Covid-19 Confinement and Changes of Adolescent’s Dietary Trends in Italy, Spain, Chile, Colombia and Brazil

This was an observational cross-sectional survey study, not an experiment. The researchers tested whether the COVID-19 confinement period (March–May 2020) was associated with changes in adolescents' dietary habits compared to their self-reported usual diet before confinement. They measured:

**Primary outcomes:** Changes in consumption frequency of 10 food groups: fried foods, sweets, fast food, sugary drinks, fruits, vegetables, legumes, pasta/rice, meat/fish/eggs, and dairy products.

**Secondary outcomes:** Whether demographic and contextual variables (gender, age, country, maternal education level, number of family members at home, watching TV during meals) predicted dietary changes.

**Comparator:** Each adolescent's retrospective recall of their "usual" diet before confinement, compared to their diet during confinement. There was no separate control group — each participant served as their own historical control.

The researchers also compared adolescents' reported intake during confinement against standard dietary guidelines (e.g., WHO recommendations for fruit and vegetable intake) to see if confinement pushed them toward or away from healthy targets.

**Sample size:** 820 adolescents

**Age range:** 10–19 years (mean age approximately 15 years, exact mean not reported)

**Gender:** 54.3% female, 45.7% male

**Countries:** Spain (n=203), Italy (n=200), Brazil (n=200), Colombia (n=117), Chile (n=100)

**Setting:** Online survey distributed through school networks and social media during the first wave of COVID-19 lockdowns (April–May 2020)

**Inclusion criteria:** Adolescents aged 10–19 years living in one of the five target countries, who were under COVID-19 confinement (defined as mandatory stay-at-home orders)

**Exclusion criteria:** Not explicitly stated; the survey was anonymous and voluntary

**Key demographics:** Maternal education level was used as a proxy for socioeconomic status — 38.7% of mothers had university education, 33.8% had secondary education, 27.5% had primary education or less. Family size ranged from 2 to 8+ members living in the same household.

**Important limitation for self-experimenters:** This is a convenience sample recruited online, not a random population sample. Adolescents who responded likely had internet access, motivated parents, and interest in nutrition — all of which could bias results toward healthier or more health-conscious families.

The researchers used a single anonymous online questionnaire developed specifically for this study (not a validated, pre-existing dietary assessment tool). The questionnaire asked adolescents to report:

1. **Frequency of consumption** for each of 10 food groups during confinement, using a 5-point scale: never, 1–3 times per month, 1–3 times per week, 4–6 times per week, daily.

2. **Same frequency questions for their usual diet before confinement** (retrospective recall).

3. **Demographic variables:** Age, gender, country, maternal education level, number of family members at home, and whether they watched TV during meals (yes/no).

4. **Adherence to dietary guidelines:** Whether they met recommended intakes for fruits (≥2 servings/day), vegetables (≥3 servings/day), legumes (≥2 servings/week), and sweets/fried foods (≤2 times/week).

**Measurement limitations:** The questionnaire was not validated against objective measures (like food diaries or biomarkers). Retrospective recall of "usual diet" is notoriously unreliable — people tend to remember their past diet as healthier than it actually was (the "good old days" bias). The frequency scale is coarse: "1–3 times per week" lumps together someone who eats sweets once a week with someone who eats them three times a week, which is a meaningful difference.

**Study design:** Cross-sectional observational survey with retrospective recall. This is not a randomized controlled trial, not a longitudinal cohort study, and not a natural experiment with a control group. It is a single-time-point survey asking people to remember the past and compare it to the present.

**Why this design matters:** The researchers chose this design because it was the only feasible way to collect data during an unprecedented global lockdown. They could not randomize people to confinement vs. no confinement (unethical and impossible), nor could they follow adolescents prospectively because the lockdown was sudden and unexpected. The design trades internal validity (ability to prove causation) for speed and feasibility.

**What this design can prove:**

It can identify associations between confinement and self-reported dietary changes.

It can show which demographic groups reported the largest changes.

It can generate hypotheses about why certain groups changed more than others.

**What this design cannot prove:**

It cannot prove that confinement *caused* the dietary changes. Other factors (seasonal food availability, media messaging about immunity, parental job loss, stress) could explain the changes.

It cannot rule out recall bias — adolescents may have misremembered their pre-confinement diet.

It cannot account for the fact that the survey itself may have changed how adolescents thought about their diet (social desirability bias — they might overreport healthy foods and underreport unhealthy ones).

**Duration:** The confinement period varied by country but generally lasted 6–10 weeks (March–May 2020). The survey was administered during the last 2–3 weeks of confinement, so adolescents were reporting on approximately 6–8 weeks of dietary change.

**Statistical approach:** The researchers used:

McNemar's test (for paired categorical data) to compare pre- vs. during-confinement proportions of adolescents meeting dietary guidelines.

Chi-square tests to examine associations between demographic variables and dietary changes.

Logistic regression to identify predictors of dietary improvement or worsening.

Significance threshold: p < 0.05 (two-tailed).

**Major methodological weaknesses:**

1. **No validation of the questionnaire** against objective dietary measures (e.g., food diaries, 24-hour recalls, biomarkers).

2. **Retrospective recall** is highly susceptible to memory bias — especially for adolescents who may not have been paying close attention to their diet before lockdown.

3. **No control group** — we cannot compare confined adolescents to unconfined adolescents during the same period.

4. **Convenience sampling** via online distribution likely selects for families with internet access, higher socioeconomic status, and greater health awareness.

5. **Self-report of dietary intake** is known to be inaccurate, especially for "unhealthy" foods (underreporting) and "healthy" foods (overreporting).

6. **The frequency scale is coarse** — it cannot capture portion sizes, which are critical for understanding actual caloric or nutritional impact.

7. **No data on physical activity, sleep, or stress** — all of which are known to affect dietary choices and may have changed dramatically during confinement.

**Primary outcomes — Changes in food group consumption:**

**Fried foods:** 35.2% of adolescents reported increased consumption during confinement, 48.5% reported no change, 16.3% reported decreased consumption. The proportion eating fried foods ≥4 times/week increased from 12.4% pre-confinement to 18.9% during confinement (p < 0.001).

**Sweets:** 38.0% reported increased consumption, 44.5% no change, 17.5% decreased. The proportion eating sweets daily increased from 18.7% to 24.3% (p < 0.001).

**Fruits:** 37.2% reported increased consumption, 47.1% no change, 15.7% decreased. The proportion meeting the guideline of ≥2 servings/day increased from 38.4% to 44.5% (p < 0.001).

**Vegetables:** 33.7% reported increased consumption, 49.6% no change, 16.7% decreased. The proportion meeting ≥3 servings/day increased from 24.3% to 29.4% (p < 0.001).

**Legumes:** 30.9% reported increased consumption, 55.0% no change, 14.1% decreased. The proportion eating legumes ≥2 times/week increased from 41.2% to 47.8% (p < 0.001).

**Fast food:** 18.9% reported increased consumption, 60.4% no change, 20.7% decreased. The proportion eating fast food ≥1 time/week decreased from 31.2% to 26.1% (p < 0.01).

**Sugary drinks:** 25.4% reported increased consumption, 52.8% no change, 21.8% decreased. The proportion drinking sugary drinks daily increased from 14.5% to 17.1% (p = 0.04).

**Pasta/rice:** 30.1% reported increased consumption, 55.2% no change, 14.7% decreased. No significant change in meeting guidelines.

**Meat/fish/eggs:** 25.6% reported increased consumption, 58.5% no change, 15.9% decreased. No significant change.

**Dairy:** 22.4% reported increased consumption, 60.5% no change, 17.1% decreased. No significant change.

**Secondary outcomes — Predictors of dietary change:**

**Gender:** Girls were more likely than boys to increase fruit consumption (OR = 1.42, 95% CI: 1.08–1.87, p = 0.01) and vegetable consumption (OR = 1.38, 95% CI: 1.04–1.83, p = 0.03). Boys were more likely to increase fried food consumption (OR = 1.52, 95% CI: 1.14–2.03, p = 0.005).

**Maternal education:** Adolescents whose mothers had university education were more likely to increase fruit consumption (OR = 1.67, 95% CI: 1.21–2.31, p = 0.002) and less likely to increase fried food consumption (OR = 0.64, 95% CI: 0.46–0.89, p = 0.008) compared to those whose mothers had primary education or less.

**Watching TV during meals:** Adolescents who watched TV during meals were more likely to increase consumption of fried foods (OR = 1.73, 95% CI: 1.28–2.34, p < 0.001) and sweets (OR = 1.48, 95% CI: 1.10–1.99, p = 0.01), and less likely to increase fruit consumption (OR = 0.71, 95% CI: 0.53–0.95, p = 0.02).

**Number of family members at home:** Living with ≥5 family members was associated with increased legume consumption (OR = 1.44, 95% CI: 1.06–1.96, p = 0.02) and decreased fast food consumption (OR = 0.68, 95% CI: 0.47–0.98, p = 0.04) compared to living with 2–3 family members.

**Country differences:** Italian adolescents showed the largest increase in fruit consumption (+12.5 percentage points meeting guidelines), while Chilean adolescents showed the largest increase in fried food consumption (+9.8 percentage points). Brazilian adolescents showed the smallest changes overall.

**Adherence to dietary guidelines during confinement:**

Only 44.5% met fruit guidelines (≥2 servings/day)

Only 29.4% met vegetable guidelines (≥3 servings/day)

47.8% met legume guidelines (≥2 servings/week)

61.2% met the guideline for limited sweets (≤2 times/week)

72.1% met the guideline for limited fried foods (≤2 times/week)

The changes, while statistically significant, were modest in absolute terms:

**Fried foods:** About 1 in 7 adolescents (14.7%) moved from eating fried foods occasionally to eating them 4+ times per week — roughly equivalent to adding one extra serving of fried food every 2–3 days.

**Fruits:** About 1 in 16 adolescents (6.1% increase in meeting guidelines) started eating at least 2 servings of fruit per day — meaning for every 16 adolescents, one additional person reached the fruit target.

**Vegetables:** About 1 in 20 adolescents (5.1% increase) started eating at least 3 servings of vegetables per day.

**Sweets:** About 1 in 18 adolescents (5.6% increase in daily consumption) added a daily sweet treat.

To put these in perspective: if you normally eat fried foods twice a week, the average change during confinement would be to eat them about 2.5 times per week. If you normally eat fruit once a day, you might increase to about 1.2 servings per day. These are small shifts at the individual level, but at a population level they could meaningfully impact obesity and diabetes risk over months to years.

The strongest predictor effects were moderate: watching TV during meals increased the odds of eating more fried foods by 73% — roughly equivalent to the difference between a family that eats together at a table vs. one that eats separately in front of screens.

**What the authors acknowledge:**

The cross-sectional design cannot establish causality.

The questionnaire was not validated against objective measures.

Recall bias may affect pre-confinement dietary reports.

The sample is not representative of all adolescents in these countries (online recruitment bias).

No data on physical activity, sleep, or mental health, which could confound dietary changes.

**What a critical reader would add:**

**No portion size data:** Frequency of consumption without portion sizes means we cannot estimate actual caloric or nutrient changes. Eating "vegetables 4–6 times per week" could mean a handful of lettuce or a full plate of broccoli.

**Social desirability bias:** Adolescents may have overreported healthy foods (fruits, vegetables) and underreported unhealthy foods (fried foods, sweets) — especially during a health crisis when "eating well" was a public health message.

**No objective validation:** No food diaries, no 24-hour recalls, no biomarkers (e.g., vitamin C for fruit intake, sodium for processed food intake).

**Short duration:** 6–10 weeks of confinement may not reflect long-term dietary changes. The "novelty" of lockdown (stockpiling, cooking at home, boredom) may have worn off after the study period.

**Age range is broad (10–19):** A 10-year-old's dietary autonomy is very different from a 19-year-old's. The study did not analyze results by age subgroups.

**No data on household food security:** Families who lost income may have reduced food variety or quantity, which would confound the "dietary change" measure.

**Single time point:** We don't know if these changes persisted after confinement ended.

**Industry funding:** The study was funded by public universities and research councils (no food industry funding declared), but the authors have no conflicts of interest to report.

For someone running their own n=1 experiment on how confinement or isolation affects your diet:

**What to test:**

The specific intervention: A period of forced home confinement (e.g., a 2-week staycation, a work-from-home period, or a planned isolation for a personal project). You cannot ethically lock yourself in your house, but you can simulate confinement by committing to no restaurant meals, no takeout, and no social eating for a set period.

The comparator: Your normal diet during a typical 2-week period with unrestricted access to restaurants, social eating, and normal routines.