An epidemic of obesity is affecting growing numbers of women in their childbearing years increasing their risk of obstetric complications including diabetes, hypertension, pre-eclampsia, some malformations, macrosomia and the need for obstetric intervention. There is growing evidence that maternal obesity may increase the risk of obesity and diabetes in the offspring. Obesity and diabetes in pregnancy have independent and additive effects on obstetric complications, and both require management during pregnancy. Management of obesity including weight loss and physical activity prior to pregnancy is likely to be beneficial for mother and baby, although the benefits of bariatric surgery remain unclear at this time. Limiting gestational weight gain to 5–9 kg among pregnant obese women is likely to improve obstetric outcomes, but how to achieve this remains an active area of research. If gestational diabetes develops, there is good evidence that clinical management reduces the risk of adverse pregnancy outcomes.
The pandemic of obesity and obesity in pregnancy
Obesity and downstream, type 2 diabetes have increased spectacularly over the last 50 years. A pictorial display of the increase in obesity (body mass index (BMI) ≥30 kg m −2 ) across USA from 1985, when no state had an obesity prevalence >15%, to the current picture of increasing numbers of states with a prevalence of adult obesity >30% can be found on the Centers for Disease Control and Prevention (CDC) website http://www.cdc.gov/obesity/data/trends.html#State (accessed 29 April 2010). This trend of increasing prevalence is occurring across the world. The extent of obesity is such that there are now three grades (using World Health Organization criteria) of severity: grade I BMI 30–34.9 kg m −2 , grade II BMI 35–39.9 kg m −2 and grade III with BMI 40+ kg m −2 . Overweight is defined as a BMI 25–29.9 kg m −2 .
The obesity epidemic is affecting not only adults, but also children, adolescents and young adults. Naturally, this means there are a growing number of obese women, who are becoming pregnant. There are now a large number of studies showing the increasing prevalence of obesity in pregnant and pre-pregnant women in different countries and different sub-populations. Fig. 1 shows the prevalence of obesity in pregnancy in a selected number of studies from the six continents by year. Only a limited number of studies emanate from the developing world, but those that do report an increasing prevalence of obesity in pregnancy, reflecting the changing socioeconomic circumstances, the growing urbanisation and the underlying ethnic and geographical features. However, in these countries, undernourishment often remains a significant health problem, which runs in parallel with the obesity epidemic.
Ethnicity is an important consideration when interpreting the major measure of obesity currently used around the world (BMI). Some ethnic groups have more fat for a given BMI (e.g., South Asians) and others (e.g., Polynesians) have a lower proportion of total fat mass. These ethnic differences reflect variation in lean body mass (i.e., largely muscle and bone) and/or different adipose distribution (i.e., more centralised vs. overall). Central fat, rather than peripheral adiposity, is more associated with resistance to insulin, a predisposing factor to gestational diabetes mellitus (GDM) and type 2 diabetes. The increasingly routine clinical measure to assess central fat distribution in non-pregnant adults (waist circumference), is generally not available in later pregnancy, hence the reliance on BMI in most studies.
Ethnicity is associated with different prevalence rates of obesity even in the same geographical location, but this relationship is often confounded by socioeconomic status, for example. It is therefore important to understand that any given national or local prevalence of obesity in pregnancy will change over time, not only in relation to any underlying secular trends in obesity, but also with any demographic shifts. However, the growth in obesity in pregnancy is clearly across all subgroups, suggesting some fundamental change in lifestyle and/or ecology underpinning the current epidemic.
In England, the growing prevalence of obesity among women of childbearing age has tracked the increasing prevalence of obesity in the general population, as shown in Fig. 2 .
Although the reasons for the obesity epidemic are, to an extent, explained by the increase in availability and consumption of energy-dense foods and a reduction in physical activity, the scientific evidence that this explains the entire explosion in obesity prevalence is incomplete. Table 1 lists other putative contributing factors to the obesity epidemic.
| Putative cause | Description |
|---|---|
| Reduction in smoking | Stopping smoking is associated with weight gain |
| Micro-organisms | There is a close interaction between adipose tissue and the immune system. Obesity promoting viruses (eg Canine distemper) and adiposity enhancing gut flora do exist |
| Epigenetics | There is evidence for maternal obesity having an intrauterine effect on the offspring through epigenetic mechanisms. Other epigenetic effects could also be happening |
| Increasing maternal age | The age at which women have their babies has been increasing. Mothers of obese children. Co-morbidities could confound. Possible mechanisms have been found in animals |
| Greater fecundity among people with higher adiposity | Evidence exists that the BMI correlates with the number of offspring produced-there are a number of confounders and which is first needs more research |
| Assortative mating for adiposity | Spousal resemblance does occur, but could be due to a range of factors after mate selection. Some studies have shown correlation before marriage and cohabitation. Animal studies suggest an impact on bodyweight can occur within one generation |
| Sleep debt | The amount of sleep has reduced over the last 40 years. Sleep deprivation is associated with obesity |
| Endocrine disrupting chemicals (EDCs) | Exposure to several EDC’s is increasing. Some EDC’s interfere with oestrogen and androgen signaling-this could be associated with body fat and weight |
| Pharmaceutical iatrogenesis | Pharmaceutical use is increasing, some pharmaceuticals (eg antipsychotics, tricyclic antidepressants, beta blockers) are associated with weight gain |
| Reduction in variability of ambient temperatures | Temperature control use (eg air conditioning) has increased and could be associated with increase in obesity |
| Intrauterine and intergenerational effects | A range of non-epigenetic mechanisms have been proposed that increase the risk of adiposity (and diabetes) in the offspring |
The purpose in showing these putative contributors is, first, not to imply that detrimental lifestyle choices are not major contributors, or that attempts to address these are inappropriate, but to emphasise that the rapidity in the growth in the epidemic could suggest that one or more additional accelerators and amplifiers are operating. Second, several of these putative factors operate through reproductive behaviours and/or the intrauterine milieu, matters of importance for those involved with obesity and diabetes in pregnancy. These are particularly important when considering interventions to arrest and reverse the current epidemic. Finally, it needs to be appreciated that while the genome may have remained relatively unaltered (beyond the hypothetical mechanisms in Table 1 ), the gene–environment interaction has clearly changed, emphasising the need to understand the underlying genetic mechanisms behind obesity and diabetes.
The pandemic of diabetes and diabetes in pregnancy
Following the obesity epidemic is a diabetes pandemic including growing numbers of women with GDM and type 2 diabetes in pregnancy (including undiagnosed type 2 diabetes). A meta-analysis across studies relating the risk of GDM to obesity identified 20 studies which included:
- •
obesity measures prior to any significant pregnancy weight gain;
- •
a comparison group of normal-weight women; and
- •
quantitative data.
The prevalence of GDM ranged from 1.3% to 19.9%, using a variety of diagnostic and screening criteria. The meta-analysis showed that the risk of developing GDM was 2.14 (95% confidence interval (CI) 1.82–2.53)-fold higher if overweight, 3.56 (3.05–4.21)-fold higher if obese and 8.56 (5.07–16.04)-fold higher if severely obese compared with normal-weight pregnant women. Interestingly, these relationships were not affected by publication date, study location, parity, rate of GDM or type of data collection. The impact of different screening approaches and diagnostic criteria were not investigated.
Since these studies, the International Association of Diabetes and Pregnancy Study Groups (IADPSG) has proposed new criteria for the diagnosis of GDM, based on the Hyperglycaemia and Adverse Outcomes Study (HAPO). The criteria use a 75-g oral glucose tolerance test (OGTT) without prior glucose challenge and diagnose GDM if the fasting glucose is ≥5.1 mmol l −1 and/or the 1-h post-load glucose is ≥10.0 mmol l −1 and/or the 2-h post-load glucose is ≥8.5 mmol l −1 . With the greater numbers with GDM, it will be interesting to see if there is an alteration in the relationship with obesity.
The pandemic of diabetes and diabetes in pregnancy
Following the obesity epidemic is a diabetes pandemic including growing numbers of women with GDM and type 2 diabetes in pregnancy (including undiagnosed type 2 diabetes). A meta-analysis across studies relating the risk of GDM to obesity identified 20 studies which included:
- •
obesity measures prior to any significant pregnancy weight gain;
- •
a comparison group of normal-weight women; and
- •
quantitative data.
The prevalence of GDM ranged from 1.3% to 19.9%, using a variety of diagnostic and screening criteria. The meta-analysis showed that the risk of developing GDM was 2.14 (95% confidence interval (CI) 1.82–2.53)-fold higher if overweight, 3.56 (3.05–4.21)-fold higher if obese and 8.56 (5.07–16.04)-fold higher if severely obese compared with normal-weight pregnant women. Interestingly, these relationships were not affected by publication date, study location, parity, rate of GDM or type of data collection. The impact of different screening approaches and diagnostic criteria were not investigated.
Since these studies, the International Association of Diabetes and Pregnancy Study Groups (IADPSG) has proposed new criteria for the diagnosis of GDM, based on the Hyperglycaemia and Adverse Outcomes Study (HAPO). The criteria use a 75-g oral glucose tolerance test (OGTT) without prior glucose challenge and diagnose GDM if the fasting glucose is ≥5.1 mmol l −1 and/or the 1-h post-load glucose is ≥10.0 mmol l −1 and/or the 2-h post-load glucose is ≥8.5 mmol l −1 . With the greater numbers with GDM, it will be interesting to see if there is an alteration in the relationship with obesity.
‘Diabesity’ and pregnancy outcomes-untangling diabetes and obesity
The adverse outcomes from both diabetes in pregnancy without obesity, and obesity in pregnancy without diabetes overlap substantially. There are obviously some complications, such as diabetic ketoacidosis, which are virtually only associated with type 1 diabetes, and others such as diabetic retinopathy only associated with pre-existing diabetes (mainly type 1 and type 2 diabetes including undiagnosed type 2 diabetes). However, there is also clearly a gradient in fetal exposure to hyperglycaemia from type 1 diabetes, to type 2 diabetes down to GDM. It is with GDM that the discussion of the impact of obesity and GDM on the foetus and mother often becomes circular, as the majority of those with GDM are obese and a significant proportion of those who are obese have GDM. Studies on the impact of obesity on obstetric and foetal outcomes often do not systematically screen for and diagnose GDM (which can develop later in pregnancy after initial screening). Furthermore, HAPO has clearly shown that the impact of hyperglycaemia on the foetus is at a much lower glucose (particularly fasting glucose) concentration than previously thought. This would mean that many of the studies showing an impact of obesity on foetal adiposity included a significant number of women with hyperglycaemia. Finally, a few studies also include the assessment of the supply of other fuels that could be increased, such as fatty acids, to the foetus. For example, maternal triglyceride concentrations are also associated with macrosomia.
Notwithstanding the overlap, Table 2 compares the relative impact of diabetes, overweight and obesity on different pregnancy outcomes in a range of studies. Naturally, in pre-existing diabetes and GDM, pregnancy outcomes also depend upon the intensity of the treatment, clinical targets set, the success in achieving the targets and the wider obstetric management. Type 1 diabetes is included in the table as a largely ‘insulin deficiency-related hyperglycaemia only’ effect. However, it needs to be remembered that increasing numbers of those with type 1 diabetes now have weight-management issues, and, that a proportion will have been predisposed to GDM and type 2 diabetes through obesity and other causes of insulin resistance/insulin deficiency, had they not developed type 1 diabetes. Both GDM and type 2 diabetes can be seen as a mix of both insulin deficiency and insulin resistance, with the expected excess supply of both glucose and fats. Type 2 diabetes has been included in the ‘pre-existing diabetes’ column because of the relatively small numbers and lack of separation in many studies (probably as a reflection of the speed with which the burden of type 2 diabetes in pregnancy has grown).
| Pre-existing diabetes | T1DM alone | GDM | Obese | Overweight | |
|---|---|---|---|---|---|
| Macrosomia/LGA | 4.91 (4.28–5.63) | 4.5 (4.0–5.1) | 1.65 (1.57–1.72)–3.27 (1.44–7.45) | 1.5 (1.1–2.2)–4.5 (2.3–8.7) | 1.2 (1.0–1.6)–1.6 (1.3–2.0) |
| Hypertension | 14.16 (10.94–18.29) | 1.53 (1.18–1.99) | 2.70 (2.33–3.13) | 3.8 (1.7–9.1)–10.6 (5.0–22.5) | 1.9 (1.0–3.7)–2.6 (1.5–4.6) |
| Pre-eclampsia | 3.97 (3.36–4.69) | 4.47 (3.77–5.31)–12.1 (9.0–16.1) | 1.61 (1.39–1.86)–1.69 (1.47–1.95) | 2.1 (1.9–2.5)–3.9 (2.4–6.4) | 1.3 (0.8–2.0)–2.0 (1.4–3.0) |
| TED | ? | ? | ? | 1.5 (0.8–2.7) | 1.4 (0.9–2.2) |
| Labour induction | 1.52 (1.35–1.72) | 1.54 (1.49–1.60) | 2.2 (1.7–2.81)–2.6 (1.7–3.9) | 1.2 (0.8–1.8)– | |
| LSCS | 2.37 (2.05–2.75) 4.83 (4.25–5.48–before labour) | 3.7 (3.2–4.2)–5.31 (4.97–5.69) | 1.47 (1.40–1.55)–1.88 (1.45–2.43) | 1.5 (1.1–2.0)–2.5 (1.6–3.9) | 1.2 (0.8–1.8)–1.5 (1.4–1.7) |
| Pre-term delivery | 2.54 (2.18–2.95) | 4.5 (3.8–5.3)–7.0 (6.3–7.6) | 1.28 (1.20–1.36)–2.18 (1.24–3.84) | 0.9 (0.9–1.0)–2.1 (1.4–3.1) | 0.8 (0.8–0.9)–1.1 (0.9–1.3) |
| Stillbirth | 2.90 (1.81–4.60) | 3.34 (2.46–4.55)–4.7 (3.2–7.0) | 1.17 (0.88–1.54) | 1.2 (0.6–1.2)–2.4 (1.3–4.3) | 1.2 (0.6–2.6)–1.5 (0.9–2.7) |
| Perinatal death | 3.29 (2.50–4.33)–4.1 (2.9–5.6) | 1.0 (0.4–2.2)–2.7 (1.2–6.1) | 1.0 (0.2–1.3)–1.8 (0.6–6.0) | ||
| Intensive care | 5.45 (4.51–6.58) | 1.41 (1.27–1.57)–4.11 (2.37–7.10) | 1.3 (1.0–1.6)–1.4 (1.2–1.6) | 0.9 (0.7–1.2)–1.2 (1.1–1.4) | |
| Hypoglycaemia | 56.8 (50.53–63.81) | 2.75 (1.01–7.52)–15.07 (14.38–15.80) | 0.9 (0.5–1.8)–2.6 (1.4–4.8) | 0.8 (0.4–1.7)–1.2 (0.6–2.1) | |
| Malformations a | 1.7 (1.3–2.2)–3.4 (2.4–4.8) | 1.7 (1.34–2.15) obese 3.11 (1.75–5.46) very obese | 1.22 (0.99–1.49) | ||
| Maternal mortality | 60.0 (14.3–249.6) | ||||
| Jaundice | 1.68 (0.71–4.01)–3.87 (2.64–5.67) | 1.0 (0.9–1.1)–1.0 (0.6–1.7) | 1.0 (0.6–1.8) |
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