Research design and instrument

This study utilized a cross-sectional design to investigate the enablers and barriers towards adopting a plant-based diet among selected Filipino adults in Metro Manila, Philippines. The use of a cross-sectional design was deemed appropriate as it enables the systematic collection and analysis of data at a single point in time, providing a comprehensive snapshot.

The research instrument was adapted from the study of Reipurth et al. [38] and van den Berg et al. [39]. It was designed to evaluate factors that facilitate or hinder the adoption of a plant-based diet and included items related to demographic characteristics, food consumption, and attitudes toward plant-based food consumption. The original instrument, evaluated by a food science and nutrition expert, was adapted to better suit the local context. The updated version was then tested for reliability. The reliability statistics yielded a Cronbach’s alpha of 0.85, indicating a high internal consistency of the items and suggesting that the questionnaire reliably measures the intended constructs. The study employed the Capability, Opportunity, and Motivation Behavior (COM-B) model [40] to guide the identification of consumers’ intentions toward shifting to a plant-based diet, focusing particularly on the role of attitudes as a key component influencing behavior change.

Research participants

Participants in the study were selected based on specific inclusion and exclusion criteria. To be eligible, individuals had to be Filipino citizens residing in Metro Manila for at least one year. They also needed to be responsible for purchasing food or planning meals within their household and be at least 18 years of age. Both sexes were included to capture diverse perspectives. Individuals from various socioeconomic backgrounds and districts within Metro Manila were considered to reflect the heterogeneity of the urban population. Individuals who did not meet any of these inclusion criteria were excluded from the study. Demographic information, including age, sex, educational attainment, income level, and household size, was collected.

Data collection and ethical considerations

Data were collected using an online survey platform. A QR code linking to the survey was displayed in major markets and grocery stores within the study area to encourage participation. Participants were informed about the purpose of the study and gave their informed consent voluntarily. They were assured of their right to withdraw at any time and were encouraged to respond with honesty. The study upheld ethical standards related to anonymity and confidentiality. Personal identifiers were excluded from the data, and information collected was used solely for the purposes of this research. After completion of the study, all data were properly disposed of in accordance with ethical research practices. Incomplete survey responses were not included in the data analysis and were permanently deleted from the system to ensure data integrity and participant confidentiality.

Data analysis

Sociodemographic characteristics, including gender, age, educational attainment, household size, and monthly household income, were analyzed using frequencies and percentages. A chi-square test of independence was conducted to examine associations between sociodemographic variables and food consumption clusters, with a significance level set at p < 0.05. Additionally, segmentation of respondents into food consumption clusters was conducted using Python’s stats models module. Logistic regression analysis was performed to compute odds ratios (ORs), identifying the likelihood of belonging to specific consumption clusters based on demographic variables.

Food consumption clusters

Respondents were segmented into food consumption clusters based on frequency of intake of red meat, white meat, fish, mollusks and crustaceans, fruits and vegetables, and grains and legumes by applying the k-means clustering method implemented using Python statsmodels module. The clustering resulted in four segments identified as (1) high meat-high plant cluster, (2) high meat-low plant cluster, (3) low meat-low plant cluster, and (4) low meat-high plant cluster. The segmentation of respondents into food consumption clusters and the median frequency of intake of red meat, white meat, fish, mollusks and crustaceans, fruits and vegetables, and grains and legumes are presented in Table 1.

As visualized in the radar chart in Figure 1, the high meat-high plant cluster exhibited the most diverse and frequent consumption across all food categories, with median intake frequencies of 5–6 for meat, fish, fruits, and grains. This suggests a balanced but high-volume dietary pattern, potentially associated with higher caloric intake and broader food variety.

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Figure 1. Dietary profile by food consumption cluster. Food product consumption: 1 = never or about less than once a month, 2 = 1–3 times per month, 3 = once a week, 4 = 2–4 times a week, 5 = 5–7 times a week, 6 = 2–3 times a day, 7 = 4 or more times per day.

The high meat-low plant cluster consumed moderate amounts of animal-based foods (median 4) but reported lower intake of plant-based items (median 4 or less), indicating a meat-centered dietary profile with reduced fiber and micronutrient diversity. In contrast, the low meat-low plant cluster reported the lowest overall consumption frequencies across all food categories (medians 2–3), which may reflect minimal dietary variety intake patterns.

The low meat-high plant cluster stood out for its higher consumption of plant-based foods—particularly grains and legumes (median = 6) and fruits and vegetables (median = 5)—despite moderate intake of animal proteins. This cluster aligns closely with plant-forward, suggesting a shift toward healthier or more sustainable eating patterns.

Sociodemographic characteristics

Sociodemographic characteristics—gender, age, educational attainment, household size, and monthly household income—were analyzed with frequencies and percentages for the total sample and by food consumption clusters, and the results of the chi-square test of independence are presented in Table 2. According to the result, food consumption has no significant association with gender, age, educational attainment, location, or household size. However, there is a significant association between monthly household income and food consumption, χ²(18, N = 427) = 31.40, p = 0.03.

The study sample comprised 427 participants, of whom 64.64% were female, and 35.36% were male. The age distribution was predominantly skewed toward younger adults, with 69.79% of participants aged 18–25 years. Regarding educational attainment, nearly half of the sample were college undergraduates (49.41%), followed by college graduates (31.62%). Household composition varied, with approximately 50% of participants residing in households of more than five members.

Intentions towards a diet change

Participant intentions towards diet change were analyzed for the total sample and by food consumption cluster using percentages and frequencies. The results of the frequency and percentage analysis of intentions toward diet change, both overall and by food cluster, are presented in Table 3, while Figure 2 provides a visual summary of the overall data.

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Figure 2. Intentions towards a diet change among all participants.

Overall, the most common intention for meat products was to reduce intake, with 39.34% of respondents indicating they would like to eat less meat. Conversely, the most common intention for plant products or plant-based foods was to increase intake (54.10%), while the majority considered their fish, dairy, and egg consumption to be appropriate. Differences emerged when comparing dietary clusters. In the high meat-high plant cluster, most participants (40.30%) felt their meat intake was appropriate, and only 31.34% expressed a desire to reduce it. A large proportion also wanted to eat more plant products or plant-based foods (53.73%). The high meat-low plant group showed similar trends, though a slightly smaller portion (15.38%) wanted to increase meat intake, and 58.46% wished to eat more plant products or plant-based foods, despite lower baseline consumption. The low meat-low plant cluster reported the highest proportion of people wanting to reduce meat intake (37.61%) and the highest share wanting to reduce fish (17.43%) and dairy (33.03%). Notably, this cluster also had the largest share wanting to exclude certain foods entirely, particularly fish and plant products or plant-based foods. The low meat-high plant group had the highest percentage of respondents wanting to reduce meat intake (47.11%) and the highest intention to increase plant products or plant-based foods (66.94%), reflecting a strong inclination toward a more plant-based dietary pattern.

ORs of belonging to the food consumption clusters were determined using logistic regression. The dependent variable was the food consumption cluster, while the independent variable was the intention towards diet change for each food product category. For each food consumption cluster, a confidence interval (CI) of the OR was calculated. A higher OR value indicates that respondents who have higher intentions to exclude or reduce the food product category from their diet are more likely to belong to a particular cluster. A CI entirely above or below 1 indicates that 95% of the time, the OR is significant.

ORs of belonging to the food consumption clusters by intentions towards diet change are presented in Table 4. Those who have higher intentions to exclude or reduce their consumption of meat products have significantly low odds of belonging to the high meat-high plant cluster, OR = 0.69, 95% CI: 0.51–0.94, and the low meat-low plant cluster, OR = 0.74, 95% CI: 0.58–0.95. Those who have higher intentions to exclude or reduce their consumption of dairy products have significantly low odds of belonging to the low meat-low plant cluster, OR = 0.78, 95% CI: 0.61–1.00. Those who have higher intentions to exclude or reduce their consumption of plant-based food have significantly low odds of belonging to the low meat-high plant cluster, OR = 0.67, 95% CI: 0.52–0.86, and significantly high odds of belonging to the low meat-low plant cluster, OR = 1.39, 95% CI: 1.13–1.72.

Intention towards shifting to a plant-based diet

ORs of intention towards shifting to a plant-based diet were determined using logistic regression. The dependent variable was the intention to shift to a plant-based diet, while the independent variables were the statements of attitudes. A CI of the OR was calculated. A higher OR value indicates that respondents who agree with the statement are more likely to have an intention to shift to a plant-based diet. A CI entirely above or below 1 indicates that 95% of the time, the OR is significant.

Table 5 presents the ORs of individuals’ intentions to shift toward a plant-based diet, analyzed through the lens of the COM-B model. The findings provide important behavioral insights. Interestingly, individuals who find it easy to prepare meals with smaller meat portions (physical capability) have significantly lower odds of intending to shift to a plant-based diet (OR = 0.72, 95% CI: 0.53–0.97). This counterintuitive result may indicate that reducing meat intake alone might give individuals a sense of partial achievement, thereby reducing motivation dietary shift. Similarly, those who perceive that preparing plant-based meat alternatives (PBMAs) takes too much time (physical opportunity) are significantly less likely to intend a dietary shift (OR = 0.71, 95% CI: 0.53–0.95), emphasizing the practical barrier of time and effort in daily food preparation.

In contrast, psychological capability plays a facilitating role: individuals who know how to replace meat in dishes with plant-based alternatives have significantly higher odds of intending to shift (OR = 1.37, 95% CI: 1.04–1.80), highlighting the importance of cooking knowledge and food literacy. Similarly, reflective motivation, as seen in those who enjoy trying vegetarian dishes, increases the likelihood of a shift (OR = 1.56, 95% CI: 1.14–2.14), suggesting that openness to new food experiences is a key enabler.

The social opportunity yields mixed effects. Those who feel they can independently decide whether to eat meat have higher odds of shifting (OR = 1.43, 95% CI: 1.03–1.99), reflecting the role of autonomy in dietary change. However, those who perceive that people around them are eating less meat have lower odds of intending to shift (OR = 0.73, 95% CI: 0.56–0.95). This may point to social normalization of meat reduction, leading some individuals to feel less urgency or personal responsibility to change, suggesting a diffusion of accountability within social groups.

Sociodemographic factors

Monthly household income showed a significant association with food consumption clusters. This finding aligns with Guenther et al. (2005) [41], who revealed that sociodemographic factors broadly predict food choices, but contradicts their emphasis on multiple factors beyond income. Additionally, in the Philippine context, households experiencing food insecurity, often linked to low income, consume inadequate nutrients, supporting the relevance of income as a key determinant [42]. International evidence also corroborates this pattern, where the International Food Information Council [43] reported that in the United States, higher-income consumers are more likely to adopt plant-based alternatives, a trend also observed in India, where consumers with more financial flexibility are willing to pay a premium for plant-based products [44]. However, studies in Europe noted that consumers perceive plant-based products as too expensive, and price or income had no significant effect on purchasing decisions, suggesting regional variations in the impact of income [45]. In the Philippines, PBMAs generally have higher costs per gram of protein compared to traditional animal-based meats. This suggests that, despite the growing availability of PBMAs, affordability may remain a barrier to wider adoption. Income, therefore, becomes a significant determinant of consumption, as higher-income consumers are more able to access these products [46].

The economic theory of consumer choice may help explain this finding, where individuals maximize utility based on budget constraints; those with higher income can afford broader food choices, including healthier or alternative options. Additionally, according to Maslow’s hierarchy of needs, only when basic needs such as food security are met can individuals prioritize health, sustainability, or ethical food considerations in their food choices [47, 48]. The implication of this finding is twofold. For theory, it underscores the need to refine food choice models to account for income as a dominant factor, especially in low- to middle-income settings [49, 50]. For practice, it suggests that policies aimed at improving food consumption quality should prioritize income-based interventions, such as subsidies or social protection for low-income households, rather than solely focusing on awareness campaigns or education [51–53].

Intentions towards diet change

There is a general trend toward decreasing meat consumption and increasing plant-based food intake across different dietary clusters, though motivations and intentions vary depending on current eating patterns. The most common intention regarding meat was to reduce consumption, while for plant-based foods, it was to increase intake. This may signal a broader shift toward sustainable or health-driven dietary motivations. In contrast, most people viewed their consumption of fish, dairy, and eggs as appropriate.

Multiple factors contribute to the shift from animal-based to plant-based diets [54, 55]. Among the most prominent motivators are health considerations, as individuals often associate plant-based eating with a reduced risk of chronic diseases and improved overall well-being [56, 57]. The four food consumption clusters identified in this study have distinct nutritional and public health implications. The high meat-high plant cluster represents a relatively balanced diet, providing diverse nutrients from both animal and plant sources, though excessive meat intake may pose health risks depending on the type of meat. The high meat-low plant cluster is protein- and fat-heavy but low in fiber and phytochemicals, which could increase the risk of chronic diseases and lower overall diet quality. The low meat-low plant cluster reflects limited consumption of both animal and plant foods, potentially leading to nutrient deficiencies and inadequate energy or protein intake [58, 59]. The low meat-high plant cluster emphasizes plant-based foods, providing increased dietary fiber, essential micronutrients, and fermented vegetables that supply probiotics to support gut health and immune function [60]. This pattern may help reduce the risk of chronic diseases, although careful attention is required to ensure sufficient intake of protein, iron, and vitamin B12 [61].

Those who intend to reduce or avoid meat are less likely to belong to the high meat-high plant group or the low meat-low plant group. Likewise, participants who intend to eat less plant-based food are less likely to be in the high meat-high plant group but more likely to be in the low meat-low plant group. These results suggest that people’s intentions to change their intake of meat or plant-based foods are reflected in the types of dietary patterns they follow. Importantly, adopting a plant-based diet may help reduce the risk of malnutrition when such dietary changes are guided and supported by healthcare professionals, including primary care physicians and dietitians [62].

Environmental concerns are a key factor influencing dietary behaviors, driven by increasing awareness of the negative ecological consequences of animal agriculture. Meat production contributes significantly to GHG emissions, deforestation, excessive water use, and land degradation [63]. By reducing meat consumption and adopting plant-based diets, individuals can help mitigate these environmental impacts, supporting more sustainable food systems and reducing the overall ecological footprint of the population [64].

Furthermore, social influences, particularly peer pressure and the norms established within social networks, can significantly shape dietary decisions [65]. Gender differences have also been observed, with women generally more inclined to adopt plant-based diets, often due to heightened concern for personal health, ethics, and the environment. Lastly, political ideology, particularly liberal political orientation, has been linked to a greater likelihood of embracing plant-based eating, reflecting values aligned with environmentalism, animal rights, and social equity [66–70].

Significant enablers and barriers toward shifting to a plant-based diet among adult Filipino consumers

The current study identified several key enablers and barriers to adopting a plant-based diet. Among the barriers were: (1) individuals who find it easy to prepare meals with slightly less meat than usual, suggesting limited motivation to make a full shift (related to physical capability), and (2) individuals who perceive that preparing plant-based alternatives takes too much time, reflecting a lack of physical opportunity.

The difficulty of preparing plant-based meals may function as a barrier to the adoption of this diet [71]. This is due to the fact that people demand convenience in food preparation in order to reduce time and mental strain [72]. The findings of the current study are consistent with those of van den Berg et al. (2022) [39] on young Dutch adults, who also believe that preparing a meal with a plant-based alternative to meat is time-consuming. This is common among young Dutch adults who have high meat consumption. These patterns may also reflect broader social and cultural norms around typical meal composition, which could influence dietary choices and the degree of willingness to adopt plant-based alternatives. Similarly, a study conducted on Finnish adults aged 18 to 75 years old reveals that making a plant-based diet was not seen as a simple chore by many respondents [37]. Aside from difficulty in preparation, difficulty in finding the ingredients in stores, as they are not always available, is also one of the reasons why it is believed that it is inconvenient and time-consuming to switch to a plant-based diet [73].

On the other hand, several enablers were identified that support the shift toward a plant-based diet: (1) individuals who know how to substitute meat in a dish with plant-based alternatives (psychological capability), (2) those who enjoy trying vegetarian dishes (reflective motivation), (3) individuals who feel they can make independent decisions about whether or not to eat meat (social opportunity), and (4) those who perceive that people around them are eating less meat (social opportunity).

In the study by van den Berg et al. [39], knowledge of how to prepare meals using PBMAs was more common among vegetarians than among individuals with high meat consumption. While this skill represents a clear opportunity for promoting plant-based diets, it also highlights a barrier: among high meat consumers, the lack of knowledge and cooking skills related to plant-based meals can hinder dietary change. This gap in information and culinary ability has been identified in multiple studies as a significant obstacle to reducing meat intake. For example, regular meat consumers often cite lack of knowledge, limited cooking skills, and uncertainty about how to prepare plant-based meals as key barriers [36, 74–76].

The findings of the current study highlight a dynamic interplay between enablers and barriers to adopting a plant-based diet in the Philippine context. On the one hand, certain barriers limit the shift toward plant-based eating. The interaction between these factors suggests that while structural and behavioral barriers exist, such as convenience, habits, and limited motivation, these can be mitigated by enhancing skills, motivation, and supportive social environments. In the Philippine setting, where meat-centered meals are culturally prevalent, interventions that combine practical guidance on plant-based cooking with social encouragement and normalization of reduced meat consumption may effectively shift dietary behaviors. To the best of our knowledge, this study is the first to investigate the shift toward plant-based diets specifically among Filipino consumers, while also exploring the enablers and barriers affecting this change.

While this study offers valuable insights into the enablers and barriers to adopting a plant-based diet among Filipino adults in Metro Manila, it has several limitations. The use of a cross-sectional design restricts the ability to determine causality between attitudes and dietary behavior. The sample was limited to participants from Metro Manila, which may not reflect dietary practices in rural or other regional areas of the Philippines. Recruitment via QR codes in markets and grocery stores may have introduced sampling bias, favoring higher-income or more tech-savvy consumers. Potential confounding variables, such as religion, health conditions, or other lifestyle factors that could influence dietary choices, were not accounted for.

Despite these limitations, the study has notable strengths. It is one of the few to explore plant-based diet adoption in the Philippine context, using a structured framework to identify key influencing factors. Future studies should consider longitudinal approaches, include more diverse populations, and incorporate qualitative methods to gain deeper insight into behavioral drivers.

Conclusion

The study found that there is an increasing intention among Filipino adult consumers in Metro Manila to shift towards a plant-based diet. However, the barriers need to be addressed to facilitate a successful transition. Efforts in educating consumers about plant-based alternatives, in providing accessibility and convenient options, and in promoting social support for dietary changes could help facilitate the adoption of a plant-based diet.

Understanding the factors that influence dietary shifts toward plant-based eating is crucial for promoting healthier and more sustainable food systems. Income disparities significantly impact food choices, meaning low-income households often face barriers to accessing nutritious and environmentally friendly foods. Addressing these economic challenges through targeted subsidies or social support can improve food security for vulnerable populations. Encouraging plant-based diets also has positive implications for reducing the environmental footprint of food production, as meat production is a major contributor to GHG emissions, deforestation, and water use. Making plant-based foods more convenient and accessible can overcome practical barriers, helping more people adopt sustainable eating habits. Enhancing cooking skills and knowledge empowers individuals to prepare nutritious plant-based meals confidently. Social influences and shifting norms around meat consumption can accelerate societal acceptance of sustainable diets. By reducing reliance on animal-based foods, societies can mitigate climate change while promoting public health. Integrating sociodemographic factors into food policy ensures more equitable and effective interventions. Ultimately, supporting plant-based dietary transitions aligns with global goals to improve food security, protect the environment, and foster resilient communities.