) 202 (88.2) 240 (85.4) 250 (90.9) 165 (87.8) 9 (52.9) 18 (60.0) 332 (87.8) 78 (87.6) 15 (65.2) 17 (85) 349 (85.3) 93 (92.1)
15 (24.6) 53 (11.8) 9 (20.9) 4 (12.1) 55 (12.7) 12 (40) 21 (20.4) 25 (13.4) 10 (4.9) 23 (12.8) 10 (38.5) 23 (18.1) 12 (6.8) 13 (6.4) 21 (12.8) 15 (20.3) 19 (27.1) 28 (11.0) 22 (15.6) 9 (16.1) 9 (15.3) 1 (16.7) 14 (17.3) 18 (9.5) 35 (15.0) 15 (13.4) 30 (12.2) 11 (12) 12 (31.6) 3 (15.0) 65 (13.3) 27 (11.8) 41 (14.6) 25 (9.1) 23 (12.2) 8 (47.1) 12 (40.0) 46 (12.2) 11 (12.4) 8 (34.8) 3 (12.4) 60 (14.7) 8 (7.9)
p-Value
101
Table 3 Physical activity characteristics of adolescents in Jimma town, Ethiopia, 2015. Variables (n = 510)
Categories
0.014
House-working
0.358
Vigorous intensity activities
b0.001
Moderate intensity activities
0.029
Walking/using bicycle
b0.001
Vigorous sport activities
0.213
Moderate sport activities
0.761
Physical activities
Sedentary behavior 0.206 Mode of transportation
No Yes None 1–2 3–5 None 1–2 3–4 5–7 None 1–2 3–4 5–7 None 1–2 3–4 5–7 None 1–2 3–4 5–7 High Medium Low b3 h ≥3 h Vehicle On foot
Overweight/obesity
p-Value
No (%)
Yes (%)
196 (81.3) 246 (91.4) 378 (86.3) 24 (75.0) 40 (100.0) 217 (83.5) 28 (82.4) 74 (89.2) 123 (92.5) 56 (59.6) 46 (97.9) 27 (79.4) 309 (93.4) 196 (78.7) 84 (95.5) 85 (93.4) 77 (93.9) 274 (83.0) 79 (91.9) 51 (96.2) 38 (92.7) 191 (91.8) 192 (94.1) 59 (60.2) 239 (94.5) 203 (79.0) 45 (54.2) 397 (93.0)
45 (18.7) 23 (8.8) 60 (13.7) 8 (25.0) – 43 (16.5) 6 (17.6) 9 (10.8) 10 (7.50 38 (40.4) 1 (2.1) 7 (20.6) 22 (6.6) 53 (21.3) 4 (4.5) 6 (6.6) 5 (6.1) 56 (17.0) 7 (8.1) 2 (3.8) 3 (7.3) 17 (8.2) 12 (5.9) 39 (39.8) 14 (5.5) 54 (21.0) 38 (45.8) 30 (7.0)
0.001 0.060
0.040
b0.001
b0.001
0.007
b0.001
b0.001 b0.001
0.831 0.120 b0.001
0.317
0.214
×/wk.: frequency of consumption per week.
was 5.3% (11 students) for males and 16.2% (49 students) for females, whereas the obesity rates among students from private versus government schools were 22.6% and 6.7% respectively. Results were analysed according to IOTF and CDC criteria and compared with findings from some selected countries and worldwide data. Based on the IOTF criteria, the prevalence of overweight and obesity among school adolescents in Jimma town was 7.1% and 1% respectively. These percentages increased to 9.2% and 3.1% respectively when the CDC 2000 overweight/obesity definitions were utilized (Fig. 1). Factors Associated With Overweight/Obesity A multivariable logistic regression analysis showed that gender, school type, paternal education, household wealth status, fruit and vegetable and animal source food consumption, physical activity and sedentary behaviours are independently associated with overweight/ obesity among school adolescents. Girls are more than three times at risk of being overweight or obese compared to boys (AOR = 3.57 [95% CI: 1.28–9.9]. Adolescents attending private schools were greater than seven times (AOR = 7. 53 [95% CI: 2.51–22.3]) more at risk for becoming overweight or obese than government school adolescents. Adolescents whose father did not attend
formal education were more at risk of being obese (AOR = 5.57 [95% CI: 1.53–20.26]) compared to whose fathers attended college and above. Adolescents from a high wealth households were 3 times more likely to be overweight or obese (AOR = 3 [95% CI: 1.094–8.26]) than those from low wealth households. Adolescents who did not consume vegetables were nine times more likely to become overweight or obese (AOR = 9.23 [1.68–50.8]) than adolescents who consumed vegetables regularly. Similarly, adolescents who ate vegetables once or twice a week were five times more likely to be overweight or obese than those who consumed vegetables regularly. Those who ate no fruits were at 5 times greater risk of overweight/obesity than those who consumed fruits on a regular basis (AOR = 5.08 [1.57–16.38]). Physically inactive adolescents were almost four times more likely to be obese/overweight (AOR = 3.7 [1.06–13.02]) than active adolescents. Adolescents who were not involved in different physical activities for N 3 h per day were 3.64 times more at risk of being obese and/overweight than their counter peers (AOR = 3.64 [1.39– 9.5]) (Table 5). Discussion Nutrition related problems early in life have an impact on the psychosocial well-being and quality of life of adolescents. They can have far-reaching impacts on the country's economic growth, both in terms of lost productivity and increased burden of disease (FDRE, 2013; WHO, 2003, 2011, 2013). Studies have shown that in Ethiopia the Table 4 The anthropometric measurements of school adolescents in Jimma town, Ethiopia/2015. Variables (n = 510)
Weight Height BAZ BMI
Sex
Type of school
Female
Male
Private
Government
52.8 159.5 0.01 20.69
50.9 162.3 −0.49 19.13
55.7 162.1 0.09 21.14
50.2 159.9 −0.33 19.54
Total
52 kg 160.6 cm −0.19 20.05 kg/m2
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Fig. 1. Prevalence of overweight/obesity using various diagnostic criteria among adolescents in Jimma town, Ethiopia, 2015.
problem of nutrition-related, non-communicable disease is increasing significantly over time. Nutrition-related, non-communicable disease, namely overweight/obesity, is becoming increasingly recognized as a public health problem, in contrast to previous policies which focused primarily on the problem of under-nutrition. Therefore, the findings of this study have meaningful input in addressing the problem of nutrition-related issues especially among school adolescents. Findings of this study showed that the overall prevalence of overweight/obesity according to WHO 2007 definition was 13.4%, which is relatively low when compared to findings from Hawassa where 15.6% of adolescents were obese/overweight (Teshome et al., 2013). However, it is relatively high when compared to findings from Gonder where only 5.9% of
adolescents were obese/overweight (Gebregergs, Yesu, & Beyen, 2013). This difference might be due to differences in socioeconomic backgrounds and the availability of recreational facilities. The findings of this study indicated that adolescent overweight/obesity was significantly associated with school type. Students who attended private school were likely to be obese than those who attended government school. This finding is consistent with a study from India (Jagadesan et al., 2014), Saudi Arabia (El-Hazmi & Warsy, 2002), Yemen (Hussein Badi, García Triana, & Suárez Martínez, 2013), Burkina Faso (Daboné, Delisle, & Receveur, 2011) and Kenya (Kyallo, Makokha, & Mwangi, 2013). This similarity might be due to the fact that these adolescents usually come from families with a higher
Table 5 Multivariable logistic regression analysis of predictors of overweight/obesity among. Variables (n = 510)
Categories
Yes (%)
No (%)
COR
AOR (95 CI)
Gender
Female Male Private Government No education Primary Secondary Tertiary Low Medium High None 1–2×/wk. 3–4×/wk. 5–7×/wk. None 1–2×/wk. 3–4×/wk. 5–7×/wk. None 1–2×/wk. 3–4×/wk. 5–7 ×/wk. Inactive Active b3 h ≥3 h
53 (17.5) 15 (7.2) 43 (26.1) 25 (7.2) 19 (23.8) 15 (14.35) 17 (10.8) 17 (10.1) 24 (8.6) 15 (15.8) 68 (13.3) 12 (40.0) 21 (20.4) 26 (13.4) 9 (4.9) 23 (12.8) 10 (38.5) 23 (18.1) 12 (6.8) 13(6.4) 21 (12.8) 15 (20.3) 19 (27.1) 40 (56.3) 28 (6.4) 14 (5.5) 54 (21)
250 (82.5) 192 (92.8) 122 (73.9) 320 (92.8) 61 (76.25) 90 (85.7) 140 (89.2) 151 (89.9) 254 (91.4) 80 (84.2) 108 (78.8) 18 (60.0) 82 (79.6) 168 (86.6) 174 (95.1) 157 (87.2) 16 (61.5) 104 (81.9) 165 (93.2) 189 (93.6) 143 (87.2) 59 (79.7) 51 (72.9) 31 (43.7) 411 (93.6) 239 (94.5) 203 (79.0)
2.7⁎ 1 4.51⁎⁎ 1 2.76⁎ 1.48 1.079 1 1 1.98 2.84⁎ 12.88⁎⁎ 4.95 2.99 1 2.01⁎
3.57 (1.28–9.91)⁎⁎ 1 7.53 (2.51–22.3)⁎
School type Father education
Wealth status
Vegetables consumption
Fruit consumption
Animal source intake
Physical activity Sedentary behavior
Jimma town adolescents in February/2015. COR: crude odd ratio, AOR: adjusted odd ratio. ⁎ Significant at b0.05. ⁎⁎ Significant at ≤0.001.
8.59 3.04 1 0.185⁎⁎ 0.39⁎ 0.68⁎ 1 18.94⁎⁎ 1 1 0.22
1 5.57 (1.53–20.26)⁎ 3.7 (1.01–13.76)⁎ 0.73 (0.19–2.82) 1 1 2.25 (0.73–6.93) 3 (1.09–8.26)⁎ 9.23 (1.68–50.8)⁎ 8 (1.93–33.9)⁎ 3.13 (0.99–9.98) 1 5.08 (1.57–16.38)⁎ 4.17 (0.56–30.85) 2.87 (0.77–10.65) 1 0.04 (0.01–0.24)⁎⁎ 0.20 (0.05–0.78)⁎ 0.37 (0.87–1.66) 1 3.7 (1.06–13.02)⁎ 1 1 3.64 (1.39–9.5)⁎
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economic status, which likely exposes them to highly-processed, energy-dense foods and a more motorized lifestyle as compared to those attending government schools. Overweight/obesity was not significantly associated with the adolescent's age, which is inconsistent with the findings of studies from Saudi Arabia (El-Hazmi & Warsy, 2002), Turkey (Jagadesan et al., 2014) and Iran (Hajian-Tilaki & Heidari, 2007). This difference could be accredited to innate genetic differences, environmental factors and overall health status, factors which are not addressed by this particular study. Girls are at greater risk of being overweight or obese than males. These results are comparable to those found in Nigeria (Mustapha & Sanusi, 2013) and Bahrain (Al-Sendi, Shetty, Musaiger, & Myatt, 2003). This can be attributed to hormonal changes at puberty resulting in fat accumulation, as well as negative attitudes toward girls' participation in outdoor activities due to certain cultural and religious restrictions. The association between family affluence and overweight/obesity has been debated and this study also found that there was a statistically significant association between overweight/obesity among adolescents from households with high economic status compared to those from households with lower economic status. This is consistent with results from the Hawassa town study (Teshome et al., 2013). This can be explained by the association of wealth with a more motorized, less-active lifestyle, as well as consumption of unhealthy foods, such as those foods which are energy dense, high in saturated fats and those with a high glycemic index. Lack of paternal education was also associated with being overweight, which is consistent with reports from Saudi Arabia (ElHazmi & Warsy, 2002) and Yemen (Nasreddine et al., 2014). This similarity may be partly explained by the hypothesis that high educational level will lead to more healthy food choices and increased physical activity. The dietary patterns of school adolescents played a significant role, as students who consumed fruit and vegetable were less overweight. Studies from Hawassa also showed that adolescents who consumed fewer fruits were more obese than adolescents who daily consumed fruits (Teshome et al., 2013). However, in Gondar town (Gebregergs et al., 2013), no association was found between fruit consumption and the incidence of overweight/obesity. Findings of this study showed that there was no statistically significant association between fast food intake and overweight/obesity. However, results from Lebanon (Nasreddine et al., 2014) reported a positive association between fast food consumption and overweight/obesity. This difference might be due to less accessibility of fast foods in Ethiopia. This study also documented the significant relationship between physical activity and overweight/obesity which is consistent with the results from Addis Ababa showing a significant association between sedentary behavior and overweight/obesity (Alemu et al., 2014). Study Limitation Although this study addressed very important issues, significant limitations were identified. Other factors which might impact rates of overweight/obesity, such as genetic influences, parental BMI and the health condition of participants were not addressed. Recall bias may influence results as the participants could forget what he or she consumed, but intensive training was given for data collectors on how to probe caregivers. Additionally, the use of BMI data may erroneously identify muscular individuals as being overweight/obese. Finally, as dietary intake and physical activity were self-reported data, over- or underreporting may be a significant concern. Practice Implications The findings of this study can be used to strengthen the health promotion activities of pediatric nurses and other health professionals in the prevention of overweight/obesity. Despite the fact that under-nutrition has been identified as the most common public health problem,
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researchers can use the result of this study as a baseline to conduct further studies on the negative consequences of over-nutrition in developing countries. Additionally, the result of this study can be also used to inform policy makers and other stakeholders about an emerging nutrition related problems among adolescents. Conclusions Our results showed that the prevalence of overweight and obesity among school adolescents in Jimma town is considerably high compared to certain previous studies done in Ethiopia. Overweight/obesity is significantly associated with being a female, attending private school, higher household economic status, dietary patterns and lifestyle. Policymakers and school communities should focus on the promotion of healthy lifestyles and proper eating habits among school adolescents. Conflict of Interests The authors declare that they have no competing. Ethics Approval and Consent to Participate Ethical clearance was obtained from the Institutional Review Board of Jimma University. Letter of support was also obtained from Population and Family Health department and submitted to the school director. Permission was also obtained from the Jimma town Education Office. Informed verbal consent was also obtained from study participants and they were also briefed about the purpose of the study, including how the study will be beneficial to them and for the whole country. Authors' Contribution The first (NG) and the second (DT) authors had equal contribution. All authors had designed and supervised the study. NG and DT had the primary responsibility for the content and finally submitted paper for publication. Acknowledgment We would like to express our sincere gratitude to Jimma University and Ethiopian Public Health Institute for their cooperation in the provision of necessary materials and study participants for their commitment and time for this study. References Alemu, E., Atnafu, A., Yitayal, M., & Yimam, K. (2014). Nutrition & food prevalence of overweight and/or obesity and associated factors among. Nutrition & Food Sciences, 4(2), 10–14. Al-Sendi, A. M., Shetty, P., Musaiger, A. O., & Myatt, M. (2003). Relationship between body composition and blood pressure in Bahraini adolescents. British Journal of Nutrition, 90(4), 837–844. Bull, F. C., Maslin, T. S., & Armstrong, T. (2009). Global physical activity questionnaire (GPAQ): Nine country reliability and validity study. Journal of Physical Activity & Health, 6(6), 790–804. Creber, R. M. M., Smeeth, L., Gilman, R. H., & Miranda, J. J. (2010). Physical activity and cardiovascular risk factors among rural and urban groups and rural-to-urban migrants in Peru: A cross-sectional study. Revista Panamericana de Salud Pública, 28(1), 1–8. Daboné, C., Delisle, H. F., & Receveur, O. (2011). Poor nutritional status of schoolchildren in urban and peri-urban areas of Ouagadougou (Burkina Faso). Nutrition Journal, 10(1), 34. El-Hazmi, M. A., & Warsy, A. S. (2002). A comparative study of prevalence of overweight and obesity in children in different provinces of Saudi Arabia. Journal of Tropical Pediatrics, 48(3), 172–177. EU (2014). EU action plan on childhood obesity 2014–2020. Nutrition and physical activity from childhood to old age: Challenges and opportunities. (February). Retrieved from http://ec.europa.eu/health/nutrition_physical_activity/docs/childhoodobesity_ actionplan_2014_2020_en.pdf FDRE (2013). National Nutrition Programme Republic of Ethiopia. Retrieved from www. unicef.org/ethiopia/National_Nutrition_Programme.pdf (2013) Gebregergs, G., Yesu, M., & Beyen, T. (2013). Overweight and obesity, and associated factors among high school. J Obes Wt Loss, 3(165), 2–6.
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