Glycosylated haemoglobin in the diagnosis of diabetes mellitus in elderly people

Effect of age on the diagnostic efficiency of HbA1c for diabetes in a Chinese middle-aged and elderly population: The Shanghai Changfeng Study

Background and aims

Glycated hemoglobin A1c (HbA1c) ≥6.5% (or 48mmol/mol) has been recommended as a new diagnostic criterion for diabetes; however, limited literature is available regarding the effect of age on the HbA1c for diagnosing diabetes and the causes for this age effect remain unknown. In this study, we investigated whether and why age affects the diagnostic efficiency of HbA1c for diabetes in a community-based Chinese population.

Methods

In total, 4325 participants without previously known diabetes were enrolled in this study. Participants were stratified by age. Receiver operating characteristic curve (ROC) was plotted for each age group and the area under the curve (AUC) represented the diagnostic efficiency of HbA1c for diabetes defined by the plasma glucose criteria. The area under the ROC curve in each one-year age group was defined as AUCage. Multiple regression analyses were performed to identify factors inducing the association between age and AUCage based on the changes in the β and P values of age.

Results

The current threshold of HbA1c (≥6.5% or 48mmol/mol) showed low sensitivity (35.6%) and high specificity (98.9%) in diagnosing diabetes. ROC curve analyses showed that the diagnostic efficiency of HbA1c in the ≥75 years age group was significantly lower than that in the 45–54 years age group (AUC: 0.755 vs. 0.878; P<0.001). Pearson correlation analysis showed that the AUCage of HbA1c was negatively correlated with age (r = -0.557, P = 0.001). When adjusting the red blood cell (RBC) count in the multiple regression model, the negative association between age and AUCage disappeared, with the regression coefficient of age reversed to 0.001 and the P value increased to 0.856.

Conclusions

The diagnostic efficiency of HbA1c for diabetes decreased with aging, and this age effect was induced by the decreasing RBC count with age. HbA1c is unsuitable for diagnosing diabetes in elderly individuals because of their physiologically decreased RBC count.

Impact of demographics and disease progression on the relationship between glucose and HbA1c

CONTEXT

Several studies have shown that the relationship between mean plasma glucose (MPG) and glycated haemoglobin (HbA1c) may vary across populations. Especially race has previously been referred to shift the regression line that links MPG to HbA1c at steady-state (Herman & Cohen, 2012).

OBJECTIVE

To assess the influence of demographic and disease progression-related covariates on the intercept of the estimated linear MPG-HbA1c relationship in a longitudinal model.

DATA

Longitudinal patient-level data from 16 late-phase trials in type 2 diabetes with a total of 8927 subjects was used to study covariates for the relationship between MPG and HbA1c. The analysed covariates included age group, BMI, gender, race, diabetes duration, and pre-trial treatment. Differences between trials were taken into account by estimating a trial-to-trial variability component.

PARTICIPANTS

Participants included 47% females and 20% above 65years. 77% were Caucasian, 9% were Asian, 5% were Black and the remaining 9% were analysed together as other races.

ANALYSIS

Estimates of the change in the intercept of the MPG-HbA1c relationship due to the mentioned covariates were determined using a longitudinal model.

RESULTS

The analysis showed that pre-trial treatment with insulin had the most pronounced impact associated with a 0.34% higher HbA1c at a given MPG. However, race, diabetes duration and age group also had an impact on the MPG-HbA1c relationship.

CONCLUSION

Our analysis shows that the relationship between MPG and HbA1c is relatively insensitive to covariates, but shows small variations across populations, which may be relevant to take into account when predicting HbA1c response based on MPG measurements in clinical trials.

Aging is associated with increased HbA1c levels, independently of glucose levels and insulin resistance, and also with decreased HbA1c diagnostic specificity

AIM

To determine whether using HbA1c for screening and management could be confounded by age differences, whether age effects can be explained by unrecognized diabetes and prediabetes, insulin resistance or postprandial hyperglycaemia, and whether the effects of aging have an impact on diagnostic accuracy.

METHODS

We conducted a cross-sectional analysis in adults without known diabetes in the Screening for Impaired Glucose Tolerance (SIGT) study 2005-2008 (n=1573) and the National Health and Nutrition Examination Survey (NHANES) 2005-2006 (n=1184).

RESULTS

Both glucose intolerance and HbA(1c) levels increased with age. In univariate analyses including all subjects, HbA(1c) levels increased by 0.93 mmol/mol (0.085%) per 10 years of age in the SIGT study and by 1.03 mmol/mol (0.094%) per 10 years in the NHANES; in both datasets, the HbA(1c) increase was 0.87 mmol/mol (0.08%) per 10 years in subjects without diabetes, and 0.76 mmol/mol (0.07%) per 10 years in subjects with normal glucose tolerance, all P<0.001. In multivariate analyses of subjects with normal glucose tolerance, the relationship between age and HbA(1c) remained significant (P<0.001) after adjustment for covariates including race, BMI, waist circumference, sagittal abdominal diameter, triglyceride/HDL ratio, and fasting and 2-h plasma glucose and other glucose levels, as assessed by an oral glucose tolerance test. In both datasets, the HbA(1c) of an 80-year-old individual with normal glucose tolerance would be 3.82 mmol/mol (0.35%) greater than that of a 30-year-old with normal glucose tolerance, a difference that is clinically significant. Moreover, the specificity of HbA(1c) -based diagnostic criteria for prediabetes decreased substantially with increasing age (P<0.0001).

CONCLUSIONS

In two large datasets, using different methods to measure HbA(1c), the association of age with higher HbA(1c) levels: was consistent and similar; was both statistically and clinically significant; was unexplained by features of aging; and reduced diagnostic specificity. Age should be taken into consideration when using HbA(1c) for the diagnosis and management of diabetes and prediabetes.

Patterns of glycemic control using glycosylated hemoglobin in diabetics

Aim:

Till now estimation of blood glucose is the highly effective method for diagnosing diabetes mellitus but it provides a short-term picture of control. More evidence is required to prove that plasma glucose and glycosylated hemoglobin levels together gives a better estimate of glycemic control and compliance with treatment. Indian diabetes risk score (IDRS) is a simplified screening tool for identifying undiagnosed diabetic subjects, requires minimum time, and effort and can help to considerably reduce the costs of screening.

Objective:

To study patterns of glycemic control using glycosylated hemoglobin in diabetic patients. To find out correlation between levels of plasma glucose and glycosylated hemoglobin in diabetics and to calculate IDRS of the study population.

Materials and Methods:

A cross sectional study was conducted among 300 known diabetic patients attending outpatient department of a rural medical college in Haryana, India. Following standard procedures and protocols FPG and glycosylated hemoglobin were measured to find out a pattern of glycemic control in them after taking their written and informed consent. A correlation between the levels of glycosylated hemoglobin and fasting blood glucose was also calculated. These patients were made to fill a performa and their demographic and clinical risk factors were noted and based on this, their IDRS was calculated. This was done to validate the IDRS in Indian rural population.

Results:

Fifty-two percent of the population had fasting plasma glucose level between 125-150 mg/dl, 21% had this level between 151-175 mg/dl. Thirteen percent of the study subjects had HbA1C between 6.5-7.5, more than half (57.3%) had this value between 7.5-8.5, 12% and 18% had values between 8.5-9.5 and 9.5-10.5, respectively. Twelve percent of the participants had HbA1C level higher than 10.5. Correlation of fasting plasma glucose level and HbA1C was also studied and found that correlation coefficient came out to be .311. This correlation was found to be statistically significant (P = .007). Sixty-five percent of the case had IDRS higher than 60.

Conclusions:

Glycaemic control in diabetics can be better assessed with glycosylated hemoglobin and FPG together. A positive correlation between FPG and HbA1c allows for the use of HbA1c along with FPG in diagnosing type 2 DM but the two should not be used interchangeably. IDRS can be used as a screening tool for diabetes.

HbA1c may not be a sensitive determinant of diabetic status in the elderly

OBJECTIVE

American Diabetes Association (ADA) has recently recommended the use of glycated haemoglobin (HbA1c) to diagnose diabetes mellitus. We aim to determine if indeed this recommendation applies to the population in Singapore and whether it varies with age.

METHOD

This is a cross sectional study of 90 patients without previous history of diabetes who underwent screening and had both oral glucose tolerance test (OGTT) and HbA1c done at the same time. These patients were stratified into 4 age groups.

RESULT

We found that HbA1c of 6.2% is the best cut-off to diagnose diabetes using ROC curve analysis. At the specified HbA1c, the area under ROC curve (AUROC) reduces as age group increases suggesting that sensitivity and specificity of HbA1c as diagnostic marker reduces as age increases.

CONCLUSION

HbA1c has a low sensitivity to diagnose diabetes in older Asian subjects and caution is required when using HbA1c in isolation. This raises the possibility that a different cut-off value for different age groups may be more appropriate.

Alterations in HbA(1c) with advancing age in subjects with normal glucose tolerance: Chandigarh Urban Diabetes Study (CUDS)

OBJECTIVE

To study the alterations in HbA(1c) with advancing age in subjects with normal glucose tolerance.

METHODS

Community-based cross-sectional study involving 2368 subjects aged ≥ 20 years from Chandigarh, India. All the subjects underwent an oral glucose tolerance test with 75 g anhydrous glucose and were classified as having normal glucose tolerance, pre-diabetes or diabetes according to World Health Organization 1999 criteria. HbA(1c) was measured on a National Glycohemoglobin Standardization Program-certified Bio-Rad D-10 system and the data were available for 1972 subjects.

RESULTS

Out of 1972 subjects, 1317 (67%) subjects had normal glucose tolerance. There was a significant positive correlation between mean HbA(1c) and age in these subjects (r = 0.308, P(trend) < 0.001). The increase in HbA(1c) with each advancing year was 0.01% above the age of 20 years and corrected HbA(1c) (%) for age was 5.09 + 0.01 (age). The 95th percentile of HbA(1c) exceeded 6.5% (48 mmol/mol) (the American Diabetes Association cut-off for diagnosis of diabetes) in subjects aged ≥ 70 years. A significantly higher number (6.5%, 21/325) of subjects had HbA(1c) of ≥ 6.5% (48 mmol/mol) in those above the age of 50 years compared with those below the age of 50 years (1.7%, 17/992) in the group with normal glucose tolerance (P < 0.001). On multivariate regression analysis, after adjusting for BMI, fasting plasma glucose and 2-h plasma glucose post-glucose load, the correlation of HbA(1c) with age still remained significant (r = 0.241, P < 0.01).

CONCLUSION

HbA(1c) increases with advancing age independent of glycaemia, suggesting caution when seeking to achieve the recommended HbA(1c) targets in the elderly population.

Effect of aging on A1C levels in individuals without diabetes: evidence from the Framingham Offspring Study and the National Health and Nutrition Examination Survey 2001-2004

OBJECTIVE

Although glycemic levels are known to rise with normal aging, the nondiabetic A1C range is not age specific. We examined whether A1C was associated with age in nondiabetic subjects and in subjects with normal glucose tolerance (NGT) in two population-based cohorts.

RESEARCH DESIGN AND METHODS

We performed cross-sectional analyses of A1C across age categories in 2,473 nondiabetic participants of the Framingham Offspring Study (FOS) and in 3,270 nondiabetic participants from the National Health and Nutrition Examination Survey (NHANES) 2001-2004. In FOS, we examined A1C by age in a subset with NGT, i.e., after excluding those with impaired fasting glucose (IFG) and/or impaired glucose tolerance (IGT). Multivariate analyses were performed, adjusting for sex, BMI, fasting glucose, and 2-h postload glucose values.

RESULTS

In the FOS and NHANES cohorts, A1C levels were positively associated with age in nondiabetic subjects. Linear regression revealed 0.014- and 0.010-unit increases in A1C per year in the nondiabetic FOS and NHANES populations, respectively. The 97.5th percentiles for A1C were 6.0% and 5.6% for nondiabetic individuals aged <40 years in FOS and NHANES, respectively, compared with 6.6% and 6.2% for individuals aged >or=70 years (P(trend) < 0.001). The association of A1C with age was similar when restricted to the subset of FOS subjects with NGT and after adjustments for sex, BMI, fasting glucose, and 2-h postload glucose values.

CONCLUSIONS

A1C levels are positively associated with age in nondiabetic populations even after exclusion of subjects with IFG and/or IGT. Further studies are needed to determine whether age-specific diagnostic and treatment criteria would be appropriate.

Glycohemoglobin screening in adolescents attending to the Department of Paediatrics at a tertiary hospital in Turkey

OBJECTIVE

To investigate glycohemoglobin (HbAIc) levels in adolescents without diabetes, attending to our Adolescent Day Care Clinic.

SUBJECTS AND METHODS

We studied on randomly selected 186 subjects aged between 9 and 18 years. HbA1c levels were measured in all subjects and those whose HbA1c levels >95th percentile were invited for oral glucose tolerance test (OGTT). Homeostasis of model assessment (HOMA-IR) value was used to define insulin resistance in subjects who underwent OGTT.

RESULTS

The median age of all subjects was 11 (min 9-max 18) years and 50.5% were boys. The median HbA1c level was higher in boys (5.2%; min 4.4-max 6.2) than girls (5.0%; min 4.0-max 6.4) (p=0.001). Fasting glucose was positively correlated to HbA1c (r=0.26, p=0.001). HOMA-IR values were >2.5 in six subjects and four of them were obese while two had impaired glucose tolerance. In multivariate analysis, it was observed that gender (boy) and high-fasting glucose levels were associated with high-HbA1c levels (OR 1.9, CI 95%: 1.0-3.4, p=0.02 and OR 1.1, CI 95%: 1.0-1.1, p=0.001, respectively).

CONCLUSIONS

We believe that routine HbA1c screening is not necessary for adolescents without diabetes. However screening may become desirable in the future at least for obese adolescents.

Prevalence of diabetes mellitus in elderly patients received enteral nutrition long-term care service

The purpose of this study was to determinate the prevalence of undiagnosed diabetes mellitus (UDM) using glycated hemoglobin (GHb) among functionally dependent and severe cognitive depressed elderly long-term care (LTC) patients received enteral nutrition. The patients were divided into three categories: control, patients with (diabetes mellitus, DM) and without previously diagnoses (UDM) of DM. Demographic, functional and cognitive status, laboratory data and rate of death were recorded. Patients with HbA-1c level of 7% and more were diagnosed as diabetic. On the baseline, 26% of the patients presented with known DM. Patients from control and previously UDM groups presented with similar fasting plasma glucose (FPG) and post-prandial glucose (PPG) levels, but were different by HbA-1c levels (p<0.001). In 79% of patients suffering from UDM, HbA-1c levels was more than 7%, and in 24% of them more than 8%. Prevalence of UDM was 21%. Patients from UDM were presented as borderline group between Control group (C-G) and DM. Those differences presented by all general characteristics of the patients: age, functional and cognitive status, BMI, comorbidity, laboratory data and rate of death. This study suggests that 47% of LTC patients who received enteral nutrition suffered from DM, and 44% of them were undiagnosed. The authors recommend that the GHb is a simple and an effective laboratory analysis in detection of DM in this group of patients.

Searching for the biological pathways between stress and health

Population-based, person-specific health surveys, with concomitant biological measures, should provide important information about the processes by which socioeconomic and psychosocial factors embed themselves in human health. Questionnaire responses allow for assessment of the perceived psychosocial environment, but biological measurements will measure the status of the psychoneuroimmunology/ psychoneuroendocrinology (PNI/PNE) pathways and may allow us to identify people who have "adapted" to their stress because of experience, expectations, stoicism, etc. This review sets criteria to evaluate potential physiological markers of chronic stress. Because population health surveys involve a massive number of samples, special consideration must be given to the laboratory analysis method and transportation time of the markers chosen. We reviewed five areas: glycosylated proteins, the immune system, hemostasis peripheral benzodiazepine receptors, and the waist-hip ratio.