Introduction: Overweight and obesity lead to numerous complications and their treatment. The associated costs represent a health and sociopolitical burden. Therefore, the development of overweight and obesity is of great importance for health policy. Methods: The Gutenberg Health Study (GHS), a population-based observational study of individuals aged 35–74 years in the city of Mainz and the district of Mainz-Bingen, examined current data on the prevalence and development of overweight and obesity and their association with concomitant diseases and medication use. Results: Among men, 48.1% were overweight and 26.3% had obesity. Among women, these proportions were 32.1% and 24.1%, respectively. Elevated body mass index (BMI) was associated with numerous complications, particularly insulin resistance and type 2 diabetes, arterial hypertension, elevated triglycerides and low HDL cholesterol, and cardiovascular disease. Accordingly, medications to treat these conditions were used significantly more often in individuals with elevated BMI. During the 10-year observation period, mean weight increased in the population. Both men and women had a moderate but significant increase in BMI compared to men and women of the same age at baseline. Individual weight changes over the 10-year observation period, on the other hand, were age-dependent. In the two younger age decades, weight gain was observed, while in the oldest age decade, mean body weight decreased. Conclusion: These current data confirm that overweight and obesity are associated with relevant complications and that these complications lead to significant use of appropriate medications. The study also suggests that there is a significant trend toward increased prevalence of obesity (BMI ≥30) over the 10-year period.

The prevalence of overweight and obesity has increased tremendously worldwide over the last decades. This trend has not only been observed in highly developed countries but also in emerging and developing countries [1]. According to the current understanding, obesity is a multifactorial, progressive, and chronic disease that requires lifelong therapy [2‒4]. The causes for the steadily increasing proportion of individuals with overweight or patients with obesity in the population are complex. The overabundance of food, combined with reduced physical activity, favors a positive energy balance and, as a consequence, the development of obesity. However, genetic, biological, psychological [5], and social factors [6‒8] also contribute to the disease [5].

In terms of health policy, the consequences of obesity are particularly relevant. Obesity is associated with numerous complications and increased all-cause mortality [9, 10]. Accordingly, the medical and societal costs associated with obesity are substantial [11].

The aim of the present study was to obtain current data on the prevalence of overweight and obesity in a representative German population. For this purpose, the population-based cohort of the Gutenberg Health Study (GHS) was examined, comprising approximately 15,010 individuals of both sexes aged 35–74 years. The study allows for a detailed analysis of complications, medication use, and body weight changes over the course of 10 years.

Study Cohort

The Gutenberg Health Study (GHS) is a population-based, prospective, monocentric cohort study in the Rhine-Main region. Between April 2007 and March 2012, a representative sample of 15,010 participants aged 35–74 years was recruited from the population of the city of Mainz and the district of Mainz-Bingen [12]. Participants underwent a comprehensive, standardized 5-h clinical examination [12, 13]. After 5 as well as 10 years, follow-up examinations of the participants took place as scheduled. The study was designed according to the principles of the revised Declaration of Helsinki, and the study protocol and sampling were approved by the Local Ethics Committee. All participants gave written informed consent prior to the study and for laboratory analyses, clinical examinations, biomaterial sampling, and use of data sets for research purposes. For the present study, we analyzed participants with complete data at baseline (n = 14,999) and 5-year follow-up (n = 12,418), as well as all participants who had also completed the 10-year follow-up (n = 7,048) at the time of data collection.

Anamnestic and Clinical Data

Participants were asked to attend fasting and underwent a 5-h standardized examination in a predefined sequence. This consists of a computer-assisted personal interview, numerous medical-technical examinations, a survey with standardized questionnaires, and comprehensive biobanking. Computer-assisted personal interview included among others sociodemographics, medical history, family history, children, health behavior (i.e., smoking, alcohol consumption, physical activity/sport). Medical-technical examinations included measurement of blood pressure, heart rate, body weight and height, temperature, electrocardiogram, echocardiography, carotid artery ultrasound, and venous blood sampling. Standardized questionnaires were used to check for mental and psychological illnesses, physical activity, nutrition, and everyday stress [12].

Definitions

Socioeconomic status (SES) was defined according to Lampert’s and Kroll’s scores of SES ranging from 3 to 21 where 3 indicates the lowest SES and 21 the highest SES [14]. This multidimensional index includes individual information on educational qualification and household characteristics of occupation and income with equal weights. Physical activity was assessed by “SQUASH” (Short Questionnaire to Assess Health-enhancing physical activity) developed by Wendel-Vos et al. [15]. The comorbidity index was determined using the Charlson comorbidity index [16].

Smoking, alcohol consumption, and sports were dichotomized. Smokers were categorized into nonsmokers (never smoker and ex-smoker) and smokers (indication of cigarette/day). Alcohol consumption was determined in grams per day and categorized into an alcohol consumption of more or less than 24 g/day for men and 12 g/day for women, which corresponds to the upper limit of medically acceptable alcohol use in Germany.

Diabetes mellitus: medical diagnosis or an HbA1c ≥6.5% or treatment with antidiabetic agents (ATC code A10). Dyslipidemia: medical diagnosis, therapy with a lipid-lowering agent, or a ratio of LDL cholesterol to HDL cholesterol of ≥3.5. Arterial hypertension: antihypertensive drug treatment in the last 2 weeks or a systolic blood pressure of ≥140 mm Hg and/or a diastolic blood pressure of ≥90 mm Hg at the study center (in each case, mean of two determinations after 8 and 11 min of supine rest).

Data Management and Statistical Analyses

Continuous variables were described by mean and standard deviation, with normal distribution, or median with interquartile range, for non-normally distributed variables. Discrete variables were presented as relative and absolute frequencies. The association of delta body mass index (BMI) (kg/m2) with determinants was analyzed with a multivariable linear regression model. Quantiles related to sex and age were estimated using quantile regression, stratified by sex, with age as a covariate. All statistical comparisons were two-sided. Because of the exploratory nature of the analysis, p values should be interpreted as a continuous measure of statistical evidence. Statistical analysis was performed using R version 4.1.0 (http://www.R-project.org).

Baseline Characteristics of the Cohort

A total of 14,999 GHS participants with complete height and weight data were included in the baseline analysis. Waist circumference was not available from 11 participants. Five-year follow-up was completed by 12,418 (82.8%) and 10-year follow-up by 7,048 (47.0%) participants; however, in 2,526 participants, the 10-year follow-up had not yet been completed. Reasons for dropping out after 5 and 10 years, respectively, were unwillingness to be followed up (1,677/3,658), inaccessibility (447/367), death (355/960), moving away from the study area (100/123). Baseline characteristics of participants included are summarized in Table 1. All analyses of change between baseline and follow-up are limited to the group with completed follow-up.

Table 1.

Baseline characteristics of the cohort

AllMenWomen
n (%) 14,999 (100) 7,577 (50.5) 7,422 (49.5) 
Age, years* 55.0±11.1 55.3±11.1 54.8±11.1 
Anthropometry* 
 Height, cm 170±10 177±7 164±7 
 Weight, kg 79.7±16.6 87.3±14.4 72.0±15.1 
 Waist, cm 94.5±13.9 99.6±12.1 89.4±13.7 
 WHtR 0.56±0.08 0.56±0.07 0.55±0.09 
 BMI,# kg/m2 26.6 (23.9/30.0) 27.3 (24.9/30.2) 25.7 (22.8/29.8) 
BMI groups, kg/m2, n (%) 
 <18.5 86 (0.6) 18 (0.2) 68 (0.9) 
 18.5–<25 5,100 (34.0) 1,921 (25.4) 3,179 (42.8) 
 25–<30 6,030 (40.2) 3,647 (48.1) 2,383 (32.1) 
 ≥30 3,783 (25.2) 1,991 (26.3) 1,792 (24.1) 
AllMenWomen
n (%) 14,999 (100) 7,577 (50.5) 7,422 (49.5) 
Age, years* 55.0±11.1 55.3±11.1 54.8±11.1 
Anthropometry* 
 Height, cm 170±10 177±7 164±7 
 Weight, kg 79.7±16.6 87.3±14.4 72.0±15.1 
 Waist, cm 94.5±13.9 99.6±12.1 89.4±13.7 
 WHtR 0.56±0.08 0.56±0.07 0.55±0.09 
 BMI,# kg/m2 26.6 (23.9/30.0) 27.3 (24.9/30.2) 25.7 (22.8/29.8) 
BMI groups, kg/m2, n (%) 
 <18.5 86 (0.6) 18 (0.2) 68 (0.9) 
 18.5–<25 5,100 (34.0) 1,921 (25.4) 3,179 (42.8) 
 25–<30 6,030 (40.2) 3,647 (48.1) 2,383 (32.1) 
 ≥30 3,783 (25.2) 1,991 (26.3) 1,792 (24.1) 

BMI, body mass index; WHtR, waist-to-height ratio; n, number of patients.

*Data are presented as mean ± standard deviation or #median (interquartile range).

Prevalence of Overweight and Obesity at Baseline

The cohort represents the age range of 35–74 years. Overall, 40.2% of participants were overweight (BMI ≥25–<30 kg/m2), and 25.2% had obesity (BMI ≥30 kg/m2). Accordingly, only slightly more than 1/3 of the cohort had normal body weight. A very small number of participants (0.6%) had a BMI <18.5 kg/m2. While only about ¼ of all men were of normal weight, this was true for over 40% of women (Table 1).

As expected, waist circumference and waist-to-height ratio increased with increasing BMI. Men were more likely to be overweight than women (48.1% vs. 32.1%, p < 0.0001), while the difference in obesity prevalence was smaller (26.3% vs. 24.1%, p < 0.01). There was a moderate increase in BMI with age in both sexes, which was more pronounced in women (Fig. 1). For comparison, we calculated the distribution of BMI weighted for German and European standard populations (online suppl. Table 1; for all online suppl. material, see https://doi.org/10.1159/000533671).

Fig. 1.

a Age dependence of body mass index (BMI) in men and women. b Age dependence of change in BMI within 5 years. Black line – median; blue – interquartile range; green – 10th–90th percentile; red – 5th–95th percentile.

Fig. 1.

a Age dependence of body mass index (BMI) in men and women. b Age dependence of change in BMI within 5 years. Black line – median; blue – interquartile range; green – 10th–90th percentile; red – 5th–95th percentile.

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Individual Weight Changes between Baseline, 5-Year, and 10-Year Follow-Up

Individual weight changes were recorded after 5 and 10 years. Men gained an average of 0.52 ± 4.99 kg (or 0.64% ± 5.50%) over the 5-year observation period and 0.76 ± 7.02 kg (or 0.90% ± 7.57%) over the 10-year observation period, and women gained 0.83 ± 5.07 kg (1.28% ± 6.64%) and 1.49 ± 6.71 kg (2.26% ± 8.96%), respectively.

Accordingly, the proportion of individuals with overweight increased slightly from 40.2% at baseline to 41.0% after 5 years and 41.1% after 10 years, and the proportion of patients with obesity increased from 25.2% to 26.0% to 28.0%, whereas the proportion of normal-weight participants decreased from 34.0% to 32.4% to 30.3%. The proportion of underweight individuals remained constant at 0.6%.

Overall, weight gain was more common than weight loss (13.6% vs. 9.1%). Weight changes were age-dependent and differed between sexes (Fig. 1; Table 2). With increasing age, participants in the age groups 35–54 on average gained weight. Less than a quarter of all participants had a weight change ≥5 kg in 5 years. Among participants aged 55–65 years, weight gain and weight loss were nearly equal, and among participants aged 65 years and older, weight loss was slightly more common than weight gain.

Table 2.

Mean weight changes over 10 years

AgeMean weight change±SD after 5 yearsMean weight change±SD after 10 years
menwomenmenwomen
kg%Nkg%Nkg%Nkg%N
35–44 1.52±5.5 1.84±6.0 1,373 1.71±5.5 2.56±7.4 1,425 2.87±7.4 3.36±7.8 868 3.55±7.4 5.33±9.2 950 
45–54 1.11±5.1 1.34±5.5 1,773 1.37±5.4 2.01±6.8 1,690 1.68±6.5 1.97±7.2 1,143 2.12±6.7 3.15±8.6 1,095 
55–64 0.27±4.7 0.34±5.2 1,722 0.58±4.6 0.94±6.0 1,643 −0.29±7.4) −0.329±7.7 950 0.23±5.4 0.42±7.4 899 
65–74 −0.83±4.4 −0.94±5.0 1,488 −0.51±4.3 −0.64±5.9 1,304 −2.22±5.3 −2.54±6.1 641 −1.57±5.7 −2.21±7.8 502 
AgeMean weight change±SD after 5 yearsMean weight change±SD after 10 years
menwomenmenwomen
kg%Nkg%Nkg%Nkg%N
35–44 1.52±5.5 1.84±6.0 1,373 1.71±5.5 2.56±7.4 1,425 2.87±7.4 3.36±7.8 868 3.55±7.4 5.33±9.2 950 
45–54 1.11±5.1 1.34±5.5 1,773 1.37±5.4 2.01±6.8 1,690 1.68±6.5 1.97±7.2 1,143 2.12±6.7 3.15±8.6 1,095 
55–64 0.27±4.7 0.34±5.2 1,722 0.58±4.6 0.94±6.0 1,643 −0.29±7.4) −0.329±7.7 950 0.23±5.4 0.42±7.4 899 
65–74 −0.83±4.4 −0.94±5.0 1,488 −0.51±4.3 −0.64±5.9 1,304 −2.22±5.3 −2.54±6.1 641 −1.57±5.7 −2.21±7.8 502 

Men were more likely to show weight loss ≥5 kg than women (9.7% vs. 8.4%, p < 0.05) and less likely to show weight gain ≥5 kg (12.8% vs. 14.5%, p < 0.01). Results were similar when relative weight change was considered (Fig. 1b). Among all participants with weight loss ≥5 kg at 5-year follow-up, 44% had obesity at baseline and 43% were overweight. In the group with weight gain ≥5 kg, the corresponding proportions were 31.7% and 39.1%. In absolute terms, the normal weight group had the largest increase in BMI (0.5 ± 1.32 kg/m2 vs. 0.35 ± 1.64 kg/m2 in individuals with overweight and 0.20 ± 2.42 kg/m2 in participants with obesity; p < 0.0001). Interestingly, the proportion of participants with a weight change ≥5 kg during the observation period was lowest in normal-weight subjects (14.6%) and increased with overweight (22.5%) and obesity class I to III (31.7%, 45.0%, and 45.5%, respectively). This suggests that large changes in body weight are more common in people with overweight or obesity.

Factors Affecting Weight and Weight Changes

At baseline, there is a strong correlation between social and behavioral factors and BMI. These are in particular school or educational qualification, employment, income, and overall socioeconomic status. The higher the educational qualification and the higher the income, the greater the likelihood of a BMI <25 kg/m2 (online suppl. Table 2). In addition, participants with a BMI <25 kg/m2 are more active in sports than participants with a BMI ≥25 kg/m2, whereas smoking and alcohol consumption are significantly higher in BMI classes <18.5 and <25 kg/m2.

Multiple linear regression identified several factors associated with relative weight changes over the study period. Thereby, it is shown that the significantly different life circumstances at baseline for the BMI groups predominantly do not have a significant influence on weight over the follow-up period of 5 years (Fig. 2). Age, diabetes, and alanine-leucine aminotransferase activity were associated with lower absolute weight gain for both sexes. Physical activity score, hypertension, and white blood cell count were only associated with lower absolute weight gain in women. When relative weight gain was analyzed, female sex was associated with increased weight gain. While participants with type 2 diabetes mellitus were more likely to have obesity, they were more likely to lose weight compared to participants without diabetes. In fact, type 2 diabetes mellitus was the single most important factor associated with weight loss (Fig. 2).

Fig. 2.

Factors affecting weight change in men and women during 5-year follow-up by multiple linear regression.

Fig. 2.

Factors affecting weight change in men and women during 5-year follow-up by multiple linear regression.

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Weight Development in the Population Cohort over the Last 10 Years

To assess changes in BMI on a population basis, we analyzed BMI in men and women aged 45–54, 55–64, and 65–74 at baseline, 5-year and 10-year follow-up. Both men and women in the respective age decades have become significantly heavier within the last 10 years. At baseline, men had an average BMI of 27.5 and women 26.2, and 10 years later, men’s BMI was 28.3 (p < 0.0001) and women’s 27.3 (p < 0.0001). When analyzing the individual age decades, especially men in the age group 45–54, as well as those from 65 to 74 have become significantly (p < 0.0001) heavier in recent years (Table 3). This trend is not seen to the same extent among women. Only the age group 65–74 is significantly (p = 0.019) heavier than at baseline. Altogether, this indicates that there is a general trend toward an increased prevalence of obesity over the 10-year period, in particular in the older age groups.

Table 3.

BMI in age groups at baseline and after 5 and 10 years

SexAgeBaselineAfter 5 yearsAfter 10 years
mean (SD)median (IQR)Nmean (SD)median (IQR)Nmean (SD)median (IQR)N
Men 45–54 27.3 (3.8) 26.78 (24.6/29.5) 1,224 27.4 (4.1) 26.6 (24.6/29.6) 1,142 28.1 (4.8) 27.2 (24.9/30.5) 907 
55–64 28.1 (4.2) 27.60 (25.2/30.4) 1,058 28.2 (4.3) 27.5 (25.2/30.6) 1,142 28.3 (4.3) 27.7 (25.3/30.7) 1,158 
65–74 27.9 (3.8) 27.42 (25.4/29.8) 696 28.3 (4.2) 27.7 (25.4/30.4) 944 28.8 (4.7) 28.2 (25.5/31.4) 1,081 
Women 45–54 26.1 (5.4) 24.9 (22.3/28.7) 1,146 26.2 (5.3) 25.1 (22.5/28.9) 1,144 26.4 (5.4) 25.4 (22.7/28.8) 939 
55–64 27.0 (5.1) 26.2 (23.3/29.8) 974 27.0 (5.5) 26.0 (23.1/29.7) 1,083 27.4 (5.9) 26.4 (23.1/30.4) 1,150 
65–74 27.2 (4.4) 26.6 (24.0/30.0) 546 27.5 (4.9) 26.6 (23.9/30.3) 841 27.8 (5.7) 26.9 (23.6/30.9) 978 
SexAgeBaselineAfter 5 yearsAfter 10 years
mean (SD)median (IQR)Nmean (SD)median (IQR)Nmean (SD)median (IQR)N
Men 45–54 27.3 (3.8) 26.78 (24.6/29.5) 1,224 27.4 (4.1) 26.6 (24.6/29.6) 1,142 28.1 (4.8) 27.2 (24.9/30.5) 907 
55–64 28.1 (4.2) 27.60 (25.2/30.4) 1,058 28.2 (4.3) 27.5 (25.2/30.6) 1,142 28.3 (4.3) 27.7 (25.3/30.7) 1,158 
65–74 27.9 (3.8) 27.42 (25.4/29.8) 696 28.3 (4.2) 27.7 (25.4/30.4) 944 28.8 (4.7) 28.2 (25.5/31.4) 1,081 
Women 45–54 26.1 (5.4) 24.9 (22.3/28.7) 1,146 26.2 (5.3) 25.1 (22.5/28.9) 1,144 26.4 (5.4) 25.4 (22.7/28.8) 939 
55–64 27.0 (5.1) 26.2 (23.3/29.8) 974 27.0 (5.5) 26.0 (23.1/29.7) 1,083 27.4 (5.9) 26.4 (23.1/30.4) 1,150 
65–74 27.2 (4.4) 26.6 (24.0/30.0) 546 27.5 (4.9) 26.6 (23.9/30.3) 841 27.8 (5.7) 26.9 (23.6/30.9) 978 

Complications Associated with BMI in Men and Women

In 14,999 subjects at baseline, we studied the association of BMI with several complications. In addition, we determined medication use in the different BMI groups.

Metabolic Complications

The prevalence of diabetes and dyslipidemia increased significantly with increasing BMI in both sexes (Table 4a, b; online suppl. Fig. 1; online suppl. Table 3a, b). Whereas there was no difference in the prevalence of type 1 diabetes between BMI classes, the prevalence of type 2 diabetes increased steadily from 2.5% in individuals with normal body weight to 23.6% in individuals with severe obesity (BMI ≥40 kg/m2). This trend was observed in both sexes (men, 3.8% to 41.1%; women, 2.1% to 29.4%). Individuals with obesity were more than five times as likely to have type 2 diabetes as individuals of normal weight (men: 21.9% vs. 3.7%; women: 16.4% vs. 2.1%). As expected, the increased prevalence of type 2 diabetes is associated with increased HbA1c, fasting glucose and insulin, and HOMA-IR, respectively.

Table 4.

Distribution of comorbidities in relation to BMI groups

a MenBMI, kg/m2p value
Variable<18.5 (18)18.5–<25 (1,921)25–<30 (3,647)30–<35 (1,530)35–<40 (354)≥40 (107)
Age, years, mean±SD 53.2±11.1 52.5±11.1 55.9±11.0 56.7±11.0 56.8±10.6 55.1±11.1 <0.0001 
Comorbidity index, median (IQR) 0 (0/1.0) 0 (0/0) 0 (0/1.0) 0 (0/1.0) 1.00 (0/2.0) 1.00 (0/1.0) <0.0001 
Carbohydrate metabolism 
 Diabetes, n (%) 1 (5.6) 83 (4.3) 325 (8.9) 301 (19.7) 107 (30.2) 45 (42.1) <0.0001 
 Diabetes type 1, n (%) 1 (5.6) 11 (0.6) 21 (0.6) 13 (0.8) 1 (0.3) 1 (0.9) 0.27 
 Diabetes type 2 known at baseline, n (%) 0 (0) 44 (2.3) 199 (5.5) 205 (13.4) 77 (21.8) 27 (25.2) <0.0001 
 Diabetes type 2 detected at baseline, n (%) 0 (0) 28 (1.5) 105 (2.9) 83 (5.4) 29 (8.2) 17 (15.9) <0.0001 
 HbA1c, % 5.45 (5.20/5.60) 5.40 (5.20/5.70) 5.50 (5.20/5.80) 5.60 (5.30/6.10) 5.70 (5.40/6.30) 6.10 (5.70/6.90) <0.0001 
 Glucose, mg/dL 86.0 (84.2/91.1) 91.0 (86.0/97.0) 93.0 (88.0/100.0) 96.0 (89.0/105.0) 98.0 (90.2/107.0) 103.0 (91.0/116.0) <0.0001 
 Insulin, pmol/L 25.8 (22.2/39.4) 33.3 (25.3/44.1) 46.4 (34.3/63.5) 69.9 (51.3/97.5) 97.1 (73.1/133.6) 113.3 (82.3/187.1) <0.0001 
Lipid metabolism 
 Cholesterol, mg/dL 205.1±31.3 215.5±39.0 219.4±40.5 212.4±39.9 203.8±36.3 206.7±38.8 <0.0001 
 LDL cholesterol, mg/dL 118.8±31.6 138.6±33.9 142.0±35.3 134.3±34.6 125.9±32.8 125.8±30.3 <0.0001 
 HDL cholesterol, mg/dL 70.8±13.8 55.5±13.1 50.4±11.8 45.6±10.3 43.9±9.8 43.4±10.4 <0.0001 
 Triglycerides, mg/dL 64 (57/92) 91 (69/124) 118 (88/162) 142 (105/196) 154 (113/202) 168 (128/224) <0.0001 
Hypertension, n (%) 6 (33.3) 655 (34.1) 2,014 (55.2) 1,093 (71.4) 282 (79.7) 89 (83.2) <0.0001 
 SBP, mm Hg 124.7±15.5 129.6±15.7 134.8±15.9 137.2±16.2 136.5±16.6 140.9±17.5 <0.0001 
 DBP, mm Hg 77.1±8.5 81.1±8.9 84.3±9.1 85.9±9.7 85.4±10.0 87.9±10.9 <0.0001 
Coronary artery disease, n (%) 0 (0) 79 (4.1) 211 (5.8) 147 (9.6) 41 (11.6) 6 (5.6) <0.0001 
Myocardial infarction, n (%) 0 (0) 47 (2.4) 137 (3.8) 118 (7.7) 30 (8.5) 7 (6.5) <0.0001 
Stroke, n (%) 1 (5.6) 28 (1.5) 89 (2.4) 51 (3.3) 9 (2.5) 4 (3.7) 0.0018 
Peripheral arterial disease, n (%) 1 (5.6) 41 (2.1) 121 (3.3) 74 (4.8) 31 (8.8) 9 (8.5) <0.0001 
Atrial fibrillation, n (%) 1 (5.6) 43 (2.2) 145 (4.0) 60 (3.9) 19 (5.4) 10 (9.3) 0.00054 
Congestive heart failure, n (%) 0 (0) 14 (0.7) 34 (0.9) 45 (2.9) 7 (2.0) 2 (1.9) 0.00030 
CKD, n (%) 0 (0) 33 (1.7) 151 (4.1) 92 (6.0) 22 (6.2) 8 (7.5) <0.0001 
COPD, n (%) 0 (0) 67 (3.5) 154 (4.2) 77 (5.0) 24 (6.8) 5 (4.7) 0.0025 
Cancer, n (%) 1 (5.6) 117 (6.1) 331 (9.1) 120 (7.9) 30 (8.5) 6 (5.6) 0.14 
Depression, n (%) 4 (22.2) 153 (8.0) 273 (7.5) 144 (9.4) 25 (7.1) 12 (11.2) 0.33 
Chronic arthropathy, n (%) 0 (0) 58 (3.0) 143 (3.9) 61 (4.0) 14 (4.0) 3 (2.8) 0.21 
a MenBMI, kg/m2p value
Variable<18.5 (18)18.5–<25 (1,921)25–<30 (3,647)30–<35 (1,530)35–<40 (354)≥40 (107)
Age, years, mean±SD 53.2±11.1 52.5±11.1 55.9±11.0 56.7±11.0 56.8±10.6 55.1±11.1 <0.0001 
Comorbidity index, median (IQR) 0 (0/1.0) 0 (0/0) 0 (0/1.0) 0 (0/1.0) 1.00 (0/2.0) 1.00 (0/1.0) <0.0001 
Carbohydrate metabolism 
 Diabetes, n (%) 1 (5.6) 83 (4.3) 325 (8.9) 301 (19.7) 107 (30.2) 45 (42.1) <0.0001 
 Diabetes type 1, n (%) 1 (5.6) 11 (0.6) 21 (0.6) 13 (0.8) 1 (0.3) 1 (0.9) 0.27 
 Diabetes type 2 known at baseline, n (%) 0 (0) 44 (2.3) 199 (5.5) 205 (13.4) 77 (21.8) 27 (25.2) <0.0001 
 Diabetes type 2 detected at baseline, n (%) 0 (0) 28 (1.5) 105 (2.9) 83 (5.4) 29 (8.2) 17 (15.9) <0.0001 
 HbA1c, % 5.45 (5.20/5.60) 5.40 (5.20/5.70) 5.50 (5.20/5.80) 5.60 (5.30/6.10) 5.70 (5.40/6.30) 6.10 (5.70/6.90) <0.0001 
 Glucose, mg/dL 86.0 (84.2/91.1) 91.0 (86.0/97.0) 93.0 (88.0/100.0) 96.0 (89.0/105.0) 98.0 (90.2/107.0) 103.0 (91.0/116.0) <0.0001 
 Insulin, pmol/L 25.8 (22.2/39.4) 33.3 (25.3/44.1) 46.4 (34.3/63.5) 69.9 (51.3/97.5) 97.1 (73.1/133.6) 113.3 (82.3/187.1) <0.0001 
Lipid metabolism 
 Cholesterol, mg/dL 205.1±31.3 215.5±39.0 219.4±40.5 212.4±39.9 203.8±36.3 206.7±38.8 <0.0001 
 LDL cholesterol, mg/dL 118.8±31.6 138.6±33.9 142.0±35.3 134.3±34.6 125.9±32.8 125.8±30.3 <0.0001 
 HDL cholesterol, mg/dL 70.8±13.8 55.5±13.1 50.4±11.8 45.6±10.3 43.9±9.8 43.4±10.4 <0.0001 
 Triglycerides, mg/dL 64 (57/92) 91 (69/124) 118 (88/162) 142 (105/196) 154 (113/202) 168 (128/224) <0.0001 
Hypertension, n (%) 6 (33.3) 655 (34.1) 2,014 (55.2) 1,093 (71.4) 282 (79.7) 89 (83.2) <0.0001 
 SBP, mm Hg 124.7±15.5 129.6±15.7 134.8±15.9 137.2±16.2 136.5±16.6 140.9±17.5 <0.0001 
 DBP, mm Hg 77.1±8.5 81.1±8.9 84.3±9.1 85.9±9.7 85.4±10.0 87.9±10.9 <0.0001 
Coronary artery disease, n (%) 0 (0) 79 (4.1) 211 (5.8) 147 (9.6) 41 (11.6) 6 (5.6) <0.0001 
Myocardial infarction, n (%) 0 (0) 47 (2.4) 137 (3.8) 118 (7.7) 30 (8.5) 7 (6.5) <0.0001 
Stroke, n (%) 1 (5.6) 28 (1.5) 89 (2.4) 51 (3.3) 9 (2.5) 4 (3.7) 0.0018 
Peripheral arterial disease, n (%) 1 (5.6) 41 (2.1) 121 (3.3) 74 (4.8) 31 (8.8) 9 (8.5) <0.0001 
Atrial fibrillation, n (%) 1 (5.6) 43 (2.2) 145 (4.0) 60 (3.9) 19 (5.4) 10 (9.3) 0.00054 
Congestive heart failure, n (%) 0 (0) 14 (0.7) 34 (0.9) 45 (2.9) 7 (2.0) 2 (1.9) 0.00030 
CKD, n (%) 0 (0) 33 (1.7) 151 (4.1) 92 (6.0) 22 (6.2) 8 (7.5) <0.0001 
COPD, n (%) 0 (0) 67 (3.5) 154 (4.2) 77 (5.0) 24 (6.8) 5 (4.7) 0.0025 
Cancer, n (%) 1 (5.6) 117 (6.1) 331 (9.1) 120 (7.9) 30 (8.5) 6 (5.6) 0.14 
Depression, n (%) 4 (22.2) 153 (8.0) 273 (7.5) 144 (9.4) 25 (7.1) 12 (11.2) 0.33 
Chronic arthropathy, n (%) 0 (0) 58 (3.0) 143 (3.9) 61 (4.0) 14 (4.0) 3 (2.8) 0.21 
b WomenBMI, kg/m2p value
Variable<18.5 (68)18.5–<25 (3,179)25–<30 (2,383)30–<35 (1,160)35–<40 (421)≥40 (211)
Age, years, mean±SD 48.4±11.3 52.1±10.9 56.3±10.9 57.8±10.7 57.7±10.5 56.1±10.5 <0.0001 
Comorbidity index, median (IQR) 0 (0/1.0) 0 (0/0) 0 (0/1.0) 0 (0/1.0) 1.00 (0/1.0) 1.00 (0/2.0) <0.0001 
Carbohydrate metabolism 
 Diabetes, n (%) 4 (6.0) 75 (2.4) 156 (6.6) 145 (12.6) 90 (21.4) 62 (29.5) <0.0001 
 Diabetes type 1, n (%) 1 (1.5) 8 (0.3) 7 (0.37) 3 (0.3) 1 (0.2) 0 (0) 0.50 
 Diabetes type 2 known at baseline, n (%) 1 (1.5) 37 (1.2) 99 (4.2) 92 (7.9) 65 (15.4) 48 (22.7) <0.0001 
 Diabetes type 2 detected at baseline, n (%) 2 (3.0) 30 (0.9) 50 (2.1) 50 (4.3) 24 (5.7) 14 (6.7) <0.0001 
 HbA1c, % 5.30 (5.02/5.60) 5.40 (5.10/5.60) 5.50 (5.20/5.80) 5.60 (5.30/6.00) 5.70 (5.40/6.10) 6.00 (5.60/6.40) <0.0001 
 Glucose, mg/dL 87.0 (81.2/91.1) 88.0 (83.0/93.0) 90.0 (85.0/96.2) 94.0 (87.0/100.0) 95.0 (88.0/103.0) 99.0 (88.2/112.0) <0.0001 
 Insulin, pmol/L 29.2 (22.9/37.0) 33.6 (26.0/43.2) 44.1 (34.1/59.1) 58.0 (44.3/79.8) 73.5 (52.5/104.6) 99.6 (71.1/130.9) <0.0001 
Lipid metabolism 
 Cholesterol, mg/dL 209±33 223±41 230±42 227±41 219±40 210±34 0.11 
 LDL cholesterol, mg/dL 118.6±30.0 135.1±35.6 144.9±36.6 143.0±35.8 136.8±35.3 129.5±29.1 <0.0001 
 HDL cholesterol, mg/dL 75.1±15.0 70.3±15.0 62.7±14.3 57.3±12.8 55.0±12.2 50.3±11.0 <0.0001 
 Triglycerides, mg/dL 72 (58/87) 81 (64/104) 101 (77/135) 119 (92/159) 126 (97/163) 138 (106/175) <0.0001 
Hypertension, n (%) 6 (8.8) 938 (29.5) 1,159 (48.7) 740 (63.8) 311 (73.9) 169 (81.6) <0.0001 
 SBP, mm Hg 118.5±17.5 124.9±17.8 130.8±18.0 133.8±17.5 134.3±16.7 136.0±18.2 <0.0001 
 DBP, mm Hg 76.1±9.3 78.9±9.2 81.9±8.9 83.9±9.4 84.1±9.0 85.5±9.9 <0.0001 
Coronary artery disease, n (%) 1 (1.5) 29 (0.9%) 48 (2.0) 51 (4.4) 16 (3.8) 12 (5.7) <0.0001 
Myocardial infarction, n (%) 1 (1.5) 19 (0.6) 31 (1.3) 31 (2.7) 13 (3.1) 8 (3.8) <0.0001 
Stroke, n (%) 0 (0) 28 (0.9) 34 (1.4) 21 (1.8) 12 (2.9) 2 (0.9) 0.0019 
Peripheral arterial disease, n (%) 1 (1.5) 53 (1.7) 75 (3.1) 57 (4.9) 22 (5.2) 19 (9.0) <0.0001 
Atrial fibrillation, n (%) 0 (0) 33 (1.0) 44 (1.8) 30 (2.6) 10 (2.4) 12 (5.7) 0.00016 
Congestive heart failure, n (%) 0 (0) 19 (0.6) 37 (1.6) 18 (1.6) 12 (2.9) 10 (4.7) 0.00024 
CKD, n (%) 0 (0) 63 (2.0) 111 (4.7) 73 (6.3) 35 (8.4) 17 (8.1) <0.0001 
COPD, n (%) 3 (4.4) 127 (4.0) 135 (5.7) 99 (8.5) 30 (7.1) 27 (12.8) <0.0001 
Cancer, n (%) 8 (11.8) 298 (9.4) 252 (10.6) 139 (12.0) 37 (8.8) 20 (9.5) 0.30 
Depression, n (%) 14 (20.6) 425 (13.4) 412 (17.3) 209 (18.0) 75 (17.9) 51 (24.2) <0.0001 
Chronic arthropathy, n (%) 2 (2.9) 128 (4.0) 148 (6.2) 88 (7.6) 39 (9.3) 15 (7.1) <0.0001 
b WomenBMI, kg/m2p value
Variable<18.5 (68)18.5–<25 (3,179)25–<30 (2,383)30–<35 (1,160)35–<40 (421)≥40 (211)
Age, years, mean±SD 48.4±11.3 52.1±10.9 56.3±10.9 57.8±10.7 57.7±10.5 56.1±10.5 <0.0001 
Comorbidity index, median (IQR) 0 (0/1.0) 0 (0/0) 0 (0/1.0) 0 (0/1.0) 1.00 (0/1.0) 1.00 (0/2.0) <0.0001 
Carbohydrate metabolism 
 Diabetes, n (%) 4 (6.0) 75 (2.4) 156 (6.6) 145 (12.6) 90 (21.4) 62 (29.5) <0.0001 
 Diabetes type 1, n (%) 1 (1.5) 8 (0.3) 7 (0.37) 3 (0.3) 1 (0.2) 0 (0) 0.50 
 Diabetes type 2 known at baseline, n (%) 1 (1.5) 37 (1.2) 99 (4.2) 92 (7.9) 65 (15.4) 48 (22.7) <0.0001 
 Diabetes type 2 detected at baseline, n (%) 2 (3.0) 30 (0.9) 50 (2.1) 50 (4.3) 24 (5.7) 14 (6.7) <0.0001 
 HbA1c, % 5.30 (5.02/5.60) 5.40 (5.10/5.60) 5.50 (5.20/5.80) 5.60 (5.30/6.00) 5.70 (5.40/6.10) 6.00 (5.60/6.40) <0.0001 
 Glucose, mg/dL 87.0 (81.2/91.1) 88.0 (83.0/93.0) 90.0 (85.0/96.2) 94.0 (87.0/100.0) 95.0 (88.0/103.0) 99.0 (88.2/112.0) <0.0001 
 Insulin, pmol/L 29.2 (22.9/37.0) 33.6 (26.0/43.2) 44.1 (34.1/59.1) 58.0 (44.3/79.8) 73.5 (52.5/104.6) 99.6 (71.1/130.9) <0.0001 
Lipid metabolism 
 Cholesterol, mg/dL 209±33 223±41 230±42 227±41 219±40 210±34 0.11 
 LDL cholesterol, mg/dL 118.6±30.0 135.1±35.6 144.9±36.6 143.0±35.8 136.8±35.3 129.5±29.1 <0.0001 
 HDL cholesterol, mg/dL 75.1±15.0 70.3±15.0 62.7±14.3 57.3±12.8 55.0±12.2 50.3±11.0 <0.0001 
 Triglycerides, mg/dL 72 (58/87) 81 (64/104) 101 (77/135) 119 (92/159) 126 (97/163) 138 (106/175) <0.0001 
Hypertension, n (%) 6 (8.8) 938 (29.5) 1,159 (48.7) 740 (63.8) 311 (73.9) 169 (81.6) <0.0001 
 SBP, mm Hg 118.5±17.5 124.9±17.8 130.8±18.0 133.8±17.5 134.3±16.7 136.0±18.2 <0.0001 
 DBP, mm Hg 76.1±9.3 78.9±9.2 81.9±8.9 83.9±9.4 84.1±9.0 85.5±9.9 <0.0001 
Coronary artery disease, n (%) 1 (1.5) 29 (0.9%) 48 (2.0) 51 (4.4) 16 (3.8) 12 (5.7) <0.0001 
Myocardial infarction, n (%) 1 (1.5) 19 (0.6) 31 (1.3) 31 (2.7) 13 (3.1) 8 (3.8) <0.0001 
Stroke, n (%) 0 (0) 28 (0.9) 34 (1.4) 21 (1.8) 12 (2.9) 2 (0.9) 0.0019 
Peripheral arterial disease, n (%) 1 (1.5) 53 (1.7) 75 (3.1) 57 (4.9) 22 (5.2) 19 (9.0) <0.0001 
Atrial fibrillation, n (%) 0 (0) 33 (1.0) 44 (1.8) 30 (2.6) 10 (2.4) 12 (5.7) 0.00016 
Congestive heart failure, n (%) 0 (0) 19 (0.6) 37 (1.6) 18 (1.6) 12 (2.9) 10 (4.7) 0.00024 
CKD, n (%) 0 (0) 63 (2.0) 111 (4.7) 73 (6.3) 35 (8.4) 17 (8.1) <0.0001 
COPD, n (%) 3 (4.4) 127 (4.0) 135 (5.7) 99 (8.5) 30 (7.1) 27 (12.8) <0.0001 
Cancer, n (%) 8 (11.8) 298 (9.4) 252 (10.6) 139 (12.0) 37 (8.8) 20 (9.5) 0.30 
Depression, n (%) 14 (20.6) 425 (13.4) 412 (17.3) 209 (18.0) 75 (17.9) 51 (24.2) <0.0001 
Chronic arthropathy, n (%) 2 (2.9) 128 (4.0) 148 (6.2) 88 (7.6) 39 (9.3) 15 (7.1) <0.0001 

COPD, chronic obstructive pulmonary disease; DBP, diastolic blood pressure; SBP, systolic blood pressure.

Dyslipidemia in obesity is characterized by elevated triglycerides and low HDL cholesterol, whereas total and LDL cholesterol tend to be lower than in normal-weight individuals, which may be related in part to the increased use of lipid-modifying drugs in individuals with obesity.

Nonalcoholic fatty liver disease, defined as a fatty liver index >60 (in absence of alcohol consumption >24 g/day in men or >12 g/day in women) and no other known chronic liver disease, increased significantly with increasing BMI (1.2% in normal-weight individuals and 85% in severe obesity). However, it should be noted that BMI and waist circumference are integral components of the fatty liver index [17].

Cardiovascular Disease and Hypertension

The prevalence of hypertension and cardiovascular disease increased significantly with increasing BMI in both sexes (Table 4a, b). The prevalence of arterial hypertension is more than twice as high in severe obesity as in normal-weight individuals. Clinically manifest cardiovascular disease was about 4 times more frequent in BMI >40 kg/m2 compared with normal weight. This was true for coronary heart disease, peripheral arterial disease, and stroke. Interestingly, atrial fibrillation was also much more common in individuals with overweight and obesity than in those of normal weight.

Other Complications

The prevalence of cancer was slightly higher in participants with overweight than normal weight (9.5% vs. 8.1%, p = 0.049). However, when both sexes were analyzed separately, this was not significant (Table 4a, b). In addition, there was no significant trend across BMI groups, as individuals with obesity had lower cancer prevalence than those with overweight (Table 4a, b). However, an increased prevalence of chronic kidney disease (CKD) and chronic obstructive pulmonary disease (COPD) in male and female participants with overweight and obesity was reported. Chronic arthropathy and depression (Table 4a, b) were associated with BMI only in women, whereas anxiety disorders showed no association with BMI.

Incidence of Complications Associated with BMI

Incidences of the following comorbidities increase with increasing BMI during the first and second 5-year follow-up: cardiovascular and coronary artery disease, myocardial infarction, stroke, peripheral arterial disease, atrial fibrillation, CKD, and COPD (online suppl. Table 4). In the case of chronic liver disease, there is a significant difference between the BMI groups at baseline, but not in the incidence. Cancer incidence over 10 years is not significantly different between BMI groups.

Accordingly, there is a significant decrease of participants without complications with increasing BMI from baseline (49% with a BMI of <18.5 kg/m2, 40% with a BMI of 18.5–<25 kg/m2, 22% with a BMI of 25–<30 kg/m2, and 11% with a BMI of ≥30 kg/m2) to five and 10 years, respectively (41% and 35% with BMI <18.5 kg/m2; 30% and 24% with BMI 18.5–<25 kg/m2; 14% and 10% with BMI 25–<30 kg/m2; and 6.1% and 4.8% with BMI ≥30 kg/m2).

Medications in BMI Classes

To analyze medication use, all participants were asked about their regular medications at baseline and follow-up. On average, participants used 1.8 medications (median 1.0, IQR 0.0–3.0). As BMI increased, there was a steady increase in medication use from a mean of 1.3 (median 1.0, IQR 0.0–2.0) in those with normal weight to 3.3 (median 3.0, IQR 1.0–5.0) in those with severe obesity (BMI >40 kg/m2) (Table 5).

Table 5.

Use of the 20 most common medications according to BMI

ATC CodeBMI, kg/m2p value
all (14,999)<18.5 (86)18.5–<25 (5,100)25–<30 (6,030)30–<35 (2,690)35–<40 (775)≥40 (318)
Age, years, mean±SD 55.0±11.1 49.4±11.7 52.3±10.9 56.1±11.0 57.2±10.9 57.3±10.5 55.7±10.7  
Regular medication,#n 1.00 (0/3.0) 1.00 (0/2.0) 1.00 (0/2.0) 1.00 (0/3.0) 2.00 (1.0/4.0) 3.00 (1.0/5.0) 3.00 (1.0/5.0) <0.0001 
C09 Agents acting on RAAS, n (%) 3,502 (23.6) 5 (5.8) 554 (11.0) 1,445 (24.2) 973 (36.4) 355 (46.0) 170 (53.8) <0.0001 
C07 β-blocking agents, n (%) 2,501 (16.8) 7 (8.1) 422 (8.4) 980 (16.4) 729 (27.3) 251 (32.5) 112 (35.4) <0.0001 
H03 Thyroid therapy, n (%) 2,119 (14.3) 11 (12.8) 665 (13.2) 787 (13.2) 446 (16.7) 141 (18.3) 69 (21.8) <0.0001* 
C10 Lipid-modifying agents, n (%) 1,965 (13.2) 3 (3.5) 334 (6.6) 851 (14.3) 536 (20.1) 176 (22.8) 65 (20.6) <0.0001 
B01 Antithrombotics, n (%) 1,756 (11.8) 6 (7.0) 316 (6.3) 723 (12.1) 501 (18.8) 152 (19.7) 58 (18.4) <0.0001 
G03 Sex hormones, n (%) 1,298 (8.7) 13 (15.1) 644 (12.8) 413 (6.9) 182 (6.8) 35 (4.5) 11 (3.5) <0.0001§ 
C08 Ca-channel blockers, n (%) 1,049 (7.1) 1 (1.2) 139 (2.8) 424 (7.1) 296 (11.1) 125 (16.2) 64 (20.3) <0.0001 
S01 Ophthalmologicals, n (%) 1,010 (6.8) 6 (7.0) 338 (6.7) 409 (6.9) 177 (6.6) 64 (8.3) 16 (5.1) n.s. 
N06 Psychoanaleptics, n (%) 948 (6.4) 6 (7.0) 259 (5.1) 358 (6.0) 224 (8.4) 68 (8.8) 33 (10.4) <0.0001** 
A02 Drugs for acid-related diseases, n (%) 926 (6.2) 2 (2.3) 153 (3.0) 372 (6.2) 270 (10.1) 91 (11.8) 38 (12.0) <0.0001 
A10 Drugs used in diabetes, n (%) 906 (6.1) 3 (3.5) 88 (1.7) 294 (4.9) 307 (11.5) 138 (17.9) 76 (24.1) <0.0001 
C03 Diuretics, n (%) 750 (5.1) 0 (0) 62 (1.2) 256 (4.3) 242 (9.1) 123 (15.9) 67 (21.2) <0.0001 
A12 Mineral supplements, n (%) 694 (4.7) 9 (10.5) 261 (5.2) 280 (4.7) 87 (3.3) 38 (4.9) 19 (6.0) n.s. 
V06 General nutrients, n (%) 616 (4.1) 5 (5.8) 242 (4.8) 237 (4.0) 87 (3.3) 32 (4.1) 13 (4.1) n.s. 
R03 Drugs for obstructive airway disease, n (%) 563 (3.8) 3 (3.5) 153 (3.0) 204 (3.4) 133 (5.0) 48 (6.2) 22 (7.0) <0.0001 
G04 Urologicals, n (%) 563 (3.8) 0 (0) 113 (2.2) 263 (4.4) 147 (5.5) 30 (3.9) 10 (3.2) n.s. 
M04 Anti-gout preparations, n (%) 476 (3.2) 0 (0) 43 (0.9) 171 (2.9) 165 (6.2) 62 (8.0) 35 (11.1) <0.0001 
M01 Anti-inflammatory and antirheumatic agents, n (%) 442 (3.0) 2 (2.3) 89 (1.8) 165 (2.8) 115 (4.3) 44 (5.7) 27 (8.5) <0.0001 
A11 Vitamins, n (%) 343 (2.3) 4 (4.7) 130 (2.6) 138 (2.3) 53 (2.0) 14 (1.8) 4 (1.3) n.s. 
B03 Antianemic preparations, n (%) 329 (2.2) 3 (3.5) 132 (2.6) 118 (2.0) 51 (1.9) 19 (2.5) 6 (1.9) n.s. 
ATC CodeBMI, kg/m2p value
all (14,999)<18.5 (86)18.5–<25 (5,100)25–<30 (6,030)30–<35 (2,690)35–<40 (775)≥40 (318)
Age, years, mean±SD 55.0±11.1 49.4±11.7 52.3±10.9 56.1±11.0 57.2±10.9 57.3±10.5 55.7±10.7  
Regular medication,#n 1.00 (0/3.0) 1.00 (0/2.0) 1.00 (0/2.0) 1.00 (0/3.0) 2.00 (1.0/4.0) 3.00 (1.0/5.0) 3.00 (1.0/5.0) <0.0001 
C09 Agents acting on RAAS, n (%) 3,502 (23.6) 5 (5.8) 554 (11.0) 1,445 (24.2) 973 (36.4) 355 (46.0) 170 (53.8) <0.0001 
C07 β-blocking agents, n (%) 2,501 (16.8) 7 (8.1) 422 (8.4) 980 (16.4) 729 (27.3) 251 (32.5) 112 (35.4) <0.0001 
H03 Thyroid therapy, n (%) 2,119 (14.3) 11 (12.8) 665 (13.2) 787 (13.2) 446 (16.7) 141 (18.3) 69 (21.8) <0.0001* 
C10 Lipid-modifying agents, n (%) 1,965 (13.2) 3 (3.5) 334 (6.6) 851 (14.3) 536 (20.1) 176 (22.8) 65 (20.6) <0.0001 
B01 Antithrombotics, n (%) 1,756 (11.8) 6 (7.0) 316 (6.3) 723 (12.1) 501 (18.8) 152 (19.7) 58 (18.4) <0.0001 
G03 Sex hormones, n (%) 1,298 (8.7) 13 (15.1) 644 (12.8) 413 (6.9) 182 (6.8) 35 (4.5) 11 (3.5) <0.0001§ 
C08 Ca-channel blockers, n (%) 1,049 (7.1) 1 (1.2) 139 (2.8) 424 (7.1) 296 (11.1) 125 (16.2) 64 (20.3) <0.0001 
S01 Ophthalmologicals, n (%) 1,010 (6.8) 6 (7.0) 338 (6.7) 409 (6.9) 177 (6.6) 64 (8.3) 16 (5.1) n.s. 
N06 Psychoanaleptics, n (%) 948 (6.4) 6 (7.0) 259 (5.1) 358 (6.0) 224 (8.4) 68 (8.8) 33 (10.4) <0.0001** 
A02 Drugs for acid-related diseases, n (%) 926 (6.2) 2 (2.3) 153 (3.0) 372 (6.2) 270 (10.1) 91 (11.8) 38 (12.0) <0.0001 
A10 Drugs used in diabetes, n (%) 906 (6.1) 3 (3.5) 88 (1.7) 294 (4.9) 307 (11.5) 138 (17.9) 76 (24.1) <0.0001 
C03 Diuretics, n (%) 750 (5.1) 0 (0) 62 (1.2) 256 (4.3) 242 (9.1) 123 (15.9) 67 (21.2) <0.0001 
A12 Mineral supplements, n (%) 694 (4.7) 9 (10.5) 261 (5.2) 280 (4.7) 87 (3.3) 38 (4.9) 19 (6.0) n.s. 
V06 General nutrients, n (%) 616 (4.1) 5 (5.8) 242 (4.8) 237 (4.0) 87 (3.3) 32 (4.1) 13 (4.1) n.s. 
R03 Drugs for obstructive airway disease, n (%) 563 (3.8) 3 (3.5) 153 (3.0) 204 (3.4) 133 (5.0) 48 (6.2) 22 (7.0) <0.0001 
G04 Urologicals, n (%) 563 (3.8) 0 (0) 113 (2.2) 263 (4.4) 147 (5.5) 30 (3.9) 10 (3.2) n.s. 
M04 Anti-gout preparations, n (%) 476 (3.2) 0 (0) 43 (0.9) 171 (2.9) 165 (6.2) 62 (8.0) 35 (11.1) <0.0001 
M01 Anti-inflammatory and antirheumatic agents, n (%) 442 (3.0) 2 (2.3) 89 (1.8) 165 (2.8) 115 (4.3) 44 (5.7) 27 (8.5) <0.0001 
A11 Vitamins, n (%) 343 (2.3) 4 (4.7) 130 (2.6) 138 (2.3) 53 (2.0) 14 (1.8) 4 (1.3) n.s. 
B03 Antianemic preparations, n (%) 329 (2.2) 3 (3.5) 132 (2.6) 118 (2.0) 51 (1.9) 19 (2.5) 6 (1.9) n.s. 

Significances were adjusted for age and sex; p values were corrected for multiple testing with Bonferroni-Holm method.

n.s., not significant.

#Data are presented as median (interquartile range).

*Significant only for H03A (thyroid preparations, n = 1,462; p < 0.0001).

**Significant only for N06A (antidepressants, n = 561; p < 0.0001).

§Inverse association with BMI.

In a next step, the 20 most frequently mentioned drug groups were analyzed by ATC code in the different BMI groups (Table 5). Medications used to treat complications of obesity, i.e., metabolic and cardiovascular diseases, were used significantly more frequently in patients with obesity than in normal-weight individuals. Other groups of medications with association to BMI were thyroid medications, antithrombotic medications, antidepressants, acid-related medications, obstructive airway disease medications, anti-inflammatory/antirheumatic medications, and anti-gout medications. Sex hormones were used more frequently by participants with normal-weight and underweight. Among the 20 most used medications are also mineral supplements, general nutrients, and vitamins, but the intake is independent of weight.

Over the past decades, the prevalence of obesity has steadily increased. The current data from the Gutenberg Health Study show in a cohort representative of Germany of 15,010 subjects aged 35–74 years that 40% (48% of men and 32% of women) of participants are overweight and 25% (26% of men and 24% of women) have obesity. Very similar prevalences for obesity were reported by the WHO for Europe in 2016 (22% for men and 25% for women) [4, 18]. Still, significantly higher prevalences are found in the USA with 32% for men and 36% for women [19]. According to the 2014/2015 GEDA-EHIS study of the Robert Koch Institute, the prevalence of obesity in Germany is assumed to be 18% [20], although the lower prevalence can probably be explained by self-reported data collection, which generally yields lower BMI results as compared to measured values [21]. Interestingly, men are more likely to be overweight than women (48 vs. 32%), whereas the proportion of obesity is almost equally distributed among sexes (26 vs. 24%). This differs from the USA and the WHO reports for Europe, which always describe a higher female proportion in obesity. In our cohort, BMI in females increases significantly more with age than in male subjects. Overall, in both sexes, weight and concomitant BMI increase significantly at ages between 35 and 55. In older participants, the increase in weight slows down, so that in the 65–74 years age group, there is no longer an increase in body weight and weight loss and increase balance each other out. This is consistent with the surveys of other studies [22, 23].

The very detailed data collection in our study allows us to make statements about concomitant diseases, but also about laboratory parameters and medication, and respective changes over time. As expected, the incidence of type 2 diabetes mellitus, dyslipidemia, hypertension, cardiovascular disease, CKD, and COPD increased with increasing BMI and age in both sexes [19, 24‒27]. This strong weight-dependent correlation is also reflected in the type and distribution of drugs. The use of drugs in Germany is recorded by the health insurance funds and the Federal Statistical Office. However, it is determined on the basis of prescriptions, and no distinction is made between long-term and on-demand medication. Dietary supplements, as well as nonreimbursable drugs, are not recorded in this system. Our data show that minerals and vitamin preparations are definitely among the 20 most frequently used medications. The trend with increasing BMI toward more medications, and thus toward polypharmacy, is consistent with the literature [28] and reflected in the prescription figures of health insurance companies [29‒32].

In our study, the prevalence for numerous obesity-associated conditions and associated medications increases continuously with BMI. In addition, the incidence of obesity-associated comorbidities increases with BMI over the next 10 years. Therefore, even a modest reduction in BMI can be expected to have a beneficial effect on complications and medication required. Our study strongly suggests that the proportion of patients with obesity in our total collective still increases over the observation period of 10 years, especially for the male subjects, in the Mainz/Mainz-Bingen area [18, 20].

The high prevalence of obesity in Germany is associated with relevant health consequences and an increased need for medication. Our data show that the prevalence of obesity still increases. Accordingly, a multimodal strategy for prevention and adequate treatment of overweight and obesity is urgently needed.

The prospective study was approved by German law (Landeskrankenhausgesetz §36 and §37) in accordance with the Declaration of Helsinki and by the Ethics Committee of “Landesärztekammer Rheinland-Pfalz” [837.020.07(5555)]. Written informed consent was obtained from participants prior to the study.

The authors state that they have no conflict of interest with this publication.

The Gutenberg Health Study is funded by the state government of Rhineland-Palatinate (Rhineland-Palatinate Foundation for Innovation, contract AZ 961-386261/733), the research programs “Wissen schafft Zukunft” and “Center for Translational Vascular Biology (CTVB)” of the Johannes Gutenberg University Mainz, and by a contract with Boehringer Ingelheim and PHILIPS Medical Systems, which includes an earmarked grant for the Gutenberg Health Study.

Philipp S. Wild and Thomas Münzel are principal investigators of the German Center for Cardiovascular Research (DZHK; BMBF 81Z0210103). Philipp S. Wild is principal investigator of the curATime research cluster (BMBF 03ZU1202AA, 03ZU1202CD, 03ZU1202DB, 03ZU1202JC, 03ZU1202KB, 03ZU1202LB, 03ZU1202MB, 03ZU1202OA) and principal investigator of the DIASyM research core (BMBF 161L0217A, 031L0217A).

Tanja Falter: study concept, data analysis and compilation, writing of the manuscript, and approval; Anita M. Hennige: study concept and design, revision of the manuscript, and approval; Andreas Schulz and Alexander Gieswinkel: data acquisition and statistical analysis, revision of the manuscript, and approval; Johannes Lotz, Heidi Rossmann, Matthias Michal, Norbert Pfeiffer, and Thomas Münzel: revision of the manuscript and approval; Manfred Beutel: psychosomatic advice, revision of the manuscript, and approval; Irene Schmidtmann: statistical advice, revision of the manuscript, and approval; Philipp S. Wild: study concept and design, data acquisition, revision of the manuscript, approval; and Karl J. Lackner: study concept and design, data analysis and compilation, revision of the manuscript, writing of the manuscript, and approval.

Data are not publicly available because this is not covered by the informed consent of participants. However, access to the data in the local database is possible upon reasonable request according to the ethics vote. Interested scientists can make their requests to the Gutenberg Health Study Steering Committee (e-mail: info@ghs-mainz.de). Further inquiries can be directed to the corresponding author.

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