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. 2022 Aug;25(8):2188-2196.
doi: 10.1017/S1368980022000763. Epub 2022 Mar 31.

Association between dietary patterns and stroke in patients with type 2 diabetes mellitus in China: a propensity score-matched analysis

Chenlu He  1 , Wei Wang  1 , Qian Chen  1 , Ziyuan Shen  1 , Enchun Pan  2 , Zhongming Sun  2 , Peian Lou  3 , Xunbao Zhang  1
Affiliations

Association between dietary patterns and stroke in patients with type 2 diabetes mellitus in China: a propensity score-matched analysis

Chenlu He et al. Public Health Nutr. 2022 Aug.

Abstract

Objective: This study aimed to examine the impact of different dietary patterns on stroke outcomes among type 2 diabetes mellitus (T2DM) patients in China.

Design: Participants were enrolled by a stratified random cluster sampling method in the study. After collecting dietary data using a quantified FFQ, latent class analysis was used to identify dietary patterns, and propensity score matching was used to reduce confounding effects between different dietary patterns. Binary logistic regression and conditional logistic regression were used to analyse the relationship between dietary patterns and stroke in patients with T2DM.

Setting: A cross-sectional survey available from December 2013 to January 2014.

Participants: A total of 13 731 Chinese residents aged 18 years or over.

Results: Two dietary patterns were identified: 61·2 % of T2DM patients were categorised in the high-fat dietary pattern while 38·8 % of patients were characterised by the balanced dietary pattern. Compared with the high-fat dietary pattern, the balanced dietary pattern was associated with reduced stroke risk (OR = 0·63, 95 %CI 0·52, 0·76, P < 0·001) after adjusting for confounding factors. The protective effect of the balanced model did not differ significantly (interaction P > 0·05).

Conclusions: This study provides sufficient evidence to support the dietary intervention strategies to prevent stroke effectively. Maintaining a balanced dietary pattern, especially with moderate consumption of foods rich in quality protein and fresh vegetables in T2DM patients, might decrease the risk of stroke in China.

Keywords: Dietary patterns; Latent class analysis; Propensity score matching; Stroke; Type 2 diabetes.

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Figures

Fig. 1
Fig. 1
Probabilities of consumption for selected food items by dietary patterns derived from latent class analysis. The green line: low intake of food; the blue line: moderate intake of food; the red line: high intake of food
Fig. 2
Fig. 2
Absolute standardised differences in fifteen covariates between high-fat pattern and balanced pattern patients before and after matching. The maroon solid circle represents absolute standardised differences before matching, and the maroon hollow diamond represents absolute standardised differences after matching
Fig. 3
Fig. 3
Impact of different dietary patterns on stroke outcomes by subgroups after propensity matching
See this image and copyright information in PMC

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