79 research outputs found
Vulnerable Vets? How Gatekeeping and Stereotypes Shape Access to Student-Veterans in the Qualitative Interview Process
Based on in-depth interviews we conducted with more than 30 student-veterans enrolled in higher education institutions, in this paper we examine the methodological challenges of collecting qualitative interview data from this population. Situated within the larger interdisciplinary literature of doing qualitative research with vulnerable groups, we explore the implications of student-veterans being labeled as vulnerable by ethics review boards and institutional agents such as veteran’s organizations. Based on our research experience, we argue that framing student-veterans as vulnerable can lead to further stereotyping of this group and to difficulties in accessing an already under-researched population. In addition, our inability to hear the voices and experiences of student veterans can impact the kind of services and support that higher educational institutions can provide them
Isolated HbA1c identifies a different subgroup of individuals with type 2 diabetes compared to fasting or post-challenge glucose in Asian Indians: The CARRS and MASALA studies.
AIMS: Guidelines recommend hemoglobin A1c (HbA1c) as a diagnostic test for type 2 diabetes, but its accuracy may differ in certain ethnic groups. METHODS: The prevalence of type 2 diabetes by HbA1c, fasting glucose, and 2 h glucose was compared in 3016 participants from Chennai and Delhi, India from the CARRS-2 Study to 757 Indians in the U.S. from the MASALA Study. Type 2 diabetes was defined as fasting glucose ≥ 7.0 mmol/L, 2-h glucose ≥ 11.1 mmol/L, or HbA1c ≥ 6.5%. Isolated HbA1c diabetes was defined as HbA1c ≥ 6.5% with fasting glucose < 7.0 mmol/L and 2 h glucose < 11.1 mmol/L. RESULTS: The age, sex, and BMI adjusted prevalence of diabetes by isolated HbA1c was 2.9% (95% CI: 2.2-4.0), 3.1% (95% CI: 2.3-4.1), and 0.8% (95% CI: 0.4-1.8) in CARRS-Chennai, CARRS-Delhi, and MASALA, respectively. The proportion of diabetes diagnosed by isolated HbA1c was 19.4%, 26.8%, and 10.8% in CARRS-Chennai, CARRS-Delhi, and MASALA respectively. In CARRS-2, individuals with type 2 diabetes by isolated HbA1c milder cardio-metabolic risk than those diagnosed by fasting or 2-h measures. CONCLUSIONS: In Asian Indians, the use of HbA1c for type 2 diabetes diagnosis could result in a higher prevalence. HbA1c may identify a subset of individuals with milder glucose intolerance
Potentially Heterogeneous Cross-Sectional Associations of Seafood Consumption with Diabetes and Glycemia in Urban South Asia.
Aims: In this study, we aimed to estimate cross-sectional associations of fish or shellfish consumption with diabetes and glycemia in three South Asian mega-cities. Methods: We analyzed baseline data from 2010-2011 of a cohort (n = 16,287) representing the population ≥20 years old that was neither pregnant nor on bedrest from Karachi (unweighted n = 4017), Delhi (unweighted n = 5364), and Chennai (unweighted n = 6906). Diabetes was defined as self-reported physician-diagnosed diabetes, fasting plasma glucose ≥126 mg/dL (7.0 mmol/L), or glycated hemoglobin A1c (HbA1c) ≥6.5% (48 mmol/mol). We estimated adjusted and unadjusted odds ratios for diabetes using survey estimation logistic regression for each city, and differences in glucose and HbA1c using survey estimation linear regression for each city. Adjusted models controlled for age, gender, body mass index, waist-height ratio, sedentary lifestyle, educational attainment, tobacco use, an unhealthy diet index score, income, self-reported physician diagnosis of high blood pressure, and self-reported physician diagnosis of high cholesterol. Results: The prevalence of diabetes was 26.7% (95% confidence interval: 24.8, 28.6) in Chennai, 36.7% (32.9, 40.5) in Delhi, and 24.3% (22.0, 26.6) in Karachi. Fish and shellfish were consumed more frequently in Chennai than in the other two cities. In Chennai, the adjusted odds ratio for diabetes, comparing more than weekly vs. less than weekly fish consumption, was 0.81 (0.61, 1.08); in Delhi, it was 1.18 (0.87, 1.58), and, in Karachi, it was 1.30 (0.94, 1.80). In Chennai, the adjusted odds ratio of prevalent diabetes among persons consuming shellfish more than weekly versus less than weekly was 1.08 (95% CI: 0.90, 1.30); in Delhi, it was 1.35 (0.90, 2.01), and, in Karachi, it was 1.68 (0.98, 2.86). Conclusions: Both the direction and the magnitude of association between seafood consumption and glycemia may vary by city. Further investigation into specific locally consumed seafoods and their prospective associations with incident diabetes and related pathophysiology are warranted
Effect of Conventional Lifestyle Interventions on Type 2 Diabetes Incidence by Glucose-Defined Prediabetes Phenotype:An Individual-Participant Data Meta-analysis of Randomized Controlled Trials
A1C Cut Points to Define Various Glucose Intolerance Groups in Asian Indians
Objective: To determine A1C cut points for glucose intolerance in Asian Indians. Research Design and Methods: A total of 2,188 participants without known diabetes were randomly selected from the Chennai Urban Rural Epidemiology Study. All had fasting plasma glucose (FPG) and 2-h postload plasma glucose measurements after a 75-g load and were classified as having impaired fasting glucose (IFG) (American Diabetes Association [ADA] criteria, FPG ≥5.5 and <7 mmol/l, and World Health Organization [WHO] criteria, FPG ≥6.1 and <7 mmol/l), impaired glucose tolerance (IGT) (2-h postload plasma glucose ≥7.8 and <11.1 mmol/l), or diabetes (FPG ≥7 mmol/l and/or 2-h postload plasma glucose ≥11.1 mmol/l). A1C was measured using the Bio-Rad Variant machine. Based on receiver operating characteristic curves, optimum sensitivity and specificity were derived for defining A1C cut points for diabetes, IGT, and IFG. Results: Mean ± SD values of A<SUB>1</SUB>C among subjects with normal glucose tolerance, IGT, and diabetes were 5.5 ± 0.4, 5.9 ± 0.6, and 8.3 ± 2.0%, respectively (P<SUB>trend</SUB> > 0.001) with considerable overlap. To identify diabetes based on 2-h postload plasma glucose, the A1C cut point of 6.1% had an area under the curve (AUC) of 0.941 with 88.0% sensitivity and 87.9% specificity. When diabetes was defined as FPG ≥7.0 mmol/l, the A1C cut point was 6.4% (AUC = 0.966, sensitivity 93.3%, and specificity 92.3%). For IGT, AUC = 0.708; for IFG, AUC = 0.632 (WHO criteria) and 0.708 (ADA criteria), and the A1C cut point was 5.6%. Conclusions: In Asian Indians, A1C cut points of 6.1 and 6.4% defined diabetes by 2-h postload plasma glucose or FPG criteria, respectively. A value of 5.6% optimally identified IGT or IFG but was <70% accurate
Lifetime risk of diabetes in metropolitan cities in India.
AIMS/HYPOTHESIS: We aimed to estimate the lifetime risk of diabetes and diabetes-free life expectancy in metropolitan cities in India among the population aged 20 years or more, and their variation by sex, age and BMI. METHODS: A Markov simulation model was adopted to estimate age-, sex- and BMI-specific lifetime risk of developing diabetes and diabetes-free life expectancy. The main data inputs used were as follows: age-, sex- and BMI-specific incidence rates of diabetes in urban India taken from the Centre for Cardiometabolic Risk Reduction in South Asia (2010-2018); age-, sex- and urban-specific rates of mortality from period lifetables reported by the Government of India (2014); and prevalence of diabetes from the Indian Council for Medical Research INdia DIABetes study (2008-2015). RESULTS: Lifetime risk (95% CI) of diabetes in 20-year-old men and women was 55.5 (51.6, 59.7)% and 64.6 (60.0, 69.5)%, respectively. Women generally had a higher lifetime risk across the lifespan. Remaining lifetime risk (95% CI) declined with age to 37.7 (30.1, 46.7)% at age 60 years among women and 27.5 (23.1, 32.4)% in men. Lifetime risk (95% CI) was highest among obese Indians: 86.0 (76.6, 91.5)% among 20-year-old women and 86.9 (75.4, 93.8)% among men. We identified considerably higher diabetes-free life expectancy at lower levels of BMI. CONCLUSIONS/INTERPRETATION: Lifetime risk of diabetes in metropolitan cities in India is alarming across the spectrum of weight and rises dramatically with higher BMI. Prevention of diabetes among metropolitan Indians of all ages is an urgent national priority, particularly given the rapid increase in urban obesogenic environments across the country. Graphical abstract
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Interaction between FTO gene variants and lifestyle factors on metabolic traits in an Asian Indian population
Background
Lifestyle factors such as diet and physical activity have been shown to modify the association between fat mass and obesity–associated (FTO) gene variants and metabolic traits in several populations; however, there are no gene-lifestyle interaction studies, to date, among Asian Indians living in India. In this study, we examined whether dietary factors and physical activity modified the association between two FTO single nucleotide polymorphisms (rs8050136 and rs11076023) (SNPs) and obesity traits and type 2 diabetes (T2D).
Methods
The study included 734 unrelated T2D and 884 normal glucose-tolerant (NGT) participants randomly selected from the urban component of the Chennai Urban Rural Epidemiology Study (CURES). Dietary intakes were assessed using a validated interviewer administered semi-quantitative food frequency questionnaire (FFQ). Physical activity was based upon the self-report. Interaction analyses were performed by including the interaction terms in the linear/logistic regression model.
Results
There was a significant interaction between SNP rs8050136 and carbohydrate intake (% energy) (Pinteraction = 0.04), where the ‘A’ allele carriers had 2.46 times increased risk of obesity than those with ‘CC’ genotype (P = 3.0 × 10−5) among individuals in the highest tertile of carbohydrate intake (% energy, 71 %). A significant interaction was also observed between SNP rs11076023 and dietary fibre intake (Pinteraction = 0.0008), where individuals with AA genotype who are in the 3rd tertile of dietary fibre intake had 1.62 cm lower waist circumference than those with ‘T’ allele carriers (P = 0.02). Furthermore, among those who were physically inactive, the ‘A’ allele carriers of the SNP rs8050136 had 1.89 times increased risk of obesity than those with ‘CC’ genotype (P = 4.0 × 10−5).
Conclusions
This is the first study to provide evidence for a gene-diet and gene-physical activity interaction on obesity and T2D in an Asian Indian population. Our findings suggest that the association between FTO SNPs and obesity might be influenced by carbohydrate and dietary fibre intake and physical inactivity. Further understanding of how FTO gene influences obesity and T2D through dietary and exercise interventions is warranted to advance the development of behavioral intervention and personalised lifestyle strategies, which could reduce the risk of metabolic diseases in this Asian Indian population
Global variation in diabetes diagnosis and prevalence based on fasting glucose and hemoglobin A1c
Fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) are both used to diagnose diabetes, but these measurements can identify different people as having diabetes. We used data from 117 population-based studies and quantified, in different world regions, the prevalence of diagnosed diabetes, and whether those who were previously undiagnosed and detected as having diabetes in survey screening, had elevated FPG, HbA1c or both. We developed prediction equations for estimating the probability that a person without previously diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa. The age-standardized proportion of diabetes that was previously undiagnosed and detected in survey screening ranged from 30% in the high-income western region to 66% in south Asia. Among those with screen-detected diabetes with either test, the age-standardized proportion who had elevated levels of both FPG and HbA1c was 29–39% across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and middle-income regions, isolated elevated HbA1c was more common than isolated elevated FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and underestimate diabetes prevalence. Our prediction equations help allocate finite resources for measuring HbA1c to reduce the global shortfall in diabetes diagnosis and surveillance
Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries
Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely
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