Investigating Pelvic Floor Muscle Strength in Women of Reproductive Age and Factors Affecting It

Abstract

This descriptive study was designed to investigate the pelvic floor muscle strength (PFMS) of women aged 18 to 49 years and to examine the factors that may have an effect on PFMS. The study was conducted on 258 women who visited a gynecology outpatient clinic between January 2019 and January 2020, who met the research criteria, and who agreed to participate in the study. The data were collected using the Sociodemographic Characteristics Information Form. The Modified Oxford Scale (MOS) and a perineometer were used to evaluate the PFMS of the women. The mean PFMS value measured using the perineometer was 31.56 ± 12.17 cmH₂O (moderate pressure). The PFMS values were 20.00 to 29.9 cmH₂O (weak pressure) and 30.00 to 39.9 cmH₂O (moderate pressure) in 23.6% of the women, respectively. The PFMS values measured with MOS were of grade 3 strength (moderate pressure) in 23.6% of the women and grade 2 strength (weak pressure) in 23.3%. A statistically significant strong correlation was found between the perineometer measurement and the women’s MOS values. Moreover, a statistically significant difference was found between the PFMS values measured with the perineometer, MOS scores, and women’s age groups, educational status, marital status, employment status, income status, persistent cough, use of nicotine, alcohol and coffee consumptions, chronic constipation, history of frequent urinary tract infections, regular exercise, body mass index, history of pregnancy, mode of delivery, use of episiotomy at birth, perineal rupture at birth, use of forceps vacuum at birth, multiple pregnancies, delivery of a baby weighing ≥4,000 g, treatment during pregnancy, hysterectomy, menopause, frequency of sexual intercourse, and pain during sexual intercourse (p < .05). We conclude that most of the women in the study had weak to moderate PFMS, that the evaluation of PFMS with the MOS positively overlapped with the perineometric measurements, and that a number of sociodemographic and obstetric variables act as risk factors that affect PFMS. The PFMS of all women should be assessed as part of their routine gynecological examinations.

Keywords

pelvic floor muscle strength reproductive age affecting factor

Introduction

The pelvic floor is a special structure consisting of the levator ani, ischiocavernosus, bulbocavernosus, and superficial transverse muscles, which protect the genitals and fascia of these muscles (Salian & Ved, 2018; Volløyhaug et al., 2016). This structure plays an important role in vital functions such as micturation, defecation, coitus, and labor. The pelvic floor muscles (PFMs) provide dynamic support to the pelvic organs by adjusting their tensions in response to changing conditions; they also play a role in regulating intra-abdominal pressure and help to reduce waist load (Bodner-Adler et al., 2019). Studies have reported that various factors, including age, ethnicity, pregnancy, delivery method, parity, medical history, family history, gynecological surgeries, and obesity, affect pelvic floor muscle strength (PFMS), and endurance. As a result, the PFMS may decrease and the ability of the PFMs to provide support may become impaired (Afshari et al., 2017; Bø et al., 2016; Hwang et al., 2019; Li et al., 2015; Ramalingam & Monga, 2015). The ligaments and fascia are under no tension as long as the PFMs are functioning normally. However, the pelvic organs remain between high intra-abdominal pressure and low atmospheric pressure when the PFMs are relaxed or damaged. The abilities of these organs to maintain their position is dependent on the ligaments. Although the ligaments can tolerate this load for a short time, the connective tissue may be damaged, and eventually, the organs are unable to maintain their positions when the PFMs do not support the pelvic floor (Friedman et al., 2012). As a result, pelvic floor dysfunctions (PFDs), which are common among women and negatively affect their quality of life, may develop, including urinary incontinence (UI), fecal incontinence (FI), pelvic organ prolapse (POP), and sexual dysfunction (Navarro Brazález et al., 2018). PFDs are serious problems that can lead women to experience low self-esteem and feelings of embarrassment and to become socially isolated; their quality of life and ability to engage in everyday activities may be negatively affected (Salian & Ved, 2018; Sangsawang & Sangsawang, 2013). In large population-based studies conducted in different countries, the prevalence of UI was reported to range from 18% to 45% (Dursun et al., 2014; García-Pérez et al., 2013; Kirss et al., 2013; Sensoy et al., 2013). POP negatively affects approximately 41% of women worldwide (Chapple & MacNeil, 2019). The FI prevalence is 14.4% in the United States and 22.4% in Indonesia (Menees et al., 2018; Suyasa et al., 2015). Previous studies also reported that the prevalence of sexual dysfunction ranges from 16.9% and 85% among women globally (Chapa et al., 2020; Guo et al., 2012). PFDs can have serious consequences and require surgery in 1 of 10 women. Annually, 300,000 women undergo surgery for UI and POP, and 29% of these surgeries are repeated. Studies have reported that 90,000 surgeries could be eliminated annually if the number of women with PFD was reduced by 25% and that 30,000 repeat surgeries could be eliminated. Identifying the factors that cause PFD and preventing them from occurring are three times more effective than the current treatments available (Demirtürk et al., 2017).

In this context, assessing PFMS and determining the factors affecting it are important for identifying women at high risk of PFD at an early stage. The present study was thus designed as a descriptive study to evaluate PFMS in women aged 18 to 49 and to examine the factors that may have an effect on PFMS.

Methods

The population of the research consisted of women who visited the gynecology outpatient clinic of a university hospital between January 2019 and January 2020. The study sample consisted of 258 women who met the research criteria and agreed to participate in the study. The necessary sample size was determined to be 251, given the sample calculation formula using the size of the known universe (Naing et al., 2006). A total of 258 women were recruited into the study through convenience sampling. The initial intention was to include 300 women in the study, but some women did not meet the inclusion criteria or did not agree to participate, leaving 258 participants. A power analysis was performed to determine the sample size, which indicated the post hoc power to be 100% for a sample of 258 individuals. The G*Power 3.1.3 software program was used to conduct the statistical power analysis.

The inclusion criteria were women who agreed to participate in the study, were willing to cooperate fully, were literate, were aged 18 to 49 years, had not received a diagnosis of and treatment for incontinence, had not received a diagnosis of and treatment for POP, did not have a urinary or vaginal infection present, did not have gynecological bleeding, and were not pregnant.

The exclusion criteria were patients who had central and peripheral nervous system diseases that affected their PFMS, had psychiatric problems, were pregnant, used muscle relaxants, had received a diagnosis of and treatment for incontinence, had received a diagnosis of and treatment for POP, had a urinary or vaginal infection present, or had gynecological bleeding.

The inclusion or exclusion of the participants in the study was based on information obtained both from the patient files and during the patient interviews.

Data Collection Forms

Data were collected using the Sociodemographic Characteristics Information Form. The PFMS of the women was evaluated using the Modified Oxford Scale (MOS) and a perineometer. The data were collected in face-to-face interviews. The Sociodemographic Characteristics Information Form took an average of 5 minutes to fill. The women’s PFMS was first measured using the MOS and then with a perineometer.

Sociodemographic Characteristics Information Form

This form was created by the researchers in consultation with the literature (Baracho et al., 2012; Kepenekci et al., 2011; Salian & Ved, 2018). The form summarized the basic characteristics of the women and consisted of 30 questions regarding their age, birthplace, educational status, the number of years they have been married, profession, their spouse’s educational status, their income status, their menopausal status, and their history of obstetric, gynecological, and chronic diseases.

Evaluation of PFMS with the MOS

The PFMS of the patients in this study was evaluated by a physician using the MOS. The patient was placed in the lithotomy position. The physician who performed the test placed two fingers (the index and middle fingers) on the vagina and asked the patient to contract her PFMs as if to stop a discharge of urine or gas. The patients were instructed not to use their abdominal, gluteal, or hip adductor muscle during the contractions. The strength of the contraction felt around the finger was evaluated according to the following scale: 0 indicated no contraction; 1 (very weak pressure), a barely perceptible contraction lasting <1 second; and 2 (weak pressure), a faint contraction persisting for 1 to 3 seconds. In contrast to these indicators of weak pelvic floor muscle contraction, a score of 3 (moderate pressure) indicated a contraction that resulted in resistance to the elevation of the examiner’s finger within the vaginal vault and a duration of 4 to 6 seconds; 4 (good pressure), perceptible resistance to the elevation of the finger for a period of 7 to 9 seconds; and 5 (strong pressure), a strong contraction with a duration of ≥9 seconds (Angelo et al., 2017).

Perineometer Measurement

The changes in PFMS of the patients were evaluated using a perineometer. This is a pressure manometer with a balloon device used to measure the force of the pelvic floor muscle contractions. For the purposes of this study, an EXTT-101 perineometer with a 26-mm-diameter and 108-mm-long vaginal probe and a 55-mm active measuring surface were used. To measure the force of the pelvic floor muscle contraction, the participants were put in a supine position, with hip and knee flexion. The probe was inserted 3 to 5 cm in the vaginal vault, and the device was zeroed. The participants were asked to perform three maximal pelvic floor muscle contractions in a row, without simultaneously contracting the abdominal, gluteal, or hip adductor muscles. The mean value of three consecutive contractions of 10 seconds each and peak flick muscle activity were measured as the maximum values of three consecutive quick contractions (Palmezoni et al., 2017).

Ethical Considerations

This research was conducted in accordance with the Declaration of Helsinki. Written permission was obtained from the medical research ethics committee of the university where the study was conducted. The participants were informed about the objectives of the study and that their information would remain confidential and that they would not be judged according to their responses. Signed informed consent forms were obtained from the participants.

Statistical Analyses

For the statistical analysis, IBM SPSS Statistics version 22.0 (SPSS Inc., Chicago, IL, USA) was used. Categorical variables are presented as numbers and percentages, whereas continuous variables are provided as means and standard deviations. The Kolmogorov–Smirnov test was used to assess the normal distribution of the data. The F and t tests and stepwise regression analysis were used to determine the relationship between the independent and dependent variables. In addition, a power analysis was performed to reveal the power of the study. The results were evaluated at a confidence interval of 95%, and the significance level was established at p < .05. In addition, the Cohen d value was used in calculating the effect size according to the difference of the group averages. When the Cohen d value was <0.2, the effect size was defined as “small”; when the Cohen d value was between 0.2 and 0.8, the effect size was defined as “medium”; when the Cohen d value was >0.8, the effect size was defined as “large” (Cohen, 1988).

Results

The mean reading using the perineometer was 31.56 ± 12.17 cmH₂O (range, 10–55 cmH₂O; moderate pressure). Of the women, 21.7% (56) had a reading of 10.00 to 19.9 cmH₂O (very weak pressure), 23.6% (61) had a reading of 20.00 to 29.9 cmH₂O (weak pressure), 23.6% (61) had a reading of 30.00 to 39.9 cmH₂O (moderate pressure), 23.3% (60) had a reading of 40.00 to 54.9 cmH₂O (good pressure), and 7.8% (20) had a reading of >55.00 cmH₂O (strong pressure).

On the MOS, 22.1% (57), 23.3% (60), 23.6% (61), 22.5% (58), and 8.5% (22) of the women had a strength of grade 1 (very weak pressure), grade 2 (weak pressure), grade 3 (moderate pressure), grade 4 (good pressure), and grade 5 (strong pressure), respectively.

Comparison of Perineometer and MOS Values According to the Sociodemographic Characteristics of the Women

A statistically significant difference was found between the women’s age, educational status, marital status, employment status, income status, persistent cough, use of nicotine, alcohol and caffeine consumptions, chronic constipation, history of frequent urinary tract infections, regular exercise, and body mass index (BMI); the PFMS values measured with a perineometer (p < .05) and MOS (p < .05; Table 1).

Table 1.

Comparison of the Perineometer and MOS Values According to the Sociodemographic Characteristics of Women (n = 258).

Variables	n	%	Perineometer		MOS
Age group (years)
18–29	84	32.6	37.63 ± 10.7	F = 37.541	3.4 ± 1.0	F = 41.500
30–38	81	31.4	33.83 ± 11.2	p < .001	2.92 ± 1.2	p < .001
39–49	93	36.0	24.11 ± 10.2	Cohen’s d = .927 (large)	1.92 ± 1.0	Cohen’s d = .945 (large)
Educational status
Primary school	84	32.6	25.63 ± 9.8	F = 12.908	2.15 ± 0.9	F = 11.425
Secondary school	16	6.2	28.81 ± 15.3	p < .001	2.31 ± 1.2	p < .001
High school	86	33.3	34.18 ± 10.4	Cohen’s d = .932 (large)	2.97 ± 1.1	Cohen’s d = .918 (large)
University or higher	72	27.9	35.6 ± 12.7	Cohen’s d = .932 (large)	3.13 ± 1.3	Cohen’s d = .918 (large)
Marital status
Married	234	90.7	31.61 ± 12.2	F = 4.205	2.72 ± 1.2	F = 4.127
Single	13	5.0	37.61 ± 10.2	p = .016	3.38 ± 1.1	p = .017
Divorced or widowed	11	4.3	23.36 ± 8.5	Cohen’s d = .819 (large)	1.90 ± 0.9	Cohen’s d = .813 (large)
Employment status
Employed	77	29.8	34.75 ± 12.1	t = 2.775	3.10 ± 1.3	t = 3.219
Employed	77	29.8	34.75 ± 12.1	p = .006	3.10 ± 1.3	p < .001
Unemployed	181	70.2	30.21 ± 11.9	Cohen’s d = .931 (large)	2.55 ± 1.2	Cohen’s d = .976 (large)
Income status
Income less than expenditure	41	8.6	27.00 ± 9.4	F = 7.820	2.19 ± 1.0	F = 10.636
Income equal to expenditure	190	58.1	31.55 ± 12.6	p < .001	2.71 ± 1.2	p < .001
Income more than expenditure	27	33.3	38.62 ± 9.03	Cohen’s d = .877 (large)	3.59 ± 1.0	Cohen’s d = .869 (large)
Persistent cough
Yes	37	14.3	21.94 ± 8.6	t = −5.480	1.72 ± 0.8	t = −5.408
Yes	37	14.3	21.94 ± 8.6	p < .001	1.72 ± 0.8	p < .001
No	221	85.7	33.18 ± 11.9	Cohen’s d = .963 (large)	2.88 ± 1.2	Cohen’s d = 973 (large)
Nicotine use (smoking)
Yes	42	16.3	24.14 ± 10.8	t = −4.477	1.92 ± 0.9	t = −4.592
Yes	42	16.3	24.14 ± 10.8	p < .001	1.92 ± 0.9	p < .001
No	216	83.7	33.01 ± 11.9	Cohen’s d = .977 (large)	2.87 ± 1.2	Cohen’s d = .893 (large)
Alcohol use
Yes	16	6.2	24.56 ± 9.0	t = −2.399	2.06 ± 0.9	t = −2.158
Yes	16	6.2	24.56 ± 9.0	p = .017	2.06 ± 0.9	p = .032
No	242	93.8	32.03 ± 12.2	Cohen’s d = .695 (medium)	2.76 ± 1.2	Cohen’s d = .613 (medium)
Caffeine use
Yes	120	46.5	27.17 ± 11.5	t = −5.731	2.25 ± 1.1	t = −5.796
Yes	120	46.5	27.17 ± 11.5	p < .001	2.25 ± 1.1	p < .001
No	138	53.5	35.39 ± 11.3	Cohen’s d = .914 (large)	3.12 ± 1.2	Cohen’s d = .924 (large)
Constipation
Yes	76	29.5	25.53 ± 10.9	t = −5.416	2.14 ± 1.0	t = −4.921
Yes	76	29.5	25.53 ± 10.9	p < .001	2.14 ± 1.0	p < .001
No	182	70.5	34.08 ± 11.7	Cohen’s d = .950 (large)	2.96 ± 1.2	Cohen’s d = .969 (large)
History of urinary tract infection
Yes	50	19.4	25.78 ± 7.0	t = −3.704	2.19 ± 0.6	t = −3.163
Yes	50	19.4	25.78 ± 7.0	p < .001	2.19 ± 0.6	p = .002
No	208	80.6	31.77 ± 13.4	Cohen’s d = .956 (large)	2.74 ± 1.3	Cohen’s d = .970 (large)
Regular sporting activity
Yes	86	33.3	37.06 ± 12.0	t = 5.405	3.25 ± 1.2	t = 5.006
Yes	86	33.3	37.06 ± 12.0	p < .001	3.25 ± 1.2	p < .001
No	172	66.7	28.81 ± 11.2	Cohen’s d = .905 (large)	2.45 ± 1.1	Cohen’s d = .952 (large)
BMI
Underweight	7	2.7	37.71 ± 6.1	F = 28.329	3.28 ± 0.4	F = 32.574
Underweight	7	2.7	37.71 ± 6.1	p < .001	3.28 ± 0.4	p < .001
Normal weight	143	55.4	36.64 ± 11.2	Cohen’s d = .905 (large)	3.28 ± 1.1	Cohen’s d = .927 (large)
Overweight	60	23.3	25.46 ± 11.0		1.98 ± 1.0
Obese	48	18.6	23.18 ± 7.9		1.87 ± 0.7

Comparison of the Perineometer and MOS Values According to the Obstetric and Gynecological Features of the Women

Statistically significant differences were found between the women’s history of pregnancy, mode of delivery, use of episiotomy at birth, perineal rupture at birth, use of forceps vacuum at birth, multiple pregnancies, delivery of a baby of ≥4,000 g, treatment for pregnancy, hysterectomy, menopause, frequency of sexual intercourse, feeling of pain during sexual intercourse, and the PFMS values measured with a perineometer (p < .05) and MOS (p < .05; Table 2).

Table 2.

Comparison of the Perineometer and MOS Values According to the Obstetric and Gynecological Features of Women.

Variable	n	%	Perineometer		MOS
Previous pregnancy
Yes	202	78.3	29.98 ± 12.2	t = −4.103	2.55 ± 1.2	t = −3.994
Yes	202	78.3	29.98 ± 12.2	p < .001	2.55 ± 1.2	p < .001
No	56	21.7	37.30 ± 10.2	Cohen’s d = .950 (large)	3.30 ± 1.1	Cohen’s d = .925 (large)
Mode of delivery
Cesarean	72	27.9	35.09 ± 12.1	F = 14.569	3.07 ± 1.3	F = 14.170
Cesarean	72	27.9	35.09 ± 12.1	p < .001	3.07 ± 1.3	p < .001
Vaginal	102	39.5	27.03 ± 11.3	Cohen’s d = .933 (large)	2.28 ± 1.1	Cohen’s d = .930 (large)
Both cesarean and vaginal	18	7.0	27.22 ± 11.7	Cohen’s d = .933 (large)	2.33 ± 1.0	Cohen’s d = .930 (large)
Episiotomy during labor
Yes	109	42.2	27.05 ± 11.5	t = −4.753	2.30 ± 1.1	t = −4.603
Yes	109	42.2	27.05 ± 11.5	p < .001	2.30 ± 1.1	p < .001
No	83	32.2	34.05 ± 12.2	Cohen’s d = .888 (large)	2.96 ± 1.2	Cohen’s d = .865 (large)
Perineal rupture during labor
Yes	79	30.6	24.43 ± 10.7	t = −6.309	2.04 ± 1.1	t = −6.272
Yes	79	30.6	24.43 ± 10.7	p < .001	2.04 ± 1.1	p < .001
No	113	43.8	33.76 ± 11.9	Cohen’s d = .929 (large)	2.94 ± 1.2	Cohen’s d = .938 (large)
Forceps vacuum use during labor
Yes	20	7.8	19.25 ± 5.7	t = −4.324	1.50 ± 0.5	t = −4.575
Yes	20	7.8	19.25 ± 5.7	p < .001	1.50 ± 0.5	p < .001
No	172	66.7	30.98 ± 12.3	Cohen’s d = .962 (large)	2.67 ± 1.2	Cohen’s d = .923 (large)
Baby of ≥4,000 g
Yes	25	9.7	20.76 ± 5.6	t = −3.721	1.58 ± 0.6	t = −4.072
Yes	25	9.7	20.76 ± 5.6	p < .001	1.58 ± 0.6	p < .001
No	167	64.7	31.20 ± 12.4	Cohen’s d = .903 (large)	2.70 ± 1.2	Cohen’s d = .967 (large)
Fertility treatment received
Yes	37	14.3	30.10 ± 12.7	t = −1.759	2.57 ± 0.7	t = −2.499
Yes	37	14.3	30.10 ± 12.7	p = .080	2.57 ± 0.7	p = .056
No	221	85.7	30.78 ± 6.2	Cohen’s d = .331 (medium)	2.59 ± 1.2	Cohen’s d = .461 (medium)
Hysterectomy
Yes	8	3.1	17.33 ± 6.8	t = −2.429	1.33 ± 0.5	t = −2.507
Yes	8	3.1	17.33 ± 6.8	p = .013	1.33 ± 0.5	p = .016
No	250	96.9	30.39 ± 12.3	Cohen’s d = .841 (large)	2.61 ± 1.2	Cohen’s d = .849 (large)
Having experienced menopause
Yes	48	18.6	22.14 ± 6.4	t = −6.403	1.77 ± 0.6	t = −6.459
Yes	48	18.6	22.14 ± 6.4	p < .001	1.77 ± 0.6	p < .001
No	210	81.4	32.22 ± 12.6	Cohen’s d = .910 (large)	2.80 ± 1.2	Cohen’s d = .946 (large)
Being sexually active
Yes	228	88.4	30.12 ± 12.3	t = −.046	2.59 ± 1.2	t = −.098
Yes	228	88.4	30.12 ± 12.3	p = .963	2.59 ± 1.2	p = .924
No	30	11.6	27.50 ± 11.3	Cohen’s d = .198 (medium)	2.25 ± 1.3	Cohen’s d = .178 (medium)
Feeling pain during sexual intercourse
Yes	70	27.1	31.75 ± 12.4	t = −3.492	2.75 ± 1.3	t = −3.501
Yes	70	27.1	31.75 ± 12.4	p < .001	2.75 ± 1.3	p < .001
No	157	60.9	27.13 ± 11.6	Cohen’s d = .810 (large)	2.28 ± 1.0	Cohen’s d = .855 (large)

Correlation of the Perineometer and MOS Values with the Variables

Statistically significant negative moderate correlations were found between the women’s PFMS values measured with a perineometer (p < .001) and the MOS (p < .001) and age, number of years married, number of pregnancies, number of vaginal births, number of living children, and BMI. A statistically significant negative weak correlation was found between the women’s PFMS values and the number of curettages. A statistically significant positive weak correlation was found between the women’s PFMS values and the number of cesarean sections (Table 3).

Table 3.

Relationship of Perineometer and MOS Values to Some Variables.

Variable	Mean ± SD	Participants (range values)	Perineometer (r p)	MOS (r p)
Age	34.92 ± 9.20	19–49	−.485 < .001	−.506 < .001
Years of marriage	10.88 ± 9.70	1–38	−.387 < .001	−.403 < .001
Age at menarche	12.28 ± 1.03	10–15	−.115 .065	−.116 .062
Number of pregnancies	2.12 ± 1.15	0–6	−.479 < .001	−.464 < .001
Number of living children	1.73 ± 0.97	0–4	−.443 < .001	−.432 < .001
Number of abortions	0.10 ± 0.34	0–2	−.052 .459	−.052 .464
Number of curettages	0.26 ± 0.54	0–2	−.190 .007	−.178 .011
Number of cesarean sections	0.61 ± 0.77	0–3	.180 .012	.181 .012
Number of vaginal births	1.24 ± 1.21	0–4	−.460 < .001	−.469 < .001
Year of menopause	5.50 ± 4.09	1–15	.138 .350	.088 .550
BMI	24.96 ± 5.09	16.80–38.10	−.527 < .001	−.519 < .001
Perineometer	31.56 ± 12.17	10–55	—	.970 < .001
MOS	3.12 ± 1.26	1–5	.970 < .001	—

A measurement of 1 (very weak) on the MOS was determined to correspond to 10.00 to 19.9 cmH₂O using the perineometer; 2 (weak), to 20.00 to 29.9 cmH₂O using the perineometer; 3 (moderate), to 30.00 to 39.9 cmH₂O using a perineometer; 4 (good), to 40.00 to 54.9 cmH₂O using the perineometer; 5 (strong), to >55.00 cmH₂O using the perineometer (X² = 244.06; p < .001; Table 4).

Table 4.

MOS and Perineometer Classifications.

Classification	MOS	Perineometer values	X ²	p
Very weak	1.00	10.00–19.9	244.06	<.001
Weak	2.00	20.00–29.9
Moderate	3.00	30.00–39.9
Good	4.00	40.00–54.9
Strong	5.00	>55.00

Note. Furthermore, a statistically significant strong correlation was found between the women’s perineometer and MOS values (r = .970, p < .001; Table 3).

Regression Analysis of the Perineometer and MOS Values with Independent Variables

The perineometer and MOS values and independent variables were examined using a stepwise regression analysis (forward; Table 5).

Table 5.

Stepwise Regression Analysis of Perineometer and MOS Values with Independent Variables.

Model	Variables	Perineometer					MOS
Model	Variables	β	t	p	R/R²	F/p	β	t	p	R/R²	F/p
1	Constant	—	22.15	<.001	R = .472	F = 46.38	—	16.67	<.001	R = .479	F = 48.27
1	Number of pregnancies	−.47	−6.81	<.001	R² = .223	p < .001	−.47	−6.94	<.001	R² = .230	p < .001
2	Constant	—	5.19	<.001	R = .557	F = 36.13	—	4.99	<.001	R = .567	F = 38.14
	Number of pregnancies	−.44	−6.77	<.001	R² = .310	p < .001	−.45	−7.05	<.001	R² = .321	p < .001
	Mode of delivery	.29	4.51	<.001	R² = .310	p < .001	.30	4.66	<.001	R² = .321	p < .001
3	Constant	—	6.78	<.001	R = .612	F = 31.89	—	1.70	.090	R = .615	F = 32.38
	Number of pregnancies	−.44	−7.08	<.001	R² = .374	p < .001	−.44	−7.09	<.001	R² = .378	p < .001
	Mode of delivery	.27	4.37	<.001			.33	5.29	<.001
	Baby of ≥4,000 g	−.25	−4.05	<.001			−.24	−3.80	<.001
4	Constant	—	3.31	<.001	R = .656	F = 30.04	—	3.16	.002	R = .640	F = 27.57
	Number of pregnancies	−.35	−5.62	<.001	R = .656	F = 30.04	−.45	−7.42	<.001	R² = .410	p < .001
	Mode of delivery	.28	4.75	<.001	R² = .430	p < .001	.31	5.02	<.001
	Baby of ≥4,000 g	−.27	−4.62	<.001			−.19	−3.00	.003
	Menopause	.25	3.96	<.001			.18	2.92	.004
5	Constant	—	1.39	.164	R = .675	F = 26.39	—	3.49	<.001	R = .661	F = 24.57
	Number of pregnancies	−.34	−5.51	<.001	R = .675	F = 26.39	−.32	−4.25	<.001	R² = .437	p < .001
	Mode of delivery	.31	5.19	<.001	R² = .455	p < .001	.30	4.92	<.001
	Baby of ≥4,000 g	−.23	−3.83	<.001			−.17	−2.83	.005
	Menopause	.23	3.77	<.001			.18	2.94	.004
	Regular sports	.16	2.67	.008			.15	2.62	.010
6	Constant	—	.81	.415	R = .691	F = 23.88	—	1.08	.282	R = .691	F = 20.31
	Number of pregnancies	−.31	−5.07	<.001	R = .691	F = 23.88	−.23	−2.88	.004	R² = .477	p < .001
	Mode of delivery	.30	5.18	<.001	R² = .477	p < .001	.30	5.07	<.001
	Baby of ≥4,000 g	−.23	−3.80	<.001			−.17	−2.95	.004
	Menopause	.20	3.13	.002			.17	2.91	.004
	Regular sports	.16	2.73	.007			.13	2.31	.022
	Persistent cough	.15	2.57	.011			.14	2.17	.031

Note. t = t test; F = analysis of variance.

The results of the regression analysis showed that the number of pregnancies, mode of delivery, delivery of a child of ≥4,000 g, menopausal status, exercising regularly, and having a persistent cough had significant impacts on the perineometer values.

The results of the regression analysis showed that the number of pregnancies, mode of delivery, delivery of a child of ≥4,000 g, menopause, exercising regularly, and having a persistent cough had significant impacts on the MOS values.

The regression analysis revealed that age, educational status, marital status, employment status, income status, use of nicotine, alcohol drinking, constipation, BMI, history of urinary tract infection, having an episiotomy during labor, perineal rupture at birth, use of forceps vacuum during labor, caffeine consumption, hysterectomy, pain during sexual intercourse, number of years married, number of living children, numbers of curettages, number of cesarean sections, and number of vaginal births had no significant effects on the perineometer and MOS values (p > .05). Therefore, these variables were not included in the stepwise regression analysis.

Discussion

This study was aimed at investigating the PFMS of women of reproductive age and the factors affecting it. Various studies have reported that vaginal palpation, manometry, dynamometry, and electromyography (EMG) are reliable tools for evaluating PFMS in women (Navarro Brazález et al., 2018; Rocha et al., 2018). The Guidelines for Reporting Reliability and Agreement study emphasized that taking a few measurements is more reliable when evaluating PFMS (Navarro Brazález et al., 2018). In the present study, PFMS was evaluated using both a perineometer and the MOS. As a result of the perineometer measurements, the mean PFMS of the women in this study was found to be 31.56 ± 12.17 (moderate) cmH₂O. Similar to our study, Angelo et al. determined that the mean PFMS value of women was 35.1 ± 22.7 cmH₂O (moderate) as a result of perineometer measurements (Angelo et al., 2017). Another study conducted in Turkey reported mean PFMS values of 3.93 ± 2.67 kPa (Demirtürk et al., 2017). Given that a pressure of 12 cmH₂O corresponds to 1.18 kPa (Demirtürk et al., 2017), this result (40 cmH₂O, moderate) is similar to that of the present study. The MOS, another method for evaluating PFMS, uses vaginal palpation. By using the MOS, the mean PFMS of the women in this study was found to be 3.12 ± 1.26. Of the women, 22.1% (57) had a strength of grade 1 (very weak pressure), 23.3% (60) had a strength of grade 2 (weak pressure), 23.6% (61) had a strength of grade 3 (moderate pressure), 22.5% (58) had a strength of grade 4 (good pressure), and 8.5.7% (22) had a strength of grade 5 (strong pressure). Likewise, in the study conducted by Angelo et al. using the MOS in 259 women, 18.5% (48) of the women had a strength of grade 1, 27.7% (72) had a strength of grade 2, 29.7% (77) had a strength of grade 3, 16.2% (42) had a strength of grade 4, and 7.7% (20) had a strength of grade 5 (Angelo et al., 2017). Moreover, in the present study, a statistically significant positive strong correlation was found between the women’s perineometer and MOS measurements. The MOS values increased as the perineometer values increased. Similar to the present study, other studies in the literature have shown a significant strong correlation between PFMS measurements obtained with the MOS and a perineometer (Angelo et al., 2017; Chevalier et al., 2014; Da Roza et al., 2013; Volløyhaug et al., 2016). These data show that a perineometer and the MOS can be used together for PFMS evaluation and that their results are consistent with each other. The MOS, which uses only vaginal palpation, can be used in clinical practice to save time and reduce cost.

Some sociodemographic characteristics may have an effect on an individual’s PFMS, one of which is age. Studies have reported that aging is a risk factor of incontinence and genital organ prolapses due to PFM weakness and that PFMS decreases with increasing age (Demirtürk et al., 2017; Li et al., 2015; Ozdemir et al., 2015). Likewise, in the present study, the PFMS values measured with both a perineometer and the MOS were found to decrease as the women’s age increased. In addition, some studies have shown significant relationships between educational status and pelvic floor disorders (Batista et al., 2011; Braekken et al., 2014; Nygaard et al., 2008; Ozdemir et al., 2015). Similarly, in the present study, the PFMS values measured with both a perineometer and the MOS were found to increase as the educational level of the women increased. This result suggests that education increases women’s awareness about PFMS. Again, in the present study, those who were not employed had lower PFMS values with both a perineometer and the MOS, and the PFMS values measured using both a perineometer and the MOS were found to decrease as the income level of women decreased. Similarly, a study conducted in Turkey with women aged 20 to 50 years found that women who were not employed and had low income levels had less PFMS (Ciledag Ozdemir & Pehlivan, 2015).

The PFMs are extremely important for continence and act as a powerful pelvic stabilizer (Jürgensen et al., 2017). They can also be consciously targeted during exercise. Sapsford and Hodges showed that voluntary abdominal muscle contraction during exercise, especially of the transversus abdominis, results in increased PFM activity in healthy subjects with no history of lower back pain (Sapsford & Hodges, 2001). Jürgensen et al. (2017) found that in healthy women, aerobic capacity and PFM function are strongly associated. Da Roza et al. (2013) evaluated PFMS with a perineometer and the MOS in sports students who had never given birth and found that the mean perineometer value of the students was 70.4 cmH₂O and that the MOS values of 84% of the students were good and strong. In the present study, similar to the literature, those who exercised regularly were found to have higher PFMS values measured with both a perineometer and the MOS.

Multichannel urodynamic studies have demonstrated a positive correlation between BMI and intra-abdominal pressure. Increased intra-abdominal pressure in obese individuals causes a chronic load on the PFMs, and obesity and increased BMI lead to an increase in the risk of pelvic floor disorders (Ramalingam & Monga, 2015). The decreased prevalence of UI due to weight loss after bariatric surgery, especially in obese patients with a high BMI, indicated a correlation between BMI and PFMS (Bodner-Adler et al., 2019; Leshem et al., 2018; Wesnes & Lose, 2013). Likewise, in the present study, the PFMS values measured with both a perineometer and the MOS were found to decrease as the BMI of the women increased. Having a persistent cough and chronic constipation are also among the factors that disrupt pelvic support structures and lead to increases in abdominal pressure and incontinence (Demirtürk et al., 2017; Hwang et al., 2019). In the present study, women with a persistent cough and chronic constipation had lower PFMS values measured with both a perineometer and the MOS.

According to the literature, parity, birth, episiotomy, giving birth to a large baby, instrumental birth, and prolonged labor are risk factors that affect PFMS (Leroy et al., 2016; Sangsawang & Sangsawang, 2013; Wesnes & Lose, 2013). Weak PFMs and decreased pelvic organ support are known effects of pregnancy (Rahmani & Mohseni-Bandpei, 2011; Staer-Jensen et al., 2015). Mechanically, the pelvic floor is under prolonged and continuous pressure due to the enlargement of the uterus, especially in the third trimester of pregnancy. Increased intra-abdominal pressure results in downward compression and tension in the PFMs, and the change in the gravitational axis affects the integrity of the pelvic floor (Li et al., 2015). Moreover, increased levels of hormones such as estrogen, progesterone and relaxin cause muscle relaxation and hypotonicity of smooth muscles, possibly leading to PFM dysfunction (Hwang et al., 2019; Ozdemir et al., 2015). Similarly, in the present study, those who had experienced pregnancy had lower PFMS values measured with both a perineometer and the MOS. The PFMS values of the women decreased as the numbers of pregnancies, living children, and curettages increased. Likewise, Salian and Ved (2018) found that the mean PFMS was 31.58 mmHg in nulliparous women, 31.25 mmHg in primiparous women, and 26.28 mmHg in multiparous women (Salian & Ved, 2018). Marshall et al. (2002) evaluated the muscle strength of 10 women who had not given birth and 10 women who had had one vaginal delivery (in the ninth to tenth postnatal month) with digital, EMG, and perineometer measurements. They determined that the muscle strength of the women who had given birth was significantly less than that of the women who had never given birth (Marshall et al., 2002). Furthermore, in the present study, we found that those who were married had lower PFMS values measured with both a perineometer and the MOS. Owing to the traditional patriarchal social structure of Turkey; individuals generally have children only after marriage. This finding was thus expected given the effects of pregnancy and labor on PFMS.

Previous studies reported that vaginal delivery increases the risk of PFM dysfunction as compared with cesarean delivery (Batista et al., 2011; Baytur et al., 2005; Bo et al., 2018; Braekken et al., 2014; Friedman et al., 2012; Howard & Makhlouf, 2016; Skinner & Dietz, 2015). Magnetic resonance imaging shows the areas of dysfunction in the striated muscles of the pelvic floor in those who have had a vaginal delivery. The results of histological examination of human cadavers indicate myogenic damage in fiber density in the levator ani muscle (Howard & Makhlouf, 2016). The present study determined that those who had had a vaginal delivery had lower PFMS values measured with both a perineometer and the MOS. We also found that the PFMS values decreased as the number of vaginal deliveries increased. Solans-Domènech et al. (2010) demonstrated that the presence of perineal rupture or episiotomy are the main factors that affect UI, although vaginal delivery seems also to be an important factor that affects PFMS (Solans-Domènech et al., 2010). Furthermore, Handa et al. (2012) and Bø et al. (2016) found that the spontaneous ruptures that occur during delivery and the use of forceps during delivery are associated with pelvic floor disorders (Bø et al., 2016; Handa et al., 2012). Similar to the literature, the present study found that those who had undergone an episiotomy or deliveries using a vacuum or forceps and had a perineal rupture had lower PFMS values measured with both a perineometer and the MOS. Considering the risks of cesarean section it is not recommended that women undergo cesarean section for prevention of only pelvic relaxation (Afshari et al., 2017). However, this result shows that the interventions used during a vaginal delivery have marked effects on PFMS and that these effects should not be ignored.

As the baby’s birth weight increases, the possibility of PFDs also increases (Baracho et al., 2012; Torrisi et al., 2012). Previous studies reported that the weight of the fetus in the mother’s womb is an independent risk factor of incontinence and POP (Diez-Itza et al., 2009; Martins et al., 2011). Another study reported that the risk of UI in the third postpartum month was 1.41 times higher in those who had a baby with a birth weight >3,800 g (Torrisi et al., 2012). The present study determined that those who had given birth to a baby weighing ≥4,000 g and had experienced multiple pregnancies had lower PFMS values measured with both a perineometer and the MOS.

The accelerated aging process after menopause decreases the capacity of tissues to repair, causing degeneration in the elastic connective tissue. The decreased estrogen level causes postmenopausal changes in the structures supporting the pelvic organs (especially in the PFMs and urethral structures) by affecting the connective tissue (Abdel-Fattah et al., 2004). The present study found that those who had entered menopause had lower PFMS values measured with both a perineometer and the MOS. Having a hysterectomy has been reported to affect pelvic floor innervation and fibromuscular structures, and abdominal hysterectomy causes minimal damage to the pelvic plexus (Abdel-Fattah et al., 2004). The present study found that women who had undergone a hysterectomy had lower PFMS values measured with both a perineometer and the MOS.

Conclusion and Recommendations

This study was conducted with women who had no pelvic floor-related complaints. The first conclusion of this study is that women living in our country have a moderate PFMS. Another result of the study was the significant and strong correlation between the evaluation using the MOS score measured with vaginal palpation and the perineometer measurements. This shows that the PFMS measurements obtained with the MOS overlap extensively with the results obtained using a perineometer.

In this study, we found that a number of sociodemographic variables (age groups, educational status, marital status, employment status, income status), healthy lifestyle behaviors and practices (use of nicotine, alcohol and coffee consumptions, chronic constipation, history of frequent urinary tract infections, regular exercise, body mass index), obstetric variables (history of pregnancy, mode of delivery, use of episiotomy at birth, perineal rupture at birth, use of forceps vacuum at birth, multiple pregnancies, delivery of a baby weighing ≥4,000 g, treatment during pregnancy) and gynecological variables (hysterectomy, menopause, frequency of sexual intercourse, and pain during sexual intercourse) constitute the risk factors of PFMS. While some of these risk factors aren’t preventable, it is noteworthy that most of them are preventable risk factors, so both healthcare professionals and all women should take care of necessary precaution and protection behavior throughout their lives. For example, our result found out that multiparous women who gave vaginal delivery had lower PFMS than those who had cesarean section. To protect the health of the pelvic floor, healthcare professionals should avoid unnecessary interventions during childbirth and pay attention to women’s urogenital symptoms during pregnancy and the postpartum period.

It should be kept in mind that factors other than muscle strength may also play a role in the etiology of incontinence, but as an one of the determinant factor, it should be protected with some lifestyle adjustments and followed regularly by professionals. For this purpose, health professionals should evaluate PFMS with the MOS as part of their routine gynecological evaluations for all women, even if they do have access to a perineometer. Rather than intervening when symptoms begin to have a significant effect, the goal should be to prevent or minimize any problems by encouraging all women to do regular pelvic floor exercises to look after the health of their pelvic floor. Women should be advised on PFM exercises by health professionals; women should also be informed about the benefits of physical activity and maintaining a healthy and balanced diet, as BMI and physical activity are considered major factors that affect PFMS.

Research Limitations

Only women who agreed to participate in the study were included in the study; this was fewer than the number targeted in the research. Moreover, a large number of patients were not included as a result of the exclusion criteria; therefore, the sample size was smaller than expected. We recommend further analyses with larger sample groups to examine the effects of the parameters discussed above.

Footnotes

Acknowledgements

We are grateful to Ege University Planning and Monitoring Coordination of Organizational Development and Directorate of Library and Documantaion for their support in editing and proofreading service of this study.

Author Contributions

Concept; SG, OK, RÖ Design; SG, OK, RÖ, Materials; SG, RÖ, IH & AOY, Statistics; SG, Writer; SG, RÖ, Critical revisions for important intellectual content: SG, OK, RÖ. This manuscript has not been published elsewhere and that it has not been submitted simultaneously for publication elsewhere. The authors also declare that they have no competing interests.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was funded by Ege University Scientific Research Project ID. 794. Written permission was obtained from the Medical Research Ethics Committee of Ege University, where the study was conducted. (Ethics Committee Approval No:17-3/2).

ORCID iD

Süreyya Gümüşsoy

Author Biographies

Süreyya Gümüşsoy: Assistant professor, Ege University Atatürk Health Care Vocational School.

Ruşen Öztürk: Research Assistant, Ege University Nursing Faculty, Department of Women’s Health and Diseases.

Oya Kavlak: Professor, Ege University Faculty of Nursing Department of Women’s Health and Diseases.

İsmet Hortu: Ege University Faculty of Medicine, Gynecology and Faculty Member of the Division of Birth.

Ahmet Özgür Yeniel: Associate Professor, Ege University Faculty of Medicine, Department of Obstetrics and Gynecology.

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