1 INTRODUCTION

Cardiovascular diseases (CVDs) are a group of disorders of the heart and blood vessels (WHO, 2021). They represent a major health problem worldwide as the leading cause of death globally. The World Health Organization (WHO) estimated that, representing 32% of all global deaths, around 17.9 million people died from CVDs in 2019 (WHO, 2021).

A complete understanding of the etiology of CVDs remains elusive to the public and professionals. However, studies have revealed that most CVDs are preventable by addressing behavioral risk factors such as unhealthy diet, obesity, and physical inactivity (WHO, 2021). A high intake of saturated fat has been associated with increased levels of low-density lipoprotein cholesterol (WHO, 2021). It is generally accepted that, due to saturated fat, meat consumption contributes to the development of CVDs as plaques form in people's blood vessels (Malakar et al., 2019; Varghese & Kumar, 2019). This is important as red meats typically have more saturated fat than white (poultry) meats. In the last few decades, a large number of cohort and case–control studies have controversially and circumstantially reported that red meat may be a detrimental diet component for developing CVDs (Astrup et al., 2020; Papier et al., 2021). However, none of these studies revealed that there are significantly different levels of cholesterol content between red meat and white meat (Beauchesne-Rondeau et al., 2003; Bergeron et al., 2019; Davidson et al., 1999; Mateo-Gallego et al., 2012; Melanson et al., 2003; Scott et al., 1994). Complementarily, a recent study revealed that choosing white meat over red meat does not necessarily reduce the undesirable type of cholesterol or decrease the risk of CVDs (Bergeron et al., 2019).

In consideration of the above biases that occurred in previous research, we ascertain that total meat (flesh of animals) may be a significant risk factor for CVDs. This hypothesis was examined through analysis of the latest available population-level data published by several United Nations (UN) agencies. Socioeconomic status, urban living, and obesity were considered confounding factors. This study also identified that, secondary to socioeconomic status, total meat is another significant risk factor for CVDs.

2 MATERIALS AND METHODS

3 RESULTS

Figure 1 shows the unadjusted correlation between total meat and CVD incidence rate. The relationship was noted to be best described by a polynomial equation (y = −0.0872x² + 27.206x + 29.345) with moderately strong correlation (r = .644, p < .001). There seems to be no outlier observed in the plots (Figure 1).

Pearson correlation and nonparametric analyses revealed that total meat was significant and strongly correlated to CVD incidence (r = .688 and r = .752, p < .001, respectively) (Table 1). The moderate to strong, but significant correlations were also observed between CVD incidence and GDP PPP, obesity, and urbanization, respectively. This warranted our selection to include them as the confounding factors in exploring the correlation between total meat and CVD incidence.

Partial correlation analysis revealed that total meat was still a significant predictor of CVD incidence while GDP PPP, obesity, and urbanization were statistically kept constant (r = .308, p < .001, Table 2). When meat intake was statistically stabilized as a confounding factor in partial correlation analysis, it was revealed that: (1) GDP PPP and urbanization were identified as significant independent predictors of CVD incidence (r = .463 and r = .249, p < .001, respectively). (2) Obesity showed nearly nil correlation to CVD incidence (Table 2).

Standard multiple linear regression (enter) analysis was applied to further predict CVD incidence with total meat intake, GDP PPP, obesity prevalence, and urbanization considered as the predicting variables. When total meat was “not added” as one of the predicting variables, GDP PPP was the only significant predictor of CVD incidence (β = .751, p < .001, Table 3A). While total meat was entered as a predicting variable, it showed a significant correlation to CVD incidence together with GDP PPP (β = .282 and .673, p < .001, respectively, Table 3B).

In the standard multiple linear regression (stepwise) analysis, when meat intake was not entered as a CVD incidence predictor, GDP PPP was the only significant predictor for CVD incidence (R² = .548, Table 3B). When meat intake was incorporated as an independent variable, second to GDP PPP, it was placed as a major predictor for CVD incidence with increasing R² to .648 (Table 3B). Obesity and urbanization were not identified as the major predictors of CVD incidence.

Table 4 shows the bivariate correlations between total meat and CVD incidence in different country groupings. In general, total meat intake was in positive correlation to CVD incidence in each country grouping. The strength and significance level may depend on the sample size and the role of total meat in predicting CVD incidence. Fisher's r-to-z transformation identified that total meat was insignificantly stronger and correlated to CVD incidence in low- and middle-income countries than in high-income countries (z = 2.52, p < .010, and z = 3.49, p < .001 in Pearson's r and nonparametric models, respectively). Similarly, the correlation in the developing country grouping had a significantly stronger correlation than in the developed country grouping (z = 2.65, p < .010, and z = 3.76, p < .001 in Pearson's r and nonparametric models, respectively). These results may suggest that the role of total meat was significantly stronger in low- and middle-income countries than in high-income countries (Table 4).

4 DISCUSSION

CVDs have been a growing public health concern owing to multiple etiologies including eating red meat. By assessing the relationship between total meat and CVD incidence, this study suggests that total meat may be another significant risk factor for developing CVDs.

A large body of studies have consistently associated meat consumption with individual CVDs. However, almost all of these studies only focused on the role of red meat, instead of total meat or white meat in contributing to CVDs. Compared to white meat, red meat contains more saturated fat, which elevates levels of cholesterol and other atherogenic lipoproteins that contribute to CVDs (Al-Shaar et al., 2020; Medeiros et al., 2019; Papier et al., 2021; Wang et al., 2022). In the past years, red meat-associated metabolites, such as trimethylamine-N-oxide (TMAO), have gained attention in their relationship between red meat eating and CVDs (Wang et al., 2022). Similarly, l-carnitine, the active form of dietary carnitine and a driver of TMAO production in red meat, has been targeted by researchers for exploring CVD prevention and treatment (Wang et al., 2022; Zhao et al., 2022).

A limited number of studies have explored the role of total meat in contributing to CVDs. Four studies involving a total of 213,722 participants identified that total meat consumption was correlated to 9%–28% increase in the risk of stroke (Bernstein et al., 2012; Kim et al., 2017; Larsson et al., 2011a, 2011b). A meta-analysis of prospective cohort studies conducted by Kim et al. (2017) revealed that greater consumption of total meat may lead to an 18% increase in the risk of stroke. Bergeron et al. (2019) suggested that limiting total meat consumption (whether red or white) may reduce cholesterol levels leading to lower CVD risk. Similar results were revealed in a prospective cohort study of men across 30 years that greater intake of total meat may be a risk factor for coronary heart defect (Al-Shaar et al., 2020). While such studies support our hypothesis, it is noted that the results may be more circumstantial as these studies were conducted within particular populations.

Only a relatively few studies have looked at the relationship between white meat consumption and CVDs. The study findings were controversial (Abete et al., 2014; Kim et al., 2017; Zhong et al., 2020). Kim et al. (2017) identified that white meat consumption was associated with a 13% increased risk of stroke. A meta-analysis concluded that white meat protected against CVDs risk and suggested that white meat could be a healthier alternative to red meat and processed meat consumption (Lupoli et al., 2021). Contradicting this suggestion, a randomized controlled trial revealed that red meat and white meat both elevated cholesterol to an identical level in healthy men and women when saturated fat levels were equivalent in two meat subgroups (Bergeron et al., 2019). Such contradictory findings argue for further study of the impact of total meat consumption.

It is worth analyzing the underlying reason for the differences between red and white meat consumption and their correlation to the adverse effects of CVD. As the other meat subgroup, white meat represents a minor portion of the human diet (FAO, 2017). Although it also contains CVD-associated substances (saturated fat, l-carnitine, TMAO, sodium), in comparison with red meat, the levels are very low (Murphy et al., 2014; Wang et al., 2019; You & Henneberg, 2016a). For instance, generally speaking, white meat only contains a quarter of carnitine in red meat (Spence et al., 2021). This means the impact of these substances in white meat may not be obvious in association with CVD prognosis. Essentially when compared to red meat (FAO, 2017), a comparatively smaller percentage of white meat intake is not clearly associated with CVD-associated substances. Additionally, white meat from poultry is largely cooked and consumed with meat on bones, for example, drumsticks and wings making it difficult for research subjects to recall with certainty the volume of white meat they consume. The potential for data collection bias in studies of CVD prognosis and white meat consumption may have been inconsistent in previous studies. This concern may be addressed by considering total meat consumption meaning data collection bias becomes tolerable and more correlated to CVD (Bernstein et al., 2012; Kim et al., 2017; Larsson et al., 2011a, 2011b).

There is a special interest in comparing CVD mortality and incidence rates between high-income countries and LMICs. The number of CVD cases and mortality have increased significantly both worldwide and with special regard to LMIC (WHO, 2021). For example, the WHO reported that three-quarters of CVD deaths occurred in LMIC (WHO, 2021). Our study suggests that the effects of total meat intake were significantly more harmful on CVD incidence in LMIC than in high-income countries (z = 2.52 and 3.49 in Pearson's r and nonparametric analyses, respectively, p < .010). There may be a couple of reasons which competed with total meat consumption for contributing to CVD incidence making total meat appear “less harmful” in LMIC: (1) This may be attributable to several unique characteristics of LMIC, such as a faster increase of obesity prevalence, rapid urbanization, and emerging socioeconomic transitions to processed foods. All these characteristics have been enabling populations in LMIC to have increasing access to total meat (flesh) intake which led to CVD incidence increase. This may have been reflected in the statistical relationship between total meat intake and CVD (r range: .555–.767, moderate to strong correlation, p < .001, Table 1). (2) There is more red meat intake in high-income countries, which should make the correlation between total meat intake and CVD incidence stronger due to higher levels of CVD risk-associated substances in red meat (saturated fat, l-carnitine, TMAO, sodium). However, people in higher income countries tend to consume unhealthier diets which include more sugar (r = .727, p < .001) (You & Henneberg, 2016b) and gluten (r = .625, p < .001) (You et al., 2020; You & Henneberg, 2016c), but less vegetables and fruits (Kalmpourtzidou et al., 2020). For example, the American Heart Association reported that unhealthy diets in US0A have been contributing to the rise of CVD incidence based noting that 91.9% of Americans have an unhealthy diet, 8% consume a somewhat healthy diet and only 0.1% consume a healthy diet (Mozaffarian et al., 2015). Furthermore, people in high-income countries tend to be sedentary (less physical exercise) and this has been postulated as a risk factor for CVD pathogenesis (Basu et al., 2013; Mozaffarian et al., 2015).

It is important to consider all aspects of diet as noted in this study which argues for an analysis of total meat (flesh) supply, instead of singling out individual meats for their role in contributing to CVDs. This approach is more in keeping with the manner in which various types of meats, red and white, are consumed as part of people's diet patterns (Tantamango-Bartley et al., 2015; You & Henneberg, 2016a). Total meat, as the independent variable, is the total amount of “flesh of animals used for food” (FAO, 2018; Lawrie & Ledward, 2006); therefore, other potential confounding factors, such as processing methods and cooking methods, may not affect the correlation of total meat to CVDs.

5 CONCLUSION

Worldwide, total meat (flesh) access may be another significant predictor of CVD especially in low and low-middle income countries. It is worth investigating more about the role of total meat intake in determining noncommunicable diseases, such as CVDs.

6 CONFLICT OF INTEREST STATEMENT

The authors declare that there is no conflict of interest regarding this study.

ETHICS APPROVAL

The data included in this study carry negligible risk and involve the use of nonidentifiable, preexisting data about human beings. Therefore, this study does not require ethical approval.