Obesity and COVID-19 in Children and Adolescents: Reciprocal Detrimental Influence—Systematic Literature Review and Meta-Analysis
Abstract
:1. Introduction
2. Materials and Methods
3. Results
3.1. Impact of COVID-19 Lockdown on Weight and Lifestyle in Children and Adolescents
3.2. Impact of Overweight/Obesity on the Risk of Hospital/ICU Admission in Children/Adolescents with COVID-19
4. Discussion
4.1. Impact of COVID-19 Lockdown on Weight and Lifestyle Changes in Children and Adolescents
4.2. Impact of Overweight/Obesity on the Severity and Outcome of COVID-19 Disease
4.3. Study Strengths and Limitations
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Conflicts of Interest
References
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Author, Year | Country | Study Period (Months) | Study Design | N | Males (N, %) | Population | Age (Mean ± SD; Range) | Setting | Weight Measure | Weight Status Before Lockdown | Weight Status After Lockdown | Change in Weight Status | Change in Eating Habits | Decrease in Physical Activity (PA) | Sleep Changes |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Androutsos O. et al., 2021 [21] | Greece | 2 | CSS | 397 | 228 (57.4) | C, A | 7.8 ± 4.1 * | O | BW | 32.3 ± 16.9 * | n.a. | stable BW: N = 214 (58.9%); BW increase: N = 127 (35%); BW decrease: N = 22 (6.1%) | Increase in fresh fruit juices, vegetables, dairy products, pasta, sweets, snacks and breakfast | N = 261 (66.9%) | Increased sleep time (h/d). BL: >10 h/d = 13.3%, <8 h/d = 15.4% vs. AL: >10 h/d = 24.2%, <8 h/d = 4.8% |
Azoulay E. et al., 2021 [22] | Israel | 7 | LS | 220 | 109 (49.5) | C, A | 10.8 ± 3.2 * | H | BMI-SDS | BMI-SDS: 1.74 (1.40, 2.03) ** | BMI-SDS: 1.70 (1.36, 1.97) ** | MFR increase in underweight (p = 0.05) and normal weight (p = 0.008), but not in overweight/obese patients. Associations in BMI z-scores (r = 0.961, p < 0.001) and MFR z-scores (r = 0.854, p < 0.001) before and during the pandemic. A multivariate linear regression model identified socioeconomic position, pre-pandemic BMI and MFR z-scores, and physical activity levels during the pandemic as predictors for delta MFR z-scores (F = 12.267, p < 0.001) | n.a. | n.a. | n.a. |
Brooks C.G. et al., 2021 [23] | USA | 12 | HC | 96,501 | n.a. | C, A | 6–17 | H | BMI-SDS | 0.31 (0.29, 0.32) ** | 0.62 (0.59, 0.64) ** | Overall increased BMI-SDS: 0.30 (0.27–0.33) *. (In obese C AL: 1.16 (1.07–1.24) ** vs. BL: 0.56 (0.52–0.61) **; Hispanic C AL: 0.93 (0.84–1.02) ** vs. BL: 0.41 (0.36–0.46) **; C lacking commercial insurance AL: 0.88 (0.81, 0.95) ** vs.BL: 0.43 (0.39, 0.47) **; DBMI higher in boys vs. girls (0.36 vs. 0.24) | n.a. | n.a. | n.a. |
Cipolla C. et al., 2021 [24] | Italy | 1 | CSS | 64 | 26 (40.6) | C, A | 13.9 ± 2.4 * | H | BMI | 27.7 ± 4.8 * | 27.6 ± 4.0 * | BMI increase: N = 31 (48.4%); BMI decrease: N = 33 (51.6%) | Increase in bread/pasta/pizza (N = 43; 67.2%); desserts (N = 3; 4.7%), meat (N = 8; 12.5); vegetables/fruit (N = 10; 15.6%); sugar drinks (N = 20; 31.2%) | Higher BMI increase in sedentary patients (p = 0.024) and in those spending longer time at videogaming (p = 0.005) | n.a. |
Hu J. et al., 2021 [25] | China | 12 | HC | 207,536 | n.a | C, A | 6–17 | H | zBMI | 0.29 ± 0.01 * | 0.45 ± 0.01 * | Increase of zBMI and OB in 2020 vs. 2014–2019 in all age groups, but significant only for ages 6–11 and 15–16. zBMI increase in boys (0.18) higher than in girls (0.13, p = 0.014). Similar rise in urban and rural areas | n.a. | n.a. | n.a. |
Jia P. et al., 2020 [26] | China | 1 | CSS | 2824 | 678 (24.0) | A | 17.5 ± 1.2 * | S | BW; BMI | BW: 58.6 ± 17.1 * BMI: 22.7 ± 6.7 * | BW: 60.2 ± 22.9 *; BMI: 23.6 ± 8.6 * | Increase in mean BMI and BW | n.a. | Decrease in moderate-/vigorous-intensity PA: 0.5 ± 1.7 * vs. 0.4 ± 1.7 * d/w | Increase in sleeping time: sleep (h/d): 7.5 ± 3.2 * vs. 7.7 ± 4.7 * (workdays); 8.0 ± 3.4 * vs. 8.2 ± 5.4 * (weekends) |
Kang H.M. et al., 2021 [27] | South Korea | 6 | HC | 226 | 96 (42.5) | C, A | 10.5 (8.7–12.4) ** | H | zBMI | 0.4 ± 1.3 * | 0.2 ± 1.3 * | OW/OB: 31.4 vs. 23.9 % (p = 0.074); increase from NW to OW/OB: 9.5%. Mean zBMI 0.42 ± 1.25 vs. 0.2 ± 1.25 (p < 0.001) Days after school closure (p = 0.004) and normoweight (p = 0.017) pre-COVID were negative predictors | n.a. | n.a. | n.a. |
Kim E.S. et al., 2021 [28] | South Korea | 6 | HC | 90 | 70 (77.8) | C, A | 12.2 ± 3.4 * | H | BW; zBW; BMI; zBMI | BW: 67.2 ± 23.8 *; zBW: 2.0 ± 0.8 *; BMI: 26.7 ± 4.6 *; zBMI: 1.9 ± 0.5 * | BW: 71.1 ± 24.2 *; zBW: 2.2 ± 0.7 *; BMI: 27.7 ± 4.6 *; zBMI: 2.0 ± 0.4 * | △zBW: 0.18 (0.1–0.29) **; △zBMI 0.06 (0–0.12) ** | n.a. | yes | n.a. |
Maltoni G. et al., 2021 [29] | Italy | 3 | LS | 51 | 31 (60.8) | C, A | 14.7 ± 2.1 * | H | BW; BMI; BMI SDS; WC; W/H-r | BMI: 32.6 ± 4.0 *; BMI SDS: 2.4 ± 0.5 *; WC: 102.1 ± 12.6 *; W/H-r: 0.6 ± 0.1 * | n.a. | △BW: 2.8 ± 3.7 *; Δ-BMI: 0.5 ± 1.3 *; Δ-BMI SDS: 0.1 ± 0.2 *; ΔWC.: 4.4 ± 7.8 *; ΔW/H-r: 0.02 ± 0.005 * △BW: M 3.8 ± 3.4 vs. F 1.2 ± 3.7 (p = 0.02) Δsedentary behavior: M3.8 ± 2.7 vs. F 1.5 ± 2.5 (p = 0.003) | Δ-intake of vegetables/fruit: −0.1 ± 0.5 * (portions/w) | yes | n.a. |
Qiu N. et al., 2021 [30] | China | 7 | LS | 446 | 260 (58.2) | C | 7–12 | S | Median BMI | 20.9 kg/m2 | 22.4 kg/m2 | Increase from NW to OW/OB in 28.1%; from OW to OB in 42.42%. Boys at significantly higher risk | Increased number of meals, higher in parents with primary school vs. high school diploma (6 ± 0.7 vs. 4.4 ± 1.3, p = 0.02) | n.a. | n.a. |
Valenzise M. et al., 2021 [31] | Italy | 12 | HC | 40 | 23 (57.5) | C, A | 11.6 ± 3.3 * | O | Δ-BMI | 30.2 ± 4.0 * | 32.0 ± 5.5 * | BMI increase (32 ± 5.5 vs. 30.2 ± 4) not significant | n.a. | N = 38 (95%) | n.a. |
Vinker-Shuster M. et al., 2021 [32] | Israel | 1 | HC | 229 | 117 (51.1) | C, A | 0–6 y: N = 60 6–18 y: N = 169 | H | aaBWp | 38.8 ± 33.7 * | 40.4 ± 34.4 * | Overall increase of weight percentile (40.4 vs. 38.8, p = 0.03) higher in boys (37.7 vs. 34.4, p = 0.01) vs girls (no significant changes), and in patients < 6 yo (39.2 vs. 33.6, p = 0.02) | n.a. | n.a. | n.a. |
Vogel M. et al., 2021 [33] | Germany | 12 | HC | 274,456 | n.a | C, A | 6–18 | H | ΔBMI-SDS | 0.001 (0.001, 0.002) ** | 0.048 (0.039, 0.056) ** | BMI-SDS increase over 3-month AL 1.38 (95% CI 1.30–1.47; p < 0.001), >30 times as high as for years 2005–2019. Highest effects in OB group (OR 1.85; 95% CI 1.45–2.35; p < 0.001), in all ages | n.a. | n.a. | n.a. |
Woolford S. et al. [34] | USA | 1 | HC | 191,509 | n.a | C, A | 5–17 | H | ΔBMI-SD | 5–11 y: 0.15 (0.11–0.18) **; 12–15 y: −0.03 (−0.07–0.00) **; 16–17 y: −0.25 (−0.30–−0.21) ** | 5–11 y: 1.72 (1.67–1.76) **; 12–15 y: 0.87 (0.83– 0.91) **; 16–17 y: 0.23 (0.18–0.28) ** | Increase in ΔBMI-SD especially for age 5–11 yo (1.57) vs. 12–15 yo (0.91) vs. 16–17 yo (0.48). OW/OB increase 8.7% (45.7 vs. 36.2%) for age 5–11 yo vs. 5.2% for age 12–15 yo vs. 3.1% for age 16–17 yo | n.a. | n.a. | n.a. |
Author | Country | Study Design | Age * (Mean; Range; yr) | N | Males (N, %) | Population | N Obese (%) | Obese Hospitalized/Admitted to ICU (N, %) | Normal Weight Hospitalized/Admitted to ICU (N, %) | Risk Factor and Outcome |
---|---|---|---|---|---|---|---|---|---|---|
Fernandes D.M. et al., 2020 [35] | US | HC; LS | 10 (1–17) | 250 * | 170 (60.5) | C, A | 85 (34.0) | 85 (100) | 165 (100) | Obesity (aOR 3.39, 95% CI 1.26–9.10) severe disease |
Graff K. et al., 2021 [36] | US | HC | 11 (0–23) | 211 * | 262 (57.7) | C, A | 63 (29.9) | 38 (60.3) | 21 (14.2) | Obesity (OR 2.48; 95% CI 1.2–5.1), and severe obesity (OR 4.8; CI 1.9–12.1) hospital admission |
Guzman et al., 2021 [37] | US | HC | 0–21 | 494 | 203 (45.6) | C, A | 115 (23.3) | 36 (31.3) | 94 (24.8) | Obesity (ARR 2.02, 95% CI 1.17–3.48) critical illness. Higher risk for age 13–21 yo [ARR 3.09, 95% CI 1.48–6.47] |
Kompanyets et al., 2021 [38] | US | CSS | 6–18 | 30,527 * | 15.974 (50.2) | C, A | 1036 (29.4) | 425 (41.0) | 2740 (9.3) | Type 1 diabetes (aRR 4.60, 95% CI, 3.91–5.42) and obesity (aRR 3.07, 95% CI, 2.66–3.54) hospitalization |
Swann O.V. et al., 2020 [39] | UK | LS | 4.6 (0.3–13.7) | 602 * | 367 (56.0) | C, A | 17 (2.8) | 17 (100) | 585 (100) | age < 1 m (OR 3.21, 95% CI 1.36–7.66), age 10–14 yo (OR 3.23, 95% CI 1.55–6.99), and black ethnicity (OR 2.82, 95% CI 1.41–5.57) admission to critical care |
Verma S. et al., 2021 [40] | US | CSS | 5 (0.2–15.2) | 48 * | 52 (63.0) | C, A | 19 (39.6) | 19 (100) | 29 (100) | Obesity ICU admission (63 vs. 28% normal weight, p = 0.02) |
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La Fauci, G.; Montalti, M.; Di Valerio, Z.; Gori, D.; Salomoni, M.G.; Salussolia, A.; Soldà, G.; Guaraldi, F. Obesity and COVID-19 in Children and Adolescents: Reciprocal Detrimental Influence—Systematic Literature Review and Meta-Analysis. Int. J. Environ. Res. Public Health 2022, 19, 7603. https://doi.org/10.3390/ijerph19137603
La Fauci G, Montalti M, Di Valerio Z, Gori D, Salomoni MG, Salussolia A, Soldà G, Guaraldi F. Obesity and COVID-19 in Children and Adolescents: Reciprocal Detrimental Influence—Systematic Literature Review and Meta-Analysis. International Journal of Environmental Research and Public Health. 2022; 19(13):7603. https://doi.org/10.3390/ijerph19137603
Chicago/Turabian StyleLa Fauci, Giusy, Marco Montalti, Zeno Di Valerio, Davide Gori, Maria Giulia Salomoni, Aurelia Salussolia, Giorgia Soldà, and Federica Guaraldi. 2022. "Obesity and COVID-19 in Children and Adolescents: Reciprocal Detrimental Influence—Systematic Literature Review and Meta-Analysis" International Journal of Environmental Research and Public Health 19, no. 13: 7603. https://doi.org/10.3390/ijerph19137603