Schneider, Bruna Celestino; Dumith, Samuel Carvalho; Orlandi, Silvana Paiva; Assunção, Maria Cecília Formoso

doi:10.1590/1413-81232017225.13972015

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REVIEW • Ciênc. saúde colet. 22 (5) • Maio 2017 • https://doi.org/10.1590/1413-81232017225.13972015 copiar

Dieta e gordura corporal na adolescência e início da vida adulta: uma revisão sistemática de estudos longitudinais

Autoria SCIMAGO INSTITUTIONS RANKINGS

Resumo

O tecido adiposo é um componente vital do corpo humano, mas em excesso representa risco à saúde. Conforme a Organização Mundial da Saúde, um dos principais fatores determinantes do excesso de peso é o hábito alimentar. Essa revisão sistemática investigou estudos longitudinais que avaliaram a relação entre dieta e gordura corporal em adolescentes e adultos jovens. Vinte e um artigos publicados de 2001 a 2015 foram selecionados. O método mais utilizado para estimar gordura corporal foi o índice de massa corporal (15 estudos). A dieta foi avaliada principalmente pelo consumo de grupos alimentares (cereais, leite e produtos lácteos) e alimentos específicos (bebidas açucaradas, refrigerantes, “fast foods”, leite e etc.). Dez estudos encontraram uma associação direta entre dieta e quantidade de gordura corporal. Um padrão alimentar com alto consumo energético e de gordura e baixo de fibras e o hábito de consumir “fast foods”, bebidas açucaradas e refrigerantes na adolescência, contribuíram para um aumento da gordura corporal no início da vida adulta. Os achados deste estudo sugerem que o consumo de alimentos específicos e grupos de alimentos não saudáveis (alta densidade energética e baixo conteúdo de nutrientes) na adolescência e início da vida adulta estão associados com maior quantidade de gordura corporal.

Dieta; Gordura corporal; Adolescente; Adulto jovem

Author, Year Country	Sample	Exposure	Outcome	Main findings
Bigornia et al., 2014 U.S.A	- N: 2,455; - Age: 10 years (baseline) followed until 13 years; Participants of the Avon Longitudinal Study of Parents and Children (ALSPAC).	- Diet: dairy consumption (total, full, and reduced fat) in grams/day; - Instrument: 3 days food records;	- Body Mass Index (BMI): Weight (kg)/height (m)² studied like overweight (25 kg/m2) and obese (30 kg/m2); - Excess adiposity: top 20% of Total Body Fat Mass in kg (TBFM) measure by dual-energy X-ray absorptiometry and adjusted for age, height and sex; Analyzed at 13 years of age.	The highest vs. lowest quartile of total dairy consumers at 10 years did not have an increased risk of excess TBFM and BMI at 13 years; Adjustments for age 10 y, gender, height at 10 y, total dairy at 13 y, adiposity at 10 y, maternal education, maternal overweight status, physical activity at 13 y, pubertal stage at 13 y, dieting at 13 y, age-10-y intakes of fruit juice, fruit and vegetables, total fat, total protein, sugar-sweetened beverages, fiber, and cereal, dietary reporting errors at 13 y and total dairy intakes.
Assmann et al., 2013 Germany	- N: 140 female and 122 male; - Age: girls 9-14 years and boys 10-15 years in baseline and followed in young adulthood (18-25 years); - Participants of the DONALD Study.	- Diet: habitual animal and plant protein intake; - Instruments: 3-day weighed food records; Dietary variables were presented energy-adjusted tertiles of intake.	- Fat Mass Index (FMI): percentage body fat (%BF) * body mass) /100. To estimate %BF was use from triceps, biceps, scapular and iliac skinfolds using Durnin and Womersley equations; Analyzed at in young adulthood.	In men, a higher animal protein intake was related to lower FMI (3.4 kg/m; 95% CI 3.0-3.8; ptrend = 0.001); The plant protein intake was not associated with FMI among either sex; Adjustments for free fat mass index (FFMI) in adulthood, FMI at baseline, breast feeding, birth weight, maternal overweight, maternal education, status, glycemic index, intakes of fiber, calcium and energy.
Gopinath et al., 2013 Australia	- N: 856; - Age: 12 at baseline and followed for 5 years.	- Diet: glycemic index (GI), glycemic load (GL) of diets and intakes of carbohydrate, sugars, fiber and the main carbohydrate containing food groups (vegetables, fruits, cereals and soft drinks); Measured at 12 years; - Instrument: semi quantitative FFQ.	- Body Fat Percentage (%BF): bioimpedance analysis; - BMI: Weight (kg)/height (m)²; Measured at 17 years;	In girls, each 1SD increase in dietary GL was associated with a concurrent 0.77 kg/m2 increase in BMI (p < 0.01), and each 1SD increase in dietary fiber intake was associated with a concurrent 0.44 kg/m2 decrease (p < 0.02); In girls, soft drinks consumption 1 or more time per day vs. never/rarely consumed, had a 4.5% increase in %BF after 5 years (p < 0.01). Adjustments for age, ethnicity, parental education, passive smoking, change in energy intake and height, screen viewing time and physical activity.
Ambrosini et al., 2012 United Kingdom	- N: 6,772; - Age: 7 years old (baseline) followed until 15 years old; - Participants of the Avon Longitudinal Study of Parents and Children (ALSPAC).	- Diet: an energy-dense, high-fat and low-fiber Dietary Pattern (DP) designed by principal component analysis (PCA); - Instruments: Food record of 2 weekdays and 1 weekend day completed by the 7, 11 and 13-year-old participants; DPs were presented in z-scores and quintiles;	- Fat Mass Index (FMI): (FM(kg) / Height(m))^x, in which x = log FM/log height and varies according to gender and age. FMI was log-transformed to obtain normal distributions, standardized to a z-score and divided in quintiles. Individuals in the top quintile of FMI z-scores were classified as having “excess adiposity”. Analyzed at 11, 13 and 15 years of age.	Positive association between DP z-scores at 13 years and FMI at 15 years. A 1 SD unit increase in DP z-score was associated with an increase in FMI z-score of 0.03 SD units (95% confidence interval (CI), 0.01–0.05). Adjustments for gender, age of evaluation, dietary misreporting, physical activity at 11 years. The association had no appreciable effect. With each 1SD unit increase in DP z-score, the odds of excess of adiposity increased by 0.13 (CI95% 0.01–0.27). Adjustment for pubertal development + maternal education and pregnancy BMI.
Fraser et al., 2012 United Kingdom	- N: 14,610; - Age: 13 years followed until 15 years; - Participants of the ALSPAC.	- Diet: fast foods; - Instruments: Food Frequency Questionnaire (FFQ); Analysed at 13 years of age.	- BMI: Weight (kg)/height (m)²; - %BF: verified with Dual energy x-ray absorptiometry (DEXA); Analyzed at 13 and 15 years of age.	The consumption of fast food was associated with a higher BMI SD score (β = 0.08, 95% CI = 0.03, 0.14); higher %BF (β = 2.06, 95% CI = 1.33, 2.79); and increased odds of being obese (OR = 1.23, 95% CI = 1.02, 1.49). Adjustment for gender, physical activity and food consumption.
Laska et al., 2012 U.S.A.	- N: 693; - Age: average of 14.6 years of age. Followed for 2 years; - Participants of the Identifying Determinants of Eating and Activity (IDEA) and Etiology of Childhood Obesity (ECHO).	- Diet: sugar-sweetened beverage, diet soda, breakfast and fast food; - Instruments: 24h dietary recalls and questions about food consumption from the previous month; Consumption measured at baseline.	- BMI: Weight (kg)/height (m)²; - %BF: Bioelectrical Impedance; Body composition measured in a follow-up assessment, 24 month after baseline.	There was no statistically significant association between the consumption of sugar-sweetened beverage, diet soda, fast food, and breakfast and BMI and %BF; Adjustment for physical activity, pubertal development, socioeconomic status, race/ethnicity, parents education, age and total energy intake.
Feeley et al., 2012 South Africa	- N: 1,298; - Age: 13 (baseline), 15 and 17 years; - Participants Birth to twenty (Bt20) study.	- Diet: snacking while watching television, fast-food consumption, confectionery consumption and sweetened beverage consumption, etc.; Instruments: unquantified FFQ; Measured at 13. 15 and 17 years.	- BMI: Weight (kg)/height (m)²; - Fat Mass (kg): dual-energy X-ray absorptiometry; Measured at 17 years.	In males, the sweetened beverage consumption > 2times/week at 13 years was positively associated with both BMI Z-score (β = 0.04 95%CI 0.022-0.067; p < 0.001) and fat mass (β = 0.02 95%CI 0.002-0.04; p < 0.01) at 17 years; Adjustment for change in socio-economic status between birth and age 12 years.
Lin et al., 2012 China	- N: 5,968; - Age: 11 years (baseline). Followed again at 13 years of age; - Participants of the Hong Kong 1997 Birth Cohort.	- Diet: Consumption of milk and dairy products; - Instruments: FFQ; Consumption measured at 11 and 13 years of age.	- BMI: Weight (kg)/height (m)² standardized to a z-score; Measured at 11 and 13 years of age.	There was no association between the consumption of milk and/or dairy products at 11 years of age and BMI at 13; Adjustment for gender, BMI at 11 years, order of birth, maternal age, parents education, family income, physical activity, consumption of vegetables, fruit and soft drinks.
Stoof et al., 2011 Netherlands	- N: 114 males and 124 females; - Age: 13 years at baseline and followed until 24-30 years; - Participants of Amsterdam Growth and Health Longitudinal Study (AGAHLS).	Diet: intake of sugar-containing beverages (SCB) divided into two categories: total SCB and SCB excluding 100% fruit juices; - Instruments: dietary history; Consumption measured at 13 years.	- %Total Fat and %Trunk Fat, obtained through dual-energy X-ray absorptiometry; - BMI: 25 kg/m² and obesity as 30 kg/m²; Measured at 24-30 years of age.	Intake of SCB excluding 100% fruit juices at 13 years was not related to BMI in adulthood; Intake of total SCB at 13 years was not related to %total fat, %trunk fat and BMI in adulthood; In males, each additional daily serving of SCB excluding 100% fruit juices at 13 years was associated with 1.14% higher %total fat (95% CI 0.04, 2.23%) and 1.62% higher %trunk fat (95% CI 0.14, 3.10%) in adulthood; Adjusted for BMI at baseline, developmental age, physical activity level and total energy intake.
Noel et al., 2011 U.S.A.	- N: 2,245; -Age: 10 years and followed until 13 years; - Participants of the Avon Longitudinal Study of Parents and Children (ALSPAC).	- Diet: types of milk (total, full fat and reduced fat); - Instruments: food records of 3 days; - Consumption measured at 10 and 13 years.	- %BF: verified with DEXA; Measured at 10 and 13 years.	Total milk intake at 10 years was associated with %BF at 11 (p = 0.01), the association remained after additional adjustment for total energy intake (p = 0.03); Total milk intake at 10 years was not associated with %BF at 13 years; Full-fat and reduced-fat milk at 10 years was not related to %BF at 11 and 13 years; Adjustment for age, gender, height, physical activity, pubertal development, maternal BMI, maternal education, intake of total fat, sugar-sweetened beverages, consumption of fruit, ready-to-eat cereals and baseline BMI.
Libuda et al., 2011 Germany	- N: 364; - Age: 3 to 18 years (baseline) and followed for 5 years; - Participants of the Dortmund Nutritional Anthropometric Longitudinally Designed Study (DONALD study).	- Diet: Salt intake; - Instruments: 3 food records with weighting; Urinary samples were collected to analyze amount of sodium excreted; Salt intake and urinary samples were analyzed at baseline and 5 years afterwards.	- BMI: Weight (kg)/height (m)² standardized to a z-score; - %BF: verified by triceps and subscapular skinfolds; Measured at baseline (3 to 18 years of age) and the last visit (5 years afterwards).	There was no significant association between the alterations in the urinary excretion of sodium and the changes in BMI and/or the %BF; Adjustment for age, parents BMI, energy and sugar-sweetened beverages intake at baseline.
Cutler et al., 2011 U.S.A.	- N: 2,516; - Average age: 15 years. Followed until 20 years of age; - Participants of the Project Eating Among Teens (EAT).	- Diet: DP obtained by Principal Component Analysis (PCA); - Instruments: self-assessed semi quantitative FFQ validated by 152 food items; DP identified at 15 years of age and afterwards at 20.	- BMI: Weight (kg)/height (m)²; Measured at 15 and at 20 years.	Boys with high adherence to DPs loading heavily on starchy food were 30% less likely to be overweight (p < 0.05); Adjustment for race/ethnicity, socioeconomic status, physical activity, weight at 15 years.
Albertson et al., 2009 U.S.A.	- N: 2,379 girls; - Age: Average of 11.5 years and followed until 18.5 years; - Participants of the National Heart, Lung, and Blood Institute Growth and Health Study.	- Diet: Cereal intake; - Instruments: 24h dietary recalls and FFQ; Verified at 13.5, 15.5, 16.5 and 18.5 years of age.	- %BF: Bioelectrical Impedance; Measured at 18.5 years of age.	Regular cereal intake during the beginning of adolescence is associated with a significant lower %BF (-0.04 ± 0.01 p = 0.01); Adjustment to the region of the study, maternal education and physical activity at baseline.
Cheng et al., 2009 Finland	- N: 396 girls; - Age: 10 to 13 years (baseline) and followed for 7 years.	- Diet: Dietary intake index (protein, calcium, potassium, phosphorus, and magnesium); - Instruments: Food records of 3 days (2 weekdays and 1 weekend day); Measured at baseline	- %BF: verified with DEXA; Measured from 17 to 20 years of age.	In a linear model, the dietary intake index at baseline was related to 25% of the changes in the %BF 7 years afterwards; The highest dietary intake index at baseline predicted a lower %BF (12%); Adjustment for menarche age, physical activity, parents education and maternal body composition.
Fulton et al., 2009 U.S.A.	- N: 472; - Age: 11 to 14 years (baseline). Followed for 4 years; Participants of the Heart Beat Project.	- Diet: Energy intake; - Instruments: FFQ (regarding the intake from the previous week); Measured at baseline.	- BMI: Weight (kg)/height (m)2; - %BF: Bioelectrical Impedance; Measured after 4 years.	There was no relation between the energy intake and the %BF and BMI; Adjustment for gender, race/ethnicity, age and pubertal development.
Libuda et al., 2008 Germany	- N: 244; - Age: 9 to 18 years and followed for 5 years; - Participants of the Dortmund Nutritional Anthropometric Longitudinally Designed Study (DONALD study).	- Diet: Beverage intakes: regular soft drink, diet soda, and sugar-sweetened beverages; - Instruments: Food record of 3 consecutive days with beverages weighting; Measured at 9-18 years of age and 5 years afterwards.	- BMI: Weight (kg)/height (m)² standardized to a z-score; - %BF: verified by triceps and subscapular skinfolds; Measured at baseline (9-18 years of age) and at the final visit (5 years afterwards).	In girls, the consumption of regular soft drinks and sugar-sweetened beverages at 9-18 years of age was related to an increase in the z-score of BMI (β = 0.070 p = 0.01 and β = 0.096 p = 0.01, respectively) 5 years afterwards. Adjustment for age, residual energy at baseline, changes in residual energy, birth weight, maternal BMI.
Ritchie et al., 2007 U.S.A.	- N: 2371 girls; - Age: 9-10 years followed until 19-20 years of age; - Participants of the National Heart, Lung, and Blood Institute Growth and Health Study cohort.	- Diet: DP obtained by Cluster analysis (habitual DP, snacks DP, meals DP, and sweets and cheese DP); - Instruments: Food record of 3 days (2 weekdays and 1 weekend day); DP measured at baseline.	- BMI: Weight (kg)/height (m)²; - %BF: verified by triceps and subscapular skinfolds; Measured at baseline and 10 years afterwards.	The average of BMI and %BF at 19-20 years of age was not significantly different between the DPs at baseline; Adjustment for BMI, menarche age, pregnancy, parents education, physical activity, and TV time at baseline.
Mundt et al., 2006 Australia	- N: 208; - Age: 8 to 15 at baseline and followed for 7 years; Participants of the University of Saskatchewan’s Pediatric Bone Mineral Accrual Study (PBMAS).	- Diet: Sugar-sweetened intake; - Instruments: 24h dietary recalls; Consumption verified during the first 3 years of monitoring.	- %BF: verified with DEXA; Annually measured during the 7 years of monitoring.	There was no significant relation between the consumption of sugar-sweetened beverages and %BF in girls and boys. (p > 0.05); Adjustment for pubertal development, lean body mass, total dietary energy intake.
Berkey et al., 2005 U.S.A.	- N: 6,149 girls e 4,620 boys; - Age: 9 to 14 (baseline). Followed for 4 years; - Participants of the Growing Up Today Study.	- Diet: milk, calcium, foods and drinks dairy and fat; - Instruments: Semi quantitative FFQ consisting of 132 food items with a recording period of 1 year; Annually measured during the 4 years of monitoring.	- BMI: Weight (kg)/height (m)². Measured at baseline and annually assessed during the 4 years of monitoring.	A 150-kcal/d increase in total energy from the prior year predicted a BMI gain for boys (0.012 Kg/m² p = 0.003) and for girls (0.008 Kg/m² p = 0.03); And there was no association statistically significant adjustment for dairy fat, dietary calcium, milk intake and total energy intake.
Phillips et al., 2003 U.S.A.	- N: 196 girls; - Age: average of 10 years (baseline). Followed until the average of 17 years of age.	- Diet: dairy products (foods and calcium); - Instruments: semi quantitative FFQ consisting of 116 food items; Consumption assessed at baseline.	- %BF: Bioelectrical Impedance; - BMI: Weight (kg)/height (m)² standardized to a z-score; Measured at 17 years of age.	There was no statistically significant connection between the consumption of dairy products and BMI; There were no relevant associations between the daily consumption of portions of dairy products or percentage of daily calories from dairy products and %BF; Adjustment for physical activity, percentage of energy from proteins, grams of proteins, total energy intake and parents overweight.
Magarey et al., 2001 Australia	- N: 243; - Age: 2 to 15 years; - Participants of a birth cohort from the South of Australia.	- Diet: macronutrients (fat, protein and carbohydrate); - Instruments: Food record of 3 days with food weighting at 2, 4 and 6 years of age and Food diary of 4 days at 8, 11, 13 and 15 years of age.	- BMI: Weight (kg)/height (m)² - Were verified triceps (TS) and subscapular (SS) skinfolds; Measurements converted to z-score and assessed at 2, 4, 5, 6, 7, 8, 11, 13, and 15 years.	There was no difference between z-score BMI, SS and TS according to the consumption of macronutrients; Macronutrients intake at 11 or at 13 years of age does not predict the %BF at 15; Adjustment for energy intake.

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[1] Collaborations

BC Schneider performed the search and selection of the articles and drafted the manuscript. SC Dumith helped to select articles and reviewed the manuscript. SV Orlandi contributed to the search and selection of articles. MCF Assunção was responsible for the study and helped to draft the manuscript. All authors read and approved the final manuscript.