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\begin{document}

\title{The Impact of Movement, Physical Activity and Position on Urine
Production: A Pilot Study}



\author[1]{Mutlu Deger}%
\author[2]{Vansh  Kapila}%
\author[3]{ Marie Astrid  Denys}%
\author[1]{Ibrahim Aridogan}%
\author[4]{Karel Everaert}%
\author[4]{François Hervé}%
\affil[1]{Cukurova University Faculty of Medicine}%
\affil[2]{Ghent University Faculty of Medicine and Health Sciences}%
\affil[3]{Ghent University}%
\affil[4]{Universitair Ziekenhuis Gent}%


\vspace{-1em}



  
  \date{May 24, 2024}


\begingroup
\let\center\flushleft
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\selectlanguage{english}
\begin{abstract}
Background: Many different internal factors have been proven to
influence urine production such as age, weight, and quality of sleep.
External factors such as consumption of caffeine and fluid consumption
have been shown to have an impact on urine production. Aim: To
investigate the impact of movement, physical activity, and position on
urine production. Methods: This prospective observational study was
executed at Ghent University Hospital, Belgium. Study participation was
open for anyone visiting the hospital. Participants collected 1 basic
and 2 extended 24-hour urine collections and filled in questionnaires
concerning their general health and physical activity. Urinary levels of
osmolality, sodium, and creatinine were determined. Data on movement,
physical activity and position was described. Results: An increase in
body movement leads to a significant increase in diuresis during
daytime, night-time, and 24 hours (p=0,002, p= \textless{}0,001, and
p=\textless{}0,001, respectively). An increase in body movement leads to
a significant decrease in osmolality during night-time and 24 hours
(p=0,009, and p=0,004, respectively). However, no significant influence
of movement on osmolality was found during daytime (p=0,12). An increase
in body movement leads to a significant decrease in creatinine during
daytime, night-time, and 24 hours (p=0,001, \textless{}0,001, and
p=\textless{}0,001, respectively). An increase in body movement leads to
a significant increase in sodium during daytime (p=0,046) but this was
statistically significant during night-time and 24 hours (p=0,32, and
p=0,84 respectively). Conclusion: Our study demonstrates a statistically
significant association of movement, physical activity, and position
with urine production. It would therefore be interesting to explore this
association further with the use of new technology to have more accurate
data. Here lays a potential role for conservative measurements and
lifestyle adaptations in the management of patients with bothersome LUTS
and more precisely nocturia.%
\end{abstract}%



\sloppy


\textbf{The Impact of Movement, Physical Activity and Position on Urine
Production: A Pilot Study}

\textbf{Abstract}

\textbf{Background:} Many different internal factors have been proven to
influence urine production such as age, weight, and quality of sleep.
External factors such as consumption of caffeine and fluid consumption
have been shown to have an impact on urine production.

\textbf{Aim:} To investigate the impact of movement, physical activity
and position on urine production.

\textbf{Methods:} This prospective observational study was executed at
Ghent University Hospital, Belgium. Study participation was open for
anyone visiting the hospital. Participants collected 1 basic and 2
extended 24-hour urine collections and filled in questionnaires
concerning their general health and physical activity. Urinary levels of
osmolality, sodium and creatinine were determined. Data on movement,
physical activity and position was described.

\textbf{Results:} An increase in body movement leads to a significant
increase in diuresis during daytime, night-time, and 24 hours (p=0,002,
p= \textless{}0,001, and p=\textless{}0,001, respectively). An increase
in body movement leads to a significant decrease in osmolality during
night-time and 24 hours (p=0,009, and p=0,004, respectively). However,
no significant influence of movement on osmolality was found during
daytime (p=0,12). An increase in body movement leads to a significant
decrease in creatinine during daytime, night-time, and 24 hours
(p=0,001, \textless{}0,001, and p=\textless{}0,001, respectively). An
increase in body movement leads to a significant increase in sodium
during daytime (p=0,046) but this was statistically significant during
night-time and 24 hours (p=0,32, and p=0,84 respectively).

\textbf{Conclusion:} Our study demonstrates a statistically significant
association of movement, physical activity, and position with urine
production. It would therefore be interesting to explore this
association further with the use of new technology to have more accurate
data. Here lays a potential role for conservative measurements and
lifestyle adaptations in the management of patients with bothersome LUTS
and more precisely nocturia.

\textbf{Keywords:} movement, physical activity, position, urine.

\textbf{What's already known about this topic?}

In a healthy person, below normal hydration levels, the body produces an
average of 1-2 liters of urine per day. Most of the urine production
occurs during waking hours, and only 20-30\% of urine is produced during
sleep. Different factors have been hypothesized to affect urine
production or voiding physiology. It may be due to internal and external
factors such as age, antidiuretic hormone, fluid consumption, and
caffeine intake, that affect urine production. In the literature, there
is no study that investigates the impact of movement, physical activity
and position on urine production.

\textbf{What does this article add?}

Our study demonstrates a statistically significant association of
movement, physical activity, and position with urine production

\textbf{Introduction}

In a healthy person, below normal hydration levels, the body produces an
average of 1-2 liters of urine per day\textsuperscript{1}. Most of the
urine production occurs during waking hours, and only 20-30\% of urine
is produced during sleep\textsuperscript{1}. Different factors have been
hypothesized to affect urine production or voiding physiology. It may be
due to internal and external factors that affect urine production. One
of the internal factors is age, as noted by Myron Miller, who studies
changes in the kidney and hormonal systems that control water and sodium
excretion\textsuperscript{2}. Hoshiyama et al. suggest that elderly
patients show an increase in nocturnal urine production due to
natriuresis resulting from increased B-type natriuretic peptide (BNP)
secretion and decreased anti-diuretic hormone (ADH)
secretion\textsuperscript{3}. Denys et al. state that circadian rhythms
of the bladder and the kidney changes as patients grow older, the study
found that 96\% of patients \textgreater{}65 years, who consulted for
complaints of UI, had nocturia \textsuperscript{4}.

Different external factors have been known to give a significant impact
on urine production. Fluid consumption is an example of such. Studies
showed that decreasing fluid intake in patients with detrusor activity
and/or urodynamic stress incontinence decreased voiding frequency,
urgency and incontinence episodes \textsuperscript{5,6}. Studies have
also shown an important impact of caffeine on urine
production\textsuperscript{7,8}. Besides caffeine and fluid intake,
there is increasing evidence to support the effect of carbonated drinks
in the development of lower urinary tract symptoms (LUTS)
\textsuperscript{8}. Robinson et al. performed a large population-based
study based on the Boston Area Community Health Survey which showed that
an overall larger intake of energy resulted in more urinary incontinence
as well as increased its severity. Furthermore, they demonstrated that
an increase in saturated fat was associated with post micturition
symptoms and nocturia \textsuperscript{7}.

In the literature, there is no study that investigates the impact of
movement, physical activity, and position on urine production. However,
we the authors, have, based on the physiology, a strong inclination to
believe that movement, physical activity, and position will have a
significant impact on urine production. Therefore, in this pilot study,
we aimed to investigate the effects of movement, physical activity, and
position on urine production.

\textbf{Subjects and methods}

\textbf{Study design and population}

This prospective, observational study is based on a clinical study
conducted at the between November 2013 and April 2016. The study
participation was open for anyone visiting the hospital interested to
participate in a clinical study.

There were no specific inclusion criteria. Exclusion criteria were
night-work employment and intake of medication with a potential effect
on urine output (such as diuretics, desmopressin, angiotensin-converting
enzyme inhibitors, angiotensin II receptor antagonists and non-steroidal
anti-inflammatory drugs).

\textbf{Study protocol}

A total of 65 persons signed an informed consent, 20 persons were
excluded (never started (n = 17), night shift (n = 1), failed to follow
the instructions for urine collections (n = 2)) and thus a total of 45
persons were eligible for analysis. Demographic data were collected.

Within a period of six weeks, two extended urine collections were
obtained during two non-consecutive 24-hour periods to determine
diuresis rate and renal functions. For this, participants were asked to
collect 5 daytime 3 and nighttime urine samples at fixed time intervals
over 24 hours. Voided volume at the time of sample collection, as well
as volumes of any interim micturition, were recorded. During the first
extended urine collection, participants also had to collect all daytime
and nighttime urine in a daytime and nighttime container. Urinary
concentration of osmolality, creatinine and sodium were determined for
all urine samples and for both urine containers. Participants had to
respect directives regarding the intake of fluids and food during both
study days (drink 1.5-2 liters water and do not drink more than 2 units
of alcohol per day; avoid salting their food and eating aperitif snacks,
sauces, fast food and ready-made meals).

Furthermore, patients were asked to keep track of their movements and
were requested to give an indication of what they had done the most
during a period of time of one hour. Movement/position was divided into
five categories. 0 was equivalent of having laid down the most that
hour. 1 meant that the participant had been sat down for most of the
hour. 2 stood for standing up. 3 was allocated to walking as the
majority movement of the hour. 4 was given if the patient had performed
more intense activity during that hour i.e. running, cycling etc.

The study was carried out in conformity with the Declaration of
Helsinki. The Ghent University Hospital Review Board approved the study
(EC/2013/802) and all participants gave written consent

\textbf{Statistical Analysis}

The statistical analysis that was done for this pilot study can be split
up in four parts.

The first step was aligning the data pertaining to movement with the
data regarding urine production. The first hurdle that had to be crossed
was that of the discrepancy in data collection moments for both urine
production as well as that of movement. As mentioned above, participants
were asked to collect eight urine samples. Contrary to the urine
sampling, participants were asked to fill in hourly updates regarding
their majority movement of the past hour, resulting in 24 inputs of data
for the same day regarding movement. The solution to this was clubbing
three inputs of data of movement. Here the range of movements no longer
went from 0-4, but now went from 0-12. Because of this, there was now a
symmetry in the data input of urine samples as well as that of movement.

The second step was to change the database format in its entirety. The
database was in a wide format. This had to be changed to a long format,
as otherwise, the analysis that had to be done would have been
statistically challenging. As such every participant in the study had 16
different data entries each pertaining to 1 of 8 timeslots of both days.

The third step was to test the hypothesis by conducting a basic
statistical test such as the Kruskal Wallis and the Mann Whitney U test.
To successfully conduct these tests, movement was divided into three
categories, defined as 1,2 and 3. They respectively stood for less,
moderate and more movement and physical activity. A p-value of
\textless{}0,05 was considered as statistically significant.

The fourth and final step was the main statistical analysis. Mixed model
statistics were used to analyze the impact of movement on urine
production. Here diuresis, osmolality, creatinine and sodium were
compared with movement to find any form of association. Parameters of
fixed effects were estimated using maximum likelihood estimation and
reported as standardized regression coefficients (\selectlanguage{greek}β\selectlanguage{english}) with their
respective standard error. A p-value \textless{}0.05 was considered as
statistically significant. These tests were conducted for the entire day
as well as day and night separately. Factors such as ``BMI'' and ``age''
were defined as confounders and included in the mixed model.

Statistical analysis was carried out using SPSS 24.

\textbf{Results}

\textbf{Patient characteristics}

A total of 45 people with a median age of 35 (26-54) were included in
the study. Of these, 29 were female and 16 were male. 25\% of the
participants had one episode of nocturia and 18\% had an average of two
or more episodes of nocturia, the remaining had no nocturia. Demographic
and patients characteristics are given in \textbf{Table 1} .

\textbf{Basic statistical analysis}

There were 448 data inputs in the first category (less movement), 160 in
the second one (moderate movement) and 29 in the third one (more
movement). This was the case for all four variables.

The mean of diuresis of less, moderate and more movement groups are
1.4\selectlanguage{ngerman}±1.0 ml/min, 1.8±1.4 ml/min, and 2.0±1.2 ml/min, respectively.
Diuresis was significantly higher in the moderate and more movement
group compared to the less movement group (p= 0,003 and p=0,014). In
terms of diuresis, there was no significant difference between the
moderate and more movement groups (p=0,701) (\textbf{Figure 1A} ).

The mean of creatinine of less, moderate and more movement groups are
108.1±70.8 mg/dl, 89.5±63.2 mg/, and 73.4±47.8 md/dl respectively.
Creatinine was significantly higher in the moderate and more movement
group compared to the less movement group (p= 0,008. and p=0,026). In
terms of creatinine, there was no significant difference between the
moderate and more movement groups (p=0,787) (\textbf{Figure 1B} ).

The mean of osmolality of less, moderate and more movement groups are
550.4±248.5 mosm/kg, 524.0±256.4 mosm/kg, 477.7±237.9 mosm/kg
respectively. There was no significant difference in terms of osmolality
between the three groups (p=0.197) (\textbf{Figure 1C} ).

The mean of sodium of less, moderate and more movement groups are
101.6±55.2 mmol/l, 96.1±59.7 mmol/l, 80.6±46.6 mmol/l respectively.
There was no significant difference in terms of sodium between the three
groups (p=0.055) (\textbf{Figure 1D} ).

\textbf{Complex statistical analysis}

The different models generated for the evaluation of diuresis,
osmolality and creatinine during daytime, nighttime and 24h had 3
variables as randomisation stratification variables: age, body mass
index (BMI), and movements (Table 2-5). The Akaike information criterion
(AIC) of the given set of data are summarized in the tables, and were
superior to the other alternative models tested.

An increase in body movement leads to a significant increase in diuresis
during daytime, night-time and 24 hours (\textbf{p=0,002, p=
\textless{}0,001, and p=\textless{}0,001, respectively} ) (\textbf{Table
2} ).

An increase in body movement leads to a significant decrease in
osmolality during night-time and 24 hours (\textbf{p=0,009, and p0,004,
respectively} ). However, no significant influence of movement on
osmolality was found during daytime (\textbf{p=0,12} ) (\textbf{Table 3}
).

An increase in body movement leads to a significant decrease in
creatinine during the daytime, night-time and 24 hours (\textbf{p=0,001,
\textless{}0,001, and p=\textless{}0,001, respectively} ) (\textbf{Table
4} ).

An increase in body movement leads to a significant increase in sodium
only during the daytime (p=0,046). However, this meaning does not exist
in terms of during the night-time and 24 hours (\textbf{p=0,32, and
p=0,84 respectively} ) (\textbf{Table 5} ).

\textbf{Discussion}

Movement, physical activity and position are known to influence a broad
spectrum of mechanisms in the human body. Therefore, we set out to
explore the impact movement may have on urine production. There is ample
existing body of literature showcasing the effects of movement, physical
activity and position, however, there is no existing data on the impact
on urine production \textsuperscript{9-11}.

Our study was performed in a population of healthy patients with age
varying from 26 years to 54 years with a mean of 35 years old. Due to
multiple variables and the complex interaction between these, we opted
for mixed model statistical analysis, A positive association was found
between diuresis and physical activity, movement and position for all
three timeframes i.e. 24 hours, daytime and night-time. Negative
associations were found between osmolality and creatinine and physical
activity, movement and position. The association between creatinine and
physical activity, movement and position were significant for all three
timeframes, however, this was not the case for osmolality where the
association was only significant for 2 timeframes being 24-hours and
night-time. Furthermore, there were no significant associations between
sodium and physical activity, movement and position except a very slight
statistically significant value for the model of daytime.

As this is a pilot study, there is a paucity of data exploring the topic
of movement and urine production. There are, however, other studies
exploring the association of physical activity and glomerular filtration
rate (GFR) as well as kidney function. The general consensus states a
positive association between physical activity and GFR as well as kidney
function \textsuperscript{9,12-14}. Moreover, Wolin et al. state that
physical activity may provide a strategy for the management of benign
prostatic hyperplasia related outcomes, particularly
nocturia\textsuperscript{11}.

Physical activity is known to increase blood pressure in the acute
setting. An increase in blood pressure would theoretically increase the
blood flow to the kidneys, without counting for any diversion of blood
flow to skeletal muscle or cerebrum in cases of flight-and-fright
responses. Nonetheless, an increase in renal blood flow, would increase
the flow within the glomerulus. This would result in an increased
glomerular filtration rate, which could be a potential hypothesis for
increased urine production. Nonetheless, one must account for processes
of reabsorption and filtration that occur within the renal tubules,
which brings us to our second hypothesis \textsuperscript{15,16}.

The renin-angiotensin-aldosterone system (RAAS) is a hormone system that
regulates fluid balance and blood pressure and works by increasing blood
volume and hence blood pressure. With increased physical activity, blood
pressure rises likely due to a combination of the baroreceptor reflex,
increased cardiac output and increased systemic vascular resistance
secondary to the effect of the sympathetic nervous system. As such,
there is a possibility that RAAS activity may not be as required by the
body's physiology since the blood pressure is already autoregulated and
no increase in blood volume is required to increase blood pressure.
Nonetheless, a simple increase in blood pressure causing an increased
glomerular filtration rate with unchanged reabsorption dynamics, could
very well be the principle cause of an increased diuresis associated
with physical activity, movement and position. This would clarify the
phenomenon of increased urinary excretion without impacting on urinary
sodium, however, it is likely it is a combination of multiple systems
that play a role \textsuperscript{10,15-17}.

The strengths of our study are that it has been performed in a
well-designed sample that is representative of the general population.
Furthermore, the study design is prospective, and the research topic is
completely novel; hence the pilot study. However, some limitations must
be noted such as the lack of data on serum. Due to this, we could not
calculate the GFR and an estimate was made using BMI and age, however,
we felt this would be too vague and not accurate enough. Furthermore, as
the initial objective of the questionnaires was to compare the basic and
extended urine sampling, targeted data for the movement was not
specifically outlined. Urine samples were taken every 3 hours and were
objectified; whereas, the data on movement was given a subjective score
every hour by the patient. This data was then transformed to make the
analysis more transparent. In addition, the sample of our study might be
considered too small to note all the differences between certain
confounders. As such it is difficult to amplify the results to larger
patient groups. It is important to note that calculating the low level-1
variations of the different mixed models may have led to the loss of
matching previous results within the same patient. As such all the data
and its results could only be made with relation to intraindividual
differences.

It remains clear that more research is necessary within this domain. As
many studies have suggested physical activity is a very easy,
non-invasive way to improve quality of life \textsuperscript{9-11,13}.
Here it is vital to focus on a larger and more varied sample, as this
could lead to more exact data. As there are many unanswered questions
within this field of research, we must try and find a better
understanding of the pathology and increase the methods and tools
available to analyse the same. In an ideal situation, the researcher
must gain information on the exact timing of movement, the exact
intensity of movement, and finally how this impacts the renal system.

In the future, the use of automated monitoring devices for factors like
voiding, urine production and residual volume, but also for diet, blood
pressure, pulse and sleep will be necessary. In addition to this,
fitting applications, such as bladder diaries and intake diaries, will
be needed as well in support of these new monitoring devices. Technology
is already available in the form of a smart flow, a smart diaper, but
also a smart mattress that can supply the required information.
Furthermore, the necessary applications are available or easy to make.
The main problems to solve are validation of the applications and
devices for the purpose of exploring nocturnal LUTS and the financial
incentive for companies to this low-volume work. However,
community-driven sponsoring might be a solution for this.

\textbf{Conclusions}

Our study demonstrates a statistically significant association of
movement, physical activity and position with urine production. It would
therefore be interesting to explore this association further with the
use of new technology to have more accurate data. Here lays a potential
role for conservative measurements and lifestyle adaptations in the
management of patients with bothersome LUTS and more precisely nocturia.

\textbf{Conflicts of Interest:}

All authors disclose any potential conflict of interest.

\textbf{Funding Sources:}

This research did not receive any specific grant from funding agencies
in the public,

commercial, or not-for-profit sectors.

\textbf{Authorship}

Study Design: Karel Everaert, Marie Astrid Denys, Data analysis: Mutlu
Deger , Vansh Kapila, Manuscript writing: Mutlu Deger, Vansh Kapila,
Manuscript editing: François Herve, Data colleciton: Marie Astrid Denys,
Vansh Kapila, Supervision: Karel Everaert, Ibrahim Atilla Aridogan,
François Herve.

All the authors have given the approval of the final version to be
published and agreed to be

accountable for all aspects of the work.

\textbf{Data Availability Statement:}

We can share our data with the journal for representing analysis and
interpretation of the data. However, we do not want the readers to see
or download our data.

\textbf{Ethics:}

The study was carried out in conformity with the Declaration of
Helsinki. The Ghent University Hospital Review Board approved the study
(EC/2013/802) and all participants gave written consent

\textbf{REFERENCES}

1. Colborn D. Urine production and the physiology of micturition.
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2. Miller M. Nocturnal polyuria in older people: pathophysiology and
clinical implications. \emph{Journal of the American Geriatrics
Society.} 2000;48(10):1321-1329.

3. Hoshiyama F, Hirayama A, Tanaka M, et al. The impact of obstructive
sleep apnea syndrome on nocturnal urine production in older men with
nocturia. \emph{Urology.} 2014;84(4):892-897.

4. Denys MA, Decalf V, Kumps C, Petrovic M, Goessaert AS, Everaert K.
Pathophysiology of nocturnal lower urinary tract symptoms in older
patients with urinary incontinence. \emph{Int J
Urol.}2017;24(11):808-815.

5. Hervé F, Delabie L, Mylle T, Weiss J, Bower W, Everaert K. Effect of
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7. Robinson D, Giarenis I, Cardozo L. You are what you eat: the impact
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symptoms.\emph{Maturitas.} 2014;79(1):8-13.

8. Robinson D, Hanna\selectlanguage{english}-Mitchell A, Rantell A, Thiagamoorthy G, Cardozo L.
Are we justified in suggesting change to caffeine, alcohol, and
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9. Hawkins MS, Sevick MA, Richardson CR, Fried LF, Arena VC, Kriska AM.
Association between physical activity and kidney function: National
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10. Warburton DE, Bredin SS. Health benefits of physical activity: a
systematic review of current systematic reviews. \emph{Current opinion
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11. Wolin KY, GRUBB III RL, Pakpahan R, et al. Physical activity and
benign prostatic hyperplasia-related outcomes and
nocturia.\emph{Medicine and science in sports and exercise.}
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12. Finkelstein J, Joshi A, Hise MK. Association of physical activity
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(NHANES III). \emph{American journal of kidney
diseases.}2006;48(3):372-382.

13. Robinson-Cohen C, Littman AJ, Duncan GE, et al. Physical activity
and change in estimated GFR among persons with CKD. \emph{Journal of the
American Society of Nephrology.} 2014;25(2):399-406.

14. Shipley R, Study R. Changes in renal blood flow, extraction of
inulin, glomerular filtration rate, tissue pressure and urine flow with
acute alterations of renal artery blood pressure. \emph{American Journal
of Physiology-Legacy Content.} 1951;167(3):676-688.

15. Arroll B, Beaglehole R. Does physical activity lower blood pressure:
a critical review of the clinical trials. \emph{Journal of clinical
epidemiology.} 1992;45(5):439-447.

16. Nelson L, Esler M, Jennings G, Korner P. Effect of changing levels
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17. Rossing P, Hommel E, Smidt UM, Parving H-H. Impact of arterial blood
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\textbf{Figure Legends:}

\emph{\textbf{Figure 1}: Pairwise comparison of diuresis (1A),
creatinine (1B), sodium (1C), and osmalility (1D) between different
categories of movement}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-1/Figure-1}

\end{center}
\end{figure}

\textbf{Hosted file}

\verb`Table 1.docx`  available at \url{https://authorea.com/users/339527/articles/533743-the-impact-of-movement-physical-activity-and-position-on-urine-production-a-pilot-study}

\textbf{Hosted file}

\verb`Table 2.docx`  available at \url{https://authorea.com/users/339527/articles/533743-the-impact-of-movement-physical-activity-and-position-on-urine-production-a-pilot-study}

\textbf{Hosted file}

\verb`Table 3.docx`  available at \url{https://authorea.com/users/339527/articles/533743-the-impact-of-movement-physical-activity-and-position-on-urine-production-a-pilot-study}

\textbf{Hosted file}

\verb`Table 4.docx`  available at \url{https://authorea.com/users/339527/articles/533743-the-impact-of-movement-physical-activity-and-position-on-urine-production-a-pilot-study}

\textbf{Hosted file}

\verb`Table 5.docx`  available at \url{https://authorea.com/users/339527/articles/533743-the-impact-of-movement-physical-activity-and-position-on-urine-production-a-pilot-study}

\selectlanguage{english}
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