>>The studies, published in the scientific journals *Medical Sciences* and *Metabolites*, address the role of social determinants of health from complementary perspectives.
>> Studies conducted on samples of 3,108 workers observe an association between lower educational attainment and a higher prevalence of obesity, as well as less favorable metabolic profiles.
Two studies conducted by researchers affiliated with the Health Research Group at the University of Mallorca (UMAC-ADEMA) have identified differences in obesity prevalence and cardiometabolic risk profiles among the working population based on educational level.
Both studies, conducted using samples of 3,108 working-age individuals, point to an association between lower levels of education and poorer health indicators. This relationship persists in the analyses after accounting for various factors related to age, sex, diet, physical activity, smoking, and diabetes.
Both studies are authored by Drs. María Teófila Vicente-Herrero and Carla Busquets-Cortés, and Drs. Pedro J. Tárraga López, Lluis Rodas Cañellas, Ángel Arturo López González, and José Ignacio Ramírez-Manent—members of the research team that investigated the relationship between educational level and various health indicators among the working population.
One of the studies, titled “Educational Inequalities and Obesity: Association and Attenuation After Lifestyle Adjustment in a Cross-Sectional Working-Age Population” and published in the scientific journal *Medical Sciences*, specifically analyzes the relationship between education level and obesity. The results place the prevalence of obesity at 19.8% among individuals with only a primary education or no formal schooling, compared to 11.5% among those with higher education.
In the initial analysis, individuals with lower levels of education were 1.89 times more likely to be obese than those with higher education. After adjusting for age and sex, the estimate fell to 1.72; upon incorporating variables related to diet, physical activity, smoking, and diabetes, the association remained at 1.61, indicating that the effect persists beyond individual habits.
Differences in certain habits were also observed. Among individuals with lower levels of education, 35.6% were smokers, compared to 27.9% in the group with higher education; 41.3% were physically inactive, compared to 33.9%; and 49% showed low adherence to the Mediterranean diet, compared to 32.5% of those with higher education.
Dr. Ángel Arturo López, Director of Scientific Publications at the University of Mallorca (UMAC-ADEMA), explained that obesity was determined through objective weight and height measurements taken by healthcare personnel and defined as a body mass index of 30 kilograms per square meter or higher. Physical activity was assessed using the international IPAQ-SF questionnaire, and adherence to the Mediterranean diet was analyzed using the MEDAS-14 questionnaire—two validated instruments commonly used in epidemiological studies.
The study concludes that anti-obesity policies should combine the promotion of healthy eating and physical activity with measures aimed at reducing the social and educational inequalities that hinder the maintenance of those habits.
Differences in cardiometabolic risk
The second study, titled “Sex Differences in the Socioeconomic Gradient of Latent Cardiometabolic Phenotypes in a Working-Age Population from the Balearic Islands (Spain): A Population-Based Analysis” and published in the scientific journal *Metabolites*, extends the analysis to the full spectrum of cardiometabolic risk. The study examined 3,108 workers aged 18 to 69 from the Balearic Islands and took into account indicators such as obesity, insulin resistance, metabolic fatty liver, the plasma atherogenic index, and metabolic syndrome.
As explained by Dr. Ángel Arturo López, Director of Scientific Publications at ADEMA, “the study’s main value lies in the fact that it does not limit itself to observing each risk factor in isolation. In contrast to the traditional approach—which measures cholesterol, glucose, obesity, or blood pressure as isolated variables—the researchers employed a statistical technique known as latent class analysis, which makes it possible to identify groups of people with similar metabolic patterns. This approach allows risk to be viewed as a comprehensive profile, one that more closely reflects each individual’s clinical reality.”
The study identified four cardiometabolic profiles: a low-risk profile, comprising 40.8% of the sample; an “obesity-dominant” profile, at 24.1%; a dysmetabolic profile, accounting for 19.3%; and a high-risk multimorbid profile, representing 15.8% of the participants.
This latter group simultaneously presents several adverse indicators. Dr. Arturo López has explained that “it is not merely a matter of individuals with obesity or a single abnormal parameter, but rather a profile characterized by the coexistence of various signs of metabolic deterioration: obesity, insulin resistance, an increased likelihood of metabolic fatty liver disease, atherogenic abnormalities, and metabolic syndrome. Consequently, this profile is of particular interest for the prevention of cardiovascular disease, type 2 diabetes, and other associated complications.”
The results also show an association between lower educational attainment and a higher likelihood of falling into unfavorable cardiometabolic profiles. Among men with lower levels of education, the relative risk of belonging to the high-risk multimorbidity profile was 1.82 times higher than that of men with higher education, whereas among women, it was 2.47 times higher.
The study notes, however, that men generally exhibit a higher absolute cardiometabolic risk burden, whereas the relative association between lower educational attainment and metabolic deterioration is more pronounced in women.
The research reinforces—in the words of Dr. Arturo López—”an idea increasingly prevalent in public health: cardiometabolic risk does not appear spontaneously in adulthood but rather develops over the course of a lifetime through the interaction of biology, habits, and the social environment. In this regard, education serves as a marker for access to resources, health literacy, job stability, and the ability to make informed preventive decisions.”
The researchers caution that, as this is a cross-sectional study, it cannot be stated that lower educational attainment directly causes cardiometabolic deterioration. What the study does demonstrate is a strong association between lower levels of education and a higher likelihood of falling into adverse metabolic profiles, particularly among women.
The main conclusion is that cardiometabolic health has a social dimension. Prevention should not be limited to interventions targeting the individual once risk factors have emerged; instead, it should address the underlying determinants that foster their development. In this regard, education, equity, working conditions, work-life balance, and access to healthy resources are also part of health policy.