Dietary phytochemical index and its relationship with diabetic sensorimotor polyneuropathy: a case-control study

Phytochemicals are compounds found in fruits, vegetables, whole grains, nuts and legumes that are non-nutritive but have bioactive properties. A high intake of these compounds is essential for optimal health and disease prevention. No study has investigated the association between Dietary Phytochemical Index (DPI) and polyneuropathy in patients with diabetes. This study aimed to examine the association between DPI and Diabetic Sensory-motor Polyneuropathy (DSPN) in a case-control study. In this case-control study, a total of 185 diabetic patients with DSPN (case group) and 185 sex- and age-matched diabetic patients without neuropathy (control group) were enrolled in this study. Participants were 30-60 years old. A validated food frequency questionnaire was used to measure the dietary intake of all participants. Daily energy derived from phytochemical-rich foods was used to calculate the DPI score. Toronto clinical neuropathy score was applied to define DSPN. Anthropometric data and fasting blood glucose levels were measured using standard methods. The Binary logistic regression was used to estimate Crude and multivariable-adjusted OR (95% CI) for DSPN across tertiles of DPI for the whole population. In the crude model, there was a significant trend across the tertile of DPI (OR <sub>highest vs. lowest tertile of DPI</sub> = 0.33; 95%CI 0.18, 0.52; P-trend < 0.001). After controlling for age, sex, and energy, a significant reverse association was observed between DPI and DSPN (OR <sub>highest vs. lowest tertile of DPI</sub> = 0.27; 95%CI 0.15, 0·48; P-trend < 0.001). Moreover, after adjusting for a wide range of confounding variables such as energy intake, physical activity, education, smoking status, and HbA1c, participants in the third tertile of DPI had 75% reduced odds for DSPN (95%CI 0.14, 0.45; P-trend < 0.001). Finally in the full adjusted model, after further adjustment for BMI, observed significant association was remained (OR <sub>highest vs. lowest tertile of DPI</sub>: 0.24; 95% CI 0.13, 0.14; P-trend < 0.001). Higher intakes of phytochemical-rich foods are associated with lower odds of DSPN.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2024-09-17
DOI
https://doi.org/10.1038/s41598-024-72602-w
Citations
1
Primary Topic
Diet and metabolism studies
Type
article
Field-Weighted Citation Impact
0.33

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Dietary phytochemical index and its relationship with diabetic sensorimotor polyneuropathy: a case-control study

Azadeh Aminianfar, Sasan Asadi, Sara Asadi, Melika Fallah et al.
1 citations
Scientific Reports
Diet and metabolism studies
0.33
article

Dietary phytochemical index and its relationship with diabetic sensorimotor polyneuropathy: a case-control study

Azadeh Aminianfar, Sasan Asadi, Sara Asadi, Melika Fallah, Fahimeh Shiva, Abbas Mohtashamian, Saeedeh Nouri-Majd
article en
1 citations

Abstract

Phytochemicals are compounds found in fruits, vegetables, whole grains, nuts and legumes that are non-nutritive but have bioactive properties. A high intake of these compounds is essential for optimal health and disease prevention. No study has investigated the association between Dietary Phytochemical Index (DPI) and polyneuropathy in patients with diabetes. This study aimed to examine the association between DPI and Diabetic Sensory-motor Polyneuropathy (DSPN) in a case-control study. In this case-control study, a total of 185 diabetic patients with DSPN (case group) and 185 sex- and age-matched diabetic patients without neuropathy (control group) were enrolled in this study. Participants were 30-60 years old. A validated food frequency questionnaire was used to measure the dietary intake of all participants. Daily energy derived from phytochemical-rich foods was used to calculate the DPI score. Toronto clinical neuropathy score was applied to define DSPN. Anthropometric data and fasting blood glucose levels were measured using standard methods. The Binary logistic regression was used to estimate Crude and multivariable-adjusted OR (95% CI) for DSPN across tertiles of DPI for the whole population. In the crude model, there was a significant trend across the tertile of DPI (OR <sub>highest vs. lowest tertile of DPI</sub> = 0.33; 95%CI 0.18, 0.52; P-trend < 0.001). After controlling for age, sex, and energy, a significant reverse association was observed between DPI and DSPN (OR <sub>highest vs. lowest tertile of DPI</sub> = 0.27; 95%CI 0.15, 0·48; P-trend < 0.001). Moreover, after adjusting for a wide range of confounding variables such as energy intake, physical activity, education, smoking status, and HbA1c, participants in the third tertile of DPI had 75% reduced odds for DSPN (95%CI 0.14, 0.45; P-trend < 0.001). Finally in the full adjusted model, after further adjustment for BMI, observed significant association was remained (OR <sub>highest vs. lowest tertile of DPI</sub>: 0.24; 95% CI 0.13, 0.14; P-trend < 0.001). Higher intakes of phytochemical-rich foods are associated with lower odds of DSPN.

Scientific ReportsVol. 14(1)
Isfahan University of Medical Sciences (IR), Mashhad University of Medical Sciences (IR), Kashan University of Medical Sciences (IR), Yahoo (Spain) (ES), Kurdistan University of Medical Sciences (IR), Tehran University of Medical Sciences (IR)
Tehran University of Medical Sciences and Health Services, Kermanshah University of Medical Sciences
Zero hunger
Openalex Percentile: Top 38%
Diet and metabolism studies
0.33
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.