Economic impact of moderate weight loss in patients with Type 2 diabetes: the Fremantle Diabetes Study

Impact of Weight Change in Adults with Type 2 Diabetes Mellitus: A Literature Review and Critical Analysis

Objective

Weight reduction is a key component of diabetes management in adults with type 2 diabetes mellitus (T2DM), yet the benefits of weight loss in T2DM patients have been difficult to quantify. We examined the medical literature regarding the relationships between weight change and 1) glycemic control and 2) cost and resource use.

Methods

Systematic searches were conducted in the electronic databases Embase, MEDLINE, and the Cochrane Database of Systematic Reviews to identify publications regarding the impact of weight change on T2DM outcomes from 2007 onward. Identified publications were screened for relevance against predefined eligibility criteria, and methodological approaches and results were extracted. Evidence for the impact of weight change on outcomes was evaluated and used to identify strengths, limitations, and gaps in the current literature.

Results

The number of studies meeting eligibility criteria for each outcome was: glycemic control (n=38) and cost and resource use (n=11). The relationship between weight change and glycemic control was dependent on the interplay of multiple factors, eg, the weight loss interventions employed, the antidiabetic medication classes used, the time horizon, and baseline BMI and glycemic control. With respect to cost and resource use, the review indicated that savings were associated with weight loss, and increased costs were associated with weight gain.

Conclusion

Studies regarding weight change in T2DM patients demonstrated varying effects on glycemic control and a positive association with costs and resource use, where weight loss was associated with decreased costs and resource use. Future studies may be able to clarify these relationships.

Real-world impact of ongoing regular exercise in overweight and obese US adults with diabetes on health care utilization and expenses

AIMS

To assess the effect of regular exercise on health care utilization patterns and expenses in a real-world national sample of overweight and obese US adults with diabetes.

METHODS

Medical Expenditure Panel Survey data (2010-2015) identified adults with diabetes and a body mass index (kg/m²) ≥25. Two groups were created: exercise (moderate or vigorous physical activity >30min at least five times weekly) and non-exercise groups.

OUTCOMES MEASURED

average total health care expenses (per-person per-annum) and the likelihood of hospitalization.

RESULTS

Among 5140 overweight and obese adults with diabetes, 49.1% reported exercising at least five times weekly. The exercise group showed lower medical care and prescription drug utilization than the non-exercise group (p<0.001). Total unadjusted health expenses in the exercise group were $5651 lower than the non-exercise group (p<0.001). After controlling for socioeconomic and health-related variables, regular exercise reduced total health care expenses by 22.1% (p<0.001) and the likelihood of hospitalization by 28% (p=0.001).

CONCLUSIONS

Reduced hospitalization and health care expenses were associated with regular exercise (≥30min at least five times weekly) in overweight and obese adults with diabetes.

Effect of Weight Change on Economic Outcomes Among Persons with Type 2 Diabetes Mellitus in the United States: Beyond Glycemic Control

BACKGROUND

Previous studies report weight loss to be associated with significantly lower total health care costs among patients with type 2 diabetes mellitus (T2DM). The effect of weight change on health care costs, independent of glycemic control and after controlling for time-varying covariates among T2DM patients, remains unknown.

OBJECTIVE

To evaluate the effect of weight change, independent of glycemic control, on all-cause and T2DM-related health care resource utilization (HCRU) and costs among T2DM patients in the United States.

METHODS

A retrospective cohort study was conducted using a linked data extract composed of IQVIA's RWI Data Adjudicated Claims-US and Ambulatory Electronic Medical Record data. Adults (aged ≥ 18 years) with T2DM receiving ≥ 1 oral antidiabetic drug (OAD) medication, glucagon-like peptide-1 receptor agonist (GLP-1RA), and/or short- or long-acting insulin between January 1, 2010, and December 31, 2014 were included (the date of the first observed medical claim with a diagnosis code or medication prescription claim was the index date). Baseline characteristics were evaluated in the 6-month pre-index period. Weight loss (3%, 5%, or 7% from baseline) was evaluated over two 6-month periods (months 1-6 and 7-12) following the index date. Covariates included time-varying weight, hemoglobin A1c (A1c), costs, and HCRU within each 6-month period. Outcomes of interest (all-cause and T2DM-related HCRU and costs) were evaluated in the 6-month (months 13-18) and 12-month (months 13-24) periods following the initial 1- to 6-month and 7- to 12-month post-index periods. Structural nested mean models were used to evaluate the effect of weight change on these outcomes, independent of glycemic control.

RESULTS

1,407 patients were included (mean age = 55 years; 55% male), with a mean baseline weight of 102.2 kg (median = 99.7 kg) and a mean baseline A1c of 7.4% (median = 6.9%). In adjusted analysis, weight loss was associated with significantly lower all-cause and T2DM-related annual total health care costs. Compared with those showing no weight change, a 3%, 5%, and 7% weight loss resulted in approximately $500, $800, and $1,100 in savings, respectively, in all-cause annual total health care costs per patient in the year following the weight loss. Similarly, compared with those with no weight change, a 3%, 5%, and 7% weight loss resulted in approximately $200, $300, and $400 in savings, respectively, in T2DM-related annual total health care costs per patient in the following year. Even greater savings (up to ~$2,000 and ~$800 in all-cause and T2DM-related annual costs per patient, respectively) were experienced by those who lost weight compared with those who gained weight.

CONCLUSIONS

After accounting for glycemic control, this study found that weight loss was associated with additional significant reductions in all-cause and T2DM-related annual total health care costs. Understanding the role of weight loss in T2DM may provide useful evidence for decision makers as they evaluate therapy options for T2DM.

DISCLOSURES

This study was funded by Novo Nordisk. Dang-Tan, Smolarz, and Iyer are employees of Novo Nordisk. Karkare and DeKoven (employees of IQVIA) and Fridman (employed by AMF Consulting) were contracted by Novo Nordisk to conduct this study. Fridman also reports personal fees from Shire, GSK, and CSL Behring, outside of the submitted work. Lu, an employee of IQVIA, accessed the database and conducted the statistical analysis for this study.

Electronic Health Lifestyle Coaching Among Diabetes Patients in a Real-Life Municipality Setting: Observational Study

Background

Internet and mobile interventions aiming to promote healthy lifestyle have attracted much attention because of their scalability and accessibility, low costs, privacy and user control, potential for use in real-life settings, as well as opportunities for real-time modifications and interactive advices. A real-life electronic health (eHealth) lifestyle coaching intervention was implemented in 8 Danish municipalities between summer 2016 and summer 2018.

Objective

The aim of this study was to assess the effects associated with the eHealth intervention among diabetes patients in a real-life municipal setting. The eHealth intervention is based on an initial meeting, establishing a strong empathic relationship, followed by digital lifestyle coaching and collaboration supported by a Web-based community among patients.

Methods

We conducted an observational study examining the effect of an eHealth intervention on self-reported weight change among 103 obese diabetes patients in a real-life municipal setting. The patients in the study participated in the eHealth intervention between 3 and 12 months. A weight change was observed at 6, 9, and 12 months. We used regression methods to estimate the impacts of the intervention on weight change.

Results

We found that the eHealth intervention significantly reduced weight among diabetes patients, on average 4.3% of the initial body mass, which corresponds to 4.8 kg over a mean period of 7.3 months. Patients who were in intervention for more than 9 months achieved a weight reduction of 6.3% or 6.8 kg.

Conclusions

This study brings forward evidence of a positive effect of a real-life eHealth lifestyle intervention on diabetes patients’ lifestyle in a municipal setting. Future research is needed to show if the effect is sustainable from a long-term perspective.

Nutrition Education and Community Pharmacy: A First Exploration of Current Attitudes and Practices in Northern Ireland

Community pharmacist is one of the most prominent and accessible healthcare professions. The community pharmacists' role in healthcare is evolving, with opportunities being taken to reduce pressure on primary care services. However, the question remains of how well community pharmacists are equipped for this changing role. This was a sequentially designed study using a mix of methods to explore nutrition education among community pharmacists in Northern Ireland. It consisted of two phases. Phase 1 was a cross-sectional exploration to map the attitudes and practice of Northern Ireland (NI) pharmacists towards diet-related health promotion and disease prevention. An online questionnaire with open and closed questions to gain both quantitative and qualitative responses was developed and distributed to community pharmacists practising in NI. A total of 91% considered nutrition important in reducing the global burden of disease. While the majority (89%) believed patients would value nutritional advice from a pharmacist, 74% were not confident in providing advice to a patient with diabetes. From the consensus gained in Phase 1 a nutrition education intervention (Phase 2) for pre-registration pharmacists was developed using the Hardens 10 question system. The training programme was advertised to pre-registration pharmacy students in NI. It was delivered by nutrition experts who have education qualifications. The intervention was evaluated using a before and after questionnaire that assessed knowledge, attitudes, and practice (KAP). Phase 2 did find sustained improvement from the baseline in KAP but there was a decline from immediately post-training to three months post-training. This suggests the need to further embed nutrition education. The education programme was found to be effective for the target population and sets the stage for the development of an implementation strategy for a wider roll-out with evaluation.

Opportunities and challenges of behavior change support systems for enhancing habit formation: A qualitative study

The formation of healthy habits is considered to play a fundamental role in health behavior change. A variety of studies on Health Behavior Change Support Systems (HBCSS) have been conducted recently, in which individuals use such systems to influence their own attitudes or behaviors to achieve their personal goals. However, comparatively much less research has been devoted to studying how the users of these systems form habits with the help of HBCSS, or to understanding how to design these systems to support habit formation.

OBJECTIVE

The objective of this article is to study HBCSS user experiences regarding habit formation through an intervention study targeted at establishing a healthier lifestyle. This study also aims to map habit formation stages, as suggested by Lally and Gardner, with the Persuasive System Design (PSD) model. The application domain is the prevention of metabolic syndrome, in which 5% weight loss can significantly reduce the prevalence of the syndrome.

METHODS

This study employs a web-based HBCSS named Onnikka, a lifestyle intervention designed for the prevention of metabolic syndrome for participants who are at risk of developing a metabolic syndrome or are already suffering from it. The system under investigation was designed according to the principles of the PSD model and Behavior Change Support System framework. Lally and Gardner's research on the stages of habit formation were used to study the extent to which the Onnikka system was able to enhance the development of new habits. A total of 43 Onnikka users were interviewed for this study during and after a 52-week intervention period. The research approach employed here was hermeneutics, which leans ontologically toward the social construction of reality, gained through language, consciousness, and shared meaning. In addition, the system's login data and participants' weight measurements were utilized to build an interpretation of the results.

RESULTS

The findings of this study suggest that IT habits appear to have a strong linkage with use adherence, whereas lifestyle habits did not seem to be directly related to the 5% weight loss among study participants. Moreover, habit formation stages provide a possible explanation for why self-monitoring, reminders, and tunneling were perceived as especially valuable features in this study.

CONCLUSIONS

For sustainable weight management, holistic e-health interventions are required, and the PSD model offers a practical approach for designing and developing them. Recognizing the stages of habit formation provides additional valuable guidance for designing systems that help shape an individual's habits.

Incremental Treatment Costs Attributable to Overweight and Obesity in Patients with Diabetes: Quantile Regression Approach

OBJECTIVE

This study aimed to estimate treatment costs attributable to overweight and obesity in patients with diabetes who were less than 65 years of age in the United States.

METHODS

This study used data from the Medical Expenditure Panel Survey from 2001 to 2013. Patients with diabetes were identified by using the International Classification of Diseases, Ninth Revision, Clinical Modification code (250), clinical classification codes (049 and 050), or self-reported physician diagnoses. Total treatment costs attributable to overweight and obesity were calculated as the differences in the adjusted costs compared with individuals with diabetes and normal weight. Adjusted costs were estimated by using generalized linear models or unconditional quantile regression models.

RESULTS

The mean annual treatment costs attributable to obesity were $1,852 higher than those attributable to normal weight, while costs attributable to overweight were $133 higher. The unconditional quantile regression results indicated that the impact of obesity on total treatment costs gradually became more significant as treatment costs approached the upper quantile.

CONCLUSIONS

Among patients with diabetes who were less than 65 years of age, patients with diabetes and obesity have significantly higher treatment costs than patients with diabetes and normal weight. The economic burden of diabetes to society will continue to increase unless more proactive preventive measures are taken to effectively treat patients with overweight or obesity.

Weight change patterns and healthcare costs in patients with newly-diagnosed type-2 diabetes in Sweden

AIMS

To describe weight-change pathways in patients with type 2 diabetes (T2D) and associated healthcare costs using repeated BMI measurements and healthcare utilization data.

METHODS

Patients with newly-diagnosed T2D with body mass index (BMI, kg/m²) at diagnosis and subsequent measures at year 1-3 were identified. Based on three-year BMI change, patients were assigned to one of 27 BMI change pathways defined by annual BMI change: BMI↗ (≥1 BMI unit increase), BMI→ (<1 BMI unit change), and BMI↘ (≥1 BMI unit decrease). Mean annual and three-year cumulative healthcare costs were estimated for each pathway by combining Swedish unit costs with resource use from primary care and national patient registers.

RESULTS

Cohort consisted of 15,819 patients; 44% women, mean age of 61 years, HbA1c of 6.7% (50mmol/mol), BMI of 30.6kg/m². Most common BMI pathways (mean costs): BMI→→→ (€5,311), BMI↘→→ (€5,461), and BMI→→↘ (€6,281). General trends: BMI→→→ linked to lowest, BMI↗→↗ linked to highest costs.

CONCLUSION

In patients with newly-diagnosed T2D, weight stability was the most common BMI change pattern over 3 years and associated with lowest healthcare costs. Relationship between weight change and healthcare costs appears complex warranting further investigation.

Association Between Weight Change, Clinical Outcomes, and Health Care Costs in Patients with Type 2 Diabetes

BACKGROUND

Previous research suggests that weight loss is associated with decreases in health care costs among individuals with type 2 diabetes mellitus (T2DM) and that weight change can affect clinical measures, including hemoglobin A1c (A1c), low-density lipoprotein cholesterol (LDLC), and blood pressure. Previous research has also demonstrated more pronounced impact of weight change among patients with T2DM who are obese and have no evidence of cardiovascular disease (CVD).

OBJECTIVES

To (a) examine the association between weight change and all-cause and diabetes-related health care costs among patients with T2DM; (b) examine the association between weight change and select clinical measures among patients with T2DM; and (c) analyze a subgroup of obese patients with no previous CVD.

METHODS

This retrospective, observational cohort study used U.S. insurance claims linked to laboratory and electronic medical records. This study included patients with T2DM aged 18 years or older who added or switched to a nonmetformin antidiabetes medication after metformin monotherapy between January 1, 2007, and June 30, 2012 (date of add/switch was the index date). The primary predictor was percentage weight change (PWC) between a weight measurement at index and a follow-up measurement 6 months later; PWC ranged from negative (weight loss) to positive (weight gain). Outcomes, measured in the 12-month period beginning at the time of follow-up weight measurement, included all-cause and diabetes-related health care costs and achievement of thresholds for A1c, blood pressure, and LDL-C. Multivariable models quantified the association between PWC (linear effect) and study outcomes.

RESULTS

A total of 1,520 patients (mean age 55 years; 47% female) were included, with 780 patients (mean age 53 years; 51% female) in the subgroup sample. Mean (SD) index weight and PWC were 224.6 (52.8) lbs and +0.2% (4.7%) in the primary analysis, and 241.3 (47.3) lbs and -0.2% (4.6%) in the subgroup sample. In adjusted analyses, decreasing PWC was associated with decreasing diabetes-specific pharmacy costs (P < 0.001) in the primary analysis sample and with decreasing all-cause pharmacy costs (P = 0.018), diabetes-specific total costs (P = 0.039), diabetes-specific medical costs (P = 0.002), and diabetes-specific pharmacy costs (P < 0.001) in the subgroup sample. PWC was not associated with all-cause total health care costs or all-cause medical costs in either sample. In adjusted analyses, decreasing PWC was also associated with increasing odds of attaining the A1c goals of < 6.5% (P < 0.001) and < 7.0% (P < 0.001) in the primary analysis sample and increasing odds of attaining the A1c goals of < 6.5% (P < 0.001), < 7.0% (P < 0.001), and < 8.0% (P = 0.010) in the subgroup sample. PWC was not associated with any of the other clinical measures in either of the study samples.

CONCLUSIONS

This real-world study suggests that among patients with T2DM, weight loss over a short-term (6-month) period is associated with positive impact on attainment of A1c goals and decreased diabetes-specific pharmacy costs over the subsequent 12 months. In the subset of patients who were obese and had no previus CVD, weight loss over the 6-month period was also associated with decreased all-cause pharmacy costs, diabetes-specific medical costs, and diabetes-specific total health care costs. Future research is warranted to examine whether these associations change over longer-term periods of follow-up.

DISCLOSURES

This study was sponsored by AstraZeneca and Bristol-Myers Squibb. Truven Health Analytics received funding from Bristol-Myers Squibb and AstraZeneca to conduct this study. Mukherjee is an employee of Bristol-Myers Squibb. Bell and Sternhufvud are employees of AstraZeneca. Johnston, Stott-Miller, and McMorrow are employees of Truven Health Analytics. Nancy Smith is a consultant to Bristol-Myers Squibb and is employed by GreenKey Resources. Study concept was created by Mukherjee, Sternhufvud, Bell, and Johnston. Stott-Miller and McMorrow took the lead in data collection, along with Johnston, with data interpretation performed by Mukherjee, Sternhufvud, Smith, Stott-Miller, and Johnston. The manuscript was written by Mukherjee, Johnston, and Stott-Miller, along with Sternhufvud and Smith, and revised by Mukherjee, Smith, and Johnston, along with Sternhufvud and Stott-Miller.

Persuasive user experiences of a health Behavior Change Support System: A 12-month study for prevention of metabolic syndrome

BACKGROUND

Obesity has become a severe health problem in the world. Even a moderate 5% weight loss can significantly reduce the prevalence of metabolic syndrome, which can be vital for preventing comorbidities caused by the obesity. Health Behavior Change Support Systems (hBCSS) emphasize an autogenous approach, where an individual uses the system to influence one's own attitude or behavior to achieve his or her own goal. Regardless of promising results, such health interventions technology has often been considered merely as a tool for delivering content that has no effect or value of its own. More research on actual system features is required.

OBJECTIVES

The objective of this study is to describe how users perceive persuasive software features designed and implemented into a support system.

METHODS

The research medium in this study is a web-based information system designed as a lifestyle intervention for participants who are at risk of developing a metabolic syndrome or who are already suffering from it. The system was designed closely following the principles of the Persuasive Systems Design (PSD) model and the Behavior Change Support Systems (BCSS) framework. A total of 43 system users were interviewed for this study during and after a 52 week intervention period. In addition, the system's login data and subjects' Body Mass Index (BMI) measures were used to interpret the results.

RESULTS

This study explains in detail how the users perceived using the system and its persuasive features. Self-monitoring, reminders, and tunneling were perceived as especially beneficial persuasive features. The need for social support appeared to grow along the duration of the intervention. Unobtrusiveness was found to be very important in all stages of the intervention rather than only at the beginning.

CONCLUSIONS

Persuasive software features have power to affect individuals' health behaviors. Through their systematicity the PSD model and the BCSS framework provide effective support for the design and development of technological health interventions. Designers of such systems may choose, for instance, to implement more self-monitoring tools to help individuals to adjust their personal goals with the system's offerings better.

Weight change and healthcare resource use in English patients with type 2 diabetes mellitus initiating a new diabetes medication class

AIMS

The aim of this study was to investigate the association between weight change and healthcare resource use (HCRU) and costs in English primary care patients with type 2 diabetes mellitus (T2DM) initiating treatment with a new diabetes medication class.

METHODS

Patients diagnosed with T2DM initiating a new diabetes medication class (first-line, switch or add-on treatment) were selected from Clinical Practice Research Datalink. Weight change (index date) was measured 6 months after initiating new treatment. HCRU was derived up to 1 year after index. Adjusted analyses evaluated the association between weight change and HCRU and costs (GBP, 2013 prices).

RESULTS

Of 9031 patients, about half (n = 4901) experienced < 3% weight change (weight neutral); the proportions gaining or losing weight were similar. Compared with the weight neutral group, weight gain was associated with significantly increased total costs within a year (3.0-5.4% weight gain: £58.9; p = 0.01, ≥ 5.5% weight gain: £52.9; p = 0.04) and diabetes primary care costs (3.0-5.4% weight gain: £29.2; p < 0.001, ≥ 5.5% weight gain: £34.2; p < 0.001). This included increased rates of prescribing drugs for diabetes and, in ≥ 5.5% weight gain, increased primary care contacts. A ≥ 5.5% weight loss was associated with increased hospital admissions (odds ratio = 1.4; p < 0.0001) and total costs (£126.3; p < 0.001).

CONCLUSION

Weight gain after initiating a new glucose-lowering medication is associated with increased prescribing and contact with primary care clinicians, with increased costs in primary care and total spending. This study supports that weight gain in diabetes is associated with increased healthcare costs.

Cost-effectiveness of once daily GLP-1 receptor agonist lixisenatide compared to bolus insulin both in combination with basal insulin for the treatment of patients with type 2 diabetes in Norway

BACKGROUND

Lixisenatide is a potent, selective and short-acting once daily prandial glucagon-like peptide-1 receptor agonist which lowers glycohemoglobin and body weight by clinically significant amounts in patients with type 2 diabetes treated with basal insulin, with limited risk of hypoglycemia.

OBJECTIVE

To assess the cost-effectiveness of lixisenatide versus bolus insulin, both in combination with basal insulin, in patients with type 2 diabetes in Norway.

METHODS

The IMS CORE Diabetes Model, a non-product-specific and validated simulation model, was used to make clinical and cost projections. Transition probabilities, risk adjustments and the progression of complication risk factors were derived from the UK Prospective Diabetes Study, supplemented with Norwegian data. Patients were assumed to receive combination treatment with basal insulin, lixisenatide or bolus insulin therapy for 3 years, followed by intensification of a basal-bolus insulin regimen for their remaining lifetime. Simulated healthcare costs, taken from the public payer perspective, were derived from microcosting and diagnosis related groups, discounted at 4% per annum and reported in Norwegian krone (NOK). Productivity costs were also captured based on extractions from the Norwegian Labor and Welfare Administration. Health state utilities were derived from a systematic literature review. Sensitivity and scenario analyses were performed.

RESULTS

Lixisenatide in combination with basal insulin was associated with increased quality-adjusted life years (QALYs) and reduced lifetime healthcare costs compared to bolus insulin in combination with basal insulin in patients with Type 2 diabetes, and can be considered dominant. The net monetary benefit of lixisenatide versus bolus insulin was NOK 39,369 per patient. Results were sensitive to discounting, the application of excess body weight associated disutility and uncertainty surrounding the changes in HbA1c.

CONCLUSIONS

Lixisenatide may be considered an economically efficient therapy in combination with basal insulin in the Norwegian setting, due to cost savings, weight loss and associated gains in health-related quality of life.

Impact of an intensive lifestyle intervention on use and cost of medical services among overweight and obese adults with type 2 diabetes: the action for health in diabetes

OBJECTIVE

To assess the relative impact of an intensive lifestyle intervention (ILI) on use and costs of health care within the Look AHEAD trial.

RESEARCH DESIGN AND METHODS

A total of 5,121 overweight or obese adults with type 2 diabetes were randomly assigned to an ILI that promoted weight loss or to a comparison condition of diabetes support and education (DSE). Use and costs of health-care services were recorded across an average of 10 years.

RESULTS

ILI led to reductions in annual hospitalizations (11%, P = 0.004), hospital days (15%, P = 0.01), and number of medications (6%, P < 0.001), resulting in cost savings for hospitalization (10%, P = 0.04) and medication (7%, P < 0.001). ILI produced a mean relative per-person 10-year cost savings of $5,280 (95% CI 3,385-7,175); however, these were not evident among individuals with a history of cardiovascular disease.

CONCLUSIONS

Compared with DSE over 10 years, ILI participants had fewer hospitalizations, fewer medications, and lower health-care costs.

Tell me what you eat and I will tell you your sociotype: coping with diabesity

The term sociotype has been introduced to describe the dynamic relationship of an individual with his/her social environment throughout life. The sociotype is a conceptual framework to highlight, in addition to bio-medical pathways, the psycho-social and environmental factors necessary to understand responses to life stresses and patient self-management for chronic illness. The sociotype interacts with genotype expression through mate selection and metabolic programming, and with the phenotype to determine adaptation throughout life from birth to old age. Following on the work of Antonovsky, Engel, and McEwen, and others in the life and social sciences, the sociotype details and expands the many factors generally included in the environmental influences on a person's life identified here as the domains of health, relationships, and environment. Physiological mediators for sociotypic influences include: adrenal steroids and the sympathetic nervous system (allostatic load), and oxytocin (social neuroscience). The biological pathways are multiple through nutrition (essential dietary-derived amino- and fatty acids for neurotransmitter synthesis, caloric restriction, and diet-gene interactions), epigenesis, and metabolic programming. Nutrition influences growth and development, fertility and longevity, and also determines susceptibility to non-communicable diseases such as cardiovascular disease and cancer, and particularly diabetes and obesity, through in-utero effects, the development of intestinal flora (microbiome), and chronic stress. Thus the sociotype and nutrition are reciprocally related in both health and disease.

Biomarkers in diabetes: hemoglobin A1c, vascular and tissue markers

Biomarkers are conventionally defined as "biological molecules that represent health and disease states." They typically are measured in readily available body fluids (blood or urine), lie outside the causal pathway, are able to detect subclinical disease, and are used to monitor clinical and subclinical disease burden and response to treatments. Biomarkers can be "direct" endpoints of the disease itself, or "indirect" or surrogate endpoints. New technologies (such as metabolomics, proteomics, genomics) bring a wealth of opportunity to develop new biomarkers. Other new technologies enable the development of nonmolecular, functional, or biophysical tissue-based biomarkers. Diabetes mellitus is a complex disease affecting almost every tissue and organ system, with metabolic ramifications extending far beyond impaired glucose metabolism. Biomarkers may reflect the presence and severity of hyperglycemia (ie, diabetes itself) or the presence and severity of the vascular complications of diabetes. Illustrative examples are considered in this brief review. In blood, hemoglobin A1c (HbA1c) may be considered as a biomarker for the presence and severity of hyperglycemia, implying diabetes or prediabetes, or, over time, as a "biomarker for a risk factor," ie, hyperglycemia as a risk factor for diabetic retinopathy, nephropathy, and other vascular complications of diabetes. In tissues, glycation and oxidative stress resulting from hyperglycemia and dyslipidemia lead to widespread modification of biomolecules by advanced glycation end products (AGEs). Some of these altered species may serve as biomarkers, whereas others may lie in the causal pathway for vascular damage. New noninvasive technologies can detect tissue damage mediated by AGE formation: these include indirect measures such as pulse wave analysis (a marker of vascular dysfunction) and more direct markers such as skin autofluorescence (a marker of long-term accumulation of AGEs). In the future, we can be optimistic that new blood and tissue-based biomarkers will enable the detection, prevention, and treatment of diabetes and its complications long before overt disease develops.