Walking, SD and urinary tract symptoms with BPH: A cross-sectional, retrospective and follow-up chain design study

doi:10.21203/rs.3.rs-1950833/v1

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Walking, SD and urinary tract symptoms with BPH: A cross-sectional, retrospective and follow-up chain design study

https://doi.org/10.21203/rs.3.rs-1950833/v1

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BACKGROUND: Lower urinary tract symptoms (LUTSs) are the most common problem in older men with benign prostatic hyperplasia (BPH). Physical activity and sedentariness may be important LUTS risk factors and suitable targets for intervention. However, what is the most effective way to engage in physical activity? There is still no consensus among academics.

OBJECTIVE: To observe which of the two different physical activity modalities, square dancing (SD) or walking, is more effective in delaying the effects of LUTSs/BPH in older men and to provide a basis for promoting active participation in appropriate physical activity for BPH patients.

DESIGN: This study was a chain design study with cross-sectional (June 2018), retrospective (from June 2014 to June 2018) and follow-up (June 2018 to June 2020) components for LUTSs.

PARTICIPANTS: Men aged 60 and over who could perform physical activity alone and lived in the same community.

MAIN MEASURES: The effect of different forms of physical activity on the alleviation of LUTSs in BPH patients was observed retrospectively; the main physical activity patterns of older adults in the town were walking and SD. Therefore, the two physical activity modalities of walking and SD were used as the main study factors, and the propensity score 1:1 matching method was applied to control for confounding factors in the retrospective cohort, which was divided into walking and SD groups to compare the clinical progression of LUTSs in the two groups. The time between study entry into the cohort and LUTS progression (appearance or exacerbation of symptoms) was used as the outcome to determine whether LUTS progression occurred in the two groups. The Cox proportional hazards model was applied to analyze the effect of walking and SD on the delay in the clinical progression of LUTSs/BPH in older men.

KEY RESULT: Multifactorial Cox regression analysis showed that patients in the square dancing group had a 0.41-fold lower risk of LUTSs than those in the walking group (HR=0.41, 95% CI: 0.19-0.88, p=0.02).

CONCLUSIONS: SD can more effectively delay the clinical progression of LUTSs in BPH patients, and the results of this study provide a good reference for the selection of self-guided physical activity intervention modalities for BPH patients.

walking and SD

LUTSs/BPH

men

A higher prevalence of moderate or severe LUTSs/BPH has been reported among older men in most parts of the world, and they seriously affect the quality of life of patients, as serious complications can endanger life ^[1–3]. There are also studies that show that LUTSs/BPH are frequently associated with physical and psychological problems, mental illness, neurological disorders and erectile dysfunction ^{[4, 5]}. Therefore, it is very important to effectively control the occurrence and progression of LUTSs.

Currently, nondrug therapy for BPH/LUTS patients has become increasingly popular due to the uncertainty of drug or surgical efficacy and possible side effects. Among them, physical activity intervention is a nondrug treatment measure, and it has long been reported in the literature that physical activity maintains a healthy BMI, thereby reducing the risk of LUTSs ^{[6, 7]}. However, previous studies have found that not all physical activity exercises were effective for LUTSs. Perhaps the type, duration, and intensity of, and even the emotions during physical activity are related. What physical activity will be the most effective? This is the question that is explored in this study.

Study Design and Population

This cross-sectional survey was conducted in Green Town in the Gelin, Hubin, and Xuewei communities of Daqing city, Heilongjiang Province in 2018 and enrolled older men aged 60–78 years. Participants were selected according to the inclusion and exclusion criteria. The inclusion criteria were as follows: (i) those who had lived in the town for ≥ 2 years, were male, ≥ 60 years old, and visited the town square at least 3 times a week for physical activity or recreation; (ii) patients with a diagnosis of BPH in a hospital; (iii) those with normal communication skills; and (iv) those who gave informed consent to participate in this research study. The exclusion criteria were as follows: those with other chronic diseases that cause LUTSs; and patients taking long-term medications that can cause LUTSs. We collected and collated the previous physical examination data of male residents in Gelin Community, Hubin Community and Xuewei Community from June 2014 to June 2018 who underwent regular physical examinations in Daqing Aixin Hospital, Heilongjiang Province, China.

Physical examination data were collected retrospectively, including general demographic information, history of present and past disease, related biochemical indicators, ultrasound results, and long-term physical activity patterns of BPH patients who had lived in the town from 2014 to June 2018. We performed 1:1 propensity score matching (PSM) for retrospective data of the participants.

Finally, follow-up and monitoring were carried out to match the included individuals by 1:1 PSM from June 2019 to June 2021.

A total of 318 individuals who regularly participated in various sports or recreational activities in the community square (116 from Gelin Community, 99 from Hubin Community and 103 from Xuewei Community) with BPH and LUTSs were diagnosed through the International Prostate Symptom Score (IPSS). A total of 126 were excluded from the study because they failed to meet the inclusion criteria (n = 102) or were reluctant to participate in the study (n = 24). A total of 192 were eligible for inclusion. Then, by PSM for 1:1, 30 men were placed into the walking group, and 30 men were placed into the SD group. At the last follow-up (24 months), 23 from the SD group and 21 from the walking group were left. The recruitment of participants for the follow-up and the details of dropouts are illustrated in Fig. 1.

A previous cross-sectional survey showed that more than 90% of older adults engaged in SD and walking, two popular activities. The follow-up lasted 24 months with appropriately matched participants by our research team; three researchers on the research team were square dancers, and two were walkers. This participatory observation contributed to the quality of our study. The evaluation of LUTSs was conducted separately at the first, 6th, 12th, 18th and 24th months to determine the effect of SD and walking on BPH/LUTSs. Participants who exercised consistently at least three days a week for at least 30 minutes each time were eligible for follow-up.

Assessment of LUTS/BPH Incidence and Progression

A new visual prostate symptom score (VPSS)^[8], designed by Chris in 2011, was used to assess LUTS/BPH incidence and progression. The VPSS correlates significantly with the IPSS, and it is more useful than the IPSS for older patients who are illiterate or have limited education. VPSS pictograms allow the patient to indicate his urinary frequency during the day (question 1) and night (question 2), his assessment of the force of his urinary stream (question 3), and his feelings about his bladder symptoms (quality of life question). The degree score is the same as in the IPSS: 0–7 indicate mild symptoms, that is, the incidence of LUTSs/BPH. 8–19 indicate moderate symptoms, and 20–35 indicate severe symptoms, that is, the progression of LUTSs/BPH.

Statistical Analysis

For descriptive statistics such as baseline characteristics, categorical data are expressed as numbers and percentages, and continuous data are expressed as means and standard deviations. In comparative analyses, categorical variables were compared for participants with or without deterioration of LUTSs using chi-square or Spearman’s tests, and continuous variables were compared using Student’s t or Mann‒Whitney U tests. All lifestyle variables were categorized using reference levels obtained from previous studies. Longitudinal analyses were conducted with paired t or Wilcoxon signed rank tests and repeated analysis of variance using baseline lifestyle factors and the outcome of LUTS deterioration between baseline and follow-up. Logistic regression was used to calculate the age-adjusted odds ratio (OR) and 95% confidence interval (CI) for the deterioration of LUTSs in the longitudinal analysis. Separate analyses were conducted for the voiding and storage symptom subtypes of LUTSs. In addition, each individual LUTS item was analyzed. Multivariable models were derived by including all variables associated with the outcome (P < 0.20) in an age-adjusted model and retained potential confounders according to the investigator. A two-sided P ≤ 0.05 was considered statistically significant. All statistical analyses were performed using IBM SPSS Statistics ver. 22.0 (IBM Co., Armonk, NY, USA).

The baseline level between the SD and walking groups

The comparison of baseline levels of general demographic characteristics, chronic diseases and clinical physiological indicators between the two groups of older men before the cohort follow-up showed that there were significant differences (P<0.05) for each variable except for the alcohol intake variable, which was not significantly different between the two groups (P>0.05). The comparison of post-baseline levels between the SD and walking groups (before PSM) is shown in Table 1.

Table 1

The baseline level comparison between the SD and walking groups (before PSM)

Variables/Groups		Mean	Std. Deviation	T/T´	P
Age Walking SD		63.52	3.07	-2.36*	0.02
		62.41	2.08
LDL-C Walking SD		2.70	0.49	-1.14	0.26
		2.65	0.42
HDL-C Walking SD		1.25	0.20	5.62*	0.00
		1.68	0.55
TGs Walking SD		1.29	0.56	-1.67*	0.101
		1.35	0.49
TC Walking SD		4.87	0.61	-0.96	0.340
		4.88	0.54
Variables Yes/no		Walking	SD	X²	P
Smoking	Yes	73（62.39%）	44（37.61%）	19.98^a	0.00
	No	22（29.33%）	53（70.67%）
Alcohol intake	Yes	60(48.78%)	63(51.22%)	0.07^a	0.80
	No	35(50.72%)	34(49.28%)
BMI	Low	55（57.89%）	40（42.11%）	5.444^a	0.07
	Normal	28（42.42%）	38（57.58%）
	High	12（38.71%）	19（61.29%）	5.444^a 0.04	0.06 0.84
Medicine	Yes	63（50.00%）	63（50.00%）
	No	32（48.48%）	34（51.52%）
Other chronic disease	Yes	92（51.69%）	86（48.31%）	4.75^a	0.03
	No	3（21.43%）	11（78.57%）
Hypertension	Yes	71（55.47%）	57（44.53%）	5.511^a\	.019
	No	24（37.50%）	40（62.50%）
Diabetes	Yes	81（57.86%）	59（42.14%）	14.52^a	0.00
	No	14（26.92%）	38（73.08%）

*Equal variances not assumed, T´

a. A total of 0 cells (0.0%) had an expected count less than 5. The minimum expected count was 43.05.

1:1 PSM between the two groups

By PSM between the two groups, the matching statistics in Table 2 show that there are 0 exact matches and 30 fuzzy matches, with a total of 30 successful matches.

Table 2

Two-group matching statistics

Match Type	Count
Exact Matches	0
Fuzzy Matches	30
Unmatched Including Missing Keys	30
Unmatched with Valid Keys	67
Sampling	without replacement
Log file	none
Maximized Matching Performance	yes

Table 2 shows that there are 0 exact matches and 30 fuzzy matches, with a total of 30 successful matches.

Match tolerances are shown in Table 3. The main matching process included exact matching with exact PS, with the number of matches at 6473 and no successful matching; based on exact matching under PS fuzzy matching (PS ± 0.02, the caliper value set in advance was 0.02), the number of matches was 6473, with 33.33% successful matching. There were no significant differences in any of the variables for the two groups (P>0.05) after PSM, as shown in Table 4.

Table 3

Two-group match tolerances

Match Variables	Value	Fuzzy Match Tries	Incremental Rejection Percentage
Exact (All Variables)	--	6473.00	100.00
PS	.020	6473.00	99.54

Tries is the number of matches.

Table 4

The baseline level comparison between the SD and walking groups (after PSM)

Variables/Groups		Mean	Std. Deviation	T	P
Age	Walking	61.97	3.69	-0.77	0.44
	SD	62.57	2.13
LDL-C	Walking	2.65	0.44	-0.459	0.65
	SD	2.70	0.41
HDL-C	Walking	1.34	0.19	-0.24	0.81
	SD	1.36	0.16
TGs	Walking	1.31	0.48	0.19	0.85
	SD	1.28	0.48
TC	Walking	4.71	0.73	-0.71	0.
	SD	4.82	0.54
Variables/Groups		Walking	SD	X²	P
Smoking	Yes	18（62.39%）	19（37.61%）	0.07^a	0.79
	No	12（29.33%）	11（70.67%）
Alcohol intake	Yes	16(48.78%)	18(51.22%)	0.27^a	0.60
	No	14(50.72%)	12(49.28%)
	High	12（38.71%）	19（61.29%）	0.00^a	1.00
Medicine	Yes	19（50.00%）	19（50.00%）
	No	11（48.48%）	11（51.52%）
Other chronic disease	Yes	29（51.69%）	29（48.31%）	0.00^a	1.00
	No	1（21.43%）	1（78.57%）
BPH	Yes	71（55.04%）	58（44.96%）	4.86^a	0.03
	No	24（38.10%）	39（61.90%）
Hypertension	Yes	10（55.47%）	12（44.53%）	0.29^a	.592
	No	18（37.50%）	12（62.50%）
Diabetes	Yes	21（57.86%）	20（42.14%）	0.77^a	0.78
	No	9（26.92%）	10（73.08%）

a. A total of 0 cells (0.0%) had an expected count less than 5.

Cox survival analysis: Effect of SD and walking on LUTS outcomes

Cox survival analysis showed that the score statistic was 5.591, p=0.018, with a likelihood ratio test X²=5.612, p=0.018. At least one independent variable in the model did not have an HR value of 1. The overall test of the model is statistically significant in Table 5. The survival functions between SD and non-SD (Fig. 2) showed that the final screened model containing only group variables is given in the equation, and physical activity can be an independent influence in relieving LUTSs in patients with BPH (p=0.02). In addition, older men who participated in physical activity effectively reduced the risk of LUTSs 0.41 times more than men who participated in walking (β=0.41; 95% CI for HR= 0.19 to 0.88).

Table 5

Omnibus Test Model Coefficients ^b

Step	-2 Log Likelihood	Overall (score)			Change From Previous Step
Step	-2 Log Likelihood	Chi-square	df	Sig.	Chi-square	df	Sig.
1^a	206.032	5.591	1	.018	5.612	1	.018

a. Variable(s) entered at step number 1: group

b. Beginning block number 1. Method = Forward Stepwise (Likelihood Ratio)

Square dancing and walking as physical activities have attracted much attention in recent years, especially among older adults in China ^[9], due to their simplicity, low cost, and entertaining and social nature ^[10]. With the popularity of all kinds of physical activity, many researchers have carried out systematic and in-depth studies on the relationship between physical activity and health and disease. At present, research on diseases is mostly conducted in the field of geriatric cognition, anxiety, depression and other psychological problems and mental diseases ^[11–14]. However, the results of studies on the relationship between LUTSs and physical activity only point to a role of physical activity in delaying LUTSs. There are no in-depth studies on the form, frequency, and duration of physical activity.

However, SD has become increasingly popular in China over the past few years, especially among older adults. This activity allows older adults to gather together to participate in music, promotes social interactions between older adults and their peers, and alleviates loneliness among older adults and a sense of social detachment ^[15]. Therefore, researchers are increasingly becoming interested in the impact of SD on older adults with psychological problems and mental illness.

A study about the correlation between physical activity and LUTSs/BPO (benign prostatic obstruction) in 2019 showed that the quality of the evidence for most of the effects of physical activity on LUTSs/BPO was very low. It was therefore uncertain whether physical activity affects symptom scores for LUTSs, and the confidence in the estimates was lowered due to study limitations, inconsistency, indirectness, and imprecision ^[16]. In the same period, a study found that more specifically, patients with reduced physical activity levels had an increased risk of moderate/severe LUTSs ^[17]. However, many studies have shown that men with the most sedentary time had a significant risk of LUTSs, but physical activity intensity was not associated with LUTS progression ^{[18, 19]}. The results of the above studies were not consistent.

However, the author, as an SD enthusiast, found that BPH patients who adhere to SD for a long time are less likely to develop moderate to severe LUTSs than those who walk for physical activity. Therefore, we verified whether SD could better alleviate LUTSs/BPH compared with walking through a follow-up observation method. The findings revealed that SD was more effective than walking in alleviating LUTSs/BPH. This result may be due to what we learned from interviews with some of the study participants: first, music plays a very important role in promoting physical activity. Although SD and walking are the two most common forms of physical activity for older adults, SD is more physically and mentally pleasing to older adults than walking, which is mostly limited to physical activity, while SD has soothing music and a suitable rhythm that is more pleasing to older adults. Second, the variety, power and amplitude of SD are more effective than walking in promoting physical activity of the lower extremities in older adults, which can predominantly strengthen pelvic floor muscle activity, promote parasympathetic nervous system activity, reduce sympathetic nervous system excitation (such as blockers), reduce prostate resting sympathetic tone, and improve the hormonal environment by regulating insulin and testosterone. In addition, a more important point that has not been mentioned in other studies is that SD is a group physical activity, which makes it easy to continue every day, but walking is not easy to adhere to regularly because it is a self-guided physical activity.

Physical activity that relieves LUTSs must be performed over a longer period to have an effect, even if the physical activity is intense and beneficial. This study concluded that participating in SD for an extended period of time is beneficial. Similar studies have proposed that dance-based physical activity can be effective in promoting community participation and enjoyment for healthy individuals ^[20]. At present, SD integrates Chinese-style dancing and music with energetic and repetitive rhythms. However, relatively more research has been conducted on the effects of SD on the cognitive function of individuals, and relatively little research has been conducted on other chronic conditions, especially on LUTSs.

The findings suggested that increased SD may lead to a reduced risk of LUTSs. However, despite the findings presented in the current study, the specific biologic mechanisms linking physical activity and LUTSs remain unknown, although they are certainly an area for future research.

In this study, through historical data review and prospective observation, to avoid confounding factors in the two study groups, two groups were matched; however, sample size after matching was small, which may have some influence on the representativeness of the results of this study. Future studies should include more participants for follow up observation. The second limitation is that this study compared two types of physical activity modalities according to the existing main physical activity modalities of older adults, walking and SD, and no comparison was made between nonphysical activity and these two physical activity modalities.

LUTSs: Lower urinary tract symptoms

BPH: Benign prostatic hyperplasia

LUTSs/BPH: The patients of Benign prostatic hyperplasia with Lower urinary tract symptoms

SD: Square dancing

PSM : Propensity score matching

IPSS: International Prostate Symptom Score

VPSS: visual prostate symptom score

Funding information

This work was supported by the Natural Science Foundation of Heilongjiang Province, China (LH2019G011), the Mudanjiang Science and Technology Bureau Project (Z2017s0003) and Science Foundation of Changzhou University(ZMF22020015). And The funding agency (number is LH2019G011) played an important role in the topic ,design and content of the study . The funding agencys (Z2017s0003 and ZMF22020015 ) played some important roles in collection, analysis, and interpretation of data . The funding agency (ZMF22020015) played an important role in writing the manuscript.

Consent for publication

This study was approved by the community resident committees surveyed. All participants provided written informed consent. All participant reports have consent for publication.

Ethics approval and consent to participate

The research involving human participants, and it have been approved by Changzhou University Ethics Review Committee that is an appropriate ethics committee(reference number is 3022082401 ).

Acknowledgments

We thank all participants for sharing their time and the residents of the Green Town Gelin Community, Hubin community and Xuewei Community of Daqing City. We thank Heilongjiang Province for their support with data collection and 3 Peer Experts who provided purely technical, and Springer Nature Author Services in writing assistance. We would also like to thank everyone in our research group for their dedication.

Authors' contributions

ZLL: Conceptualization, methodology, formal analysis, data curation, writing-original draft, writing—review & editing, visualization, project administration, and supervision. ZH: Conceptualization, methodology, formal analysis, and data curation. JDX: Investigation, formal analysis, and data curation. SM: Investigation and data curation. And all authors have read and approved the manuscript. ZH and JDX I had contributed more to the data collection.

Conflicts of interest

The authors declare that there are no conflicts of interest.

Availability of data and materials

The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request by contacting us via email at [email protected].

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Walking, SD and urinary tract symptoms with BPH: A cross-sectional, retrospective and follow-up chain design study

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Abstract

Figures

Introduction

Methods

Study Design and Population

Assessment of LUTS/BPH Incidence and Progression

Statistical Analysis

Results

The baseline level between the SD and walking groups

Cox survival analysis: Effect of SD and walking on LUTS outcomes

Discussion

Conclusions

Limitations

Abbreviations

Declarations

References

Supplementary Files

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