Dietary Intake and Arterial Stiffness in Children and Adolescents: A Systematic Review
Abstract
:1. Introduction
2. Materials and Methods
2.1. Literature Search
2.2. Eligibility Criteria
2.3. Data Management and Extraction
2.4. Quality Assessment
2.5. Data Synthesis
3. Results
3.1. Study Selection
3.2. Characteristics of Included Studies
3.3. Quality Assessment
3.4. Findings from Intervention Studies
3.4.1. Vitamin D Supplementation
3.4.2. Omega-3 Fatty Acid Supplementation
3.4.3. Milk Protein Supplementation
3.5. Findings from Observational Studies
3.5.1. Prospective Cohort Studies
3.5.2. Cross-Sectional Studies
3.5.3. Infant Feeding Practices
Prospective Cohort Studies
Cross-Sectional Studies
3.5.4. Dietary Patterns
Prospective Cohort Studies
Cross-Sectional Studies
3.5.5. Consumption of Specific Food Groups
Cross-Sectional Studies
3.5.6. Macronutrient Intake
Prospective Cohort Studies
Cross-Sectional Studies
3.5.7. Sodium Intake
Cross-Sectional Studies
4. Discussion
4.1. Intervention Studies
4.2. Observatoinal Studies
4.3. Clinical Implications and Future Research
4.4. Strength and Limitations
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Characteristic | No. of Studies |
---|---|
Study design | |
Intervention | 6 |
Prospective cohort | 4 |
Cross-sectional | 9 |
Dietary exposure | |
Supplemental vitamin D | 3 |
Supplemental omega-3 fatty acids | 2 |
Supplemental milk proteins | 2 |
Infant feeding practices | 3 |
Dietary patterns | 6 |
Macronutrient intake | 2 |
Consumption of specific food groups | 3 |
Sodium | 1 |
Outcome: index of arterial stiffness | |
PWV | 18 |
Cf-PWV | 17 |
Carotid-radial PWV | 3 |
Carotid-distal PWV | 1 |
Radial-distal PWV | 1 |
Carotid-dorsalis-pedis (foot) PWV | 1 |
Brachial PWV | 1 |
AIx | 7 |
Arterial-AIx | 5 |
Radial-AIx | 2 |
Carotid arterial distensibility | 1 |
Brachial artery distensibility | 1 |
Citation | Study Design | Location and Name of Study (If Any) | Sample 1 | Age (Mean (SD) Unless Stated) | % Male | Weight Status or If Not Reported, BMI | Index of Arterial Stiffness | Diet Component |
---|---|---|---|---|---|---|---|---|
Arnberg et al., 2013 [24] | Parallel RCT | Copenhagen, Denmark | n = 173 Aged 12–15 years, overweight or with obesity, consuming ≤250 mL/d milk and yoghurt, recruited via Civil Registration System | Males: 13.2 (0.7) years Females: 13.2 (0.7) years | 38% | Median BMI 25.0 kg/m2 | Cf-PWV Radial AIx (Applanation tonometry, SphygmoCor System, AtCor Medical) | Milk, e.g., skimmed milk (casein: whey ratio of 80:20) and milk proteins, e.g., whey-based drink (casein: whey ratio of 0:100) and casein-based drink (casein: whey ratio of 100:0) All drinks contained 35 g/100 g total protein |
Rajakumar et al., 2020 [19] | Parallel RCT | Pittsburgh, Pennsylvania, US | n = 225 Aged 10–18 years, overweight or with obesity, with vitamin D deficiency (serum 25(OH)D < 20 ng/mL), recruited from primary care centre of children’s hospital and advertisements on paediatric research network | 13.6 (2.3) years | 35% | Overweight 33.3% Obese 66.7% | Cf-PWV Aortic AIx-75 (Arterial tonometry, SphygmoCor CVMS V9 CPVH System, AtCor Medical) | Supplemental vitamin D3 |
Varshney et al., 2019 [25] | Parallel RCT | India | n = 189 Aged 11–17 years with obesity, recruited from endocrinology clinic for management of obesity | Intervention: 12.9 (1.6) years Control: 13.2 (1.5) years | 64% | Obese 100% | Cf-PWV Carotid-radial PWV Carotid-distal PWV Radial-distal PWV (Applanation tonometry, SphygmoCor, AtCor Medical) | Supplemental vitamin D |
Dong et al., 2010 [23] | Parallel RCT | Richmond County, Augusta, Georgia, US | n = 35 Aged 14–18 years, apparently healthy African-American adolescents recruited from high schools | Intervention: 16.5 (1.4) y Control: 16.3 (1.1) years | Intervention: 44% Control: 71% | Mean (SD) BMI percentile: Experimental: 67.8 (SD 30.9) Control: 61.6 (33.4) | Cf-PWV Carotid-radial PWV Carotid-dorsalis-pedis (foot) PWV (Applanation tonometry, Millar Instruments with SphygmoCor software, AtCor Medical) | Supplemental vitamin D3 |
Dangardt et al., 2010 [26] | Randomized Cross-over trial | Sweden | n = 25 Aged 14–17 years with obesity, referred to outpatient clinic for obesity treatment | 15.7 (1.0) years | 44% | Obese 100% | Carotid-radial PWV (Applanation tonometry, SphygmoCor, AtCor Medical) AIx (Arterial tonometry, Endo-PAT, Itamar Medical Ltd.) | Supplemental omega-3 fatty acid |
Ayer et al., 2009 [27] | 3-y follow-up of 5-y parallel RCT | Sydney, Australia Childhood Asthma Prevention Study (CAPS) | n = 386 Aged 8 years, previously enrolled in 5-years RCT at birth | Intervention: 8.0 (0.1) years Control: 8.0 (0.1) years | Intervention: 50% Control: 52% | Intervention: 17.8 (SD) 3.3 kg/m2 Control: 17.4 (2.8) kg/m2 | Brachial PWV (Electrocardiogram-gated left carotid and radial waveforms) (n = 276) Radial AIx-75 Carotid AIx-75 (Applanation tonometry, SPC-301 Millar Instruments with SphygmoCor, AtCor Medical) Carotid arterial distensibility (ultrasound) | ≈1:5 ratio of omega-3 to omega-6 fatty acids via supplements and spreads |
Citation | Study Design | Location and Name of Study (If Any) | Sample 1 | Age (Mean (SD) Unless Stated) | % Male | Weight Status or If Not Reported, BMI | Index of Arterial Stiffness | Diet Component |
---|---|---|---|---|---|---|---|---|
Prospective cohort studies | ||||||||
Schack-Nielsen et al., 2005 [28] | Prospective cohort 10 y follow-up (birth to age 10 year) | Copenhagen, Denmark Copenhagen Cohort Study on Infant Nutrition and Growth | n = 93 Aged 10 years, recruited from birth cohort study | 10.0 (0.1) year | 47% | Males Underweight or healthy 90.9% Overweight 9.1% Females Underweight or healthy 91.8% Overweight 8.2% | Cf-PWV Carotid-radial PWV (Optical method, ECG and infrared transducer with Pulse Analysis version 97.1.1 software) | Duration of breastfeeding, current % energy from total fat |
de Jonge et al., 2013 [29] | Prospective cohort 6 y follow-up (birth to age 6 years) | Rotterdam, The Netherlands Generation R Study | n = 4024 Aged 6 years, mothers enrolled in birth cohort study during prenatal care visit | Ever breastfed: median 6.0 (95% range 5.6–7.4) years Never breastfed: 6.0 (5.6–7.2) years | Ever breastfed: 50% Never breastfed: 49% | Not reported | Cf-PWV (automatic Complior SP device, Artech Medical) | Ever breastfed, breastfeeding duration, breastfeeding exclusivity, age at introduction of solids |
Kerr et al., 2018 [18] | Prospective cohort 9 year follow-up (ages 4 y to 15 years) | Melbourne, Australia Parent Education and Support (PEAS) Kids Growth Study | n = 188 Aged 15 year, first-born children, parents recruited during routine appointments with Maternal and Child Health Nurses | 15.1 (0.5) years | 48% | Mean (SD) BMI z-score 0.4 (0.9) | Cf-PWV (Applanation tonometry, SphygmoCor XCEL, AtCor Medical) | 4 empirically derived trajectories of dietary patterns |
Van den Hooven et al., 2013 [30] | Prospective cohort 5 y follow-up (ages 14 m to 6 years) | Rotterdam, The Netherlands Generation R Study | n = 2427 Aged 6 years, mothers enrolled in population-based prospective cohort study | Median 5.9 (95% range 5.6–6.6) years | 46% | 16.0 (1.6) kg/m2 | Cf-PWV (automatic Complior SP device, Artech Medical) | Macronutrient intake (total and type) |
Cross-sectional studies | ||||||||
Montero López, Mora-Urda, Mill, Silva, Santos Batista and B Molina [33] | Cross-sectional | Vitória, Brazil; Madrid, Spain; Luanda, Angola | n = 520 (Brazil n = 231, Spain n = 176, Angola n = 113) Aged 9–10 years, enrolled in elementary schools | Brazil: 9.6 (0.5) years Spain: 9.4 (0.5) years Angola: 9.4 (0.5) years | Brazil: 50% Spain: 53% Angola: 48% | Brazil Underweight or healthy 59.9% Overweight or obese 45% Spain Underweight or healthy weight 61.4% Overweight or obese 38.6% Angola Underweight or healthy weight 83.2% Overweight or obese 16.8% | Cf-PWV (applanation tonometry, SphygmoCor System, AtCor Medical) | Duration of exclusive breastfeeding |
Saeedi et al., 2020 [35] | Cross-sectional | Dunedin, New Zealand Physical Activity, Exercise, Diet, And Lifestyle Study (PEDALS) | n = 389 Students in years 5 or 6 of primary school, recruited from 17 schools | 9.7 (0.7) years | 49% | Underweight or healthy weight 81.2 Overweight 14.2% Obese 4.6% | Cf-PWV AIx-75 (site unclear) (Applanation tonometry, SphygmoCor XCEL, AtCor Medical) | 2 empirically derived dietary patterns |
Lydakis et al., 2012 [32] | Cross-sectional | Heraklion, Crete, Greece | n = 277 Students in first year of high school, recruited from three schools | 12 (8) years | 48% | Healthy 56.7% Overweight 30.3% Obese 13.0% | Arterial AIx (Oscillometric method, PulseCor) | Mediterranean dietary pattern |
Ruiz-Moreno et al., 2020 [34] | Cross-sectional | Malaga, Spain | n = 75 Aged 6–11 years, recruited from preschools and elementary schools, BMI in ≥95th percentile for age and sex | 10.1 (1.3) years | 54% | Obese 100% | Cf-PWV (simultaneous tonometry using oscillometric device, Vicorder, Skidmore Medical LTD) | Mediterranean dietary pattern |
Pucci et al., 2021 [36] | Cross-sectional | Terni, Italy MACISTE (Metabolic And Cardiovascular Investigation at School, TErni) Study | n = 387 Aged 13–19 years, recruited from one school | 17.1 (1.4) years | 53% | Underweight or healthy 88% Overweight 11% Obese 1% | Cf-PWV (Applanation tonometry, SphygmoCor Vx, AtCor Medical) | Heart-healthy dietary pattern |
Giontella et al., 2019 [17] | Cross-sectional | Verona South, Italy | n = 300 Aged 7–10 years, recruited from four primary schools | 8.6 (0.7) years | 50% | Male Healthy 63.3% Overweight 23.3% Obese 13.4% Female Healthy 68% Overweight 19.3% Obese 12.7% | Cf-PWV (applanation tonometry, SphygmoCor XCEL, AtCor Medical) | Intake of 14 foods/food groups and 2 empirically derived dietary patterns |
Saraf et al., 2022 [37] | Cross-sectional | Australia Child Health CheckPoint (sub study of the Longitudinal Study of Australian Children (LSAC)) | n = 1780 Aged 11–12 years, recruited from population-based birth cohort study | 11.5 (0.5) years | 51% | Underweight or healthy 77.1% Overweight 18.2% Obese 4.8% | Cf-PWV (applanation tonometry, SphygmoCor XCEL, AtCor Medical) | Consumption of fast food and sugar-sweetened beverages |
Arnberg et al., 2012 [31] | Cross-sectional | Copenhagen, Denmark | n = 183 Aged 12–15 years, overweight or with obesity, consuming ≤250 mL/d milk and yoghurt, recruited via Civil Registration System for participation in intervention study [24] | 13.2 years | 38% | 25.0 kg/m2 | Cf-PWV AIx-75 (Applanation tonometry, SphygmoCor System, AtCor Medical) | Energy intake, % energy from fat, % energy from protein, milk and yoghurt intake |
Brady et al., 2022 [16] | Cross-sectional | Cincinnati, US | n = 614 Aged 10–24 years, 31% with type 2 diabetes, 32% with obesity, enrolled in study examining effect of obesity and T2DM on cardiovascular function | 17.9 (3.3) years | 35% | Underweight or healthy 36.9% Overweight 31% Obese 32.1% | Cf-PWV AIx-75 (applanation tonometry, SphygmoCor SCOR-PVx System above, AtCor Medical) Brachial artery distensibility (DynaPulse Pathway System, Pulse Metric Inc.) | Sodium intake, sodium density |
Citation | Study Design | Dietary Component | Intervention | Duration | Blinding and Intention-to-Treat | Main Findings (Effect of Diet Component on A/S) O No Association ↑ Increased ↓ Decreased | Details of Findings | Study Quality 1 |
---|---|---|---|---|---|---|---|---|
Arnberg et al., 2013 [24] | Randomized parallel intervention | Consumption of skimmed milk, whey drink or casein drink | 1 L/d (containing 35 g/L protein) skimmed milk, whey drink or casein drink vs. water or pre-test control | 12-w for the milk-based drinks Subgroup of participants had an additional 12-w as the pre-test control group | Investigators, skimmed milk, whey and casein groups blinded; water and pre-test control groups unblinded Yes ITT | Skimmed milk, whey drink and casein drink: O cf-PWV O radial-AIx | No difference in cf-PWV or radial-AIx in the skimmed milk, whey or casein groups relative to the water group | (Ø) |
Rajakumar et al., 2020 [19] | Parallel RCT | Supplemental vitamin D3 | 2000 vs. 1000 vs. active control 600 IU/d vitamin D3 | 6-m | Double-blinded Yes ITT | 1000 IU and 2000 IU (vs. 600 IU): O cf-PWV; O AIx | No difference in cf-PWV or aortic-AIx in the 2000 or 1000 IU/d groups relative to the 600 IU/d group | (+) |
Varshney et al., 2019 [25] | Parallel RCT | Supplemental vitamin D | 120,000 vs. active control 12,000 IU/d vitamin D (form not specified) | 1 year | Double-blinded No ITT | 120,000 IU (vs. 12,000 IU): O cf-PWV; O cr-PWV; O cd-PWV; O rd-PWV | No difference in cf-, cr-, cd- or rd-PWV between the 120,000 or 12,000 IU/d groups | (Ø) |
Dong et al., 2010 [23] | Parallel RCT | Supplemental vitamin D3 | 2000 vs. active control 400 IU/d vitamin D3 | 16-w | Investigators blinded; participants unblinded No ITT | 2000 IU/d: ↓ cf-PWV O cr-PWV O carotid-dorsalis-pedis (foot) PWV | Significant time by group effect: cf-PWV decreased after 16-w of 2000 IU/d (baseline 5.41 ± 0.73, 16-w 5.33 ± 0.79 m/s) and increased after 16-w on 400 IU/d (5.38 ± 0.53, 16-w 5.71 ± 0.75 m/s; interaction p = 0.016) No difference in cr-PWV or carotid-dorsalis-pedis PWV between the 2000 and 400 IU/d groups | (+) |
Dangart et al., 2010 [26] | Cross-over trial | Supplemental omega-3 fatty acid | Total omega-3 1.2 g (930 mg EPA + 290 mg DHA + 100 mg GLA + 18 mg vitamin E per day) vs. placebo capsules (medium chain triglycerides) | 3-m in each condition with 6-w washout | Double-blinded No ITT | O cr-PWV ↓ AIx | No difference in cr-PWV between supplemental and placebo conditions AIx was lower following omega-3 condition (−15.0 ± 7.6%) compared to following the placebo condition (−11.4 ± 11.2%; p = 0.05) Negative correlations between ∆AIx and ∆serum EPA (r = −0.47, p = 0.025) and ∆AIx and ∆total serum omega-3 fatty acids (r = −0.47, p = 0.02) | (Ø) |
Ayer et al., 2009 [27] | 3-y follow-up of 5-y parallel RCT | ≈1:5 ratio of omega-3 to omega-6 fatty acids via supplements and spreads Plasma EPA, DHA, ALA, LA, AA | ≈1:5 ratio of omega-3 to omega-6 fatty acids via supplements and oils/spreads vs. control ratio found in general population (range 1:15–1:20) | 5-y intervention, 3-y follow-up | Double-blinded Yes ITT | 1:5 ratio: O b-PWV O r-AIx O c-AIx O CAD | No difference in b-PWV, CAD, r-AIx-75 or c-AIx-75 between 1:5 group and control group 3-y post-intervention Pearson correlation coefficients between markers of arterial stiffness at 8 years and plasma concentrations of specific omega-3 (DHA, EPA, ALA) and omega-6 (LA, AA) fatty acids measured at 18 mo, 3 y and 5 y 18 mo: No association between any omega-3 or omega-6 fatty acids and b-PWV, CAD, r-AIx-75 or c-AIx-75 3 y: No association between any omega-3 or omega-6 fatty acids and b-PWV, CAD, r-AIx-75 or c-AIx-75 5 y: weak correlation between plasma EPA and b-PWV (−0.15, p = 0.04) and between r-AIx-75 and linoleic acid (r = 0.14, p = 0.01). | (+) |
Citation | Study Design | Diet Component | Diet Assessment Method | Covariates | Main Findings O No Association ↑ Associated with Increase ↓ Associated with Decrease | Details of Findings 1 | Study Quality 2 |
---|---|---|---|---|---|---|---|
Schack-Nielsen et al., 2005 [28] | Prospective cohort 10 y follow-up (birth to age 10 y) | Duration of breastfeeding, current % energy from total fat | Breastfeeding status reported at 9 m of age Duration (months) of breastfeeding included exclusive or partial (at least once daily) breastfeeding. Energy and fat intake at age 10 y assessed via 7-d food record completed by parents, children reported food consumed at school. | Gender, height, weight, body fat percentage (DEXA), SBP, DBP, energy, % energy from fat, time spent in physical activity that affected breathing (1-day diary) | Longer duration breastfeeding: ↑ cf-PWV; O cr-PWV Greater current % energy from fat: ↑ cf-PWV; ↑ cr-PWV Greater current total energy intake: O cf-PWV; ↑ cr-PWV | Longer duration of breastfeeding (months) was associated with higher cf-PWV (β-coefficient = 2.1 (95% CI 0.4, 3.7) cm/s, p < 0.05). No association between duration of breastfeeding and cr-PWV. Cross-sectional associations at 10 years: Greater current % energy from fat was positively associated with cr-PWV (β-coefficient = 3.1 (95% CI 0.9, 5.2) cm/s, p < 0.01) and cf-PWV (β-coefficient = 1.8 (95% CI 0.2, 3.2), p < 0.05). Greater energy intake (MJ/d) was negatively associated with cr-PWV (β-coefficient = −6.4 (95% CI −11.7, −0.8) cm/s, p < 0.05) but not associated with cf-PWV. | (+) |
de Jonge et al., 2013 [29] | Prospective cohort 6 y follow-up (birth to age 6 y) | Ever breastfed, breastfeeding duration, breastfeeding exclusivity, age at introduction of solids | Questionnaires at infant ages 2, 6 and 12 m (medical records were used if responses were missing) Breastfeeding duration: <2 mo, 2- < 4 mo, 4- < 6 mo or ≥6 mo Breastfeeding exclusivity based on age formula and solid food were introduced: never, partial for ≥4 mo or exclusive for ≥4 mo Introduction of solid foods based on age fruit or vegetable snack was given for first time: <4 mo, 4–5 mo, >5 mo | Maternal age, ethnicity, parity, educational level, prepregnancy BMI, smoking during pregnancy and child’s sex, gestational age at birth, birth weight, weight gain between birth and first year of life, current age, body surface area | Ever breastfed (vs never breastfed): ↓ cf-PWV Duration of breastfeeding: O cf-PWV Breastfeeding exclusivity: O cf-PWV Age at introduction of solids: O cf-PWV | cf-PWV at age 6 y was higher in never-breastfed children compared to those who had ever been breastfed (β-coefficient for never-breastfed = 0.13 (95% CI 0.03, 0.24) m/s) No significant associations between cf-PWV and duration or exclusivity of breastfeeding or age at introduction of solids. | (+) |
Kerr et al., 2018 [18] | Prospective cohort 9 y follow-up (ages 4 y to 15 y) | 4 empirically derived dietary pattern trajectories: healthy, moderately healthy, moderately unhealthy and unhealthy | 4-d food checklist (two weekdays and two weekend-days) collected on eight occasions—six times between ages 4–6.5 y, once at age 10 y and once at age 15 y. Parents or children recorded frequency of consumption of 12 food items (including fruit, milk, water, confectionery). Responses were scored against the 2013 Australian Dietary Guidelines and entered into latent class analysis to produce trajectories of dietary patterns. | Maternal education and socioeconomic position when child was 4 y, current child age, sex, pubertal development and percent of time spent in moderate-to-vigorous physical activity (accelerometer) at age 15-y, BMI z-score | Dietary pattern trajectory: O cf-PWV Dietary pattern score: O cf-PWV | No significant associations between cf-PWV at age 15 y and trajectories of dietary patterns No cross-sectional correlations between cf-PWV and dietary pattern score throughout ages 4.5–15 y | (+) |
van den Hooven et al., 2013 [30] | Prospective cohort 5 y follow-up (ages 14 m to 6 y) | Macronutrient intake (total and type): total protein (vegetable protein, animal protein), total fat (saturated fat, monounsaturated fat, polyunsaturated fat), total carbohydrate (mono-and disaccharides, polysaccharides) | 221-item validated FFQ developed for Dutch children in second year of life | Macronutrient intakes adjusted for energy intake, models further adjusted for maternal educational, smoking during pregnancy, child’s sex, ethnicity, birth weight, television watching in childhood (<1 h/d or ≥1 h/d), current age, current BMI | Total fat intake: ↑ cf-PWV Saturated, monosaturated or polyunsaturated fat intake: O cf-PWV Total carbohydrate: ↓ cf-PWV Mono-and disaccharides: ↓ cf-PWV Total protein intake: O cf-PWV Vegetable or animal protein: O cf-PWV | Highest tertile of total fat intake at age 14 m was associated with higher cf-PWV at age 6 compared to the lowest tertile (β-coefficient difference between tertile 3 and tertile 1 = 0.11 (95% CI 0.02, 0.20) m/s, p = 0.01). No association between middle tertile of fat intake and lowest. Middle tertile of total carbohydrate intake at age 14 m was associated with lower cf-PWV at age 6 compared to the lowest tertile (β-coefficient difference between tertile 2 and 1 = −0.14 (−0.22, −0.05) m/s, p < 0.01). No association between highest tertile of carbohydrate intake and lowest. Middle tertile of mono- and disaccharide intake at age 14 m was associated with lower cf-PWV at age 6 compared to the lowest tertile (β-coefficient difference between tertile 2 and tertile 1 = −0.12 (−0.20, −0.03) m/s, p < 0.01). No association between highest tertile of mono- and disaccharide intake and lowest. No associations between protein (total, vegetable or animal), saturated, monounsaturated or polyunsaturated fat or polysaccharides and cf-PWV. | (Ø) |
Arnberg et al., 2012 [31] | Cross-sectional | Energy, % energy from fat, % energy from protein, milk and yoghurt | 4-d food record completed by children (three weekdays and one weekend day). | cf-PWV models adjusted for age, gender, mean arterial pressure, Tanner stage, heart rate and BMI AIx models adjusted for age, gender, Tanner stage, height and BMI | Greater % energy from protein: ↑ cf-PWV; O radial AIx Greater milk and yoghurt intake: ↓ cf-PWV; O AIx Total energy: O cf-PWV O AIx % energy from fat: O cf-PWV O AIx | Greater % energy from protein was associated with higher cf-PWV (β-coefficient for % energy from protein = 0.05 (95% CI not reported) m/s, p < 0.01) Trend for greater consumption of milk and yoghurt (g/d) associated with lower cf-PWV (β-coefficient = −0.64 (95% CI not reported) m/s, p = 0.05) No associations between energy intake or % energy from fat and cf-PWV or AIx | (Ø) |
Brady et al., 2022 [16] | Cross-sectional | Sodium density (mg/kcal/d) | 3-d diet record including at least one weekend-day. | Age, sex, race, % body fat via DEXA, T2DM, SBP z-score. Height also included in AIx model. | Higher sodium density ↑ cf-PWV ↑ AIx ↓ brachial artery distensibility | Higher sodium density (mg/kcal/day) associated with lower brachial artery distensibility (β-coefficient = −0.58% change/mm Hg, p = 0.004); higher PWV (β-coefficient = 0.42 m/sec, p < 0.001) and a trend for higher AIx (β-coefficient = 2.27%, p = 0.05). Highest (β-coefficient = −1.55 (−2.36, −0.75) m/s, p = 0.0002) and middle tertiles (β-coefficient = −0.76 (−1.55, 0.04) m/s, p = 0.06) of sodium density associated with higher cf-PWV compared to the lowest tertile. Highest tertile of sodium density vs. lowest tertile was associated with lower AIx (β-coefficent = −16.0 (95% CI −27.32, −4.61)%, p = 0.006). Highest tertile of sodium density vs. lowest tertile was associated with lower brachial distensibility (β-coefficient = −0.26 (−0.47, −0.04)% change/mmHg, p = 0.02) | (Ø) |
Giontella et al., 2019 [17] | Cross-sectional | Intake of 14 foods/food groups: fast food, cereals and tubers, vegetables, fruit, eggs, meat, dairy products, sweets, legumes, fish, nuts, extra virgin olive oil, animal-derived fat, seed oil 2 empirically derived dietary patterns: ‘healthy’ and ‘unhealthy’ | 61-item validated FFQ completed by child | Age, sex, ethnicity, BMI, energy intake, physical activity score (PAQ-C score) | Greater consumption of fast food: ↑ cf-PWV cereals and tubers, vegetables, fruit, eggs, meat, dairy products, sweets, legumes, fish, nuts, extra virgin olive oil, animal-derived fat, seed oil: O cf-PWV ‘Healthy’ and ‘unhealthy’ dietary patterns: O cf-PWV | Association between fast food and cf-PWV in adjusted analysis (β-coefficient for fast food = 0.337 (95% CI 0.140, 0.534) m/s p < 0.01). There were no associations between cereals and tubers, vegetables, fruit, eggs, meat, dairy products, sweets, legumes, fish, nuts, extra virgin olive oil, animal-derived fat, seed oil and cf-PWV. No significant correlations between the ’healthy’ or ‘unhealthy’ dietary patterns and cf-PWV. | (Ø) |
Lydakis et al., 2012 [32] | Cross-sectional | Adherence to Mediterranean dietary pattern | 16-item KIDMED questionnaire, child reported | Gender, heart rate, peripheral mean pressure, BMI, waist circumference | Greater adherence to Mediterranean diet: ↓ AIx | Higher adherence to Mediterranean diet associated with lower AIx (β-coefficient for KIDMED score = −0.114 (95% CI not reported), p = 0.026). | (Ø) |
Montero López et al., 2019 [33] | Cross-sectional | Retrospective information on duration of exclusive breastfeeding | Weeks of exclusive breastfeeding (no other liquids or solids except for vitamin drops or syrups, mineral supplements or medications) extracted from each child’s health cards provided by the family | Sex, birth weight, current BMI, SBP | Duration of exclusive breastfeeding: O cf-PWV | No association between duration of exclusive breastfeeding and cf-PWV. | (Ø) |
Pucci et al., 2021 [36] | Cross-sectional | Adherence to heart-healthy dietary pattern | 24-h recall and validated FFQ, completed by child. Responses scored against cardiovascular recommendations of (1) ≥400 g/d fruits and vegetables, (2) ≥200 g/wk fish; (3) sodium ≤1500 mg/day; (4) sugar-sweetened beverages ≤450 kcal/wk (1 L/wk) and (5) ≥3 serves/d whole grains scaled to a 2000-kcal/d diet | Unadjusted | Consumption of ‘ideal’ heart-healthy dietary pattern: ↓ cf-PWV | Participants with diets scored by researchers as ‘ideal’ for cardiovascular health had lower cf-PWV than those with diets considered ‘not ideal’ (4.57 m/s vs. 4.98 m/s, p < 0.05) (unadjusted univariate analysis) | (Ø) |
Ruiz-Moreno et al., 2020 [34] | Cross-sectional | Adherence to Mediterranean dietary pattern | 14-item FFQ (not reported if parent or child completed) | Age, weight, BMI, BMI z-score, serum total cholesterol, serum LDL-cholesterol, serum HDL-cholesterol, fasting glucose, serum insulin levels, HOMA-IR index | Adherence to Mediterranean diet: O cf-PWV | No association between adherence to Mediterranean dietary pattern and cf-PWV. | (Ø) |
Saeedi et al., 2020 [35] | Cross-sectional | 2 empirically derived dietary patterns: ‘snacks’ and ‘fruit and vegetables’ identified using principal component analysis | 28-item validated FFQ completed by child | Age, sex, ethnicity, socioeconomic deprivation, heart rate, mean arterial pressure, moderate and vigorous physical activity (accelerometer), cardiorespiratory fitness (VO2max), fat mass, fat free mass (bioelectrical impedance analyzer) | ‘Snacks’ or ‘fruit and vegetables’ dietary patterns: O cf-PWV; O AIx | No associations between the ‘snacks’ or ‘fruit and vegetables’ dietary patterns and cf-PWV or AIx | (+) |
Saraf et al., 2022 [37] | Cross-sectional | Consumption of fast food and sugar-sweetened beverages | FFQ, parent and child reported. Items about fast food and sugar-sweetened beverage consumption dichotomized into <once per week or ≥once per week. | Age, sex, socioeconomic position | Consumption of takeaway food or sugar-sweetened beverages: O cf-PWV | No associations between frequency per week of consumption of takeaway food or sugar-sweetened beverages and cf-PWV | (+) |
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Leed, A.; Sheridan, E.; Baker, B.; Bamford, S.; Emmanouilidis, E.; Stewart, F.; Ostafe, K.; Sarwari, M.; Lim, K.; Zheng, M.; et al. Dietary Intake and Arterial Stiffness in Children and Adolescents: A Systematic Review. Nutrients 2023, 15, 2092. https://doi.org/10.3390/nu15092092
Leed A, Sheridan E, Baker B, Bamford S, Emmanouilidis E, Stewart F, Ostafe K, Sarwari M, Lim K, Zheng M, et al. Dietary Intake and Arterial Stiffness in Children and Adolescents: A Systematic Review. Nutrients. 2023; 15(9):2092. https://doi.org/10.3390/nu15092092
Chicago/Turabian StyleLeed, Allanah, Emma Sheridan, Brooke Baker, Sara Bamford, Elana Emmanouilidis, Fletcher Stewart, Kristen Ostafe, Mustafa Sarwari, Karen Lim, Miaobing Zheng, and et al. 2023. "Dietary Intake and Arterial Stiffness in Children and Adolescents: A Systematic Review" Nutrients 15, no. 9: 2092. https://doi.org/10.3390/nu15092092
APA StyleLeed, A., Sheridan, E., Baker, B., Bamford, S., Emmanouilidis, E., Stewart, F., Ostafe, K., Sarwari, M., Lim, K., Zheng, M., Islam, S. M. S., Bolton, K. A., & Grimes, C. A. (2023). Dietary Intake and Arterial Stiffness in Children and Adolescents: A Systematic Review. Nutrients, 15(9), 2092. https://doi.org/10.3390/nu15092092