Professor N. Sattar, Division of Cardiovascular and Medical Sciences, University of Glasgow, UK.
Whether booking body mass index (BMI) in the UK is increasing is unknown but is of clinical interest since overweight or obese pregnant women face far greater risks of pregnancy complications including pre-eclampsia and gestational diabetes. We examined booking BMI in 1990 and 2002/2004, of women with singleton pregnancies. Our analyses indicate an increase of 1 U in mean BMI over this period despite lower parity in recent years. When the model was adjusted for maternal age, parity, smoking status and deprivation category the mean BMI was 1.37 U higher in 2002/2004 than in 1990. More striking was the significant increase in the proportion of women who were obese (BMI ≥ 30 kg/m2) at booking—more than twofold higher in unadjusted analysis (18.9%vs 9.4%) rising to greater than threefold higher in multivariate analysis. These findings suggest that obesity-related pregnancy complications are likely to increase with implications for both mother and child.
Increasing obesity in the developed world is a pertinent issue with the escalating health and economic burden of obesity-related diseases. The majority of public and research focus has been on chronic conditions such as heart disease, stroke, diabetes and cancer, which tend to affect the older population. However, overweight and obese pregnant women are known to be at increased risk of a number of important complications when compared to mothers with normal body mass index (BMI).1–3 These include increased pregnancy loss, increased medical and intrapartum complications.1–3 Thus, the increasing ‘epidemic’ of obesity is equally relevant to the carers of pregnant women in the UK.
There is evidence of increases in maternal booking weight of up to 20% over the last two decades in the United States with a concomitant increase in maternal and perinatal morbidity attributable to obesity.4 However, similar trends in the maternity population have not been examined in the United Kingdom. Over the time period between 1995 and 1998 the Scottish Health Survey showed an increase in the prevalence (by between 47% and 54.2%) of overweight and obesity across all age groups but specific maternity data were lacking.
Our aim was therefore to identify the trend in obesity among the maternity population of the Princess Royal Maternity Unit (PRMU) at Glasgow Royal Infirmary, which serves women from a variety of socio-economic strata, including those residing in areas of considerable social deprivation. We also examined whether such BMI changes were generalised or restricted to particular subgroups and whether they were explicable by changes in maternal factors such as age, parity, smoking and socio-economic status.
Maternity records of women who booked up to or including 14 weeks of gestation at the PRMU for the time points 1990 (n= 202) and 2002/2004 (n= 312) were randomly selected by medical records staff. Data extraction included booking height, weight, age, postcode, medical history, smoking status and parity.
BMI was calculated as booking weight (kg), divided by height (m) squared. Deprivation category (DEPCAT score), a measure of socio-economic status, was assigned using the Scottish Area Deprivation Index for Scottish postcode sectors, 1998. World Health Organization (WHO) definitions were used to calculate the proportions of underweight (BMI < 18.5), normal weight (BMI 18.5–24.9), overweight (BMI 25–29.9) and obese (BMI ≥ 30) women in these groups.
Our aim was to gather at least 200 cases from these two time periods in order to give 80% power to detect a 1-U difference in BMI at the conventional significance level of 5%. We examined differences in mean values (t tests) or proportions (χ2 tests) over time (2002/2004 vs 1990) for all variables. Multiple linear regression was used to examine the association between time (independent variable) and BMI as continuous variable (dependent variable). The association between time (independent variable) and obesity (dependent variable, BMI ≥ 30 kg/m2) was tested in a series of logistic regression analyses. All estimates were adjusted for the following potential confounders—maternal age, parity, DEPCAT score, gestational age at booking and smoking status. Finally, we had a small number (n= 83) of case notes from 1980 and these data are included for reference in Fig. 1 but were not subjected to statistical analyses. Analyses were performed using STATA (version 7.0, StataCorp, College Station, Texas).
Table 1 shows that the women in both 1990 or 2002/2004 groups were of similar age. The proportion of women who were smokers at booking was reduced by around half from 1990 to 2002/2004. By contrast, the percent of women who were nulliparous was higher, reflecting the well-known pattern of lower parity and later age of first child birth in recent years. There was a difference in booking gestational age of around one week.
Table 1. Baseline characteristics at antenatal clinic booking visit in 1990 and 2002/2004. Values are presented as means and standard deviation or percentages.
Although there was no significant difference in the DEPCAT score over time, at both time points more than 60% of women were from deprived areas, consistent with our hospital catchment area. Deprivation was a potent independent associate of obesity, with the odds ratio for obesity of 3.52 [95% CI 1.03–11.97, P= 0.044] among those in the lower socio-economic strata (DEPCAT intermediate or deprived) compared with those more affluent, in analyses adjusted for maternal age, parity, booking gestational age, smoking and year group (2002/2004 or 1990).
In unadjusted analyses BMI was significantly greater (by mean of 0.9 U) in 2002/2004 than in 1990. This increase in BMI with time was greater following adjustment for potential confounders—when the model was adjusted for maternal age and parity, the mean BMI in 2002/2004 was 1.25 U higher (95% CI, 0.30–2.20, P= 0.01) than in 1990. With additional adjustment for booking gestation as well, the mean BMI was 1.5 U higher in 2002/2004. With adjustment also for smoking status and deprivation category (as both are powerful confounders of obesity/time relationship), the mean BMI was 1.37 U higher (95% CI, 0.30–2.44, P= 0.012) in 2002/2004 than in 1990.
More notably, the proportion of women who were obese at booking more than doubled over time in unadjusted analyses (Table 1) such that nearly one in five were obese at booking. In addition, the likelihood of obesity in 2002/2004 relative to 1990 was increased following adjustment for potential confounders such that the likelihood of obesity (BMI ≥ 30 kg/m2) was 3.07-fold higher (95% CI, 1.60–5.89, P= 0.001) in 2002/2004 in analyses adjusted for age, parity, booking gestation, smoking and deprivation category. Similarly, women were 60% more likely to be obese or overweight (BMI ≥ 25 kg/m2) in 2002/2004 relative to 1990—with an adjusted odds ratio of 1.62 (95% CI 1.04–2.53, P= 0.033).
Our study did not have sufficient power to test for the relation between time, obesity and pregnancy complications.
Within our population, there was an overall increase in mean booking BMI of around 1 U over a period of 12 years despite lower parity in recent times. Moreover, although both smoking and deprivation influence maternal BMI, adjusting for these confounders also did not attenuate the increase in BMI over the 12-year period. More striking was the significant increase with time in the proportion of women who were obese at booking—more than twofold in unadjusted analyses and more than threefold higher odds ratio for obesity in multivariate analysis. Indeed, nearly one in five women booking for antenatal care in 2002/2004 was obese.
Our findings are significant for several reasons. First, our data suggest that weight trends in women in their early to mid reproductive years (average age of 27–28 years) are following the same trend as in the general population. Second, and of more interest for obstetricians perhaps, is the range of pregnancy complications that are more common in these overweight or obese women. This clearly has implications for obstetric practice. For example, extrapolating from a systematic review of the association between BMI and the incidence of pre-eclampsia, a 1-U increase in BMI would result in around a 0.6% increase in the incidence of this condition.5
We have recently demonstrated women who book for antenatal care with elevated BMI (median BMI 31 kg/m2) have a significantly altered metabolic milieu in terms of lipid, inflammatory proteins, insulin and leptin levels in the third trimester compared with lean women (median BMI 22 kg/m2),6 and others have postulated that obesity in women may lead to ‘aberrant’ fetal nutrition and programming.7
We acknowledge several limitations of our study. The ‘random’ method of case record selection by medical records staff could have been more robust and pre-pregnancy weight, in addition to booking weight, would have been useful. We included only modest numbers of women; however, retrieval of such data took considerable effort because booking weight and height is not routinely gathered for the purposes of national statistics on pregnancy outcome. Additionally, our study was not powered to detect an increase in pregnancy complications over the years and much greater numbers and time investment would be required to examine this issue. However, others have clearly demonstrated increases in maternal booking weight over the last two decades in the United States, which is associated with a concomitant increase in maternal and perinatal morbidity.3 Our study has strengths in that we were careful to account for potential confounders such as parity, smoking, gestational age and socio-economic status in our analyses.
Finally, the health and economic repercussions of this trend are of significant public health importance. There is a clear need for effective intervention strategies for weight control before and during women's reproductive years in an attempt to modify obesity's adverse effects on pregnancy outcomes and offspring health.
The authors would like to thank the Medical records department at the PRMU who were responsible for most of the data collection.