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Mobile phone use has brought convenience, but the long or improper use of mobile phones can cause harm to the human body.
We aimed to assess the impact of improper mobile phone use on the risks of accidents and chronic disorders.
We systematically searched in PubMed, EMBASE, Cochrane, and Web of Science databases for studies published prior to April 5, 2019; relevant reviews were also searched to identify additional studies. A random-effects model was used to calculate the overall pooled estimates.
Mobile phone users had a higher risk of accidents (relative risk [RR] 1.37, 95% CI 1.22 to 1.55). Long-term use of mobile phones increased accident risk relative to nonuse or short-term use (RR 2.10, 95% CI 1.63 to 2.70). Compared with nonuse, mobile phone use resulted in a higher risk for neoplasms (RR 1.07, 95% CI 1.01 to 1.14), eye diseases (RR 2.03, 95% CI 1.27 to 3.23), mental health disorders (RR 1.16, 95% CI 1.02 to 1.32), and headaches (RR 1.25, 95% CI 1.18 to 1.32); the pooled risk of other chronic disorders was 1.20 (95% CI 0.90 to 1.59). Subgroup analyses also confirmed the increased risk of accidents and chronic disorders.
Improper use of mobile phones can harm the human body. While enjoying the convenience brought by mobile phones, people have to use mobile phones properly and reasonably.
In the first quarter of 2019, the number of mobile phone users reached 7.9 billion, with an increase of approximately 2% year-on-year [
Although many countries and regions have passed laws prohibiting the use of mobile phones while driving, the number of reported traffic accidents caused by using mobile phones while driving has been increasing in recent years [
Given that the use of mobile phones is growing rapidly, it is still doubted whether the improper use of mobile phones causes injuries to the human body. Our paper will provide a thorough review of literature to explore the impact of improper mobile phone use, which includes accidents and chronic disorders, on human body health.
Two of the authors systematically searched PubMed, EMBASE, Cochrane, and Web of Science databases from inception to April 4, 2019. The search was limited to studies on the human body published in the English language. Additional literature was screened by manually searching the reference lists of recent reviews and studies for papers meeting the inclusion criteria.
According to the International Statistical Classification of Diseases, tenth revision [
Our inclusion criteria were studies that focused on (1) damage, including accidents and chronic disorders, instead of promoting healthy outcomes; (2) the use of mobile phones, including digital phone and mobile phone radio frequency radiation; (3) improper use of mobile phone, including inappropriate use occasions (eg, using mobile phone while driving or cycling), long-time or long-term use of mobile phone, and using the phone in an incorrect posture; (4) accidents occurring during mobile phone use or chronic disorders resulting from mobile phone use rather than those from any other cause (eg, occupational injuries); and studies that were (5) published in English and with (6) outcome indicators, including odd ratios (OR) or relative risk (RR) and 95% confidence intervals or mean and standard deviation.
Abstracts, comments, conferences, replies, responses, reviews (including systematic reviews), case reports, and animal studies were excluded. Additionally, studies with incomplete data and duplicate studies were also excluded.
The 2 authors worked simultaneously, but independently, to screen studies, extract data from studies meeting the inclusion criteria, and assess the quality of these studies. Each author’s results were cross-checked by the other, and any disagreements on study selection, data extraction, and study quality assessment were resolved by another author.
The following information was collected using standardized data extraction forms: author information, publication year, study design, participant age, sample size, study area, measures of mobile phone use, measures of outcome-related behavior, and key outcomes.
The Newcastle-Ottawa Scale [
A random-effects model was used to calculate overall pooled estimates. Tests for heterogeneity between studies’ results were performed with the Cochran Q statistic and were quantified with the
To examine the robustness of the findings, we performed subgroup analyses by country, participant age, sample size, and study-specific outcomes (accidents and chronic disorders). To validate the robustness of the findings, we performed a sensitivity analysis. The potential for publication bias was graphically explored with funnel plots, and publication bias was tested for significance with the Egger test and Begg test. All statistical procedures were 2-tailed with a significance level of 0.05 and were conducted using Stata software (version 13.0; StataCorp LLC).
A total of 4228 studies were identified by the initial database search, and 3 studies were obtained by searching references; 2329 studies remained after the removal of duplicates (
Flowchart of the selection of studies.
Of the 41 papers, 29 papers were published between 2011 and 2019 [
The results of the quality assessment indicated that 16 studies were good quality, and 25 were fair (Table S3 in
Compared with nonmobile phone users, people who use mobile phones had a significantly higher risk for all accidents, with a pooled OR/RR of 1.55 (n=15,517,418, 95% CI 1.40 to 1.71;
Forest plot of accident risk and mobile phone use.
The pooled risk of chronic disorders caused by mobile phone use was 1.07 times that of nonmobile phone use (95% CI 1.01 to 1.14;
Forest plot of chronic disorder risk (neoplasms) and cell phone use.
Chronic nonneoplasm disorders caused by mobile phone use included mental disorders (ADHD, nomophobia), headaches, sleep disorders, injuries to the head (eye, ear, and oral), injuries to the wrist, male reproductive health issues, and other unspecific chronic disorders. Compared with nonmobile phone use, mobile phone use increased the risk of headaches (pooled risk 1.25, 95% CI 1.18 to 1.32,
Forest plot of chronic disorder risk (nonneoplasm) and cell phone use. ADHD: attention deficit/hyperactivity disorder; BCSFB: blood-cerebrospinal fluid barrier.
Compared to nonmobile phone users and short-term users, the risk for nomophobia among long-term users was –0.06 (95% CI –0.74 to 0.63;
Forest plot of chronic disorder risk and cell phone use (continuous data). WMD: weight mean difference.
Subgroup analysis showed a consistent increase in the overall risk of cancer in the population (
Subgroup analyses of the risk of injuries by mobile phone use or nonuse.
Component | Studies, n (%) | Odds ratio (95% CI) (or random-effects weighted mean differencea) | |||
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Iran | 2 (2) | 1.08 (0.51, 2.27) | ||
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Canada | 3 (3) | 1.95 (0.94, 4.07) | ||
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United States | 5 (13) | 1.35 (1.18, 1.55) | ||
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Denmark | 1 (6) | 1.25 (1.18, 1.32) | ||
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Sweden | 4 (7) | 1.06 (0.91, 1.24) | ||
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100-500 | 5 (8) | 1.17 (0.79, 1.72) | ||
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500-1000 | 5 (6) | 1.76 (1.14, 2.71) | ||
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>1000 | 10 (22) | 1.21 (1.11, 1.32) | ||
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1-18 years | 4 (9) | 1.23 (1.15, 1.32) | ||
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18-35 years | 4 (4) | 1.62 (1.31, 2.00) | ||
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35-65 years | 5 (7) | 1.02 (0.87, 1.21) | ||
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Car accident | 3 (5) | 1.31 (0.81, 2.13) | ||
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Unspecified transport accidents | 6 (11) | 1.43 (1.25, 1.64) | ||
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Motorcycle accident | 3 (3) | 1.13 (0.51, 2.48) | ||
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Mental disorders | 2 (2) | 1.37 (0.54, 3.51) | ||
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Headache | 1 (6) | 1.25 (1.18, 1.32) | ||
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Neoplasms | 4 (7) | 1.07 (0.93, 1.23) | ||
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Other unspecific chronic disorders | 2 (2) | 1.04 (0.60, 1.82) | ||
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Other unspecific chronic disorders | 2 (4) | 0.51 (0.04, 0.99)a | ||
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Injuries to ear | 1 (4) | 4.54 (3.29, 5.80)a | ||
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DNA damage | 1 (1) | 0.13 (-0.15, 0.40)a |
aOutcome measures are continuous variables; therefore, random-effects weighted mean difference was used.
Among the participants with various mobile phone use duration, Canadians and Koreans had a higher risk of injury to the human body compared with that of other populations. In studies with a participant sample size that ranged from 100 to 500 and with participants aged 18 to 35 years, there was a higher risk of accidents and chronic disorders (
Subgroup analyses of the risk of injuries by the duration of mobile phone use.
Component | Studies (included entries), n (%) | Odds ratio (95% CI) (or random-effects weighted mean differencea) | |||
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United States | 3 (23) | 1.20 (0.78, 1.84) | ||
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Canada | 1 (14) | 1.91 (1.54, 2.35) | ||
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Korea | 1 (12) | 1.20 (1.05, 1.37) | ||
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Sweden | 4 (37) | 1.06 (0.98, 1.15) | ||
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100-500 | 4 (19) | 1.89 (1.32, 2.71) | ||
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500-1000 | 1 (12) | 1.13 (0.99, 1.28) | ||
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>1000 | 5 (55) | 1.16 (1.07, 1.25) | ||
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1-18 years | 1 (12) | 1.20 (1.05, 1.37) | ||
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35-65 years | 6 (41) | 1.16 (1.03, 1.30) | ||
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Car accident | 2 (21) | 1.95 (1.49, 2.55) | ||
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Unspecified transport accidents | 1 (4) | 3.23 (1.65, 6.30) | ||
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Mental disorders | 1 (12) | 1.20 (1.05, 1.37) | ||
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Tumors | 4 (41) | 1.07 (1.00, 1.15) | ||
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Other unspecific chronic disorders | 2 (8) | 1.26 (0.91, 1.74) | ||
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Nomophobia | 1 (4) | –0.06 (–0.74, 0.63)a | ||
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Oral problem | 2 (9) | 0.01 (–0.15, 0.18)a | ||
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DNA damage | 2 (4) | 7.52 (2.23, 12.81)a | ||
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Male reproductive health issues | 1 (4) | –4.69 (–5.64, –3.75)a | ||
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Injuries to wrist | 1 (2) | 0.82 (–0.53, 2.16)a |
aOutcome measures are continuous variables; therefore, random-effects weighted mean difference was used.
Research results that are statistically significant may be more likely to be reported and published than results that are insignificant and invalid. In our study, the funnel plot was generally symmetric, indicating the absence of publication bias (Figure S1 in
Our review included large participant-level cohort, cross-sectional, and case-control studies on the impact of mobile phone use on outcomes related to harm to the human body. The findings suggested that mobile phone use increased the risk of accidents and chronic disorders involving the human body. Mobile phone use increased the risk of accidents by 55%. Car accidents had the highest relative risk of traffic injuries for mobile phone users. Mobile phone use also increased the risk of chronic disorders, increasing the risk of neoplasms, ADHD, headaches, and eye injuries by 7%, 16%, 25%, and 103%, respectively.
Consistent with the findings of previous studies [
Although the risk of neoplasm from mobile phone use is still unclear, our meta-analysis suggests that improper use of mobile phones increases the risk of brain tumor, glioma, and thyroid cancer. Mobile phone radiation has been classified as possibly carcinogenic to humans [
The inclusion criteria for our study were rigorous, and thus, some reports were excluded. For example, the incidences of taking selfies and sharing them on social media as well as selfie-related behaviors are increasing, particularly among young people, which possibly leads to selfie-related trauma [
Our study also has some limitations. First, “damage” and “injury” were used as search queries in our study to retrieve papers on the health effects of mobile phones, other adverse outcomes caused by phone use may have been missed. Second, only 10 of the 41 studies were longitudinal studies. Additional longitudinal studies could confirm the causal relationship between mobile phone use and human health. Third, the different environments and behaviors of using mobile phones might lead to different risks of injury. We did not consider different patterns or reasons for using mobile phones in different regions and by different people, and we did not further analyze specific types and purposes of using mobile phones, such as texting or making phone calls. Finally, there was heterogeneity in our study (
There is growing evidence that mobile phone use affects the human body. Our study suggests that the use of mobile phones causes not only accidents but also chronic disorders to the human body. Although some findings are still controversial, the harm that mobile phones cause to the human body cannot be underestimated, and more research is needed to explore the direct evidence of damage to the human body.
Literature search strategy, basic characteristics of studies, quality assessment, and publication bias test.
attention-deficit/hyperactivity disorder
free prostate specific antigen
odds ratio
relative risk
total prostate specific antigen
weighted mean difference
This study was partly funded by the National Natural Science Foundation of China (grants 91746205, 71910107004, 71673199), and the China Medical Board (grant 16-262). The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. The two corresponding authors had full access to all the data in the study and had final responsibility for the decision to submit the study for publication.
XC and YC are co-first authors. PJ (jiapengff@hotmail.com) and YW (wyg@tmu.edu.cn) are co-corresponding authors.
None declared.