Mexican Americans' diabetes symptom prevalence, burden, and clusters

Subjective Experiences of Spanish-Speaking Patients Residing in the United States With Low English Proficiency Learning to Manage Their Diabetes: A Qualitative Study

INTRODUCTION

Language discordance is a known barrier to diabetes care in patients with type 2 diabetes. This study aimed to better understand the subjective experiences of a group of Spanish-speaking study participants with low English proficiency who were learning to manage their diabetes using a language-concordant health coaching intervention.

METHODOLOGY

This qualitative exploratory study used structured interview data to understand subjective experiences among participants. Thematic content analysis was conducted from a subset of health coaching phone transcripts (n = 17) performed during a language-concordant health coaching intervention study.

RESULTS

Among the 17 participants included in the study, even with language-concordant coaching, participants had challenges in managing their diabetes care. Participants described internal and external factors, such as socioeconomic instability, that complicated their behavior changes and self-management abilities.

DISCUSSION

A health coaching intervention in patients with low English proficiency can help to improve health outcomes. Findings from this study can guide the development of health care services and the management of chronic diseases in diverse populations.

"No sufro, estoy bien/I am not suffering, so I am doing OK": A mixed method exploration of individual and network-level factors and Type 2 Diabetes Mellitus (T2DM) among Mexican American adults in New York City

INTRODUCTION

The prevalence of type 2 Diabetes Mellitus (T2DM) is 2-3 times greater among Mexican Americans than non-Latino whites, and Mexican Americans are more likely to develop T2DM at younger ages and experience higher rates of complications. Social networks might play a crucial role in both T2DM etiology and management through social support, access to resources, social engagement, and health behavioral norms.

OBJECTIVE

To quantitatively identify the social network features associated with glycated hemoglobin (HbA1c) in a community sample of Mexican immigrants residing in New York City, and to explore the extent to which these quantitative findings converge with qualitative narratives of their lived experiences.

METHODS

This study used a convergent mixed methods design. To collect personal network data, we used EgoWeb, and obtained 1,400 personal network ties from 81 participants. HbA1c readings were collected using dried blood spots and categorized according to the laboratory criteria of the American Diabetes Association. Additional survey data were collected using Qualtrics software. To investigate the significance of the network-level factors after accounting for the socioeconomic and demographic individual-level factors that the literature indicates to be associated with T2DM, we used a multiple regression model on quantitative data sources. For the qualitative portion of the study, we selected a subset of individuals who participated in the quantitative portion, which represented 500 personal network ties from 25 participants. We conducted in-depth interviews guided by the visualization of these ties to explore who was helpful or difficult in managing their health and health behaviors.

RESULTS

Individual-level indicators associated with lower HbA1c scores were body mass index (β = -0.07, p<0.05), and healthy eating index scores (β = -0.03, p<0.02). The network-level predictor associated with higher HbA1c levels was the percentage of diabetic alters in the network (β = 0.08, p <0.001, with a 25% increase in the percentages associated 2.0 change in HbA1c levels. The qualitative data highlighted that most of the diabetes-related information diffused through the social networks of our participants was related to dietary practices, such as reducing sugar and red meat consumption, eating out less, and reducing portion sizes. Notably, even among those with elevated levels and diabetes-related health complications, HbA1c was not considered a part of the lay descriptions of good health since they were not "suffering." Participants regarded doctors as the ultimate authority in diabetes care, even if they had supportive members in their personal networks.

CONCLUSION

Our study provides quantitative evidence for the significant role of diabetic network members in the etiology and management of T2DM among Mexican Americans. Our qualitative findings suggest important ley terms for T2DM management and the importance of physicians, which could be included in in future social networks studies seeking to diffuse diabetes-related health information for T2DM prevention and management efforts in this population.

Symptom clusters in breast cancer survivors with and without type 2 diabetes over the cancer trajectory

Objective

This study aimed to investigate symptoms and symptom clusters in breast cancer survivors (BCS) with and without type 2 diabetes across three crucial periods during the cancer trajectory (0-6 months, 12-18 months, and 24-30 months) post-initial chemotherapy.

Methods

Eight common symptoms in both BCS and individuals with diabetes were identified through natural language processing of electronic health records from January 2007 to December 2018. Exploratory factor analysis was employed to discern symptom clusters, evaluating their stability, consistency, and clinical relevance.

Results

Among the 4601 BCS in the study, 20% (n = 905) had a diabetes diagnosis. Gastrointestinal symptoms and fatigue were prevalent in both groups. While BCS in both groups exhibited an equal number of clusters, the composition of these clusters differed. Symptom clusters varied over time between BCS with and without diabetes. BCS with diabetes demonstrated less stability (repeated clusters) and consistency (same individual symptoms comprising clusters) than their counterparts without diabetes. This suggests that BCS with diabetes may experience distinct symptom clusters at pivotal points in the cancer treatment trajectory.

Conclusions

Healthcare providers must be attentive to BCS with diabetes throughout the cancer trajectory, considering intensified and/or unique profiles of symptoms and symptom clusters. Interdisciplinary cancer survivorship models are essential for effective diabetes management in BCS. Implementing a comprehensive diabetes management program throughout the cancer trajectory could alleviate symptoms and symptom clusters, ultimately enhancing health outcomes and potentially reducing healthcare resource utilization.

Prevalence and burden of diabetes mellitus-related symptoms in patients with type 2 diabetes mellitus: A cross-sectional study

Introduction

Type 2 diabetes mellitus (T2DM) is a significant non-communicable disease in Malaysia, with a prevalence of 18.1%, per the National Health and Morbidity Survey. This study aimed to determine the prevalence and burden of diabetes mellitus-related symptoms and whether these symptoms were addressed by primary care doctors.

Methods

This 1-month cross-sectional study was conducted at an urban hospital-based primary care clinic in Malaysia. Patients with T2DM were recruited using systematic random sampling. Participants answered a self-administered questionnaire adapted from the Diabetes Symptom Checklist-Revised, which evaluated the sociodemographic characteristics, burden of diabetes mellitus-related symptoms in the past month and post-consultation feedback about symptoms. Data were analysed using SPSS.

Results

Four hundred eighteen participants were included, yielding a response rate of 97.7%. Hyperglycaemia was the most prevalent symptom, with 48.1% of the participants reporting a frequent need to empty their bladder. Most participants experienced a low symptom burden, so 56.7% did not report their symptoms to their doctors. The participants who reported their symptoms had a higher symptom burden. Among them, 97.5% indicated that their doctors addressed their symptoms. Approximately 78% reported satisfaction and good coping skills when their symptoms were addressed.

Conclusion

Hyperglycaemia was the most prevalent diabetes mellitus-related symptom among the patients with T2DM. The symptom burden was generally low, so most patients did not report their symptoms to their doctors. Those who reported their symptoms had a higher symptom burden. Further studies must explore why patients do not report their symptoms and how doctors address patients' symptoms.

Impact of Fatigue and Its Influencing Factors on Diabetes Self-Management in Adults With Type 2 Diabetes: A Structural Equation Modeling Analysis

PURPOSE

The purposes of this study were to (1) examine the relationships between fatigue, its influencing factors, and diabetes self-management and (2) test the mediation effects of fatigue on the link between the influencing factors and diabetes self-management in adults with type 2 diabetes.

METHODS

This cross-sectional, correlational study was guided by the theory of unpleasant symptoms. Data were collected using structured questionnaires. Fatigue was measured by the Fatigue Symptom Inventory and the Multidimensional Fatigue Inventory. Diabetes self-management was measured by the Summary of Diabetes Self-Care Activities. From March to July 2021, a convenience sample of 150 participants was recruited from 2 diabetes outpatient clinics of a regional hospital in Taiwan. Data were analyzed using structural equation modeling.

RESULTS

A more recent diagnosis of diabetes, more depressive symptoms, and lower sleep quality were related to higher fatigue. Higher fatigue correlated with less performance in diabetes self-management. Fatigue mediated the relationship between depressive symptoms, sleep quality, and diabetes self-management.

CONCLUSIONS

Fatigue had a mediating effect on the link between psychological influencing factors and diabetes self-management. Future development of fatigue interventions integrating depressive symptoms and sleep management will likely increase the performance of diabetes self-management and improve the health outcomes in adults with type 2 diabetes. The study tested the theory of unpleasant symptoms using empirical data and will assist in building theory-guided fatigue interventions to improve diabetes self-management in people with type 2 diabetes.

Characterization of Symptoms and Symptom Clusters for Type 2 Diabetes Using a Large Nationwide Electronic Health Record Database

OBJECTIVE

A variety of symptoms may be associated with type 2 diabetes and its complications. Symptoms in chronic diseases may be described in terms of prevalence, severity, and trajectory and often co-occur in groups, known as symptom clusters, which may be representative of a common etiology. The purpose of this study was to characterize type 2 diabetes-related symptoms using a large nationwide electronic health record (EHR) database.

METHODS

We acquired the Cerner Health Facts, a nationwide EHR database. The type 2 diabetes cohort (n = 1,136,301 patients) was identified using a rule-based phenotype method. A multistep procedure was then used to identify type 2 diabetes-related symptoms based on International Classification of Diseases, 9th and 10th revisions, diagnosis codes. Type 2 diabetes-related symptoms and co-occurring symptom clusters, including their temporal patterns, were characterized based the longitudinal EHR data.

RESULTS

Patients had a mean age of 61.4 years, 51.2% were female, and 70.0% were White. Among 1,136,301 patients, there were 8,008,276 occurrences of 59 symptoms. The most frequently reported symptoms included pain, heartburn, shortness of breath, fatigue, and swelling, which occurred in 21-60% of the patients. We also observed over-represented type 2 diabetes symptoms, including difficulty speaking, feeling confused, trouble remembering, weakness, and drowsiness/sleepiness. Some of these are rare and difficult to detect by traditional patient-reported outcomes studies.

CONCLUSION

To the best of our knowledge, this is the first study to use a nationwide EHR database to characterize type 2 diabetes-related symptoms and their temporal patterns. Fifty-nine symptoms, including both over-represented and rare diabetes-related symptoms, were identified.

Characterizing shared and distinct symptom clusters in common chronic conditions through natural language processing of nursing notes

Data-driven characterization of symptom clusters in chronic conditions is essential for shared cluster detection and physiological mechanism discovery. This study aims to computationally describe symptom documentation from electronic nursing notes and compare symptom clusters among patients diagnosed with four chronic conditions-chronic obstructive pulmonary disease (COPD), heart failure, type 2 diabetes mellitus, and cancer. Nursing notes (N = 504,395; 133,977 patients) were obtained for the 2016 calendar year from a single medical center. We used NimbleMiner, a natural language processing application, to identify the presence of 56 symptoms. We calculated symptom documentation prevalence by note and patient for the corpus. Then, we visually compared documentation for a subset of patients (N = 22,657) diagnosed with COPD (n = 3339), heart failure (n = 6587), diabetes (n = 12,139), and cancer (n = 7269) and conducted multiple correspondence analysis and hierarchical clustering to discover underlying groups of patients who have similar symptom profiles (i.e., symptom clusters) for each condition. As expected, pain was the most frequently documented symptom. All conditions had a group of patients characterized by no symptoms. Shared clusters included cardiovascular symptoms for heart failure and diabetes; pain and other symptoms for COPD, diabetes, and cancer; and a newly-identified cognitive and neurological symptom cluster for heart failure, diabetes, and cancer. Cancer (gastrointestinal symptoms and fatigue) and COPD (mental health symptoms) each contained a unique cluster. In summary, we report both shared and distinct, as well as established and novel, symptom clusters across chronic conditions. Findings support the use of electronic health record-derived notes and NLP methods to study symptoms and symptom clusters to advance symptom science.

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.

Analyzing the symptoms in colorectal and breast cancer patients with or without type 2 diabetes using EHR data

This research extracted patient-reported symptoms from free-text EHR notes of colorectal and breast cancer patients and studied the correlation of the symptoms with comorbid type 2 diabetes, race, and smoking status. An NLP framework was developed first to use UMLS MetaMap to extract all symptom terms from the 366,398 EHR clinical notes of 1694 colorectal cancer (CRC) patients and 3458 breast cancer (BC) patients. Semantic analysis and clustering algorithms were then developed to categorize all the relevant symptoms into eight symptom clusters defined by seed terms. After all the relevant symptoms were extracted from the EHR clinical notes, the frequency of the symptoms reported from colorectal cancer (CRC) and breast cancer (BC) patients over three time-periods post-chemotherapy was calculated. Logistic regression (LR) was performed with each symptom cluster as the response variable while controlling for diabetes, race, and smoking status. The results show that the CRC and BC patients with Type 2 Diabetes (T2D) were more likely to report symptoms than CRC and BC without T2D over three time-periods in the cancer trajectory. We also found that current smokers were more likely to report anxiety (CRC, BC), neuropathic symptoms (CRC, BC), anxiety (BC), and depression (BC) than non-smokers.