Data collection

(i) The quantitative part (a) Oral glucose tolerance test

We informed all women to avoid unusual hard physical activity, and unusual diet such as high or low carbohydrate diet two days before test. At the test day, all women attended a five-point OGGT at their respective study hospitals, starting between 08.00-10.00 am, after at least an 8 hours overnight fast that also included no smoke or snuff (Fig. 5). On arrival, they signed an

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informed consent in their native language, before delivering a urine test to exclude infection or pregnancy. Then, the study personnel inserted a catheter in an elbow vein (the antecubital vein) for blood sampling. A slow sodium chloride 0.9% infusion kept the catheter open during the OGTT. Blood samples for glucose, insulin, C-peptide, HbA1c, routine clinical chemistry, lipids, incretins and DNA were taken. This dissertation only includes biomarkers related to glucose, insulin, C-peptide and HbA1c. HbA1c was collected at time point 0 minute, while glucose, insulin and C-peptide were collected at 0, 15, 30, 60 and 120 minutes after intake of 75 g anhydrated glucose. All women were asked to consume the glucose load within 5 minutes. During the OGTT, the women remained fasted and answered questionnaires about demographics, their previous pregnancy, physical activity and quality of life. In addition, the women were asked to perform a web-based food frequency questionnaire during the last hour of the OGTT. This dissertation only includes data related to demographics, previous

pregnancy, and physical activity.

Fig. 5. Overview of the procedures during the five-point oral glucose tolerance test (OGTT). Figure was produced in Servier Medical Art, provided by Servier, licensed under a Creative Commons Attribution 3.0 license.

(b) Clinical and anthropometric measurements

Before the OGTT, we measured blood pressure, weight, height, waist and hip circumference.

Blood pressure was calculated as the mean of the last two of three measurements in the sitting position after five min rest (electronic sphygmomanometer Riester Ri Champion N, Rudolf Riester GmbH, Germany). Anthropometric tests were measured by maximum two different

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persons at the respective hospitals. Women were examined in an upright position with light clothing and without shoes. We used calibrated digital weights to measure weight. Height was measured by a standard altimeter. We measured waist and hip circumference with a

standardised stretch‐resistant tape (Gulick II Measuring Tape), and ensured that the tape only snugged around the body. Waist circumference was measured at the midpoint between the lower rib, and the highest level of the hip (iliac crest) when women were breathing out. Hip circumference was measured at the widest level of the buttocks (trochanter major).

(c) Definitions

Prediabetes was defined according to WHO, WHO-IEC, and ADA criteria in paper II, and according to WHO-IEC criteria in paper III (Table 1).

Diabetes was defined as in Table 1, and consistent with international standards. International standards require two separate tests for a clinical diabetes diagnosis in individuals without diabetes symptoms. For research purposes, however, it is considered appropriate to perform only one measurement, and therefore, we recorded one test as diagnostic for diabetes in the DIASA 1 trial.

(d) Calculations

In paper III we calculated different indexes for insulin sensitivity, insulin secretion, beta cell function, and hepatic insulin clearance. We used the following formula to estimate these indexes:

- Insulin sensitivity. We divided insulin sensitivity into hepatic, muscle, and whole-body insulin sensitivity. Hepatic insulin sensitivity was based on homeostatic model

assessment2-sensitivty (HOMA2-S), and calculated by plotting fasting serum insulin (FSI) [pmol/L], and fasting plasma glucose (FPG) [mmol/L] into the HOMA

calculator (22, 83). Muscle insulin sensitivity was based on the muscle-insulin sensitivity index (muscle-ISI), and calculated by plotting plasma glucose [mmol/L] and insulin values [pmol/L] into the muscle-ISI calculator (84). This calculator estimate muscle insulin sensitivity as the ratio of reduction in glucose values from peak to nadir, and mean insulin values during the OGTT (25). Whole-body insulin sensitivity was based on the Matsuda insulin sensitivity index (Matsuda ISI), and calculated manually by using this formula:

10,000/√ (FSI [uIU/mL] × FPG [mg/dL]) × (mean OGTT insulin [uIU/mL]) × (mean OGTT glucose [mg/dL]) (85).

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- Pre-hepatic insulin levels. To account for that a large part of the newly secreted insulin is cleared in liver, we calculated pre-hepatic insulin levels. As C-peptide clearance in the liver is almost nil, we used C-peptide deconvolution technique by the ISEC software program (86) to estimate pre-hepatic insulin levels (pmol/L). We used standard settings in the program, i.e., subjects with obesity, variation coefficient was set to 5%, and basal function was on (i.e., we specified the 'basal' C-peptide measurement to avoid that the basal secretion was affected by ‘smoothing of the secretion’ between the time-points during the OGTT. The ISEC program was then forced to fit the basal C-peptide

concentration, and produced basal secretion with measurement error approaching zero).

Assumptions required to utilise the program were also addressed. These included that C-peptide and insulin have an equimolar secretion from pancreas and different hepatic clearance rate, and that C-peptide kinetics are described by a 2-compartment model (i.e., C-peptide’s slower disappearance from plasma to extravascular compartments, and vice versa). By not considering this disappearance kinetics, we would have presented a

‘delayed’ pre-hepatic insulin secretion curve in situations with fast changes in insulin secretion (such as during an OGTT).

Further, the ISEC software program uses a population model to calculate the individual parameters of C-peptide kinetics. This allowed us to estimate parameters based on the women’s weight, height, age, sex, and by classifying them as normal, obese or having non-insulin dependent diabetes. Assumption related to measurement errors were also made such as that these errors should be uncorrelated with the zero mean, and have a constant standard deviation.

- Insulin secretion. We applied the insulinogenic index to estimate early insulin response, and tested it with both estimated pre-hepatic and measured peripheral insulin levels.

Insulinogenic index was calculated manually as ΔInsulin0–30min [uIU/mL]/ΔGlucose0–

30min [mg/dL] during the OGTT (24, 87). To estimate fasting insulin secretion, we calculated the HOMA2-beta cell function (HOMA2-B) by plotting fasting C-peptide [pmol/L], and fasting plasma glucose (FPG) [mmol/L] into the HOMA calculator (22, 83).

- Beta cell function. Insulin secretion adjusted for insulin resistance, the disposition index, reflects beta cell function. Disposition index was manually calculated as the product of insulinogenic index * Matsuda-ISI, and reflected the combined hepatic and peripheral disposition index (88). It was also visualised in a scatter plot. Here, the hyperbolic relationship between the indexes for insulin secretion and insulin sensitivity, is constant for individuals within the same glucose tolerance category (29, 89).

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Another way to estimate beta cell function is to calculate the beta cell glucose sensitivity.

This parameter reflects the relationship between glucose and pre-hepatic insulin levels during the OGTT (90). It was derived as the slope of this relationship, and implies the increase in pre-hepatic insulin levels [pmol/L] per increase in glucose levels [mmol/L].

- Hepatic insulin clearance. Based on the estimated pre-hepatic and measured peripheral insulin levels, we calculated fasting and postprandial (during the OGTT) hepatic insulin clearance as:

Hepatic insulin clearance fasting = pre-hepatic insulin fasting/insulin fasting.

Postprandial hepatic insulin clearance was calculated by applying area under the curve (AUC) estimates:

Hepatic insulin clearance OGTT = AUC pre-hepatic insulin/AUC insulin (26, 91).

- AUC. In this dissertation, we calculated total AUC by the trapezoid rule (92, 93).

(e) Laboratory analyses

All blood samples were taken by the DIASA personnel at the respective hospitals, and centrifuged at 3040 G for 10 min. The different analyses, however, required specific processing.

- Blood for glucose analyses were collected in cooled sodium fluoride tubes, and kept on ice until plasma was separated by centrifugation at 4 ℃, preferable within 10 min after blood sampling.

- Blood for insulin and C-peptide analyses were collected in tubes without anticoagulant - serum-separating tubes. They were stored at room temperature for clot formation. Serum was separated by centrifugation after ~30 minutes at 17-20 ℃.

- Whole blood for HbA1c analyses were collected in ethylenediaminetetraacetic acid (EDTA) tubes, and stored at 4 ℃.

All blood samples were sent by regular transport, and analysed at Oslo University Hospital, Aker. The central laboratory uses enzymatic photometry (Roche Diagnostics, Mannheim, Germany) to analyse plasma glucose, and high-performance liquid chromatography (Tosoh G8 analyser, Tokyo, Japan) to analyse whole-blood HbA1c. Insulin and C-peptide were analysed at the Hormone Laboratory by electrochemiluminescence immunoassay (ECLIA) (Cobas e601, Roche Diagnostics). The inter-assay variation coefficients were 2.5%, 7%, 4-5%, and 1.5-2.5% for glucose, insulin, C-peptide, and HbA1, respectively.

41 (ii) The qualitative part

In the qualitative study, we used focus group interview technique to obtain knowledge about the study aims. The focus group interviews were conducted outside a clinical setting at Akershus University Hospital. To enhance attendance, the interviews took place both during and outside office hours, and were mainly held in the participants’ native language. A flexible interview guide (Fig. 6), based on relevant literature (48-50) and developed by the research team, was applied to elicit women’s perceptions of their experience with GDM, their health and disease beliefs, and facilitators or hurdles in health-promoting behaviours. Demographic data were collected from the DIASA 1 study, whilst a short questionnaire with information about Norwegian language levels and immigrant status was answered on arrival. The interviews were conducted by the PhD candidate, acting as moderator (endocrinologist with South Asian background, fluent in Norwegian, English, Urdu and Hindi), and a co-moderator (Norwegian diabetes nurse and DIASA 1 study nurse) who took notes and documented the emotional response. Additionally, the first focus group was performed together with an experienced interviewer (last author in paper I). The interviews lasted between 60 and 90 minutes, and were audio-recorded.

Fig. 6. Focus group interview guide used in the DIAbetes in South Asian (DIASA 1) study.

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