Urbanization has led to an increase in environmental stressors, among which noise pollution stands out as a major public health concern. Defined as unwanted or harmful sound that affects human health and environmental quality, noise pollution has been associated with a wide range of adverse health effects, especially in densely populated cities (1). While the physical consequences such as hearing impairment, cardiovascular issues, and sleep disturbances have been well-documented (WHO, 2018) (2), there is growing evidence linking chronic exposure to urban noise with psychiatric and psychological disturbances including anxiety, depression, irritability, and cognitive dysfunction (3).

Epidemiological studies have observed that individuals living near airports, highways, and industrial zones are more susceptible to emotional distress and mental fatigue, with a higher incidence of stress-related disorders (4). However, much of the current literature focuses on noise exposure in occupational or specific environmental contexts rather than capturing the general psychiatric impact of ambient urban noise. There is a lack of comprehensive cross-sectional studies assessing psychiatric morbidity related to environmental noise in mixed urban populations, particularly in low- and middle-income countries where urban noise regulation is limited or poorly enforced.

Moreover, previous research has not consistently accounted for confounding variables such as socioeconomic status, sleep quality, and comorbid health conditions, which may modulate the psychological impact of noise exposure (5). There also remains limited exploration of gender, age, and duration of residence as mediating factors in the relationship between noise pollution and mental health outcomes.

Therefore, the current study aims to investigate the psychiatric impact of environmental noise pollution in urban areas through a cross-sectional design. It seeks to assess the prevalence of psychiatric symptoms such as anxiety, depression, and sleep disturbance among individuals exposed to varying degrees of urban noise. The study also aims to explore demographic and environmental correlates of psychological distress, contributing to a better understanding of how chronic noise exposure affects mental well-being in real-world urban settings.

A cross-sectional observational study was conducted in the year 2023 at the Department of Psychiatry, Gandhi Medical College, Hyderabad. The study aimed to assess the psychiatric effects of noise pollution in urban settings among adult residents of Hyderabad.

The study included a total of 1200 participants aged 18 to 60 years, residing in various urban localities of Hyderabad with varying exposure to environmental noise. Participants were selected using stratified random sampling to ensure representation from areas with different noise levels, including residential zones near main roads, commercial markets, and quieter residential neighborhoods.

Inclusion criteria:

• Residents aged between 18 and 60 years
• Living in the current locality for at least one year
• Willingness to give informed consent

Exclusion criteria:

• Individuals with a known history of major psychiatric illness prior to relocation
• Persons with significant hearing impairment or neurological disorders
• Current use of psychotropic medications for unrelated diagnoses

Data Collection Tools

1. Noise Exposure Assessment:
2. Ambient noise levels were recorded using a calibrated portable sound level meter (Type 2 accuracy) at each participant’s locality during peak and non-peak hours, averaged over three consecutive days. Based on WHO guidelines, noise exposure was categorized as:

• Low: <55 dB
• Moderate: 55–70 dB
• High: >70 dB
• Psychiatric Evaluation:
• General Health Questionnaire-28 (GHQ-28): To screen for general psychiatric distress
• Patient Health Questionnaire-9 (PHQ-9): For depressive symptoms
• Generalized Anxiety Disorder-7 (GAD-7): For anxiety symptoms
• Pittsburgh Sleep Quality Index (PSQI): For sleep disturbance

These were administered by trained psychiatry residents through face-to-face interviews after obtaining informed consent.

Ethical Considerations

The study protocol was reviewed and approved by the Institutional Ethics Committee of Gandhi Medical College, Hyderabad. Written informed consent was obtained from all participants prior to their inclusion in the study. Data confidentiality and anonymity were strictly maintained throughout the research process.

Statistical Analysis

Data were entered into Microsoft Excel and analyzed using SPSS version 26. Descriptive statistics were used to summarize demographic variables. Chi-square tests and ANOVA were used for group comparisons, while multiple logistic regression was applied to identify associations between noise exposure levels and psychiatric symptoms, adjusting for confounding variables such as age, gender, socioeconomic status, and comorbid health conditions. A p-value <0.05 was considered statistically significant.

Table 1: Demographic Profile of Study Participants

The study included a total of 1200 urban residents aged between 18 and 60 years, with a mean age of 35.6 ± 10.4 years. The gender distribution was fairly balanced, comprising 52.5% males and 47.5% females. Most participants were married (70%), followed by unmarried individuals (27.5%), and a small proportion were widowed or divorced (2.5%). In terms of educational attainment, nearly half were graduates (46%), while 26% had completed up to high school, and 28% held postgraduate or higher degrees. Regarding employment status, 57% were employed, 24% were unemployed, and 19% were students or engaged in other roles. The duration of residence in their current locality varied, with 39% living there for 5–10 years, 38% for over 10 years, and 23% for less than 5 years (Table 1).

Table2: Noise Exposure Levels in Participant Localities (N = 1200)

Ambient noise levels at the participants' residential areas were measured and categorized into three groups based on WHO guidelines: low (<55 dB), moderate (55–70 dB), and high (>70 dB). Among the 1200 participants, 49% were exposed to moderate noise levels, 26% to low noise levels, and 25% to high noise levels. The mean noise level in the low exposure group was 51.2 ± 2.1 dB, while it was 63.4 ± 4.5 dB in the moderate group and 74.8 ± 3.2 dB in the high exposure group Table 2

Table 3: GHQ-28 Scores Among Study Participants (N = 1200)

The General Health Questionnaire-28 (GHQ-28) was used to screen for psychological distress among the 1200 study participants. Based on the scoring, 57% (n = 684) of individuals were classified as normal with scores between 0 and 4, while 43% (n = 516) showed signs of psychological distress with scores of 5 or more. These findings indicate that nearly half of the urban population reported mental health concerns, warranting further attention to environmental stressors such as noise pollution and their psychological consequences (Table 3).

Table 4: PHQ-9 Score Distribution among Participants (N = 1200)

The Patient Health Questionnaire-9 (PHQ-9) was used to assess the severity of depressive symptoms among the study population. Of the 1200 participants, 40.5% reported minimal or no depression (scores 0–4), while 26% had mild symptoms (scores 5–9). Moderate depression was observed in 17% of participants, 11% reported moderately severe symptoms, and 5.5% had severe depression (Table 4)

Table 5: GAD-7 Score Distribution among Participants (N = 1200)

The table 5 presents the distribution of GAD-7 scores among 1200 participants, categorizing them based on the severity of anxiety symptoms. The majority of participants (41.5%) had minimal anxiety with scores between 0 and 4, followed by 27.5% showing mild anxiety (scores 5–9). Moderate anxiety (scores 10–14) was observed in 18.5% of the individuals, while 12.5% reported severe anxiety with scores ranging from 15 to 21. Overall, 69% of the participants experienced minimal to mild levels of anxiety, whereas 31% showed moderate to severe symptoms, indicating a significant portion of the group may benefit from mental health support or intervention. (Table 5)

Table 6: PSQI Score Distribution among Participants (N = 1200)

Table 6 shows, Pittsburgh Sleep Quality Index (PSQI) was used to assess the sleep quality of the 1200 participants. Based on the scoring, 38.5% of participants were categorized as having good sleep quality (PSQI score 0–5), while a larger proportion 61.5% reported poor sleep quality (PSQI score >5).

Table 7: Pearson’s Correlation between Psychological Scores (N = 1200)

Pearson’s correlation analysis was performed to examine the relationship between depression, anxiety, psychological distress, and sleep quality among the participants. A strong positive correlation was observed between PHQ-9 and GAD-7 scores (r = 0.69, p < 0.001), indicating that depressive and anxiety symptoms often co-occur. Moderate positive correlations were found between PHQ-9 and PSQI (r = 0.52), GAD-7 and PSQI (r = 0.47), and GHQ-28 and PSQI (r = 0.58), all statistically significant at p < 0.001 (Table 7).

Table 7: Association between Noise Exposure and Psychiatric Variables (Chi-Square Test)

Table 8: Multiple Logistic Regression – Predictors of Psychological Distress (GHQ-28 ≥5)

The present study aimed to evaluate the psychiatric effects of environmental noise pollution among urban residents in Hyderabad, with a focus on psychological distress, depression, anxiety, and sleep quality. The findings indicate a strong association between increasing levels of noise exposure and the prevalence of psychological morbidity.

In our sample of 1200 participants, nearly 43% reported significant psychological distress based on GHQ-28 scores, and a notable 61.5% demonstrated poor sleep quality (PSQI >5). The prevalence of moderate to severe depressive symptoms (PHQ-9 ≥10) and anxiety symptoms (GAD-7 ≥10) was 33.5% and 31% respectively, with these conditions more frequently reported in participants from high-noise areas.

These results align with previous research by Seidler et al. (2017), which demonstrated increased rates of depression among individuals exposed to aircraft noise (6). Similarly, Hardoy et al. (2005) reported a positive correlation between environmental noise and psychiatric disturbances in Sardinia, Italy (4). In another large-scale study, Stansfeld et al. (2000) found that children exposed to chronic aircraft noise exhibited higher levels of anxiety and reduced cognitive performance (7). Our findings further validate these earlier reports, while extending the evidence to a broader urban population in an Indian context.

The present study also showed strong positive correlations between PHQ-9, GAD-7, and PSQI scores, indicating that depressive and anxiety symptoms were closely linked with poor sleep quality. This supports earlier studies such as Hume et al. (2012), which highlighted the bidirectional relationship between environmental noise and sleep disruption, further exacerbating emotional dysregulation (8).

The multiple logistic regression analysis revealed that high noise exposure significantly increased the odds of psychological distress (OR = 2.34), even after adjusting for age, gender, depression, anxiety, and sleep quality. Additionally, poor sleep quality (PSQI >5) emerged as the strongest independent predictor (OR = 2.81), reinforcing the critical role of sleep as a mediating factor between environmental stress and mental health.

Despite these important findings, the study has certain limitations. Being cross-sectional in design, causal relationships cannot be firmly established. Noise measurements were localized to the participant’s residential area, without accounting for occupational or travel exposures. Self-reported psychological instruments may also introduce subjective bias.

Nevertheless, this study contributes valuable regional data to the growing global concern on urban noise pollution and its mental health consequences. It emphasizes the need for urban planning and public health strategies to incorporate noise regulation policies and mental health screening programs in high-noise residential zones.

The study concludes that exposure to higher levels of urban noise pollution is significantly associated with increased psychological distress, depression, anxiety, and poor sleep quality. Among the variables, poor sleep quality and high noise exposure were the most significant predictors of psychiatric morbidity. These findings underscore the urgent need for noise pollution control measures in Indian urban environments and greater integration of mental health services in community health planning.

1. Basner M, Babisch W, Davis A, Brink M, Clark C, Janssen S, Stansfeld S. Auditory and non-auditory effects of noise on health. The lancet. 2014 Apr 12;383(9925):1325-32.
2. Europe WH. Environmental noise guidelines for the European region. World Health Organisation Regional Office for Europe, Copenhagen, Accessed. 2018 Dec;7.
3. Mucci N, Traversini V, Lorini C, De Sio S, Galea RP, Bonaccorsi G, Arcangeli G. Urban noise and psychological distress: A systematic review. International journal of environmental research and public health. 2020 Jan;17(18):6621.
4. Hardoy MC, Carta MG, Marci AR, Carbone F, Cadeddu M, Kovess V, Dell’Osso L, Carpiniello B. Exposure to aircraft noise and risk of psychiatric disorders: The Elmas survey: Aircraft noise and psychiatric disorders. Social Psychiatry and Psychiatric Epidemiology. 2005 Jan;40:24-6.
5. Ju YJ, Lee JE, Choi DW, Han KT, Lee SY. Association between perceived environmental pollution and poor sleep quality: results from nationwide general population sample of 162,797 people. Sleep Med. 2021;80:236-243. doi:10.1016/j.sleep.2021.01.043
6. Seidler A, Hegewald J, Seidler AL, et al. Association between aircraft, road and railway traffic noise and depression in a large case-control study based on secondary data. Environ Res. 2017;152:263-271. doi:10.1016/j.envres.2016.10.017
7. Stansfeld S, Haines M, Brown B. Noise and health in the urban environment. Reviews on environmental health. 2000 Jan;15(1-2):43-82.
8. Hume KI, Brink M, Basner M. Effects of environmental noise on sleep. Noise Health. 2012;14(61):297-302. doi:10.4103/1463-1741.104897