---
title: "Dietary PUFA Intake, Sleep Patterns, and Lung Cancer Risk: Case-Control Findings from Southwest Ch"
id: "plos-one-23-associations-of-dietary-polyunsaturated-fatty-acids-and-sleep-patterns-with"
canonical_url: "https://medichelpline.com/clinical-feed/plos-one-23-associations-of-dietary-polyunsaturated-fatty-acids-and-sleep-patterns-with"
content_type: "clinical_feed_article"
specialty: "Oncology"
source_name: "PLOS ONE (Medicine)"
source_url: "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0358576"
published_at: "2026-09-30T14:00:00.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Dietary PUFA Intake, Sleep Patterns, and Lung Cancer Risk: Case-Control Findings from Southwest Ch
## Provenance & Clinical Metadata
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- **Specialty:** [Oncology](https://medichelpline.com/clinical-feed/oncology.md)
- **Primary Source:** PLOS ONE (Medicine)
- **Source URL:** [Original Journal Publication](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0358576)
- **Published At:** 2026-09-30T14:00:00.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- This matched case-control study in Chongqing, southwest China, examined associations of dietary **PUFA** intake (omega-3, omega-6, total) and composite **sleep patterns** with odds of **lung cancer**. - The analytic sample included 322 newly/recently diagnosed lung cancer cases and 644 matched controls (1:2 match by age group and sex). Exposure recall covered the 12 months prior to diagnosis for cases and prior to survey for controls. - Dietary intakes were measured using a validated semi-quantitative food frequency questionnaire (SQFFQ) tailored to Chongqing diets; PUFA intakes expressed in g/day using Chinese food composition tables. - Sleep was summarized with a 0–5 healthy sleep score combining sleep duration, chronotype, insomnia, snoring, and daytime sleepiness; categories: unfavorable (0–1), medium (2–3), favorable (4–5). - Multivariable conditional logistic regression adjusted for sociodemographics, smoking, BMI, energy intake, diabetes, passive smoking, occupational and cooking oil exposure, and fish oil supplementation habit. - Continuous analyses: each 1-g/day higher **omega-3 PUFA** intake was associated with lower odds of lung cancer (adjusted OR 0.82, 95% CI 0.70–0.96). - Tertile analyses: highest vs lowest tertile showed lower odds for omega-3 (OR 0.50), omega-6 (OR 0.50), and total PUFA (OR 0.48) in the fully adjusted model; trends across tertiles were significant. - Favorable sleep patterns were associated with lower odds of lung cancer versus unfavorable patterns (adjusted OR 0.59, 95% CI 0.40–0.87). - Stratified analyses suggested numerically lower sleep–lung cancer ORs in the higher omega-3 intake stratum, but multiplicative interaction tests were not statistically significant. - Authors conclude higher dietary **omega-3 PUFA** intake and favorable **sleep patterns** were each associated with lower odds of lung cancer, and recommend confirmation in prospective studies.
## Clinical Analysis & Structured Key Points
Associations of dietary polyunsaturated fatty acids and sleep patterns with lung cancer in southwest China: A case-control study | PLOS One Browse Subject Areas ? Click through the PLOS taxonomy to find articles in your field. For more information about PLOS Subject Areas, click here . Article Authors Metrics Comments Media Coverage Peer Review Reader Comments Figures Figures Abstract Background Evidence on the associations of polyunsaturated fatty acid (PUFA) intake and sleep patterns with lung cancer remains inconsistent. We aimed to examine these associations in southwest China and to explore whether the association between sleep patterns and lung cancer differed according to dietary PUFA intake. Methods We conducted a matched case-control study in Chongqing, southwest China, from August 22, 2023, to September 30, 2024. Each lung cancer case was matched to two controls by age group ( 65 years) and sex. Dietary PUFA intake was assessed using a validated semi-quantitative food frequency questionnaire (SQFFQ), and sleep patterns were evaluated using a composite healthy sleep score based on five sleep characteristics. Multivariable conditional logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Results A total of 322 lung cancer cases and 644 matched controls were included. In continuous analyses, each 1-g/day increase in omega-3 PUFA intake was associated with lower odds of lung cancer (OR = 0.82, 95% CI: 0.70–0.96). In tertile-based analyses, participants in the highest versus lowest intake tertiles had lower odds of lung cancer across all three PUFA types (omega-3 PUFAs: OR = 0.50, 95% CI: 0.32–0.78; omega-6 PUFAs: OR = 0.50, 95% CI: 0.31–0.80; total PUFAs: OR = 0.48, 95% CI: 0.30–0.79). Favorable sleep patterns were also associated with lower odds of lung cancer compared with unfavorable sleep patterns (OR = 0.59, 95% CI: 0.40–0.87). Although lower stratum-specific ORs were observed in the higher omega-3 PUFA intake stratum, the multiplicative interaction tests were not statistically significant. Conclusion Higher dietary omega-3 PUFA intake and favorable sleep patterns were each associated with lower odds of lung cancer in this matched case-control study. Associations for omega-6 and total PUFA intake were observed in tertile-based analyses but were not consistent across modeling approaches. These observational findings require confirmation in prospective studies. Citation: Zuo X, Zhou Q, Pang L, Li G, Long F, Xiang Z, et al. (2026) Associations of dietary polyunsaturated fatty acids and sleep patterns with lung cancer in southwest China: A case-control study. PLoS One 21(9): e0358576. https://doi.org/10.1371/journal.pone.0358576 Editor: Assoc. Prof. Phakkharawat Sittiprapaporn, Mae Fah Luang University School of Anti Aging and Regenerative Medicine, THAILAND Received: March 24, 2026; Accepted: September 2, 2026; Published: September 30, 2026 Copyright: © 2026 Zuo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: The minimal anonymized dataset and codebook are provided in S1 File , the analytic code is provided in S2 File , and the code used to generate Fig 2 is provided in S3 File . Funding: This work was funded by Chongqing Natural Science Foundation (Chongqing Science and Technology Development Foundation) (No. CSTB2024NSCQ-KJFZMSX0027), and Chongqing Medical Scientific (Disease Control and Prevention) Research Project (No. 2026KWJK1006). Competing interests: The authors have declared that no competing interests exist. Introduction Lung cancer remains the most commonly diagnosed malignancy and the leading cause of cancer-related mortality worldwide, with approximately 2.5 million new cases and 1.8 million deaths reported in 2022 [ 1 ]. Projections estimate that by 2050, the global incidence could reach 3.8 million cases annually, resulting in approximately 3.2 million deaths [ 2 ]. In China, lung cancer accounted for roughly 1.0 million new cases and 0.7 million deaths in 2022, with incidence and mortality rates approximately 1.7 and 1.6 times higher than the global averages, respectively [ 3 ]. Identifying potential risk factors therefore remains a priority for lung cancer prevention and control. Lung cancer risk factors include non-modifiable determinants such as age, sex, and family history, as well as modifiable factors including smoking, environmental exposure, diet, and sleep. Among these, smoking is the leading contributor to the global disease burden [ 4 ]. Nonetheless, accumulating evidence suggests that dietary factors may also be associated with lung cancer [ 5 ]. Notably, dietary polyunsaturated fatty acids (PUFAs), including omega-3, omega-6, and total PUFA intakes, have been investigated for their possible associations with lung cancer risk, although results are inconsistent. Some studies have reported inverse associations between PUFA intake and lung cancer, whereas others have reported null or positive associations, particularly for omega-6 and total PUFA intake [ 6 – 9 ]. To date, few studies have examined these associations in populations from southwest China. Sleep characteristics, including sleep duration, chronotype, insomnia, snoring, and daytime sleepiness, have increasingly been examined as lifestyle factors potentially related to lung cancer risk [ 10 – 12 ]. A growing body of evidence suggests that unfavorable sleep behaviors may influence carcinogenesis by impairing immune function, hormonal regulation, and DNA repair processes [ 13 – 16 ]. However, many previous studies have focused on individual sleep components rather than overall sleep patterns. To address this limitation, a composite healthy sleep score incorporating multiple sleep characteristics has been applied across various health outcomes [ 17 ], providing a broader assessment of sleep health. Although prior subgroup analyses have examined whether associations between sleep and cancer vary according to genetic susceptibility, age, or body mass index (BMI) [ 18 , 19 ], to our knowledge, potential variation in the sleep–lung cancer association across dietary PUFA intake levels has not been examined. Shared inflammatory and metabolic pathways involving dietary PUFA intake and sleep may be relevant to carcinogenesis [ 6 ] and provide a rationale for this exploratory assessment. The primary objective of this study was to examine the associations of dietary PUFA intake and sleep patterns with lung cancer in a population from southwest China. As a secondary objective, we conducted exploratory stratified analyses and formally assessed multiplicative interactions between sleep patterns and dietary PUFA intake. Materials and methods Study design and participants We conducted a hospital- and community-based matched case-control study in Chongqing, southwest China, between August 22, 2023, and September 30, 2024. Cases were patients with newly or recently diagnosed lung cancer recruited from two sources: the Department of Thoracic Surgery at the Third Affiliated Hospital of Chongqing Medical University between October 2023 and September 2024, and the Chongqing Tumor Registration System, through which community-based cases were identified in August 2023 and recruited by local primary healthcare institutions from randomly sampled communities in Nanan District and Tongnan District. Cases were eligible if they: (i) had a definite histopathological diagnosis of lung cancer (ICD-10 C33-C34); (ii) were aged ≥18 years; (iii) had a disease duration of ≤2 years; and (iv) had a local Chongqing household registration or living in Chongqing for ≥20 years. Patients with concurrent malignancies or those who were pregnant or lactating were excluded. The control group was recruited in August 2023 and July 2024 from multiple communities in Nanan District and Tongnan District, Chongqing, which were randomly selected using the same sampling procedure as the community-based case group. Community residents were recruited by local primary care institutions. Eligible controls were required to have no cancer record in the Chongqing Tumor Registration System and to self-report no current or previous history of cancer. They were also required to meet the same residential criteria as cases, namely, to have local household registration in Chongqing or to have lived in Chongqing for ≥20 years. Individuals who were pregnant or lactating were excluded. Cases and controls were matched at a ratio of 1:2 by sex and age group ( 65 years). Of 1,177 participants initially enrolled (355 cases, 822 controls), 27 were excluded for not meeting eligibility criteria (19 cases, 8 controls) and a further 33 (8 cases, 25 controls) were excluded due to missing data on key variables or implausible energy intakes (men: 4,200 kcal/day; women: 3,500 kcal/day) [ 20 ]. This left 328 cases and 789 controls eligible for matching. After 1:2 matching by age group and sex, the final analytic sample comprised 322 cases and 644 matched controls ( Fig 1 ). Download: PNG larger image TIFF original image Fig 1. Flowchart of the analytic sample selection process. https://doi.org/10.1371/journal.pone.0358576.g001 Sample size and selection. The sample size was estimated based on previous epidemiological studies on dietary PUFAs, sleep quality, and lung cancer [ 6 , 21 ]. Using a 1:2 case-to-control matching ratio in PASS 11.0 (NCS, USA), the calculation indicated that at least 205 cases and 410 controls were required. Data collection and measurements Prior to data collection, all participants provided written informed consent. Structured face-to-face interviews were conducted by trained and certified interviewers. All exposure information, including dietary intake and sleep behaviors, was collected retrospectively with reference to the 12 months preceding lung cancer diagnosis for cases, and the 12 months preceding questionnaire completion for controls. Assessment of dietary PUFAs . Dietary intakes of omega-3, omega-6, and total PUFAs were assessed using a validated semi-quantitative food frequency questionnaire (SQFFQ) developed to reflect the dietary habits of urban and rural populations in Chongqing. The SQFFQ was originally developed from 3-day weighed food records from Chongqing adults and was designed to capture major food and nutrient intakes in this population. Its relative validity was evaluated in 92 healthy adults aged 35–55 years from urban and rural areas of Chongqing using 3-day weighed food records as the reference method, while its reproducibility was assessed in 48 adults of the same age range using repeated SQFFQ administrations at a 4-week interval [ 22 ]. Dietary intake was assessed over the 12 months preceding lung cancer diagnosis for cases and the 12 months preceding questionnaire completion for controls. The questionnaire included 119 food items grouped into 12 main food groups. Participants reported usual consumption frequency using eight predefined categories, ranging from 1–3 times per month to >3 times per day, and average portion size in grams for each food item. Trained interviewers used standardized household measures, including bowls, plates, and cups, together with a detailed food atlas, to assist participants in estimating portion sizes. The daily intake of each food item was calculated by converting the reported frequency to a daily rate and multiplying it by the reported portion size. Nutrient and energy intakes were estimated using the Chinese Food Composition Tables (Standard Edition, 6th Edition) [ 23 ]. Daily intakes of omega-3, omega-6, and total PUFA were calculated by summing the PUFA contributions from all reported food items and were expressed as grams per day. Assessment of sleep patterns and healthy sleep score. Five sleep characteristics were assessed: sleep duration, chronotype, insomnia, snoring, and daytime sleepiness. Sleep duration was based on the question ‘Over the past year, excluding nap time, how many hours do you sleep on average each day?’; responses of 7–8 hours/day were considered favorable (1 point). Chronotype was assessed by asking, ‘How would you describe yourself over the past year? (i) definitely a “morning” person, (ii) more a “morning” than “evening” person, (iii) more an “evening” than “morning” person, or (iv) definitely an “evening” person over the past year’; morning-type responses (i or ii) were considered favorable (1 point). Insomnia was assessed by asking ‘Over the past year, have you had difficulty falling asleep or waking up in the middle of the night?’, with responses of (i) never/rarely, (ii) sometimes, or (iii) usually; never/rarely was considered favorable (1 point). Snoring was assessed by the question ‘Over the past year, have you snored? Or have your family or friends complained about your snoring?’, responses included (i) yes, or (ii) no; no snoring was considered favorable (1 point). Daytime sleepiness was captured by ‘Over the past year, how likely are you to doze off or fall asleep unintentionally during the day (e.g., while working, reading, or driving)?’, with responses of (i) never/rarely, (ii) sometimes, (iii) often, or (iv) all of the time; never/rarely was considered favorable (1 point). A healthy sleep score (range, 0–5) was calculated by summing points across the five characteristics, with higher scores reflecting healthier overall sleep. Participants were classified into three categories based on the total score: unfavorable (0–1), medium (2–3), and favorable (4–5). This composite scoring approach has been previously applied to examine sleep patterns in relation to type 2 diabetes [ 24 ], heart failure [ 25 ], and arrhythmia [ 26 ]. Statistical analyses We summarized participant characteristics as mean (standard deviation [SD]) for normally distributed variables, median (interquartile range) for skewed variables, and number (percentage) for categorical variables. For comparisons between cases and controls a t‑test (for normally distributed variables) and a Mann–Whitney U test (for skewed variables) were used to analyze continuous variables, and a chi‑squared test was used to analyze categorical variables. Multivariable conditional logistic regression was used to estimate ORs and 95% CIs. Three models were fitted, and all models were conditioned on the matched sets to account for the 1:2 matching by age group and sex. The crude model included no additional covariate adjustment. Based on previous studies [ 27 – 30 ], two multivariable models were fitted. Model 1 was adjusted for education level (primary education or illiterate, junior high school, high school, or junior college or above), yearly household income (CNY) (<60,000 or ≥60,000), family history of lung cancer (yes/no), smoking status (never smokers, current smokers, or former smokers), and fish oil supplementation habit (yes/no). Model 2 was further adjusted for diabetes at baseline (yes/no) and BMI (<24.0, 24.0–27.9 or ≥28.0 kg/m 2 ), energy (kcal/day), alcohol intake frequency (frequent, daily to 3–4 times per week; occasional, 1–2 times per week to 1–3 times per month; rarely/never, less than once per month or rare/never), passive smoking (yes/no), occupational exposure (yes/no), and hot cooking oil exposure (low, none or minor; high, moderate or heavy). The primary analyses examined the associations of dietary PUFA intake and sleep patterns separately with the odds of lung cancer. Dietary intakes of omega-3, omega-6, and total PUFAs were modeled as continuous variables, with ORs estimated per 1-g/day increase. PUFA intake was additionally categorized into tertiles, with the lowest tertile used as the reference. Tests for linear trend were conducted by assigning the median value of each tertile as a continuous variable in the conditional logistic regression model. Sleep patterns were categorized as unfavorable, medium, and favorable, with the unfavorable category as the reference. Secondary exploratory analyses examined stratum-specific associations between sleep patterns and lung cancer according to dietary PUFA intake. Each PUFA measure was dichotomized at the median to define lower- and higher-intake groups. All stratified analyses were adjusted for covariates included in Model 2. For each PUFA measure, multiplicative interaction was assessed by adding two cross-product terms to Model 2: medium sleep pattern × higher PUFA intake and favorable sleep pattern × higher PUFA intake. All analyses were performed using SPSS 25.0 and R 4.4.3. Two-sided P values <0.05 were considered statistically significant. Ethical approval This study was approved by the Ethics Committee of Chongqing Center for Disease Control and Prevention (approval No.KY-2023-007-1 and No. KY-2023-007-2). All participants provided written informed consent before participation, and the study was conducted in accordance with the Declaration of Helsinki and relevant guidelines and regulations. Participants were informed of the study aims, foreseeable harms (e.g., psychological distress from sensitive questions), and potential societal benefits. Data confidentiality was protected through coded identifiers, removal of direct personal identifiers, and restricted access by authorized staff. Study registration This observational matched case-control study was retrospectively registered in the Chinese Clinical Trial Registry (registration ID: ChiCTR2500106928) on July 31, 2025, after completion of participant recruitment and data collection, which took place from August 2023 to September 2024. Results Characteristics of the participants Table 1 summarizes the characteristics of the 322 lung cancer cases and 644 matched controls. Compared with controls, cases were more likely to have a family history of lung cancer, higher annual household income, passive smoking, occupational exposure, and current or former smokers. Cases had a lower prevalence of diabetes at baseline and obesity (BMI ≥ 28 kg/m 2 ). They were also more likely to have unfavorable sleep patterns and reported lower omega-3, omega-6, and total PUFA intakes than controls. Download: PNG larger image TIFF original image Table 1. Characteristics of participants according to lung cancer status. https://doi.org/10.1371/journal.pone.0358576.t001 Association between dietary PUFA intake and lung cancer Table 2 shows the associations between dietary PUFA intake and lung cancer. When modeled continuously, higher omega-3 PUFA intake was consistently associated with lower odds of lung cancer across all models. In Model 2, each 1-g/day increase in omega-3 PUFA intake was associated with lower odds of lung cancer (OR = 0.82, 95% CI: 0.70–0.96; P = 0.012). Neither omega-6 PUFA intake nor total PUFA intake was statistically significantly associated with lung cancer in Model 2 (omega-6 PUFA intake: OR = 0.97, 95% CI: 0.94–1.00; P = 0.090; total PUFA intake: OR = 0.99, 95% CI: 0.97–1.01; P = 0.377). Download: PNG larger image TIFF original image Table 2. Association between dietary PUFA intake and lung cancer. https://doi.org/10.1371/journal.pone.0358576.t002 In the tertile-based analyses, participants in the highest versus lowest tertile had lower odds of lung cancer for all three PUFA measures in Model 2 (omega-3 PUFA intake: OR = 0.50, 95% CI: 0.32–0.78; P = 0.002; omega-6 PUFA intake: OR = 0.50, 95% CI: 0.31–0.80; P = 0.004; total PUFA intake: OR = 0.48, 95% CI: 0.30–0.79; P = 0.003). Similar associations were observed in the crude model and Model 1. Trends toward lower odds across tertiles were also observed for omega-3, omega-6, and total PUFA intake ( P for trend = 0.002, 0.006, 0.003 for omega-3 PUFAs, omega-6 PUFAs, and total PUFAs, respectively). Association between sleep patterns an
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