Introduction

The prevalence of obesity has reached epidemic proportions. Worldwide in 2008, 1.5 billion adults were overweight, defined as a body mass index (BMI) of 25 kg/m2 or higher. Of these adults, over 200 million men and nearly 300 million women were obese (BMI ≥ 30 kg/m2) [1]. In the Netherlands, the prevalence of overweight and obesity is relatively low in comparison with other European countries and the USA [2, 3], but steadily increasing [4, 5]. In the Netherlands in 2011, 48 % of the population were overweight, and 11 % were obese [2]. In comparison, the prevalence of overweight in the US in 2007–2008 was 68 %, and the prevalence of obesity was 34 % [6].

Obesity is a well-established risk factor for type 2 diabetes, cardiovascular diseases (CVD), chronic kidney disease, and certain cancers and is therefore a major public health problem [7, 8]. In addition, obesity may contribute to debilitating health problems such as osteoarthritis and pulmonary diseases [8], and is related to stress, anxiety and depression [9, 10]. Obesity-related diseases are highly prevalent [8] and related to premature death [11]. Therefore, understanding of the underlying pathofysiology of obesity-related diseases is important.

Obesity is a complex, multifactorial condition, and many endogenous genetic, endocrine and inflammatory pathways and environmental factors are involved in the development of obesity-related diseases. The hierarchy and interactions between these pathways have only been identified to a limited extent. The notion of obesity as a heterogeneous condition is underscored by the fact that the threshold for adipose tissue accumulation to ultimately result in disease apparently varies considerably among obese individuals. In order to tailor preventive strategies in obesity and to treat obesity-related diseases in terms of personalized care, it is extremely important to improve the risk-stratification of obese individuals by extensive phenotyping and dissecting causal pathways that contribute to the pathogenesis of obesity-related disorders.

We hypothesize that obesity affects major systemic responses in certain subgroups, such as dyslipidemia, inflammation, insulin resistance, hypercoagulation, oxidative stress and endothelial dysfunction, that may be causally related to the occurrence of major common diseases. In addition, we hypothesize that the extent and occurrence of these diseases is related to individual characteristics, including genetics, differential fat distribution, and environmental factors including diet and physical activity, as well as interactions between the various systemic responses, and the (subclinical) disease outcomes. The Netherlands Epidemiology of Obesity (NEO) study is designed to investigate the pathways that lead to obesity-related diseases and conditions in a population-based prospective cohort study of individuals aged 45–65 years, with an oversampling of individuals with overweight or obesity. As subclinical endpoints insulin resistance, hypertension, dyslipidemia, airways obstruction, atherosclerosis, and non-alcoholic fatty liver disease will be studied. Clinical endpoints of the NEO study include type 2 diabetes, CVD, thrombosis, chronic kidney disease, asthma, chronic obstructive pulmonary disease (COPD), osteoarthritis, cirrhosis, depression, and mortality. The interrelationships between classic established risk factors and novel determinants and between various diseases and conditions that will be studied in the NEO study are depicted in Figure 1.

Fig. 1
figure 1

Path diagram of the hypothetical pathways between genetic and behavioral factors and disease in persons with overweight or obesity. Pathways may also be interlinked, but these associations are not shown. NAFLD Non-alcoholic fatty liver disease, Type 2 DM Type 2 diabetes mellitus, CVD Cardiovascular diseases (angina pectoris, myocardial infarction, congestive heart failure, stroke or peripheral vascular disease), Thrombosis Deep venous thrombosis and/or pulmonary embolism, CKD Chronic kidney disease, COPD Chronic obstructive pulmonary disease. 1inflammation (increased levels of CRP, TNF-a, IL-6 and leptin, and decreased levels of adiponectin), 2Adipokines: TNF-a, IL-6, leptin, adiponectin, resistin, visfatin, RBP-4, renin, angiotensinogen. 3Blood coagulation: thrombin generation, factor VIII, fibrinogen, von Willebrand factor, protein C, protein S, antithrombin, thrombin-antithrombin complexes (TAT), and fragment 1,2

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Study design NEO study

Study population

Men and women aged between 45 and 65 years with a self-reported BMI of 27 kg/m2 or higher, living in the greater area of Leiden (in the West of the Netherlands) were eligible to participate in the NEO study. In addition, all inhabitants aged between 45 and 65 years from one municipality (Leiderdorp) were invited, irrespective of their BMI.

The study was approved by the medical ethical committee of the Leiden University Medical Center (LUMC). Eligible participants were given detailed written information on the study, in addition to an oral explanation at the study site. Participants have given written informed consent for participation in the study, for storage of urine and blood samples, and for obtaining medical records and information on vital status during follow-up.

Recruitment of participants started in September 2008 and completed at the end of September 2012. In total, 6,673 participants have been included, of whom 5,217 with a BMI of 27 kg/m2 or higher. According to the WHO criteria, 2,880 participants had overweight (BMI of 25–30 kg/m2) and 3,020 participants were obese (BMI of 30 kg/m2 or higher).

Recruitment strategies

Participants were recruited via three recruitment strategies. First, participants were recruited by general practitioners in the area of Leiden, The Netherlands. The majority of these general practitioners (GP) are part of a research network of university-affiliated primary care centers (LEON). General practitioners sent invitations to participate in the NEO study to their population aged between 45 and 65 years. Men and women within this age group and with a self-reported BMI of 27 kg/m2 or higher were invited to contact the NEO study center by telephone or by completing a web-based form. After 2 weeks, a reminder was sent. Second, participants were recruited through advertisements in local newspapers and through posters distributed in public areas of Leiden and surroundings. Third, participants were recruited via the registries of three municipalities surrounding Leiden (Katwijk, Leiderdorp and Teylingen). All inhabitants aged between 45 and 65 years were sent an invitation to participate in the NEO study. Inhabitants of Katwijk and Teylingen were invited to participate if they had a self-reported BMI of 27 kg/m2 or higher. All inhabitants aged between 45 and 65 years of Leiderdorp were invited to participate, irrespective of their BMI.

Table 1 gives the number of included participants and the age, sex and BMI, stratified by recruitment source. The BMI distribution of the participants from Leiderdorp is similar to the BMI distribution of the Dutch general population [12], suggesting that the Leiderdorp population may be representative for this age group.

Table 1 Number and characteristics of participants of the NEO study stratified by recruitment source (n = 6,673)
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Cross-sectional analyses with the baseline data will be weighted to the BMI distribution of the Leiderdorp population, so that results apply to the general population.

Study design

The NEO study is a population-based, prospective cohort study of individuals aged 45–65 years, with an oversampling of individuals with overweight or obesity. Participants were invited to come to the NEO study center of the LUMC for one baseline study visit after an overnight fast. Prior to this study visit, participants collected their urine over 24 h and completed a general questionnaire at home to report demographic, lifestyle, and clinical data in addition to questions on diet, physical activity, symptoms of osteoarthritis, sleep and anxiety, quality of life and depression. The participants were asked to bring all medication they were using in the month preceding the study visit to the NEO study site, both prescribed medication, as well as self-medication such as vitamin supplements. Names and dosages of all medication were recorded in a database by research nurses. At the NEO study center several measurements have been performed including an extensive physical examination and blood sampling. Magnetic resonance imaging (MRI) of abdominal fat, pulse wave velocity, heart, and brain, magnetic resonance spectroscopy (MRS) of the liver, indirect calorimetry, dual-energy X-ray absorptiometry, accelerometry, and heart rate variability measurements were performed in random subsets of participants. The measurements are listed in Table 2 and described in detail below.

Table 2 List of baseline measurements of the NEO study
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The results of all laboratory analyses and the ECGs and MRI scans were screened by specialists on incidental findings. Incidental abnormal results that are likely to have serious health consequences if left undiagnosed, have been disclosed to the participants and their general practitioners, accompanied by an advice for further work-up. The number (% of screened) of incidental findings were 6 (0.1) for the laboratory analyses, 25 (0.4) for ECGs, 48 (1.9) for MRI of the body, 8 (0.7) for MRI of the brain, and 11 (0.9) of MRI of the knee.

Within 2 weeks after the study visit, participants received feedback on the results of tests for which, according to national guidelines, advice or testing is recommended (e.g. blood pressure, renal function, lung function, and blood concentrations of glucose, triglycerides, and total and HDL-cholesterol). Abnormal results were marked and accompanied with an advice to consult the general practitioner. Results of other measurements have not been disclosed.

Participants are followed for the incidence of obesity-related diseases and mortality.

Data collection

Questionnaires

Questionnaires were sent to all participants to be completed at home. The general questionnaire included questions about demographic, lifestyle, and clinical data such as family history of type 2 diabetes, CVD, stroke, colon cancer and breast cancer, asthma and allergies in first-degree relatives and personal medical history, and about current weight, weight change in the past 5 years, weight at the age of 20 years, and birth weight. In addition, validated questionnaires on diet, physical activity, symptoms of osteoarthritis, sleep, anxiety, and quality of life were completed, as described below.

Dietary intake

Dietary intake was assessed using a semi-quantitative food frequency questionnaire (FFQ), originally validated in the Dutch general population [13]. For calibration purposes in our study population, two 24-h dietary recalls have been performed by telephone in a random subsample of 110 men and 119 women.

Physical activity

Participants reported their usual physical activity over the past 4 weeks on the Short Questionnaire to Assess Health-enhancing physical activity (SQUASH), a previously validated tool to assess physical activity in the Dutch population [14, 15].

Symptoms of osteoarthritis

An osteoarthritis phenotype was determined based on the clinical criteria sets from the American College of Rheumatology (ACR), using the Knee injury and Osteoarthritis Outcome Score (KOOS) [16, 17] and the Australian/Canadian (AUSCAN) Osteoarthritis Hand Index [18, 19].

Sleep

Several questionnaires were completed to assess daytime sleepiness (Epworth sleepiness scale) [20], quality of sleep (Pittsburg sleep quality index) [21], and the presence of obstructive sleep apnea syndrome (Berlin questionnaire) [22].

Depression and anxiety

Several validated subjective stress indicators were collected including the Inventory of Depressive Symptoms [23], Beck Anxiety Inventory [24, 25], and the Brugha questionnaire of negative life events [26].

Quality of life

The SF-36® Health Survey was used to assess quality of life. The SF-36 is a multipurpose, 36-item survey that measures eight domains of health: physical functioning, role limitations due to physical health, bodily pain, general health perceptions, vitality, social functioning, role limitations due to emotional problems, and mental health. It yields scale scores for each of these eight health domains, and two summary measures of physical and mental health: the Physical Component Summary (PCS) and Mental Component Summary (MCS) [27–29].

Urine sampling

Containers together with a detailed instruction were distributed to all participants for collection of 24-h urine samples prior to the study visit. In addition, a separate early morning urine sample was collected. This morning urine sample was analyzed for albumin and creatinine in the central clinical chemical laboratory of the LUMC (Table 2). The 24-h urine sample was aliquoted and 1.5 mL aliquots were stored at −80 °C for future analyses of urinary concentrations of nitrogen, creatinine, cortisol, catecholamines, and other research questions.

Fasting and postprandial blood sampling

A first blood sample of 108 mL was taken after an overnight fast of at least 10 h. Within 5 min after the first blood sample, participants drank a liquid mixed meal. This meal (total 400 mL) contained 600 kCal, with 16 percent of energy (En%) derived from protein, 50 En% carbohydrates, and 34 En% fat. Two postprandial blood samples of 63 mL were drawn 30 and 150 min after the mixed meal. Subjective ratings of hunger, satiety, fullness and prospective food consumption were made on 100 mm visual analogue scales (VAS) immediately before the meal and before drawing the two postprandial blood samples.

Serum, heparin-plasma, citrated-plasma and EDTA-plasma were collected during each of the threeblood draws. Serum or plasma concentrations of glucose, insulin, HbA1c, total cholesterol, high-density lipoprotein cholesterol, triglycerides, albumin, creatinine, 25-hydroxyvitamin D, alanine transaminase, aspartate transaminase, calcium, sodium, potassium, and uric acid were determined in the central clinical chemistry laboratory of the LUMC by using standard methods (Table 3). Hemoglobin, hematocrit, white blood cell count, mean corpuscular volume, platelet count, platelet distribution width, and mean platelet volume were determined in the central clinical hematology laboratory of the LUMC by using standard methods (Table 3). Throughout the study biases were below the maximum allowable biases based on biological variation [30].

Table 3 Laboratory analyses of blood and urine samples in the NEO study
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The remaining blood was separated into plasma and serum, and aliquots were stored at −80 °C for future analyses of inflammatory markers, incretines, adipokines, markers of oxidative stress, haemostatic factors and markers related to other research questions. Genomic DNA was isolated and stored for SNP genotyping analyses.

Physical examination

All participants underwent an extensive physical examination, including anthropometry, blood pressure measurements, electrocardiography (ECG), and measurements of the carotid intima-media thickness (cIMT) and of the pulmonary function. Height was measured with a vertically fixed, calibrated tape measure. Body weight and percent body fat were measured by the Tanita bio impedance balance (TBF-310, Tanita International Division, UK) without shoes and one kilogram was subtracted to correct for the weight of clothing. BMI was calculated by dividing the weight in kilograms by the height in meters squared. Waist circumference was measured with a horizontally placed tape measure mid-way between the lower costal margin and the iliac crest with a precision of 0.1 cm. Hip circumference was measured at the maximum circumference of the buttocks.

Brachial blood pressure was measured in a seated position on the right arm using a validated automatic oscillometric device (OMRON, Model M10-IT, Omron Health Care Inc, IL, USA). Blood pressure was measured three times with 5 min rest between consecutive measurements. The mean systolic and diastolic blood pressure was calculated.

All participants were examined on symptoms of osteoarthritis by examination of the presence of swelling and hard tissue enlargement of the interphalangeal joints of the hands and knees, and crepitations of the knees.

A resting 12-lead ECG was obtained using a Mortara Eli-350 (Mortara Instrument Inc., Milwaukee, WI, USA). The raw data were extracted and transferred to the University of Glasgow ECG core lab where ECGs were automatically processed and Minnesota codes assigned using the University of Glasgow ECG analysis program.

Carotid intima-media thickness

The cIMT was assessed by ultrasonography of the far wall of the left and right common carotid arteries (CCA) along a 15 mm long section 10 mm proximal of the bifurcation in recumbent position. A 7.5–10 MHz linear-array transducer (Art.Lab version 2.1, Esaote, Maastricht, The Netherlands) in B-mode setting was used to visualize the distal CCA and a wall track system was used to detect the lumen-intima and media-adventitia boundaries. The cIMT was measured in three predefined angles per side (180, 135 and 90 degrees for the right CCA and 180, 225 and 270 degrees for the left CCA).

Pulmonary function

Forced expiratory volume in one second (FEV1) and forced vital capacity (FVC) were determined by spirometry. FEV1 is a volumetric measurement, a reflection of the speed of emptying of the lung, and therefore, indirectly of airflow. The FVC is the maximum volume obtained by a forced exhalation from a maximal inspiration. Participants were required to perform at least three forced expiratory maneuvers. The highest FEV1 value of the minimum of three tests with acceptable curves was used in analyses. The lung function results are expressed as percentage of the predicted values of individuals with similar characteristics (height, age, sex).

The following paragraphs describe the protocols for MRI and MRS, indirect calorimetry, dual-energy X-ray absorptiometry, accelerometry, and heart rate variability measurements, which were performed in subsets of participants. Approximately fifty percent of the participants without contraindications for MRI were appointed to different compositions of MRI studies according to standardized protocols. The other measurements were randomly distributed over all participants.

MRI and MRS measurements

A screening form was completed by all participants at the time of inclusion in the NEO study, asking about anything that might create a health risk or interfere with imaging (most notably metallic devices, or claustrophobia). A body circumference of more than 1.70 m was an additional contraindication. Abdominal subcutaneous and visceral fat was assessed in 2,580 participants, in combination with imaging of the pulse wave velocity of the aorta, and proton (1H)-MRS of the liver to assess hepatic triglyceride content. In addition, either the heart was imaged (1,207 participants), or the brain (1,212 participants).

Abdominal subcutaneous and visceral fat depots were quantified by a turbo spin echo imaging protocol. At the level of the 5th lumbar vertebra 3 transverse images each with a slice thickness of 10 mm were obtained during a breath-hold [31].

Velocity-encoded MRI was used for assessment of transmitral flow for evaluation of LV diastolic function and pulse wave velocity (PWV) of the aorta. Data were analysed using MASS and FLOW software.

The heart was imaged in short-axis view using a ECG-triggered balanced turbo-field-echo sequence. Imaging of the brain was performed with T2-weighted and FLAIR (white matter lesions), diffusion weighted MRI (ischemic changes) and susceptibility weighted scans (microbleeds) with 3 mm contiguous slices covering the entire brain. In addition, isotropic 3D-T1-weighted MRI was performed (atrophy) with a 1.5 mm resolution also covering the entire brain. Data were analysed using FSL and Q-BRAIN software.

In another 1,285 participants a knee osteoarthritis phenotype was determined based on structural osteoarthritic damage in the right knee as detected at MRI and assessed by the Knee Osteoarthritis Score System (KOSS).

All imaging was performed on an MR system operating at a field strength of 1.5 Tesla (Philips Medical Systems, Best, Netherlands).

Indirect calorimetry

Indirect calorimetry was performed in 1,452 participants. After an overnight fast and a period of resting for 15 min, participants were placed under a ventilated hood while lying on a bed, awake, in a quiet room for 30 min. The volume of oxygen inspired (\( \dot{V} \)O2) and the expired volume of carbon dioxide (\( \dot{V} \)CO2) were measured every minute (Oxycon Pro). Resting metabolic rate and substrate oxidation rates were calculated using standard formulas [32].

Dual-energy X-ray absorptiometry

Dual-energy X-ray absorptiometry (DXA) was used to asses bone mineral densitometry (BMD), total fat mass, lean body mass, abdominal fat mass, and abdominal aortic calcifications in 916 participants (Hologic Discovery A, Tromp Medical BV, Castricum, The Netherlands). Absolute BMD values, Z-scores and T-scores (number of standard deviations below the BMD of a younger reference group) for lumbar spine (L1–L4) and proximal femur were reported. Total fat mass (kg) was assessed from the whole-body DXA scans. The androidal or abdominal region of interest was defined as 20 % from pelvis cut to neck cut. Abdominal fat mass is the weight of fat tissue in this region. Lateral images of the thoraco-lumbar spine were obtained to assess vertebral deformities. Abdominal aortic calcification on lateral DXA images was assessed using a previously validated 8-point aortic calcification scale [33].

Accelerometry, heart rate variability and sleep patterns

Fifteen percent of the participants (n = 955) were equipped with an accelerometer combined with 2 ECG electrodes (ActiHeart®, CamNtech Ltd, UK) for four consecutive days. The Actiheart was placed on the chest of the participants at the level of the third intercostal space. This combined heart rate monitor and accelerometer simultaneously measures heart rate and uniaxial (vertical when standing up) acceleration of the torso. In a subgroup of participants who were equipped with an Actiheart, an 8-min ramped step test was performed to assess the individual relationship between heart rate and workload. Using a branched equation algorithm the acceleration and heart rate information was translated into calibrated estimates of physical activity energy expenditure and of minutes per day spent in several MET-categories [34, 35]. In addition, measures of heart rate variability (HRV) are calculated for assessing activity of the cardiac autonomic nervous system [36].

A small subgroup (n = 360) not allocated to the Actiheart were equipped with a single accelerometer (ActiWatch®, CamNtech Ltd, UK) for a period of 7 days to collect objective data on sleep patterns for multiple days in a person’s ambulatory environment. This noninvasive approach enables to objectively assess sleep onset latency, number of awakenings, total sleep time, wake after sleep onset, and sleep efficiency [37].

Ascertainment of incident diseases during follow-up

Study endpoints of the NEO study include clinical diagnoses of type 2 diabetes, CVD (angina pectoris, myocardial infarction, congestive heart failure, stroke or peripheral vascular disease, deep venous thrombosis and/or pulmonary embolism), COPD, asthma, chronic kidney disease, osteoarthritis, cirrhosis, depression, and mortality (Fig. 1).

Participants are followed for the incidence of these obesity-related diseases via postal follow-up questionnaires, through the medical records of their general practitioner, and by linkage with hospital discharge databases. Information on vital status and causes of death are obtained from the Central Bureau of Statistics Netherlands, which stores all Dutch death certificates.

In the Netherlands, general practitioners keep an electronic patient record (EPR) of each patient that covers all medical information concerning the patient including information on prescriptions and reports from laboratories and specialists. Drug prescriptions in the EPR are coded according to the Anatomical Therapeutic Chemical (ATC) codes [38]. Confirmed diagnoses are coded according to the International Classification of Primary Care (ICPC) [39]. NEO participants are marked as such in the electronic information system of the general practitioner. At each follow-up moment, incident diagnoses of the study endpoints, laboratory results and medication prescriptions are retrieved from the EPR’s of the NEO participants. Four years after the start of the study, data is extracted for the first time, which will be repeated with three-year intervals.

Statistical considerations

Sample size

Each of the study endpoints has an incidence of 1 per 1,000 person-years (ischaemic stroke) to 10 per 1,000 person-years (osteoarthritis) in the general population [40–44]. For obese individuals the incidences will be 1.3 (asthma, myocardial infarction) to 10-fold (osteoarthritis) higher [8, 43, 45–48]. As an example, we estimated the number of cases and incidence rates for type 2 diabetes [49] and coronary heart disease in our study population after a mean follow-up of 4 years, on the basis of age-standardized incidence rates of type 2 diabetes and coronary heart disease [40] in the Dutch population aged 45–65 years. For type 2 diabetes, we estimated to detect at least 343 cases with a corresponding incidence rate with 95 % confidence interval of 1.43 (1.28, 1.59) per 100 person-years. For coronary heart disease at least 322 cases are expected with an incidence rate of 1.33 (1.19, 1.49) per 100 person-years.

Imputation

MRI techniques, indirect calorimetry, dual-energy X-ray absorptiometry, and accelerometry are too time-consuming and expensive to be performed in all participants. We will use imputation techniques which allow performing these measurements in random subsets of the participants and imputing them in the remainder of the study population, based on their relation to other more feasible measurements that are performed in the total study population [50].

Reliability

The short-term and long-term reliability of the measurements in the NEO study is evaluated by assessment of the magnitude of measurement error and intra individual variation in all measurements by estimation of the intraclass correlation coefficient (ICC) of two repeated measurements [51]. To that extent, repeated measurements have been performed in 183 participants who have been invited to come to the LUMC for a second study visit. For the evaluation of the short-term reliability, the second visit occurred approximately 3 months after the first visit (n = 100). For the long-term reliability, the second visit occurred approximately 2.5 years after the first visit (n = 83).

Conclusion

The NEO study investigates pathways that lead to obesity-related diseases. The collection of data started in September 2008 and completed at the end of September 2012. Cross-sectional analyses with baseline measurements are currently ongoing. Participants are followed for the incidence of obesity-related diseases and mortality. A better understanding of the mechanisms underlying the development of disease in obesity may help to identify individuals who are susceptible to the detrimental metabolic, cardiovascular and other consequences of obesity and has implications for the development of prevention and treatment strategies.