Empowering Diabetics: Advancements in Smartphone-Based Food Classification, Volume Measurement, and Nutritional Estimation.

Diabetes has emerged as a worldwide health crisis, affecting approximately 537 million adults. Maintaining blood glucose requires careful observation of diet, physical activity, and adherence to medications if necessary. Diet monitoring historically involves keeping food diaries; however, this process can be labor-intensive, and recollection of food items may introduce errors. Automated technologies such as food image recognition systems (FIRS) can make use of computer vision and mobile cameras to reduce the burden of keeping diaries and improve diet tracking. These tools provide various levels of diet analysis, and some offer further suggestions for improving the nutritional quality of meals. The current study is a systematic review of mobile computer vision-based approaches for food classification, volume estimation, and nutrient estimation. Relevant articles published over the last two decades are evaluated, and both future directions and issues related to FIRS are explored.

Twenty year fitness trends in young adults and incidence of prediabetes and diabetes: the CARDIA study.

AIMS/HYPOTHESIS: The prospective association between cardiorespiratory fitness (CRF) measured in young adulthood and middle age on development of prediabetes, defined as impaired fasting glucose and/or impaired glucose tolerance, or diabetes by middle age remains unknown. We hypothesised that higher fitness levels would be associated with reduced risk for developing incident prediabetes/diabetes by middle age. METHODS: Participants were from the Coronary Artery Risk Development in Young Adults (CARDIA) study who were free from prediabetes/diabetes at baseline (year 0 [Y0]: 1985-1986). CRF was quantified by treadmill duration (converted to metabolic equivalents [METs]) at Y0, Y7 and Y20 and prediabetes/diabetes status was assessed at Y0, Y7, Y10, Y15, Y20 and Y25. We use an extended Cox model with CRF as the primary time-varying exposure. BMI was included as a time-varying covariate. The outcome was development of either prediabetes or diabetes after Y0. Model 1 included age, race, sex, field centre, CRF and BMI. Model 2 additionally included baseline (Y0) smoking, energy intake, alcohol intake, education, systolic BP, BP medication use and lipid profile. RESULTS: Higher fitness was associated with lower risk for developing incident prediabetes/diabetes (difference of 1 MET: HR 0.99898 [95% CI 0.99861, 0.99940], p < 0.01), which persisted (difference of 1 MET: HR 0.99872 [95% CI 0.99840, 0.99904], p < 0.01] when adjusting for covariates. CONCLUSIONS/INTERPRETATION: Examining participants who had fitness measured from young adulthood to middle age, we found that fitness was associated with lower risk for developing prediabetes/diabetes, even when adjusting for BMI over this time period. These findings emphasise the importance of fitness in reducing the health burden of prediabetes and diabetes.

Cumulative BMI and incident prediabetes over 30 years of follow-up: The CARDIA study.

OBJECTIVE: This study examined how cumulative BMI (cBMI) is associated with incident prediabetes in a biracial observational cohort study followed from young adulthood to middle age. METHODS: Black and White men and women (n = 4190) from the Coronary Artery Risk Development in Young Adults (CARDIA) study, ages 18 to 30 years in 1985 to 1986 and free of prediabetes or diabetes at baseline, were followed for 30 years. Cox regression was used to determine how cBMI was associated with incident prediabetes after controlling for traditional cardiovascular risk factors. RESULTS: Over 30 years of follow-up, 46.2% of the sample developed prediabetes. Mean cBMI was 801.4 BMI-years for those with prediabetes and 658.3 BMI-years for those without (p < 0.0001). After multivariable adjustment, the hazard rate ratio for the highest cBMI quartile was 2.064 (95% CI: 1.793-2.377) relative to the lowest quartile. The second and third quartiles did not differ from the first quartile, consistent with a nonlinear trend. CONCLUSIONS: The cumulative burden of higher weight and longer duration was associated with incident prediabetes, but this association was statistically significant only after a higher threshold was reached. Strategies for prevention of prediabetes in middle age may focus on avoiding overweight in young adulthood to limit duration.

Development of a Noninvasive Blood Glucose Monitoring System Prototype: Pilot Study.

BACKGROUND: Diabetes mellitus is a severe disease characterized by high blood glucose levels resulting from dysregulation of the hormone insulin. Diabetes is managed through physical activity and dietary modification and requires careful monitoring of blood glucose concentration. Blood glucose concentration is typically monitored throughout the day by analyzing a sample of blood drawn from a finger prick using a commercially available glucometer. However, this process is invasive and painful, and leads to a risk of infection. Therefore, there is an urgent need for noninvasive, inexpensive, novel platforms for continuous blood sugar monitoring. OBJECTIVE: Our study aimed to describe a pilot test to test the accuracy of a noninvasive glucose monitoring prototype that uses laser technology based on near-infrared spectroscopy. METHODS: Our system is based on Raspberry Pi, a portable camera (Raspberry Pi camera), and a visible light laser. The Raspberry Pi camera captures a set of images when a visible light laser passes through skin tissue. The glucose concentration is estimated by an artificial neural network model using the absorption and scattering of light in the skin tissue. This prototype was developed using TensorFlow, Keras, and Python code. A pilot study was run with 8 volunteers that used the prototype on their fingers and ears. Blood glucose values obtained by the prototype were compared with commercially available glucometers to estimate accuracy. RESULTS: When using images from the finger, the accuracy of the prototype is 79%. Taken from the ear, the accuracy is attenuated to 62%. Though the current data set is limited, these results are encouraging. However, three main limitations need to be addressed in future studies of the prototype: (1) increase the size of the database to improve the robustness of the artificial neural network model; (2) analyze the impact of external factors such as skin color, skin thickness, and ambient temperature in the current prototype; and (3) improve the prototype enclosure to make it suitable for easy finger and ear placement. CONCLUSIONS: Our pilot study demonstrates that blood glucose concentration can be estimated using a small hardware prototype that uses infrared images of human tissue. Although more studies need to be conducted to overcome limitations, this pilot study shows that an affordable device can be used to avoid the use of blood and multiple finger pricks for blood glucose monitoring in the diabetic population.

Prepregnancy Protein Source and BCAA Intake Are Associated with Gestational Diabetes Mellitus in the CARDIA Study.

Diet quality and protein source are associated with type 2 diabetes, however relationships with GDM are less clear. This study aimed to determine whether prepregnancy diet quality and protein source are associated with gestational diabetes mellitus (GDM). Participants were 1314 Black and White women without diabetes, who had at least one birth during 25 years of follow-up in the Coronary Artery Risk Development in Young Adults (CARDIA) cohort study. The CARDIA A Priori Diet Quality Score (APDQS) was assessed in the overall cohort at enrollment and again at Year 7. Protein source and branched-chain amino acid (BCAA) intake were assessed only at the Year 7 exam (n = 565). Logistic regression analysis was used to determine associations between prepregnancy dietary factors and GDM. Women who developed GDM (n = 161) were more likely to have prepregnancy obesity and a family history of diabetes (p < 0.05). GDM was not associated with prepregnancy diet quality at enrollment (Year 0) (odds ratio [OR]: 1.01; 95% confidence interval [CI] 0.99, 1.02) or Year 7 (odds ratio [OR]: 0.97; 95% confidence interval [CI] 0.94, 1.00) in an adjusted model. Conversely, BCAA intake (OR:1.59, 95% CI 1.03, 2.43) and animal protein intake (OR: 1.06, 95% CI 1.02, 1.10) as a proportion of total protein intake, were associated with increased odds of GDM, while proportion of plant protein was associated with decreased odds of GDM (OR: 0.95, 95% CI 0.91, 0.99). In conclusion, GDM is strongly associated with source of prepregnancy dietary protein intake but not APDQS in the CARDIA study.

Changes in Cardiometabolic Risk Factors Before and After Gestational Diabetes: A Prospective Life-Course Analysis in CARDIA Women.

OBJECTIVE: This study hypothesized that both preconception and postchildbearing patterns of cardiometabolic risk factors may be different for women with gestational diabetes mellitus (GDM) compared with women without GDM. METHODS: Among 1,302 (51% black) women in the Coronary Artery Risk Development in Young Adults (CARDIA) study with births and followed for 30 years, this study evaluated changes in cardiometabolic factors (BMI, waist circumference [WC], lipids, blood pressure) during prechildbearing (prior to the first postbaseline birth) and postchildbearing periods (after the last birth) by GDM status using piecewise linear mixed models adjusted for sociodemographics, parity, and time-varying covariates. RESULTS: Compared with women who did not develop GDM, weight and WC increases in women who developed GDM (n = 152, 12%) were faster (BMI difference: +0.12 kg/m2 /y, P = 0.04; WC difference: +0.28 cm/y, P = 0.04) during the prechildbearing period, accounting for covariates. This translated to an average of 1.3 kg of excess weight gain across 4 years among women with subsequent GDM versus non-GDM births. In contrast, slopes after childbearing did not differ by GDM status, nor were there other cardiometabolic differences. CONCLUSIONS: Women with GDM exhibited an increasing prepregnancy pattern of weight gain and central adiposity. Absolute postchildbearing weight was also higher in GDM-affected women, but the slope of gain after GDM was not.

Prepregnancy Fitness and Risk of Gestational Diabetes: A Longitudinal Analysis.

PURPOSE: This study aimed to assess the associations of prepregnancy cardiorespiratory fitness, moderate- to vigorous-intensity physical activity (MVPA), and time spent watching television with subsequent development of gestational diabetes mellitus (GDM). METHODS: Participants were 1333 women enrolled in the Coronary Artery Risk Development in Young Adults study who did not have diabetes either at baseline (1985-86) or before births occurring after baseline. Baseline fitness was estimated using a graded symptom-limited maximal exercise treadmill test and expressed in MET units. Baseline MVPA (exercise units per day) was measured using the Coronary Artery Risk Development in Young Adults physical activity history questionnaire, and television viewing (h·d) was assessed by self-report in 1990-1991. Logistic regression analysis was used to derive odds ratios and 95% confidence intervals, adjusting for time from baseline to delivery and baseline study center, age, race, education, parity, family history of diabetes, smoking, alcohol, saturated fat intake, waist circumference, homeostasis model assessment of insulin resistance, and HDL cholesterol. RESULTS: Over 25 yr of follow-up, 164 women developed GDM. The odds of developing GDM were 21% lower for each 1 SD increment in baseline level of fitness (2.3 METs, odds ratio = 0.79, 95% confidence interval = 0.65-0.96). Prepregnancy MVPA and television viewing were not statistically associated with the development of GDM. CONCLUSION: Study findings indicate that objectively assessed prepregnancy fitness, but not self-reported MVPA or television time, is associated with GDM. Clinicians should counsel women on the benefits of improving fitness in the preconception period, particularly among women at greater risk for GDM.

F2-Isoprostanes Reflect Oxidative Stress Correlated With Lean Mass and Bone Density but Not Insulin Resistance.

CONTEXT: F2-isoprostanes (F2-isoPs) are biomarkers for oxidative stress in humans and have been shown to be elevated in obesity, cardiovascular disease, and diabetes. Therefore, F2-isoPs are often implicated in oxidative stress contributing to insulin resistance, although this has not been rigorously examined. OBJECTIVE: To determine whether urinary F2-isoPs are predictive of insulin sensitivity and other clinical metabolic parameters. PARTICIPANTS: Sedentary, weight-stable, nondiabetic adults equilibrated on a standard isocaloric diet. MAIN OUTCOME MEASURES: Insulin sensitivity via hyperinsulinemic-euglycemic clamp, urinary F2-isoPs by gas chromatography-mass spectrometry, and body composition by dual-energy x-ray absorptiometry. RESULTS: No correlation was found between 15-F2t-IsoP nor its major metabolite, 2,3-dinor-5,6-dihydro-15-F2t-IsoP, with insulin sensitivity, even after adjusting for age, race, sex, BMI, and smoking status. 15-F2t-IsoP was also not associated with body fat. However, there was a strong negative correlation between 15-F2t-IsoP and lean body mass (LBM; r = -0.46, P = 0.0001), bone mineral content (BMC; r = -0.58, P < 0.0001), bone mineral density (BMD; r = -0.65, P < 0.0001), and skeletal muscle protein 4-hydroxynonenal (4-HNE; r = -0.54, P = 0.0239), another marker of oxidative stress. 15-F2t-IsoP was also positively associated with circulating triglycerides and total cholesterol, and increased as a function of age. CONCLUSIONS: Urinary 15-F2t-IsoP and its major metabolite are not associated with insulin sensitivity, suggesting the lipid peroxidation process that produces F2-isoPs does not reflect oxidative stress reactions operative in insulin resistance. However, urinary F2-isoPs were negatively correlated with LBM, BMC, BMD, and muscle 4-HNE. Because lean and bone mass decline as a function of biological aging, F2-isoPs may reflect the oxidative stress operative in the aging process.

Nonalcoholic fatty liver disease and measures of early brain health in middle-aged adults: The CARDIA study.

OBJECTIVE: To assess associations between nonalcoholic fatty liver disease (NAFLD) and measures of brain health in a population-based sample of adults. METHODS: Participants from the CARDIA study (Y25 exam; age 43-55 years) with concurrent computed tomography quantification of liver fat, visceral adipose tissue (VAT), and brain magnetic resonance (MR) images were included (n = 505). NAFLD was identified after exclusion of other causes of liver fat. Total tissue volume (TTV) and gray matter cerebral blood flow (GM-CBF) were estimated using 3T brain MR images. RESULTS: NAFLD prevalence was 18%. NAFLD was associated with lower TTV and GM-CBF after adjusting for intracranial volume, demographics, and health behaviors (P < 0.04 for all). In models with additional adjustment for cardiovascular risk factors, the association of NAFLD with GM-CBF remained significant (P = 0.04) but was attenuated after adjustment for VAT (P = 0.06) and eliminated with BMI (P = 0.20). NAFLD was not associated with TTV after adjustment for cardiovascular risk factors (P = 0.10) or additional adjustment for VAT (P = 0.14) or BMI (P = 0.05). CONCLUSIONS: NAFLD is negatively associated with early brain health as assessed by MR measures of structure (TTV) and perfusion (GM-CBF). BMI and VAT attenuated this relationship, providing insight into the potential metabolic role of liver fat in brain health and disease.

Association of Mediterranean diet and cardiorespiratory fitness with the development of pre-diabetes and diabetes: the Coronary Artery Risk Development in Young Adults (CARDIA) study.

OBJECTIVE: To better understand the association between a modified Mediterranean diet pattern in young adulthood, cardiorespiratory fitness in young adulthood, and the odds of developing pre-diabetes or diabetes by middle age. RESEARCH DESIGN AND METHODS: Participants from the Coronary Artery Risk Development in Young Adults (CARDIA) study who did not have pre-diabetes or diabetes at baseline (year 0 (Y0), ages 18-30) and who had data available at the Y0 and year 25 (Y25) visits were included in this analysis (n=3358). Polytomous logistic regression models were used to assess the association between baseline dietary intake and fitness data and odds of pre-diabetes or diabetes by middle age (Y25, ages 43-55). RESULTS: At the Y25 visit, 1319 participants (39%) had pre-diabetes and 393 (12%) had diabetes. Higher baseline fitness was associated with lower odds of pre-diabetes and of diabetes at Y25. After adjustment for covariates, each SD increment in treadmill duration (181 s) was associated with lower odds for pre-diabetes (OR 0.85, 95% CI 0.75 to 0.95, p=0.005) and for diabetes (OR 0.71, 95% CI 0.60 to 0.85, p=0.0002) when compared to normal glycemia. A modified Mediterranean diet pattern was not associated with either pre-diabetes or diabetes. No interaction between cardiorespiratory fitness and dietary intake was observed, but baseline fitness remained independently associated with incident pre-diabetes and diabetes following adjustment for diet. CONCLUSIONS: Higher cardiorespiratory fitness in young adulthood, but not a modified Mediterranean diet pattern, is associated with lower odds of pre-diabetes and of diabetes in middle age. TRIAL REGISTRATION NUMBER: NCT00005130.

BMI, RQ, diabetes, and sex affect the relationships between amino acids and clamp measures of insulin action in humans.

Previous studies have used indirect measures of insulin sensitivity to link circulating amino acids with insulin resistance and identify potential biomarkers of diabetes risk. Using direct measures (i.e., hyperinsulinemic-euglycemic clamps), we examined the relationships between the metabolomic amino acid profile and insulin action (i.e., glucose disposal rate [GDR]). Relationships between GDR and serum amino acids were determined among insulin-sensitive, insulin-resistant, and type 2 diabetic (T2DM) individuals. In all subjects, glycine (Gly) had the strongest correlation with GDR (positive association), followed by leucine/isoleucine (Leu/Ile) (negative association). These relationships were dramatically influenced by BMI, the resting respiratory quotient (RQ), T2DM, and sex. Gly had a strong positive correlation with GDR regardless of BMI, RQ, or sex but became nonsignificant in T2DM. In contrast, Leu/Ile was negatively associated with GDR in nonobese and T2DM subjects. Increased resting fat metabolism (i.e., low RQ) and obesity were observed to independently promote and negate the association between Leu/Ile and insulin resistance, respectively. Additionally, the relationship between Leu/Ile and GDR was magnified in T2DM males. Future studies are needed to determine whether Gly has a mechanistic role in glucose homeostasis and whether dietary Gly enrichment may be an effective intervention in diseases characterized by insulin resistance.

Limitations in the use of indices using glucose and insulin levels to predict insulin sensitivity: impact of race and gender and superiority of the indices derived from oral glucose tolerance test in African Americans.

OBJECTIVE To examine the utility of commonly used insulin sensitivity indices in nondiabetic European Americans (EAs) and African Americans (AAs). RESEARCH DESIGN AND METHODS Two-hundred forty nondiabetic participants were studied. Euglycemic-hyperinsulinemic clamp was the gold standard approach to assess glucose disposal rates (GDR) normalized by lean body mass. The homeostatic model assessment for insulin resistance (HOMA-IR) and the quantitative insulin sensitivity check index (QUICKI) were calculated from fasting plasma glucose and insulin (FIL). Oral glucose tolerance test (OGTT) was performed to determine Matsuda index, the simple index assessing insulin sensitivity (SI(is)OGTT), Avignon index, and Stomvoll index. Relationships among these indices with GDR were analyzed by multiple regression. RESULTS GDR values were similar in EA and AA subgroups; even so, AA exhibited higher FIL and were insulin-resistant compared with EA, as assessed by HOMA-IR, QUICKI, Matsuda index, SI(is)OGTT, Avignon index, and Stumvoll index. In the overall study population, GDR was significantly correlated with all studied insulin sensitivity indices (/r/ = 0.381-0.513); however, these indices were not superior to FIL in predicting GDR. Race and gender affected the strength of this relationship. In AA males, FIL and HOMA-IR were not correlated with GDR. In contrast, Matsuda index and SI(is)OGTT were significantly correlated with GDR in AA males, and Matsuda index was superior to HOMA-IR and QUICKI in AAs overall. CONCLUSIONS Insulin sensitivity indices based on glucose and insulin levels should be used cautiously as measures of peripheral insulin sensitivity when comparing mixed gender and mixed race populations. Matsuda index and SI(is)OGTT are reliable in studies that include AA males.

Skeletal muscle lipid peroxidation and insulin resistance in humans.

OBJECTIVE: The relationships among skeletal muscle lipid peroxidation, intramyocellular lipid content (IMCL), and insulin sensitivity were evaluated in nine insulin-sensitive (IS), 13 insulin-resistant (IR), and 10 adults with type 2 diabetes (T2DM). DESIGN: Insulin sensitivity was assessed by hyperinsulinemic-euglycemic clamp [glucose disposal rate (GDR)]. Lipid peroxidation was assessed by 4-hydroxynonenal (HNE)-protein adducts and general oxidative stress by protein carbonyl content. All patients were sedentary. RESULTS: Protein-HNE adducts were elevated 1.6-fold in T2DM compared with IS adults, whereas IR showed intermediate levels of HNE-modified proteins. Protein-HNE adducts correlated with GDR, waist circumference, and body mass index. IMCL was increased by 4.0- and 1.9-fold in T2DM and IR patients, respectively, compared with IS, and was correlated with GDR and waist circumference but not BMI. Protein carbonyls were not different among groups and did not correlate with any of the measured variables. Correlations were detected between IMCL and protein-HNE. CONCLUSION: Our data show for the first time that skeletal muscle protein-HNE adducts are related to the severity of insulin resistance in sedentary adults. These results suggest that muscle lipid peroxidation could be involved in the development of insulin resistance.

Intramyocellular lipid and insulin resistance: differential relationships in European and African Americans.

Insulin resistance has been associated with the accumulation of fat within skeletal muscle fibers as intramyocellular lipid (IMCL). Here, we have examined in a cross-sectional study the interrelationships among IMCL, insulin sensitivity, and adiposity in European Americans (EAs) and African Americans (AAs). In 43 EA and 43 AA subjects, we measured soleus IMCL content with proton-magnetic resonance spectroscopy, insulin sensitivity with hyperinsulinemic-euglycemic clamp, and body composition with dual-energy X-ray absorptiometry. The AA and EA subgroups had similar IMCL content, insulin sensitivity, and percent fat, but only in EA was IMCL correlated with insulin sensitivity (r = -0.47, P < 0.01), BMI (r = 0.56, P < 0.01), percent fat (r = 0.35, P < 0.05), trunk fat (r = 0.47, P < 0.01), leg fat (r = 0.40, P < 0.05), and waist and hip circumferences (r = 0.54 and 0.55, respectively, P < 0.01). In a multiple regression model including IMCL, race, and a race by IMCL interaction, the interaction was found to be a significant predictor (t = 1.69, DF = 1, P = 0.0422). IMCL is related to insulin sensitivity and adiposity in EA but not in AA, suggesting that IMCL may not function as a pathophysiological factor in individuals of African descent. These results highlight ethnic differences in the determinants of insulin sensitivity and in the pathogenesis of the metabolic syndrome trait cluster.