Fatigue and Sleep Quality Predict Eating Behavior Among People With Type 2 Diabetes

Latent Profile Analysis of Fatigue Subtypes in Adults With Type 2 Diabetes

BACKGROUND

People with type 2 diabetes mellitus (T2DM) commonly report a higher fatigue intensity than the general population. However, effective fatigue management is lacking because little is known about other fatigue characteristics, including timing, distress, and quality, as well as the potential fatigue subtypes experienced in people with T2DM.

OBJECTIVE

This study aims to describe fatigue intensity, timing, distress, and quality and to identify fatigue subtypes in people with T2DM.

METHODS

This cross-sectional, descriptive study included a sample of 150 participants with T2DM recruited from two diabetes outpatient clinics in Taiwan. Fatigue intensity, timing, and distress were measured using the Fatigue Symptom Inventory. Fatigue quality was measured using the Multidimensional Fatigue Inventory. Fatigue subtypes were identified using a latent profile analysis.

RESULTS

Participants reported a mild fatigue intensity, experiencing fatigue for about 22% of the day with worse fatigue in the afternoon and evening and having mild disturbances. Three fatigue subtypes were identified. The "high/persistent fatigue with mild distress" subtype was characterized by high fatigue intensity and duration with severe general, physical, and mental fatigue that mildly interfered with functioning. The "moderate/frequent fatigue with minimal distress" group showed moderate levels of fatigue intensity and duration levels with intermediate of general, physical, and mental fatigue and minimal fatigue disturbances. The "no fatigue and distress" subtype was characterized by overall low fatigue scores.

DISCUSSION

We identified fatigue characteristics and subtypes in people with T2DM, providing insights into better fatigue management. People with T2DM reported having mild but persistent fatigue. The latent profile analysis revealed that fatigue is likely composed of a mixture of physical and mental components. Nurses should assess both the physical and the mental aspects of fatigue while addressing features of the fatigue characteristics in tailored management strategies to alleviate all aspects of fatigue in people with T2DM.

Incidence of accidental falls and development of a fall risk prediction model among elderly patients with diabetes mellitus: A prospective cohort study

AIMS

To investigate the incidence of accidental falls and develop a fall risk prediction tool in elderly patients with diabetes mellitus.

BACKGROUND

The risk of fall in elderly patients with diabetes is higher than that in the general elderly, there is fewer fall assessment tools for elderly patients with diabetes.

DESIGN

A prospective cohort study.

METHODS

Between June and September 2019, a total of 1007 elderly patients with diabetes were enrolled from a tertiary specialist diabetes hospital in Tianjin and were prospectively followed up for 6 months to determine outcomes of accidental falls through telephone. Demographic and diseases related factors were collected at baseline. Incidence of falls was investigated, and a nomogram was developed based on logistic regression model. SPSS 21.0 and R 3.6.3 were used to analyse the data. The article was reported in accordance with STROBE guidelines.

RESULTS

Among 1007 elderly patients, 950 finished the follow-up. A total of 133 falls occurred in 93 patients during the follow-up period, with a fall rate of 9.79%. Diabetic peripheral neuropathy, walking aids, depression, fall history, fatigue and sex were independent predictors of accidental fall in diabetes elderly patients. The sensitivity and specificity of the predictive model were 73.12% and 52.63%, respectively, and a fall risk prediction nomogram was developed based on the regression model.

CONCLUSIONS

A nomogram including 6 easily available prediction factors (diabetic peripheral neuropathy, walking aids, depression, fall history within 1 year, fatigue, sex) was developed, and it can be used in safety management among Chinese elderly patients diagnosed with diabetes.

RELEVANCE TO CLINICAL PRACTICE

Nomogram can be used to identify diabetic elderly patients at high risk of accidental falls.

Association between poor sleep quality and emotional eating in US Latinx adults and the mediating role of negative emotions

INTRODUCTION

Poor sleep quality is associated with negative emotions and may modulate emotional eating (EE). However, this has not been studied among US Latinx adults, a group experiencing sleep disparities.

OBJECTIVE

To examine the association between sleep quality and EE in Latinx adults and explore the mediating role of negative emotions.

METHODS

This cross-sectional analysis used data from the Latino Health and Well-being Study. Sleep quality was measured with the Pittsburgh Sleep Quality Index. EE was measured with the EE subscale of the Three Factor Eating Questionnaire R18-V2 (categorized as no EE, low EE, and high EE). Negative emotions were measured via a composite score that included depression, anxiety, and perceived stress. Poisson regression models with robust variance errors estimated prevalence ratios (PR) and 95% confidence intervals (CI). Mediation was evaluated with the Karlsson-Holm-Breen method.

RESULTS

More individuals with poor (vs. good) sleep quality experienced high EE (39.1% vs. 17.9%). Individuals with poor (vs. good) sleep quality were more likely to experience high EE vs. no EE (total effect = 1.74; 95% CI = 1.34, 2.26). Controlling for negative emotions, the effect of poor sleep on high EE was reduced to 1.23 (95% CI = 0.92, 1.65), leaving an indirect effect of 1.41 (95% CI = 1.25, 1.60); 62.6% of the effect was explained by negative emotions.

CONCLUSION

Poor sleep quality was associated with high EE in US Latinx adults and negative emotions partially mediated this relationship. Longitudinal studies are needed. Interventions and clinical programs should concomitantly address sleep quality and negative emotions to help prevent dysfunctional eating behaviors.

An integrative review of fatigue in adults with type 2 diabetes mellitus: Implications for self-management and quality of life

AIMS AND OBJECTIVES

To synthesise empirical studies on factors related to fatigue and its impact on diabetes self-management (DSM) and quality of life (QOL) in adults with type 2 diabetes mellitus (T2DM).

BACKGROUND

Fatigue is commonly reported in people with T2DM, a chronic condition that is highly prevalent worldwide. However, a holistic understanding of the consequences and factors related to fatigue in adults with T2DM is not well synthesised.

DESIGN

This integrative review used Whittemore and Knafl's methodology and was reported according to the Preferred Reporting for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and checklist.

METHODS

The theory of unpleasant symptoms (TOUS) was used as a conceptual model to guide the review. The PubMed, PsychINFO and CINAHL databases were searched to identify studies that recruited adults with T2DM, were peer-reviewed, written in English and investigated fatigue as a primary or secondary outcome. Two investigators independently appraised the quality of the studies and extracted the data.

RESULTS

Twenty-nine articles met the inclusion criteria: 23 observational studies, two randomised controlled trials, one quasi-experimental study and three qualitative studies. All articles were of high quality. Physiological (e.g. T2DM duration, complications and inflammatory biomarkers), psychological (e.g. diabetes distress, depression and sleep quality) and situational factors (e.g. race/ethnicity, education and social support) were related to fatigue. Studies reported fatigue as a barrier to physical activity, healthy eating behaviours and the physical aspect of QOL.

CONCLUSIONS

Multiple factors are related to fatigue in adults with T2DM. Gaps in the literature include the multiple dimensions of fatigue, the effectiveness of interventions to alleviate fatigue and fatigue experiences in under-represented populations.

RELEVANCE TO CLINICAL PRACTICE

This integrative review supports the complex origin of fatigue and its impact on adults with T2DM. Nurses should evaluate modifiable factors related to fatigue and provide support to help improve DSM and QOL in this population.

Actigraphy-Derived Sleep Is Associated with Eating Behavior Characteristics

Poor sleep is a determinant of obesity, with overconsumption of energy contributing to this relationship. Eating behavior characteristics are predictive of energy intake and weight change and may underlie observed associations of sleep with weight status and obesity risk factors. However, relationships between sleep and dimensions of eating behavior, as well as possible individual differences in these relations, are not well characterized. Therefore, the aim of this study was to evaluate whether sleep behaviors, including duration, timing, quality, and regularity relate to dietary restraint, disinhibition, and tendency towards hunger and to explore whether these associations differ by sex. This cross-sectional study included 179 adults aged 20–73 years (68.7% women, 64.8% with BMI ≥ 25 kg/m²). Sleep was evaluated by accelerometry over 2 weeks. Eating behavior dimensions were measured with the Three-Factor Eating Questionnaire. Prolonged wake after sleep onset (WASO) (0.029 ± 0.011, p = 0.007), greater sleep fragmentation index (0.074 ± 0.036, p = 0.041), and lower sleep efficiency (−0.133 ± 0.051, p = 0.010) were associated with higher dietary restraint. However, higher restraint attenuated associations of higher WASO and sleep fragmentation with higher BMI (p-interactions < 0.10). In terms of individual differences, sex influenced associations of sleep quality measures with tendency towards hunger (p-interactions < 0.10). Stratified analyses showed that, in men only, higher sleep fragmentation index, longer sleep onset latency, and lower sleep efficiency were associated with greater tendency towards hunger (β = 0.115 ± 0.037, p = 0.003, β = 0.169 ± 0.072, p = 0.023, β = −0.150 ± 0.055, p = 0.009, respectively). Results of this analysis suggest that the association of poor sleep on food intake could be exacerbated in those with eating behavior traits that predispose to overeating, and this sleep-eating behavior relation may be sex-dependent. Strategies to counter overconsumption in the context of poor quality sleep should be evaluated in light of eating behavior traits.