Patterns of Sleep Disruption and Circadian Rhythm Irregularities among Adults in Sub-Division Jawali, District Kangra, Himachal Pradesh: A Cross-Sectional Study

Sleep is a fundamental biological process essential for physical health, cognitive performance, emotional regulation, and overall well-being. Adequate and well-timed sleep supports metabolic homeostasis, immune competence, neurocognitive functioning, and psychological resilience. In contrast, chronic sleep disruption has been associated with a wide range of adverse outcomes, including impaired attention, reduced productivity, mood disorders, metabolic dysregulation, and increased cardiovascular risk [1,2]. In recent decades, sleep-related problems have emerged as a growing public health concern across both developed and developing nations. Sleep health is closely regulated by the circadian timing system, an endogenous biological clock that synchronizes physiological and behavioural processes with the external light–dark cycle. In humans, this system is hierarchically organized, with the suprachiasmatic nucleus (SCN) of the hypothalamus acting as the central pacemaker, coordinating peripheral clocks distributed throughout various organs [3]. Proper alignment between the circadian rhythm and behavioural cycles—such as sleep–wake timing, feeding, and activity—is critical for maintaining optimal physiological function. Disruption of this alignment, commonly referred to as circadian misalignment, occurs when internal biological rhythms are out of synchrony with environmental cues or social schedules. Circadian misalignment is increasingly prevalent due to modern lifestyle factors, including prolonged exposure to artificial light at night, excessive screen use, irregular sleep schedules, shift work, and heightened psychosocial stress. Experimental and epidemiological studies have demonstrated that such misalignment contributes to sleep fragmentation, reduced sleep quality, excessive daytime sleepiness, and impaired cognitive performance [4,5]. Furthermore, long-term circadian disruption has been linked to metabolic disorders, mood disturbances, and increased susceptibility to chronic diseases [6,7]. Young adults represent a particularly vulnerable demographic group. Academic demands, social engagement, digital media use, and lifestyle transitions often result in delayed bedtimes, insufficient sleep duration, and inconsistent sleep–wake patterns. Studies among college-going populations globally have consistently reported sleep durations below recommended levels, with associated declines in attention, learning efficiency, and mental health [8,9]. Despite this growing body of evidence, most research has focused on urban or institutional settings, while data from rural and semi-rural regions—especially in the Indian context—remain limited. In India, sleep health research has traditionally received less attention compared to other non-communicable health concerns. Rural populations are often assumed to have healthier sleep patterns due to earlier work schedules and greater exposure to natural light. However, this assumption is increasingly challenged by the rapid penetration of digital technology, changing occupational patterns, academic pressures, and psychosocial stressors even in rural settings. Emerging evidence suggests that rural youth may experience a unique convergence of traditional work-related stress and modern lifestyle-induced circadian disruption, leading to compromised sleep health [10]. Sub-Division Jawali in District Kangra, Himachal Pradesh, represents a predominantly rural Himalayan region undergoing socio-behavioural transitions. Young adults in this area increasingly engage in prolonged screen use, irregular sleep routines, and academic or occupational activities that may conflict with biological rhythms. However, systematic data on sleep disruption and circadian misalignment in this population are lacking. The absence of region-specific evidence limits the development of targeted public health strategies and sleep hygiene interventions. Therefore, the present study was undertaken to address this gap by systematically assessing sleep patterns, circadian behaviours, and associated daytime functional outcomes among adults in Sub-Division Jawali. By examining lifestyle factors such as electronic device use, caffeine consumption, shift work, and psychological stress alongside sleep quality and duration, this study aims to provide context-specific evidence on the magnitude and determinants of sleep disruption in a rural North Indian setting. The findings are expected to contribute to the growing literature on sleep health in India and inform community-level awareness and preventive strategies.

MATERIALS AND METHODS

Study Area

The study was carried out in Sub-Division Jawali, District Kangra, Himachal Pradesh, India. This region is located in the western Himalayan foothills at approximately 32.15° N latitude and 76.02° E longitude, with an average elevation of about 625 meters above mean sea level. The area comprises predominantly rural settlements with mixed occupational profiles, including students, agriculturists, and employed individuals. The population is increasingly exposed to digital technology and changing lifestyle patterns, making it suitable for studying emerging sleep-related health concerns.

Study Population

The study population consisted of adult residents of Sub-Division Jawali. Although individuals from a wider age range participated, young adults aged 18–30 years constituted the majority of respondents and were therefore the primary analytical focus. This age group was selected due to its higher vulnerability to lifestyle-induced sleep disruption and circadian misalignment.

Sample Size and Sampling Method

A total of 154 participants completed the survey and were included in the final analysis. Participants were recruited using a convenience sampling technique based on voluntary participation and accessibility. The questionnaire was disseminated electronically through social media platforms such as WhatsApp and direct messaging to ensure broad reach within the study area. While probability-based sampling was not feasible, the achieved sample size was adequate for descriptive and inferential analysis in a cross-sectional design. Eligibility criteria included adults residing in Sub-Division Jawali, District Kangra, Himachal Pradesh, who were willing to provide informed consent and able to access and complete the online questionnaire. Individuals with incomplete or inconsistent survey responses, or those with a self-reported diagnosis of clinically established sleep disorders such as chronic insomnia or narcolepsy, were excluded from the study.

Data Collection Tool

Data were collected using a structured, self-administered questionnaire developed specifically for this study. The instrument consisted of 27 items grouped into five sections covering demographic characteristics (age, gender, occupation, and residence), sleep habits (bedtime, sleep duration, night awakenings, sleep quality, and morning refreshment), daytime functioning (daytime sleepiness, fatigue, concentration difficulties, and unintentional sleep episodes), lifestyle and circadian factors (screen use before bedtime, caffeine consumption, shift work, and regularity of sleep timing), and psychological and medical factors (stress-related thoughts, sensory sensitivities, nightmares, diagnosed medical conditions, and medication use). The questionnaire was designed to be concise, easy to understand, and appropriate for self-reporting in a community-based setting.

Data Collection Procedure

Data collection was conducted during April 2025 using Google Forms. Participants were provided with a brief explanation of the study objectives prior to participation. Responses were recorded anonymously, and no personally identifiable information was collected. Participation was entirely voluntary, and respondents were free to withdraw at any stage before submission. Ethical principles for human research were followed, with electronic informed consent obtained from all participants. Anonymity and confidentiality were maintained, the study was purely academic and non-interventional, and no conflicts of interest were involved.

Statistical Analysis

Data obtained from Google Forms were exported to Microsoft Excel and subsequently analysed using SPSS (version 26.0) for statistical processing. Data cleaning was performed to remove incomplete and inconsistent entries. Descriptive statistics were used to summarize demographic variables, sleep characteristics, and lifestyle factors, expressed as frequencies, percentages, means, and standard deviations where appropriate. Inferential statistical analyses were conducted to examine associations between sleep parameters and functional outcomes. Chi-square tests were used to assess relationships among categorical variables such as sleep duration, sleep quality, screen use, caffeine consumption, and daytime sleepiness, while binary logistic regression evaluated the predictive effect of inadequate sleep duration on daytime fatigue and concentration difficulties. All statistical tests were two-tailed, and a p-value of less than 0.05 was considered statistically significant.

RESULTS

Demographic Characteristics

A total of 154 respondents from Sub-Division Jawali, District Kangra (Himachal Pradesh), were included in the final analysis. The dataset was complete and suitable for both descriptive and inferential statistical evaluation. The age distribution revealed a predominance of young adults (Table 1). Participants aged 18–30 years constituted 82.5% (n = 127) of the sample, followed by individuals above 40 years (7.1%), 31–35 years (5.8%), 36–40 years (3.3%), and below 18 years (1.3%). Gender-wise, females comprised 64% (n = 99) of the respondents, while males accounted for 36% (n = 55). Regarding occupation, students formed the largest subgroup (60%), followed by employed individuals (30%) and unemployed participants (10%). This occupational distribution reflects the dominance of young adults and academically active individuals within the study population.

Table 1. Demographic characteristics of study participants (n = 154)

Sleep Duration and General Sleep Patterns

Analysis of sleep duration showed that a substantial majority of participants reported inadequate sleep. Only 16.2% (n = 25) achieved 8 or more hours of sleep per night, while 68.8% (n = 106) slept for 6–7 hours. Shorter sleep durations were also reported, with 14.3% (n = 22) sleeping for 4–5 hours and 0.6% (n = 1) sleeping for less than 4 hours per night (Table 2). Bedtime patterns indicated delayed sleep onset in a considerable proportion of respondents. While 53.9% reported going to bed between 9:00 p.m. and 11:00 p.m., 29.9% went to bed between 11:00 p.m. and 1:00 a.m., and 5.2% after 1:00 a.m. Thus, more than one-third of the population (35.1%) exhibited late-night bedtimes suggestive of delayed sleep phase tendencies.

Table 2. Sleep duration and bedtime characteristics of participants

Sleep Quality and Morning Refreshment

Self-reported sleep quality ratings revealed that only 6.5% (n = 10) described their sleep as excellent. The majority rated their sleep as good (45.5%, n = 70) or average (40.3%, n = 62), while 7.8% (n = 12) reported poor or very poor sleep quality (Table 3). Night-time awakenings were common. Approximately 47.4% reported waking up sometimes during the night, 33.1% rarely, and 11% never, while 10.4% experienced frequent or persistent awakenings. This indicates a high prevalence of fragmented sleep within the study population. Regarding morning refreshment, 55% of participants reported feeling refreshed upon waking, 32% felt refreshed only sometimes, and 13% reported never feeling refreshed. Thus, nearly 45% of respondents experienced non-restorative sleep on a regular or intermittent basis.

Table 3. Self-reported sleep quality and night-time sleep characteristics

Daytime Sleepiness and Functional Impairment

Daytime consequences of poor sleep were prominent. While 63% of respondents reported rarely experiencing daytime sleepiness, 27.9% reported frequent daytime fatigue, and 9.1% reported never experiencing it (Table 4). Difficulty in concentration or completing daily tasks due to poor sleep was reported by 63% of participants, indicating a substantial impact of sleep disruption on cognitive functioning and productivity. Unintentional daytime sleep episodes were also common. Approximately 37.7% reported occasional episodes, 28.6% reported frequent episodes, and only 33.8% reported never falling asleep unintentionally during the day. Collectively, 66.3% of respondents experienced some degree of excessive daytime sleepiness.

Table 4. Daytime functional consequences of sleep disruption