Chinese Journal of Physiology

: 2020  |  Volume : 63  |  Issue : 1  |  Page : 1--6

Sex-related differences in sudomotor function in healthy early twenties focused on activated sweat gland density

Tae-Hwan Park1, Jeong-Beom Lee2, Hye-Jin Lee2, Bahda Yun3,  
1 College of Medicine, Soonchunhyang University, 366-1 Ssangyong-dong, Cheonan 31151, Republic of Korea
2 Department of Physiology, College of Medicine, Soonchunhyang University, 366-1 Ssangyong-dong, Cheonan 31151, Republic of Korea
3 College of Arts and Sciences, Case Western Reserve University, Cleveland, OH 44106, USA

Correspondence Address:
Prof. Jeong-Beom Lee
Department of Physiology, College of Medicine, Soonchunhyang University, 366-1 Ssangyong-dong, Cheonan 31151
Republic of Korea


The purpose of this study was to quantitatively assess the difference in sudomotor function between healthy males and females in their early twenties by measuring skin surface area and activated sweat gland density (ASGD). The quantitative sudomotor axon reflex test (QSART), a method for evaluating autonomic nervous system activity, was used for quantification. In QSART, the sweat glands are activated directly or indirectly by the subcutaneous application of neurotransmitters, such as acetylcholine, through iontophoresis. This series of mechanisms is called the sudomotor axon reflex. After recording age, height, weight, and several measurements of the forearm, QSART was performed on 101 healthy controls aged 21–26 years to measure ASGD. The mean temperature and humidity on the measurement days were 11.4°C and 58.1% on May 3, 2018, and 14.7°C and 70.3% on May 10, 2018. The result of independent sample t-test showed higher ASGD in women (P < 0.05). The body surface area and the surface area of the forearms were higher in men (P < 0.001), but the number of activated sweat glands was not significantly different according to sex. The activated sweat gland counts of the body and forearms were analyzed through linear regression by age for males and females. Except for the activated sweat gland count of the male body, the analysis showed a tendency to decrease with increasing age but was not statistically significant in any case (P > 0.05). Showing insufficient coefficient of determination (R2), multiple regression analyses with sex and ages did not correct this insignificance between age and activated sweat gland count.

How to cite this article:
Park TH, Lee JB, Lee HJ, Yun B. Sex-related differences in sudomotor function in healthy early twenties focused on activated sweat gland density.Chin J Physiol 2020;63:1-6

How to cite this URL:
Park TH, Lee JB, Lee HJ, Yun B. Sex-related differences in sudomotor function in healthy early twenties focused on activated sweat gland density. Chin J Physiol [serial online] 2020 [cited 2020 Feb 26 ];63:1-6
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Full Text


On the surface of the human body, there are 3–4 million sweat glands under control of sympathetic nerves which secrete sweat in volumes ranging from several liters to 10 L/day.[1],[2] The number and function of the sweat glands are determined by several factors, including age, sex,[3],[4] body part, and climate.[5],[6] When temperature stimuli received through the heat receptors are transmitted to the central nervous system, the cerebral cortex recognizes this signal. At the same time, the thermoregulatory center regulates sweat secretion through the autonomic nervous system.[7],[8],[9] Since it is well known that autonomic nervous function is reduced by aging, sudomotor function could also be expected to be reduced if it follows the mechanism above. Assessment of this sweating response in the human body through specific procedures such as thermoregulatory sweat testing and the quantitative sudomotor axon reflex test (QSART)[10] can result in indirect but considerable testing of autonomic function.

QSART was used in this study, in which quantitative evaluation of acetylcholine (ACh) sensitivity of the sweat glands was performed through iontophoresis.[1],[2],[5],[11],[12] Dry sauna, heat bath, and exercise have been commonly used as thermal stimuli to induce sweating even though they required many labors. However, in QSART, simple cholinergic stimulation can directly activate the muscarinic receptors of the sweat glands and the nicotinic receptors on the nerve endings distributed in the sweat glands. Interestingly, the latter generates antidromic signal and activates neighboring sweat glands through the other branches of the same axon. So-called axon reflex can be analyzed through QSART [Figure 1]. In this case, the neurotransmitter indirectly activates the sweat glands of AXR (indirect activated sweating, black dotted arrows in [Figure 1]).[3],[13],[14]{Figure 1}

Sweating activity of AXR (indirect activated sweating by muscarinic receptor-mediated sweat activity) induced by ACh applied iontophoretically. Sweating activity of DIR (direct activated sweating by muscarinic receptor-mediated sweat activity) induced by ACh applied iontophoretically.[3],[14],[17]

Neurophysiological changes and differences are one of the most critical factors in numerous neurologic diseases and therefore have been researched for decades. Various attempts have been made to reveal physiologic and pathologic variation of the human nervous system status. Although there have often been studies of differences in the output, onset, and density of activated glands between specific population or features,[1],[5],[15],[16],[17],[18],[19] few studies have explained how the physiological variation in activated sweat gland density (ASGD) between males and females was made. To evaluate and explain the sex-related difference of ASGD, we performed QSART in addition to physical measurements in healthy twenties, of which their body condition is at peak. We think that by quantifying the number, distribution, and function of the sweat glands according to the biological differences in each individual body, a useful model for sudomotor function in a healthy body can be constructed and be used for clinical diagnosis. In this context, this research is a step forward in building the model by collecting additional quantification data.

 Materials and Methods


One hundred and one healthy participants (64 males and 37 females) participated in the experiment at the College of Medicine of Soonchunhyang University in Cheonan (36°48'N, 127°06'E). We confirmed that there were no major underlying conditions such as heart disease, diabetes, hypertension, as well as diseases that could directly affect the experiment, such as neuropathy or skin disease. The average temperature and humidity on the measurement days observed at an unmanned weather station were 11.4°C and 58.1%, respectively, on May 3, 2018, and 14.7°C and 70.3%, respectively, on May 10, 2018. These participants were asked to refrain from caffeine, smoking, alcohol, medication use, and exercise 48 h before the test. Each participant provided written informed consent to participate in the study after being thoroughly acquainted with the purpose and experimental procedures as well as any potential risks. Participants were notified that they could stop the experiment at any time if they feel pain or intolerable sensations. Mild tingling sensation was often reported as electricity was used for iontophoresis, but it did not last more than 5 min after the end of the procedure. Furthermore, there were no suspected symptoms of hypersensitivity reactions such as wheal-flare reaction and respiratory distress. This work was supported and supervised by the Soonchunhyang University Research Fund (approval no. 20190017), complying with the 2013 Declaration of Helsinki of the World Medical Association and the experimental protocol from the University of Soonchunhyang Research Committee.


A 10% aqueous ACh chloride solution was used as a neurotransmitter for the quantification of sweat secretion by the QSART. Because ACh is positively charged in aqueous solution, it is not delivered to the sweat glands when directly applied to the skin without a special method. Therefore, an electric circuit was used to perform iontophoresis [Figure 2]. In order to measure the number of sweat glands using the sweat secreted from the activated glands, iodine-impregnated paper, which changes a blue color upon reaction with sweat, was used.[20]{Figure 2}

Measurements and procedures

Measurements were performed between May 3 (51 participants) and May 10 (50 participants), 2018. Both experiments were performed between 14:00 and 17:00 to minimize the effect of circadian rhythm.[21] During age, sex, height, and body weight were being recorded before QSART, participants were told to rest more than an hour at room temperature to minimize the effects of physical activity and heat acclimation. Then, the body surface area (BSA) and forearm surface area (FSA) were calculated. The former was calculated from the height and body weight using the Du Bois formula,[22] and the latter was estimated from the length and circumference of the forearm using an improvement of a preexisting method [Table 1].[23]{Table 1}

In this method, a cotton soaked with 1 mL of 10% ACh chloride was placed in the slit of the QSART capsule (anode) and the capsule was attached on anterior of the thickest part of the forearm with the reagent touching the skin. A flexible plate electrode (cathode) was placed 10 cm distal to the capsule. If the cathode is too far away, adjusting the current can be difficult. An ammeter was used to make a current of 2 mA constantly flow for 5 min while performing the ACh iontophoresis [Figure 2]. The unit was removed and the moisture was wiped away from the area of the capsule. Iodine-impregnated paper was put on the area and pressed firmly. The activated sweat glands appeared as blue-colored points [Figure 3]. As shown in [Figure 3], the number of stained points in an area corresponding to a square of 0.5 cm × 0.5 cm at the site where direct activated sweating by muscarinic receptor-mediated sweat activity (DIR) sudomotor activity occurred were counted. Care was taken not to touch the paper with bare hands to prevent increase in size of colored points due to secretions.{Figure 3}

Statistical analysis

The age of the participants was calculated in Korean style; one is considered 1 year old immediately after his or her birth. For accurate analysis, age was expressed in decimals, considering year, month, and day. Measurements were expressed as the mean ± standard deviation. Statistical values of 101 samples and independent sample t-tests were performed using Microsoft Excel, and linear regression analysis and multiple regression analysis conducted according to age and sex were calculated using IBM SPSS statistics for Windows, Version 24.0 (IBM Crop., Armonk, NY, USA). P < 0.05 was considered statistically significant.


In sex-specific differences, the ASGD was lower in males than in females by 12.87 count/cm2 (females: 131.62 ± 32.82 count/cm2 and males: 118.75 ± 34.25 count/cm2) [P < 0.05; [Figure 4]. Compared to females, the male BSAs and FSAs were each 0.30 m2 and 105.21 cm2 higher [P < 0.001; [Figure 5]. The number of total activated sweat glands and forearm activated sweat glands were obtained by multiplying the ASGD by the BSA and FSA, respectively. Body surface and forearm sweat gland counts were both higher in the male group but were not statistically significant [P > 0.05; [Figure 5]. The number of activated sweat glands in the body and forearms was analyzed by linear regression according to the age of each male and female. With the exception of the male body, the counts only showed a tendency to decrease with increasing age but were not statistically significant in any case [P > 0.05; [Figure 6]. Based on the above results for ASGD and sweat gland counts, however, we tried to correct the insignificance of the correlation between age and the count by multiple regression analysis using gender and age as independent variables. However, this too was statistically insignificant showing low coefficient of determination (R2).{Figure 4}{Figure 5}{Figure 6}


The ASGD among the study participants in their early twenties showed sex-specific differences. Although the total activated sweat gland counts and the forearm activated sweat gland counts did not show significant differences between men and women, the BSAs and FSAs were larger in men [Figure 5]. The anatomical development of sweat glands is completed within 2.5 years after birth.[1],[2] It is implied that growth determines the difference in ASGD between the sexes through the fact that the ASGD was different in adult men and women and was confirmed through QSART conclusively. This is consistent with results from previous experiments using heat stimulation (central regulation) and QSART (peripheral stimulation)[15],[16],[24],[25] which supports the association of ASGD with physical factors, including the body size and shape of men and women. If the same study was conducted with children before the formation of secondary sex characteristics (6–12 years old), we may be able to speculate further. Since 6–12 years old is the time when physical differences between boys and girls intensify, we may be able to see whether the ASGD difference is due to body volume differences or sex chromosome activity. Interestingly, one study that measured the sweat rate of male and female participants before and after puberty concluded that the difference was due to gene expression induced by androgens.[26]

The association with age lacked statistical significance and was within the expected limits. However, the integration of this study with the results of previous studies can confirm the association. In a previous study in the same laboratory, QSART was performed for participants aged 37–79 years.[17] This study of participants in their twenties (females: 131.62 ± 32.82 count/cm2 and males: 118.75 ± 34.25 count/cm2) fits the linear relationship between age and ASGD derived at that time (approximately 127 count/cm2, roughly calculated by assigning 22.56, the mean age of this study), so further analysis of age may be attempted. Related meta-analysis can be precisely conducted at the next opportunity, and this time we focused on the differences according to gender. The decrease in ASGD on the body and the forearms with aging seems to be due to the decrease in the number of sweat glands[27] and the autonomic system nervous activity[28] involved in the sweating mechanism. In addition, the ASGD divided by the sweat gland density can be an important clinical physiologic indicator. Since the number of sweat glands activated by thermal stimulation or neurotransmitters is different from the number of actual sweat glands identified by histological analysis,[29],[30] there is a strong possibility that the changes due to aging are also likely to be different.

According to the independent sample t-test, the differences in BSA and FSA were significant from those of the other measurements. This is because these statistical values were measured using a tape measure, while the ASGD was measured using the QSART and iodine-impregnated paper, the latter of which is based on counting points directly by eye. Calculating the entire body or forearm sweat gland counts from the local gland distribution in only 0.25 cm2 can also impart errors.

The study had some limitations. First, the total activated sweat gland count was estimated using the ASGD of the forearm, which would be different from the actual value. However, regions such as the forearm, back, face, chest, and scalp show different ASGDs even for the same human body.[5],[31],[32] Furthermore, while differences in the distribution of sweat secretion rates by sex have been studied,[33] additional studies are needed to determine whether the ASGD also varies. Therefore, calculating the sweat glands on the whole-body surface of about 2 m2 makes an inevitable error. An accurate measure is virtually impossible until a new measurement method is developed. Second, minimization of the number of people making the measurements was not completely achieved due to labor and time problems. ASGD measurements from more than one person may cause errors. One study tried to counted dots on iodine-impregnated paper using computer-assisted analysis and pointed out that the results obtained by human eyes and the computer were similar.[20] However, still there is no report on which of the two methods is more accurate. Moreover, errors may appear not only in counting sweat gland with bare eyes but also in obtaining iodine-impregnated paper due to variable pressing force, pressing time, and degree of cleansing after iontophoresis. This is the biggest problem with the reproducibility of this experiment, and we look forward to work on standardization and automation of the measurements. Finally, the age of the subject group was limited to the early twenties. The age group of 22–23-year-olds accounted for 75% of the total study population, and the number of older participants decreased sharply. This increased the influence of older group measurements on the statistics, but they were less represented. As a result, the effect of age on the ASGD was seen only as a trend and was not statistically significant. This is because the initial goal of this study was to focus on the ASGD differences according to the sex of participants in their early twenties. If we were to concentrate on the ASGD changes with age, as in previous research,[17] we would have recruited participants evenly at various ages. However, if we had known at the planning stage that age-based analyses would be valuable and recruited similar numbers of participants at each age, we might have seen significant results, even within the early twenties.


In conclusion, identifying the relationship between ASGD, sex, age, and health status will allow us to devise a noninvasive test method for the evaluation of autonomic nervous function or the diagnosis of skin disease. From a clinical perspective, the application of biological information which varies with sex and age requires a large data pool. The result of this study highlights the necessity for subsequent data collection.


The authors extend their thanks to the individuals whose participation made this study possible. This study was financially supported by the Soonchunhyang University Research Fund (No. 20190017).

Financial support and sponsorship

This study was financially supported by the Soonchunhyang University Research Fund (No. 20190017).

Conflicts of interest

There are no conflicts of interest.


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