Table 1. Studies reporting anthropometric measures.

First author, y	Main objective (s)	Study design	Setting: Rural/urban	Sample size	Age (y)	Sex (M/F)	Exposure (s)	Outcome (s)	Main findings
Alemayehu T, 2010 [29]	To assess the magnitude of adolescents’ undernutrition and its determinants in public schools	Cross-sectional study	Urban	425 in-school adolescents	10–19	M/F	Age, sex, food intake, family livestock ownership	Under-weight and over-weight	Underweight 27.5% (boys 29.8%, girls 24.6%), young adolescents 38.1%, older adolescents 18.6%) Overweight 4.3% (boys 3.8%, girls 4.9%) Underweight predictors: younger age between 10–14 years (AOR = 1.99, 955% CI: 1.01–3.57), household who produce inadequate food supply as a result obliged to purchase (AOR = 2.4, 95% CI: 1.24–4.74) and family possessed no cattle (AOR = 2.4, 95% CI: 1.24–4.74)P<0.05)
Gebreyohannes Y, 2014 [31]	To assess and compare nutritional status of adolescents and analyze the risk factors associated with overweight/obesity in government and private secondary schools	Comparative cross sectional study	Urban	1024	13–19	M/F	School type	Stunting, underweight, overweight/ obese	Stunting 7.2% (boys 7.7%, girls 6.9%, public school 10.0%, private 4.5%). Underweight 6.2% (boys 9.8%, girls 2.6%, public school 7.0%, private 5.5%), Overweight/obese 8.5% (boys 5.8%, girls 11.3%, public school 4.3%, private 12.7%). Adolescent in private schools are more overweight/obese (AOR 2.2; 95% CI: 1.2–4.2)
Herrador Z, 2014 [30]	To determine prevalence of stunting and thinness and their related factors in Libo Kemkem and Fogera, and compare urban and rural areas. Northwest Ethiopia	Cross-sectional Study	Urban/rural	886 children (259 aged 10–15)	11–15	M/F	Residence/setting	Stunting and thinness	Stunting 53.9% (rural 55.3% and urban 48.4%, P-value <0.05)
Assefa H, 2015 [22]	To identify socio-demographic factors associated with underweight and stunting among adolescents	5-year longitudinal study	Urban/rural	2084	Mean age 14.8 (SD 1.3)	M/F	Socio-demographic factors	Stunting and underweight	Stunted 16% (boys 21%, girls 11%, urban 12%, semi-urban 16%, rural 20%). Underweight 80.8% (boys 73%, girls 89%%, urban 83%, Semi urban 84%, rural 75%, p-value <0.05), Underweight predictors: male sex (β = -0.7; 95% CI: -0.8, -0.6), age in years (β = 0.1; 95% CI: 0.02, 0.1), attending public school (β = 0.8; 95% CI: 0.02, 1.6) Stunting predictors: male sex (β = -0.2; 95% CI: -0.3, -0.1), attending private school (β = —1.2; 95% CI: -1.9, -0.5), household income (β = 0.001, 95% CI: 0.001, 0.002), household size (β = -0.02, 95% CI: -0.04, -0.01)
Roba A, 2015 [90]	To assess nutritional status and dietary intake of rural adolescent girls and determine pulse and food intake patterns associated with poor nutritional status	Cross-sectional study	Rural	188	15–19	F	pulse and food intake patterns	Stunting and Underweight	Stunting was 30.9% and underweight was 13.3%. Stunting and underweight associated with low food and nutrient intake.
Melaku Y, 2015 [33]	To determine prevalence and factors associated with stunting and thinness	Cross sectional study	Rural/urban	348 School adolescents	10–19	M/F	Sex, sex & setting	Stunting and thinness	Stunting 28.5% (boys 37.7%; girls 21.2%, urban 23.5%, rural 36.4%) Thinness 26.1% (boys 32.4, girls 21.6%, urban 29.5%, rural 20.6%) Mean height-for-age and BMI-for-age Z-scores: -1.49 & -1.29, respectively. Stunting predictors: age 13–15 years (AOR =  2.23; 95% CI: 1.22, 4.08), being male (AOR  =  2.53; 95% CI: 1.52, 4.21) and rural residence (AOR  =  2.15; 95% CI: 1.20, 3.86). Thinness predictor: male sex (AOR  =  1.97; 95% CI: 1.19, 3.25), age 16–19 years (AOR  =  0.5; 95% CI: 0.2, 0.9) compared to age 10–12 years
Berheto TM, 2015 [32]	To determine urban-rural disparities in the nutritional status of school adolescent girls in the Mizan district, south-western Ethiopia	Comparative cross-sectional study	Urban/rural	622 (rural 311 and urban 311)	11–19	F	Setting	Stunting	Stunting 4.4% (urban 1.9% and rural 6.9%) Thinness 6.7% (urban 5.2% and rural 8.2%) Overweight 0.6% (urban 1% and rural 0.3%) Mean height-for-age Z-score and BMI-for-age Z-score: –0.6 ± (0.9) and –0.4 (1.0) in urban and –0.8 (0.8) and –0.5 (0.9) in rural areas, respectively
Weres ZG 2015 [36]	To assess the prevalence of adolescent under nutrition and its associated factors	Cross sectional study	Unstated	411	10–19	M/F	Age, sex,	Stunting, thinness, underweight	Stunting, 25.5% (Boys 29.6%, girls 21.6%), thinness 44% (boys 54.7%, girls 33.7%) and underweight 55% (boys 65.5%, girls 44.7%) Thinness predictors: younger (10–14 years) age AOR = 4.7; 95% CI = 1.8, 12.1), male sex (AOR = 5.3; 95% CI = 1.7, 16.3)
Wassie M, 2015 [34]	To assesses level of low BMI-for- age and height-for- age and their associated factors	Cross-sectional study	Unstated	1320	10–19	F	Age, dietary diversity, access for nutrition information, and community based nutrition service, food insecurity	Stunting, thinness	Stunting 31.5%, Thinness 13.6% Thinness predictors: age group 10–14 years (AOR = 5.8, 95% CI: 3.3, 10.4), age group 15–17 years (AOR = 2.1, 95% CI: 1.1, 3.9), with poor dietary diversity score (AOR = 2.5, 95% CI: 1.6, 3.8), utilizing community based nutrition service (AOR = 0.7, 95% CI: 0.5, 0.9) Stunting predictors: age group 10–14 years (AOR = 6.1, 95% CI: 4.0,9.2), age group 15–17(AOR = 1.4, 95% CI: 1.9,2.1), had nutrition and health information(AOR = 1.9, 95% CI: 1.5, 2.6), living in food secured households (AOR:0.7,95% CI: 0.5, 0.8)
Alelign T 2015 [35]	To assess the prevalence and factors associated with undernutrition	Cross sectional study	Urban/rural	403 (209 age 10–14)	10–14	M/F	-	Stunting	Stunting 16.8%, underweight 23.9%
Awel A, 2016 [38]	To assess nutritional status and associated factors	Cross sectional	Rural	655	10–18	M/F	Age, sex, family occupation, family size, parental education, daily food intake frequency	Stunting, thinness	Stunting 11.5% (boys 8.4%, girls 14.9%) Thinness 22.9% (boys 20.8%, girls 25.3%) Stunting predictors: female sex (AOR1 = 2.4, 95% CI: (1.3, 4.3); Age 15–18 (AOR = 10.9, 95% CI: 4.8, 24.4), Family size >5 (AOR = 1.9, 95% CI: 1.1, 3.6), lower family wealth index (AOR = 3.2, 95% CI: 1.5, 6.9), Food insecure adolescent (AOR = 2.6, 95% CI: 1.4, 4.9), agro pastoral family occupation (AOR = 2.5, 95% CI: 1.4, 4.7). Thinness predictors: family size >5 (AOR = 1.7, 95% CI: 1.1,2.6), lower family wealth index (AOR = 1.9 (AOR = 1.1, 95%CI:1.1, 3.2), food insecure adolescent (AOR = 2.0, 95%CI: 1.2,3.3)
DHS report: Adolescent nutrition, 2000–2016 [75]	To assess the nutritional status of adolescent	Cross-sectional survey	Urban/rural	-	15–19	M/F		Thinness	Thinness: girls = Urban 2.2%, rural 6.8%; Boys = Urban 22.9%, rural 29.6% Overweight: girls = Urban 11.4%, rural (not indicated)? BMI-for-age: Girls thin: 2000 (12.3%), 2005(9.4%), 2011 (8.7%), 2016 (5.7%) BMI-for-age: thinness boys: 2003 (36.6%), 2008 (28.3%) BMI-for-age: Girls overweight: 2000 (2.1%), 2005 (3.9%), 2011 (3.2%), 2016 (4.9%). BMI-for-age: boys overweight: 2003 (0.5)%, 2008 0.8%) Percentage of short stature girls: Urban (10.0%), rural (13.0%) BMI-for-age: Girls; 2000 (20.4%), 2005 (16.6%), 2011 (17.7%), 2016 (12.4%).
Roba KT, 2016 [40]	To identify the level of malnutrition and associated Factors	Cross sectional study	urban	726	15–19	F	Parental education, father occupation, DDS,	Stunting and thinness	Stunting 15.6%, Thinness 21.3%, Overweight 3.3%, obese 1.0%, Thinness predictors: Adolescent from illiterate mother (AOR = 5.4; 95% CI: 4.71–9.1, mothers primary level education (AOR = 1.7; 95% CI:0.9–3.2), FATHERS Illiterate (AOR = 3.1; 95% CI:1.7–5.6), Father primary level education (AOR = 2.4; 95% CI:1.4–4.0), Father ocuupation as daily laborer (AOR = 2.7;95% CI:1.5–4.8), adolescent low DDS (AOR = 2.1; 95% CI:1.5–3.9),
Tegegne M, 2016 [42]	To assess the nutritional status and associated factors	Cross sectional study	Urban/rural	598	10–19	F	Age, setting, parental education, parental occupation, family size, DDS	Stunting, thinness	Stunting 20.9%, thinness 11.9% Stunting predictors: mothers illiterate (AOR = 13; 95%CI: (2.7–18.08), low DDS (AOR = 2.7; 95% CI: 1.5–5.04) Thinness predictors: age≤14 (AOR = 1.7; 95%CI: 1.5–2.6), mother illiterate (AOR = 9.6; 95% CI: 2.6–23.3), mother only read/write (AOR = 7.6; 95% CI: 2.2–19.1), mother primary level education (AOR = 5.2; 95%CI:1.4–17.4)
Taji K, 2016 [39]	To assess the nutritional status of adolescent girls	Cross sectional study	Urban/rural	547	10–19	F	Setting, water source, parental education, parental occupation,	Stunting, thinness, overweight, obesity	Stunting 15% (95% CI: 12.1, 18.3) (urban 8.3%, rural 22.7%), Thin 21.6%, Overweight 4.8% (95% CI: 3.1, 6.)9 Obese 1.1% obese (95% CI: 0.4–2.3) Stunting predictors: fathers with farming occupation (AOR = 2.4; 95% CI: 1.2–4.8), rural residence (AOR = 0.4; 95% CI: 0.2–0.8), younger adolescent (AOR = 0.5; 95% CI: 0.3–0.9)
Shegaze M, 2016 [43]	To determine the prevalence of overweight/obesity and associated factors	Cross sectional study	Urban	456	13–19	M/F	Se, age, family wealth status, physical activity, nutrition knowledge	Overweight/obesity	Overweight 9.7% (95% CI: 6.9, 12.4%), Obesity 4.2% 95% CI: 2.3, 6.0%), Overweight/obesity 13.9% (95% CI: 10.6, 17.1%, boys 4.9%, girls 27.6%) Overweight/obesity predictors: female sex (AOR = 7.3; 95%CI: 3.8, 14.1), private school (AOR = 3.5; 95%CI: 2.0, 6.2), high family wealth (AOR = 4.8; 95%CI: 2.4, 9.8), day time sitting >3 hours (AOR = 6.1; 95%CI: 3.5, 10.8), family size>4 (AOR = 0.3; 95%CI: 0.2, 0.6), low total physical activity level (AOR = 8; 95%CI: 3.9, 16.2), ate sweet food in last 7 days (AOR = 6.3; 95%CI: 3.6, 10.9), meal >3times/day (AOR = 3.0; 1.4, 6.6), better nutrtion knowledge (AOR = 0.2; 95%CI: 0.1, 0.4),
Gebregyorgis T. 2016 [91]	To assess the prevalence of thinness, stunting, and associated factors	Cross sectional	Urban /rural	814	10–19	F	Age, mother education, eating frequency, poor water source, family size, father occupation, father education, wealth index,	Stunting and thinness	Stunting 12.2%, Thinness 21.4% Stunting predictor: Family size >5 [AOR = 2.05 (1.31, 3.23)] and unimproved source of drinking water [AOR = 3.82 (2.20, 6.62)] Thinness predictors: Age of adolescent [AOR = 2.15 (1.14, 4.03)], mother’s educational status [AOR = 2.34 (1.14, 4.80)], eating less than 3 meals per day [AOR = 1.66 (1.12, 2.46)], having family size >5 [AOR = 2.53 (1.66, 3.86)]
Gali N, 2017 [44]	To determine the prevalence and predictors of obesity and overweight among school adolescents in Jimma town	A school-based cross-sectional study	Urban	546	Mean age 15.37 (SD 1.88)	M/F	Age, sex, parental education, dietary intake, school type, family wealth, physical activity,	Overweight/Obesity	Overweight/obesity 13.3% (boys 7.2% and girls 17.5%). Overweight/Obesity predictors: female sex (AOR = 3.4; 95% CI:1.3–9.9]), attending private schools (AOR = 7.5; 95% CI: 2.5–22.3), adolescents from wealthy households (AOR = 3; 95% CI:1.1–8.3]) and. those who were physically inactive (AOR = 3.7; 95% CI:1.1–13.02]) and adolescent with sedentary lifestyles (AOR = 3.6; 95% CI:1.4–9.5) were found to be more obese than their counter peers.
Hassen K, 2017 [45]	To investigated the nutritional outcomes of adolescents and their determinants in coffee farming households	Cross-sectional study	Urban/rural	550	10–19	M/F	Age, residency, family wealth, age dependent family size, parental education, household food insecurity, family size,	Stunting, thinness, overweight/obesity	Stunting 15.6% (girls 16.0%, boys 15.1%, urban 19.8%, rural14.9%), Thinness 11.6% (girls 10.9%, boys 12.6%, urban 11.1%, rural 11.7%), Overweight/obesity 7.1% (girls 9.0%, boys 4.6%, urban 4.9%, rural 7.5%) Stunting predictors: lower teritial of wealth index (AOR = 5.6, 95% CI: 2.6–12.0), Overweight/obesity predictors: middle teritial of wealth index (AOR = 2.7; 95% CI 1.1–6.9) compared to highest wealth index teritial, adolescents in low age dependent family size of 1–2 person/household(AOR = 2.6; 95% CI:1.1–6.2), male sex (AOR = 2.4; 95% CI:1.1–5.1) Thinness predictors: lower wealth teritial (AOR = 5.9; 95% CI: 2.8–12.9), higher family size (AOR = 1.3; 95% CI:1.1–1.5)
Bidu KT 2018 [55]	To assess the prevalence and associated factors of undernutrition	Cross sectional study	urban/rural	640	10–19	M/F	-	Stunting, thinness,	Stunting 17.0% (95% CI; 14%, 20%, boys 20.2%, girls 13.7%, urban 26.0%, rural 12.8%) Thinness 18.8%(95% CI; 15.6%, 21.9%, boys 23.3%, girls 14%)
Birru SM, 2018 [47]	To assess prevalence of stunting and associated factors among school adolescent girls in Gondar City	Cross-sectional study	Urban	812	10–19	F	Age, type od school, parental education, parental occupation, dietary diversity, family wealth index and media exposure	Stunting	Stunting 33.1% (private school 12.1%, public school 38.8%) Stunting predictors: younger (AOR = 0.2; 95% CI: 0.0,0.2), middle age adolescent (AOR = 0.2; 95% CI: 0.2, 0.3), and unsatisfactory media exposure (AOR = 1.7; 95% CI: 1.1, 2.8) and poor mother’s education (AOR = 2.8; 95% CI: 1.1, 7.9)
Juju D, 2018 [46]	To assess prevalence and factors associated with nutritional status of adolescents in the selected khat and coffee-growing areas	Cross-sectional study	Rural	234	12–18	M/F	Health problems in the past 30 days	Food insecurity experiences	Stunting 7.3% (boys 8.5%, girls 6.0%). Thinness 12.8% (boys 17.9%, girls 7.7%). Stunting predictors: age 12–14 years (AOR = 3.6; 95% CI, 1.1, 11.5), adolescent from illiterate mothers (AOR = 5.6; 95% CI, 1.6, 20.4). Thinness predictors: Female sex (AOR = 0.4; 95% CI, 0.2, 0.9), dietary frequency <3 times a day (A OR = 4.164; 95% CI, 1.6, 10.7)
Teferi D, 2018 [41]	To assess the prevalence of malnutrition and associated factors	Cross sectional study	Urban/rural dominated by urban	655	10–19	M/F	Age, sex, maternal education, DDS, school type	Stunting, thinness, overweight	Mean height 162.43 cm and weight51.96 kg. Mean HAZ −0.49, and BAZ −0.58 Stunting 5.2% (95% CI: 3.4%,7%, boys 5.9%, girls 4.4%, urban 4.2%, rural 8.8%), thinness 4.8% (95% CI: 3%,6.7%, boys 7.4%, girls 1.9%), and overweight/obesity 5.1% (boys 0.9%, girls 9.5%) Stunting predictors: Maternal secondary educational level (AOR = 0.2; 95% CI: 0.1, 0.9) Thinness predictors: Being male (AOR = 4.1; 95% CI: 2.4,7.0), adolescent from public school (AOR = 0.4; 95% CI: 0.2,0.7), mothers with no formal education (AOR = 4.0; 95% CI: 1.8,8.9), skipping meals (AOR = 1.7; 95% CI: 1.1, 2.7), and illness in 2 weeks prior to survey (AOR = 2.7; 95% CI: 1.5, 4.8) Overweight/obesity predictor: being male (AOR = 0.1; 95% CI: 0.03, 0.2)
Zenebe M, 2018 [92]	To examine the effects of school feeding program on dietary diversity, nutritional status and class attendance of school children	Comparative cross-sectional study	Urban/rural	292	10–14	M/F	School food program	HAZ, BAZ, DDS	Mean (±SD) HAZ score in adolescents with school feeding program was (− 1.45 ± 1.38) compared to those without school feeding program (− 2.17 ± 1.15 which was statistically significant (P < 0.001) adjusted for age, sex, family wealth and parental educational status.
Tariku E, 2018 [49]	To assess the prevalence of stunting and thinness and their associated factors among school age children	cross-sectional study	Rural	389 (137 aged 12–14)	12–14	M/F	-	stunting and thinness	Stunting 51.1% (boys 47.4, girls 36.4%), Thinness 10.2%.
Mekonnen T, 2018 [48]	To assess the prevalence of overweight/obesity and associated factors	cross-sectional study	Urban	634 (327 aged 10–14)	10–12	M/F	-	Overweight/obesity	Overweight/obese 10.4%
Moges T, 2018 [50]	To determine and compare the levels of overweight/obesity among adolescents in private schools with and without adequate play area	Cross-sectional study	Urban	1,276	10–19	M/F	School play area	Obesity	Overweight/obesity 17.0% (boys 14%, girls 20%, age 10–14 years 16.8%, age 15-19years 17.3%). Mean ± SD BAZ was −0.2± 1.3 Overweight predictor: School with no adequate play area (AOR = 1.6; 95% CI: 1.1, 2.5)
Mitiku H, 2018 [52]	To assess the nutritional status of adolescent	Cross sectional study	urban/rural	1523 (767 aged 10–18)	10–18	M/F	-	Stunting and thinness	Stunting 28.0% (in age 10–14 = 26.0%, age 15–18 = 35.3%) Thinness 19.3%(in age 10–14 = 17.6%%, age 15–18 = 39.7%)
Girmay A, 2018 [53]	To assess the prevalence of overweight, obesity and associated factors	Cross sectional study	Urban	950	12–15	M/F	Age, sex, family size, family income, dietary intake,	Overweight/obesity	Overweight/obesity 14.9% (boys 10.9%, 19.1%) positive predictors are female sex (AOR = 1.8; 95% CI:1.2, 2.6)) and taking soft drinks four or more times per week(AOR = 1.0;95%CI: 0.4, 4.6) and lower (<4) family size (AOR = 3.0;95%CI;1.9, 5.0)
Demilew Y, 2018 [51]	To assess the prevalence of under nutrition and its associated factors	cross-sectional study	Urban /rural	424 school adolescents	Mean 16.7 (SD 0.9)	M/F	Sex, parental residence, frequency of dietary intake, water source, family size, illness episode	Under nutrition (stunting and thinness)	Stunting 24.8% (boys 36.2%, girls 15.1%, urban 19.6%, rural 29.3%) Thinness 7.1% (boys 13.8%, girls 1.4%) Stunting predictors: Male sex (AOR = 3.2; 95% CI: (1.7, 5.8), low dietary frequency (1–2 times per day) (AOR = 4.6; 95% CI: 2.6, 8.0), lack of latrine (AOR = 2.7, 95% CI: 1.2, 6.0), and poor hand washing practice (AOR = 3.9; 95% CI: 1.9, 8.1). Thinness predictors: being male [AOR = 11.5; 95% CI: 3.3, 39.5), illness in the last two weeks (AOR = 2.9; 95% CI: 1.2, 7.0), and having more than five family members (AOR = 3.6; 95% CI: 1.3, 9.4)
Tariku EZ 2018	to assess the prevalence of stunting and thinness and their associated factors	Cross-sectional	Rural	389 (age 12–14, n = 137)	12–14	M/F	Sex, age, family size, family income, food security, DDS, parental education,	Stunting and thinness	Stunting 51.1% (boys 47.4%, girls 36.4%) Thinness 10.2%
Arage G, 2019 [56]	To determine the prevalence and factor associated with nutritional status of school adolescent girls in Lay Guyint Woreda, Northwest Ethiopia	Cross-sectional study	Urban /rural	362	10–19	F	Age, residence, mother’s occupation, dietary diversity, frequency of dietary intake	Stunting and thinness	Stunting 16.3% (urban 22.2%, rural 14.6%). Thinness 29% (urban 24.7%, rural 30.2%). Stunting predictors: aged 14–15years (AOR = 3.7; 95% CI: 1.9, 7.1), residence in rural areas (AOR = 1.3; 95% CI: 1.2, 2.3), those who did not have snack (AOR = 11.4; 95% CI: 1.5, 17.8) and farming mother’s occupation (AOR = 0.1; 95% CI: 0.2, 0.9). Thinness predictors: rural resident (AOR = 2.4; 95% CI: 1.1, 5.1) and adolescents aged 14–15years (AOR = 6.1; 95% CI: 2.2, 17.1).
Belay E, 2019 [58]	To find out the prevalence and determinants of pre-adolescent (5–14 years) acute and chronic undernutrition	Cross sectional study	Urban/rural	848 (338 aged 10–14)	10–14	M/F	-	Stunting and thinness	Stunting 41.1%, thinness 12.4%
Beyene S 2019 [63]	To assess the prevalence of undernutrition and associated factors	Cross sectional study	Rural	1437	10–19	M/F	-	Stunting	Stunting 18.4% (boys 18.5%, girls 18.3%) and thinness 15.0% (boys 19.3%, girls 10.7%)
Daba D, 2019 [61]	To assess the prevalence of undernutrition and its associated factors	Cross sectional study	Urban	312	12–18	M/F	Age, sex, DDS, food intake frequency, water source, substance use,	Stunting and thinness	Stunting 30.4%, thinness 29.2% (Boys 27.0%, girls 48.4%), Thinness predictor: female sex (AOR: 2.55; 95%CI: 1.16–5.63), Ever skipped one or more daily meal per day (AOR: 6.56; 95%CI: 2.25–19.15), low dietary diversity score (AOR: 1.86; 95%CI: 1.05–3.27) and using unprotected water source (AOR: 1.78;95%CI: 1.03–3.05) Stunting predictors; age group 15–18 (AOR: 5.78; 95%CI: 3.20−10.40) and ever used substance (AOR: 3.01; 95%CI: 1.17–7.77).
Jikamo B, 2019 [62]	To assess the association between dietary diversity and nutritional status of adolescents	Cross sectional study (Data from the Jimma Longitudinal Family Survey of Youth (JLFSY)	Urban/rural	2084	13–17	M/F	Age, sex, household food insecurity, adolescent food insecurity DDS, workload	Stunting, thinness	Stunting 27.8% (boys 22%, girls 33.8%, Urban 26.5, Rural 28.3), Thinness 25.3% (urban 16.7%, 28.1%)) Stunning predictors: female sex (AOR = 2.0; 95% CI: 1.6, 2.4), household food insecurity (AOR = 1.7; 95% CI: 0.6, 0.9) Thinness predictor: Household food insecurity (AOR = 1.8; 95% CI: 0.6, 0.8), Rural residents (AOR = 1.6; 95% CI: 1.3, 2.2), Adolescent with higher workload (AOR = 2.6; 95% CI: 1.2, 3.1)
Tariku A, 2019. [57]	To assess the prevalence and associated factors of dietary diversity among adolescent girls.	cross-sectional study	Urban/rural	1550	10–19	F	-		Stunting 47.4% and thin 16.1%
Wolde T, 2019 [60]	To determine the prevalence of stunting and its impact on academic performance	Cross sectional study	Rural/urban	408 school adolescent	10–15	M/F	-	Stunting	Stunting 16.9%.
Zemene M, 2019 [59]	To assess the prevalence and its associated factors of nutritional status	Cross-sectional study	Urban/rural	327	10–19	M/F	Age, sex, residence, family size, water source		Stunting 15% (boys 10.6%, girls 19.2%, urban 11.7%, rural 21.1%). Thinness 4.9% (boys 3.1%, girls 6.6%, urban 2.1%, rural 9.6%). Stunting predictors: female sex (AOR = 2.2, 95% CI: 1.2, 4.4), rural residence (AOR = 2.5, 95%CI: 1.3, 4.8), and family size of ≥6 (AOR = 3.4, 95% CI:1.7, 7.1) Thinness predictors: Female sex (AOR = 1.8 95% CI: 0.5, 6.5), Rural residence (AOR = 3.7, 95% CI: 1.2, 11.6)
Berhe K, 2020 [64]	To assess the prevalence of undernutrition and associated factors among adolescent girls in Hawzen woreda, Northern Ethiopia	Cross sectional study	Urban/rural	398	10–19	F	Age, residence, parental occupation, parental education, frequency of dietary intake, family wealth	Stunting, underweight	Stunting 33.4% (urban 29.4%, rural 35.9%), Underweight 32.2% (urban 25.5%, rural 36.3%), Both stunted and underweight 8.8%. Underweight predictors: rural residence (AOR = 1.2; 95% CI: 0.3, 3.1), age 10–13 years (AOR = 0.6; 95% CI: 0.2, 1), unemployed father (AOR = 8.1; 95% CI: 0.5–12.5), unemployed mother (AOR = 2.4; 05% CI: 1.2, 3.6), father illiterate (AOR = 1.4; 95% CI: 1.1, 1.7) Stunting predictors: unemployed father (AOR = 3.2; 95% CI: 1.93–6.4), unemployed mother (AOR = 2.2, 95% CI: 1.1, 3.3), father illiterate (AOR = 1.6; 95% CI: 1.01, 2.2)
Gagebo D, 2020 [66]	To assess the prevalence of undernutrition and associated factors among adolescent girls	Cross-sectional study	Rural	719	10–19	F	Age, family size, parental occupation, parental education, family wealth and dietary frequency	Stunting and thinness	Stunting 29.6% (younger adolescent 25.7%, older 35.6%). Thinness 19.5% (younger adolescent 17.9%, older 21.8%). Stunting predictors: older adolescents (AOR = 2.1; 95% CI: 1.1, 3.9), farmer mother (AOR = 2.4; 95% CI: 1.3, 4.3) and employed mother (AOR = 3.1; 95% CI: 1.4, 6.9)), low household wealth index (AOR = 1.9; 95% CI: 1.3, 2.9), secondary maternal education ((AOR = 0.5; 95% CI: 0.3,0.9), and above secondary maternal education (AOR = 0.3; 95% CI: 0.1, 0.7)). Thinness predictors: father primary education ((AOR = 0.5; 95% CI: 0.3, 0.8) and fathers secondary education (AOR = 0.5; 95% CI: 0.3, 0.8), mother primary education (AOR = 0.6; 95% CI: 0.4, 0.9), adolescent having meal frequency (<2/day) (AOR = 1.9; 95% CI: 1.1, 3.1).
Kahssay M, 2020 [65]	To assess the nutritional status of adolescent girls and its associated factors	Cross-sectional study	Urban	348	10–19	F	Age, family size, dietary diversity, parental occupation,		Stunted 22.9%, thinness 8.8%. Stunting predictors: adolescent age 14–15 years (AOR = 1.4, 95% CI: 1.1–4.3), and dietary diversity score of <4 food groups (AOR = 2.2, 95% CI: 1.4–4.5). Thinness predictors: dietary diversity score of <4 food groups (AOR = 1.8, 95% CI: 1.1–4.4) and low food consumption (AOR = 3, 95% CI:1.2–7.9)
Taklual W, 2020 [93]	Aimed at assessing nutritional status and associated factors among female adolescents	school-based cross-sectional study	Urban	682	14–19	F	Age, family size, religion, ethnicity, parental occupation, parental education, family wealth, types of staple diet, diet diversity, menarche onset	Underweight, overweight, and obesity	Underweight 15%, overweight 8.4%, and obesity 4.7% Underweight predictors: Age groups of 14–16.5 years (AOR: 1.7, 95% CI: 1.03–2.69), family size ≥ 4 (AOR: 2.8, 95% CI: 1.05–4.99), participants who did not eat meat once per week (AOR: 1.6, 95% CI: 1.90–2.82), and no onset of menarche (AOR: 4.4, 95% CI: 1.21–15.75) Overweight predictors: family monthly income above 6500 ETB (AOR: 12.7, 95% CI: 2.47–65.62), consumption of meat two or more times per week (AOR: 2.07, 95% CI: 1.47–9.14), and consumption of fruit at least once a week (AOR: 0.20, 95% CI: 0.05–0.78)
Irenso A, 2020 [94]	To assess the magnitude and factors associated with adolescent linear growth and stunting	Cross-sectional	Urban/rural	2010	10–19	M/F	Age, sex, residence, hygiene,	Linear growth and stunting	Overall stunting 26.9% (Boys 30.7, girls 22.9; Urban 8.1%, Rural 47.9%. Significant interaction between residence and sex on the risk of stunting [AOR = 4.17 (95% CI 2.66, 9.9), P < 0.001], and height-for-age z score (HAZ) (b = 0.51, P < 0.001). In urban adolescents, older age (18 to 19 years) was negatively associated with linear growth (b = 0.29; P < 0.001). In rural setting, hand washing practice after toileting was positively associated with HAZ (0.62; P < 0.001) and with lower risk of stunting [AOR = 0.51 (95% CI 0.34, 0.76)]. Urban females had significantly higher HAZ than urban males [b = 0.52; P < 0.01)], and a significantly lower risk of stunting [AOR = 0.29 (95% CI 0.18, 0.48)].
Tamrat A, 2020 [95]	Aimed at determining the prevalence of stunting and its associated factors	school-based cross-sectional study	Urban	662	10–14	F	Age, religion, grade level, parental education, parental occupation, family size	Stunting	Stunting 27.5%. Stunting predictors: being grade 5 student [AOR; 95% CI: 1.90; 1.13–3.20], less than three meal a day [AOR; 95% CI: 2.37; 1.60–3.50], household food-insecurity [AOR; 95% CI: 2.52; 1.70–3.73]. Stunting preventive factors: Government employed mothers [AOR; 95% CI: 0.48; 0.26–0.89] or merchants [AOR; 95% CI: 0.43; 0.28–0.67]
Andargie M, 2020 [96]	to assess the magnitude and associated factors of overweight and obesity among public and private secondary school adolescents in Mekelle city	school-based comparative cross-sectional between private and public school adolescents	Urban	858	14–19	M/F	Age, type of school, religion, family size, birth order, grade level, physical activity, food frequency, type of transport to school, nutrition knowledge, parental occupation, parental education, parental wealth	Overweight and obesity	Overall overweight and obesity 7.8% (boys 5.9(, girls 9.8%, private school 11.8% and public schools 3.9%) Overweight/obesity predictors: Consuming dinner not daily [AOR = 5.3:95% CI = 1.93–14.6] and working moderate-intensity sports at least 10 minutes/day continuously [AOR = 0.19:95% CI = 0.04–0.9] were associated factors of overweight and obesity in public school adolescent students. Being female [AOR = 2.03:95% CI = 1.08–3.8], time taken from home to public physical activities ≤ 15 minutes [AOR = 3.6:95% CI = 1.13–11.51], using transport from school to home [AOR = 2.2:95% CI = 1.06–4.18] and good knowledgeable adolescents [AOR = 0.5:95% CI = 0.27–0.9] were associated factors of overweight and obesity in private schools.
Sisay B, 2020 [89]	To evaluate the performance of MUAC to identify overweight (including obesity) in the late adolescence period	Cross-sectional study	Urban	851	15–19	M/F	-		Overweight 11.2% (95% CI; 9.2–13.5%), Obesity 3.3% (95% CI; 2.3–4.7%) BMI Z score 0.44 (±1.2)
Worku M, 2021 [97]	To assess the prevalence and associated factors of overweight and obesity	nstitution-based cross-sectional study	Urban	551	10–19	M/F	Age, sex, school type, DDS, religion, parents occupation, family wealth status	overweight and obesity	Mixed overweight and obesity 12.5% (Boys 13.3%, Girls 11.5%) Overweight/obesity predictors: Having self-employed mothers (AOR: 4.57; 95% CI: 1.06, 19.78), having government-employed mothers (AOR: 6.49; 95% CI: 1.96, 21.54), and having school feeding access (AOR: 0.44; 95% CI: 0.26, 0.76)
Kebede D, 2021 [98]	To assess the prevalence and associated factors of stunting and thinness	school-based cross-sectional study	Urban	397	10–19	M/F	Age, sex, family wealth, grade, place of residence, religion, parental education, parental occupation, family size, DDS	Stunting and thinness among	Stunting 21.8% (Boys 26.8%, girls 20.5%) & thinness 16.9% (Boys 22.1%, girls 2.7%) Stunting predictors: having a family monthly income of less than $28.37 (P = 0.044) and having less than four dietary diversity (P = 0.021) Thinness predictors: Early adolescent age, being male, having a family monthly income of less than $28.37, having a family monthly income between $28.37 and $56.74 (P = 0.021) (35.25 Birr = 1 USD) and using clean water (P = 0.045)
Alemu T, 2021 [99]	Aimed at comparing the rural and urban prevalence’s ofstunting and thinness and their associated factors	ommunity-based comparative cross-sectional study	Urban/Rural	792	10–19	F	Age, educational status, residence, parental occupation, parental education, famlily sixe, family wealth, religion	Stunting and thinness	Stunting 20.1% (Urban 16%, Rural 24.2%), Thinness 10.3% (Urban 12.1%, rural 8.5%) Stunting predictors: Food insecurity [AOR: 1.95 (95% CI: 1.01, 3.78)] Stunting predictors in urban settings: early age adolescent [AOR:3.17 (95% CI:1.445,6.95)] Stunting predicators rural settings: lack of latrine [AOR: 1.95 (95% CI: 1.11, 3.43)], lowest media exposure [AOR: 5.14 (95% CI: 1.16, 22.74)], lower wealth class [AOR:2.58 (95% CI: 1.310, 5.091)], and middle wealth class[AOR: 2.37 (95% CI: 1.230, 4.554)] Thinness predictors Rural settings: Middle age adolescent groups [AOR: 3.67 (95% CI: 1.21, 11.149)]. Thinness predictors Urban setting: early age adolescent [AOR: 8.39 (95% CI: 2.48–28.30)].
Handiso Y, 2021 [100]	To assess the nutritional status and associated factors among adolescent	community-based cross-sectional study	Rural	843	10–19	F	Age, religion, school grade, family size, family income nutrition edutaion, dewarming, nutrtion service receved,	Thinness, stunting	Stunting 8.8%, Thinness 27.5%, Predictors of thinness: [AOR; 95% CI = 2.91; 2.03–4.173], large family size [AOR; 95% CI = 1.6; 1.11–2. 40], low monthly income [AOR; 95% CI = 2.54; 1.66–3. 87], not taking deworming tablets [AOR; 95% CI = 1.56;1.11–21], low educational status of the father [AOR; 95% CI 2.45; 1.02–5.86], source of food only from market [AOR; 95% CI = 5.14; 2.1–12.8], Predictors of stunting: lack of service from health extension workers [AOR; 95% CI = 1.72; 1.7–2.4], and not washing hand with soap before eating and after using the toilet [AOR; 95% CI = 2.25, 1.079–4.675]
Hadush G, 2021 [101]	to assess prevalence of nutritional status and associated factors among adolescent girls	school-based cross-sectional study	Rural	736	10–19	F	Age, family size, parents occupational status, parents educational status, family wealth status, household food insecurity	Thinness and stunting	Stunting 26.6%, Thinness 15.8%, Stunting predictors: being at an early adolescent age (AOR = 1.96, 95% CI 1.02–3.74), household food insecure (AOR = 2.88, 95% CI 1.15–7.21), menstruation status (AOR = 2.42, 95% CI 1.03–5.71), and availability of home latrine (AOR = 3.26, 95% CI 1.15–4.42). Thinness predictors: early age adolescent (AOR = 2.89, 95% CI 1.23–6.81)
Kebede WA, 2021 [102]	aimed at assessing the magnitude of stunting and associated factors among adolescent students	School survey	Urban/rural	424	14–19	M/F	Age, sex, religion, residence, family economy, parental education, grade level, water and sanitation,	Stunting	Stunting 24.9% (Boys 33%, girls 16.5%) Stunting predictors: male sex [AOR  =  2.1; 95% CI: 1.73–5.90], meal frequency (<3/day) [AOR  =  4.6; 95% CI: 2.61–8.24], infrequent hand washing practice [AOR  =  3.6; 95% CI: 1.30–9.40], absence of latrine facility (AOR  =  5.51; 95% CI: 3.03–9.9), and consumption of unsafe water [AOR  =  2.8; 95% CI: 1.35–6.19].
Birru GM, 2021 [103]	to assess malnutrition and the associated factors among adolescents	School survey	Urban	365	14–19	M/F	Age, sex, parental marital status, DDS, food frequency, diet quality, mother occupation, snack intake	Stunting, underweight,/thinnessoverweight/obesity	Stunted 15.7%, Underweight 6.3%, and overweight/obesity 8.2%. Stunting predictor: Daily snack intake (AOR = 0.38, 95% CI: 0.20, 0.71), and inadequate diet quality (AOR = 3.36, 95% CI: 1.15, 7.82) underweight/thin: Being a male (AOR = 2.76, 95% CI: 1.03, 7.44) and meal consumption <3 times/day (AOR = 4.21, 95% CI: 1.35, 13.11) Overweight/Obesity: Dietary diversity score<5 (AOR = 0.35, 95% CI: 0.13, 0.89)
Kedir S, 2022 [104]	Aimed at identifying context-specific determinants of overweight and/or obesity among adolescents	School-based unmatched case-control study design	Urban	297	10–19	M/F	Sex, Age, wealth, soft drinks consumption, physically activity, screen time, nutritional knowledge, family size, parental education, diet diversity, fast food consumption	Overweight/ obesity.	High socioeconomic status [AOR = 5.8, 95% CI (2.66, 12.5)], consumed soft drinks 3and more times per week [AOR = 3.7, 95% CI (1.8, 7.3)], physically inactive [AOR = 4.4 95% CI (1.68, 11.6)], spent free time by watching television/ movies for 3and above hours per day [AOR = 8.6, 95% CI (4.3, 17)] and with poor nutritional knowledge [AOR = 3.4, 95%CI (1.7, 6.9)] were significantly associated with overweight/ obesity.
Tafasa, S.M. 2022 [105]	to assess the prevalence of undernutrition and its associated factors among school adolescent girls	School based study	Urban/rural	587	10–19	F	Age, religion, place f residence, family marital status, educational level parental education, family size, physical activity, DDS, food frequency, water source, nutrition knowledge, illness episodes, menstruation	Stunting and thinness	Stunting 15.4%; thinness 14.2%, Stunting predictors: Less than 3 meal/day [AOR  =  3.62, 95% C.I (2.16, 6.05)], attending lower grades [AOR  =  2.08, 95% C.I (1.07, 4.04)] and did not started menstruation [AOR  =  1.71, 95% C.I (1.06, 2.73)] Thinness predictors: vigorous physical activities [AOR  =  2.51, 95% C.I (1.14, 5.54)], low dietary diversity score [AOR  =  4.05, 95% C.I (1.43, 11.46)] and younger adolescent (10–14 yrs) [AOR  =  3.77, 95% C.I (1.06, 13.37)]
Belay M, 2022 [106]	To determine the magnitude of overnutrition and associated factors among school adolescents in Diredawa city	School based survey	Urban	498	10–19	M/F	Age, sex, meal preference, type of school, snack intake, physical activity, parental education, parental occupation, household wealth status	Overnutrition	Overnutrition of 26.1% (boys 13.5%, girls 36.8%); Overweight 23.7% and Obesity 2.4% Overnutrition Predictors: Being female (AOR = 3.32; 95% CI: 1.65–6.63), attending at private school (AOR = 4.97; 95% CI: 1.72–14.35), having sweet food preferences (AOR = 6.26; 95% CI: 3.14–12.5), snacking (AOR = 3.05; 95% CI: 1.11–8.36), sedentary behavior (AOR = 3.20; 95% CI: 1.67–6.09), and eating while watching TV (AOR = 2.95; 95% CI: 1.47–5.95)