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Social inequity in health among patients with severe obesity and multimorbidity

Mads Fiil Hjorth & Arne Astrup

12. jun. 2024
8 min.


Obesity is a global challenge associated with socioeconomic conditions in most geographies. Obesity affects the health of the individual living with obesity and impacts society through increased healthcare costs [1]. In Denmark, severe obesity results in additional annual costs of DKK 10 billion due to lost productivity and DKK 3.8 billion due to the need for treatment, care and medication [2]. In a Danish context, the individuals with the lowest educational level are 1.6 (64.7% versus 40.8%) and 2.8 (27.2% versus 9.8%) times more likely to live with overweight and obesity, respectively, than those with the highest educational level [3]. Obesity is closely linked to cardiometabolic diseases, and these differences contribute to inequity in health. Therefore, it would be important to investigate the distribution among individuals with an even higher BMI and specifically among those with obesity-related comorbidities.

This study aimed to investigate the prevalence of individuals with a BMI 35 kg/m2 by educational level and municipality as well as to investigate the number of comorbidities among individuals witha BMI 35 kg/m2 byeducational level.


All data used in this study are from the Danish National Health Survey 2021, a cross-sectional sample that aims to describe the prevalence and distribution of health and morbidity in the Danish adult population. The questionnaire was sent out to a national and municipality-representative sample of 324,000 individuals (≥ 16 years) and achieved a response rate of 56.7% (n = 183,646).

As part of the questionnaire, all individuals were asked about a long list of comorbidities [4], from which the following 12 obesity-related comorbidities were selected and included in the sum of comorbidities: asthma; type 2 diabetes mellitus (T2DM); hypertension; coronary artery syndrome; chronic bronchitis, chronic obstructive lung disease (COLD); osteoarthritis; rheumatoid arthritis; mental disorder; disc herniation or sciatica; myocardial infarction (current/previous); stroke (current/previous); cancer (current/previous). The comorbidities were categorised into four groups (0, 1, 2, ≥ 3). Self-reported height and weight were included in the questionnaire and used to calculate BMI.

The number of individuals in the Danish population ≥ 16 years with a BMI 35 kg/m2 was estimated based on the prevalence in the current cohort multiplied by the Danish population ≥ 16 years of age [5]. The same was done among those ≥ 30 years of age (as this subsample was used in the analyses including educational level to allow sufficient time to obtain a higher education). The population ≥30 years of age were stratified into the highest of five educational levels (elementary school (≤ 10 years); vocational school (11-12 years); higher education, short (13-14 years), medium (15-16 years) or long (≥ 17 years)) [6]. All prevalences were weighted according to weights provided by Statistics Denmark to minimise the problem of selective non-response [3].

Trial registration: not relevant.


A total of n = 167,573 had sufficient data to be included in the analyses, among whom n = 9,735 (5.8%) had a BMI 35 kg/m2. Hence, an estimated 280,500 Danes ≥ 16 years of age live with a BMI 35 kg/m2 (6.3% and 216,500 Danes ≥ 30 years of age).

The prevalence of BMI 35 kg/m2 in the 98 Danish municipalities ranges from 2.2% to 10.7% (Figure 1) and from 2.6% to 8.8% according to education level (≤ 10 years: 8.8%; 11-12 years: 7.7%; 13-14 years: 5.9%; 15-16 years: 5.3%; ≥ 17 years: 2.6%).

Among the individuals with BMI 35 kg/m2 and ≥ 30 years of age, a total of 13.7%, 50.5%, 9.1%, 20.3% and 6.5% had the highest education of ≤ 10 years; 11-12 years; 13-14 years, 15-16 years and ≥ 17 years, respectively.

Out of the estimated 280,500 individuals in the Danish population aged ≥ 16 with a BMI 35 kg/m2, 31.0% had no comorbidities, whereas the remaining 69.0% had ≥ 1 comorbidity (Figure 2 A and B). The prevalence for each comorbidity was as follows: hypertension (36.1%), osteoarthritis (32.9%), mental disorder (< 6 mos.: 8.1%; > 6 mos.: 14.9%), disc herniation or sciatica (16.9%), T2DM (14.6%), rheumatoid arthritis (12.5%), asthma (10.9%), cancer (7.0%), chronic bronchitis/COLD (6.9%), myocardial infarction (3.6%); stroke (3.5%) and coronary artery syndrome (2.0%).

Among individuals (age 30) with a BMI 35 kg/m2 and elementary school as the highest educational level, 13.4% had no comorbidities, and 45.6% had ≥ 3 comorbidities. In contrast, among individuals with a long higher education, 47.4% had no comorbidities and 14.6% had ≥ 3 comorbidities (Figure 2 C). The educational group with the highest absolute number of individuals with a BMI 35 kg/m2 accompanied by comorbidities was vocational school (Figure 2 D). Among those with a BMI 35 kg/m2 and ≥ 3 comorbidities, 73.6% (n = 45,800) had elementary school or vocational school as the highest education level, and 3.4% (n = 2,200) had a long higher education, although representing 58% and 7% of the Danish population, respectively.

The difference between individuals with the lowest and highest education level is a factor 3.4 (2.6% versus 8.8%) and 10.6 ((8.8% × 0.456) = 4.0% versus (2.6% × 0.146) = 0.4%) among individuals with a BMI 35 kg/m2 and a BMI 35 kg/m2 with ≥ 3 comorbidities, respectively.


The prevalence of individuals living with a BMI 35 kg/m2 differed by 3-5-fold depending on municipality and educational level. Additionally, the less educated group living with a BMI 35 kg/m2 was three times more likely to have ≥ 3 comorbidities than the most educated group. Combined with existing knowledge on overweight and obesity, social inequity in health becomes more pronounced as BMI increases and comorbidities start to emerge.

In a recent survey of more than 5,000 Danish adults, eight out of ten believed that prevention and management of obesity was the individual’s responsibility [7], even though research has clearly shown that obesity develops as an interaction between genetic, epigenetic and environmental factors, of which many are poorly understood [8] and likely to be deeply rooted in social inequity. Therefore, the responsibility for the obesity pandemic has been suggested to lie with the 1) national level, 2) food system, 3) education system, 4) medical system, 5) public healthcare system, 6) municipality, 7) society/community, 8) parental level, but only at the 9) individual level when adequate resources are available [9].

Genes alone cannot explain the excessive increase in the number of people living with overweight and obesity or the socio-demographic variations described herein. Changes in food systems (e.g., energy-dense, processed and highly palatable food), exercise habits and potentially also sleep deprivation contribute. Still, the interplay with the person’s innate biological and psychological factors likely determines the individual’s susceptibility to excessive energy intake and obesity.

Educational level – which is also likely to explain parts of the difference between municipalities – is one of the most pronounced effect modifiers in health research and is often difficult to remove by known contributors such as diet and exercise. Furthermore, educational level is a complex variable that may not fully capture socio-economic status or health literacy, and the relationship between education and obesity is likely bidirectional [10]. Nevertheless, we may gain important insights into novel causal factors of obesity by more carefully studying the differences between individuals with different educational levels. If we enhance our understanding of these differences, we may also improve prevention and management of obesity in the future. This may potentially involve environmental factors such as mental and social stress, sleep, pollutants, diet components, exercise regimens, atmospheric CO2, noise, ambient temperature, microbial environment, viral infections, drugs and other yet unknown factors with a potential interplay with (epi)genetics, some of which are likely to be deeply rooted in social inequity [11].

Correspondence Mads Fiil Hjorth. E-mail:

Accepted 17 April 2024

Conflicts of interest Potential conflicts of interest have been declared. Disclosure forms provided by the authors are available with the article at

Acknowledgements The Danish National Health Survey was funded by The Capital Region, Region Zealand, The South Denmark Region, The Central Denmark Region, The North Denmark Region, the Danish Ministry of Health and the National Institute of Public Health, University of Southern Denmark. Michael Davidsen (National Institute of Public Health, University of Southern Denmark) conducted the data analysis.

References can be found with the article at

Cite this as Dan Med J 2024;71(7):A01240059

doi 10.61409/A01240059

Open Access under Creative Commons License CC BY-NC-ND 4.0


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