Determinants of body weight changes during Ramadan fasting in India amid COVID-19: A cross-sectional study

Abstract

Ramadan intermittent fasting (RIF) presents unique challenges and opportunities for public health and clinical practice, especially in populations with a high prevalence of non-communicable diseases. This study aims to investigate the impact of RIF on weight change among Indian Muslims and explore the associated demographic, dietary, and behavioral factors. A cross-sectional survey was conducted with a sample of Indian Muslim adults who observed RIF. Participants were asked to report their demographic information, family and personal health history, and dietary and lifestyle behaviors before and during Ramadan month. The primary outcome was body weight change, with secondary outcomes including changes in dietary patterns, physical activity, and other health-related lifestyle behaviors. The study found that during Ramadan, nearly half of the participants (48.5%) self-reported a retained initial weight, while a significant fraction (30.9%) self-reported a modest weight reduction between 0.5 to 2.5 kg at the end of Ramadan. Additionally, self-reported eating practices demonstrated moderately altered by about half (48.4%) of the study participants, with 32.2% reporting minor changes and 8.2% indicating substantial changes. An urban residence was associated with a higher likelihood of weight gain, where urban residents showed 3 times the odds of increased weight compared to rural inhabitants. Employment status emerged as a significant determinant for weight fluctuation, influencing both weight gain and loss. During Ramadan, there was a significant rise in snacking frequency, increasing from 21.7% to 32.6% in comparison with pre-Ramadan. The consumption of large quantities of food more frequently grew from 14.9% to 36%, and the incidence of eating despite not being hungry went up from 17.4% to 33.2%. The study demonstrates that RIF is associated with variable changes in body weight among adult Indian Muslims, influenced by urbanization, employment status, and dietary changes. The findings suggest that clinicians should provide tailored advice about body weight regulation during Ramadan and consider integrating community-based health initiatives within religious settings to improve health outcomes.

1. Introduction

The observance of Ramadan intermittent fasting (RIF), one of the 5 pillars of Islam, encompasses a period of abstinence from dawn until sunset over the course of a lunar month (29–30 days). This practice, representing a form of diurnal intermittent fasting, is embraced by adult Muslims globally.^[1] The duration of the daily fast varies, ranging from 11 to 20 hours, and is influenced by geographical differences and seasonal variations in day length. Fasting is traditionally broken with a sunset meal known as Iftar and initiated with a predawn meal termed Suhoor. While this practice is deeply rooted in spirituality, it presents a unique model for studying time-restricted eating and its physiological implications.

Extensive research has investigated the health effects of RIF, revealing improvements in metabolic syndrome parameters, body weight, and body composition, especially visceral fat.^[2] Moreover, observing RIF has been linked to reductions in markers of inflammation and oxidative stress and improvements in glucometabolic regulation and liver function.^[1–3] These findings have extended the interest in RIF beyond its spiritual significance, positioning it as a potential intervention for improving health outcomes.^[4] However, the advent of the COVID-19 pandemic has complicated the observance of Ramadan, particularly in densely populated and diverse nations like India.^[5] The pandemic’s restrictions have imposed changes in daily routines, potentially affecting the lifestyle and dietary habits of individuals observing Ramadan.^[6] Notably, multiple studies highlighted modifications in physical activity (PA) and dietary patterns during the pandemic, along with its adverse effects on mental and emotional well-being.^[7,8]

This interplay between a global health crisis and a period of religious fasting poses significant questions regarding the safety and advisability of traditional fasting practices. While existing literature suggests that RIF does not compromise immune function, the specific impact of fasting during a pandemic remains to be fully understood.^[9,10] Consequently, medical and religious bodies have recommended personalized approaches to fasting, balancing health risks against spiritual commitments.^[11] The COVID-19 pandemic has imposed unprecedented changes in daily life, affecting dietary and lifestyle patterns worldwide.^[12,13] During Ramadan, a period of intermittent fasting, such shifts may have unique implications on the fasting practices and associated behaviors of observing individuals, particularly in the context of restricted movement and altered social structures.

The current research aims to explore the implications of these dietary and lifestyle adjustments on the body weight changes of individuals observing RIF amid the COVID-19 pandemic in India. The restrictions imposed by the pandemic, including curfews and lockdowns, have created an unprecedented context for such an assessment, potentially leading to reduced PA and altered weight changes.^[13]

Therefore, this cross-sectional study hypothesizes that the unique conditions of the COVID-19 pandemic have altered the traditional practices and experiences of Ramadan, potentially impacting dietary behaviors, PA. The objectives of this study coalesce to form a holistic inquiry into the multifaceted impacts of the COVID-19 pandemic on the traditional practice of RIF. Firstly, the current work was designed to assess the changes in body weight in relation to changes in dietary and eating behaviors among the fasting population. Also, the study tries to evaluate the changes in body weight in relation to lifestyle changes which include shifts in PA levels, time spent with family or on computers or television, and sleep patterns that have occurred during the month of Ramadan.

2. Materials and methods

2.1. Study design and sample size calculation

The current study was a cross-sectional, observational study, with targeted recruitment of adult Muslims who fasted during Ramadan. This study was initiated and supervised by researchers in the UAE. A detailed description of the methodology is described elsewhere.^[12,14] Data collection was initiated on the 10th of May 2021 (corresponding to the 27th Ramadan month in 1442 Hijri). The study ended on the 10th of June 2021 (29th Shawwal 1442 Hijri). Inclusion criteria were adult Muslims (≥18 years) who observed fasting during Ramadan. Exclusion criteria were those with mental illnesses. Individuals on special diets and shift workers were excluded from study participation as well. Data collection was done by collaborators from 4 different regions in the country (Northern India, Eastern India, Western India, and South India). The study was conducted adhering to the code of ethics of the Helsinki Guidelines.^[15] Before collecting data, the study was approved by the Bharaath Institutional Ethics Committee (BIEC-021-21). The objectives and procedures of the study were stated before seeking informed consent from participants. In this study, the snowball sampling method was utilized to achieve the necessary sample size. The sample size was determined to be a minimum of 377 participants based on a calculation using the Raosoft sample size calculator, aiming for a margin of error of 5% and a confidence level of 95%.^[16]

2.2. Instrument design and cultural validation

Using previously validated surveys, a self-administered, structured online questionnaire was created.^[17–22] The questionnaire, which was offered in Hindi, Urdu, and English, looked at eating habits, sleeping patterns, nutritional intake, and PA during RIF. The questionnaire underwent rigorous pilot testing to ensure clarity and cultural appropriateness, with the 30 pilot participants being included in the final dataset. Translations adhered to best practices for linguistic and cultural appropriateness as per the methodology.^[23]

2.3. Data collection methodology

This study was initiated and supervised by researchers in the United Arab Emirates (UAE). Later the coordination of the research was undertaken by a dedicated team of researchers in India. In an effort to reach a diverse and representative sample of the population, the team engaged a cadre of voluntary researchers from different regions of the country. These researchers were recruited through specialized research-oriented groups on Facebook, a strategy that leveraged existing academic networks to maximize the study’s reach.

Upon recruitment, each research collaborator was equipped with a unique digital survey form. This form was designed to be disseminated widely via an assortment of online channels, including but not limited to emails, WhatsApp, and Facebook. The unique link assigned to each collaborator ensured that the data could be tracked and consolidated accurately upon completion of the data-collection phase.

This innovative approach to data collection proved to be particularly advantageous during the challenging times of the COVID-19 pandemic. With lockdowns and social distancing measures in place, traditional fieldwork was unfeasible. However, the utilization of digital platforms allowed for an uninterrupted and extensive distribution of the survey, ensuring a comprehensive collection of data despite the constraints imposed by the pandemic.

2.4. Demographic and lifestyle measures

The survey solicited a range of demographic details from participants, encompassing sex, age, marital status (categorized as unmarried, married, separated, or widowed), urbanization level of their residence (classified as urban, or rural), household earnings, living arrangements (whether alone, with peers, or with family), the highest educational qualification achieved, and the total number of days fasted during Ramadan. The fasting duration question was designed to capture variations in fasting practices due to travel, health issues, or other personal reasons.

Given the multi-regional nature of the study, we stratified household income into quintiles to normalize economic status across diverse contexts. Total household income was computed for standardization purposes into 5 quintiles: the upper class (top 20%), upper-middle (upper 20%), basic middle (middle 20%), marginal middle (lower 20%), and lower (lowest 20%).^[24] To assess smoking patterns, specifically cigarette and shisha use, we incorporated a specialized questionnaire to document any changes in smoking habits before and throughout Ramadan.

PA metrics were derived from the internationally recognized short-form International Physical Activity Questionnaire.^[21] This tool allowed us to measure overall PA, including both vigorous and moderate activities, and participants’ perceived energy expenditure before and during the fasting period. For analytical simplicity, we combined vigorous and moderate PA responses into 1 comprehensive PA variable. The Copenhagen Psychosocial Questionnaire, a validated instrument, provided the basis for questions related to screen time, sleep quality, and social interaction.^[22] Responses regarding the use of computers and other devices for both professional and leisure activities were consolidated into a single measure of screen time.

Sociodemographic information included sex and age (years), country of residence, nationality, region, marital status (single, married, divorced, and widowed), living area (city, town, and village), household income, living conditions (alone, with friends or with family), education level, and the number of fasting days experienced (the experienced fasting days, as some people may fast <29 to 30 days of Ramadan month due to different reasons such as travel or unexpected sickness). Participants were asked to self-report the duration of time (hours) they spent on electronic devices such as television and computers for both work/study and entertainment during both day and night hours before and during Ramadan. Total household income was computed for standardization purposes into 5 quintiles: the upper class (top 20%), upper-middle (upper 20%), basic middle (middle 20%), marginal middle (lower 20%), and lower (lowest 20%). The respondents were requested to classify their economic status as per their economic conditions concerning their community and local region/country. A structured, self-administered questionnaire was developed from previously validated questionnaires. The smoking behavior questionnaire was utilized to identify smoking behaviors before and during the month of Ramadan. Dietary behaviors, eating habits and choices of food, snacking behavior, water intake, modification of food groups 20 items.^[19] Consumption of the number of foods was based on the short food frequency questionnaire.^[20] Participants were also asked how many times they consumed fast food or ate out before and during the month of Ramadan. PA level was derived from the International Physical Activity Questionnaire Short Form.^[21]

2.5. Nutritional intake and dietary measures

The dietary section of our survey was comprehensive, inquiring about changes in food consumption habits, frequency of snacking, hydration levels, episodes of substantial food intake, and hunger sensations during Ramadan. T We organized these items into 8 major food categories, with initial responses classified as “not consumed,” “decreased,” “unchanged,” or “increased.” These responses were further distilled into binary terms for analysis. For nutrient-rich food groups such as fruits, vegetables, and proteins, we used the terms “adequate” or “inadequate” to indicate whether consumption met or fell below usual levels. For less essential food groups, including those high in fats, sugars, and salts, we employed the terms “regular” or “irregular” consumption patterns to denote their frequency of intake. This binary classification was extended to other variables like water consumption, PA, dining out, and screen use, to facilitate a clearer analysis of lifestyle changes during the fasting period.

2.6. Statistical analysis

The reliability of the research instrument was ascertained through the calculation of Cronbach alpha, which served to measure the internal consistency of the questionnaire. The appropriateness of the data for the subsequent statistical tests was confirmed by the Kolmogorov–Smirnov test, which was carried out to ensure the normality of the data distribution. In presenting the demographic details of the participants, descriptive statistics were utilized, involving the computation of frequencies and percentages. This provided a base-level depiction of the sample’s demographic profile. In examining the determinants of weight variation during the month of Ramadan, a multinomial logistic regression analysis was conducted. This analysis was pivotal in calculating both unadjusted and adjusted odds ratios, thereby shedding light on the strength of the links between various risk factors and the observed weight changes. The regression model was particularly valuable in discerning the distinct probabilities of experiencing weight loss or gain during the period of fasting. Through the regression analysis, the relationships between several independent variables—namely dietary habits, PA levels, and sociodemographic factors—and the dependent variable of weight change were explicated. The associations were presented in the form of crude odds ratios, illustrating the direct correlations, alongside adjusted odds ratios, which took into account the effect of potential confounding variables. A value of P < .05 was assumed as the significance level. Data were analyzed with IBM SPSS version 23 for Windows (SPSS, Chicago, IL).

3. Results

A total of 1684 responses were received, but 57 of these responses were excluded due to not meeting the inclusion criteria or having incomplete data. Table 1 describes the sociodemographic characteristics of participants. The demographic breakdown from Table 1 of the study population revealed a predominance of male participants, who constitute 56.9% compared to 43.1% of female participants of the 1627 total participants. The average age among those surveyed was around 36 years. Body mass index classification^[25] indicated that half of the participants were of normal weight, while 30.1% were overweight, 14.3% were obese, and a minority of 5.6% were underweight. In terms of residence, the majority (61.2%) were living in cities as opposed to 38.8% in villages. Marital status shows a nearly even split between married (49.8%) and single (47.6%) participants, with divorced and widowed individuals accounting for only small fractions at 1.4% and 1.2%, respectively. Educational levels were skewed towards higher education, with 50.1% having an undergraduate degree, while only 1.4% hold a doctorate (PhD). The employment status of the participants was striking, with 59.3% being unemployed, 38.2% employed, and a small percentage of 2.6% were retired. Household income levels varied, with the largest segment falling into the “Basic Middle (Middle 20%)” income category at 46.6%, followed by the “Upper middle (Upper 20%)” at 18.5%, and “Marginal Middle (Lower 20%)” at 25.3%. The “Upper Class (Top 20%)” and “Lower (Lowest 20%)” categories are the least, represented at 3.6% and 6.0%, respectively.

Table 1.

Sociodemographic characteristics of study participants (n = 1627).

Parameters	Frequency	Percentage
Sex
Female	701	43.1
Male	926	56.9
Age, years (mean ± SD)	35.99 ± 15.7
BMI (kg/m2)
Underweight (<18.5)	45	5.6
Normal (18.50–24.9)	405	50
Overweight (25.0–29.9)	244	30.1
Obese (≥30)	116	14.3
Residential place
City	995	61.2
Village	632	38.8
Marital status
Divorced	22	1.4
Married	811	49.8
Single	774	47.6
Widowed	20	1.2
Educational level
Less than primary education	62	3.8
Primary education	260	16
High school	297	18.3
Undergraduate	814	50.1
Masters	170	10.4
Doctorate	23	1.4
Employment status
Employed	621	38.2
Unemployed	964	59.3
Retired	42	2.6
Household income class
Upper Class (Top 20%)	59	3.6
Upper middle (Upper 20%)	301	18.5
Basic Middle (Middle 20%)	758	46.6
Marginal Middle (Lower 20%)	411	25.3
Lower (Lowest 20%)	98	6

Figure 1 indicates that a substantial segment of the study’s participants reported a familial predisposition to several major health conditions, with 40% having a family history of obesity, 48.90% of hypertension, 50.70% of diabetes, and 32.40% with heart disease. These figures underscore the potential genetic predisposing factors. However, when comparing these statistics to personal health histories, the numbers were markedly lower: 20.30% of participants had a history of obesity, 16% had hypertension, 15.60% had diabetes, and 7.60% had heart disease.

Figure 1.

Personal and family history of chronic medical illnesses (n = 1627).

Table 2 reveals that during Ramadan, about two-thirds of the participants (66.1%) fasted for 21 to 30 days, with a smaller group completing 11–20 days (27.7%), and very few (4.6%) observed 10 days or less; a marginal number (1.6%) did not fast at all. Weight fluctuations were common: while 48.5% reported unchanged body weight by the end of Ramadan, about 30.9% experienced a weight loss of 0.5 to 2.5 kg, and 13.3% gained a body weight.

Table 2.

Lifestyle practices during Ramadan (n = 1627).

Behavior	Frequency	Percentage
Number of days of fasting
1–10	75	4.6
11–20	451	27.7
21–30	1075	66.1
None	26	1.6
Weight lost or gained since the beginning of Ramadan (kg)
0	789	48.5
−0.5 to −2.5	502	30.9
−3 to −4	64	3.9
≥−4.5	10	0.6
0.5 to 2.5	216	13.3
3 to 4	35	2.2
≥+4.5	11	0.7
Have you modified eating practices since the beginning of Ramadan?
No	92	5.7
A little	522	32.2
Moderately	787	48.4
A lot	133	8.2
I don’t know	92	5.7
How often do you snack from Iftar to Suhoor?
Less than once a week	71	4.4
1 to 3 times a week	107	6.6
4 to 6 times a week	105	6.5
1 or 2 times a day, every day	856	52.6
3 to 5 times a day, every day	451	27.7
6 times or more a day, every day	36	2.2
Have modified physical activity level since the beginning of Ramadan?
Decreased	699	43
Increased	148	9.1
Not changed	779	47.9

Changes in eating practices since the beginning of Ramadan were reported by a majority, with 48.4% indicating moderate changes and 32.2% only slight changes. Snacking from iftar to Suhoor was frequent, with 52.6% stacking 1 or 2 times during the night hours, and 27.7% snacking 3 to 5 times. PA levels varied, with 43% of participants reporting decreased activity during Ramadan, 9.1% reported increased activity, and 47.9% reported no change.

Table 3 shows the changes in consumption patterns of various food items during Ramadan among the study participants. The data reveal that the majority of participants maintained their usual consumption levels of vegetables (44.9%), cereals (47.2%), and dairy products (39.4%) during Ramadan. However, there was a notable increase in the consumption of fruits (47.6%), dates (57.7%), and homemade foods (42.5%).

Table 3.

Food consumption modification during Ramadan (n = 1627).

Have you modified consumption during Ramadan?	Decreased	Do not consume	Increased	Remain as usual
Vegetables	429 (26.4%)	91 (5.6%)	376 (23.1%)	730 (44.9%)
Fruits	341 (21%)	55 (3.4%)	775 (47.6%)	455 (28%)
Cereals	418 (25.7%)	69 (4.2%)	371 (22.8%)	768 (47.2%)
Oils and fat	375 (21.9%)	70 (4.3%)	666 (40.9%)	533 (32.8%)
Dairy products	403 (24.3%)	98 (6%)	484 (29.7%)	641 (39.4%)
Pulses	532 (32.7%)	91 (5.6%)	347 (21.3%)	656 (40.3%)
Dates	202 (12.4%)	52 (3.2%)	939 (57.7%)	433 (26.6%)
Fish and seafood	400 (24.6%)	201 (12.4%)	385 (23.7%)	640 (39.3%)
Low-fat meat	277 (17%)	56 (3.4%)	543 (33.4%)	750 (46.1%)
Red meat	405 (24.9%)	113 (6.9%)	489 (30.1%)	619 (38%)
Sugar	235 (14.4%)	124 (7.6%)	616 (37.9%)	651 (40%)
Salt	425 (26.1%)	52 (3.2%)	360 (22.1%)	789 (48.5%)
Salty snacks	492 (30.2%)	165 (10.1%)	405 (24.9%)	564 (34.7%)
Fried food	354 (21.8%)	80 (4.9%)	700 (43%)	492 (30.2%)
Carbonated and/or sugary beverages	455 (28%)	294 (18.1%)	322 (19.8%)	555 (34.1%)
Energy drinks	285 (17.5%)	982 (60.4%)	127 (7.8%)	232 (14.3%)
Hot beverages (Tea/ Coffee)	520 (32%)	162 (10%)	316 (19.4%)	628 (38.6%)
Pastries (cookies, custards, sweets, or cakes)	401 (24.6%)	178 (10.9%)	424 (26.1%)	623 (38.3%)
Homemade foods	255 (15.7%)	41 (2.5%)	691 (42.5%)	639 (39.3%)
Traditional dishes	321 (19.7%)	63 (3.9%)	574 (35.3%)	668 (41.1%)

Conversely, a decrease in consumption was observed for pulses (32.7%), salty snacks (30.2%), and hot beverages like tea and coffee (32%). A significant proportion of participants reported not consuming energy drinks at all (60.4%). Meanwhile, changes in the consumption of oils and fat, fish and seafood, and red meat were mixed with no clear trend towards increase or decrease. Overall, the consumption patterns exhibit a mix of adherence to traditional dietary habits and adaptations to the fasting requirements of Ramadan.

Table 4 shows a notable improvement in participants’ self-reported health state during Ramadan, with a rise in those rating their self-reported health status as “excellent” from 23.7% to 41%, and a corresponding decrease in those rating “good.” A similar trend was observed in participants’ assessment of their diet quality, with those rating it as “excellent” increased from 16.5% to 33%. Additionally, there was a significant decline in ordering food delivery or takeaways and eating out in restaurants during Ramadan. During Ramadan, there was a significant rise in snacking frequency, with the percentage of individuals snacking 3 to 5 times daily increasing from 21.7% to 32.6%. The consumption of large quantities of food more frequently grew from 14.9% to 36%, and the incidence of eating despite not being hungry went up from 17.4% to 33.2% during Ramadan in comparison with before Ramadan.

Table 4.

Eating behaviors difference before and during Ramadan (n = 1627).

Behavior	Before Ramadan n(%)	During Ramadan n(%)	P-value
Self-reported health state
Excellent	386 (23.7%)	667 (41%)	<.0001*
Very good	543 (33.4%)	586 (36%)
Good	586 (36%)	287 (17.6%)
Fair	105 (6.5%)	77 (4.7%)
Poor	7 (0.4%)	10 (0.6%)
Self-rated diet quality
Excellent	268 (16.5%)	537 (33%)	<.0001*
Very good	508 (31.2%)	584 (35.9%)
Good	639 (39.3%)	369 (22.7%)
Fair	187 (11.5%)	119 (7.3%)
Poor	24 (1.5%)	17 (1%)
Order food delivery or takeaways
Never or rarely	685 (42.1%)	876 (53.9%)	<.0001*
Daily	16 (1%)	22 (1.4%)
1–2 times per week	198 (12.2%)	119 (7.3%)
3–6 times per week	58 (3.6%)	58 (3.6%)
≥1 time per month	669 (41.1%)	551 (33.9%)
Eat out in a restaurant during night time
Never or rarely	841 (51.7%)	1118 (68.8%)	<.0001*
Daily	14 (0.9%)	13 (0.8%)
1–2 times per week	104 (6.4%)	66 (4.1%)
3–6 times per week	54 (3.3%)	33 (2%)
≥1 time per month	613 (37.7%)	396 (24.3%)
Snacking during night hours
No	346 (21.3%)	404 (24.8%)	<.0001
Less often	927 (57%)	800 (42.6%)
More often	353 (21.7%)	529 (32.6%)
Consume large quantities of food
No	393 (24.2%)	401 (24.6%)	<.0001
Less often	990 (60.9%)	642 (39.4%)
More often	244 (14.9%)	585 (36%)
Eating despite not being hungry
No	409 (25.1%)	456 (28%)	<.0001
Less often	935 (57.5%)	631 (38.8%)
More often	283 (17.4%)	540 (33.2%)
Water consumption
1–3 cups	199 (12.2%)	289 (17.8%)	<.0001
4–7 cups	743 (45.5%)	766 (47.1%)
8 cups or more	684 (42%)	571 (35.1%)
Cigarette smoking (no. of cigarettes)
0	1399 (86%)	1449 (89.1%)	1
1–5	95 (5.8%)	132 (8.1%)
6–10	98 (6%)	36 (2.2%)
11–20	28 (1.7%)	9 (0.6%)
>20	7 (0.4%)	1 (0.1%)
Shisha smoking (no. of days)
0	1462 (89.9%)	1511 (92.9%)	1
1–5	90 (5.5%)	76 (4.7%)
6–10	48 (3%)	27 (1.7%)
11–20	16 (1%)	7 (0.4%)
All 30 days	11 (0.7%)	6 (0.3%)

^*Fisher exact test was used.

Table 5 reflects changes in lifestyle behaviors, where assessments of eating healthy food, engaging in PA, and self-reported sleep quality showed a significant positive trend during Ramadan, with slight improvements in each category. Mental well-being and the ability to perform routine normal activities also witnessed improvements during the holy month, with more participants rating these aspects of their lives as “excellent” or “very good.”

Table 5.

Lifestyle characteristics of the participants (n = 1627).

	Before Ramadan n(%)	During Ramadan n(%)	P-value
Living with
Alone	132 (8.1%)	124 (7.6%)	<.0001
With Family	1360 (83.6%)	1446 (88.9%)
With Friends	135 (8.3%)	57 (3.5%)
Used to do any exercise for at least 10 minutes at a time
>3 times/week	377 (23.2%)	208 (12.8%)	<.0001
1 to 3 times a week	819 (50.3%)	665 (40.9%)
None	430 (26.4%)	753 (46.3%)
Used to do heavy lifting, digging, aerobics, or fast bicycling for at least 10 minutes at a time
>3 times/week	297 (18.3%)	125 (7.7%)	<.0001
1 to 3 times a week	478 (29.4%)	463 (28.5%)
None	851 (52.3%)	1038 (63.8%)
Used to do jogging, bike riding, brisk walking, or swimming for at least 10 minutes at a time
>3 times/week	426 (36.2%)	265 (16.3%)	<.0001
1 to 3 times a week	635 (39.1%)	493 (30.3%)
None	565 (34.7%)	868 (53.3%)
Duration of night sleep (hours)
7–9	792 (48.7%)	714 (43.9%)	<.0001
<7	376 (23.1%)	497 (30.5%)
More than 9	458 (28.1%)	415 (25.5%)
Self-reported sleep quality
Good	1008 (62%)	621 (38.2%)	<.0001
Poor	168 (10.3%)	192 (11.8%)
Very good	450 (27.7%)	813 (50%)
Self-reported energy level
Energized	599 (36.8%)	813 (50%)	<.0001
Lazy	150 (9.2%)	229 (14.1%)
Neutral	877 (53.9%)	584 (35.9%)
Daily time spent with family
None	136 (8.4%)	126 (7.7%)	<.0001
<30 minutes	153 (9.4%)	210 (12.9%)
1–2 hours	454 (27.9%)	276 (17%)
3–5 hours	312 (19.2%)	386 (23.7%)
More than 6 hours	571 (35.1%)	628 (38.6%)
Daily time spent on the electronic devices
None	213 (13.1%)	316 (19.4%)	<.0001
<30 minutes	150 (9.2%)	477 (29.3%)
1–2 hours	671 (41.2%)	466 (28.6%)
3–5 hours	375 (23%)	217 (13.3%)
More than 6 hours	217 (13.3%)	150 (9.2%)
Daily time spent on the TV
None	82 (5%)	182 (11.2%)	<.0001
<30 minutes	214 (13.2%)	506 (31.1%)
1–2 hours	729 (44.8%)	646 (39.7%)
3–5 hours	458 (28.1%)	212 (13%)
More than 6 hours	143 (8.8%)	80 (4.9%)

A dramatic shift in sedentary behaviors was observed, with a decrease in time spent on the screen such as computer and TV during Ramadan. The data indicates a shift towards less screen time and potentially more engagement in other activities, whether for religious observances or social interactions.

Table 6 examines the likelihood of weight change during Ramadan concerning demographic and behavioral factors. Urban residents were more likely to gain weight 3 times greater (OR = 3.01) than rural residents. Age also played a role; participants aged 20 or less were more likely to gain weight (OR = 1.88) compared to other age groups. Employment status was a significant determinant, with employed individuals more likely to experience both weight gain (OR = 1.99) and weight loss (OR = 2.38) during Ramadan. A history of diabetes, hypertension, or heart disease was associated with a decreased by 42% likelihood of gaining weight (OR = 0.58). Changes in eating practices during Ramadan were also influential; those unsure of their changes were more likely to gain weight (OR = 1.95), while those who did not change their eating habits were less likely to gain weight (OR = 0.4). The frequency of eating out and snacking behaviors during Ramadan was associated with more weight change, with less frequent eating out or snacking associated with a decreased likelihood of weight gain. Consuming large quantities of food less often was associated with a lower likelihood of weight gain (OR = 0.52), and eating despite not feeling hungry less often was similarly associated with reduced odds of weight gain (OR = 0.58). These associations suggest that urban living, employment status, and specific eating behaviors during Ramadan may shape the magnitude of body weight changes in this population.

Table 6.

Multinomial logistic regression showing crude and adjusted ORs of risk factors for weight loss and gain during Ramadan and respective P-values (n = 1627).

Variable	Weight gain	Weight loss	P-Value	Weight gain	Weight loss
	Crude OR (95% CI)	Crude OR (95% CI)		Adjusted OR (95% CI)	Adjusted OR (95% CI)
Residence
Urban	4.07 (2.83–5.84)	1.99 (1.57–2.51)	<0.0001	3.01 (1.98–4.56)	1.63 (1.24–2.15)
Rural	Reference			Reference
Age (years)
20 or less	1.23 (0.82–1.88)	0.66 (0.47–193)	<.0001	1.88 (1.06–3.34)	1.28 (0.83–1.96)
21–30	1.01 (0.73–1.39)	0.6 (0.47–0.77)		1.43 (0.93–2.19)	0.91 (0.67–1.23)
31–50	Reference			Reference
Sex
Male	Reference		.006	Reference
Female	1.09 (0.81–1.46)	0.72 (0.57–0.9)		1.24 (0.87–1.76)	0.87 (0.68–1.12)
Employment status
Unemployed	Reference		<.0001	Reference
Employed	2.31 (1.72–3.12)	2.81 (2.23–3.53)		1.99 (1.33–2.97)	2.38 (1.79–3.16)
BMI (kg/m2)
Underweight (<18.5)	1.15 (0.64–2.05)	1.06 (0.66–1.71)	.16	1.09 (0.65–2.00)	1.02 (0.62–1.70)
Normal (18.50–24.9)	0.11 (0.01–0.84)	0.78 (0.36–1.68)		0.15 (0.02–0.90)	0.80 (0.40–1.60)
Overweight (25.0–29.9)	1.11 (0.6–2.04)	0.88 (0.53–1.47)		1.10 (0.61–2.00)	0.90 (0.55–1.45)
Obese (≥30)	Reference
History of diabetes, hypertension, or heart disease
No	0.62 (0.46–0.84)	0.63 (0.49–0.79)	<.0001	0.58 (0.39–0.85)	0.78 (0.59–1.05)
Yes	Reference			Reference
Changed eating practices during Ramadan
I don’t know	2.49 (1.52–4.11)	0.72 (0.41–1.25)	<.0001	1.95 (1.11–3.43)	0.67 (0.38–1.2)
No	0.64 (0.31–1.31)	0.67 (0.41–1.11)		0.4 (0.19–0.85)	0.58 (0.34–0.98)
Yes	Reference			Reference
Cups of water drunk/night during Ramadan
1–3 cups	1.3 (0.82–2.07)	1.06 (0.76–1.47)	<.0001	1.9 (1.14–3.17)	1.16 (0.81–1.66)
4–7 cups	2.5 (1.77–3.53)	1.74 (1.36–2.23)		2.37 (1.64–3.44)	1.62 (1.24–2.11)
8 cups or more	Reference			Reference
Frequency of ordering food or takeaway during Ramadan
Never or rarely	0.22 (0.16–0.31)	0.79 (0.62–1.01)	<0.0001	0.28 (0.18–0.42)	0.81 (0.59–1.12)
Daily	0.36 (0.08–1.62)	1.12 (0.45–2.8)		0.4 (0.08–2.07)	2.48 (0.84–7.29)
1–2 times weekly	1.17 (0.71–1.91)	1.04 (0.65–1.66)		0.99 (0.57–1.7)	1.14 (0.69–1.9)
3–6 times weekly	0.57 (0.26–1.22)	0.74 (0.39–1.4)		0.56 (0.25–1.29)	0.84 (0.43–1.67)
1 or more times monthly	Reference			Reference
Frequency of eating out during Ramadan night hours
Never or rarely	0.45 (0.33–0.62)	0.89 (0.68–1.16)	<.0001	0.88 (0.58–1.33)	1.17 (0.83–1.65)
Daily	0.31 (0.04–2.51)	0.87 (0.26–2.95)		0.64 (0.07–5.59)	1.19 (0.33–4.29)
1–2 times weekly	1.24 (0.64–2.37)	0.98 (0.53–1.82)		1.31 (0.62–2.76)	0.85 (0.43–1.69)
3–6 times weekly	0.59 (0.23–1.5)	0.14 (0.03–0.6)		0.91 (0.32–2.56)	0.11 (0.24–0.55)
1 or more times monthly	Reference			Reference
Snacking during Ramadan night hours
Less often	0.53 (0.37–0.75)	0.66 (0.5–0.87)	<.0001	0.78 (0.46–1.32)	0.75 (0.51–1.11)
More often	0.53 (0.37–0.77)	0.45 (0.33–0.6)		0.87 (0.49–1.56)	0.68 (0.43–1.09)
No	Reference			Reference
Consuming large quantities of food during Ramadan night hours
Less often	0.52 (0.36–0.76)	0.95 (0.72–1.26)	<.0001	0.76 (0.43–1.35)	1.39 (0.89–2.17)
More often	0.65 (0.45–0.93)	0.66 (0.49–0.89)		1.33 (0.76–2.33)	1.42 (0.88–2.75)
No	Reference			Reference
Eating despite not feeling hungry during Ramadan night hours
Less often	0.58 (0.41–0.83)	0.94 (0.72–1.23)	<.0001	0.97 (0.58–1.61)	1.09 (0.74–1.61)
More often	0.59 (0.41–0.84)	0.59 (0.44–0.79)		0.75 (0.44–1.29)	0.79 (0.51–1.22)
No	Reference			Reference

4. Discussion

This study offers a comprehensive examination of the relationship between demographic characteristics, behavioral patterns, and body weight changes during Ramadan among Indian Muslims, shedding light on the intricate interactions between the different determinants of health. To the best of our knowledge, this is the first nationwide study performed to assess Ramadan dietary patterns in India concerning body weight changes and self-reported overall lifestyle changes during Ramadan.

The marked participation of males in the survey parallels trends documented in regional research, signaling potential sex biases in the willingness to participate by men in minimal-risk studies.^[26,27] Notably, the high prevalence of family history of non-communicable diseases such as diabetes and hypertension compared to individual histories may point to a genetic predisposition^[28] emphasizing the imperative for culturally sensitive health interventions that address these hereditary risks. The observance of fasting by a majority of participants did not universally translate into weight loss, highlighting the multifactorial nature of weight dynamics during Ramadan.^[29]

The propensity for weight gain among urban dwellers suggests the influence of an urban environment, which often promotes sedentary lifestyles and access to high-calorie foods^[30] phenomenon warranting urban-specific public health strategies. Employment status was another influential factor, where being employed was associated with variable weight outcomes. This dual effect may reflect the divergent impacts of various occupations on PA levels and dietary options during Ramadan.^[31] Hence, there is a critical need to delve deeper into the socioeconomic transitions that influence lifestyle diseases in this context.^[32]

The association between uncertainty in dietary behavior changes during Ramadan and weight gain underscores the potential benefits of mindful eating practices.^[33] The incongruity between self-perceived health improvement and actual lifestyle modifications suggests a complex interplay between perception and behavior that requires further exploration.

Despite the cultural significance of Ramadan, the maintenance of PA was reported by nearly half of the participants, aligning with the literature that emphasizes PA as an essential component of weight management.^[34] This indicates that religious fasting is not a standalone solution for weight loss, advocating for a holistic approach to health promotion that includes PA.

The rise in individuals snacking between Iftar and Suhoor from 21.7% to 32.6%, and the increase in those consuming large quantities of food from 14.9% to 36%, along with a similar rise in eating without hunger from 17.4% to 33.2%, suggest a behavioral shift that may contribute to weight gain. These behaviors could offset the potential weight loss benefits of fasting due to increased caloric intake during the non-fasting hours. It is crucial to consider that while the fasting period might reduce overall meal frequency, the substantial increase in snacking and consumption of large portions during active eating periods could lead to a net increase in caloric intake, thereby influencing body weight.^[29] Further research is needed to explore the balance between caloric restriction during the fast and the increased intake during nighttime eating and its net effect.

PA levels remained unchanged, suggesting an adaptive response to restrictions. Self-reported sleep quality improved, suggesting a complex interaction between the pandemic’s psychological impacts and Ramadan spiritual experiences. The study highlights the importance of considering the dynamic interplay between public health challenges and individual and community adaptive capacities during religious and culturally significant periods. Instead, it suggests that individuals may have found unique ways to adapt to the challenges posed, maintaining or even improving certain aspects of health behavior. These insights contribute to the broader discourse on health behavior resilience during the pandemic and highlight the need for public health strategies that support healthy practices in times of crisis.^[35]

Critically, these findings must be interpreted within the context of the study’s limitations. The reliance on self-reported data introduces the potential for recall bias and social desirability bias, which could skew the results.^[36] Additionally, the cross-sectional nature of the study precludes any causal inferences, making it difficult to directly attribute changes in behaviors to the pandemic without longitudinal data. Our findings also bring to light the broader epidemiological concerns of non-communicable disease prevalence within the Indian Muslim community. The disparity between the reported family and personal history of chronic diseases could signify underreporting or delayed onset of these conditions, raising questions about health literacy and access to healthcare in this demographic.^[37]

Epidemiological data suggest significant health disparities among Indian Muslims, often linked to socioeconomic, educational, and healthcare accessibility factors.^[38] The critical interplay between religious practices like fasting during Ramadan and chronic disease management underscores the need for targeted public health initiatives. Culturally tailored health education programs could offer guidance on nutrition and disease management during fasting periods.^[39] Additionally, mosque-based interventions could serve as a platform for promoting PA and health screenings.^[40]

The study possesses several strengths that contribute to its value in the field of public health and clinical practice. Firstly, its focus on the Indian Muslim population during Ramadan addresses a significant gap in the literature regarding the intersection of religious practices and chronic disease management. The study’s sizable sample size enhances the statistical power and the reliability of the findings. Furthermore, the comprehensive data collection on various lifestyle behaviors, such as diet and PA, provides a holistic view of the participants’ health during Ramadan. Despite these strengths, the study’s limitations must be acknowledged. The cross-sectional design limits the ability to draw causal inferences from the observed associations. Self-reported data can be subject to bias, including recall bias and social desirability bias, which may impact the accuracy of reported behaviors and health status. The study also did not account for the intensity of fasting or the variations in fasting practices, which can differ widely within the Muslim community. Another limitation is the lack of biochemical verification of chronic diseases, which relies solely on participants’ reporting. Furthermore, the findings may not be generalizable beyond the Indian Muslim population or those who observe Ramadan.

The study’s findings have several implications for clinical practice. Clinicians caring for Indian Muslim patients may need to be particularly attentive to the management of chronic diseases during Ramadan. During Ramadan, healthcare providers should engage in culturally sensitive counseling, advising patients on the risks and benefits of fasting. The significant change in eating and PA behaviors during Ramadan also underscores the need for clinicians to provide tailored advice on maintaining a healthy diet and lifestyle during this period. Moreover, the findings suggest the potential for integrating religious and cultural considerations into the design of health promotion programs. For instance, leveraging community settings such as mosques for health education and screenings could improve the reach and effectiveness of such programs. Furthermore, providers should incorporate a comprehensive assessment of family history when managing chronic diseases in Indian Muslim patients, particularly during Ramadan. Clinicians should also be equipped to offer culturally sensitive advice on fasting, medication management, and lifestyle adjustments to support patient well-being during this period.^[41]

The potential integration of religious and cultural considerations into health promotion programs could be instrumental in enhancing their efficacy.^[42] Utilizing community venues like mosques for health education could substantially improve outreach and engagement.^[43]

In summary, this study illustrates the complex interactions between sociodemographic factors, lifestyle behaviors, and weight changes during Ramadan. It underscores the necessity for a multifaceted public health approach during fasting periods, attentive to the individual’s environment, employment status, and dietary mindfulness. Longitudinal studies are warranted to corroborate these findings and further elucidate the influences on health outcomes during Ramadan and beyond.

5. Conclusion

In conclusion, this study has critically examined the impact of observing RIF on weight change among Indian Muslims, delineating the relationships with demographic factors, lifestyle, and dietary choices. The findings reveal that observing RIF is a widespread practice. Urban living, employment status, and uncertainty in dietary behaviors during Ramadan emerge as significant determinants. The study’s findings indicate a surprising adaptability in dietary and PA behaviors among Indian Muslims during Ramadan amid the COVID-19 pandemic. While some anticipated negative impacts were observed, the overall data suggest a resilience that has potential implications for public health strategies during prolonged crises. Given the limitations inherent in the study’s design and methodology, further research is warranted to understand the long-term effects of these behavioral adaptations. Hence further research is needed to explore these relationships longitudinally and across more diverse populations. Nonetheless, the current research provides valuable insights for the development of culturally appropriate health promotion strategies and highlights the need for healthcare providers to adopt a more culturally competent approach to patient care during Ramadan. The study’s implications extend to public health policy, emphasizing the potential benefits of community-based health initiatives within religious settings.

Author contributions

Conceptualization: Moien A.B. Khan, Sajjad Ahmed Khan, Kalaivani Annadurai, Surya Bahadur Parajuli, Sohrab Amiri, Moezalislam Faris.

Formal analysis: Kalaivani Annadurai.

Investigation: Sajjad Ahmed Khan, Waseem N. Ahmed, Tejaswini Ashok, Dhaval Shah, Yakub Sayyad, Ashish Dubey, Abdullah Tariq, Romana Riyaz, Fayeza Hasan.

Methodology: Surya Bahadur Parajuli.

Resources: Saoud Altamimi.

Software: Saoud Altamimi.

Supervision: Sohrab Amiri, Moezalislam Faris.

Validation: Moezalislam Faris.

Writing – original draft: Moien A.B. Khan, Sajjad Ahmed Khan, Surya Bahadur Parajuli, Waseem N. Ahmed, Fayeza Hasan, Moezalislam Faris.

Writing – review & editing: Moien A.B. Khan, Surya Bahadur Parajuli, Sohrab Amiri, Moezalislam Faris.