Chrononutrition Patterns and Nutritional Status Among Working and Non-Working Women Aged 20-60 Years: A Cross-Sectional Study from Surat, India

Shilpee  Agrawal; Umaymah Mohmad Degia

doi:10.70851/jfines.2025.2(2).46.59

Authors

Dr. Shilpee Agrawal Department of Food and Nutrition, Faculty of Science, Vanita Vishram Women’s University, AthwaGate, Surat - 395001, Gujarat, India Author https://orcid.org/0000-0003-4343-651X
Umaymah Mohmad Degia Department of Food and Nutrition, Faculty of Science, Vanita Vishram Women’s University, AthwaGate, Surat - 395001, Gujarat, India Author

DOI:

https://doi.org/10.70851/jfines.2025.2(2).46.59

Keywords:

Nutritional Status, Chrononutrition, Women, Metabolic risk

Abstract

Chrononutrition aligns eating patterns with circadian rhythms and is crucial for metabolic regulation. This study assessed the association between chrononutrition patterns and nutritional status among working and non-working women in Surat, Gujarat. A community-based cross-sectional study involved 400 women aged 20–60 years (200 working, 200 non-working). Data were collected using a structured, pre-tested questionnaire on demographics, anthropometric indices (BMI, WHR), dietary intake, physical activity, and chronotype. Data were analyzed using SPSS 25.0, with p<0.05 considered statistically significant. Younger women (26–30 years) were more prevalent in the working group, while older women (56–60 years) were predominantly non-working. Non-working women had significantly higher BMI (27.6 ± 6.8 kg/m² vs. 25 ± 5.5 kg/m², p<0.05) and waist circumference (85.9 ± 18.1 cm vs. 77.7 ± 17.6 cm, p<0.05), with 48.5% exhibiting central obesity (WC >88 cm) compared to 28.5% of working women. Most participants identified as intermediate chronotypes; however, the working group had a higher percentage of evening chronotypes (18% vs. 16%), while non-working women were more likely to be morning types (29% vs. 25.5%). Both groups had inadequate energy and protein intake but exceeded fat intake, reflecting poor dietary quality. Among working women, chronotype significantly associated with BMI (p=0.029), fat intake (p=0.035), and wake-up timing (p=0.04). In non-working women, significant associations were found with waist circumference (p=0.023), energy intake (p=0.01), and morning tiredness (p=0.00). Overall, chronotype influences nutritional status and dietary patterns, particularly in non-working women, who showed higher levels of central obesity and disrupted eating rhythms. These findings underscore the necessity for targeted dietary and lifestyle interventions aligned with chronotype to mitigate metabolic risks among sedentary women.

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