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Role of dietary patterns and inter-meal intervals in hypopharyngeal cancer: A case–control study from Assam, India
For correspondence: Dr Lipi B. Mahanta, Department of Mathematical and Computational Sciences, Physical Sciences Division, Institute of Advanced Study in Science and Technology, Guwahati 781 035, Assam, India e-mail: lipimahanta@yahoo.co.in
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Received: ,
Accepted: ,
How to cite this article: Dey R, Mahanta LB, Rahman T, Krishnatreya M. Role of dietary patterns and inter-meal intervals in hypopharyngeal cancer: A case–control study from Assam, India. Indian J Med Res. 2026;163:387-98. doi: 10.25259/IJMR_2866_2025.
Abstract
Background and objectives
Despite a high incidence of hypopharyngeal cancer in northeast India, the role of dietary patterns and meal timing remains poorly understood. This study examined the association between inter-meal intervals, dietary patterns, and the risk of hypopharyngeal cancer in northeastern India.
Methods
A hospital-based case-control study was conducted at a tertiary cancer centre in northeastern India, enrolling 300 histologically confirmed cases with hypopharyngeal cancer and 300 frequency-matched controls between May 2023 and August 2024. Dietary intake and inter-meal intervals were assessed using a semi-quantitative food frequency questionnaire. Multivariable logistic regression calculated odds ratios and 95% confidence intervals, adjusting for demographics, socioeconomic status, alcohol consumption, smoking, and tobacco use, including areca nut consumption.
Results
Prolonged inter-meal intervals (≥5 h) conferred a nearly three-fold increased risk of hypopharyngeal cancer compared to intervals <4 h [adjusted odds ratio (OR) 2.69, 95% confidence interval (CI): 1.56-4.69]. Strong protective effects emerged for citrus fruits (highest tertile OR 0.13, 95% CI: 0.05-0.32) and leafy green vegetables (highest tertile OR 0.21, 95% CI: 0.09-0.49). Coffee consumption was inversely associated with the risk of hypopharyngeal cancer (OR 0.54, 95% CI: 0.30-0.94), while higher milk intake increased the risk of hypopharyngeal cancer (OR 2.06, 95% CI: 1.22-3.52).
Interpretation and conclusions
We provide epidemiological evidence linking prolonged inter-meal intervals to the risk of hypopharyngeal carcinoma in an Indian population. Meal timing patterns may be as important as dietary composition for cancer prevention, with implications for public health interventions in high-risk populations.
Keywords
Case-control study
Cancer prevention
Chrononutrition
Dietary patterns
Hypopharyngeal cancer
Inter-meal intervals
Hypopharyngeal cancer represents one of the most aggressive forms of head and neck malignancies, accounting for approximately 3-5% of all head and neck cancers globally.1-3
India bears a disproportionate burden of head and neck cancers, with age-standardised incidence rates of 25.9 and 8.0 per 100,000 for males and females, respectively. 4 Within India, northeastern States show substantially elevated HC rates. Population-Based Cancer Registries in Assam report male incidence rates of 20.0 (Kamrup Urban), 10.8 (Dibrugarh), and 13.0 (Cachar) per 100,000, 5,6 suggesting the involvement of region-specific risk factors, including unique dietary patterns, tobacco use practices, and environmental exposures.
While tobacco and alcohol consumption are well-established HC risk,7-9 mounting evidence highlights the role of dietary factors in both disease development and prevention.10,11 Recent chrononutrition research has unveiled the importance of meal timing and eating patterns in health outcomes,12-16 yet the association between inter-meal intervals and cancer risk remains largely unexplored.
Several biological mechanisms support a potential role of inter-meal intervals in the development of hypopharyngeal cancer. Prolonged gaps between meals can lead to sustained gastric acid secretion without food buffering, increasing gastroesophageal reflux, 17,18 irregular eating patterns may disrupt circadian rhythms, affecting DNA repair and immune function, 12,13 and the timing of carcinogen exposure relative to meals may influence mucosal vulnerability. These mechanisms are particularly relevant for the hypopharynx, which is exposed to both ingested substances and refluxate. For these reasons, the inter-meal interval was included as a pre-specified dietary-timing exposure in this study.
Northeastern India represents a distinct epidemiological context, characterised by unique dietary practices and high consumption of areca nut and tobacco products, 19,20 and irregular meal patterns often influenced by agricultural work schedules, and socioeconomic constraints. Combined with high areca nut consumption, the practice of consuming areca nut during prolonged inter-meal periods may amplify mucosal irritation through synergistic mechanisms.
This study had two primary objectives: (i) to examine the association between inter-meal interval patterns and the risk of hypopharyngeal cancer; and (ii) to assess the associations between dietary composition (fruits, vegetables, and other food groups) and the risk of hypopharyngeal cancer in northeastern India. We hypothesised that prolonged inter-meal intervals would increase the risk of hypopharyngeal cancer through reflux-mediated mechanisms, while higher consumption of fruits and vegetables would confer protective effects through antioxidant and anti-inflammatory pathways.
Methods
This case-control study was undertaken by the department of Mathematical and Computational Sciences, Physical Sciences Division, Institute of Advanced Study in Science and Technology (IASST), Guwahati, Assam, in collaboration with Dr. B. Borooah Cancer Institute, Guwahati, Assam, India. Written informed consent was obtained from all participants, and ethical approval was granted by the Institutional Ethics Committee.
Study design and setting
A hospital-based case-control study was conducted between May 2023 and August 2024 in northeastern India. Cases were recruited from a tertiary cancer centre serving as a major regional referral hub. Controls were randomly selected from hospital premises and frequency-matched to cases by age, gender, and broad geographic location using the region’s administrative divisions.
Sample size and participant selection
Sample size was determined using 5% type I error and 80% power, hypothesising that unhealthy dietary patterns might increase the odds of hypopharyngeal cancer by 1.6 times. We enrolled 300 newly diagnosed cases with hypopharyngeal cancer and 300 controls using consecutive sampling throughout the recruitment period.
Cases were prospectively enrolled immediately after endoscopic and histopathological confirmation and before initiation of any treatment. Controls consisted mainly of patient caregivers or hospital visitors willing to participate, frequency-matched to cases by age group, sex, and region, with no cancer history or clinical suspicion. Both cases and controls were permanent residents of the study region, aged above 18 years, and physically and mentally fit for interviews. Exclusion criteria included residence outside the geographic region, recurrent or metastatic cancer diagnosis, or inability to participate due to health limitations. To reduce the possibility of bias from symptom-driven alterations in eating habits, interviewers confirmed that cases reported their habitual dietary intake and meal-timing patterns preceding symptom onset, with particular attention to differentiating long-standing dietary habits from any recent changes attributable to emerging symptoms.
Data collection and exposure assessment
Data were collected using a structured, interviewer-administered questionnaire developed after reviewing relevant literature 21,22 and pre-tested to ensure clarity and reliability. It captured information on demographics, socioeconomic status (SES), dietary intake, and lifestyle factors. Using the year before symptom onset (cases) or interview (controls) as a reference timeframe, interviewers elicited long-established practices rather than recent changes, minimising bias from disease-related dietary modifications. All interviews were conducted face-to-face in confidential settings by trained field investigators.
Socioeconomic status assessment
SES was assessed using a composite index derived from family income, education level, and occupation. Ordinal scores (1-4) were assigned to each domain. The scores were summed (range: 3-12) and regrouped into tertiles (≤5=low, 6-8=middle, ≥9=high), reflecting the modified Kuppuswamy scale structure. 23
Dietary assessment
Dietary intake was evaluated using a semi-quantitative food frequency questionnaire listing commonly consumed food items in the study region, including rice, roti, fruits, vegetables, fish, meat, dairy products, and traditional foods. Food items were grouped into categories for analysis. Fruit categories included: (i) total fruits (banana, apple, mango, melon, watermelon, pear, grapes, and citrus fruits); (ii) citrus fruits (oranges, lemons, limes); and (iii) non-citrus fruits (remaining fruits from total fruit list). Vegetable categories comprised: (i) total vegetables (encompassing all raw and cooked vegetables consumed); (ii) leafy green vegetables (spinach, water spinach, colocasia, fiddlehead fern, palak, and salad); and (iii) yellow-orange vegetables (carrots and pumpkins). These categorisations were established based on phytochemical composition and regional dietary patterns. Participants reported consumption frequency during the year prior to the interview with response options: Never, ≤1 time/month, ≤1 time/week, 2-4 times/week, about once per day, or more than once per day.
Assessment of inter-meal intervals
Inter-meal intervals represent the duration between consecutive eating occasions throughout the day. Participants recalled typical eating patterns during the year prior to the interview, including timing of all meals and snacks in a 24-h format. We calculated daytime intervals from the first morning meal to the last evening meal and identified the longest interval, excluding the overnight fasting period. Tea or coffee without substantial food was not counted as an eating occasion. Participants were categorised into three groups: <4 h (short interval, reference), 4-5 h (moderate interval), and ≥5 h (prolonged interval). The 5-h threshold was selected based on gastric physiology, as intervals exceeding 5 h may result in prolonged acid secretion without food buffering, potentially increasing reflux and mucosal irritation. Inter-meal interval was also examined continuously (per 1-h increase) to assess dose-response. In this study population, intervals ranged from 2 to 11 h, with a median of 5.0 h (interquartile range 4.0–6.0 h).
Statistical analysis
Data management proceeded in three stages. Questionnaire responses were transcribed into Microsoft Excel, imported into IBM SPSS Statistics v26 (IBM, Armonk, NY, USA) for data cleaning, then exported to R v4.1.4 for analyses. Baseline characteristics were expressed as frequency and percentage. Pearson chi-square test and Fisher’s exact tests detected associations between exposures and outcome. For each food group, intake categories were defined by tertiles of the control distribution.
Binary unconditional logistic regression in adjusted models determined odds ratios and 95% confidence intervals. To comprehensively address potential confounding by established risk factors, we employed three sequential adjustment models. Model 1 (Adjusted odds a) adjusted for age group (≤35, 36-50, 51-65, >65 yr), gender, SES, and administrative division. Model 2 (Adjusted odds b) additionally adjusted for areca nut consumption (yes/no), smoking (yes/no), and smokeless tobacco consumption (yes/no). Model 3 (Adjusted odds c) further controlled for duration (years) and intensity (per-day frequency) of areca nut consumption, smoking, and smokeless tobacco use, plus alcohol consumption (yes/no). This progressive adjustment strategy ensures that observed dietary associations are independent of the major established risk factors for hypopharyngeal cancer in this population. The first tertile was the reference group for categorical variables.
Linear trend tests were performed, treating categorical variables as ordinal. Models were implemented using the GLM function (family=binomial), and chi-square tests were performed. Two-sided P<0.05 was considered statistically significant. Model diagnostics assessed multicollinearity using variance inflation factors (VIF)<2 for all predictors. Global calibration was evaluated with the Hosmer-Lemeshow test.
Results
Between May 2023 and August 2024, 300 eligible cases and 300 controls were enrolled in a frequency-matched design. We approached 411 potential controls, of whom 300 agreed to participate (73.0% response rate).
Socio-demographic and lifestyle characteristics of the study participants are summarised in Figure 1 and Supplementary Table. Cases and controls demonstrated similar distributions across matching variables, including administrative region, age, sex, religious affiliation, caste category, and urban/rural residence. A notable SES disparity emerged, with cases showing greater representation in lower socioeconomic strata (Fig. 1). Cases exhibited significantly higher rates of cigarette smoking, areca nut consumption, and smokeless tobacco use compared to controls (all P<0.001). As shown in Figure 1, the age distribution of cases and controls was comparable, with the highest proportion in the 50–65 yr age group (cases: 52.3%; controls: 52.7%).

- Dumbbell plot of baseline characteristics among cases and controls.
After comprehensive multivariable adjustment for all major established risk factors (tobacco use, areca nut consumption, alcohol intake, and sociodemographic factors), habitual inter-meal intervals ≥5 hours conferred almost three-fold increased HC odds relative to intervals <4 h [Odds ratio (OR)=2.69, 95% confidence interval (CI): 1.56-4.69], whereas gaps of 4-5 h showed no significant association (OR 1.12, 95% CI: 0.66-1.88) ( Table I, Fig. 2). When analysed as a continuous variable, each one-hour increase in inter-meal interval was associated with 46% increased odds of HC (OR=1.46, 95% CI: 1.20-1.80, P<0.001), demonstrating a clear dose-response relationship. The consistency between categorical and continuous analyses strengthens causal inference. Higher roti consumption demonstrated protective effects (OR=0.48, 95% CI: 0.28-0.82) ( Table I).
| Dietary factor | Case (n,%) | Control (n,%) | Crude odds ratio | Adjusted oddsa | Adjusted oddsb | Adjusted oddsc |
|---|---|---|---|---|---|---|
| Inter-meal intervals (continuous, per h) | 1.27 (1.09-1.48) | 1.32 (1.12-1.56) | 1.34 (1.13-1.61) | 1.50 (1.23-1.86) | ||
| Inter-meal intervals | ||||||
| <4 h | 99 (33) | 119 (39.67) | ||||
| 4-5 h | 99 (33) | 118 (39.33) | 1.01 (0.69-1.47) | 1.06 (0.71-1.59) | 1.04 (0.66-1.62) | 1.12 (0.66-1.88) |
| 5+ h | 102 (34) | 63 (21) | 1.95 (1.29-2.95) | 2.14 (1.38-3.33) | 2.15 (1.33-3.50) | 2.69 (1.56-4.69) |
| Rice | ||||||
| 1st Tertile | 122 (40.67) | 92 (30.67) | ||||
| 2nd Tertile | 92 (30.67) | 106 (35.33) | 0.65 (0.44-0.96) | 0.67 (0.45-1.01) | 0.76 (0.48-1.20) | 0.74 (0.44-1.23) |
| 3rd Tertile | 86 (28.67) | 102 (34) | 0.64 (0.43-0.94) | 0.66 (0.43-0.99) | 0.77 (0.49-1.21) | 0.80 (0.48-1.34) |
| Roti | ||||||
| 1st Tertile | 90 (30) | 75 (25) | ` | |||
| 2nd Tertile | 108 (36) | 126 (41.67) | 0.71 (0.48-1.06) | 0.65 (0.43-0.99) | 0.57 (0.36-0.91) | 0.48 (0.28-0.82) |
| 3rd Tertile | 102 (34) | 99 (33) | 0.86 (0.57-1.30) | 0.83 (0.53-1.27) | 0.78 (0.48-1.26) | 0.71 (0.42-1.21) |
| Lentils | ||||||
| 1st Tertile | 12 (4) | 13 (4.33) | ||||
| 2nd Tertile | 41 (13.67) | 33 (11) | 1.35 (0.54-3.38) | 1.56 (0.59-4.17) | 2.02 (0.71-5.82) | 2.88 (0.81-11.1) |
| 3rd Tertile | 27 (9) | 254 (84.67) | 1.05 (0.47-2.39) | 1.31 (0.55-3.17) | 1.45 (0.58-3.68) | 1.93 (0.61-6.66) |
| Split black gram lentils | ||||||
| Yes | 217 (72.33) | 208 (69.33) | 1.16 (0.81-1.65) | 1.12 (0.77-1.62) | 1.03 (0.68-1.55) | 0.85 (0.54-1.35) |
| No | 83 (27.67) | 92 (30.67) | ||||
aAdjusted for age, sex, division and SES
bAdditionally adjusted for areca nut consumption (yes/no), smoking (yes/no), smokeless tobacco consumption.
cFurther adjusted for alcohol consumption (yes/no), duration (years) and intensity (frequency/day) of areca nut consumption, smoking and smokeless tobacco

- Association between inter-meal intervals and hypopharyngeal cancer risk.
Overall vegetable intake showed no significant association, but higher intake of leafy green vegetables was strongly protective, with the highest tertile showing approximately 80% reduced risk (OR 0.21, 95% CI: 0.09-0.49). Yellow-orange vegetable intake also suggested protective effects, though borderline significant ( Table II). Total fruit consumption was inversely associated with HC, with both second and third tertiles showing significant protective effects ( Table II). For citrus fruits, the highest tertile showed 87% lower risk (OR 0.13, 95% CI: 0.05-0.32). Non-citrus fruits also reduced risk significantly (OR 0.35, 95% CI: 0.14-0.87) ( Table II).
| Dietary factor | Case (n,%) | Control (n,%) | Crude odds ratio | Adjusted oddsa | Adjusted oddsb | Adjusted oddsc |
|---|---|---|---|---|---|---|
| All vegetables | ||||||
| 1st Tertile | 19 (6.33) | 20 (6.67) | ||||
| 2nd Tertile | 27 (9) | 17 (5.67) | 1.67 (0.70-4.05) | 1.98 (0.79-5.01) | 1.79 (0.66-4.91) | 2.07 (0.67-6.57) |
| 3rd Tertile | 254 (84.67) | 263 (87.67) | 1.02 (0.53-1.96) | 1.04 (0.52-2.07) | 0.89 (0.43-1.87) | 1.06 (0.45-2.60) |
| Yellow/orange vegetables | ||||||
| 1st Tertile | 38 (12.67) | 28 (9.33) | ||||
| 2nd Tertile | 160 (53.33) | 160 (53.33) | 0.73 (0.43-1.25) | 0.70 (0.39-1.23) | 0.52 (0.28-0.96) | 0.52 (0.26-1.04) |
| 3rd Tertile | 102 (34) | 112 (37.33) | 0.67 (0.38-1.17) | 0.65 (0.36-1.17) | 0.50 (0.26-0.94) | 0.51 (0.25-1.02) |
| Leafy green vegetables | ||||||
| 1st Tertile | 34 (11.33) | 14 (4.67) | ||||
| 2nd Tertile | 169 (56.33) | 154 (51.33) | 0.45 (0.22-0.86) | 0.40 (0.19-0.79) | 0.33 (0.15-0.71) | 0.43 (0.18-0.98) |
| 3rd Tertile | 97 (32.33) | 132 (44) | 0.30 (0.15-0.58) | 0.25 (0.12-0.50) | 0.20 (0.09-0.43) | 0.21 (0.09-0.49) |
| Onion and garlic | ||||||
| 1st Tertile | 96 (32) | 117 (39) | ||||
| 2nd Tertile | 100 (33.33) | 88 (29.33) | 1.38 (0.93-2.06) | 1.41 (0.93- 2.14) | 1.35 (0.85-2.13) | 1.77 (1.06-2.99) |
| 3rd Tertile | 104 (34.67) | 95 (31.67) | 1.33 (0.91-1.97) | 1.39 (0.93-2.10) | 1.40 (0.89-2.20) | 1.63 (0.97-2.75) |
| Tomato | ||||||
| 1st Tertile | 88 (29.33) | 101 (33.67) | ||||
| 2nd Tertile | 155 (51.67) | 141 (47) | 1.26 (0.87-1.82) | 1.22 (0.83-1.79) | 1.02 (0.67-1.57) | 1.01 (0.62-1.66) |
| 3rd Tertile | 57 (19) | 58 (19.33) | 1.13 (0.71-1.80) | 1.07 (0.65-1.74) | 0.99 (0.58-1.69) | 1.12 (0.62-2.04) |
| All fruits | ||||||
| 1st Tertile | 36 (12) | 16 (5.33) | ||||
| 2nd Tertile | 190 (63.33) | 210 (70) | 0.40 (0.21-0.74) | 0.38 (0.20-0.73) | 0.36 (0.17-0.73) | 0.30 (0.14-0.65) |
| 3rd Tertile | 74 (24.67) | 74 (24.67) | 0.44 (0.22-0.86) | 0.47 (0.23-0.95) | 0.40 (0.18-0.87) | 0.31 (0.13-0.73) |
| Citrus fruits | ||||||
| 1st Tertile | 30 (10) | 10 (3.33) | ||||
| 2nd Tertile | 117 (39) | 127 (42.33) | 0.31 (0.13-0.63) | 0.25 (0.11-0.53) | 0.20 (0.08-0.47) | 0.15 (0.06-0.37) |
| 3rd Tertile | 153 (51) | 163 (54.33) | 0.31 (0.14-0.64) | 0.24 (0.11-0.52) | 0.19 (0.07-0.44) | 0.13 (0.05-0.32) |
| Non-citrus fruits | ||||||
| 1st Tertile | 36 (12) | 16 (5.33) | ||||
| 2nd Tertile | 223 (74.33) | 235 (78.33) | 0.42 (0.22-0.77) | 0.42 (0.21-0.78) | 0.37 (0.17-0.75) | 0.29 (0.13-0.62) |
| 3rd Tertile | 41 (13.67) | 49 (16.33) | 0.37 (0.18-0.75) | 0.42 (0.19-0.88) | 0.41 (0.17-0.95) | 0.35 (0.14-0.87) |
aAdjusted for age, sex, division and SES
bAdditionally adjusted for areca nut consumption (yes/no), smoking (yes/no), smokeless tobacco consumption
cFurther adjusted for alcohol consumption (yes/no), duration (years) and intensity (frequency/day) of areca nut consumption, smoking and smokeless tobacco
Higher milk intake was positively associated with HC risk (OR 2.06, 95% CI: 1.22-3.52) ( Table III). Coffee consumption was inversely associated with HC (OR 0.54, 95% CI: 0.30-0.94) ( Table IV). Total meat intake demonstrated a significant increase in the second tertile (OR=1.63, 95% CI: 1.04-2.55), while red meat showed no association. Tea consumption, including type, temperature, and frequency, was not associated with HC. No associations were observed for fish, egg, lentils, smoked fish, smoked meat, bamboo shoot, split black gram lentils, or kolakhar ( Table IV).
| Dietary factor | Case (n,%) | Control (n,%) | Crude odds ratio | Adjusted oddsa | Adjusted oddsb | Adjusted oddsc |
|---|---|---|---|---|---|---|
| Milk | ||||||
| 1st Tertile | 119 (39.67) | 156 (52) | ||||
| 2nd Tertile | 99 (33) | 71 (23.67) | 1.83 (1.24-2.70) | 1.91 (1.27-2.88) | 1.99 (1.27-3.12) | 1.98 (1.19-3.30) |
| 3rd Tertile | 82 (27.33) | 73 (24.33) | 1.47 (0.99-2.19) | 1.59 (1.04-2.44) | 1.79 (1.12-2.89) | 2.06 (1.22-3.52) |
| Ghee and butter | ||||||
| Rarely | 183 (61) | 185 (61.67) | ||||
| Frequently | 117 (39) | 115 (38.33) | 1.03 (0.74-1.43) | 1.02 (0.72-1.45) | 0.91 (0.62-1.33) | 0.81 (0.52-1.26) |
| Fish | ||||||
| 1st Tertile | 29 (9.67) | 26 (8.67) | ||||
| 2nd Tertile | 112 (37.33) | 91 (30.33) | 1.10 (0.61-2.01) | 1.11 (0.58-2.09) | 1.15 (0.56-2.31) | 1.28 (0.58-2.86) |
| 3rd Tertile | 159 (53) | 183 (61) | 0.78 (0.44-1.38) | 0.75 (0.41-1.37) | 0.85 (0.43-1.67) | 1.02 (0.48-2.19) |
| Egg | ||||||
| 1st Tertile | 104 (34.67) | 112 (37.33) | ||||
| 2nd Tertile | 117 (39) | 98 (32.67) | 1.29 (0.88-1.88) | 1.30 (0.87-1.95) | 1.31 (0.84-2.04) | 1.51 (0.91-2.51) |
| 3rd Tertile | 79 (26.33) | 90 (30) | 0.95 (0.63-1.41) | 0.87 (0.56-1.34) | 0.88 (0.55-1.42) | 0.76 (0.44-1.31) |
| Meat | ||||||
| 1st Tertile | 119 (39.67) | 139 (46.33) | ||||
| 2nd Tertile | 147 (49) | 128 (42.67) | 1.34 (0.95-1.89) | 1.41 (0.98-2.02) | 1.41 (0.95-2.10) | 1.63 (1.04-2.55) |
| 3rd Tertile | 34 (11.33) | 33 (11) | 1.20 (0.70-2.07) | 1.32 (0.74-2.34) | 1.38 (0.73-2.64) | 1.57 (0.75-3.26) |
| Red meat | ||||||
| 1st Tertile | 134 (44.67) | 116 (38.67) | ||||
| 2nd Tertile | 111 (37) | 121 (40.33) | 0.79 (0.55-1.14) | 0.77 (0.53-1.12) | 0.76(0.50-1.16) | 0.74 (0.46-1.19) |
| 3rd Tertile | 55 (18.33) | 63 (21) | 0.75 (0.49-1.17) | 0.74 (0.46-1.17) | 0.80 (0.48-1.33) | 0.77 (0.44-1.37) |
| Smoked fish | ||||||
| Yes | 91 (30.33) | 92 (30.67) | 0.98 (0.69-1.39) | 1.00 (0.69-1.45) | 0.99 (0.66-1.49) | 0.93 (0.58-1.46) |
| No | 209 (69.67) | 208 (69.33) | ||||
| Smoked meat | ||||||
| Yes | 29 (9.67) | 20 (6.67) | 1.50 (0.83-2.75) | 1.62 (0.86-3.11) | 1.67 (0.84-3.38) | 1.27 (0.57-2.80) |
| No | 271 (90.33) | 280 (93.33) | ||||
| Kolakhar | ||||||
| Yes | 146 (48.67) | 136 (45.33) | 1.14 (0.83-1.58) | 1.28 (0.91-1.80) | 1.07 (0.73-1.56) | 1.02 (0.67-1.56) |
| No | 154 (51.33) | 164 (54.67) | ||||
| Bamboo shoot | ||||||
| Yes | 71 (23.67) | 66 (22) | 1.10 (0.75-1.61) | 1.18 (0.77-1.78) | 0.96 (0.61-1.52) | 0.90 (0.54-1.50) |
| No | 229 (76.33) | 234 (78) | ||||
aAdjusted for age, sex, division and SES
bAdditionally adjusted for areca nut consumption (yes/no), smoking (yes/no), smokeless tobacco consumption
cFurther adjusted for alcohol consumption (yes/no), duration (years) and intensity (frequency/day) of areca nut consumption, smoking and smokeless tobacco
| Dietary factor | Case (n,%) | Control(n,%) | Crude odds ratio | Adjusted oddsa | Adjusted oddsb | Adjusted oddsc |
|---|---|---|---|---|---|---|
| Mustard oil intake | ||||||
| 1st Tertile | 115 (38.33) | 95 (31.67) | ||||
| 2nd Tertile | 113 (37.67) | 122 (40.67) | 0.76 (0.53- 1.11) | 0.81 (0.55-1.20) | 0.75 (0.48-1.16) | 0.71 (0.43-1.17) |
| 3rd Tertile | 72 (24) | 83 (27.67) | 0.72 (0.47-1.09) | 0.71 (0.45-1.10) | 0.73 (0.45-1.19) | 0.84 (0.49-1.46) |
| Tea consumption | ||||||
| Never | 7 (2.33) | 7 (2.33) | ||||
| Black tea | 74 (24.67) | 88 (29.33) | 0.84 (0.27-2.56) | 1.13 (0.35-3.68) | 0.55 (0.15-1.99) | 0.75 (0.18-3.23) |
| Milk tea | 54 (18) | 52 (17.33) | 1.04 (0.33-3.23) | 1.55 (0.46-5.15) | 0.87 (0.24-3.21) | 1.15 (0.27-5.09) |
| Both | 165 (55) | 153 (51) | 1.08 (0.36-3.22) | 1.70 (0.53-5.44) | 0.78 (0.22-2.75) | 1.02 (0.25-4.34) |
| Tea temperature | ||||||
| Warm | 17 (5.67) | 23 (7.67) | ||||
| Hot | 143 (47.67) | 147 (49) | 1.32 (0.68-2.60) | 1.45 (0.72-2.99) | 1.60 (0.73-3.53) | 1.38 (0.58-3.40) |
| Extremely hot | 133 (44.33) | 123 (41) | 1.46 (0.75-2.91) | 1.45 (0.71-2.98) | 1.30 (0.59-2.88) | 1.17 (0.49-2.89) |
| Intensity of taking tea | ||||||
| Never | 7 (2.33) | 7 (2.33) | ||||
| <4 cups/day | 223 (74.33) | 252 (84) | 0.88 (0.29-2.62) | 1.30 (0.41-4.11) | 0.66 (0.19-2.30) | 0.90 (0.23-3.80) |
| >4cups/day | 70 (23.33) | 41 (13.67) | 1.71 (0.54-5.32) | 2.63 (0.79-8.78) | 1.10 (0.30-4.05) | 1.03 (0.24-4.66) |
| Coffee consumption | ||||||
| Yes | 39 (13) | 73 (24.33) | 0.46 (0.30-0.71) | 0.55 (0.35-0.87) | 0.52 (0.32-0.84) | 0.54 (0.30-0.94) |
| No | 261 (87) | 227 (75.67) | ||||
aAdjusted for age, sex, division and SES
bAdditionally adjusted for areca nut consumption (yes/no), smoking (yes/no), smokeless tobacco consumption
cFurther adjusted for alcohol consumption (yes/no), duration (years) and intensity (frequency/day) of areca nut consumption, smoking and smokeless tobacco
Figure 3 presents a comprehensive visual representation of the key dietary and meal timing factors associated with HC risk identified in our study. The forest plot illustrates the magnitude and precision of associations, clearly distinguishing between protective factors (odds ratios below 1.0) and risk factors (odds ratios above 1.0). The most pronounced protective effects are demonstrated by citrus fruits in the highest tertile (OR 0.13, 95% CI: 0.05-0.32), followed closely by leafy green vegetables (OR 0.21, 95% CI: 0.09-0.49), indicating substantial risk reductions of 87% and 79%, respectively. It also reveals the concerning impact of prolonged inter-meal intervals (≥5 h), which emerged as the strongest risk factor with an odds ratio of 2.69 (95% CI: 1.56-4.69), representing a nearly three-fold increase in cancer risk.

- Forest plot of key risk and protective factors for hypopharyngeal cancer.
Discussion
This hospital-based case-control study provides novel evidence linking prolonged inter-meal intervals to hypopharyngeal carcinoma risk in northeastern India. Habitual inter-meal intervals ≥5 h were associated with nearly three-fold higher odds of hypopharyngeal cancer, with a clear dose–response pattern, each additional hour increased risk by 46%.
Our study strongly supports the protective role of fruits and vegetables against HC. The protective effects observed for both citrus and non-citrus fruits in the highest consumption tertiles align with findings from other Indian populations and international studies on head and neck cancer.24-26 The remarkable protective effect of leafy green vegetables and yellow/orange vegetables aligns with their high content of folate, carotenoids, and various phytonutrients. 27,28 The consumption of citrus fruits and fresh tomatoes was associated with reduced risks of oral cavity cancer in previous head and neck cancer studies, supporting our findings regarding the protective effects of specific fruit categories. 29,30 The dose-response relationship observed strengthens evidence for causality. 27 The protective mechanisms likely involve multiple pathways, including antioxidant activity, enhancement of DNA repair mechanisms, modulation of carcinogen metabolism, and anti-inflammatory effects. 31
The positive association between milk consumption and risk of hypopharyngeal cancer contrasts with some international studies but may reflect specific patterns of milk consumption, processing methods, or population-specific factors in this region. 32 This finding requires careful interpretation and further investigation, as it may be confounded by unmeasured lifestyle or dietary factors associated with higher milk consumption in this population. 33 Inverse association of Coffee consumption with risk of hypopharyngeal cancer is consistent with meta-analytic evidence for approximately 25-30% lower risk of oral/pharyngeal cancers among higher coffee consumers. 34,35 The protective effect of roti consumption may reflect higher dietary fibre and lower glycaemic characteristics typical of some whole-wheat flatbreads. 36
Although direct comparisons are limited due to the novelty of analysing inter-meal intervals, converging chrononutrition studies indicate that eating timing patterns relate to elevated cancer risk at other sites. 37,38 The hypopharynx’s anatomical proximity to both upper digestive and respiratory tracts makes it particularly susceptible to chemical irritation from gastroesophageal reflux, which may be exacerbated by irregular eating patterns. In this population, where areca nut chewing is highly prevalent. The practice of consuming areca nut without meals during prolonged intervals may further worsen acid reflux and mucosal irritation. 17,18
This study has several strengths. We employed prospective recruitment of newly diagnosed cases, ensuring systematic enrolment and standardised data collection at a high-volume tertiary cancer centre serving as the regional referral hub. Recruiting cases before treatment initiation ensured high-quality data and avoided biases typically associated with retrospective record reviews. Frequency matching and systematic adjustment for major confounders, including tobacco use, areca nut consumption, alcohol intake, and socioeconomic status, strengthen result reliability. Our study design also ensured to minimise reverse causation concerns. All cases were enrolled at diagnosis prior to treatment initiation, and dietary assessment captured lifelong habitual patterns established before symptom onset. This temporal sequence of lifelong dietary habits preceding cancer development supports a potential causal interpretation rather than disease-related dietary changes.
Several limitations warrant consideration. While patient recruitment was prospective, dietary assessment was necessarily retrospective, relying on participants’ recall of habitual patterns. We attempted to minimise recall bias by focusing on long-standing dietary and meal-timing habits rather than recent intake and by enrolling cases immediately after diagnosis, before treatment initiation; nevertheless, some degree of recall error is inherent to this approach. As a hospital-based case-control study, potential selection bias exists, although our prospective recruitment and frequency matching help minimise this concern. Residual confounding from unmeasured factors such as specific cooking methods, gastroesophageal reflux severity, genetic susceptibility, and Human Papillomavirus infection status cannot be completely ruled out.
Dietary epidemiology has inherent limitations, and the associations observed in case–control studies should be interpreted with caution. Although our findings align with evidence from large prospective studies and the WCRF/AICR Expert Report supporting a protective role of fruits and vegetables in head and neck cancer, causality cannot be inferred. 10,39-41 These results should therefore be viewed as hypothesis-generating and warrant confirmation in prospective studies. While large, long-term prospective cohort studies are the gold standard for establishing causality in nutritional epidemiology, they are particularly challenging for rare cancers such as HC, where accruing adequate numbers would require extremely large populations and decades of follow-up. In such contexts, case control studies remain an appropriate and widely used approach, offering a practical and informative design where a prospective cohort study would require thousands of participants and decades of follow up, an undertaking currently not feasible in our setting. The monograph “Epidemiologic research of rare cancers: trends, resources, and challenges” argues that rare cancers pose serious obstacles to prospective cohort research due to difficulty in recruiting sufficient numbers, and highlights the value of case–control and other observational designs. 42 Modern research continues to validate this approach: for instance, a recent hospital-based case–control study in Nepal included 549 head and neck cancer cases and 601 controls to identify risk factors in a context similar to ours. 43
Our findings provide preliminary evidence that both dietary composition and meal-timing behaviours may contribute to the risk of hypopharyngeal cancer in this high-incidence region. The associations observed after adjustment for major confounders provide a basis for future hypothesis-driven research and for developing prevention strategies targeting multiple dietary practices.
Author contributions
RD: Study conceptualisation, questionnaire development, ethical approval coordination, primary data collection, patient recruitment, data entry and management, statistical analysis, interpretation of results, manuscript writing, creation of figures and tables; LBM: Principal investigator, study design and methodology, supervision of data collection and analysis, critical interpretation of statistical results, manuscript writing, project administration, securing funding; TR: Clinical guidance on hypopharyngeal cancer diagnosis and patient selection, facilitation of patient recruitment, validation of clinical data, resources provision (access to cancer registry and patient database), manuscript writing; MK: Administrative oversight at BBCI, coordination with hospital administration for ethical clearance, facilitation of data collection activities, resources provision (hospital infrastructure and patient access), manuscript writing. Institutional Collaboration: This study was conducted as a collaborative effort between IASST (providing statistical expertise, analytical infrastructure, and funding) and Dr. B. Borooah Cancer Institute (providing clinical expertise, patient recruitment infrastructure, and ethical clearance). Data collection occurred at BBCI, while data analysis was performed at IASST.
Financial support and sponsorship
None.
Conflicts of Interest
None.
Use of Artificial Intelligence (AI)-Assisted Technology for manuscript preparation
The authors confirm that there was no use of AI-assisted technology for assisting in the writing of the manuscript and no images were manipulated using AI.
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