Effects of an Alkalizing or Acidizing Diet on High-Intensity Exercise Performance under Normoxic and Hypoxic Conditions in Physically Active Adults: A Randomized, Crossover Trial

Abstract

Pre-alkalization caused by dietary supplements such as sodium bicarbonate improves anaerobic exercise performance. However, the influence of a base-forming nutrition on anaerobic performance in hypoxia remains unknown. Herein, we investigated the effects of an alkalizing or acidizing diet on high-intensity performance and associated metabolic parameters in normoxia and hypoxia. In a randomized crossover design, 15 participants (24.5 ± 3.9 years old) performed two trials following four days of either an alkalizing (BASE) or an acidizing (ACID) diet in normoxia. Subsequently, participants performed two trials (BASE; ACID) after 12 h of normobaric hypoxic exposure. Anaerobic exercise performance was assessed using the portable tethered sprint running (PTSR) test. PTSR assessed overall peak force, mean force, and fatigue index. Blood lactate levels, blood gas parameters, heart rate, and rate of perceived exertion were assessed post-PTSR. Urinary pH was analyzed daily. There were no differences between BASE and ACID conditions for any of the PTSR-related parameters. However, urinary pH, blood pH, blood bicarbonate concentration, and base excess were significantly higher in BASE compared with ACID (p < 0.001). These findings show a diet-induced increase in blood buffer capacity, represented by blood bicarbonate concentration and base excess. However, diet-induced metabolic changes did not improve PTSR-related anaerobic performance.

Full text

nutrients
Article
Effects of an Alkalizing or Acidizing Diet on
High-Intensity Exercise Performance under Normoxic
and Hypoxic Conditions in Physically Active Adults:
A Randomized, Crossover Trial
Mirjam Limmer 1, 2, * , Juliane Sonntag 2, Markus de Marées 1and Petra Platen 1
1
Department of Sports Medicine & Sports Nutrition, Ruhr-University Bochum, Gesundheitscampus Nord 10,
44801 Bochum, Germany; markus.demarees@rub.de (M.d.M.); petra.platen@rub.de (P.P.)
2Institute of Outdoor Sports and Environmental Science, German Sport University Cologne, 50933 Cologne,
Germany; jule.sonntag@yahoo.de
*Correspondence: mirjam.limmer@rub.de
Received: 19 January 2020; Accepted: 2 March 2020; Published: 4 March 2020


Abstract:
Pre-alkalization caused by dietary supplements such as sodium bicarbonate improves
anaerobic exercise performance. However, the influence of a base-forming nutrition on anaerobic
performance in hypoxia remains unknown. Herein, we investigated the effects of an alkalizing or
acidizing diet on high-intensity performance and associated metabolic parameters in normoxia and
hypoxia. In a randomized crossover design, 15 participants (24.5
±
3.9 years old) performed two
trials following four days of either an alkalizing (BASE) or an acidizing (ACID) diet in normoxia.
Subsequently, participants performed two trials (BASE; ACID) after 12 h of normobaric hypoxic
exposure. Anaerobic exercise performance was assessed using the portable tethered sprint running
(PTSR) test. PTSR assessed overall peak force, mean force, and fatigue index. Blood lactate
levels, blood gas parameters, heart rate, and rate of perceived exertion were assessed post-PTSR.
Urinary pH was analyzed daily. There were no differences between BASE and ACID conditions
for any of the PTSR-related parameters. However, urinary pH, blood pH, blood bicarbonate
concentration, and base excess were significantly higher in BASE compared with ACID (p<0.001).
These findings show a diet-induced increase in blood buffer capacity, represented by blood
bicarbonate concentration and base excess. However, diet-induced metabolic changes did not
improve PTSR-related anaerobic performance.
Keywords:
acid–base balance; potential renal acid load (PRAL); base–forming nutrition; acid-forming
nutrition; moderate simulated altitude; hypoxic chamber; sports nutrition; mountain sport disciplines;
anaerobic exercise test
1. Introduction
Many sport competitions staged at terrestrial altitudes ranging up to 3500 m (e.g., track-and-field,
cycling and team sport events, cross-country or alpine ski races, and mountain biking challenges) often
require single or multiple bouts of high-intensity, anaerobic exercise performance [
1
–
5
]. In addition,
although insufficiently investigated to date, several mountaineering disciplines are performed at
moderate to high altitudes with high anaerobic demands (e.g., ski touring, and single- or multi-pitch
rock, mixed, or ice climbing) [6,7].
However, acute exposure to moderate and high altitudes above 1500 m can impair anaerobic
exercise performance [
8
]. Reduced exercise tolerance above the lactate threshold at altitude is mainly
caused by severe disruption to homeostasis resulting from a decline in arterial oxygen saturation
Nutrients 2020,12, 688; doi:10.3390/nu12030688 www.mdpi.com/journal/nutrients

Nutrients 2020,12, 688 2 of 18
(S
a
O
2
) because of reduced oxygen pressure in the ambient and inspired air (P
I
O
2
) [
9
]. The reduced
P
I
O
2
leads to a decrease in arterial oxygen partial pressure (PO
2
) and to hypoxemia, which stimulates
the peripheral chemoreceptors to evoke CO
2
washout [
10
–
12
]. Concurrently, hyperventilation occurs
as a hypoxic ventilatory response during acclimatization to high altitude, while carbon dioxide
partial pressure (PCO
2
) falls and arterial pH increases according to the Henderson
−
Hasselbalch
equation [
10
,
13
,
14
]. This respiratory alkalosis is subsequently compensated for by the increased renal
elimination of bicarbonate ions ([HCO
3−
]), which results in a decrease in blood [HCO
3−
] and an
arterial pH returning to normal [
10
,
11
,
13
]. Blood [HCO
3−
] is an essential blood buffer for metabolic
acids. During maximal workloads with blood lactate levels up to 15 mmol/L, there is a corresponding
decrease in plasma [HCO
3−
] [
15
]. Thus, the resulting decline in [HCO
3−
] and blood buffer capacity
in the course of altitude adaption may significantly affect anaerobic exercise performance at altitude,
particularly above the lactate threshold [10,16–19].
Regarding anaerobic exercise performance at altitude, several studies have investigated the effects
of acute hypoxia on anaerobic performance parameters [
20
–
25
]. However, there are inconsistent and
controversial findings, with reports of either a significant impairment [
20
–
25
] or unaffected [
26
–
29
]
anaerobic exercise performance when exposed to acute hypoxia. Considering the applied study
protocols, this inconsistent and often unaffected anaerobic exercise performance may relate to the lack of
conformity in the duration of exposure to hypoxic conditions prior to exercise. Metabolic compensation
of respiratory alkalosis and the associated [HCO
3−
] loss is considered a slow-adapting mechanism.
For example, progression after 6 h and completion after 24 h of low to moderate altitude exposure was
reported [
10
,
30
]. Furthermore, this process was reported to remain incomplete after 24 h of exposure
to high altitude, but was completed after some days [10,12,30,31].
However, pre-exercise exposure to hypoxia within these studies investigating anaerobic exercise
performance at simulated altitudes mainly ranged between 15 min and 1 h [
20
–
22
,
24
,
32
]. Thus,
we suggest that this short exposure to simulated hypoxic conditions does not reflect the time
course of renal compensation of hypoxia-induced respiratory alkalosis, and is inappropriate for
assessing decreases in anaerobic exercise performance because of the metabolic compensation of
respiratory alkalosis and the associated [HCO
3−
] loss. Additionally, recent studies reporting no
impairment of anaerobic exercise performance mainly used 30-s and 45-s Wingate tests to assess
anaerobic exercise performance [
26
–
29
], despite the evidence that short duration, high-intensity
exercise performance can be maintained in acute hypoxic conditions because of a shift toward anaerobic
metabolism [
33
,
34
]. By contrast, power output for tests with continuous or repeated high-intensity
exercise longer than 45 s, like the 3-min all-out critical power test and repeated sprints, is often reduced
in acute hypoxia [
20
–
22
,
24
,
32
]. Therefore, we propose that performance tests assessing for anaerobic,
high-intensity exercise performance in hypoxic conditions should last for more than 45 s.
A number of studies have also examined the positive effects of supplementation with ergogenic
aids such as sodium bicarbonate (NaHCO
3
) or dietary nitrate as alkalotic buffers for attenuation of the
impaired exercise performance under hypoxic conditions [
32
,
35
–
39
]. Ingestion of NaHCO
3
increases the
[HCO
3−
] concentration in extracellular fluids, which leads to an enhanced buffering of hydrogen ([H
+
])
ions [
40
,
41
]. This [HCO
3−
]-induced increased buffering capacity seems to improve high-intensity
exercise performance in normoxia [
32
,
40
,
42
] and hypoxia [
32
,
35
–
37
,
43
–
45
]. A few studies have
examined the effect of NaHCO
3
ingestion on anaerobic exercise performance at altitude. Although some
studies found no effect of [HCO
3−
] supplementation on the power output of high-intensity exercise at
simulated altitudes of 3000 m and 2500 m [
46
,
47
], a constant or improved anaerobic exercise performance
at simulated altitude compared with anaerobic exercise performance under normoxic conditions was
described for participants receiving alkalizing agent supplements prior to exercise [
43
–
45
]. In addition,
positive effects of NaHCO
3
ingestion under acute moderate normobaric hypoxic conditions during
intermittent and repeated high-intensity exercise were reported [
32
,
35
–
37
]. In those studies, the authors
concluded that NaHCO
3
ingestion may offer an effective ergogenic strategy to alleviate hypoxia-induced
declines in anaerobic exercise performance.

Nutrients 2020,12, 688 3 of 18
Nevertheless, the effects of an alkalizing or acidizing dietary modification on anaerobic
performance under hypoxic conditions has not been investigated to date. Nutrition has a strong
impact on acid base balance [
48
–
50
], above all the urinary acid excretion, intestinal absorption rates
of nutrients, and the dietary protein and mineral contents [
51
,
52
], which can be quantified via the
potential renal acid load (PRAL) [
49
,
53
–
55
]. However remaining controversial [
56
,
57
], an improvement
in anaerobic exercise performance after a low-PRAL (alkalizing) diet for tests with a duration of 60 s
to 2 min [
48
,
58
,
59
], as well as an influence on blood and urinary pH, and [HCO
3−
], have often been
described when following an alkalizing diet [57,59,60].
Overall, these studies suggest that NaHCO
3
ingestion and the associated [HCO
3−
]-induced
enhanced buffering capacity may enhance high-intensity anaerobic exercise performance under
acute normobaric hypoxic conditions [
32
,
35
–
37
,
43
–
45
]. Additionally, several studies propose that
an alkalizing diet can change the blood buffer capacity, which influences high-intensity anaerobic
exercise performance in a way similar to NaHCO
3
ingestion [
48
,
58
,
59
]. However, there are no studies
investigating the effects of a low-PRAL (alkalizing) or high-PRAL (acidizing) diet on anaerobic exercise
performance after several hours of hypoxic exposure. Therefore, the aim of the present study was to
investigate the influence of an alkalizing versus acidizing diet on a single bout of anaerobic exercise
performance, maximum capillary blood lactate concentrations, blood gas parameters, heart rate (HR),
rating of perceived exertion, and urinary pH (pH
u
) in moderately trained young participants under
normoxic conditions and after 12 h of exposure to hypoxia. We hypothesized that an alkalizing diet
would enhance extracellular buffering capacity, and thus increase anaerobic exercise performance,
under normoxic conditions, and mitigate potential hypoxia-induced declines in anaerobic exercise
performance under hypoxic conditions.
2. Materials and Methods
2.1. Participants
Sixteen healthy, nonspecifically trained adult volunteers (n=8 men, n=8 women) participated
in the present study. One woman withdrew from the study because of a busy schedule. The results
presented are for the remaining 15 participants. For men (n=8), the mean (
±
standard deviation) age
was 24.6
±
4.6 years, the mean height was 180.0
±
5.6 cm, and the mean body mass was 72.1
±
5.5 kg,
while for women (n=7) these values were 24.4
±
3.4 years, 167.3
±
5.9 cm, and 60.9
±
9.5 kg,
respectively. All participants underwent medical screening before entering the study. Participants
had to be in good health with no pre-existing altitude illnesses, cardiac or pulmonary conditions,
and no musculoskeletal injuries that could interfere with running activities. All participants lived
close to sea level, were recreationally active (i.e., practicing various physical activities for 12 h per
week), and were familiar with sprinting activities. Exclusion criteria included acute muscular injuries
or restrictions, chronic medication intake, alcohol consumption, acute infections, and time spent above
2000 m in the four weeks prior to the investigation. In addition, individuals ingesting any nutritional
supplements or following any specific diet in the two months prior to the initiation of the study were
excluded. The study was approved by the ethical committee of the German Sport University Cologne
in accordance with the Declaration of Helsinki. Participants gave their written informed consent after
they had been informed of all experimental procedures and risks.
2.2. Experimental Design
The present investigation was conceptualized as a randomized, single-blind, counterbalanced
crossover trial (Figure 1). Whereas investigators were blinded for treatment assignments, participants
needed to be informed about necessary dietary modifications to obtain high or low PRAL values,
but not about expected influences of the diets and associated hypotheses. After having ad libitum
breakfast, all participants performed four anaerobic performance tests in a laboratory setting at intervals
of one week under normoxic (NOR) conditions for the first two weeks and hypoxic (HYP) conditions

Nutrients 2020,12, 688 4 of 18
in weeks 3 and 4. To limit the effects of diurnal variation on the measured variables, the four anaerobic
performance test trials were performed at approximately the same time each day. In a randomized
order, an acidizing (ACID) or alkalizing (BASE) dietary intervention was followed, resulting in four
groups (ABAB, ABBA, BAAB, BABA). This resulted in the four treatment conditions NOR ACID,
NOR BASE, HYP ACID, and HYP BASE. Each dietary intervention was maintained for four days [
56
],
followed by three washout-days with an unmodified diet before the next dietary intervention started
in a crossover trial. Participants were requested to abstain from strenuous high-intensity exercise and
alcohol for 24 h before each trial, and we requested compliance with these instructions before each
anaerobic performance test trial.
Nutrients 2020, 12, x FOR PEER REVIEW 4 of 19
conditions NOR ACID, NOR BASE, HYP ACID, and HYP BASE. Each dietary intervention was
maintained for four days [56], followed by three washout-days with an unmodified diet before the
next dietary intervention started in a crossover trial. Participants were requested to abstain from
strenuous high-intensity exercise and alcohol for 24 h before each trial, and we requested
compliance with these instructions before each anaerobic performance test trial.
Figure 1. Experimental sequence. NOR = normoxia; HYP = hypoxia; PTSR = portable tethered sprint
running test; ACID = acidizing diet; BASE = alkalizing diet.
2.3. Dietary Interventions
For the assessment of the daily PRAL values, as well as caloric and fluid intake, participants
were asked to document all foods and beverages consumed during the dietary interventions using
the Freiburger Nutrition Protocol (Freiburger Ernährungsprotokoll, Nutri-Science GmbH, Hausach,
Germany). PRAL values represent a quantification of the effects of ingested nutrients on the acid‒
base status [49,53]. The PRAL model is based on the content of proteins, Cl−, PO43−, SO42−, Na+, K+,
Ca2+, and Mg2+ [52] and was calculated as follows: PRAL (mEq/100 g) = 0.49 × protein (g/100 g) + 0.037
× phosphorus (mg/100 g) − 0.021 × potassium (mg/100 g) − 0.026 × magnesium (mg/100 g) − 0.013 ×
calcium (mg/100 g) [56]. In general, vegetables, fruits, and potatoes have the highest alkalizing
potential (low-PRAL nutrients), while meat, cheese, cereal products, and eggs promote systemic
acidity (high-PRAL nutrients) [48,54,55]. In addition, a German PRAL food list published by the
Institute for Prevention and Nutrition, Ismaning, Germany, [52] and suggestions for recipes were
given to the participants to meet the requirements of the alkalizing or acidizing diet. Participants
were instructed to make food and amount choices ad libitum based on the respective PRAL values of
foods. Following the common recommendations for PRAL-manipulating diets, participants were
specifically instructed to eat mainly fruits and vegetables during the alkalizing, low-PRAL diet,
combined with energy-dense foods such as starchy vegetables (e.g., potatoes and sweet potatoes),
plant sources of fat (e.g., seeds and nuts, avocadoes), and dried fruits (e.g., figs, dates, and raisins).
During the acidizing, high-PRAL diet, participants were instructed to eat mainly grains (e.g., oats,
bread, pasta), hard cheese (e.g., parmesan), and meats. Nutrients with moderate PRAL values, such
as white rice, yogurt, and legumes, were allowed for both dietary trials to ensure an adequate energy
intake, especially for the alkalizing diet [48,56]. Based on the daily nutrition protocols, overall fluid
intake (∑ fluid), caloric intake (∑ CAL), and overall PRAL sum value (∑ PRAL) were calculated for
each participant for the four conditions of NOR ACID, NOR BASE, HYP ACID, and HYP BASE for
statistical analyses.
2.4. Urinary pH
pHu was determined in spontaneous early morning urine samples (at least 5 mL of urine) using
Neutralit® pH-indicator strips pH 5.0–10.0 (Merck, Darmstadt, Germany). pHu was measured on
Figure 1.
Experimental sequence. NOR =normoxia; HYP =hypoxia; PTSR =portable tethered sprint
running test; ACID =acidizing diet; BASE =alkalizing diet.
2.3. Dietary Interventions
For the assessment of the daily PRAL values, as well as caloric and fluid intake, participants
were asked to document all foods and beverages consumed during the dietary interventions using
the Freiburger Nutrition Protocol (Freiburger Ernährungsprotokoll, Nutri-Science GmbH, Hausach,
Germany). PRAL values represent a quantification of the effects of ingested nutrients on the acid-base
status [
49
,
53
]. The PRAL model is based on the content of proteins, Cl
−
, PO4
3−
, SO4
2−
, Na
+
, K
+
, Ca
2+
,
and Mg
2+
[
52
] and was calculated as follows: PRAL (mEq/100 g) =0.49
×
protein (g/100 g) +0.037
×
phosphorus (mg/100 g)
−
0.021
×
potassium (mg/100 g)
−
0.026
×
magnesium (mg/100 g)
−
0.013
×
calcium (mg/100 g) [
56
]. In general, vegetables, fruits, and potatoes have the highest alkalizing
potential (low-PRAL nutrients), while meat, cheese, cereal products, and eggs promote systemic acidity
(high-PRAL nutrients) [
48
,
54
,
55
]. In addition, a German PRAL food list published by the Institute
for Prevention and Nutrition, Ismaning, Germany, [
52
] and suggestions for recipes were given to the
participants to meet the requirements of the alkalizing or acidizing diet. Participants were instructed to
make food and amount choices ad libitum based on the respective PRAL values of foods. Following the
common recommendations for PRAL-manipulating diets, participants were specifically instructed to
eat mainly fruits and vegetables during the alkalizing, low-PRAL diet, combined with energy-dense
foods such as starchy vegetables (e.g., potatoes and sweet potatoes), plant sources of fat (e.g., seeds
and nuts, avocadoes), and dried fruits (e.g., figs, dates, and raisins). During the acidizing, high-PRAL
diet, participants were instructed to eat mainly grains (e.g., oats, bread, pasta), hard cheese (e.g.,
parmesan), and meats. Nutrients with moderate PRAL values, such as white rice, yogurt, and legumes,
were allowed for both dietary trials to ensure an adequate energy intake, especially for the alkalizing
diet [
48
,
56
]. Based on the daily nutrition protocols, overall fluid intake (
P
fluid), caloric intake (
P
CAL),
and overall PRAL sum value (
P
PRAL) were calculated for each participant for the four conditions of
NOR ACID, NOR BASE, HYP ACID, and HYP BASE for statistical analyses.

Nutrients 2020,12, 688 5 of 18
2.4. Urinary pH
pHuwas determined in spontaneous early morning urine samples (at least 5 mL of urine) using
Neutralit
®
pH-indicator strips pH 5.0–10.0 (Merck, Darmstadt, Germany). pH
u
was measured on each
day of the four-day dietary interventions, and served as a control marker to ensure that the dietary
intervention had been implemented successfully [
61
]. The pH
u
of day 4 of the dietary intervention,
when the portable tethered sprint running (PTSR) test was performed, was used for statistical analyses.
2.5. High-Intensity Anaerobic Performance Test
Anaerobic performance was measured using the PTSR test [
62
]. The PTSR test was chosen because
it is simple, requires little space, and does not involve heavy and unwieldy equipment. The PTSR test
is suitable for field studies investigating high-intensity exercise performance during altitude sojourns,
as well as for the restricted space in hypoxic chambers, and thus allows direct comparability between
studies in normobaric and hypobaric hypoxic conditions. For the test, participants ran in one place with
a belt round their waist for force measurements. The belt was attached to an inextensible static rope
combined in series with a load cell, and fixed to a pillar at 90
◦
to the subject’s waist height. The belt was
located at the iliac crest to assure that participants were not hampered to pull maximally against the
tether. Before each PTSR test, the participants completed a pretest warm-up, which included 5 min of
aerobic exercise and 5 min of coordination and dynamic stretching. ‘Ready’, ‘Set’, and ‘Go’ commands
were provided, and the participant performed an all-out sprint for 60 s. At ‘Go’, participants started to
sprint at maximum effort and pulled with full force. Study investigators were all PTSR-experienced
and provided strong verbal encouragement for the entire test duration to ensure that participants
pulled the rope until voluntary exhaustion. Tethered running involves an often unfamiliar moving
pattern. Participants who were not familiar with tethered running thus had to perform an additional
habituation session prior to the first test trial to assure adequate test implementation of the PTSR
test and related physiological responses. Force data were recorded and downloaded to an online PC
using a sampling rate of 100 Hz. Overall peak force (PF) and overall mean force (MF) over 60 s were
recorded for subsequent analysis. Fatigue level during the PTSR test was assessed by calculating the
fatigue index (FI), following the recommended calculations for Wingate tests [
63
]. HR was recorded
as a control parameter throughout the tests using HR monitors (Polar T31; Polar Electro, Kempele,
Finland). Thus, HR was measured before and after the PTSR tests. Maximal post-exercise HR after
performance tests was used for further analyses. Blood lactate levels were measured in 20-
µ
L capillary
blood samples collected from a hyperemized earlobe before and 2, 4, 6, 8, and 10 min after PTSR
testing. Blood lactate measurements were carried out directly after each PTSR trial (Biosen S-Line;
EKF-diagnostic GmbH, Magdeburg, Germany). The maximum post-exercise lactate concentration
(La
max
) occurred mainly between 4 to 6 min after PTSR testing and was used for statistical analyses.
Borg’s rating of perceived exertion (RPE) was used to assess subjective perception of effort after each
PTSR test [
64
]. Borg’s RPE was explained to each participant by trained practitioners before the PTSR
tests, and was used as a marker for the relationships between subjective measures of exertion and the
objectively measured metabolic parameters of blood lactate and blood gas analysis.
2.6. Blood Gas Analysis
Capillary blood samples (100
µ
L) were taken from a hyperemized earlobe before (PRE PTSR) and
within 1 min after each PTSR trial (POST PTSR). Blood samples were immediately analyzed for blood
gas parameters using a blood gas analyzer (ABL80 FLEX CO-OX; Radiometer, Willich, Germany). PO
2
,
PCO
2
, blood pH (pH
b
), S
a
O
2
, blood [HCO
3−
], and base excess (BE) were determined. For HYP trials,
additional capillary blood samples were taken before entering the hypoxic chamber (PRE HYP) to
assess them for influences on acid-base balance because of hypoxic conditions.

Nutrients 2020,12, 688 6 of 18
2.7. Anthropometric Characteristics
Body weight was determined with a sliding weight mechanical scale (Seca 709; Seca, Hamburg,
Germany). Height was measured (to the nearest 0.1 cm) using the scale-integrated stadiometer.
2.8. Hypoxic Conditions
For HYP conditions in weeks 3 and 4 of the experimental period, all test subjects were exposed
to a simulated altitude of 3000 m. Altitude was simulated through nitrogen injection (VPSA S325
V16; van Amerongen, Tiel, The Netherlands) in a 65 m
3
environmental chamber located at sea level.
For simulation of an altitude of 3000 m, inspired air consisted of 15.0% O
2
, and the room temperature
in the hypoxic chamber was kept at a constant level of 21–23
◦
C using air conditioning (42 WKR
61; Carrier, Neuss, Germany). For the conditions HYP ACID and HYP BASE, all test subjects were
exposed to normobaric hypoxic conditions in two test sessions for 12 h overnight. Participants entered
the hypoxic chamber in the evening between 8 p.m. and 9 p.m., and performed the PTSR test the
next morning between 8 a.m. and 9 a.m. under hypoxic conditions after having ad libitum breakfast.
Participants were asked to perform only quiet and sedentary activities without any further activity
specifications during the 12-h stay in the hypoxic chamber.
2.9. Statistical Analysis
Data are presented as mean
±
standard deviation. All departures from normal distribution
were identified using the Shapiro–Wilk test. The effects of treatments on the parameters PF, MF, FI,
La
max
,HR, RPE, pH
u
,
P
fluid,
P
CAL, and
P
PRAL over time (NOR ACID, NOR BASE, HYP ACID,
and HYP BASE) were tested by one-way repeated-measures ANOVA, with sex (male and female) as a
between-subject factor. The effects of treatments on the blood gas analysis parameters PO
2
,PCO
2
, pH
b
,
S
a
O
2
, [HCO
3−
], and BE over time (NOR ACID PRE PTSR, NOR ACID POST PTSR, NOR BASE PRE
PTSR, NOR BASE POST PTSR, PRE HYP ACID, HYP ACID PRE PTSR, HYP ACID POST PTSR, PRE
HYP BASE, HYP BASE PRE PTSR, HYP BASE POST PTSR) were tested by one-way repeated-measures
ANOVA, with sex (male and female) as a between-subject factor. Violations of the assumption of
sphericity were corrected for by Greenhouse–Geisser adjustments. Two-tailed paired t-tests were
utilized as post hoc tests to indicate significant differences. A Bonferroni procedure was used (p*) to
retain an
α
=0.05, and the significance level was set at p
≤
0.05 in all comparisons. Effect sizes were
calculated using partial
η
squared (
η
p
2
), and were interpreted as small (0.01), medium (0.06), and large
(0.14). For post hoc analyses, Cohen’s d (d) was used to calculate effect sizes, with 0.2 considered to
indicate a small effect, 0.5 a medium effect, and 0.8 a large effect [65].
We also performed stepwise multiple linear regression analyses to elucidate whether the variables
P
PRAL,
P
fluid,
P
CAL, pH
u
, pH
b
PRE PTSR, [HCO
3−
] PRE PTSR, and BE PRE PTSR were
predictors of the PTSR-related performance measurements PF, MF, FI, La
max
, and HR. Furthermore, to
determine which of the abovementioned variables may predict the PTSR-related measurement of RPE,
we performed an ordinal logistic regression analysis.
Finally, we performed an a priori analysis to compute the required sample size for our study,
based on a previous study [
48
], in which a low-PRAL, alkalizing diet resulted in a 21% improvement
of anaerobic time to exhaustion (2.56
±
0.36) compared with a high-PRAL, acidizing diet (
2.11 ±0.31 s
).
Using an
α
-level of 0.05, this indicated a sufficient sample size of eight participants to detect the
expected changes with a power of at least 0.95. The
α
-level was set at p
≤
0.05, and all analyses
were conducted using statistical software (SPSS v25; IBM Co., Armonk, NY, USA). The free software
G*Power was used to calculate the required sample sizes and effect sizes [66].

Nutrients 2020,12, 688 7 of 18
3. Results
3.1. Dietary Intervention
We found significant main effects for
P
CAL (p=0.014,
η
p
2
=0.298) and
P
PRAL (p<0.001,
η
p
2
=0.888). There was no significant main effect for
P
fluid (p=0.893,
η
p
2
=0.009). Post hoc analyses
showed significantly lower values in
P
CAL for NOR BASE (5576.1
±
2125.4) compared with HYP
ACID (7379.5
±
2066.6 kcal; p* =0.038, d=0.86), and significantly higher values in
P
PRAL for NOR
ACID (142.6
±
71.9 mEq/day) compared with NOR BASE (
−
222.3
±
118.6 mEq/day; p* <0.001, d=3.53),
HYP ACID (175.6
±
38.3 mEq/day) compared with HYP BASE (
−
255.0
±
103.0 mEq/day; p* <0.001,
d=4.77), HYP ACID compared with NOR BASE (p* <0.001, d=3.80), and NOR ACID compared with
HYP BASE (p* <0.001, d=4.35) (Figure 2A
−
C). The participants’ sex had no influence on any of the
dietary intervention parameters.
Figure 2.
Changes in dietary intervention-related parameters after acidizing (ACID) and alkalinizing
(BASE) diet under normoxic (NOR) and hypoxic (HYP) conditions for (
A
) overall caloric intake (
P
CAL), (
B
) potential renal acid load sum value (
P
PRAL), and (
C
) overall fluid intake (
P
fluid), as well
as the associated physiological response of (
D
) urinary pH (pH
u
). Data points represent individual
values (
#
). Bar charts are mean
±
standard deviation. * p
≤
0.05, ** p
≤
0.01, *** p
≤
0.001. See Section 2.
Materials and Methods for further details.
3.2. Urinary pH
We found a main effect for pH
u
(p<0.001,
η
p
2
=0.655). Post hoc analyses showed significantly
lower pH
u
values for NOR ACID (5.64
±
0.41) compared with NOR BASE (6.54
±
0.57; p* =0.002,
d=1.75), HYP ACID (5.79
±
0.38) compared with HYP BASE (7.0
±
0.71; *<0.001, d=1.98), HYP

Nutrients 2020,12, 688 8 of 18
ACID compared with NOR BASE (p* =0.007, d=1.49), and NOR ACID compared with HYP BASE
(p* <0.001, d=2.21) (Figure 2D). The participants’ sex had no influence on pH
u
(p=0.376,
η
p
2
=0.078).
3.3. High-Intensity Anaerobic Performance Test
Results for all PTSR related parameters are shown in Figure 3. There were no significant main
effects in PF (p=0.158,
η
p
2
=0.132), MF (p=0.300,
η
p
2
=0.088), and FI (p=0.056,
η
p
2
=0.174)
(Figure 3A–C). However, there was a significant main effect for La
max
(p=0.011,
η
p
2
=0.246) (Figure 3D),
with significantly lower La
max
values for male (14.0
±
1.5 mmol/L) compared with female participants
(10.6
±
0.9 mmol/L; p<0.001). There were also no main effects in HR (p=0.948,
η
p
2
=0.009) and
RPE (p=0.780, ηp2=0.027) (Figure 3E,F). Additionally, the participants’ sex showed no influence on
PTSR-related parameters except for Lamax.
Nutrients 2020, 12, x FOR PEER REVIEW 8 of 19
3.3. High-Intensity Anaerobic Performance Test
Results for all PTSR related parameters are shown in Figure 3. There were no significant main
effects in PF (p = 0.158, ηp2 = 0.132), MF (p = 0.300, ηp2 = 0.088), and FI (p = 0.056, ηp2 = 0.174) (Figure
3A–C). However, there was a significant main effect for Lamax (p = 0.011, ηp2 = 0.246) (Figure 3D),
with significantly lower Lamax values for male (14.0 ± 1.5 mmol/L) compared with female participants
(10.6 ± 0.9 mmol/L; p < 0.001). There were also no main effects in HR (p = 0.948, ηp2 = 0.009) and RPE
(p = 0.780, ηp2 = 0.027) (Figure 3E,F). Additionally, the participants’ sex showed no influence on
PTSR-related parameters except for Lamax.
Figure 3. Performance measurements after acidizing (ACID) and alkalinizing (BASE) diet under
normoxic (NOR) and hypoxic (HYP) conditions for (A) peak force (PF), (B) mean force (MF), and (C)
fatigue index (FI), as well as the associated physiological response (D) maximum blood lactate
Figure 3.
Performance measurements after acidizing (ACID) and alkalinizing (BASE) diet under
normoxic (NOR) and hypoxic (HYP) conditions for (
A
) peak force (PF), (
B
) mean force (MF), and
(
C
) fatigue index (FI), as well as the associated physiological response (
D
) maximum blood lactate
(La
max
), (
E
) heart rate (HR), and (
F
) Borg’s rating of perceived exertion (RPE). Data points represent
individual values (
#
). Bar charts are mean
±
standard deviation. See Section 2. Materials and Methods
for further details.

Nutrients 2020,12, 688 9 of 18
3.4. Blood Gas Analysis
There was a significant main effect for PO
2
(p <0.001,
η
p
2
=0.761), PCO
2
(p<0.001,
η
p
2
=0.450)
,
S
a
O
2
(p<0.001,
η
p
2
=0.842), pH
b
(p<0.001,
η
p
2
=0.941), [HCO
3−
] (p<0.001,
η
p
2
=0.914), and BE
(p<0.001, ηp2=0.931). Significant differences in post hoc tests are shown in Table 1.
Table 1.
Portable tethered sprint running test (PTSR)-related blood gas parameters after acidizing or
alkalinizing diet under normoxic and hypoxic conditions.
PO2
[mmHg]
PCO2
[mmHg]
SaO2
[%]
pHb[HCO3−]
[mmol/L]
BE
[mmol/L]
N
O
R
ACID PRE PTSR 85.7 ±7.6 # 37.6 ±2.2 98.4 ±1.1 # 7.40 ±0.02 22.9 ±1.1 −0.7 ±1.3
POST PTSR 91.5 ±9.7 # 42.2 ±5.0 96.9 ±1.4 # 7.20 ±0.05 15.7 ±2.0 −11.4 ±2.6
BASE PRE PTSR 85.6 ±4.0 # 38.9 ±3.5 98.3 ±0.9 # 7.41 ±0.02 24.3 ±1.7 * 0.1 ±1.3
POST PTSR 89.9 ±7.4 # 43.1 ±5.5 97.0 ±13 # 7.23 ±0.04 17.2 ±2.1 * −10.8 ±2.8
H
Y
P
ACID
PRE HYP 90.1 ±9.0 # 39.8 ±3.5 # 98.6 ±0.9 # 7.39 ±0.02 23.7 ±1.5 # −0.6 ±1.2
PRE PTSR 67.8 ±4.3 36.2 ±3.8 94.4 ±1.3 7.41 ±0.02 22.5 ±2.0 −1.2 ±1.5
POST PTSR 72.8 ±5.9 38.1 ±5.7 91.5 ±2.9 7.22 ±0.06 15.1 ±1.8 −12.0 ±2.4
BASE
PRE HYP 90.3 ±7.9 # 41.1 ±2.9 # 98.5 ±0.6 # 7.41 ±0.01 25.5 ±1.6 #* 1.2 ±1.3 *
PRE PTSR 66.3 ±4.6 37.1 ±3.3 93.3 ±1.4 7.43 ±0.01 * 24.0 ±1.8 0.4 ±1.4
POST PTSR 70.3 ±5.6 40.1 ±6.4 90.8 ±2.1 7.24 ±0.06 16.5 ±2.0 −10.3 ±2.5
Note: Data are presented as mean
±
standard deviation. PO
2
=oxygen partial pressure; PCO
2
=carbon dioxide
partial pressure; S
a
O
2
=oxygen saturation; pH
b
=blood pH value; [HCO
3−
]=blood bicarbonate concentration;
BE =base excess; ACID =acidizing diet; BASE =alkalinizing diet; NOR =normoxia, HYP =hypoxia, PRE
PTSR =pre-PTSR values; POST PTSR =post-PTSR values. For further details see Section 2. Materials and Methods
*p<0.05 vs. ACID, # p<0.05 vs. HYP. For p-values see Section 3. Results.
Additionally, the participants’ sex showed a significant influence on PCO
2
(p=0.045,
η
p
2
=0.177)
and pH
b
(p=0.014,
η
p
2
=0.221). In post hoc analyses, male participants had significantly higher
values for PCO
2
compared with female participants in NOR BASE PRE PTSR (male: 41.4
±
2.9, female:
36.2 ±1.5 mmHg
;p* =0.010, d=2.26), HYP BASE PRE HYP (male: 42.9
±
2.5, female:
39.0 ±1.8 mmHg
;
p* =0.040, d=1.85), HYP BASE POST PTSR (male: 44.5
±
3.0, female: 35.0
±
5.3 mmHg; p* =0.020,
d=2.19), HYP ACID PRE HYP (male: 42.0
±
2.8, female: 37.2
±
2.2 mmHg; p* =0.030, d=1.88), and
HYP ACID POST PTSR (male: 42.0
±
2.7, female: 33.7
±
4.9 mmHg; p* =0.010, d=2.12). For pH
b
,
post hoc analyses showed significantly lower values in HYP BASE POST PTSR for male (7.20
±
0.03)
compared with female participants (7.28
±
0.05; p* =0.040, d=1.78). The participants’ sex had no
significant influence on PO
2
(p=0.220,
η
p
2
=0.094)
,
S
a
O
2
(p=0.131,
η
p
2
=0.108), [HCO
3−
] (p=0.514,
ηp2=0.059), or BE (p=0.160, ηp2=0.117).
3.5. Regression Analyses
Multiple linear regression analyses revealed no relevant predictors for PF, MF, and FI incorporating
the variables
P
PRAL,
P
fluid,
P
CAL, pH
u
, pH
b
PRE PTSR, [HCO
3−
] PRE PTSR, and BE PRE PTSR.
However, [HCO
3−
] PRE PTSR was identified as a significant predictor for La
max
and pH
b
, while PRE
PTSR was identified as a significant predictor for HR, whereas the variables
P
PRAL,
P
fluid,
P
CAL,
pH
u
, and BE PRE PTSR did not significantly predict La
max
and HR. The results of the multiple linear
regression analyses on La
max
and HR are shown in Table 2. Relationships between La
max
and [HCO
3−
]
PRE PTSR, as well as HR and pHb PRE PTSR, are shown in Figure 4. Ordinal logistic regression
analysis revealed no significant result in the main model fitting for RPE (χ2=0 8.495, p=0.273).

Nutrients 2020,12, 688 10 of 18
Nutrients 2020, 12, x FOR PEER REVIEW 11 of 19
Figure 4. Relationships between PTSR-related (A) maximum post-exercise lactate concentration
(Lamax) and (B) heart rate (HR) and the blood gas measurements before PTSR tests of blood pH (pHb
PRE PTSR) and blood bicarbonate ([HCO3−] PRE PTSR). Data points represent individual values for
the four treatment conditions NOR ACID (n = 15), NOR BASE (n = 15), HYP ACID (n = 15), and HYP
BASE (n = 15). NOR = normoxia, HYP = hypoxia, ACID = acidizing diet, and BASE = alkalinizing diet.
See Section 2. Materials and Methods for further details.
4. Discussion
Figure 4.
Relationships between PTSR-related (
A
) maximum post-exercise lactate concentration (La
max
)
and (
B
) heart rate (HR) and the blood gas measurements before PTSR tests of blood pH (pH
b
PRE
PTSR) and blood bicarbonate ([HCO
3−
] PRE PTSR). Data points represent individual values for the
four treatment conditions NOR ACID (n=15), NOR BASE (n=15), HYP ACID (n=15), and HYP
BASE (n=15). NOR =normoxia, HYP =hypoxia, ACID =acidizing diet, and BASE =alkalinizing diet.
See Section 2. Materials and Methods for further details.

Nutrients 2020,12, 688 11 of 18
Table 2.
Linear multiple regression analysis on portable tethered sprint running test (PTSR)-related
maximum post-exercise lactate concentration (Lamax) and heart rate (HR).
Predictor Variable R2Corrected R2F p Standardized βT p
Lamax
Model 0.200 0.184 12.746 0.001 *
PPRAL 0.073 0.539 0.592
PFluid 0.030 0.241 0.811
PCAL 0.145 1.163 0.250
pHu−0.212 −1.689 0.097
pHbPRE PTSR −0.224 −1.823 0.074
[HCO3-] PRE PTSR 0.447 3.570 0.001 *
BE PRE PTSR −0.304 −1.021 0.312
HR
Model 0.091 0.073 5.084 0.028 *
PPRAL −0.176 −1.255 0.215
Pfluid 0.065 0.480 0.633
PCAL 0.168 1.265 0.212
pHu0.089 0.603 0.550
pHbPRE PTSR −0.301 −2.255 0.028 *
[HCO3−] PRE PTSR 0.172 1.294 0.202
BE PRE PTSR 0.183 1.367 0.178
Note: Linear multiple regression on La
max
and HR in response to potential renal acid load sum value (
P
PRAL),
overall fluid intake (
P
fluid), overall caloric intake (
P
CAL), urinary pH (pH
u
), baseline blood pH value (pH
b
PRE
PTSR), baseline blood [HCO3−] ([HCO3−] PRE PTSR), and baseline BE (BE PRE PTSR); (n=60). * p≤0.05.
4. Discussion
The central aim of this study was to determine the effect of an alkalizing versus acidizing diet on
a single bout of high-intensity exercise performance represented by PTSR test performance outputs,
maximum capillary blood lactate concentrations, blood gas parameters, HR, rating of perceived
exertion, and urinary pH in moderately trained young participants under normoxic conditions and
after 12 h of exposure to a simulated altitude of 3000 m above sea level. As such, the main finding of the
study was that alkalizing or acidizing diets had no significant influence on PTSR-related performance
outputs and associated physiological responses, regardless of a high impact of the dietary interventions
on acid-base balance.
We assumed an adequate implementation of the dietary intervention because overall PRAL
values, which represent the acid- or base-forming potential of consumed nutrients, differed
significantly between the ACID and BASE conditions. Positive PRAL values reflect an excess
of acid-forming, acidizing potential, whereas negative values reflect an excess of base-forming,
alkalizing potential
[49,53]
, and we found significantly higher PRAL values for ACID conditions
compared with BASE conditions in the present study. Thus, we conclude that our specific instructions
for the modification of the participants’ habitual diets were understandable and feasible for the
study participants, and that the dietary interventions were able to be included in a daily routine.
The conclusion of a successful dietary modification is supported by significantly increased pH
u
values
during the BASE trials, in contrast with the ACID trials. In a recent study, pH
u
was used as a
surrogate marker for a successfully-conducted dietary intervention, and in general, a pH
u
of
≥
7.0 was
proposed for successful alkalizing diets and
≤
6.0 for acidizing diets [
48
,
61
]. Thus, we assume that
the significant increase in pH
u
values in the present study represents a profound impact on acid-base
balance because of the alkalizing or acidizing diets. In addition, the impact of the dietary interventions
on acid-base balance can be estimated by blood gas analysis parameters, and an increase in [HCO3−]
concentration and elevated pH
b
are both found after acid-base manipulation with ergogenic aids such
as NaHCO3[40,41].
A few recent studies have suggested that alkalizing diets are unable to produce the same severe
effect on acid-base balance and blood buffering capacity compared with alkalizing ergogenic aids [
55
,
67
].
However, the present study showed significantly increased pH
b
, [HCO
3−
], and BE values for the
BASE condition compared with the ACID conditions, indicating a higher alkalotic state prior to PTSR
exercise testing for the BASE trials. It was suggested that metabolic manipulation of the acid-base

Nutrients 2020,12, 688 12 of 18
balance by NaHCO
3
ingestion enhances anaerobic exercise performance by increasing the availability
of [HCO
3−
], thereby strengthening the physiochemical processes of buffering capacity (e.g., stimulation
of the lactate/[H
+
] cotransporter) and leading to increased removal of [H
+
] during exercise [
32
,
40
,
42
].
The suggested mechanism underlying the increased [H
+
] efflux from the intracellular to extracellular
compartments involves increased removal of [H
+
] from the extracellular buffering systems [
40
,
41
],
as well as improved protection of intramuscular pH and increased anaerobic energy provision and
glycogen utilization [
66
,
68
]. Therefore, this leads to the assumption that the higher alkalotic state prior
to exercise for the alkalizing diet trials within the present study would result in higher performance
outputs in the PTSR trial.
However, despite an apparent influence of the dietary intervention on acid-base balance parameters
and blood buffer capacity, the alkalizing or acidizing diets had no significant effect on PTSR-related
performance parameters (PF, MF, and FI), or on the associated physiologic responses of La
max
and
HR. It was previously reported that pre-alkalization prior to exercise had an ergogenic effect for
anaerobic exercise performance under normoxic [
32
,
40
,
42
] and hypoxic conditions [
32
,
35
–
37
,
43
–
45
].
However, whereas NaHCO3ingestion is a well-established method for an enhancement of anaerobic
performance, the influence of an alkalizing diet on anaerobic exercise performance is still controversially
discussed [
67
] and some investigations reported for less pronounced systemic alkalinity, blood buffer
capacity, and an unaffected anaerobic exercise performance after an alkalizing diet [
56
–
58
]. The present
study contributes to this negative assumption as we found no differences in any of the PTSR-related
parameters for the ACID or BASE trials under either normoxic or hypoxic conditions. In addition,
we assumed that the hypoxia-induced declines in high-intensity, anaerobic exercise performance
would appear under normobaric hypoxic conditions, because a significant impairment of anaerobic
exercise performance was previously reported [
20
–
25
], and as a reduced [HCO
3−
] concentration and
accompanying acidification of extracellular fluids as a consequence of the renal compensation to
hypoxia-induced respiratory alkalosis was reported to negatively affect exercise performance at altitude,
particularly above the lactate threshold [
10
,
16
–
19
]. In the present study, we observed significantly
reduced PO
2
,PCO
2
, S
a
O
2
, and [HCO
3−
] values after 12 h of exposure to a simulated altitude of
3000 m, indicating a hypoxia-induced respiratory alkalosis. However, a respiratory alkalosis is typically
associated with elevated pH
b
values, which we did not observe. This lack of effect on pH
b
may be
attributed to an ongoing renal compensation of the respiratory alkalosis with subsequent [HCO
3−
] loss
and restoration of pH
b
to normal. However, this assumption should be treated with caution because
we did not perform hourly acid-base analysis under hypoxic conditions, and our data do not allow for
direct deduction of a [HCO
3−
] loss and pH
b
stabilization based on the lack of a significant increase in
pH
b
. Nevertheless, the apparent discrepancies in anaerobic performance outputs and expected diet- or
hypoxia-induced changes may be attributable to several factors, as detailed below.
First, we observed a reduced caloric intake for the BASE trials compared with the ACID trials,
despite food recommendations for an adequate energy intake during the BASE trial. A caloric
deficit during consuming alkalizing diets was previously reported [
59
], and alkalizing dietary
recommendations are presumed for caloric deficits [
69
]. When consuming alkalizing diets, increasing
the consumption of fruits and vegetables, and minimizing consumption of protein (e.g., meats, cheese)
and carbohydrate sources (e.g., grains such as bread or pasta) [
54
], are often suggested to achieve
low PRAL values. It is well established that an alkalizing diet makes it difficult to maintain the high
caloric intake necessary to meet the high energy demands, and the requirement for dietary protein
and carbohydrate sources, reported for sport disciplines with a high anaerobic contribution of energy
production [
53
,
54
,
56
]. In particular, an influence of carbohydrate intake on exercise performance with
high anaerobic demands was previously reported [
70
,
71
]. We provided ad libitum breakfast prior to the
PTSR tests but omitted to standardize caloric and carbohydrate intake during breakfast. This may have
resulted in individual differences in glucose and glycogen availability and an influence on performance
data, and should therefore be considered as a limitation of this investigation. Furthermore, within
the present study the caloric deficit and associated reduction in carbohydrate intake under BASE

Nutrients 2020,12, 688 13 of 18
conditions may have mitigated the ergogenic effects of the pre-alkalization. Indeed, consumption of
carbohydrate-rich vegetables and fruits, such as fresh and dried fruits, fruit juices, and potatoes, was
highly advised to participants when specific instructions for the nutritional modification were explained
prior to the test trials [48]. However, in that study, despite a high commitment for implementation of
dietary instructions, participants were not able to maintain caloric intake during the BASE trials. Thus,
future studies should focus on completion of food diaries, as well as a rigorous control of food intake
using daily contact with a dietician to provide specific and individual food suggestions. Additionally,
the use of mineral waters rich in [HCO
3−
] should be encouraged to simplify achieving an alkalizing
diet while maintaining the high-energy diet required for anaerobic exercise performance [53,72,73].
Second, we examined a single bout of anaerobic exercise performance using the PTSR test.
The PTSR test was selected because it is simple to setup, requires minimal space, and does not involve
heavy and unwieldy equipment. These aspects are important when planning for investigations in
altitude field settings. Field investigations assessing exercise performance during mountaineering
tours and high-altitude expeditions may require the test equipment to be carried, and the anaerobic
testing to be performed in restricted spaces (e.g., a mountain hut). Thus, the PTSR test is one of only a
few tests feasible for the investigation of anaerobic exercise performance in altitude field conditions [
62
].
Other test procedures for the assessment of anaerobic exercise performance in the laboratory or field
settings include evaluation of repeated sprint and intermittent sprint performance [
74
–
76
]. In this
context, a recent review suggested that a single sprint of running or cycling activities in the laboratory
environment of a hypoxic chamber is unaffected by acute exposure to normobaric hypoxia [
77
], while
larger alterations in sprint outputs were found for repeated sprints or continuous high-intensity exercise
lasting longer than 45 s [20,24,32,77]. Additionally, running performance is impaired for single bouts
of performance in running distances of 800 m or longer when competing at altitudes above 1000 m [
5
].
This difference in anaerobic performance outputs may relate to the relatively low contributions of
energy from aerobic metabolism required for efforts of short durations (<45 s), and thus the larger
anaerobic contribution to the total energy requirement [
78
]. Aerobic energy availability for sprinting is
reduced in oxygen deprived environments [
79
,
80
]. Therefore, whereas performance maintenance for
single sprints of a short duration in hypoxic conditions is attributed to increased rates of anaerobic
energy release that compensate for the reduced aerobic energy production, anaerobic exercise efforts
of longer durations or multiple bouts are more affected by hypoxic conditions because of the higher
aerobic energy contribution [
25
,
27
,
77
]. We assumed that a test duration of 60 s was sufficient for
optimal assessment of continuous exhaustive anaerobic exercise performance as the aerobic/anaerobic
energy contribution for a 400-m event usually lasting between 50–70 s was calculated as 41% or 59%,
respectively [
81
]. However, the lack of differences in performance outputs within the present study
may among others relate to the applied exercise test protocol, and future investigations may further
contribute to the still controversially discussed topic of impaired anaerobic exercise performance in
hypoxia using different test protocols including assessments of all-out running for longer durations up
to 3 min or repeated sprint performance.
The theory of strong ion difference (SID) may also explain the unexpected lack of an ergogenic effect
of the alkalizing diet [
82
]. Our findings were based on the Henderson–Hasselbalch approach, which
presumes that blood pH is determined by changes in [H
+
] and [HCO
3−
]. However, the contrasting
SID theory incorporates intracellular and extracellular ions, and describes the difference between the
concentrations of strong cations (sodium, potassium, calcium, and magnesium) and strong anions
(lactate and chloride). The SID was also suggested to affect muscle performance by altering intracellular
or extracellular pH because of an independent effect on blood pH [
82
]. The SID approach may therefore
explain the increase in pre-PTSR [HCO
3−
] and BE for the BASE conditions with simultaneously
persistent pH
b
in normoxia. Thus, acidizing dietary interventions may have had a positive impact
on intracellular and extracellular ions, and following muscle performance, regardless of changes in
[H
+
] and [HCO
3−
]. However, this conclusion should be interpreted with caution because no SID

Nutrients 2020,12, 688 14 of 18
measurements were conducted in the present study. Thus, future studies are required to examine the
influence of changes in the SID on anaerobic exercise performance under hypoxic conditions.
A low statistical test power is a common study limitation used to explain a lack of expected
effects. Although an a priori analysis was performed prior to the present investigation, the number of
15 participants is still a small sample size and may result in small test power for statistical analyses.
Thus, we reported our effect sizes, and found medium to large effect sizes for
P
CAL, PRAL, pH
u
, PF,
MF, FI, La
max
,PO
2
,PCO
2
, S
a
O
2
, pH
b
, [HCO
3−
], and BE, ranging between
η
p
2
=0.088 and
η
p
2
=0.941.
These data indicate sufficient testing power for analyzing the effect of an alkalizing or acidizing dietary
intervention and normobaric hypoxic conditions on these parameters. Thus, we conclude that our
sample size of 15 participants was sufficient to detect possible differences in the investigated dietary,
PTSR-related, and BGA-related parameters, and to exclude a type 2 error within our interpretation.
5. Conclusions
We provide novel data on the effects of an alkalizing or acidizing dietary intervention on anaerobic
exercise performance under normoxic or hypoxic conditions after 12 h of exposure to a simulated
altitude of 3000 m. Our principle finding was that dietary intervention significantly increased the blood
buffer capacity, represented by pre-exercise [HCO
3−
] and BE values, but did not affect PTSR-related
exercise performance outputs or associated physiologic parameters. A higher alkalotic state of
the acid–base balance prior to exercise under hypoxic conditions is often associated with higher
anaerobic performance outputs and higher maximum blood lactate values after high-intensity exercise
in normoxic and hypoxic conditions. Explanations for the apparent lack of any ergogenic effect of
pre-alkalization caused by an alkalizing diet include a reduced caloric intake for the BASE trials
compared with the ACID trials, the duration of the 60-s portable tethered sprint test and the associated
energy contributions, and possible changes in intracellular and extracellular ions other than [H
+
]
and [HCO3−].
Author Contributions:
Conceptualization, M.L. and P.P.; methodology, M.L. and P.P.; validation, M.L., M.d.M. and
P.P.; formal analysis, M.L.; investigation, M.L. and J.S.; resources, P.P.; data curation, M.L.; writing—original draft
preparation, M.L.; writing—review and editing, M.L., M.d.M. and P.P.; visualization, M.L.; supervision, M.d.M.
and P.P.; project administration, M.L. All authors have read and agreed to the published version of the manuscript.
Funding: The APC was funded by the DFG Open Access Publication Funds of the Ruhr-University Bochum.
Acknowledgments:
We thank all subjects for participating in this study, our laboratory stafffor contributions and
support, and Edanz Group (https://en-author-services.edanzgroup.com/) for editing a draft of this manuscript.
Dataset:
All datasets generated for this study are available from the figshare repository database
(doi:10.6084/m9.figshare.11534547).
Conflicts of Interest: The authors declare no conflict of interest.
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