The Impact of Obesity on Urinary Incontinence Symptoms, Severity, Urodynamic Characteristics and Quality of Life
Article Outline
- Abstract
- Materials and Methods
- Results
- Discussion
- Conclusions
- Appendix. Format for Crediting Sites and Funding in Publications
- References
- Copyright
Purpose
We compared urinary incontinence severity measures and the impact of stress urinary incontinence in normal, overweight and obese women.
Materials and Methods
Baseline characteristics of subjects in the SISTEr (655) and the TOMUS (597) were analyzed. Body mass index was defined as normal (less than 25 kg/m2), overweight (25 to less than 30 kg/m2) and obese (30 kg/m2 or greater). Independent urinary incontinence severity measures included a 3-day diary including incontinence episode frequency, Urogenital Distress Inventory scores and Valsalva leak point pressure from urodynamic testing. Impact was measured using the Incontinence Impact Questionnaire. Multivariable regression models were fit for each severity measure (Urogenital Distress Inventory, incontinence episode frequency, Valsalva leak point pressure and Incontinence Impact Questionnaire) on weight category. Covariates included age, race, diabetes and variables significantly associated with body mass index on bivariate analysis.
Results
Mean age (SD) of participants was 51.9 (10.3) in SISTEr and 52.9 (11.0) in TOMUS. In each trial 45% of subjects were obese. In SISTEr multivariable regression analyses showed that higher weight category was independently associated with higher mean Urogenital Distress Inventory score (p = 0.003), incontinence episode frequency (p <0.0001), Valsalva leak point pressure (p = 0.003) and Incontinence Impact Questionnaire score (p = 0.0004). In TOMUS higher weight category was not associated with Urogenital Distress Inventory score (p = 0.24) but was associated with higher incontinence episode frequency (p = 0.0003), Valsalva leak point pressure (p = 0.0006) and Incontinence Impact Questionnaire score (p <0.0001).
Conclusions
Obese women undergoing surgery for stress urinary incontinence report more incontinence episodes, more symptom distress and worse quality of life despite better measure of urethral function (higher Valsalva leak point pressure) on urodynamics.
Key Words: obesity, urinary incontinence, stress, urodynamics
Abbreviations and Acronyms: BMI, body mass index, HRT, hormone replacement therapy, IEF, incontinence episode frequency, IIQ, Incontinence Impact Questionnaire, MESA, Medical, Epidemiological, and Social Aspects of Aging, MUCP, maximum urethral closure pressure, Pabd, intra-abdominal pressure, PFS, pressure flow study, POP-Q, pelvic organ prolapse quantification, Pves, intravesical pressure, Qmax, maximum flow rate, SISTEr, Stress Incontinence Surgical Treatment Efficacy Trial, SUI, stress urinary incontinence, TOMUS, Trial of Mid-Urethral Slings, UDI, Urogenital Distress Inventory, UDS, urodynamics, UI, urinary incontinence, UUI, urge urinary incontinence, VLPP, Valsalva leak point pressure
Stress urinary incontinence is prevalent in women in the United States and has a significant quality of life impact.1 Thus, SUI presents tremendous health related2 and economic3 burdens. Obesity is a modifiable risk factor for the development of urinary incontinence with numerous epidemiological studies describing the impact of obesity on UI prevalence.4, 5, 6 The estimated prevalence of obesity, defined as a BMI of 30 kg/m2 or greater, exceeds 30% of the adult population in the United States.4 Increased BMI is associated with prevalent and incident UI as well as with UI severity.6 A large cross-sectional study demonstrated that each 5-unit increase in BMI was associated with a 60% increase in daily UI, with obesity having the largest attributable risk for daily UI compared to other factors.7 These findings were confirmed in surgical cohorts.8, 9 Behaviorally induced 10, 11, 12 and surgically induced13, 14 weight reduction are associated with decreased UI severity.
The pathophysiological basis posited for the relationship between obesity and UI lies in the significant correlation between BMI and intra-abdominal pressure, suggesting that obesity may stress the pelvic floor secondary to a chronic state of increased pressure.15, 16 However, there are limited data on the impact of obesity on patient oriented and urodynamic parameters, and on the mechanistic factors that may underlie UI in obese and normal weight women.
To more clearly understand the specific factors that may be associated with signs and symptoms of UI we compared baseline characteristics of a large number of normal weight, overweight and obese women who enrolled in 2 randomized comparative effectiveness trials for the surgical treatment of SUI. Specifically we compared UI severity measures and the impact of SUI among obese, overweight and normal weight women planning to undergo SUI surgery.
Materials and Methods
The Urinary Incontinence Treatment Network performed 2 large randomized comparative effectiveness trials studying the surgical treatment of SUI in women. The first trial, SISTEr, randomized 655 subjects to Burch colposuspension or autologous rectus fascial sling for SUI. The second trial, TOMUS, randomized 597 subjects to polypropylene midurethral sling placed via the retropubic or transobturator approach. Primary outcomes for SISTEr have been published17and will soon be available for TOMUS. Design papers have been published for both trials.18, 19 This article represents the analyses of the preoperative data collected from these 2 trials. WHO definitions of BMI were used to define weight groups as obese—30 kg/m2 or greater, overweight—25 to less than 30 kg/m2 and healthy weight—less than 25 kg/m2.
Demographic variables reported included age, race/ethnicity, education, marital status and occupational score. Continuous clinical variables included height, weight, BMI, specific parameters from POP-Q, the most prolapsed portion of the anterior vaginal wall (Ba), the most prolapsed portion of the posterior vaginal wall (Bp), the genital hiatus (gh), the Q-tip test (delta angle), mean muscle strength (Brink) scores, 24-hour pad weight, IEF from a 3-day bladder diary and general patient health score. Categorical clinical variables included prior UI surgery, prior prolapse surgery, prior hysterectomy, menopausal status, HRT, diabetes and smoking status. Subjective measures included the UDI, IIQ and the MESA questionnaire. Subjective categorical variables included responses to questions about physical accommodation, character of urine stream and fecal incontinence. Continuous UDS variables included VLPP, Pves, Pabd, bladder volume at first desire, bladder volume at strong desire, maximal cystometric capacity and pressure flow data (Qmax, Pves at Qmax, Pabd at Qmax, time to Qmax). The only categorical urodynamic variable was pressure flow voiding pattern (normal or abnormal).
Analyses were performed in parallel for the SISTEr and TOMUS subjects because the trials had different inclusion and exclusion criteria representing the different populations. Continuous variables were summarized using mean (SD) values. Distributions of continuous measures were assessed for normality. Although the distribution of some measures was moderately skewed, we elected to conduct and report analyses in the natural scales for ease of interpretation. To investigate the bivariate relationships of demographic, clinical and UDS variables with BMI category, 1-way ANOVA was used for continuous measures, and cross-classification and the chi-square test or Fisher's exact test were used for categorical measures as appropriate.
To assess multicollinearity among the multiple measures of incontinence, a preliminary principal components analysis was computed,20 which indicated that there were 3 independent dimensions of stress incontinence. One dimension was weighted most heavily by the subjective measures composed of the MESA stress score, UDI stress and IIQ total scores. The second dimension was most heavily weighted by the objective measures of pad weight and mean incontinence episodes per day. The third dimension was weighted by the objective urodynamic measures composed of VLPP and MUCP (the latter in TOMUS only). Based on this analysis we selected independent measures of incontinence for further analysis to reduce the number of redundant hypothesis testing. Within each dimension we selected a single measure to represent that aspect of incontinence, except in the subjective dimension as we wanted to explore subjective symptom distress and symptom impact. Thus, we report the association of weight category with 1 objective measure of UI severity (IEF), 2 subjective measures of UI severity (UDI total score and IIQ) and 1 urodynamic parameter of UI severity (VLPP).21 To further understand the associations of weight category with severity, we computed an ANCOVA of each severity and impact measure on weight category controlling for clinically important variables and those significantly associated with weight in bivariate analysis. Analyses were performed using SAS® version 9.2. Because of the large number of hypothesis tests we defined statistical significance by p = 0.01.
Results
Participants in the SISTEr and TOMUS trials had mean (SD) ages of 51.9 (10.3) and 52.9 (11.0) years, respectively. In SISTEr the mean BMI of normal weight women was 22.9 (1.6), of overweight women 27.5 (1.4) and of obese women 35.4 (4.8). Similarly in TOMUS the mean BMI of normal weight women was 22.6 (1.7), of overweight women 27.4 (1.2) and of obese women 36.5 (5.0). Of SISTEr subjects 73% and of those in TOMUS 79% were Caucasian. In both trials compared to normal weight women obese women were more likely to have less education and report poorer health. Additionally, obese women in SISTEr were more likely to smoke and less likely to use hormone therapy. There were no differences among the groups in age, cesarean deliveries, hysterectomy, prior UI surgery, prior prolapse surgery or POP-Q stage (table 1). In both trials obese women had a greater Q-tip resting angle, and smaller difference between strain and resting Q-tip angles (table 2). Other POP-Q points did not differ significantly by weight group.
Table 1. Association of selected participant characteristics with weight classification
| SISTEr | TOMUS | |||||
|---|---|---|---|---|---|---|
| Normal | Overweight | Obese | Normal | Overweight | Obese | |
| No. (%) | 142 (22) | 218 (33) | 290 (45) | 137 (23) | 192 (32) | 262 (45) |
| Mean age(SD)⁎ | 51.4 (10.9) | 52.5 (10.1) | 51.7 (10.1) | 52.5 (11.5) | 54.2 (11.3) | 52.1 (10.4) |
| No. race/ethnicity(%):† | ||||||
| Nonwhite | 32 (23) | 53 (24) | 88 (30) | 23 (17) | 31 (16) | 69 (26) |
| White | 110 (77) | 165 (76) | 201 (70) | 114 (83) | 161 (84) | 193 (74) |
| No. education(%):† | ‡ | ‡ | ||||
| Less than high school | 34 (24) | 93 (43) | 98 (34) | 31 (23) | 55 (28) | 96 (37) |
| Greater than high school | 58 (41) | 78 (36) | 123 (42) | 44 (32) | 72 (38) | 99 (38) |
| Completed college | 50 (35) | 47 (21) | 69 (24) | 62 (45) | 65 (34) | 67 (25) |
| No. smoking(%):† | ‡ | |||||
| Never | 91 (64) | 120 (55) | 141 (49) | 81 (59) | 100 (52) | 135 (52) |
| Former | 37 (26) | 60 (28) | 110 (38) | 47 (34) | 69 (36) | 80 (30) |
| Current | 14 (10) | 38 (17) | 39 (13) | 9 (7) | 23 (12) | 47 (18) |
| No. diabetes† | 4 (3) | 12 (6) | 29 (10) | 5 (4) | 8 (4) | 26 (10) |
| No. hormone therapy(%):† | ‡ | |||||
| No | 30 (21) | 89 (41) | 112 (39) | 46 (34) | 76 (40) | 117 (45) |
| Yes | 58 (41) | 71 (33) | 92 (32) | 39 (28) | 64 (33) | 67 (26) |
| Premenopausal | 54 (38) | 57 (26) | 86 (30) | 52 (38) | 52 (27) | 76 (29) |
| No. cesarean section† | 10 (7) | 18 (8) | 22 (8) | 13 (9) | 13 (7) | 32 (12) |
| No. prior hysterectomy† | 42 (30) | 68 (31) | 91 (31) | 35 (26) | 52 (27) | 78 (30) |
| No. prior UI surgery† | 16 (11) | 33 (15) | 44 (15) | 22 (16) | 19 (10) | 36 (14) |
| No. prior prolapse surgery§ | 5 (4) | 6 (3) | 2 (1) | 4 (3) | 9 (5) | 10 (4) |
| No. general health score(%):† | ∥ | ∥ | ||||
| Excellent | 47 (33) | 53 (24) | 45 (16) | 65 (47) | 42 (22) | 43 (17) |
| Very good | 56 (39) | 78 (36) | 103 (36) | 54 (39) | 97 (51) | 100 (38) |
| Good + fair + poor | 39 (27) | 87 (40) | 139 (48) | 18 (13) | 50 (27) | 118 (45) |
⁎Equality of means tested by ANOVA. |
†Equality of frequencies tested using the chi-square test. |
‡0.001 ≤ p <0.01. |
§Prior prolapse surgery tested using Fisher's exact test. |
∥Chi-square test p <0.001. |
Table 2. Association of anatomical characteristics with weight categories
| SISTEr | TOMUS | |||||
|---|---|---|---|---|---|---|
| Normal | Overweight | Obese | Normal | Overweight | Obese | |
| Mean resting angle (SD)⁎ | 8.8 (15.0) | 14.9 (15.6) | 19.0 (19.5)† | 6.7 (13.0) | 5.5 (11.7) | 11.8 (13.5)† |
| Mean strain angle(SD)⁎ | 59.2 (18.8) | 60.0 (17.8) | 60.8 (18.4) | 46.9 (20.2) | 44.7 (21.5) | 46.5 (20.5) |
| Mean delta(SD)⁎ | 50.5 (18.0) | 45.1 (17.6) | 41.7 (18.1)† | 40.3 (18.7) | 39.2 (20.5) | 34.7 (17.9)‡ |
| No. POP-Q(%):§ | ||||||
| Stages 0–I | 33 (23) | 54 (25) | 74 (26) | 64 (47) | 82 (43) | 120 (46) |
| Stage II | 85 (60) | 119 (55) | 180 (62) | 60 (44) | 93 (48) | 124 (47) |
| Stage III | 24 (17) | 45 (21) | 36 (12) | 13 (9) | 17 (9) | 18 (7) |
| Mean point Ba(SD)⁎ | −0.4 (2.1) | −0.4 (2.0) | −0.8 (1.6) | −1.2 (1.5) | −1.2 (1.8) | −1.4 (1.3) |
| Mean point Bp(SD)⁎ | −1.7 (1.8) | −1.6 (1.7) | −1.7 (1.4) | −1.9 (1.3) | −1.8 (1.8) | −2.0 (1.1) |
| Mean point gh(SD)⁎ | 3.5 (1.0) | 3.5 (1.3) | 3.7 (1.2) | 3.3 (1.0) | 3.4 (1.0) | 3.6 (1.1) |
| Mean Brink score(SD)⁎ | 9.1 (2.0) | 8.9 (2.2) | 8.9 (2.0) | 8.9 (1.8) | 8.7 (2.1) | 8.7 (2.0) |
⁎Equality of means tested by ANOVA. |
†p <0.001. |
‡0.001 ≤ p <0.01. |
§Equality of frequencies tested using the chi-square test. |
Of the women in SISTEr 16% and in TOMUS 10% reported fecal incontinence as well as UI. The proportion did not differ by weight category (10%, 17% and 17% in SISTEr, and 9%, 6% and 13% in TOMUS for normal weight, overweight and obese women, respectively). Obese women did not differ from the normal weight counterparts in reporting abnormal voiding symptoms such as slow stream, hesitating or splinting (data not shown). Baseline UDS measures for each trial are summarized in table 3. In both trials obese women had higher VLPP, Pves and Pabd at baseline, and higher Pves and Pabd at Qmax than normal and overweight women. Interestingly there were no differences in the presence of detrusor overactivity among normal, overweight and obese subjects in these trials.
Table 3. Association of urodynamic measures with weight categories
| SISTEr | TOMUS | |||||
|---|---|---|---|---|---|---|
| Normal | Overweight | Obese | Normal | Overweight | Obese | |
| Mean VLPP (SD) | 107.3 (31.8) | 115.8 (37.1) | 122.2 (39.6)⁎ | 107.9 (35.2) | 114.0 (39.3) | 130.2 (46.1)† |
| Mean Pves baseline(SD) | 31.7 (10.4) | 35.4 (10.8) | 40.3 (11.8)† | 32.3 (9.2) | 35.0 (11.1) | 39.4 (11.9)† |
| Mean Pabd baseline(SD) | 30.0 (10.5) | 33.5 (11.1) | 38.4 (12.2)† | 30.3 (9.7) | 33.0 (11.2) | 37.8 (11.2)† |
| Mean bladder vol first desire(SD) | 150.1 (108.8) | 145.6 (96.5) | 135.1 (88.7) | 133.4 (85.8) | 111.5 (85.4) | 111.5 (73.1) |
| Mean bladder vol strong desire(SD) | 276.0 (155.9) | 259.2 (138.2) | 252.0 (126.6) | 250.1 (126.4) | 222.1 (119.0) | 219.1 (111.7) |
| Mean max cystometric capacity(SD) | 399.9 (141.0) | 391.8 (140.9) | 387.6 (134.4) | 371.0 (136.4) | 350.3 (122.4) | 341.4 (114.5) |
| No./total No. detrusor overactivity(%) | 12/139(9) | 15/217(7) | 33/285(12) | 12/133(9) | 21/190(11) | 37/260(14) |
| Mean max flow(pressure flow study)(SD) | 20.8 (10.6) | 21.7 (9.8) | 21.3 (9.8) | 21.9 (10.6) | 21.9 (11.2) | 22.2 (10.5) |
| Mean Pves at Qmax(SD) | 50.4 (18.4) | 54.2 (23.8) | 65.5 (24.8)† | 47.5 (19.1) | 53.8 (28.1) | 64.1 (27.2)† |
| Mean Pabd at Qmax(SD) | 33.8 (18.6) | 36.6 (21.7) | 44.6 (23.7)† | 30.2 (21.2) | 36.0 (28.9) | 42.5 (27.0)† |
| Mean secs to max flow(SD) | 24.9 (33.4) | 19.2 (23.3) | 17.5 (25.8) | 20.6 (25.6) | 21.7 (30.2) | 24.1 (48.5) |
⁎0.001 ≤ p <0.01. |
†p <0.001. |
Obese women had poorer scores on all 3 measures of incontinence severity and impact (table 4). Specifically in both trials obese women experienced more incontinence episodes, reported higher symptom distress, had higher VLPPs and had greater symptom specific impact on quality of life.
Table 4. Association of weight category with incontinence severity
| SISTEr | TOMUS | |||||
|---|---|---|---|---|---|---|
| Normal | Overweight | Obese | Normal | Overweight | Obese | |
| Unadjusted mean (SD):⁎ | ||||||
| IIQ total score | 132.1 (87.0) | 170.5 (102.5) | 191.2 (101.1)† | 119.9 (78.3) | 132.3 (89.7) | 182.7 (102.6)† |
| UDI total score | 138.8 (43.7) | 146.7 (51.4) | 160.0 (46.4)† | 125.2 (41.1) | 129.9 (44.0) | 143.3 (47.1)† |
| UDI urge subscale score | 39.6 (22.6) | 45.7 (24.5) | 53.3 (25.4)† | 33.7 (21.4) | 37.6 (25.6) | 48.2 (25.5)† |
| UDI stress subscale score | 77.2 (19.3) | 74.0 (24.6) | 81.4 (20.4)† | 75.7 (21.9) | 74.6 (21.4) | 73.8 (21.4) |
| IEF | 2.2 (2.1) | 3.3 (3.3) | 3.6 (3.0)† | 2.9 (3.3) | 2.8 (2.2) | 3.9 (3.1)† |
| VLPP | 107.3 (31.8) | 115.8 (37.1) | 122.2 (39.6)‡ | 107.9 (35.2) | 114.0 (39.3) | 130.2 (46.1)† |
| Adjusted mean:§ | ||||||
| IIQ total score | 151.3 | 175.9 | 189.7† | 158.2 | 155.0 | 189.8† |
| UDI total score | 144.9 | 147.2 | 159.1‡ | 143.9 | 142.3 | 149.1 |
| IEF | 2.8 | 3.8 | 4.2† | 2.9 | 2.7 | 3.8† |
| VLPP | 108.3 | 118.0 | 124.8‡ | 110.8 | 116.6 | 131.9† |
⁎Equality of means tested by ANOVA. |
†p <0.001. |
‡0.001 ≤ p <0.01. |
§Means adjusted for age, education race/ethnicity, smoking status, general health HRT use and diabetes using ANCOVA. |
To explore whether the association of these measures of incontinence with weight category remained when covariates were controlled, we computed a multivariable analysis (ANCOVA) of each severity measure on weight category controlling for age, race and ethnicity, education, general patient health score, HRT use, diabetes and smoking. This analysis showed that in SISTEr, weight category remained significantly associated with higher UDI total score (p = 0.003), increasing IEF (p <0.0001), higher VLPP (p = 0.003) and higher impact (p = 0.0004). In TOMUS the weight category was no longer associated with higher UDI score (p = 0.24) but was associated with increased incontinence episodes (p = 0.0003), higher VLPP (p = 0.0006) and higher impact (p <0.0001) when covariates were controlled. As a check on our decision to conduct analyses using the natural scales of the measures, sensitivity analyses using normalizing transformations were performed and the results were the same as those reported in table 4.
Discussion
Obese women with SUI participating in 2 large randomized surgical trials had worse objective and subjective measures of UI severity compared to normal weight women. Obese women reported greater symptom distress and impact on quality of life from UI symptoms, and experienced more incontinent episodes, suggesting they have worse disease and/or experience other factors which increase the symptom burden. As BMI weight categories increased, subjective and objective UI severity seemed to increase. Interestingly while women in both trials reported greater overall symptom distress from UI, stress specific symptom distress did not differ among the obese and normal and overweight women. However, obese women with SUI did have more concomitant urge incontinence compared to normal and overweight women, which may have contributed to increased symptoms (table 4). Clinicians commonly believe that women with mixed UI symptoms (SUI and UUI) have more severe UI than those with either pure SUI or UUI. In a large epidemiological study 38% of women with mixed incontinence had severe incontinence and almost half were bothered by their incontinence. In contrast, only 17% of SUI only women had severe incontinence and only a third were bothered.22
Weight group remained significantly associated with higher IEF when other characteristics were held constant, implying that UI severity is not explained by other factors that may be associated with higher weight category. This is consistent with weight reduction data showing that incontinence episode frequency decreases with significant weight loss.7, 10, 11, 12 A recent study comparing an intensive 6-month weight loss program (diet, exercise and behavior modification) to a structured education program demonstrated that in the intervention group a BMI decrease of 8% was associated with 47% fewer incontinence episodes, while in the control group there was a mean BMI decrease of 1.6% with a 28% decrease in incontinence episode frequency.12 In addition, the intervention group had a greater decrease in SUI episodes but not urge incontinence episodes. These data differ somewhat from our subjective data, which suggests a difference in bother from UUI but not SUI in obese women compared to normal weight women. We did not differentiate between stress and urge incontinence episodes in our diary data.
Several urodynamic parameters differed among obese, normal and overweight women. Consistent with previous studies obese women had higher baseline intravesical and abdominal pressures than normal weight women.15, 16 Previously it was hypothesized that higher abdominal pressure in women with greater BMI may explain the greater prevalence of UI and UI severity in obese women.13, 15 In a small cohort of women after surgical weight loss intravesical pressure decreased.13 It seems plausible that the increased UI severity seen in obese women may be in part due to the higher abdominal and vesical pressures which put them closer to the leakage threshold regardless of urethral function. This hypothesis requires further study.
While obese women had worse UI severity than normal weight women, they had higher VLPP values than normal and overweight women. The association between VLPP and obesity in women was noted in a previous analysis of clinical and demographic factors associated with VLPP in the SISTEr population.23 We did not measure urethral pressure simultaneously with vesical and abdominal pressures at baseline to determine if higher pressures were transmitted to the urethra in obese women, similar to the higher pressures transmitted to the bladder and abdomen. It seems plausible that at rest, urethral pressures are greater in obese women, but the urethra is unable to respond to events that require quick increases in urethral pressure. It is possible that obese women rely on greater muscle contraction and force at rest, thereby recruiting a larger proportion of the motor unit pool to maintain continence at rest. When a stress event occurs they are unable to recruit any additional motor units resulting in urinary leakage. Such a hypothesis is consistent with Henneman's principle for motor unit recruitment in striated muscles which states that as the requirement for greater muscle contraction and force increases, more and larger motor units are recruited.24 Research in other fields has demonstrated that obesity is associated with slower median nerve conduction velocities, which further supports a potential neuromuscular etiology for our findings.25 Further studies which more precisely assess urethral neuromuscular function in obese and normal weight women are necessary.
Obese women had less urethral mobility with straining (as measured by change in Q-tip angle from rest with straining) than normal weight women. Lack of urethral mobility is associated with poorer outcomes after SUI treatments and may contribute to increased UI severity in obese women despite better measures of intrinsic urethral function. In a case-control study of stress incontinent and continent control women, DeLancey et al recently demonstrated that urethral function, measured as MUCP, was more strongly associated with SUI than urethral mobility/support.26 MUCP predicted half the occurrence of SUI. However, urethral support/mobility did predict 16% of SUI cases.
Our analyses are strengthened by inclusion of a large number of women with stress incontinence representing all BMI categories from 2 randomized surgical trials. Study participants are well characterized using validated subjective and objective measures. In addition, urodynamic techniques were standardized and validated across participating sites.27 The consistency of the findings across the 2 study samples supports the conclusion that the associations found are robust in women with SUI. Our study may have been strengthened by the inclusion of urethral pressure measurements during cystometry and VLPP measurements. Such inclusion may have provided further insight into urethral function. It may also have been more informative if incontinence episodes had been broken down by cause, ie associated with stress or urge UI.
The main statistical limitation is of multiple hypothesis testing because this can lead to identification of apparent associations due to chance. However, performing the analysis in parallel across the 2 samples showed consistency, providing evidence of a real association and not just chance. Modeling was performed to assess whether relationships between BMI and incontinence severity measures held controlling for confounders. However, we only partially addressed collinearity, did not test any interaction effects and did not formally test models for goodness of fit. These issues would be more relevant if we were trying to develop an explanatory model for incontinence, which was not the purpose of this report.
Conclusions
Obese women planning incontinence surgery have more severe UI symptom distress, quality of life impact and objective findings than normal weight women. Surprisingly, obese women also seem to have better urethral function as measured by traditional urodynamic techniques. Factors other than urethral failure may contribute to UI in obese women. Further investigation into urethral function changes with stress events is warranted.
Appendix. Format for Crediting Sites and Funding in Publications
Steering Committee
Elizabeth A. Gormley, MD, Chair (Dartmouth Hitchcock Medical Center, Lebanon, NH); Larry Sirls, MD, Salil Khandwala, MD (William Beaumont Hospital, Royal Oak, MI and Oakwood Hospital, Dearborn, MI; U01 DK58231); Linda Brubaker, MD, Kimberly Kenton, MD (Loyola University Medical Center, Maywood, IL; U01 DK60379); Holly E. Richter, PhD, MD, L. Keith Lloyd, MD (University of Alabama at Birmingham, Birmingham, AL; U01 DK60380); Michael Albo, MD, Charles Nager, MD (University of California, San Diego, CA; U01 DK60401); Toby C. Chai, MD, Harry W. Johnson, MD (University of Maryland, Baltimore, MD; U01 DK60397); Halina M. Zyczynski, MD, Wendy Leng, MD (University of Pittsburgh, Pittsburgh, PA; U01 DK 58225); Philippe Zimmern, MD, Gary Lemack, MD (University of Texas Southwestern, Dallas, TX; U01 DK60395); Stephen Kraus, MD, Thomas Rozanski, MD (University of Texas Health Sciences Center, San Antonio, TX; U01 DK58234); Peggy Norton, MD, Ingrid Nygaard, MD (University of Utah, Salt Lake City, UT; U01 DK60393); Sharon Tennstedt, PhD, Anne Stoddard, ScD (New England Research Institutes, Watertown, MA; U01 DK58229); Debuene Chang, MD, Marva Moxey-Mims, MD, Rebekah Rasooly, MD (National Institute of Diabetes and Digestive and Kidney Diseases).
Co-Investigators
Amy Arisco, MD; Jan Baker, APRN; Diane Borello-France, PT, PhD; Kathryn L. Burgio, PhD; Ananias Diokno, MD; Melissa Fischer, MD; MaryPat Fitzgerald, MD; Chiara Ghetti, MD; Patricia S. Goode, MD; Robert L. Holley, MD; Margie Kahn, MD; Jerry Lowder, MD; Karl Luber, MD; Emily Luckacz, MD; Alayne Markland, DO, MSc; Shawn Menefee, MD; Pamela Moalli, MD; Elizabeth Mueller, MD; Pradeep Nagaraju, MD; Kenneth Peters, MD; Elizabeth Sagan, MD; Joseph Schaffer, MD; Amanda Simsiman, MD; Robert Starr, MD; Gary Sutkin, MD; R. Edward Varner, MD.
Study Coordinators
Laura Burr, RN; JoAnn Columbo, BS, CCRC; Tamara Dickinson, RN, CURN, CCCN, BCIA-PMDB; Rosanna Dinh, RN, CCRC; Judy Gruss, RN; Alice Howell, RN, BSN, CCRC; Chaandini Jayachandran, MSc; Kathy Jesse, RN; D. Lynn Kalinoski, PhD; Barbara Leemon, RN; Kristen Mangus; Karen Mislanovich, RN; Elva Kelly Moore, RN; Caren Prather, RN; Sylvia Sluder, CCRP; Mary Tulke, RN; Robin Willingham, RN, BSN; Kimberly Woodson, RN, MPH; Gisselle Zazueta-Damian.
Data Coordinating Center
Kimberly J. Dandreo, MSc; Liyuan Huang, MS; Rose Kowalski, MA; Heather Litman, PhD; Marina Mihova, MHA; Anne Stoddard, ScD (Co-PI); Kerry Tanwar, BA; Sharon Tennstedt, PhD (PI); Yan Xu, MS.
Data Safety and Monitoring Board
J. Quentin Clemens, MD, Chair, Northwestern University Medical School, Chicago, IL; Paul Abrams, MD, Bristol Urological Institute, Bristol, United Kingdom; Diedre Bland, MD, Blue Ridge Medical Associates, Winston-Salem, NC; Timothy B. Boone, MD, The Methodist Hospital, Baylor College of Medicine, Houston, TX; John Connett, PhD, University of Minnesota, Minneapolis, MN; Dee Fenner, MD, University of Michigan, Ann Arbor, MI; William Henderson, PhD, University of Colorado, Aurora, CO; Sheryl Kelsey, PhD, University of Pittsburgh, Pittsburgh, PA; Deborah J. Lightner, MD, Mayo Clinic, Rochester, MN; Deborah Myers, MD, Brown University School of Medicine, Providence, RI; Bassem Wadie, MBBCh, MSc, MD, Mansoura Urology and Nephrology Center, Mansoura, Egypt; J. Christian Winters, MD, Louisiana State University Health Sciences Center, New Orleans, LA.
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Supported by cooperative agreements U01 DK58225, U01 DK58229, U01 DK58234, U01 DK58231, U01 DK60379, U01 DK60380, U01 DK60393, U01 DK60395, U01 DK60397 and U01 DK60401 from the National Institute of Diabetes and Digestive and Kidney Diseases.
See Editorial on page 427.
For another article on a related topic see page 780.
PII: S0022-5347(09)02624-X
doi:10.1016/j.juro.2009.09.083
© 2010 American Urological Association. Published by Elsevier Inc. All rights reserved.
Refers to article:
- Body Mass Index as a Predictor of Urological Disease and Outcomes—Overly Simplistic? , 14 December 2009
- Bladder Dysfunction in a New Mutant Mouse Model With Increased Superoxide—Lack of Nitric Oxide? , 17 December 2009