There is now substantial evidence that maternal obesity is a risk factor for gestational complications such as hypertension, diabetes, and preeclampsia, and those postpartum rates of hyperlipidemia and cardiovascular diseases are increased.1–4 Prepregnancy body mass index (BMI, calculated as weight (kg)/[height (m)]2) traditionally has been used for determining maternal obesity status, and pregnancy weight gain and BMI have been correlated with hemodynamic and metabolic changes including physiologic increases in fat, uterine, breast tissue, extracellular fluid, and fetal and placental growth.5,6
The underlying mechanisms and pathways linking maternal obesity with gestational and postpartum vascular complications are poorly defined and are complex.4,7 It has been hypothesized that small vessel endothelial dysfunction may partly underlie the link between maternal obesity and adverse outcomes with a microvascular component, but the contribution and exact role of the microcirculation during pregnancy is unclear as a result of difficulties in its assessment.8 Advancements in retinal imaging have allowed a direct and noninvasive assessment of the systemic microcirculation.9 Studies among general adult and children populations have shown that a greater BMI is associated with adverse retinal microvascular changes (eg, retinal arteriolar narrowing, retinal venular widening, or both).10–14 In this study, we estimated the relationships of maternal BMI (prepregnancy BMI and 26-week pregnancy BMI) and early pregnancy weight gain with a range of retinal microvascular measures (retinal vascular caliber, tortuosity, and fractal dimension) in pregnant women for the first time. Such information may allow us to better understand the effect of maternal BMI on the microcirculation during pregnancy.
MATERIALS AND METHODS
We studied 814 pregnant women recruited as part of the Growing Up in Singapore Toward Health Outcomes study, an ongoing birth cohort study from two government hospitals in Singapore since 2009. The study was approved by both Singhealth Centralized institutional review board and the National Health Group's domain-specific review board. Our study included both naturally conceived pregnancies and women who conceived through assisted reproductive techniques. Inclusion criteria were: Singapore citizens or Singapore permanent residents of age 18 years and older, attending the first-trimester antenatal clinic at one of the two government hospitals (KK Women and Children's Hospital), intending to eventually deliver in the named hospitals and to reside in Singapore for the next 5 years and willing to take retinal photography. Pregnant women on chemotherapy, with significant medical conditions such as insulin-dependent diabetes mellitus, psychosis, under certain medication such as psychotropic drugs, or mixed marriages were excluded.
With written informed consent, 835 of the 952 participants (87.7%) attending the KK Women and Children's Hospital clinic at 26 weeks of gestation underwent retinal examination; 814 of these (97.5%) had gradable retinal photographs and anthropometric measurements.
Standing height and weight were measured according to standard protocol using SECA models 213 and 803, respectively.15 Both measurements were taken twice separately with bare feet. If the first two measurements differed by 1.0 cm or 200 g for height or weight, a third measurement was taken for the average calculation.
Digital retinal photographs were taken from participants without pharmacologic pupil dilation using a 45° nonmydriatic retinal camera. Right eye photographs centered on the optic disc were used for the measurement of retinal vascular parameters by a trained grader with a semiautomated computer-based program that measures a spectrum of retinal vascular parameters quantitatively from 0.5 to 2.0 disc diameters away from the optic disc margin (Fig. 1) according to standardized protocols.16,17
A set of retinal vascular parameters were assessed and subsequently defined. Retinal vascular caliber was represented as central retinal arteriolar equivalent and central retinal venular equivalent, respectively. Retinal vascular tortuosity was defined as the integral of the curvature square along the path of the vessel and normalized by the total path length, which took into account the bowing and points of inflection.17 Retinal fractal dimension quantified the complexity of the branching pattern of the retinal vascular tree and was defined as the gradient of logarithms of the number of boxes and the size of the boxes.17 Retinal branching angle was defined as the first angle subtended between two daughter vessels at each bifurcation.17
A total of 90 randomly selected retinal photographs underwent repeat grading to determine intragrader variability. The intraclass correlation coefficient was 0.94 for retinal arteriolar caliber, 0.97 for retinal venular caliber, 0.95 for retinal arteriolar tortuosity, 0.87 for retinal venular tortuosity, 0.92 for total fractal dimension, and 0.82 for total retinal branching angle.
Peripheral blood pressure was measured using the automatic Omron sphygmomanoter after 5 minutes of rest, according to standard protocols.18 With back support, all pregnant women were seated in a resting status when blood pressure was measured. The average of three separate measurements was taken. We calculated mean arterial blood pressure as two-thirds diastolic blood pressure plus one-third systolic blood pressure.
Autorefraction to determine ocular refractive error was performed using a Canon Autorefractor RK-F1, in which the average from five consecutive readings of sphere and cylinder was obtained. Readings were considered acceptable if the difference between the lowest and highest reading was 0.25 D or less. Spherical equivalent was calculated as the sphere plus a half of negative cylinder.
Questionnaires on sociodemographic information were completed by participants in English, Chinese, Malay, or Tamil. Household income was classified into five categories as 1) 0–999 Singapore dollars per month; 2) 1,000–1,999 Singapore dollars per month; 3) 2,000–3,999 Singapore dollars per month; 4) 4,000–5,999 Singapore dollars per month; or 5) more than or equal to 6,000 Singapore dollars per month. The mother's primiparous status whether she was pregnant for the first time or not was documented, and ethnicity, cigarette smoking, and history of hypertension and diabetes were obtained from the clinic interview.
Prepregnancy and pregnancy BMI were calculated from the woman's height and her recalled prepregnancy and measured 26-week weights, respectively. Weight gain was calculated as the difference between prepregnancy and 26-week weights.
According to World Health Organization prepregnancy BMI criteria, we classified patients into four groups as follows: underweight (less than 18.5), normal weight (18.5–24.9), overweight (25.0–29.9), obese (30.0 or greater).19,20 We chose to use these rather than the lower Asian standards used by Jafar et al21 (overweight or obese as 23.0 or greater) to allow comparison to available literature and guidelines. Full-term BMI-specific weight gain cutoff is referred to the Institute of Medicine weight gain guideline.22 As recommended by the Institute of Medicine, ideal weight gain is 12.5–18 kg, 11.5–16 kg, 7.0–11.5 kg, and less than 7.0 kg for underweight, normal weight, overweight, and obese women based on their prepregnancy BMI, respectively.22 Because there is no guideline for ideal weight gain at 26 weeks of gestation or the second trimester, we used the Institute of Medicine guideline as a reference; thus, three groups (less than ideal weight gain, within ideal weight, and greater than ideal weight gain) were accordingly classified among our patients.
We compared all baseline characteristics between eligible and ineligible participants by using the Student's t test and χ2 test (two-sided). Anthropometric parameters including prepregnancy BMI, pregnancy BMI, and 26 weeks gestational weight gain were analyzed continuously (each standard deviation [SD]) and categorized (quartiles or clinical cutoff).
Multiple linear regression models were constructed to estimate the associations between various weight measurements and retinal vascular parameters. Retinal vascular caliber was analyzed as dependent variables and the main covariates were prepregnancy BMI, weight gain, and 26-week pregnancy BMI. The multivariable models were adjusted for age, ethnicity, household income, primiparous status, hypertension history, diabetes history, cigarette smoking, systolic blood pressure, spherical equivalent, Pittsburgh Sleep Quality Index, weight gain and mean of prepregnancy and pregnancy weight, and fellow retinal vessel. Other retinal vascular parameters (tortuosity, fractal dimension, and branching angle) were analyzed also as dependent variables, except that fellow vessel was not included in the fully adjusted model. Because self-administered Pittsburgh Sleep Quality Index was significantly associated with retinal vascular caliber in our population (Li, unpublished data), and retinal venular caliber accounts for approximately 30% of the variability in arteriolar caliber as a result of shared genetic and ocular factors and vice versa.23 Pittsburgh Sleep Quality Index and fellow retinal vessels (central retinal arteriolar equivalent adjusted for central retinal venular equivalent and central retinal venular equivalent adjusted for central retinal arteriolar equivalent) were considered possible confounding factors in this current analysis. Stepwise backward methods were selected to choose the most parsimonious and best fitting model. The test of trend was determined by treating quintiles of blood pressure as continuous ordinal variables.12,17
A series of potential effect modifiers, such as prepregnancy BMI*age, pregnancy BMI*age, prepregnancy BMI*ethnicity, pregnancy BMI*ethnicity, prepregnancy BMI*systolic blood pressure, and pregnancy BMI*systolic blood pressure, were examined as interaction terms in the two models mentioned. A significant P value (two-tailed) was defined as <.05. All statistical analyses were performed using PASW 19.0.
Table 1 compares the baseline characteristics between participants with retinal photography (n=814) and without retinal photography (n=138) who both attended the 26-week gestation KK Women and Children's Hospital clinic visit. Those with retinal photography were less likely to be primiparous and more likely to be past or current smokers than those who declined but there were no significant differences in maternal age, composition of ethnicity, household income, systolic blood pressure, BMI, spherical equivalent, or Pittsburgh Sleep Quality Index.
The associations between maternal BMI and retinal vascular caliber are shown in Table 2. The associations of higher prepregnancy and 26-week pregnancy BMI with retinal arteriolar narrowing and retinal venular widening were consistent in age- and ethnicity-adjusted models as well as in a multivariable adjusted model. In the multivariable model, each SD increase of prepregnancy BMI (4.61) was associated with a reduction of 1.61 micrometers (P<.001) in retinal arteriolar caliber and an increase of 1.26 micrometers (P=.02) in retinal venular caliber. Obese and overweight pregnant women had narrower arteriolar caliber (118.81/119.86 compared with 124.87/123.38 micrometers; P trend <.001) and wider retinal venular caliber (175.81/176.04 compared with 169.83/173.01 micrometers; P trend <.01) compared with women who were underweight and normal weight. Obese patients had the largest retinal venular tortuosity compared with the other three groups (129.92 compared with 124.19–117.07 [10−6]; P<.01). Figure 2 shows the visual differences of retinal arteriolar caliber, retinal venular caliber, and retinal venular tortuosity between an obese patient and a normal-weight patient who were selected from our study. Similarly, each SD increase in 26-week pregnancy BMI (4.57) was associated with a reduction of 1.58 micrometers (P<.001) in retinal arteriolar caliber and an increase of 1.28 micrometers (P=.02) in retinal venular caliber. The highest quartile of pregnancy BMI had significantly narrower retinal arteriolar caliber (120.36 compared with 124.14 micrometers; P trend <.001) and a wider retinal venular caliber (175.17 compared with 171.98 micrometers; P trend=0.03) compared with the lowest quartile of pregnancy BMI. Furthermore, each SD increase of pregnancy and prepregnancy BMI was associated with an increase of 2.44 (10−6) (P=.01) and 2.57 (10−6) (P<.01) in retinal venular tortuosity, respectively. No statistically significant associations were observed between prepregnancy or pregnancy BMI and retinal vascular fractal dimension.
Table 3 shows the association between pregnancy weight gain and retinal vascular caliber. In a multiple linear regression model, pregnancy weight gain was not associated with retinal arteriolar caliber (−0.62 micrometers; P=.10) or retinal venular caliber (0.15 micrometers; P=.31) Women with greater weight gain regardless of prepregnancy BMI status had marginally narrower retinal arteriolar caliber than those with normal or lower weight gain (120.68 compared with 121.91 compared with 123.17 micrometers; P trend=.05). No association was found between weight gain and retinal arteriolar tortuosity (−1.10×10−6, P=.26) or retinal venular tortuosity (−0.47×10−6, P=.61). There was no potential effect modifier on the relationship between blood pressure and retinal vascular parameters (data not shown).
In our study, greater prepregnancy BMI and pregnancy BMI were associated with narrower retinal arteriolar caliber, wider retinal venular caliber, and more tortuous retinal venules in Asian pregnant women. Women with greater pregnancy weight gain had marginally narrower retinal arteriolar caliber. Our study may potentially help providing evidence on pathophysiologic mechanisms how maternal obesity interacts with microcirculation during pregnancy.
Some epidemiologic studies further reported that indices of adiposity such as BMI, waist-to-hip ratio, and triceps skinfold are associated with retinal arteriolar narrowing, retinal venular widening, or both retinal arteriolar narrowing and retinal venular widening in both adults and children.10–14 Wong et al14 studied a multiethnic population of 5,979 Americans aged 45 to 84 years and reported that each SD increase (5.4) in BMI was associated with retinal venular widening (by 2.21 micrometers, P<.001). In a study of 2,353 Australian adolescents with a mean age of 12.7 years, Gopinath et al11 found that obese adolescents had a narrower retinal arteriolar caliber (by 2.8 micrometers, P=.01) and a wider retinal venular caliber (by 4.5 micrometers, P=.01) than adolescents with normal weight. Despite that biological mechanisms of how retinal microvasculature abnormality or retinal vascular remodeling occur on overweight or obesity have not been clearly identified, it has been repeatedly reported that obese patients have increased markers such as high-density lipoprotein cholesterol, triglyceride, and C-reactive protein.10–12,14,24 Because all these markers are closely related to endothelial activation chronic vascular inflammation, the pathophysiologic mechanisms underlying such association between BMI and retinal microvasculature have been speculated as oxidative stress, reduction in nitric oxide production, and chronic inflammation 10–13 Although maternal obesity is associated with a series of adverse maternal disorders including gestational hypertension, gestational diabetes, and preeclampsia together with higher rates of cesarean delivery and postpartum hyperlipidemia and cardiovascular diseases,10,13,14,25,26 data on the quality of the microcirculation among pregnant women are largely lacking.
Consistent with previous studies in nonpregnant adults and children,10–13 we found associations between either maternal prepregnancy or pregnancy BMI and retinal vascular changes. Mothers with higher prepregnancy or pregnancy BMI were more likely to have retinal arteriolar narrowing, retinal venular widening, more tortuous retinal venules, or all of these. Our finding that there were no consistent associations between BMI and retinal vascular branching angle or fractal dimension may be because short-term stress imposed by increased BMI during pregnancy may not be severe to cause structural reformation on retinal microvasculature.
Maternal cardiovascular hemodynamic adaptations to pregnancy include increased cardiac output, heart rate, and stroke volume.27 Some studies have suggested that women with higher BMI are subject to a greater risk of adverse maternal hemodynamic changes compared with their leaner counterparts, including higher arterial blood pressure, hemoconcentration, impaired blood flow, and altered cardiac function28,29 and put them at risk of hypertensive disorders7,30–36 and venous thromboembolism.37 Maternal obesity and excessive gestational weight gain are independently associated with increased insulin resistance and a greater risk of gestational diabetes, and microvascular dysfunction is implicated in these disorders. Studies of pregnancy-associated changes in the retinal microvasculature may provide a valuable approach to evaluating the pathogenesis of these pregnancy-associated diseases.38–40
The strengths of our study include standardized protocols, validated assessment of retinal microvascular characteristics, and detailed information on a range of potential confounders. Limitations include the cross-sectional design, which restricts interpretation of the temporal relationship of BMI and retinal vascular parameters. Second, a degree of selection bias may be present because pregnant women were recruited from a single site, were more likely to be current or past smokers, and less likely to be primiparous. Third, recall bias for prepregnancy weight may have influenced the association of prepregnancy BMI and weight gain with retinal vascular parameters. However, recall of pregnancy weight has been used and validated in many other studies.41–43 Lastly, the bias in applying Institute of Medicine full-term weight gain guideline in our participants at 26 weeks of gestation might dilute the association to a null value.
In summary, we found that higher prepregnancy and pregnancy BMI were associated with changes in retinal microvasculature and maternal obesity may play a role in microcirculation during pregnancy.
1. Catalano PM. Obesity, insulin resistance, and pregnancy outcome. Reproduction 2010;140:365–71.
2. Melzer K, Schutz Y. Pre-pregnancy and pregnancy predictors of obesity. Int J Obes (Lond) 2010;34:S44–52.
3. Yogev Y, Catalano PM. Pregnancy and obesity. Obstet Gynecol Clin North Am 2009;36:285–300, viii.
4. Dixit A, Girling JC. Obesity and pregnancy. J Obstet Gynaecol 2008;28:14–23.
5. Mi J, Law C, Zhang KL, Osmond C, Stein C, Barker D. Effects of infant birthweight and maternal body mass index in pregnancy on components of the insulin resistance syndrome in China. Ann Intern Med 2000;132:253–60.
6. Forsen T, Eriksson JG, Tuomilehto J, Teramo K, Osmond C, Barker DJ. Mother's weight in pregnancy and coronary heart disease in a cohort of Finnish men: follow up study. BMJ 1997;315:837–40.
7. Guelinckx I, Devlieger R, Beckers K, Vansant G. Maternal obesity: pregnancy complications, gestational weight gain and nutrition. Obes Rev 2008;9:140–50.
8. Smith SA, Hulsey T, Goodnight W. Effects of obesity on pregnancy. J Obstet Gynecol Neonatal Nurs 2008;37:176–84.
9. Liew G, Wang JJ, Mitchell P, Wong TY. Retinal vascular imaging: a new tool in microvascular disease research. Circ Cardiovasc Imaging 2008;1:156–61.
10. Cheung N, Saw SM, Islam FM, Rogers SL, Shankar A, de Haseth K, et al.. BMI and retinal vascular caliber in children. Obesity (Silver Spring) 2007;15:209–15.
11. Gopinath B, Baur LA, Teber E, Liew G, Wong TY, Mitchell P. Effect of obesity on retinal vascular structure in pre-adolescent children. Int J Pediatr Obes 2011;6:e353–9.
12. Li LJ, Cheung CY, Chia A, Selvaraj P, Lin XY, Mitchell P, et al.. The relationship of body fatness indices and retinal vascular caliber in children. Int J Pediatr Obes 2011;6:267–74.
13. Wong TY, Duncan BB, Golden SH, Klein R, Couper DJ, Klein BE, et al.. Associations between the metabolic syndrome and retinal microvascular signs: the Atherosclerosis Risk In Communities study. Invest Ophthalmol Vis Sci 2004;45:2949–54.
14. Wong TY, Islam FM, Klein R, Klein BE, Cotch MF, Castro C, et al.. Retinal vascular caliber, cardiovascular risk factors, and inflammation: the multi-ethnic study of atherosclerosis (MESA). Invest Ophthalmol Vis Sci 2006;47:2341–50.
15. Wong TY, Klein R, Klein BE, Tielsch JM, Hubbard L, Nieto FJ. Retinal microvascular abnormalities and their relationship with hypertension, cardiovascular disease, and mortality. Surv Ophthalmol 2001;46:59–80.
16. Cheung N, Liew G, Lindley RI, Liu EY, Wang JJ, Hand P, et al.. Retinal fractals and acute lacunar stroke. Ann Neurol 2010;68:107–11.
17. Cheung CY, Tay WT, Mitchell P, Wang JJ, Hsu W, Lee ML, et al.. Quantitative and qualitative retinal microvascular characteristics and blood pressure. J Hypertens 2011;29:1380–91.
18. El Assaad MA, Topouchian JA, Darne BM, Asmar RG. Validation of the Omron HEM-907 device for blood pressure measurement. Blood Press Monit 2002;7:237–41.
19. Obesity: preventing and managing the global epidemic. Report of a WHO consultation. World Health Organ Tech Rep Ser 2000;894:i–xii–253, 1–253.
20. Davies GA, Maxwell C, McLeod L, Gagnon R, Basso M, Bos H, et al.. SOGC Clinical Practice Guidelines: Obesity in pregnancy. No. 239, February 2010. Int J Gynaecol Obstet 2010;110:167–73.
21. Jafar TH, Chaturvedi N, Pappas G. Prevalence of overweight and obesity and their association with hypertension and diabetes mellitus in an Indo-Asian population. CMAJ 2006;175:1071–7.
22. Institute of Medicine. Nutritional status and weight gain. Nutrition during pregnancy. Washington, DC: National Academies Press; 1990. p. 227–33.
23. Liew G, Wong TY, Mitchell P, Wang JJ. Are narrower or wider retinal venules associated with incident hypertension? Hypertension 2006;48:e10.
24. Taylor B, Rochtchina E, Wang JJ, Wong TY, Heikal S, Saw SM, et al.. Body mass index and its effects on retinal vessel diameter in 6-year-old children. Int J Obes (Lond) 2007;31:1527–33.
25. Kip KE, Marroquin OC, Kelley DE, Johnson BD, Kelsey SF, Shaw LJ, et al.. Clinical importance of obesity versus the metabolic syndrome in cardiovascular risk in women: a report from the Women's Ischemia Syndrome Evaluation (WISE) study. Circulation 2004;109:706–13.
26. Raj M. Obesity and cardiovascular risk in children and adolescents. Indian J Endocrinol Metab 2012;16:13–9.
27. Duvekot JJ, Peeters LL. Maternal cardiovascular hemodynamic adaptation to pregnancy. Obstet Gynecol Surv 1994;49:S1–14.
28. Tomoda S, Tamura T, Sudo Y, Ogita S. Effects of obesity on pregnant women: maternal hemodynamic change. Am J Perinatol 1996;13:73–8.
29. Galtier-Dereure F, Boegner C, Bringer J. Obesity and pregnancy: complications and cost. Am J Clin Nutr 2000;71:1242–8S.
30. Frederick IO, Rudra CB, Miller RS, Foster JC, Williams MA. Adult weight change, weight cycling, and prepregnancy obesity in relation to risk of preeclampsia. Epidemiology 2006;17:428–34.
31. Naeye RL. Maternal body weight and pregnancy outcome. Am J Clin Nutr 1990;52:273–9.
32. Johnson SR, Kolberg BH, Varner MW, Railsback LD. Maternal obesity and pregnancy. Surg Gynecol Obstet 1987;164:431–7.
33. Garbaciak JA Jr, Richter M, Miller S, Barton JJ. Maternal weight and pregnancy complications. Am J Obstet Gynecol 1985;152:238–45.
34. Abrams B, Parker J. Overweight and pregnancy complications. Int J Obes 1988;12:293–303.
35. Edwards LE, Hellerstedt WL, Alton IR, Story M, Himes JH. Pregnancy complications and birth outcomes in obese and normal-weight women: effects of gestational weight change. Obstet Gynecol 1996;87:389–94.
36. Galtier-Dereure F, Montpeyroux F, Boulot P, Bringer J, Jaffiol C. Weight excess before pregnancy: complications and cost. Int J Obes Relat Metab Disord 1995;19:443–8.
37. Larsen TB, Sorensen HT, Gislum M, Johnsen SP. Maternal smoking, obesity, and risk of venous thromboembolism during pregnancy and the puerperium: a population-based nested case–control study. Thromb Res 2007;120:505–9.
38. Yamakawa K, Bhutto IA, Lu Z, Watanabe Y, Amemiya T. Retinal vascular changes in rats with inherited hypercholesterolemia–corrosion cast demonstration. Curr Eye Res 2001;22:258–65.
39. Witt N, Wong TY, Hughes AD, Chaturvedi N, Klein BE, Evans R, et al.. Abnormalities of retinal microvascular structure and risk of mortality from ischemic heart disease and stroke. Hypertension 2006;47:975–81.
40. Tomita Y, Kubis N, Calando Y, Tran Dinh A, Meric P, Seylaz J, et al.. Long-term in vivo investigation of mouse cerebral microcirculation by fluorescence confocal microscopy in the area of focal ischemia. J Cereb Blood Flow Metab 2005;25:858–67.
41. Yu SM, Nagey DA. Validity of self-reported pregravid weight. Ann Epidemiol 1992;2:715–21.
42. Saldana TM, Siega-Riz AM, Adair LS. Effect of macronutrient intake on the development of glucose intolerance during pregnancy. Am J Clin Nutr 2004;79:479–86.
© 2012 by The American College of Obstetricians and Gynecologists. Published by Wolters Kluwer Health, Inc. All rights reserved.
43. Lederman SA, Paxton A. Maternal reporting of prepregnancy weight and birth outcome: consistency and completeness compared with the clinical record. Matern Child Health 1998;2:123–6.