Eating Slowly Is Associated with Undernutrition among Community-Dwelling Adult Men and Older Adult Women

Nakamura, Tomiyo; Nakamura, Yasuyuki; Takashima, Naoyuki; Kadota, Aya; Miura, Katsuyuki; Ueshima, Hirotsugu; Kita, Y.

doi:10.3390/nu14010054

Cited by 6 publications

(9 citation statements)

References 40 publications

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“…The present study also reported that slow–speed eating was related to poor nutrition ( 17 ). By contrast, fast eating speed is related to obesity, T2DM, and NAFLD ( 14 – 16 ).…”

Section: Discussionsupporting

confidence: 78%

“…Eating speed is also important because fast eating is associated with obesity ( 14 ), non–alcoholic fatty liver disease (NAFLD) ( 15 ), and T2DM ( 16 ); therefore, slow eating speed may be effective for lowering obesity risk. On the contrary, slow eating increases the risk of undernutrition ( 17 ). It is because slow speed eating increases anorexigenic gut hormones such as peptide YY and glucagon–like peptide−1 (GLP−1) ( 18 , 19 ) and diet–induced thermogenesis ( 20 , 21 ).…”

Section: Introductionmentioning

confidence: 99%

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Impact of Eating Speed on Muscle Mass in Older Patients With Type 2 Diabetes: A Prospective Study of KAMOGAWA–DM Cohort

et al. 2022

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Background and AimsMaintenance of muscle mass is important for sarcopenia prevention. However, the effect of eating speed, especially fast, normal, or slow speed, on muscle mass changes remains unclear. Therefore, the purpose of this prospective study was to investigate the effect of eating speed on muscle mass changes in patients with type 2 diabetes (T2DM).MethodsThis study included 284 patients with T2DM. Based on a self–reported questionnaire, participants were classified into three groups: fast–, normal–, and slow–speed eating. Muscle mass was assessed using a multifrequency impedance body composition analyzer, and skeletal muscle mass (SMI) decrease (kg/m2/year) was defined as [baseline SMI (kg/m2)–follow–up SMI (kg/m2)] ÷ follow–up duration (year). The rate of SMI decrease (%) was defined as [SMI decrease (kg/m2/year) ÷ baseline SMI (kg/m2)] × 100.ResultsThe proportions of patients with fast–, normal–, and slow–speed eating were, respectively, 50.5%, 42.9%, and 6.6% among those aged <65 years and 40.4%, 38.3%, and 21.3% among those aged ≥65 years. In patients aged ≥65 years, the rate of SMI decrease in the normal (0.85 [95% confidence interval, CI: −0.66 to 2.35]) and slow (0.93 [95% CI −0.61 to 2.46]) speed eating groups was higher than that in the fast speed eating group (−1.08 [95% CI −2.52 to 0.36]). On the contrary, there was no difference in the rate of SMI decrease among the groups in patients aged <65 years. Compared with slow speed eating, the adjusted odds ratios of incident muscle loss [defined as rate of SMI decrease (%) ≥0.5%] due to fast– and normal–speed eating were 0.42 (95% CI 0.18 to 0.98) and 0.82 (95% CI 0.36 to 2.03), respectively.ConclusionSlow–speed eating is associated with a higher risk of muscle mass loss in older patients with T2DM.

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“…The present study also reported that slow–speed eating was related to poor nutrition ( 17 ). By contrast, fast eating speed is related to obesity, T2DM, and NAFLD ( 14 – 16 ).…”

Section: Discussionsupporting

confidence: 78%

Section: Introductionmentioning

confidence: 99%

Impact of Eating Speed on Muscle Mass in Older Patients With Type 2 Diabetes: A Prospective Study of KAMOGAWA–DM Cohort

et al. 2022

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“…Earlier research has revealed that eating speed is strongly connected to body weight: fast eating is often tied to a high BMI and its associated comorbidities [18,23,[26][27][28][29], whereas slow eating is related to a lean weight status [30]. Reasons for this phenomenon are not entirely clear, although it is feasible that fast eating engenders greater energy intake [31], whereas slow eating does the opposite [32].…”

Section: Discussionmentioning

confidence: 99%

Eating Speed Is Associated with the Presence of Sarcopenia in Older Patients with Type 2 Diabetes: A Cross-Sectional Study of the KAMOGAWA-DM Cohort

et al. 2022

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To determine the relationship between eating speed and the presence of sarcopenia in older patients with type 2 diabetes (T2D), in this cross-sectional study, patient eating speeds were classified as “fast-”, “normal-” and “slow-speed eating.” A multifrequency impedance analyzer was used to evaluate patient body compositions. Sarcopenia was defined as having both low muscle strength, a handgrip strength <28 kg for men and <18 kg for women, and low skeletal muscle mass as a skeletal muscle mass index <7.0 kg/m2 for men and <5.7 kg/m2 for women. Among 239 individuals, the frequencies of fast-, normal-, and slow-speed eating were 47.3%, 32.2%, and 20.5%, respectively; and the prevalence of sarcopenia was 15.9%. Patients with a slow eating speed had greater prevalence of low skeletal muscle mass, low muscle strength, and sarcopenia than those with a fast or normal eating speed. After adjusting for covariates, compared to slow eaters, the odds ratio of having sarcopenia among fast- and normal-speed eaters was 0.31 [95% CI: 0.12–0.80] and 0.18 [95% CI: 0.06–0.53], respectively. Having a slow eating speed is associated with a heightened risk of sarcopenia in older patients with T2D.

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“…The sample sizes of the reviewed studies varied greatly, ranging from 10 (50) to 197 825 (51) participants. Similarly, participants from various age groups were included, with age ranging from 4 years (52,53) to 87 (54) years. Most studies (n = 76; 73%) included adults between 18 and 65 years old, a number of studies (n = 21; 20%) (7,43,46,47,52,53,(55)(56)(57)(58)(59)(60)(61)(62)(63)(64)(65)(66)(67)(68)(69) explicitly explored eating rate among children or adolescents, and seven studies (8,11,22,44,54,70,71) (7%) investigated older adults.…”

Section: General Study Characteristicsmentioning

confidence: 99%

Factors associated with eating rate: a systematic review and narrative synthesis informed by socio-ecological model

Chen,

Fogel,

et al. 2023

Nutr. Res. Rev.

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Accumulating evidence shows associations between rapid eating and overweight. Modifying eating rate might be a potential weight management strategy without imposing additional dietary restrictions. A comprehensive understanding of factors associated with eating speed will help with designing effective interventions. The aim of this review was to synthesize the current state of knowledge on the factors associated with eating rate. The socio-ecological model (SEM) was utilized to scaffold the identified factors. A comprehensive literature search of 11 databases was conducted to identify factors associated with eating rate. The 104 studies that met the inclusion criteria were heterogenous in design and methods of eating rate measurement. We identified 39 factors that were independently linked to eating speed and mapped them onto the individual, social and environmental levels of the SEM. The majority of the reported factors pertained to the individual characteristics (n=20) including demographics, cognitive/psychological factors and habitual food oral processing behaviours. Social factors (n=11) included eating companions, social and cultural norms, and family structure. Environmental factors (n=8) included food texture and presentation, methods of consumption or background sounds. Measures of body weight, food form and characteristics, food oral processing behaviours and gender, age and ethnicity were the most researched and consistent factors associated with eating rate. A number of other novel and underresearched factors emerged, but these require replication and further research. We highlight directions for further research in this space and potential evidence-based candidates for interventions targeting eating rate.

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Eating Slowly Is Associated with Undernutrition among Community-Dwelling Adult Men and Older Adult Women

Cited by 6 publications

References 40 publications

Impact of Eating Speed on Muscle Mass in Older Patients With Type 2 Diabetes: A Prospective Study of KAMOGAWA–DM Cohort

Impact of Eating Speed on Muscle Mass in Older Patients With Type 2 Diabetes: A Prospective Study of KAMOGAWA–DM Cohort

Eating Speed Is Associated with the Presence of Sarcopenia in Older Patients with Type 2 Diabetes: A Cross-Sectional Study of the KAMOGAWA-DM Cohort

Factors associated with eating rate: a systematic review and narrative synthesis informed by socio-ecological model

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