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Chronobiology InternationalThe Journal of Biological and Medical Rhythm Research

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Exposure by males to light emitted from mediadevices at night is linked with decline of spermquality and correlated with sleep quality measures

Amit Green, Shlomi Barak, Lior Shine, Arik Kahane & Yaron Dagan

To cite this article: Amit Green, Shlomi Barak, Lior Shine, Arik Kahane & Yaron Dagan (2020)Exposure by males to light emitted from media devices at night is linked with decline of spermquality and correlated with sleep quality measures, Chronobiology International, 37:3, 414-424,DOI: 10.1080/07420528.2020.1727918

To link to this article: https://doi.org/10.1080/07420528.2020.1727918

Published online: 04 Mar 2020.

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Exposure by males to light emitted from media devices at night is linked withdecline of sperm quality and correlated with sleep quality measuresAmit Green a,b, Shlomi Barakc,d, Lior Shinee, Arik Kahanef, and Yaron Dagana,b,g

aThe Sleep and Fatigue Institute, Assuta Medical Center, Tel Aviv, Israel; bThe Research Institute of Applied Chronobiology, The AcademicCollege of Tel-Hai, Israel; cReproductive Services, Assuta University Hospital, Ashdod, Israel; dBen-Gurion University of the Negev, Be'er-Sheva, Israel; eThe Andrology Laboratory, Assuta Medical Center, Rishon Le-Zion, Israel; fThe IFV Unit, Assuta Medical Center, Rishon Le-Zion,Israel; gThe Human Biology Department, Haifa University, Haifa, Israel

ABSTRACTThe last several decades have been characterized by the widespread usage of digital devices,especially smartphones. At the same time, there have been reports of both decline in sleep durationand quality and male fertility decline. The aim of this study was to assess the relationship betweenevening exposure to the light-emitting screens of digital media devices and measures of both sleepand sperm quality. Semen samples were obtained from 116 men undergoing fertility evaluation forthe following sperm variables: volume (mL), pH, sperm concentration (million/mL), motility percen-tage (progressive% + non-progressive motility%), and total sperm count. Exposure to the screens ofelectronic devices and sleep habits was obtained bymeans of a questionnaire. Smartphone and tabletusage in the evening and after bedtimewas negatively correlatedwith spermmotility (−0.392;−0.369;p < .05), sperm progressive motility (−0.322; −0.299; p < .05), and sperm concentration (−0.169;p < .05), and positively correlated with the percentage of immotile sperm (0.382; 0.344; p < .05). Inaddition, sleep duration was positively correlated with sperm total and progressive motility (0.249;0.233; p < .05) and negatively correlated with semen pH (−0.349; p < .05). A significant negativecorrelation was observed between subjective sleepiness and total and progressive motility (−0.264;p < .05) as well as total motile sperm number (−0.173; p < .05). The results of this study support a linkbetween evening and post-bedtime exposure to light-emitting digital media screens and spermquality. Further research is required to establish the proposed causative link and may lead to thefuture development of relevant therapeutic and lifestyle interventions.

ARTICLE HISTORYReceived 25 December 2019Revised 4 February 2020Accepted 5 February 2020

KEYWORDSSleep; sleepiness; digitaldevice; light; melatonin;sperm quality; male fertility;ALAN

Introduction

Significant sperm concentration decline has beenreported over the last decades in Western andindustrialized countries, while studies from non-Western countries showed no such trend (Levineet al. 2017). Various factors have been attributed tothis sperm quality decline, such as obesity, envir-onmental toxins (e.g. pesticides, air pollution, etc.),mobile phone radiation, and stress (Adams et al.2014; Chiu et al. 2015; Jurewicz et al. 2009; Krausz2011; Lafuente et al. 2016; Macdonald et al. 2013;Nordkap et al. 2016, 2012; Sharma et al. 2013).Concomitant with this decline in sperm quality isthe increased availability of digital media devices,namely televisions, desktop and laptop computers,tablets, and smartphones. Tablets and smart-phones, in particular, are electronic media devicesthat are developed to be portable, multi-functional,

and useful for various everyday tasks, such ascommunication, work, games, entertainment, andsocial media.

Exposure to bright light has increased exponentiallyespecially in the western countries of the world due tounintentional exposure to illumination from electronicscreens that emit light directly into the eyes. Millions ofcomputers, tablets, televisions, and especially smartphonesare bought worldwide each month, and the usage time ofthese devices is constantly increasing, including in theevening and at night shortly prior to sleep onset. Nineout of ten subjects (90%) reported using a digital mediadevice within 1 h before sleep in the “2011 Sleep inAmerica” survey (Gradisar et al. 2013). Several studiesreported negative physiological outcomes related to digitalmedia screen artificial light at night (ALAN) exposure.Short wavelength light (SWL) emitted from the screens ofelectronic devices can inhibit melatonin (MLT) secretion

CONTACT Amit Green amitg@assuta.co.il The Sleep and Fatigue Institute, Assuta Medical Center, 96 Yigal Alon Street, Tel Aviv 67891, Israel

CHRONOBIOLOGY INTERNATIONAL2020, VOL. 37, NO. 3, 414–424https://doi.org/10.1080/07420528.2020.1727918

© 2020 Taylor & Francis Group, LLC

(Chang et al. 2015; Higuchi et al. 2005; Wood et al. 2013)and disturb thermoregulation (Green et al. 2017; Higuchiet al. 2005). It can also have negative impact on sleepphysiology and sleepiness measures (Custers and Vanden Bulck 2012; Figueiro et al. 2011; Green et al. 2017;Nathan and Zeitzer 2013; Wood et al. 2013), cognitiveperformance (Cajochenet al. 2011), andmood (SroykhamandWongsawat 2013).

The relationship between exposure to SWL lightemitted from digital screens and sperm quality has notbeen previously explored, and only a few studies haveevaluated the relationship between sleep disorders andsemen quality. Two recent studies assessing young menfrom the general population reported an inverseU-shaped association between self-reported sleep distur-bances and semen quality (Chen et al. 2016; Jensen et al.2013), indicating that sleep duration may play a role inthe regulation of the male reproductive process.

The aim of this study is to assess the relationshipbetween exposure to digital media device screensand measures of sleep and sperm quality. Themajor hypothesis is; explored herein is exposure toALAN from digital media devices in the evening andnight is negatively correlated/with sperm quality.

Methods

Participants

One hundred and thirty Men referred to the IVFunit in Assuta Medical Center, betweenSeptember 2018 and August 2019, were recruitedto this study and provided written informed con-sent to participate. As part of the routine stan-dard of care, they were sent to semen evaluationin the andrology lab. Fourteen participantsreported working night shifts and were excludedfrom the study. A total of 116 male adults agedbetween 21 and 59 (35.2 ± 7.2) were included inthe study. 71% percent of participants were mar-ried, 19% single, 4% divorced, and 6% ina relationship. All participants were normallydiurnally active Hebrew-speaking residents ofthe state of Israel. Participants completed thequestionnaires in the presence of a research assis-tant. The study was approved by the AssutaMedical Center institutional ethical reviewboard. The experimental protocol of the studyconfirms all ethical standards of biologicalrhythms research (Portaluppi et al. 2010).

Procedure

A single semen sample was collected from each partici-pant after an abstinence period of 2–7 days. Semensamples were collected by masturbation into 120-mlsterile polystyrene wide-mouth cup in a room adjacentto theAndrology laboratory. Participants were instructedto capture the first part of the ejaculate in the process ofsample collection and to avoid any collection of spilledsemen. Samples were analyzed within 1 h of ejaculation.Semen analysis was performed according to WorldHealth Organization criteria (WHO) in adherence tothe Laboratory Manual for the Examination andProcessing of Human Semen (2010).

The Semen analysis was viewed undera microscope (Olympus BX-41) at a magnificationof 20x using a Makler counting chamber. The spermmorphology was viewed under a microscope(Olympus BX-41) at a magnification of 100x.Semen volume was measured by serological pipette,and sperm concentration was assessed usinga Makler counting chamber. The Makler chamberwas designed specifically for the determination ofsperm concentration and motility in undilutedsemen. It has a reported depth of 0.01 mm. Thegrid area in the center of the coverslip is 1 mm ×1mm and is divided into 100 smaller squares, each ofwhich is 0.1mm× 0.1mm. A 10 μL volume of semenor sperm suspension was loaded into the chamber,and, in order to ensure consistent counting,a minimum of 100 sperms were counted in eachchamber.

Measured variables

Sperm variablesThe following variables were taken into consideration:complete liquification, color, viscosity, volume (mL),sperm concentration (million/mL), and motility (%).Sperm motility was graded into total (progressive +non-progressive motility) and progressive motility.Total sperm count (volume × sperm concentration)was also calculated. Reference values from the WHOsemen analysis manual were used to assess spermconcentration and motility as described, in accor-dance with the most recent guidelines from theWorld Health Organization (2010). Sperm morphol-ogy was evaluated using Kruger’s strict criteria andESHRE monographs. An external quality control

CHRONOBIOLOGY INTERNATIONAL 415

program, created by the College of AmericanPathologists (CAP), was established in the laboratoryin order to control for random and systematic errorsand interlaboratory differences.

Demographic, health status, and sleep variables:Self-reporting questionnaires were utilized to obtaindemographic, general health, sleep patterning anddifficulties, and prevalence of and exposure patternsto digital media screen information. This question-naire was validated in Green et al. (2018).

(1) Demographic: age, gender, family status,education, and employment status, includ-ing shift work.

(2) General health: chronic diseases, prescriptionand non-prescription medications, height, andweight. The morning level of Concentrationand attention of participants was evaluated bya 9-point Likert scale in response to the state-ment “Please rate your level of concentration inthe morning.” All of the numbers have validpoint values, but only the odd numbers havedescriptions: 1 = “extremely poor concentra-tion”; 3= “not able to concentrate”; 5= “neutral,neither unable to concentrate or concentrate”;7 = “able to concentrate”; and 9 = “extremelygood concentration.” (Green et al. 2018).

(3) Sleep: The Pittsburgh Sleep Quality Index(PSQI) was applied to evaluate sleep timing,sleep onset latency, sleep duration, sleepdifficulties, and sleep quality. The PSQI isa self-reporting questionnaire that assessessleep quality over a 1-month time interval.The PSQI consists of 19 individual items,comprising seven components that producea single global score. The PSQI isa standardized sleep questionnaire for clin-icians and researchers to use with ease andfor multiple populations, and is used inmany research and clinical settings to diag-nose (Buysse et al. 1989). We used theKarolinska Sleepiness Scale (KSS) to assesssleepiness and tiredness. It is a 9-pointLikert scale, in which all of the numbershave valid point values, but only the oddnumbers have descriptions: 1 = “extremelyalert”; 3 = “alert”; 5 = “neither alert norsleepy”; 7 = “sleepy”; and 9 = “extremelysleepy” (Åkerstedt and Gillberg 1990).

(4) Exposure to screens of digital media devices:We asked the participants about the presenceand usage habits of digital media devicesequipped with a screen (television, computer,tablet, smartphone) and whether they hada television, computer, tablet, and/or smart-phone in their homes and bedrooms. Theyreported the duration of their exposure to digi-tal screens of any digital media device at dif-ferent times of day, from the morning untilafter bedtime, both during weekdays and onweekends. Participants were asked to reporttheir exposure time to screens of digitaldevices, giving the mean time in minutes foreach time of day, to enable calculation of theexposure summation (sum) for the differentperiods of the day: early morning, duringwork or study time, evening time until bed-time, and after bedtime. Digital media usagefor all devices (televisions, computers, smart-phones, and tablets) was derived through thesummation (sum in minutes) of each of thefour afore-defined periods of the day. We alsoderived an additional “sum-total,”a summation of the “sum-evening” and “sum-night” variables.

Statistical analysis

The paired t-test was applied to assess differencesin usage time of digital media devices betweenweekdays and weekends. Pearson/Spearman corre-lations were calculated between the variables in thestudy in order to identify significant variables totest for confounders. We calculated partial corre-lation between the variables in the study using theconfounder-variables (days of abstinence, age,marital status, and BMI), and we reported onlythose correlation coefficients that were significantunder the partial correlation test. We performedall statistical analyses using SPSS, version 25 (SPSSInc., Chicago, IL, USA).

Results

Exposure to screens of digital devices and usagepatterns

Fifty-eight participants (51%) reported that theyhad televisions in their bedrooms, and 28 (24%)

416 A. GREEN ET AL.

had computers in their bedrooms. Almost theentire sample, 115 participants (99%), had smart-phones, and 23 (20%) owned tablets. Televisionwas the digital media device most used in theevening, followed by smartphones, computers,and tablets (Table 1). By contrast, after bedtime,smartphones were the most used, followed by tele-vision, computers, and tablets. This pattern ofdigital devices uses in the evening and after bed-time was similar between weekdays and weekends.We did not detect significant differences in usagetime of digital devices between weekdays andweekends.

Sleep

Based on information obtained the PSQI, mean bed-time was 00:07 h (±11.0 min), mean time taken to fallasleep was 20.5 min (±16.6 min), mean wakeup hourwas 08:03 h (±11.4min), andmean sleep duration was6.5 h (±61.1 min). Table 2 presents the percentagefrequency distribution of the sleep complaints andsleep evaluation based on data of the PSQI

questionnaire. The most frequent complaints were“Wake up in the middle of the night or early morn-ing,” “Cannot get to sleep within 30 minutes,” and“others.” The majority of the participants reportedthat they sleep well (86.1%), while the rest complainedthat they sleep badly (13.9%).

Semen

Table 3 contains the mean (std) and CI-95% of thesemen analysis variables: volume, pH, total motilitypercentage, progressive percentage, non-progressivepercentage, immotile percentage, total motile spermnumber, total sperm number, and spermconcentration.

Associations between exposure time to screens ofdigital media devices and sperm qualityvariables

Total motility percentage was found to be negativelycorrelated with smartphone use in the evening andafter bedtime, tablet use after bedtime, the sum of

Table 2. Frequency distribution (in percentages) of each complaint in the PSQI questionnaire.Not during thepast month

Less thanonce a week

Once ortwice a week

Three or moretimes a week

Cannot get to sleep within 30 min 54.4 18.4 15.8 11.4Wake up in the middle of the night or early morning 44.9 18.1 19.0 18.0Have to get up to use the bathroom 57.0 14.9 13.2 14.9Cannot breathe comfortably 76.3 7.9 6.1 9.6Cough or snore loudly 73.7 7.0 7.9 11.4Feel too cool 84.8 8.9 1.8 4.5Feel too hot 72.6 12.4 12.4 2.7Had bad dream 73.2 17.9 7.1 1.8Have pain 78.4 9.9 5.4 6.3Other reasons 62.5 7.5 10.6 19.4During the past month, how often have you taken medicine to help yoursleep?

95.5 0 3.6 0.9

During the past month, how often have you had trouble staying awake whiledriving, eating meals, or engaging in social activity?

75.9 18.8 4.5 0.9

During the past month, how much of a problem has it been for you to keep upenough enthusiasm to get things done?

49.1 26.8 19.6 4.5

Very good Fairly good Fairly bad Very badDuring the past month, how would you rate your sleep quality overall? 32.2 53.9 11.3 2.6

Table 1. The mean exposure time in minutes and (±SD) to screens of digital media devices(televisions, smartphones, computers, and tablets) on weekdays and weekends in the eveningand after bedtime, as well as sum-evening and sum-after bedtime.

Weekdays Weekend

Evening After Bedtime Evening After Bedtime

Television 76 (± 61.2) 13 (± 27.8) 77 (± 68.3) 12 (± 24.0)Smartphone 67 (± 54.2) 22 (± 31.1) 58 (± 58.2) 15 (± 22.4)Computer 46 (± 70.0) 8 (± 30.2) 35 (± 62.8) 8 (± 25.6)Tablet 3 (± 12.5) 0.6 (± 3.1) 3 (± 14.4) 0.3 (± 2.4)Sum 192 (± 123.6) 44 (± 60.5) 173 (± 129.7) 35 (± 46.3)

CHRONOBIOLOGY INTERNATIONAL 417

exposure to screens after bedtime, and the sum of useof portable screens (tablet and smartphone) in theevening and after bedtime. The percentage of progres-sive sperm was found to be negatively correlated withsmartphone use in the evening and after bedtime,tablet use after bedtime, and the sum of use of por-table screens (tablet and smartphone) in the eveningand after bedtime. The immotile percentage of spermcorrelated positively with smartphone use in the eve-ning and after bedtime, the sum of use of portablescreens (tablet and smartphone) in the evening andafter bedtime, and the sum of exposure to screensafter bedtime. The total motile sperm number corre-lated negatively with smartphone use in the evening,tablet use after bedtime, and the sum of use of por-table screens (tablet and smartphone) in the eveningand after bedtime. Sperm concentration was alsofound to be negatively correlated with smartphoneuse in the evening, tablet use after bedtime, and tele-vision use in the evening. All correlation coefficientsare presented in Table 4. Significant correlations aremarked * = p < .05.

Associations between sleep duration, subjectivesleepiness, cognitive concentration ability, andsperm quality variables

Figures 1 and 2 present the frequency distributions ofsubjective sleepiness evaluations and levels of concen-tration in the morning for the sample. Two-thirds(65%) of the participants reported some level of con-centration disability in the morning, while one-third(32%) reported subjective sleepiness. Correlation ana-lysis (Table 4) revealed a significant positive correla-tion between sleep duration and percentage of totalmotility and percentage of progressive sperm, anda negative correlation with pH. We observed signifi-cant negative correlation between subjective sleepinessmeasured by the KSS and percentage of total motility,percentage of progressive sperm, total sperm number,totalmotile spermnumber, and age, as well as positivecorrelation with pH and percentage of immotile. Inaddition, we found that the concentration level isnegatively correlated with the percentage of totalmotility and percentage of progressive sperm, andpositively correlated with pH and immotile percen-tage. We did not observe significant correlationbetween BMI and any of the sperm variables.

Associations between exposure time to screens ofdigital media devices and sleep complaints, sleepquality, and subjective sleepiness

Correlation analysis revealed significant positive cor-relation between the complaint “Wake up in the mid-dle of the night” in the PSQI questionnaire and use of

Table 3. The mean (±SD) and confidence-interval 95% ofsemen samples.

Mean (±SD) CI-95%

Volume (ml) 3.3 (1.4) 3.0–3.6pH 8.4 (0.4) 8.3–8.5Total motility (%) 51.9 (16.1) 49.1–55.2Progressive (%) 34.3 (14.1) 31.9–37.2Non-progressive (%) 18.1 (10.2) 15.9–19.3Immotile (%) 46.7 (16.0) 43.6–49.8Sperm concentration 38.9 (28.7) 34.0–45.0Total sperm number 122.7 (113.1) 103.1–14.7Total motile sperm number 71.6 (76.7) 57.5–8.9

Table 4. Coefficient correlation between sperm parameters quality and exposure to digital media devices in the evening and afterbedtime (night).

Volume(ml) ph

Total motility(%)

Progressive(%)

Nonprogressive (%)

Immotile(%)

Spermconcentration

Total motile spermnumber

Smartphone evening 0.025 0.036 −0.392* −0.322* −0.003 0.382* −0.169* −0.173*Smartphone night 0.005 0.026 −0.369* −0.299* −0.064 0.344* −0.137 0.074Tablet evening 0.046 0.031 −0.132 0.159 −0.100 0.036 0.070 −0.017Tablet night −0.013 −0.139 −0.167* −0.312* −0.102 −0.138 −0.204* −0.168*Tv evening −0.022 0.021 0.012 −0.265 −0.097 0.226 −0.199* −0.147Tv night −0.039 0.114 −0.200 −0.027 −0.157 0.016 −0.137 −0.001Computer evening 0.072 0.056 −0.131 0.008 −0.054 0.015 0.003 0.101Computer night 0.047 0.042 −0.095 −0.116 −0.176 0.112 0.043 0.025Sum evening 0.020 0.085 −0.161* −0.027 0.065 0.200* 0.053 0.060Sum night 0.03 0.135 −0.100 0.04 0.112 −0.128 −0.017 0.046Sum portablesevening-night

0.029 0.039 −0.346* −0.345* −0.137 0.421* 0.037 −0.184*

Sleep duration 0.016 −0.349* 0.249* 0.233* 0.059 −0.100 0.050 0.119Sleepiness (KSS) −0.030 0.254* −0.251* −0.264* −0.037 0.238* −.137 −0.173*Concentration level −0.137 0.254* −0.250* −0.264* −0.018 0.230* 0.038 0.048

*p < .05.

418 A. GREEN ET AL.

television in the evening, as well as use of smartphonesin the evening and after bedtime. We observed posi-tive correlation between the sleep complaint “Havebad dreams” and the use of computers in the eveningand after bedtime; this complaint was also positivelycorrelated with the sum of all exposure to screens inthe evening and after bedtime. In addition, weobserved positive correlation between the answer tothe question “how often have you taken medicine?”and the sum exposure to screens in the evening and at

night. We did not detect significant correlationsbetween any other sleep complaint in the PSQI ques-tionnaire and exposure to screens of any other digitalmedia device. The sleep quality rating was negativelyassociated with smartphone usage in the evening andcomputers at night, meaning that extensive use ofsmartphones and computers in the evening andafter bedtime is correlated with bad sleep qualityreports. We noted significant positive correlationbetween subjective sleepiness by means of the KSSand the following variables: computer usage in theevening, computer usage after bedtime, smartphoneuse in the evening, and tablet use after bedtime. Allcorrelation coefficients are presented in Table 5.A significant correlation is marked * = p < .05.

Discussion

In line with the major tested hypothesis, smart-phone and tablet use in the evening and afterbedtime was correlated with decline in spermquality (motility and sperm progressive motility),and were positively correlated with the percentageof immotile sperm. Furthermore, smartphone usein the evening, tablet use after bedtime, and tele-vision use in the evening were all correlated withthe decline of sperm concentration. To the best ofour knowledge, this is the first study to reportthese types of correlations between sperm qualityand exposure time to SWL emitted from digital

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Figure 1. Frequency distribution of level of concentration in themorning (n = 116).Frequency distribution of level of concentration in the morning.1 – ”extremely poor concentration,” 3 – “not able to concen-trate,” 5 – “neutral, neither unable to concentrate or concen-trate,” 7 – “able to concentrate,” and 9 – “extremely goodconcentration.”

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KSS Questionnaire

Figure 2. Frequency distribution of subjective sleepiness in the KSS questionnaire (n = 116).Frequency distribution of subjective sleepiness in the KSS questionnaire. 1 – “extremely alert,” 3 – “alert,” 5 – “neither alert norsleepy,” 7 – ”sleepy,” and 9 – ”extremely sleepy.”

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media, especially smartphones and tablets, in theevening and after bedtime.

Recent comprehensive systematic review andmeta-regression analysis of 185 studies demon-strated significant sperm concentration decline overthe past several decades. Declines were shown to besignificant in studies from Western and industrialcountries, while studies from non-Western countriesshowed no such significance (Levine et al. 2017).Various factors, such as elevated body mass index(BMI), endocrine disruption, stress, nutrition, infec-tions, elevated ambient temperature, and air pollu-tion have been cited as explanations for the observeddecline in sperm concentration (Adams et al. 2014;Chiu et al. 2015; Jurewicz et al. 2009; Krausz 2011;Lafuente et al. 2016; Macdonald et al. 2013; Nordkapet al. 2012, 2016; Sharma et al. 2013). Our resultssuggest this decline in sperm quality is also asso-ciated with exposure to SWL light emitted fromdigital media screens in the evening and at night.

Over the past two decades, the use of electronicmedia devices has significantly increased in Westernsocieties. Specifically, the use of light-emittingdevices in close to sleep time has become extremelypopular, and the usage time has also increasedrapidly (Adam et al. 2007; Brunborg et al. 2011;Cain and Gradisar 2010; Mesquita and Reimao2007; Shochat et al. 2010). Users are increasinglyexposed to ongoing SWL light emitted from digitalscreens in the evening and at night, while SWL light-ing is a major environmental time cue affecting thehuman biological clock. Several studies reportednegative physiological outcomes related to the

“Circadian disruption” caused by exposure to digitalmedia screens at night. It is well known that lightemitted from electronic screen devices suppressesmelatonin secretion (Chang et al. 2015; Green et al.2017; Grønli et al. 2016; Higuchi et al. 2005).Exposure to SWL light emitted from digital screensis associated with the decline of sleep quality andquantity, and disturbance of biological rhythms.Such effects rely on the characteristics of the lightsource, specifically the brightness of the light and theduration of the exposure to ALAN. Even light that isnot particularly bright can have a robust impact ifthe light is characterized by SWL and the exposureoccurs in the evening or before bedtime.

Melatonin is a neurohormone secreted by thepineal gland whose secretion is regulated both bydark-light and seasonal cycles. Circadian dysfunc-tion caused by chronic ALAN exposure has beenshown to affect cardiovascular, metabolic, andimmune system functions, and pose a risk for thedevelopment of cancer (Haim and Portnov 2013;Stevens et al. 2014). Melatonin’s “reproductive” rolein seasonal breeding animals is well-established(Hazlerigg and Simonneaux 2014; Malpaux et al.1996). However, a growing body of evidence sug-gests melatonin might have a significant effect onhuman male reproduction as well.

Spermatogenesis is regulated by a complex net-work of signaling processes involving the hypotha-lamic-pituitary-testicular axis. Both Leydig andSertoli cells (the main testicular somatic cells) aretargets of LH and FSH produced by the pituitarygland. Several studies suggest melatonin also plays

Table 5. Coefficient correlation between complaints in the PSQI questionnaire, subjective sleepiness, andexposure to digital media devices in the evening and after bedtime (night).

Wake up in the middle ofthe night

Have baddreams

How often have you takenmedicine?

Sleepquality

Sleepiness(KSS)

Smartphone,evening

0.210* 0.087 0.113 −0.168* 0.199*

Smartphone, night 0.204* 0.111 0.098 −0.176* 0.115Tablet, evening 0.113 0.054 0.059 0.100 0.118Tablet, night 0.072 0.115 0.206* −0.020 0.191*Television, evening 0.197* 0.032 −0.023 0.011 0.088Television, night 0.062 −0.09 0.008 −0.009 0.04Computer, evening 0.058 0.161* 0.114 0.115 0.166*Computer, night 0.142 0.194* 0.099 0.038 0.157*Sum, evening 0.111 0.231* 0.196* 0.119 0.099Sum, night 0.092 0.117 0.11 0.058 0.101Sum, portablesevening-night

0.049 0.088 0.074 0.117 0.065

*p < .05.

420 A. GREEN ET AL.

an important role in regulating spermatogenesis.Melatonin receptors have been detected in thehuman hypothalamus and pituitary, suggestingmelatonin may regulate the production of gonado-tropin-releasing hormone (GnRH), FSH, and LH(Weaver et al. 1993). Melatonin may likewise reg-ulate testicular development directly by binding tospecific receptors expressed in the testis (Izzo et al.2010; Rossi et al. 2014). Melatonin is considereda powerful antioxidant and has been shown to bemore effective than Vitamin E in removing freeradicals (Pieri et al. 1994, 1995). In a rat modelwith an artificially induced varicocele, melatonintreatment reduced the severity of the damage sus-tained by the epithelium and seminiferous tubuleswhile also increasing antioxidant enzyme activityand reducing the level of nitric oxide (NO), whichmight impair sperm function (Semercioz et al.2003).

In men, abnormal levels of melatonin in the semenwere shown to be associated with infertility (Awadet al. 2006). In vitro studies demonstrated the use ofamelatonin-containing incubationmedium increasedthe percentage ofmotile, progressive, and rapid spermcells, increased mitochondrial activity, and decreasedendogenous NO levels relative to those observed insperm cultivated in melatonin-free media (Du Plessiset al. 2010). These effects were attributed to melato-nin’s antioxidant properties.

The results of the current study support a negativecorrelation between evening and post-bedtime expo-sure to digital media screens and various parametersof semen quality, specifically sperm concentration,and motility. Based on melatonin’s suggested involve-ment in spermatogenesis, and because the lightemitted from electronic screen devices may suppressmelatonin secretion (Higuchi et al. 2005; Wood et al.2013), such disruption may compromise sperm con-centration and quality. Given its antioxidant effect,alterations in melatonin secretion may also cause anintra-testicular oxidative imbalance, thus increasingsusceptibility to sperm DNA damage (Wang et al.2018).

The current study also assessed the relationshipsbetween sleep (duration-pattern-quality) andsperm quality. We demonstrated a positive corre-lation between sleep duration and sperm total andprogressive motility. A significant negative corre-lation was observed between subjective sleepiness

and total and progressive motility, as well as totalmotile sperm number. Recently, two studies havesuggested the association between sleep qualityand/or duration and male reproductive health.A cross-sectional study of 953 young Danish menfrom the general population detected an inverseU-shaped association between self-reported sleepdisturbances and sperm concentration, total spermcount, sperm morphology, and testes size. Men inthe highest category of sleep disturbances had anapproximately 25% lower total sperm count thanmen with less disturbed sleep. Men who reportedno sleep disturbances also had a trend towardlower semen quality (Jensen et al. 2013). Chenet al. (2016) report a similar U-shaped associationbetween sleep duration and sperm quality ina cohort of 796 Chinese college students. In eachof the studies, either restricted or excessive sleepwas associated with decline in sperm quality ina dose-response manner.

There are several limitations to our study. Thestudy cohort was rather small. Moreover, the effectsof other sources of artificial light at night besidesmedia devices, e.g. room lighting, were not assessed.Additionally, we did sample melatonin levels of thesubjects to confirm suppressed levels, but rather weaccepted the findings suggesting exposure to SWLlight emitted from digital screens results in suchand, therefore, is associated with the observed declinein sperm quality. Therefore, future studies shouldmeasure the levels of melatonin in order to evaluatethe effect of melatonin secretion on sperm quality.Additionally, we have no way to differentiate betweenthe effects of the suppression of melatonin secretioncaused by SWL emitted from digital media devicesand the effects of sleep deprivation/sleep quality onsperm quality. Future studies should be designed torespond to this query, in order to evaluate whether thedecline in sperm quality is linked to sleep deprivationresulting from overexposure to SWL light or whetherit is caused by the suppression of melatonin secretionscaused by SWL (with no connection to sleep). Furtherresearch aiming to establish this proposed causativelink may lead to the development of relevant thera-peutic interventions. Furthermore, our data on theduration and timing of exposure to SWL frommedia devices are based on self-reports. The charac-teristics of the light emitted from these devices couldnot be measured due to the nature of this study.

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Finally, due to the almost universal use of light-emitting devices in everyday life today, the study wasunable to incorporate a control group that was devoidof no exposure to them.

The results of our study support the hypothesisthat exposure to SWL emitted from screens of mediadevices is associated with a decline in semen quality.Given the role of melatonin in spermatogenesis, wepropose that disruption of melatonin secretion andproduction by emitted light from screens of mediadevices at nighttime may be a major “linkage” todecline in sperm concentration and quality.

Compliance with ethical standards

The study was approved by the institutional ethical reviewboard at Assuta Medical Center.

Conflict of interest

Dr. Amit Green, Dr. Shlomi Barak, Mr. Lior Shine, Dr. ArikKahane, and Prof. Yaron Dagan declare that they have noconflict of interest.

All authors have seen and approved the manuscript.

Funding

All authors declare no financial or non-financial disclosure.

ORCID

Amit Green http://orcid.org/0000-0002-5668-2712

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