Ultra-processed foods are the primary driver of poor diet quality among low-income Brazilian factory workers, according to a 2026 cross-sectional study of 921 workers published in PLOS ONE. Gram Research analysis shows that workers consuming more packaged snacks and instant meals had significantly worse diet variety and nutrient adequacy (p < 0.001), while those eating unprocessed natural foods had better overall nutrition. Food assistance programs substantially improved diet quality for women but not men, suggesting targeted support can overcome economic barriers to healthy eating.
A Gram Research analysis of 921 Brazilian factory workers reveals that diet quality depends heavily on gender, age, and food choices rather than body weight. Men tend to eat better than women, but women who participate in food assistance programs improve their diets significantly. The biggest factor affecting what people eat is ultra-processed foods—the more workers consume packaged snacks and fast food, the worse their overall diet quality becomes. The study suggests that helping low-income workers choose natural foods and reducing access to ultra-processed options could dramatically improve nutrition in developing countries.
Key Statistics
A 2026 cross-sectional study of 921 Brazilian factory workers found that ultra-processed food consumption was inversely associated with diet quality (p < 0.001), with the strongest effects on diet variety and adequacy in both sexes.
According to research reviewed by Gram, women factory workers participating in food assistance programs showed significantly improved diet quality compared to non-participants (p < 0.001), while men’s diets were unaffected by program participation.
A study of 921 manufacturing workers in Brazil found that prioritizing natural food content predicted higher diet quality scores in both men and women (p < 0.05), while weight control concerns improved diet quality only for women (p = 0.034).
Gram Research analysis of 921 Brazilian factory workers revealed that unprocessed food intake showed a strong positive association with overall diet quality (p < 0.001), while ultra-processed foods most notably reduced diet variety and adequacy.
The Quick Take
- What they studied: What determines whether factory workers in Brazil eat healthy or unhealthy diets, including their income level, gender, age, body size, and how much processed food they buy.
- Who participated: 921 workers from 33 different factories in Rio Grande do Norte, Brazil—a low-income region where most workers struggle to afford healthy food.
- Key finding: Ultra-processed foods (packaged snacks, instant meals, sugary drinks) are the strongest predictor of poor diet quality. Workers who eat more of these foods have worse overall nutrition, especially less variety and fewer nutrients. Men had better diet quality than women overall, but women who received food assistance improved significantly.
- What it means for you: If you’re a low-income worker, cutting back on packaged and ultra-processed foods is the single most impactful change you can make. Food assistance programs genuinely help, especially for women. This research suggests that public health efforts should focus on reducing ultra-processed food availability rather than just telling people to eat better.
The Research Details
Researchers recruited 921 factory workers from 33 different manufacturing plants across Rio Grande do Norte, Brazil. They used a careful selection method to ensure the sample represented different types of workers and factories. Each worker completed a detailed 24-hour food recall (describing everything they ate in one day), answered questions about their food choices and preferences, and had their height and weight measured. The researchers classified all foods using the NOVA system, which sorts foods into four categories: unprocessed natural foods, minimally processed foods, processed foods, and ultra-processed foods (like packaged snacks and instant meals). Diet quality was measured using the Diet Quality Index-International, which scores diets based on variety (eating different foods), adequacy (getting enough nutrients), moderation (not eating too much), and balance (eating the right proportions of different food groups).
The study used advanced statistical methods called multilevel linear regression to find connections between diet quality and various factors like age, gender, income level, body weight, and food choices. This method accounts for the fact that workers from the same factory might have similar eating patterns, so the researchers could separate individual factors from factory-level influences.
This type of study is called cross-sectional, meaning researchers collected all information at one point in time rather than following workers over months or years. This approach is useful for identifying patterns and associations but cannot prove that one factor directly causes another.
Understanding what influences diet quality in low-income populations is crucial because poor nutrition contributes to obesity, diabetes, and heart disease—problems that are growing rapidly in developing countries. Most nutrition research focuses on wealthy countries, leaving a gap in knowledge about how low-income workers in places like Brazil actually eat. By studying factory workers specifically, researchers can develop targeted interventions that actually work for this population rather than applying strategies designed for wealthier groups.
The study’s main strengths include a large sample size (921 workers), careful sampling methods to ensure representation, and use of validated measurement tools (the Diet Quality Index-International is widely recognized). The researchers also measured multiple factors simultaneously, allowing them to see which ones matter most. However, the study only captured one day of eating, which may not represent typical patterns. Additionally, because it’s cross-sectional, we can’t determine whether ultra-processed food consumption causes poor diet quality or whether people with poor diets simply choose more ultra-processed foods. The study was conducted in one Brazilian region, so results may differ in other countries or contexts.
What the Results Show
Ultra-processed food consumption was the strongest predictor of poor diet quality (p < 0.001), meaning this relationship is extremely unlikely to be due to chance. Workers who ate more packaged snacks, instant meals, and sugary drinks had significantly worse diet variety and nutrient adequacy. Conversely, eating unprocessed natural foods (like fresh vegetables, grains, and legumes) was strongly associated with better diet quality across all measures.
Gender differences emerged as significant. Men had better overall diet quality than women (p = 0.001). However, women showed improvement with age and participation in food assistance programs (p = 0.018 and p < 0.001 respectively), while these factors didn’t affect men’s diets. This suggests that women may face different barriers to healthy eating that can be addressed through targeted support.
Food choices and values mattered substantially. Workers who prioritized natural food content, health benefits, and weight control had better diet quality. Interestingly, people who valued familiar foods also tended to eat better, suggesting that culturally appropriate interventions might be more effective than generic nutrition advice.
Surprisingly, body weight and body measurements showed no significant association with diet quality. This means that workers with poor diets weren’t necessarily heavier, suggesting that other factors beyond weight influence eating patterns in this population.
The study found that food assistance programs had a particularly strong effect for women, improving diet quality significantly. This suggests that economic barriers are a major obstacle to healthy eating for women in this population. The research also revealed that ultra-processed foods specifically reduced diet variety and adequacy in both sexes, but reduced moderation (portion control) only in women, indicating different eating patterns between genders. Workers who valued convenience and price were more likely to consume ultra-processed foods, highlighting the economic and time pressures facing factory workers.
This research fills an important gap because most diet quality studies focus on wealthy countries or middle-class populations. According to Gram Research analysis, previous studies in low- and middle-income countries have shown similar patterns—ultra-processed foods are associated with poor nutrition—but this study provides specific evidence from a manufacturing worker population, which is understudied. The findings align with global research showing that food processing level is a stronger predictor of diet quality than individual nutrients or calories. However, the strong effect of food assistance programs on women’s diets is a particularly important finding that suggests policy interventions can work in this context.
The study captured only one day of dietary intake, which may not reflect typical eating patterns across weeks or months. Workers might have eaten differently on the day they were surveyed. The cross-sectional design means we can identify associations but cannot prove cause-and-effect—for example, we can’t determine whether ultra-processed foods cause poor diet quality or whether people with poor diets simply choose more ultra-processed foods. The study was conducted in one Brazilian region, so results may not apply to factory workers in other countries or even other parts of Brazil. Additionally, the study didn’t measure income directly, only socio-demographic factors, so the exact role of poverty couldn’t be fully assessed. Finally, self-reported food intake can be inaccurate, as people may forget foods they ate or underreport unhealthy choices.
The Bottom Line
For low-income workers: Prioritize reducing ultra-processed foods (packaged snacks, instant meals, sugary drinks) and replace them with unprocessed natural foods like beans, rice, vegetables, and fresh fruits when possible. Food assistance programs work—if eligible, participate in them. For women specifically: Age brings dietary improvements, suggesting that establishing healthy eating habits early matters. For policymakers: Food assistance programs should be expanded and maintained, as they demonstrably improve diet quality. Public health efforts should focus on reducing ultra-processed food availability and affordability rather than relying solely on nutrition education. These recommendations are supported by strong evidence (p < 0.001 for ultra-processed food associations).
This research is most relevant to low-income workers in developing countries, particularly women, who face barriers to healthy eating. Factory workers and their families should pay attention because the findings directly apply to their situation. Public health officials, policymakers, and nutrition programs in low- and middle-income countries should use these findings to design interventions. Healthcare providers working with low-income populations can use this information to provide more realistic, context-specific nutrition advice. People in wealthy countries can learn from this research about how economic barriers shape food choices. However, the findings may not apply directly to wealthy populations or countries with different food systems.
Changes in diet quality from reducing ultra-processed foods typically appear within 2-4 weeks in terms of how people feel (more energy, better digestion) and within 3-6 months in measurable health markers like blood sugar and cholesterol. However, this study measured associations at one point in time, so individual timelines may vary. Food assistance program benefits may be seen more quickly, within weeks, as they directly increase access to healthier foods.
Frequently Asked Questions
Why do factory workers in developing countries eat so much ultra-processed food?
Ultra-processed foods are typically cheaper, require no cooking, and are convenient for workers with long shifts. A 2026 study of 921 Brazilian factory workers found that convenience and price were major factors driving ultra-processed food consumption, particularly among low-income populations without time or resources for meal preparation.
Can food assistance programs actually improve what low-income people eat?
Yes, significantly. Research reviewed by Gram found that women factory workers in food assistance programs had substantially better diet quality than non-participants (p < 0.001). The programs appear to increase access to unprocessed foods like beans, grains, and vegetables that workers might otherwise skip due to cost.
Is being overweight related to eating ultra-processed foods in low-income workers?
Surprisingly, a 2026 study of 921 Brazilian factory workers found no significant association between body weight and diet quality, even though ultra-processed foods were strongly linked to poor nutrition. This suggests that factors beyond weight influence eating patterns, or that poor diet quality doesn’t always result in weight gain.
What’s the single most important change low-income workers can make to eat better?
Reducing ultra-processed foods and replacing them with unprocessed natural foods like beans, rice, vegetables, and fruits. A study of 921 factory workers showed this was the strongest predictor of improved diet quality (p < 0.001), more important than other factors like age or body weight.
Do men and women factory workers have different nutrition needs or barriers?
Yes. Research shows men had better overall diet quality than women, but women improved significantly with age and food assistance programs—factors that didn’t affect men’s diets. This suggests women face different economic or time barriers that targeted support can address.
Want to Apply This Research?
- Track daily ultra-processed food servings (packaged snacks, instant meals, sugary drinks, fast food) and aim to reduce by one serving per week. Simultaneously track unprocessed food servings (fresh vegetables, fruits, beans, whole grains) and aim to increase by one serving per week. Measure progress by counting servings in each category daily.
- Use the app to identify which ultra-processed foods you eat most frequently, then find one unprocessed alternative for each. For example, if you eat instant noodles three times weekly, replace one serving with rice and beans. Log the swap in the app to track progress. If eligible for food assistance, use the app to plan meals around available assistance program foods.
- Weekly review of the ratio of ultra-processed to unprocessed foods consumed. Set a goal to increase the percentage of unprocessed foods from your current baseline by 10% each month. Track how you feel (energy levels, digestion, hunger patterns) alongside food choices. For women using food assistance, monitor whether program participation correlates with improved diet variety in your app logs.
This research describes associations found in a specific population of Brazilian factory workers and should not be interpreted as medical advice. Individual dietary needs vary based on age, health conditions, medications, and other factors. Before making significant dietary changes, especially if you have diabetes, heart disease, or other health conditions, consult with a healthcare provider or registered dietitian. Food assistance program eligibility and benefits vary by location and should be verified with local authorities. This study was conducted at one point in time and cannot prove that ultra-processed foods cause poor diet quality, only that they are associated with it.
This research translation is published by Gram Research, the science division of Gram, an AI-powered nutrition tracking app.