Nutrola's 2026 User Nutrition Report: What 2 Million Users Actually Eat

Every day, more than 2 million people open Nutrola and log what they eat. They photograph their plates, scan barcodes, speak meals into their phones, and manually search a verified food database of over 12 million entries. The result is one of the largest real-world nutrition datasets in existence, spanning 195 countries, every age group, and virtually every dietary pattern.

This is our 2026 Annual User Nutrition Report. Drawing on anonymized, aggregated data collected between January 1, 2025, and February 28, 2026, it provides a detailed picture of what people actually consume, where the gaps are, and which habits are associated with the best outcomes. No self-reported surveys. No 24-hour recall bias. Just logged meals, tracked nutrients, and measured results.

Executive Summary

The data tells a clear story. Most users consume enough calories, but the composition of those calories leaves significant room for improvement. Protein intake falls short of recommendations for the majority of users over 40. Fiber remains chronically low across every demographic. Vitamin D, magnesium, and potassium deficiencies are widespread, with more than half of all users falling below the Recommended Dietary Allowance for at least one of these micronutrients.

On the positive side, users who track consistently, defined as five or more days per week, lose significantly more weight than sporadic trackers. High-protein diets have overtaken keto as the most popular dietary pattern. And year-over-year, average fiber intake has risen for the first time in the three years we have been publishing this report.

Here are the key findings at a glance:

• Average daily calorie intake: 2,114 kcal (all users)
• Most logged food: chicken breast (logged 14.2 million times)
• Most common deficiency: Vitamin D (68% of users below RDA)
• Average protein intake: 89 g/day (vs. 105 g recommended for average user weight)
• Weekend calorie surplus: +347 kcal on average compared to weekdays
• Users tracking 6-7 days/week lost 3.1x more weight than those tracking 1-2 days
• Top diet trend: high-protein (followed by 22% of users with a declared diet type)

Average Daily Intake by Gender and Age Group

The table below shows mean daily nutrient intake across our user base, segmented by gender and age group. All figures represent the arithmetic mean of daily totals logged during the reporting period.

Female Users

Age Group	Calories (kcal)	Protein (g)	Carbs (g)	Fat (g)	Fiber (g)	Sodium (mg)	Sugar (g)
18-24	1,842	72	224	68	16.2	2,480	62
25-34	1,894	79	218	72	17.8	2,390	58
35-44	1,826	76	208	70	18.4	2,310	54
45-54	1,762	71	198	68	17.1	2,280	51
55-64	1,688	65	192	64	17.6	2,190	48
65+	1,594	58	184	60	16.8	2,040	45

Male Users

Age Group	Calories (kcal)	Protein (g)	Carbs (g)	Fat (g)	Fiber (g)	Sodium (mg)	Sugar (g)
18-24	2,384	104	278	88	19.4	3,210	71
25-34	2,462	112	272	94	20.6	3,140	66
35-44	2,348	106	258	90	20.2	3,020	61
45-54	2,218	96	244	86	19.1	2,890	57
55-64	2,098	86	232	80	18.8	2,740	52
65+	1,942	74	218	74	17.9	2,580	47

Several patterns stand out. Protein intake peaks in the 25-34 age group for both genders and declines steadily with age, precisely when maintaining muscle mass becomes most critical. Fiber intake fails to reach the recommended 25 g/day (female) or 38 g/day (male) in any demographic group. Sodium exceeds the 2,300 mg guideline for every male age group and for females under 35.

Most Logged Foods: Top 20

The following table lists the 20 most frequently logged food items across all Nutrola users during the reporting period. Frequency counts reflect individual log entries, not unique users.

Rank	Food Item	Times Logged	Avg. Serving Size
1	Chicken breast	14,200,000	152 g
2	Eggs	12,800,000	2 large
3	Rice (white)	11,400,000	186 g (cooked)
4	Banana	10,900,000	1 medium
5	Coffee (black)	9,600,000	240 ml
6	Oats / oatmeal	8,700,000	78 g (dry)
7	Bread (whole wheat)	7,900,000	2 slices
8	Greek yogurt	7,400,000	170 g
9	Apple	6,800,000	1 medium
10	Milk (whole or semi-skimmed)	6,200,000	244 ml
11	Pasta (cooked)	5,800,000	200 g
12	Avocado	5,500,000	0.5 fruit
13	Sweet potato	5,100,000	150 g
14	Salmon	4,700,000	140 g
15	Ground beef (lean)	4,400,000	130 g
16	Broccoli	4,100,000	91 g
17	Peanut butter	3,900,000	32 g
18	Protein shake / powder	3,700,000	1 scoop (30 g)
19	Almonds	3,400,000	28 g
20	Cheddar cheese	3,200,000	28 g

Chicken breast and eggs have held the top two positions for three consecutive years. The biggest mover was protein shake/powder, which climbed from 24th in 2025 to 18th in 2026, reflecting the broader shift toward high-protein eating patterns. Sweet potato also rose significantly, jumping from 19th to 13th, likely driven by its popularity in meal-prep communities.

Most Common Nutrient Deficiencies

Nutrola tracks over 100 nutrients. By comparing each user's average daily intake against their age- and gender-specific RDA, we can identify widespread deficiency patterns. The table below shows the percentage of users whose average daily intake falls below the RDA for each nutrient.

Nutrient	% of Users Below RDA	Average Intake	RDA (Adult Average)	Shortfall
Vitamin D	68%	11.2 mcg	15 mcg	-25%
Potassium	62%	2,640 mg	3,400 mg	-22%
Magnesium	58%	298 mg	400 mg	-26%
Fiber	56%	18.6 g	28 g (avg)	-34%
Calcium	41%	892 mg	1,000 mg	-11%
Iron	34%	14.8 mg	18 mg (female) / 8 mg (male)	varies
Vitamin B12	19%	3.8 mcg	2.4 mcg	+58% (mean is adequate; issue is concentrated in plant-based dieters)

Vitamin D deficiency is the most pervasive issue in our dataset. Nearly seven in ten users fail to meet the RDA through diet alone, a finding consistent with population-level studies published by the NIH and WHO. Potassium and magnesium follow closely. Fiber, despite being the most discussed of these nutrients, remains 34% below recommendations on average.

The B12 finding deserves a note. While the overall mean exceeds the RDA, the deficiency is concentrated: 71% of users self-identifying as vegan fall below the B12 threshold, compared to just 6% of omnivores. This highlights why aggregate averages can mask important subgroup patterns.

Iron deficiency is most prevalent among women aged 18-44 (48% below RDA), while men in all age groups generally exceed the RDA.

The Protein Gap

Protein has become the most discussed macronutrient in popular nutrition, and our data shows that awareness has not yet translated into adequate intake for many users. We calculated each user's recommended protein intake using 1.2 g per kilogram of body weight, a moderate target supported by current literature for active adults.

Demographic	Avg. Body Weight (kg)	Recommended Protein (g)	Actual Avg. Intake (g)	Gap (g)	Gap (%)
Female 18-34	66	79	76	-3	-4%
Female 35-54	71	85	74	-11	-13%
Female 55+	69	83	62	-21	-25%
Male 18-34	82	98	108	+10	+10%
Male 35-54	86	103	101	-2	-2%
Male 55+	83	100	80	-20	-20%

Young men are the only group consistently exceeding protein targets. Women over 55 and men over 55 face the largest protein gaps, at 25% and 20% below recommended levels, respectively. This is concerning because sarcopenia, the age-related loss of muscle mass, accelerates precisely in these demographics. Higher protein intake, combined with resistance training, is one of the strongest evidence-based interventions to slow muscle loss in older adults.

Among users who identified a fitness goal, those targeting muscle gain consumed an average of 132 g of protein per day, while those focused on weight loss averaged 94 g. Users with no declared goal averaged 82 g.

Meal Timing Patterns

Nutrola timestamps every meal entry, giving us granular data on when people eat across different time zones. After normalizing for local time, clear patterns emerge.

Peak meal times across all users:

• Breakfast: 7:00-8:00 AM (38% of breakfast entries fall in this window)
• Lunch: 12:00-1:00 PM (44% of lunch entries)
• Dinner: 6:00-7:00 PM (36% of dinner entries)
• Late-night snacking (after 9:00 PM): 23% of users log at least one snack after 9 PM on any given day

The most concentrated meal is lunch, with nearly half of all lunch entries occurring in a single hour. Breakfast is the most skipped meal: 31% of users log fewer than four breakfasts per week. Dinner has the widest distribution, with meaningful entry volume from 5:00 PM through 9:00 PM.

Late-night snacking is more common than many users might expect. The 23% figure represents users who log after 9 PM; actual prevalence may be higher, as nighttime eating is among the most under-reported behaviors in food logging research. The most common late-night logged items are fruit, yogurt, nuts, cereal, and ice cream, in that order.

Users who log no meals after 8:30 PM consume an average of 187 fewer calories per day than users who routinely snack late. While this is a correlation, not a causal finding, it aligns with time-restricted eating research showing metabolic benefits of earlier eating windows.

Weekend vs. Weekday Eating

One of the most consistent findings in our data, year after year, is the weekend calorie surplus. Users eat more on Saturdays and Sundays, and the composition of those extra calories skews toward fat and alcohol.

Day Type	Avg. Calories	Avg. Protein (g)	Avg. Carbs (g)	Avg. Fat (g)	Avg. Alcohol (g)
Weekday (Mon-Fri)	2,024	88	234	76	4.2
Weekend (Sat-Sun)	2,371	86	262	94	12.8
Difference	+347	-2	+28	+18	+8.6

The average weekend surplus is 347 calories per day, which amounts to approximately 694 extra calories over the weekend. That is equivalent to roughly 0.09 kg of fat tissue per week if not offset by additional activity or weekday restriction. Over a year, an uncompensated weekend surplus of this size translates to approximately 4.7 kg of fat gain.

Notably, protein intake actually dips slightly on weekends. The extra calories come almost entirely from additional carbohydrates (often restaurant meals, baked goods, and snacks), higher fat intake, and a threefold increase in alcohol consumption. Saturday shows a higher calorie surplus than Sunday in our data (average +382 kcal on Saturday vs. +312 kcal on Sunday).

Diet Trend Data

Nutrola allows users to optionally declare a dietary pattern or goal. Among the 1.24 million users who have set a diet preference, the following distribution emerged:

Diet Type	% of Users	Avg. Daily Calories	Avg. Protein (g)	Avg. Carbs (g)	Avg. Fat (g)
High-protein	22%	2,186	142	198	74
Intermittent fasting	18%	1,864	86	204	72
Mediterranean	14%	2,048	88	238	82
Keto / low-carb	12%	1,892	98	48	128
Calorie counting (no specific pattern)	11%	1,946	84	228	74
Vegan / plant-based	8%	1,812	68	248	62
Paleo	5%	2,098	118	148	96
Whole30 / elimination	3%	1,924	104	162	82
Other	7%	2,012	90	224	78

High-protein has overtaken keto as the most popular declared diet type among Nutrola users, rising from 16% in 2025 to 22% in 2026. Keto, which held the top position in our 2024 report, has declined from 18% to 12%. Intermittent fasting remains stable at 18%. The Mediterranean diet continues to grow slowly but steadily, up from 11% to 14%.

Vegan and plant-based users represent 8% of those with a declared diet type. Their average protein intake (68 g) is the lowest of any group, and as noted in the deficiency section, this group faces elevated B12 risk. However, their fiber intake leads all groups at 28.4 g/day, the only dietary pattern whose adherents meet the average fiber RDA.

Tracking Consistency and Weight Loss Results

Among users who logged body weight data alongside food entries for at least 12 continuous weeks, we measured the relationship between tracking frequency and weight change. The results strongly favor consistency.

Days Tracked Per Week	Avg. Users in Group	Avg. Weight Change (12 wk)	% Who Lost Weight	Avg. kg Lost (among losers)
1-2 days	148,000	-0.4 kg	38%	-1.2 kg
3-4 days	224,000	-1.3 kg	54%	-2.4 kg
5-6 days	312,000	-2.8 kg	71%	-3.9 kg
7 days	186,000	-3.6 kg	78%	-4.6 kg

Users who tracked every day lost an average of 3.6 kg over 12 weeks, compared to just 0.4 kg for those tracking 1-2 days per week. The percentage of users who achieved any weight loss rose from 38% in the least consistent group to 78% among daily trackers. This represents a 3.1x difference in average weight loss between the most and least consistent groups.

We recognize that this is correlational data. Users who track daily may also be more motivated, more disciplined in their food choices, or more engaged with their health overall. However, the gradient is consistent and strong, and it aligns with published clinical research showing that self-monitoring frequency is one of the strongest predictors of weight management success.

Regional Differences in Daily Nutrition

Nutrition patterns vary substantially by region. The following table shows average daily macronutrient intake for users in four major regions.

Region	Avg. Calories (kcal)	Protein (g)	Carbs (g)	Fat (g)	Fiber (g)	Top Logged Food
North America	2,218	96	248	86	17.2	Chicken breast
Europe	2,064	84	232	82	20.4	Eggs
Asia-Pacific	1,986	78	268	62	16.8	Rice (white)
Latin America	2,142	82	258	78	19.6	Rice (white)

North American users consume the most calories and protein on average, driven in part by higher meat consumption and protein supplement use. European users have the highest fiber intake among the four regions (20.4 g/day), likely reflecting higher consumption of whole grains, legumes, and vegetables. Asia-Pacific users eat the most carbohydrates relative to total intake (54% of calories from carbs) and the least fat (28% of calories), consistent with rice-centric dietary patterns. Latin American users fall in the middle across most metrics, with rice appearing as their most logged food as well.

The protein disparity between North America (96 g) and Asia-Pacific (78 g) is notable but narrows significantly when adjusted for average body weight. Per kilogram of body weight, North American users average 1.12 g/kg versus 1.04 g/kg for Asia-Pacific users.

Year-over-Year Trends: 2025 vs. 2026

Comparing this year's data to our 2025 report reveals several meaningful shifts in user nutrition behavior.

Metric	2025	2026	Change
Avg. daily calories	2,098	2,114	+0.8%
Avg. daily protein	84 g	89 g	+6.0%
Avg. daily fiber	17.4 g	18.6 g	+6.9%
Avg. daily sodium	2,780 mg	2,720 mg	-2.2%
Avg. daily sugar	61 g	57 g	-6.6%
Users below Vitamin D RDA	72%	68%	-4 pp
Users below fiber RDA	61%	56%	-5 pp
Weekend calorie surplus	+362 kcal	+347 kcal	-15 kcal
Avg. days tracked/week	4.1	4.4	+0.3 days
Most popular diet type	Keto (18%)	High-protein (22%)	shift

The most encouraging trends are the increases in protein (+6.0%) and fiber (+6.9%) intake. Both nutrients were chronically under-consumed in prior years, and while they remain below recommendations for most users, the direction is positive. Sugar consumption dropped by 6.6%, and sodium fell modestly by 2.2%.

Tracking consistency improved from 4.1 to 4.4 days per week on average, suggesting that users are building stronger logging habits over time. Features introduced by Nutrola in 2025, including voice-based meal logging and improved AI photo recognition accuracy, may have contributed to this increase by reducing friction in the logging process.

The shift from keto to high-protein as the most popular declared diet aligns with broader cultural trends favoring protein-centric nutrition without strict carbohydrate restriction.

Key Takeaways for the General Public

Based on the data presented in this report, here are the most actionable findings for anyone trying to improve their nutrition:

1. Most people do not eat enough protein after age 40. The protein gap widens significantly with age, especially for women. Prioritizing protein at every meal becomes increasingly important in midlife and beyond to preserve muscle mass and support metabolic health.

2. Fiber is the most under-consumed nutrient relative to recommendations. At 34% below the RDA on average, fiber deficiency is nearly universal in our dataset. Increasing intake of vegetables, legumes, whole grains, and fruit is the simplest intervention with the broadest impact.

3. Vitamin D, magnesium, and potassium are the most common micronutrient gaps. These deficiencies are difficult to close through diet alone without deliberate food choices. Fatty fish, fortified foods, leafy greens, nuts, seeds, and potassium-rich produce (bananas, potatoes, avocados) can help.

4. Weekends undermine weekday discipline. A 347-calorie daily surplus on weekends erases a meaningful portion of a weekday deficit. Awareness of this pattern is the first step toward managing it.

5. Consistency matters more than perfection. The strongest predictor of weight loss success in our data is tracking frequency. Users do not need to eat perfectly; they need to track regularly. Even moving from 3 days to 5 days per week was associated with more than doubling average weight loss.

6. High-protein eating is the dominant dietary trend of 2026. Protein-forward approaches have overtaken keto and continue to grow. This shift is supported by the data: high-protein users show the strongest adherence rates and the most favorable body composition changes.

Methodology Note

All data presented in this report was collected from Nutrola app users who opted in to anonymized data sharing. Individual user data was never accessed, reviewed, or shared. All analyses were performed on aggregated, de-identified datasets.

Meals were logged via Nutrola's AI photo recognition (Snap & Track), barcode scanning, voice logging, or manual search within our verified food database of over 12 million entries. Entries flagged as physiologically implausible (single-meal entries below 20 kcal or above 5,000 kcal) were excluded from analysis. Nutrient intake was calculated using Nutrola's database, which sources data from USDA FoodData Central, national food composition databases, and manufacturer-provided nutrition facts.

Body weight data was included only from users who logged weight at least once per week for 12 or more consecutive weeks. RDA comparisons use values published by the National Institutes of Health Office of Dietary Supplements, adjusted for age and gender.

No individual-level data is shared with any third party. This report is published for educational purposes and to contribute to the public understanding of real-world nutrition patterns. For questions about data methodology, contact research@nutrola.com.

FAQ

How was the data in this report collected?

All data comes from anonymized, aggregated meal and nutrient logs submitted by Nutrola users who opted in to data sharing. Users log meals through AI photo recognition, barcode scanning, voice input, or manual search across Nutrola's verified database of over 12 million food entries. No individual user data was accessed or shared. The dataset covers the period from January 2025 through February 2026 and includes inputs from more than 2 million active users globally.

What does it mean that 68% of users are deficient in Vitamin D?

This means that 68% of Nutrola users have an average daily dietary intake of Vitamin D that falls below the Recommended Dietary Allowance (RDA) of 15 mcg. It is important to note that this reflects dietary intake only. Many people obtain Vitamin D through sun exposure or supplementation, which are not captured in food logs. The figure highlights how difficult it is to meet Vitamin D needs through food alone.

Does tracking more days per week actually cause more weight loss?

Our data shows a strong correlation between tracking frequency and weight loss, but we cannot confirm a causal relationship from observational data alone. Users who track daily may also be more motivated or make more deliberate food choices. That said, the association is consistent, large in magnitude, and aligns with published clinical research identifying self-monitoring as one of the strongest behavioral predictors of successful weight management.

Why is the protein gap larger for older adults?

Two factors contribute. First, appetite and total food intake tend to decline with age, which reduces protein consumption along with overall calorie intake. Second, older adults are less likely to prioritize protein-rich foods or use protein supplements compared to younger users. This is particularly concerning because protein needs may actually increase with age due to reduced efficiency of muscle protein synthesis. Current evidence supports a minimum of 1.0-1.2 g of protein per kilogram of body weight per day for adults over 55.

How does Nutrola determine if a user is following a specific diet?

Diet type is self-declared by users who choose to set a dietary preference in the app. Nutrola does not algorithmically assign diet labels. Users can select from preset options (keto, Mediterranean, high-protein, vegan, intermittent fasting, etc.) or enter a custom label. The percentages in this report reflect only the 1.24 million users (approximately 62% of the total user base) who have actively set a diet preference. Users without a declared preference are excluded from diet-type breakdowns.

Can I access my own nutrition data compared to these averages?

Yes. Nutrola's Insights dashboard shows your personal averages for all tracked nutrients alongside population benchmarks. You can view how your intake compares to users of the same age, gender, and activity level. This feature is available to all users, including those on the free plan. Nutrola tracks over 100 nutrients, giving you a comprehensive view of your dietary patterns beyond just calories and macros.