Impact of Noise Pollution during Covid-19: A Case Study of Balasore, Odisha

Abstract

Activities such as development of industrialisation, urbanisation is a part of our life in the present scenario. During this phase we face a lot of health issues due to noise pollution. Growing of vehicle traffic is one of the major causes towards noise pollution and it affects significantly on the environment. The impact of such pollution had been assessed in 20 major squares (Commercial, residential and silence area) of the Balasore town during and after lockdown imposition of Covid-19. During lockdown period, the noise level of the town was within the permissible limit set by CPCB while before and after lockdown period it was beyond the permissible limit. The demographics and psychophysiological (annoyance, sleeping problem, tiredness, headache, and depression) responses of the participants were collected using standard questionnaires. It was also observed that there were better health conditions among the public (150 participated in the questionnaire) during the lockdown period, then before and after the lockdown phase. It was revealed that socio-demographic factors have no effects on the annoyance level.

1. Introduction

One of the most common job-related occupational risks is noise and is a global problem. In urban areas it affects the health of people and also the environment. In many reports it has been reported how the people from different part of world are exposed and affected by noise pollution [1, 2, 3, 4]. Many studies also reported that there is a corelation between noise and health problems like headache, irritability etc. [5, 6, 7]. The main source of noise pollution is vehicular traffic noise or road traffic noise, as reported by many studies [3, 8, 9, 10, 11, 12]. Increased noise exposure is known to produce annoyance [5, 13, 14], headaches [15, 16, 17, 18], diabetes [19], irritability [20], sleep disturbances [21, 22, 23, 24, 25, 26], hypertension [27, 28, 29, 30], and problem in blood pressure [31]. Presently, it is a global problem [32].

Again, in many studies, it was also reported about the noise pollution level and its impact on public in world-wide [33, 34, 35, 36]. Similarly, in many parts of India, research has been going-on on noise pollution and its impact on human health. In most of the study, it also been reported that the noise levels on Indian road conditions was more than the prescribed noise level set by CPCB [37]. The noise levels of many towns of Odisha are also more than the prescribed limit [38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52]. Silence zones were the most affected by noise pollution, according to Kalawapudi et al. [53], followed by residential, business, and industrial zones. They went on to say that proper city design could help people avoid being exposed to growing noise pollution levels, in Mumbai Metropolitan region. Thakre et al. [54] also discovered a 4.4 and 5.2 dB increase in the morning and evening sessions, respectively, in Nagpur from 2012 to 2019 [54]. The impact noise on bus driver [9], public coming to the park for refreshment [10], Office [55], Bank [56, 57], festivals [11, 41], Industrial areas [58, 59] and workers working in the stone crusher industry [60, 61] has also been reported. Zambon et al. [62] reported about the comparison to the same period in 2019, noise levels in terms of both absolute noise levels (Lden) and hourly noise profiles (median across lockdown period) showed a substantial drop of nearly 6 dB [62], while it was 1–3 dB in Boston metropolitan areas of USA [63] and reduction of 5.1 dB in Ruhr area of Germany [64]. The highest sound levels were found along major roadways, with a logarithmic reduction as distance from the roads increased [63]. Significant outdoor noise fluctuations were discovered, and participants clearly perceived noise variations both in urban and indoor settings, claimed by Caniato et al. [65]. Alias and Alsina-Pages reported that there was a significant reduction in the harmful impact of noise on the population of Milan urban and Rome suburban areas [66].

Now, most of the Indian cities are going to face major threats in the form of noise pollution on public’s health. It can affect both physically and mentally on the public’s health. But the life changed after the spreading of COVID-19 in whole world. After its existence, first Janata Curfew was coming in to existence followed by the lock-down system. During this period the vehicular traffic noise has been reduced drastically in world-wide. But how much it was reduced is a concern. In this study, an attempt has been made to access the noise levels of the Balasore town before, during and after lockdown phase in different areas. The impact of such noise levels on public’s health was also accessed through questionnaire. Suggestive reduction procedures are also given in the present study.

2. Methodology

2.1 Study area

Balasore is one of the famous districts in the state Odisha and situated in the eastern part of the state. It is famous for its cultural heritage, vast sea-beach and many more. It is also famous for Chandipur Sea Beach. The study area is the district head-quarter. As per 2011 census of India, Balasore District has a population of 2,320,529 in 2011 but estimates as per aadhar uidai.gov.in Dec 2020 data as 2,645,403. But the population of the municipality/metropolitan areas was 1,77,751 and city had 1,18,162. The latitude and longitude of the district is 21 29 39 North, 86 55 54 East respectively (Figure 1). The monitoring town has elevation of 16 m. the maximum and minimum temperatures are observed to be 31.8 and 21.9 respectively, with an average rainfall of 1706.1 mm, average relative humidity of 71% and speed of 11 km/h. The research area is about 194 km away from the state capital. Different rural roads are connected to this town. Thousands of vehicles along-with number of heavy vehicles are flowing on different roads of the town. The town has a very wide commercial areas and lot of people from different regions were depending on this market for their daily needs. The major road of the town also connected with the Chandipur beach, and other religious areas of the district. Thus, heavy rush in vehicle flow has been shown on the town. Every day, thousands of different cars enter and exit the city. The metropolitan environment has a diverse traffic flow. It is one of the busiest municipalities/towns of the state, with a variety of land-use patterns.

Figure 1.

Map of India showing the location area of the study area.

Nationwide lockdown (21 days) imposition in India was implemented between 25th March 2020 and 14th April 2020 as Phase 1 and between 15th April and 3rd May 2020 as Phase 2, Phase 3 from 4th May 2020 and 17th May 2020 and last phase (Phase 4) 18th May 2020 to 31st May 2020. Before this nation-wide voluntary public curfew was implemented on 22nd March 2020 for a time period of 14-hour. The same process of lockdown was also implemented in the Balasore town accordingly. Only essential good services are provided to the public. The Unlock phases was came into exist. The first unlock 1.0 came in to exist between 1st June to 30th June 2020. After the month of June 2020, the unlock phases was going on from unlock phase 1 to unlock 21 (1 February 2022 to 28 February 2022). In the present study, the noise levels recorded during unlock phase 1.0 and 2.0, i.e. 1st June 2020 to 30th June 2020 and 1st July 2021 to 31st July 2021. Similarly, the noise level also monitored during December 2019, January 2020 and February 2020 before imposition of the lockdown. During lockdown phase, the noise level had been accessed in the month of May 2020.

2.2 Monitoring sites

At 20 separate locations throughout the town, the acoustic level was measured. All these monitoring stations are divided into three sections such as commercial zone, residential and silence zone. Seven locations from both commercial and residential zones are selected and six stations were selected for silence zone. Some of these locations are belong to the commercial zone, such as Cinema square, Fandi square, Motiganj Bazar, Station square, ITI square, Padhuanpada square, and Policeline square, while others are in silence areas, such as Hospital gate, Durganurshing home, FM college, Zilla school, Near Kendriya Vidyalay (KV), and Police High School and others are in residential areas, such as Mandal bagicha, Near ACPL apartment, Khaparapada New Colony, Rajabagicha, Angargadia, Santikanana and Swastik tower.

2.3 Sampling and data acquisition

The sound level metre Model HD2110L was used to collect acoustic data at each of the 20 sample stations in and around Balasore town. The calibration of the equipment was carried out according to the manufacturer’s instructions. The measurements were conducted on working days at street level in and around the chosen locations’ major road connections. The instrument was comfortably set in road sides, with the microphone aimed at the source of noise. The equipment was placed 2 m distant from the reflecting object, and the data was gathered while standing 1.5 m above ground level on the roadside. Within 10–20 m gaps, noise levels were measured based on road width. Each station’s noise levels were measured in the morning (8–10 a.m.), afternoon (3 p.m.–5 p.m.), and evening (7 p.m.–9 p.m.). The noise levels were measured in four different directions at each station, and one reading was taken every 2 min, for a total of five readings within a 10-minute time frame [67, 68, 69, 70]. All of the information is saved on a computer for further study.

For noise level data analysis, noise indices such as Lmin, Lmax, and Leq were calculated. The maximum, minimum, and equivalent noise levels were calculated using all of the recorded data on an excel sheet. The minimal sound pressure level is Lmin, the maximum sound pressure level is Lmax, and the equivalent continuous sound level during that time period is Leq. Again, L10 and L90 refer to sound intensities that are greater than 10% and 90%, respectively.

2.4 Community response

The community reaction was gathered through the use of questionnaires distributed to members of the public going along the various route segments. During the month of March 2020, the public’s replies were gathered and recorded on a computer. The questionnaire sent to the participants through whatsapp and in some cases hard copies are also shared and the process was completed during the month of November 2020. One hundred fifty participants have been responded to the questionnaire. This questionnaire was filled out by individuals (those who agreed) who were 18 years old or older. There were two sections to the questionnaire. The first section of the questionnaire is about demographics, while the second section is about various health issues related to the town’s acoustic noise. The questionnaire in this study was designed in accordance with Vianna et al. [71], and the questionnaire was constructed appropriately. A total of 150 people from various age groups replied to the questionnaire in this study. The first section contains demographic data such as name, gender, age, educational attainment, and marital status. After minor adjustments by Vianna et al. [71], the second half of the questionnaire was separated into the following sections. The respondents completed the noise sensitivity scale created by Weinstein [72] and Eysenc’s personality Inventory (EPI) in this study [73]. Two items given under perception of noise such as aware of noise pollution and environmental noise asked the participants to answer in 5-point Likert scale. The question based on annoyance level and anxiety are also in 5-point Likert scale. Questions are given on hearing condition, sound quality of the environment, personality traits such as aggression, depression, stability, working ability, tiredness and drowsy, sensitivity, relaxation, developing symptoms, and on health risk. This part asks about how people perceive noise from things like road traffic and other sources, and the answer is either Yes or No. High, Moderate, and Little annoyance in regard to noise sources; Noise exposure effects (hearing loss, sleep disturbances, headaches, fatigue, drowsiness, and other illnesses); Hearing condition (Excellent, Good, Moderate, and Poor); environmental sound quality (Normal, Moderate, and Noisy); and environmental perception (Yes, No, and Undecided) [9, 71, 73]. The Chi-square test in SPSS 20.0 was used to look into the correlations between demographic characteristics and annoyance, and other environmental factors and the ANNOVA test was used to look into the association between noise exposure and the probable impacts of that noise on this community. At a significance threshold of 0.05, the relationship between individual and combination socio-demographic characteristics was examined. The datasets were analysed using SPSS software (20.0).

3. Results and discussion

3.1 Studies related to zone specific noise

The average noise levels of the 20 stations of different categories have been accessed and presented in Table 1 (Before Lockdown), Table 2 (during lockdown) and Table 3 (Unlock phases). The data collected during the month December 2019 and January and February 2020 are considered as pre-lockdown phase. 17th March 2020 to 31st May 2020 considered as lockdown period. After 1st June 2020 it is considered as unlock phases or after lockdown period. The comparative monthly variation of equivalent noise levels of these areas having different land use type is presented in Figure 2. The figure clearly depicts that there is a sharp trend of noise levels of the town during three phases of the lockdown. It also demonstrates that the noise level during the lock down phases is very low than unlock and before lockdown phases. The monthly noise variation of all the stations is depicted in the Figures 2–10. In each figure, first three belongs to the monthly noise level before lockdown period, while the fourth one belongs to the lockdown period and the last portions belong to the unlock phases.

Sl. No.	Name of the square	Morning (8–10 am)						Afternoon (3–5 pm)						Evening (7–9 pm)
		Max	Min	L10	L50	L90	Leq	Max	Min	L10	L50	L90	Leq	Max	Min	L10	L50	L90	Leq
1	Cinema sq	88.9	61.6	82.6	75.8	66.4	80.5	90.4	59.8	82.7	75.6	65.2	81.1	89.3	58.4	83.6	76.9	67.5	81.5
2	Fandi sq	89.2	62.4	81.4	76.2	67.3	79.8	91.6	60.7	82.1	75.2	64.8	80.5	90.8	59.5	83.7	75.4	68.2	79.7
3	Motiganj Bazar	87.7	57.7	80.8	75.1	64.9	79.6	88.7	59.3	81.8	76.3	64.4	81.7	90.3	59.8	82.5	75.3	67.4	79.4
4	Station sq	86.6	59.9	80.3	75.4	63.7	80.3	91.4	60.2	80.7	74.5	62.7	80.3	90.7	60.8	81.4	76.7	70.3	78.9
5	ITI sq	86.8	61.6	80.3	74.6	65.8	78.4	88.6	58.4	79.9	72.7	63.6	77.4	89.3	56.8	78.7	72.6	65.5	75.7
6	Padhuanpada sq	91.6	58.8	79.7	72.1	62.7	77.3	90.8	57.3	80.8	74.6	65.8	78.6	93.7	57.5	81.4	76.7	68.4	79.7
7	Policeline sq	86.4	58.5	79.5	71.6	61.8	77.2	87.9	57.4	79.7	72.2	65.6	75.7	88.2	58.6	79.7	72.4	66.6	75.5
8	Hospital gate	87.4	62.7	79.3	72.8	65.4	76.3	88.3	61.3	80.6	73.7	64.8	78.2	91.6	59.7	80.3	74.5	65.5	78.4
9	Durga nursing home	86.7	61.8	77.5	70.4	63.7	73.8	88.1	60.9	79.1	72.2	65.7	75.4	90.8	58.4	79.1	72.5	65.8	75.6
10	FM college	89.8	64.3	79.4	73.6	67.8	76.0	91.7	62.2	80.3	75.8	70.1	77.7	90.3	56.6	80.8	76.3	71.7	77.7
11	Zilla School	86.2	57.7	77.3	71.4	62.4	75.4	89.9	59.6	80.4	75.2	68.4	77.7	86.5	53.5	77.3	72.8	64.9	75.5
12	Near KV	90.3	57.4	75.5	70.1	62.9	72.9	91.6	58.8	78.3	72.8	64.4	76.3	85.9	54.8	77.7	72.4	65.8	74.9
13	Police HS	86.6	59.5	76.2	69.3	62.6	72.6	87.9	60.3	77.3	70.6	63.5	74.0	84.3	53.8	77.8	71.4	67.2	73.4
14	Mandal bagicha	82.8	55.9	74.2	67.2	59.1	71.3	84.4	56.8	75.7	68.9	60.4	73.1	85.9	55.2	72.2	66.4	59.2	69.4
15	Near ACPL Apartment	84.7	56.6	73.2	66.2	59.4	69.6	86.2	57.9	72.8	65.4	60.3	68.2	88.4	54.8	71.4	65.3	57.7	68.6
16	Khaparapada New Colony	82.8	56.3	73.7	65.9	59.4	69.5	85.8	58.6	74.4	67.7	60.9	70.9	85.2	50.2	71.6	65.1	58.4	68.2
17	Rajabagicha	85.6	64.7	76.8	71.3	66.6	73.2	87.3	61.5	77.4	71.9	64.8	74.7	91.6	60.6	75.9	70.3	64.7	72.5
18	Angargadia	85.1	61.3	75.1	69.8	64.8	71.7	89.8	59.4	75.6	70.2	63.9	72.6	90.4	54.2	73.2	69.1	62.7	71.1
19	Santikanan	83.8	57.6	74.7	69.3	64.9	71.0	86.1	58.3	74.7	69.7	62.8	72.2	85.7	50.6	70.1	64.2	59.3	66.3
20	Swastik tower	84.1	62.6	73.9	68.4	64.7	69.9	87.3	60.9	74.5	69.8	64.1	71.7	89.2	50.3	70.3	63.4	58.6	65.8

Table 1.

Noise levels in dB at different traffic squares of Balasore town during different time interval (pre-lock down phase).

Sl. No.	Name of the square	Morning (8–10 am)						Afternoon (3–5 pm)						Evening (7–9 pm)
		Max	Min	L10	L50	L90	Leq	Max	Min	L10	L50	L90	Leq	Max	Min	L10	L50	L90	Leq
1	Cinema sq	62.4	43.5	57.7	53.7	50.5	54.6	61.9	42.1	57.3	53.4	49.9	54.4	60.7	40.3	54.5	50.5	48.4	51.2
2	Fandi sq	67.8	42.6	56.1	52.8	48.6	53.8	63.5	41.7	56.5	52.7	48.8	53.7	64.7	41.1	55.1	51.6	48.2	52.5
3	Motiganj Bazar	70.1	40.1	58.4	54.4	48.4	56.2	69.5	40.2	56.1	52.5	48.6	53.5	66.8	43.8	55.7	52.8	49.9	53.4
4	Station sq	66.3	41.4	56.9	53.8	49.7	54.7	70.2	40.6	55.9	52.4	48.4	53.4	64.6	42.7	54.8	51.7	49.4	52.2
5	ITI sq	64.9	40.3	56.1	51.8	47.4	53.2	78.5	40.4	55.9	51.4	46.8	52.8	67.6	41.7	54.3	50.7	47.8	51.5
6	Padhuanpada sq	71.7	41.8	56.4	52.2	48.2	53.4	81.4	40.3	55.7	51.8	47.4	53.0	65.9	41.9	54.7	50.2	47.6	51.1
7	Policeline sq	64.4	40.1	55.5	52.1	48.3	53.0	65.4	40.7	54.6	51.8	46.9	52.8	63.9	40.9	53.8	50.7	46.5	51.6
8	Hospital gate	72.8	53.8	61.4	57.7	55.7	58.3	70.7	48.7	60.2	55.7	52.9	56.7	78.3	51.6	63.8	58.6	52.8	60.7
9	Durga nursing home	67.3	44.8	60.3	56.3	52.5	57.4	65.8	45.1	59.4	54.7	50.1	56.2	68.7	47.6	55.7	53.6	49.4	54.3
10	FM college	66.1	44.2	54.4	52.4	48.8	52.9	60.8	42.8	56.1	52.6	50.6	53.1	62.8	42.7	53.6	49.5	44.7	50.9
11	Zilla School	65.3	40.8	54.8	51.2	47.6	52.1	61.2	44.6	54.7	50.6	47.8	51.5	66.5	44.8	53.3	49.2	45.1	50.4
12	Kendriya vidyalaya	62.8	41.7	53.6	50.4	47.4	51.1	61.7	43.8	54.2	49.6	46.8	50.6	63.9	42.5	53.1	49.1	45.6	50.1
13	Police HS	64.9	42.8	53.7	50.4	47.8	51.0	60.8	42.8	53.4	48.6	45.8	49.6	67.4	41.6	52.9	48.7	44.3	50.0
14	Mandal bagicha	58.6	40.2	51.7	45.4	43.7	46.5	57.6	39.5	49.5	44.3	42.6	45.2	58.1	38.3	49.2	44.1	42.2	44.9
15	Near ACPL Apartment	60.7	41.4	50.3	45.2	43.6	46.0	56.7	40.2	48.8	44.2	42.3	44.9	57.5	39.4	48.2	44.4	41.8	45.1
16	Khaparapada New Colony	71.9	40.7	49.7	45.6	42.8	46.5	63.3	41.1	48.5	44.5	42.8	45.1	56.8	40.2	47.6	43.7	41.4	44.4
17	Rajabagicha	59.5	40.3	50.2	45.7	43.8	46.4	58.4	40.7	48.1	44.1	43.7	44.5	57.8	40.5	47.5	43.5	41.8	44.1
18	Angargadia	67.3	42.3	51.1	47.7	44.7	48.4	59.7	40.2	49.8	44.6	43.3	45.4	57.2	38.4	46.5	43.7	42.7	43.9
19	Santikanan	56.6	40.7	50.3	45.6	43.3	46.5	58.3	39.4	48.6	43.8	40.8	44.8	56.1	39.7	46.7	43.3	42.4	43.6
20	Swastik tower	56.5	40.2	49.5	45.1	42.9	45.9	57.8	38.4	47.3	43.1	49.5	43.2	56.9	38.6	46.2	43.1	41.7	43.4

Table 2.

Noise levels in dB at different traffic squares of Balasore town during different time interval (during lock down phase).

Sl. No.	Name of the square	Morning (8–10 am)						Afternoon (3–5 pm)						Evening (7–9 pm)
		Max	Min	L10	L50	L90	Leq	Max	Min	L10	L50	L90	Leq	Max	Min	L10	L50	L90	Leq
1	Cinema sq	91.3	55.6	73.8	69.6	64.8	71.0	90.7	56.7	74.7	70.1	65.8	71.5	90.3	54.8	75.3	71.7	66.6	73.1
2	Fandi sq	92.5	54.2	73.3	70	65.2	71.2	91.6	60.7	74.1	70.1	65.3	71.5	90.1	54.2	74.6	70.8	65.3	72.3
3	Motiganj Bazar	90.3	52.8	73.1	68.5	63.7	70.1	88.7	59.3	73.6	69.6	64.4	71.1	88.4	52.9	74.7	70.4	64.2	72.4
4	Station sq	88.5	54.8	72.5	68.7	64.3	69.9	91.4	60.2	73.2	69.4	63.7	71.0	85.2	51.7	73.2	69.8	63.3	71.5
5	ITI sq	87.1	54.7	72.2	68.4	64.7	69.4	88.6	58.4	72.5	68.7	62.9	70.3	84.6	52.5	73.7	68.7	63.6	70.5
6	Padhuanpada sq	90.5	53.6	73.7	69.2	63.5	71.1	90.8	57.3	72.7	69.5	63.1	71.1	83.9	50.5	73.1	69.2	63.2	70.9
7	Policeline sq	89.5	55.5	71.6	67.7	62.4	69.2	87.9	57.4	72.4	69.1	63.8	70.4	83.7	51.6	72.7	68.5	61.8	70.6
8	Hospital gate	88.7	56.8	75.7	70.7	64.4	72.9	88.3	61.3	75.2	71.1	65.8	72.7	86.4	55.2	72.5	68.3	64.7	69.4
9	Durga nursing home	85.3	56.2	70.2	66.2	62.5	67.3	88.1	60.9	72.7	67.3	64.6	68.5	81.8	52.8	72.1	67.4	63.3	68.8
10	FM college	90.4	56.3	70.4	65.4	62.3	66.6	91.7	62.2	72.3	67.2	64.4	68.3	83.7	53.6	72.4	68.1	63.5	69.5
11	Zilla School	85.3	51.9	70.3	65.2	62.6	66.3	89.9	59.6	72.1	66.6	62.8	68.1	82.9	52.5	72.5	67.6	62.4	69.4
12	Near KV	81.1	54.7	70.3	65.4	62.2	66.6	91.6	58.8	71.8	66.2	63.3	67.5	84.6	52.6	71.1	66.5	61.4	68.2
13	Police HS	82.7	54.8	69.5	64.3	60.5	65.7	87.9	60.3	71	65.9	63.5	66.9	83.5	52.1	71.4	66.2	61.3	68.0
14	Mandal bagicha	77.7	52.4	65.3	60.2	56.5	61.6	75.8	48.5	62.4	58.7	54.5	59.8	72.7	51.8	61.6	57.4	53.6	58.5
15	Near ACPL Apartment	78.9	51.9	65.1	59.8	57.8	60.7	72.6	47.7	62.4	57.3	53.3	58.8	70.3	49.3	61.4	57.2	53.3	58.4
16	Khaparapada New Colony	80.5	52.8	64.7	59.5	57.3	60.5	70.7	50.3	62.1	57.4	53.6	58.7	71.9	45.7	61.7	56.5	52.4	58.0
17	Rajabagicha	85.6	60.1	65.5	60.4	56.4	61.9	71.9	49.6	63.6	60.4	55.8	61.5	75.7	49.5	60.8	56.2	52.2	57.5
18	Angargadia	85.9	53.7	64.6	60.1	56.2	61.4	70.8	48.8	62.1	58.3	54.2	59.4	71.1	48.6	60.4	56.3	52.4	57.4
19	Santikanan	84.7	54.8	64.2	60.1	56.5	61.2	73.5	47.5	61.5	56.7	52.6	58.1	70.8	50.1	60.7	56.1	52.7	57.2
20	Swastik tower	82.9	55.6	63.5	59.7	55.6	60.8	71.4	46.2	61.2	56.2	53.2	57.3	70.8	48.4	60.4	55.5	51.8	56.8

Table 3.

Noise levels in dB at different traffic squares of Balasore town during different time interval (post-lock down phase).

Figure 2.

Comparative equivalent noise level (first three are before lock-down, middle on during lock-down and the last twos are during unlock phase) for the morning hour of commercial zone.

Figure 3.

Comparative equivalent noise level (first three are before lock-down, middle on during lock-down and the last twos are during unlock phase) for the afternoon hour of commercial zone.

Figure 4.

Comparative equivalent noise level (first three are before lock-down, middle on during lock-down and the last twos are during unlock phase) for the evening hour of commercial zone.

Figure 5.

Comparative equivalent noise level (first three are before lock-down, middle on during lock-down and the last twos are during unlock phase) for the morning hour of silence zone.

Figure 6.

Comparative equivalent noise level (first three are before lock-down, middle on during lock-down and the last twos are during unlock phase) for the afternoon hour of silence zone.

Figure 7.

Comparative equivalent noise level (first three are before lock-down, middle on during lock-down and the last twos are during unlock phase) for the evening hour of silence zone.

Figure 8.

Comparative equivalent noise level (first three are before lock-down, middle on during lock-down and the last twos are during unlock phase) for the morning hour of residential zone.

Figure 9.

Comparative equivalent noise level (first three are before lock-down, middle on during lock-down and the last twos are during unlock phase) for the afternoon hour of residential zone.

Figure 10.

Comparative equivalent noise level (first three are before lock-down, middle on during lock-down and the last twos are during unlock phase) for the evening hour of residential zone.

The Table 1 clearly depicts that the noise levels for commercial zone ranged from 57.7 to 91.6 dB, 57.3 to 91.6 dB and 56.8 to 93.7 dB for morning, afternoon and evening hour respectively. Similarly, the noise level for silence zone ranged from 57.4 to 90.3 dB; 58.8 to 91.7 dB and 53.5 to 91.6 dB during the morning, afternoon and evening hour respectively and from 55.9 to 85.6 dB; 56.8 to 89.8 dB and 50.2 to 91.6 dB during the morning, afternoon and evening hour respectively for residential zone. It can be summarised that the noise for all zones before lockdown period had a ranged from 55.9 to 91.6 dB; 56.8 to 91.7 dB and 50.2 to 93.7 dB during the morning, afternoon and evening hour respectively. Table 1 also clearly depicted that for all time the noise level ranged from 50.2 to 91.7 dB during before lock-down phase (Table 1).

Similarly, Table 2 clearly demonstrated that all zones lie in the range of 38.3 to 81.4 dB during lockdown period (Table 2) and then the range gradually increased to 45.7 to 92.5 dB during unlock period (Table 3). The equivalent noise levels of all zones lie in the range of 65.8 to 81.7 dB (Table 1); reduced to 43.2 to 60.7 dB during lock-down period (Table 2) and the range then gradually increased from 56.8 to 73.1 dB during unlock period (Table 3). The permitted limit for the said locations, as defined by the CPCB for Indian road conditions, is 65 dB during the day and 55 dB at night [37]. During the day time, the noise level exceeded the permitted limit [74, 75, 76, 77, 78]. The noise level during unlock phase and before imposing lockdown was beyond the permissible limit in the present study. It was reported that, if the exposure of noise level is more than 80 dB (A), then risk of hypertension will increase [34]. More research is needed to investigate the effect of such noise level on the public’s health in future study.

From the monthly variation it was demonstrated that the noise levels of residential areas during the morning hour are decreased by a noise level of 24.8 dB and then it increased up to 15.1 dB during unlock phase in Mandal Bagicha area. Similarly, the noise levels in other monitoring areas decreased by a noise level of 23.5, 23, 26.8, 23.3, 24.5 and 24 dB and then it was increased up to 14.7, 14, 15.5, 13, 14.7 and 19.95 dB for ACPL, Khaparapada, Rajabagicha, Angargadia, Santikanan and Swastik tower, respectively (Table 1). During afternoon hour, the maximum reduction of noise level was noticed at Rajabagicha area (30.2 dB) and then it increased up to 17 dB during the unlock phase. From the Table 1, it clearly depicts that maximum noise reduction between before lock-down phase and during unlock phase was observed at commercial zone (more than 25.5 dB) followed by residential zone (more than 25 dB) and silence zone (more than 22 dB). All these data are mentioned here are in an average data. Similarly, the maximum growing noise level between during lock-down and unlock phase was also noticed at commercial zone (more than 17.8 dB) and followed by silence zone (16.7 dB) and residential zone (14.1 dB). During evening hour and at Padhuanpada square maximum noise reduction i.e., 28.6 dB was noticed, while the lowest reduction was at 16.3 dB during morning hour at Durga Nursing home. Again, maximum increase of noise level was noticed at Cinema square (21.9 dB) during the evening hour, while the minimum increase noise was noticed at Hospital gate (8.7 dB) during the evening hour also.

Table 1 also clearly depicted that the equivalent noise level during before lock down phase ranged from 77.2 to 80.5 dB; 75.7 dB to 81.7 dB and 75.5 to 81.5 dB for morning, afternoon and evening hour respectively. But the noise level during the lock-down phase ranged from 53.9 to 56.2 dB; 52.8 to 54.4 dB and 51.1 to 53.4 dB during the morning, afternoon and evening hour respectively (Table 2). Similarly, the noise level during the unlock phase ranged from 69.2 to 71.2 dB; 70.3 to 71.5 dB and 70.5 to 73.1 dB during the morning, afternoon and evening hour respectively (Table 3). The noise level at silence zone ranged from 72.6 dB to 76.3 dB; 74 to 78.2 dB; 73.4 to 78.4 dB during before lock down phase; 51 to 58.3 dB; 49.6 to 56.7 dB and 50 to 60.7 dB during lock-down phases at morning, afternoon and evening hour and 65.7 to 72.9 dB; 66.9 to 72.7 dB and 68 to 69.5 dB during morning, afternoon and evening hour respectively. In the residential areas it ranged from 69.5 to 73.2 dB; 68.2 to 74.7 dB and 65.8 to 72.5 dB during before lock down phase; in lock-down phase the noise level ranged from 45.9 to 48.4 dB; 43.2 to 45.4 dB and 43.4 to 45.1 dB and in unlock phase it ranged from 60.5 to 61.9 dB; 57.3 to 61.5 dB and 56.8 to 58.5 dB in the morning, afternoon and evening hour respectively.

In location wise, Tables 1–3 clearly depicts the noise variation in all the monitoring stations. These Tables demonstrated that there is a reduction of 25.9 dB, 26.7 dB; 30.3 dB in three different monitoring hours for site 1 of commercial zone. Conversely, the reduction is almost 26, 26.8 and 27.2 dB for site 2, 23.4, 28.2, 26 dB for Site-3 and a similar trend was found in all other monitoring sites belong to commercial zone. In the commercial zone the minimum noise reduction ranged from 22.9 to 28.2 dB and 23.9 to 30.3 dB during afternoon and evening hour of the commercial zone. Again, the reduction of noise level ranged from 16.4 to 23.3 dB; 19.2 to 26.2 dB and 17.7 to 26.8 dB of silence zone and from 23 to 26.8 dB; 23.3 to 30.2 dB and 22.4 to 28.4 dB of residential zone during morning, afternoon and evening hour respectively. This result clearly depicted that there is almost same trend in the noise level reduction, both in commercial and residential zone of the town. The minimum noise level reduction was more than 15 dB and found at silence zone of the town and clearly depicted that due to the nationwide lock-down imposition, there was a sharp reduction in the noise level. It will impact the environment in a positive manner.

In comparison between Leq values of a particular sites during the lock-down period with unlock phase, there was sharp increase in the noise levels of each location. Noise levels from 13.9 to 17.7 dB was increased during the morning hour in between lockdown and unlock phases. Similarly, the noise levels increased by 17.1 to 18.1 dB and 19 to 21.9 dB in afternoon and evening hour of commercial zone. Again, the increased noise level ranged from 9.9 to 15.5 dB, 12.3 to 17.3 dB and 8.7 to 19 dB of silence zone and ranged from 13 to 15.5 dB, 13.3 to 17 dB and 13.3 to 13.6 dB of the residential zone during morning, afternoon and evening hour, respectively. Due to slight relaxation provided by the local administration, there was a sharp increase in noise level of the town. This trend was more commercial zone. In the present study it is also reported that there is no relation between the different monitoring hours and the situation i.e., before imposing lockdown and after imposing and lifting the lockdown phase of the town. But there is a good association between different areas such as residential, commercial and silence zone with unlock and before lock down phase of the town (Table 4). In case of monthly noise level variation with different phases of the lockdown situation there is also good association between them and is presented in the Table 5.

Source	Type III sum of squares	df	Mean square	F	Sig.
Corrected model	34.837a	2	17.419	138.614	0.001
Intercept	13.532	1	13.532	107.684	0.001
Unlock	3.144	1	3.144	25.020	0.001
BeforeLockdown	1.186	1	1.186	9.441	0.003
Error	7.163	57	0.126
Total	282.000	60
Corrected Total	42.000	59

Table 4.

Two way ANNOVA analysis for equivalent noise levels during unlock and before lockdown phases with different areas.

^a

Rsquared = 0.829 (Adjusted Rsquared = 0.823).

		Sum of squares	df	Mean square	F	Sig.
December	Between groups	738.064	2	369.032	92.802	.001
	Within groups	226.663	57	3.977
	Total	964.727	59
January	Between groups	755.856	2	377.928	87.198	.001
	Within groups	247.046	57	4.334
	Total	1002.902	59
February	Between groups	780.520	2	390.260	68.810	.001
	Within groups	323.277	57	5.672
	Total	1103.797	59
May	Between groups	868.172	2	434.086	98.290	.001
	Within groups	251.732	57	4.416
	Total	1119.904	59
June	Between groups	1655.407	2	827.704	232.770	.001
	Within groups	202.686	57	3.556
	Total	1858.093	59
July	Between groups	1464.398	2	732.199	209.703	.001
	Within groups	199.022	57	3.492
	Total	1663.419	59

Table 5.

One way ANNOVA analysis for monthly equivalent noise levels with different areas.

In the present study, it was found that the noise level in the residential areas is growing on due to imposition of lockdown in the town. Due to lockdown, the commercial areas of the town and for such the people are selling different grocery items in the different parts of the residential areas. The open shops are instantly made on the roadside and there is slight gathering around such place. These shops are opened from 7 am to 7 pm during the unlock phase while it was opened from 7 am to 2 pm during the lockdown phase. Around the market or shop area there was gathering and due to which, the noise level during the unlock phase was raising. Again, during the unlock phase, the noise level suddenly increased due to immediate rush in different parts of the town, due to purchase of goods for their house. They creating a such situation unnecessarily by gathering around the temporary shops.

In case of silence zone, schools and hospitals were taken in the present study. All the monitoring stations were located along the main road. College and school squares are also along the road of different hospitals. Many private clinics and hospitals are also very close to the schools and colleges of the town. During lockdown, many shops, schools and colleges and other establishments were closed. All medicinal shops are opened throughout the day time. But vehicles are flowing on the road due to health matter. Continuous flowing of many vehicles including heavy vehicles on the road are controlled, but running of the two wheelers, ambulances and responsible for the noise levels of the town.

3.2 Community responses

During the month of March 2020, the public’s replies were gathered and recorded on a computer. The questionnaire was supplied to the participants both in online and offline mode. Those are expertise in the android mobile phones or in their PC or laptop they are responded to the questionnaire through online mode. Those are not comfortable in using these devices, asked the researcher to provide the such through offline mode and also provided to them as such. After getting their responses, it was then transferred in to MS Excel for its further analysis.

The questionnaire was completed by 150 people, as mentioned in the content and methods section. The average age of the responders was 37.8 years old, with a standard deviation of 9.4 years. Table 6 lists the various personal characteristics of the individuals. Table 6 clearly depicts that the majority of the participants are male respondent (59.3%), with 68.7% of the total completing their education at the graduation level. In the present study, majority of the participants are employed. Majority of the participants (78.7%) participated in this survey work are married. In the present study most of the young generation (48%) between the age of 18 to 30, responded to this questionnaire.

Sl. No.	Characteristics	Variables	Response in %
1	Gender	Male	59.3%
		Female	40.7%
2	Age	18–30	48%
		31–45	36.7%
		More than 45	15.3%
3	Marital status	Unmarried	21.3%
		Married	78.7%
4	Qualification	Under matric	7.3%
		Matric	5.3%
		Intermediate	18.6%
		Graduation	68.7%
5	Occupation	Employed	51.3%
		Self-Employed	28%
		Un-employed	20.7%

Table 6.

Personal characteristics of respondents (in percentage).

The Pearson Chi-square of noise discomfort to different demographic characters is shown in Table 7. Table 7 clearly depicts that there is a good association between annoyance and gender of the present work. Again, there is no direct relationship between annoyance and other demographic characteristics, according to the data.

Demographic characters	X^2	df	Asymp. Sig. (2-sided)
Gender	15.622	4	0.004
Age	7.384	8	0.496
Marital status	6.968	4	0.138
Qualification	11.698	12	0.470
Occupation	8.679	8	0.370

Table 7.

Relation between demographic character and annoyance.

In this study it was found that 36.7% individuals were extremely irritated, while 39.5% remain silent. In a study conducted by Alimohammadi et al. [73] on White-collar employees in Teharan, it was discovered that married people were more irritated than unmarried people. But in the present study it was contradicted that result (p = 0.217).

The participants’ perceptions on noise, health issues, hearing conditions, sound quality of the environment, environmental problems, opinion of participants on noise preventability, sensitivity to noise, annoyance, and the importance of controlling the town’s noise were all examined in the current study and presented in the Table 8.

Personality traits		Number	Percentage
Perception of noise (aware of noise pollution)	Strongly agree	46	30.7
	Agree	89	59.3
	Neutral	6	4
	Disagree	9	6
	Strongly disagree	—	—
Health issues	High	10	6.7
	Moderate	27	18
	A little	55	36.7
	No feeling	21	14
	Neutral	37	24.6
Hearing condition	Excellent	1	0.7
	Good	51	34
	Moderate	57	38
	Bad	41	27.3
	Worst	—	—
Sound quality of the environment	Normal	6	4
	Moderate	54	36
	Noisy	90	60
Environmental problems	Strongly agree	29	19.3
	Agree	85	56.7
	Neutral	10	6.7
	Disagree	26	17.3
	Strongly disagree	—	—
Developing symptoms	Feeling ill	61	40.7
	Headache	82	54.7
	Respiratory problems	7	4.7
	Eye irritation	—	—
Annoyance	Never	14	9.3
	Occasionally	5	3.3
	Sometimes	10	6.7
	Often	86	57.3
	Always	35	23.3
Source of noise pollution	Mobile phones	35	23.3
	Running of vehicles	134	89.3
	Honking	106	70.7
	Railway	115	76.7
	Two wheelers	117	75

Table 8.

Participant’s perception towards different aspects of noise pollution.

On awareness towards road traffic noise pollution, majority of the participants (59.3%) were aware of it. More than 30% respondents were strongly aware about the noise pollution, which is also a good sign for the society. Regarding health issues majority respondents (36.7%) opined about a little impact of noise pollution on their health, while 24.6% respondents remain silent and only 18% viewed that they suffered moderately by the noise pollution. On hearing condition most of the participants (38%) were in moderate condition, while 30% responded as good in condition. Only 27.3% opined that their hearing condition was not so good or in bad condition. How much the hearing problem is affected is not studied in the present study. The researcher aimed to conduct the audiometry study of these respondents very soon to know their actual level of hearing in the next study. Noise induced hearing loss is also the most frequently recognised occupational disease in many countries [79, 80, 81].

The sound quality of the town was not so good as per the response of the participants. Due to such issues, they face a lot of problems (56.7%) in their day-to-day life. According to the findings, 40.7% of the participants suffered illness, while most of them faced headache (54.7%) due to road traffic noise. How much it affects the public health and what are the possible symptoms are developed is to be investigated in the next phase of study. Majority of the respondents (57.3%) responded that they annoyed often. Running of vehicles (89.3%) is the major source of pollution, followed by railway (76.7%), two wheelers (75%), honking (70.7%) (Table 8).

The acoustic quality of the area was described as noisy by the majority of the participants (60%). According to the study, majority of the of interviewees felt that road traffic noise was polluting the environment. When the participants’ knowledge was assessed, most of them said that road traffic noise poses a significant health risk. Noise pollution upset 67.3% of the participants, while 58.7% were sensitive to noise and 60% found it difficult to relax in these situations. More than 48% felt depressed, 82% were felt tired, 48.7% were not working in a stability manner. It may be due to the effect of the noise pollution.

The chi-square test was used to determine the relationship between age and annoyance in this study, and no link was found at p = 0.01. However, there is a strong association between annoyance and gender (p = 0.004). There was also a link between work place noise levels and annoyance, according to Allomohammadi et al. [73]. But this result is similar to the present study. It can be said that occupation is not a good characteristic towards annoyance. According to reports, there is no correlation between age, education, or marital status and the town’s level of annoyance. The current study’s findings are comparable to those of Ohrstrom et al. [82], who found that age, sex, and other characteristics do not explain differences in annoyance between people and is very similar to the results of the present study. However, it has been reported in many research that annoyance is the most vulnerable consequence of traffic noise exposure [83, 84], which contradicts the findings of the current study in many circumstances.

There is good association between gender and drowsiness of the public (p = 0.015) (Table 9). Table 9 also demonstrates that there is an association between drowsy and qualification. Table 10 depicts that there is an association between relaxation and gender (p = 0.001) and age (p = 0.006). Most of the demographic characters have a good association with noise sensitivity (Table 11). Noise sensitivity has a good association with gender (p = 0.001), age (p = 0.005), marital status (p = 0.001) and qualification (p = 0.038) of the present study (Table 11). Table 12 reveals that both gender (p = 0.001) and marital status (p = 0.001) has an association with anxiety of the noise pollution (Table 12). Gender is not a significant element in the influence of noise concern, according to certain studies [5, 85]. Similar results also depicted in the present study. There was also a link between the individuals’ age and sleep problems (p = 0.046). It was also said that age is not a significant factor when it comes to the effects of noise exposure [5, 80]. Increased parent-reported sleep issues were identified in the few studies that looked at the link between noise and child/adolescent sleep [23, 82]. Sleep fragmentation, sleep continuity, and total sleep time have all been linked to noise [24, 25]. There was no association between sleep duration and hourly minimum noise levels [86]. Again, it was also reported that there was no relation between sleep efficiency and mean noise levels, according to Missildine et al. [87]. But, the result of the present study contradicts it and it shows that there is an association between sleep problems and noise level of the town (p = 0.016).

Demographic characters	X^2	df	Asymp. Sig. (two-sided)
Gender	10.432	3	0.015
Age	10.889	6	0.092
Marital status	5.992	3	0.112
Qualification	28.342	9	0.001
Occupation	7.476	6	0.279

Table 9.

Relation between demographic character and drowsy.

Demographic characters	X^2	df	Asymp. Sig. (two-sided)
Gender	19.507	4	0.001
Age	21.261	8	0.006
Marital status	7.570	4	0.109
Qualification	7.787	12	0.802
Occupation	10.700	8	0.219

Table 10.

Relation between demographic character and relax.

Demographic characters	X^2	df	Asymp. Sig. (two-sided)
Gender	17.837	4	0.001
Age	21.817	8	0.005
Marital status	19.403	4	0.001
Qualification	21.981	12	0.038
Occupation	12.233	8	0.141

Table 11.

Relation between demographic character and sensitive.

Demographic characters	X^2	df	Asymp. Sig. (two-sided)
Gender	20.517	4	0.000
Age	9.797	8	0.280
Marital status	23.082	4	0.000
Qualification	13.892	12	0.308
Occupation	5.683	8	0.683

Table 12.

Relation between demographic character and Anexiety.

Table 13 depicts the results of ANNOVA analysis between noise annoyance and demographic characteristics. The table clearly depicts that there is an association between annoyance and gender of the study. However, there is no statistically significant link between other demographic factors and annoyance. There is a link between sex and anxiety (p = 0.033) as seen in Table 14. There is no direct relation between sensitivity with the demographic characters except marital status (Table 15). Table 16 reveals that there is an association between relaxation and age (p = 0.008) and sex (p = 0.001) of the participants of the present study. Table 17 shows the relation between annoyance and different environmental issues. This table clearly depicts that there is a strong association between relaxation, sensitivity, environmental noise, anxiety, irritation. Different vehicles are running on the main road of the town. During lock-down and unlock phases, ambulances are flowing from different areas of the town to the district hospital centre and also to the other clinics of the town. it has been reported that noise sensitivity—internal states that increase the chance of noise annoyance [88]—could alter the relationship between noise and health. Noise sensitivity has been linked to the beginning of depressed and psychological symptoms in adulthood. Higher morning saliva cortisol levels were linked to significant noise irritation and residing in high-noise locations in adolescents [89]. We did not have a way to gauge noise sensitivity or annoyance, so we could not assess its impact [90].

Source	Type III sum of squares	Df	Mean square	F	Sig.
Corrected model	9.770a	5	1.954	2.289	0.049
Intercept	33.806	1	33.806	39.603	0.000
Age	0.111	1	0.111	0.130	0.719
Sex	6.623	1	6.623	7.759	0.006
Qualification	0.104	1	0.104	0.121	0.728
Marital status	0.107	1	0.107	0.126	0.724
Occupation	2.998	1	2.998	3.512	0.063
Error	122.923	144	0.854
Total	2422.000	150
Corrected total	132.693	149

Table 13.

Analysis of ANNOVA between demographic characteristics and annoyance.

^a

Rsquared = 0.074 (Adjusted Rsquared = 0.041).

Source	Type III sum of squares	Df	Mean square	F	Sig.
Corrected model	11.910a	5	2.382	1.870	0.103
Intercept	27.567	1	27.567	21.642	0.000
Age	0.053	1	0.053	0.042	0.839
Sex	7.565	1	7.565	5.939	0.016
Qualification	1.247	1	1.247	0.979	0.324
Marital status	1.301	1	1.301	1.021	0.314
Occupation	1.171	1	1.171	0.919	0.339
Error	183.430	144	1.274
Total	1909.000	150
Corrected total	195.340	149

Table 14.

Analysis of ANNOVA between demographic characteristics and anxiety.

a

Rsquared = 0.061 (Adjusted Rsquared = 0.028).

Source	Type III sum of squares	df	Mean square	F	Sig.
Corrected model	32.004a	5	6.401	4.229	0.001
Intercept	5.506	1	5.506	3.638	0.058
Age	1.008	1	1.008	0.666	0.416
Sex	3.096	1	3.096	2.045	0.155
Qualification	0.891	1	0.891	0.589	0.444
Marital status	24.006	1	24.006	15.859	0.000
Occupation	0.787	1	0.787	0.520	0.472
Error	217.969	144	1.514
Total	1930.000	150
Corrected total	249.973	149

Table 15.

Analysis of ANNOVA between demographic characteristics and sensitivity.

^a

Rsquared = 0.128 (Adjusted Rsquared = 0.098).

Source	Type III sum of squares	df	Mean square	F	Sig.
Corrected model	18.485a	5	3.697	3.841	0.003
Intercept	9.228	1	9.228	9.588	0.002
Age	6.870	1	6.870	7.138	0.008
Sex	10.157	1	10.157	10.553	0.001
Qualification	2.278	1	2.278	2.367	0.126
Marital status	.062	1	0.062	0.064	0.800
Occupation	1.534	1	1.534	1.594	0.209
Error	138.588	144	0.962
Total	1055.000	150
Corrected total	157.073	149

Table 16.

Analysis of ANNOVA between demographic characteristics and relax.

^a

Rsquared = 0.118 (Adjusted Rsquared = 0.087).

Source	Type III sum of squares	df	Mean square	F	Sig.
Corrected model	67.409a	9	7.490	16.062	0.000
Intercept	0.906	1	0.906	1.942	0.166
Relax	6.410	1	6.410	13.746	0.000
Sensitive	8.560	1	8.560	18.356	0.000
Aware of noise pollution	0.010	1	0.010	0.021	0.884
Environmental noise	6.235	1	6.235	13.371	0.000
Hearing condition	0.643	1	0.643	1.379	0.242
Anexiety	4.360	1	4.360	9.350	0.003
Irritation	3.798	1	3.798	8.145	0.005
Depression	0.000	1	0.000	0.001	0.981
Health risk	8.296	1	8.296	17.790	0.000
Error	65.284	140	0.466
Total	2422.000	150
Corrected total	132.693	149

Table 17.

Analysis of ANNOVA between annoyance and environmental factors.

^a

Rsquared = 0.508 (Adjusted Rsquared = 0.476).

The current research clearly shows that persons in the study locations are sensitive to noise levels based on their age. Respondents are employed in a variety of sub-urban work sites. They are subjected to various types of noise. They are irritated by the noise levels in the vicinity as a result of this. It is impossible to say that the level of noise in their workplace is the sole source of their annoyance, although it could be one of them.

During unlock phases, different offices are also opened in a regular and controlled manner. The running of vehicles on the road also growing accordingly and that may affect the public health in anyway. Different construction works also going on in many parts of the town and it may cause problem to the public of the town. Heavy vehicles carrying various raw materials are also moving on this road due to road building in various portions of the road. Vehicles are driven at all hours of the day and night. People of all ages are directly exposed to these levels of noise. This activity may exacerbate their sleeping problems.

4. Conclusion

Our findings may have been influenced by the fact that the noise level decreased due to the imposition of the nationwide lockdown and it then increase sharply due to the incoming of unlock phases. Still, the reported noise level of the town was beyond the permissible limit except lockdown phases in residential and silence zone. It was reported in the present study that there is a good association between different areas such as residential, commercial and silence zone with unlock and before lock down phase of the town. In case of monthly noise level variation with different phases of the lockdown situation there is also good association between them and is presented in the Table 5. Finally, studies have demonstrated that the relationship between noise and health differs depending on sex, health status, and other factors but we lacked the sample size to evaluate the relationship by subgroup. Longitudinal designs, enhanced exposure assessment, and objective sleep assessments of whether particular subgroups of teenagers are more susceptible to the potential negative effects of environmental noise, should be prioritised in future investigations. Direct regulation of noise sources as well as changes to the built environment are two public health techniques for reducing noise exposure [21, 91]. We were unable to demonstrate a temporal relationship between exposure and outcome since the study was cross-sectional. Future research may want to utilise objective of audiometry test to test the exactness of the hearing quality of the respondents of the town.

Acknowledgments

The authors are very much thankful to Indrajit Patra and Pravat Kumar Mandal for their support in monitoring the noise levels.

Conflicts of interest

The authors declare that they have no conflicts of interest with regard to the content of this report.