Association of obesity with cardiorespiratory fitness and oxidative stress markers in apparently healthy adults with and without family history of type 2 diabetes mellitus

Introduction

Type 2 Diabetes Mellitus (T2DM) is primarily caused by a combination of defective insulin secretion by pancreatic β-cells and the inability of insulin-sensitive tissues to respond to insulin [1] . Insulin release and action must precisely meet metabolic demand; hence, the molecular mechanisms involved in the synthesis and release of insulin must be tightly regulated. Defects in any of these mechanisms can lead to pathogenesis of T2DM. According to the World Health Organization (WHO), diabetes mellitus is a chronic, metabolic disease characterised by elevated levels of blood glucose, leading over time to damage to the heart, vasculature, eyes, kidneys and nerves. Over 90% of diabetes mellitus cases are T2DM, marked by deficient insulin secretion by pancreatic islet β-cells, tissue insulin resistance (IR), and an inadequate compensatory insulin secretory response [2] . Patients with T2DM are mostly characterised by obesity or higher body fat percentage, distributed predominantly in the abdominal region. In this condition, adipose tissue promotes IR through various inflammatory mechanisms, including increased free fatty acid (FFA) release and adipokine deregulation. The main drivers of the T2DM epidemic are the global rise in obesity, sedentary lifestyles, high-caloric diets, and population ageing, which have quadrupled the incidence and prevalence of T2DM [3] . The organs involved in T2DM development include the pancreas (α-cells and β-cells), liver, skeletal muscle, kidneys, brain, small intestine, and adipose tissue [4] . Evolving data suggest that adipokine dysregulation, inflammation, and abnormalities in gut microbiota and immune function represent important pathophysiological factors [5] . T2DM risk factors include a complex combination of genetic, metabolic, and environmental factors. Although individual predisposition to T2DM due to non-modifiable risk factors (ethnicity and family history/genetic predisposition) has a strong genetic basis, evidence from epidemiological studies suggests that many cases can be prevented by improving modifiable risk factors such as obesity, low physical activity, and an unhealthy diet [6] . Globally, the incidence and prevalence of T2DM vary widely depending on ethnicity and geographical region [7,8,9] .Genetic predisposition plays an important part in the risk of developing T2DM. Over the past decade, several genome-wide association studies have demonstrated the complex polygenic nature of T2DM, with most identified loci increasing risk through effects on insulin secretion [10,11] . Cardiorespiratory fitness, a key physiological marker, is inversely associated with obesity and metabolic disorders. Given the established links between family history of T2DM, obesity, and oxidative stress, the present study aims to evaluate the association of obesity with cardiorespiratory fitness and oxidative stress markers in apparently healthy adults with and without a family history of T2DM.

Materials and Methods

This is a cross-sectional observational study conducted in the Department of Biochemistry, Sree Balaji Medical College and Hospital, Chennai, Tamil Nadu, from April 2018 to March 2019. The study was approved by the Institutional Ethics Committee of Sree Balaji Medical College and Hospital. All participants provided written informed consent prior to enrolment.

Inclusion Criteria

 Either gender, aged 18 to 60 years.  First-degree relatives of Type 2 Diabetes Mellitus patients (case group).  Age-and gender-matched apparently healthy adults with no family history of diabetes (control group, n = 45).

Exclusion Criteria

Morbid obesity, chronic alcoholism, chronic smoking, pregnancy, lactating women, kyphosis, scoliosis, use of medications preventing sub-maximal exercise, or regular engagement in physical activity, yoga, or biofeedback.

Sample Size

The sample size of N = 90 (45 per group) was calculated based on the expected effect size for group differences in body composition and oxidative stress parameters, with α = 0.05 and power = 80%.

Procedure

One day prior to recording, participants were instructed to obtain adequate sleep and abstain from caffeinated beverages, exercise, alcohol, and nicotine for 24 hours. After overnight fasting, participants reported to the Department of Cardiology in the morning. Anthropometric and basal characteristics (height, weight, body mass index [BMI], waist-hip ratio [WHR], body fat percentage, and visceral fat) were recorded after participants had emptied their bladders.

A fasting venous blood sample (5 mL) was collected from the median cubital vein using sodium fluoride tubes for biochemical analysis. Fasting blood glucose (FBS) was measured using a semi-automated analyser. Oxidative stress markers, specifically total antioxidant status (TAOS) and malondialdehyde (MDA), were measured by colorimetric methods. Analytical details including the specific instrument models and assay kit manufacturers are to be confirmed by the corresponding author for reproducibility. Cardiovascular parameters were recorded at rest: heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP), pulse pressure (PP = SBP-DBP), mean arterial pressure (MAP = DBP + PP/3), and rate pressure product (RPP = HR×SBP). Cardiorespiratory fitness was assessed using the Cooper 12minute run test. Participants were instructed to cover the maximum distance possible in 12 minutes on a standard running track. Estimated VO₂max (mL/kg/min) was derived using the Cooper formula: VO₂max = (distance in metres -504.9) / 44.73. Observations were analysed using an independent samples t-test with IBM SPSS Statistics, version 25.

Note: Lipid profile data (total cholesterol, LDL, HDL, and triglycerides) were collected in this study and will be reported in a subsequent publication.

Results

Table Table 1 shows the baseline and anthropometric parameters of controls and cases. There was no significant difference in age (p=0.400) or height (p=0.072) between groups, confirming adequate matching. Between controls and cases, significant differences were observed in weight (p<0.001), BMI (p<0.001), and WHR (p=0.004). Table 2 presents cardiovascular parameters. Heart rate (p<0.001), SBP (p<0.001), DBP (p<0.001), MAP (p<0.001), and RPP (p<0.001) were all significantly higher in cases compared to controls. Pulse pressure did not differ significantly between groups (p=0.106). Table 4 shows oxidative stress parameters. Between controls and cases, there was a significant difference in TAOS (p<0.001) and MDA (p<0.001), with cases exhibiting markedly lower antioxidant capacity and higher lipid peroxidation.

Discussion

The present study compared cardiovascular parameters, body composition, cardiorespiratory fitness, and oxidative stress between apparently healthy adults with and without a family history of T2DM. Key findings were that cases had significantly higher weight, BMI, WHR, body fat percentage, and visceral fat; elevated HR, SBP, DBP, MAP, and RPP; lower cardiorespiratory fitness (Cooper test distance and estimated VO₂max); higher FBS; lower TAOS; and higher MDA compared to controls. Pulse pressure did not differ significantly (p=0.106). These findings suggest early physiological and metabolic derangements in individuals genetically predisposed to T2DM, even before clinical disease onset. It is well established that cardiorespiratory fitness is inversely associated with impaired glucose tolerance and diabetes; however, fewer investigations have examined demographic and behavioural factors associated with cardiorespiratory fitness among adults at high genetic risk. This study demonstrated that, similar to findings in individuals with overt diabetes, individuals with a family history of T2DM and lower physical activity and higher BMI generally exhibited lower cardiorespiratory fitness. This is concerning in that not only may genetic predisposition increase risk for premature cardiovascular morbidity, [12] but low cardiorespiratory fitness is itself an independent predictor of mortality even after adjusting for comorbidities [13] . The findings showed that estimates of cardiorespiratory fitness were lower in those with positive family history, consistent with other studies examining diabetes-associated fitness decline [14] . Both measurement methods have inherent error; the heart rate extrapolation method carries error from the estimate of maximal heart rate (220-age). Jackson et al. [15] showed this formula can overestimate maximal heart rate by up to 22 beats per minute, particularly among hypertensive individuals. The non-exercise prediction used in the present study has been cross-validated in independent samples [16,17] . Regular physical activity participation is associated with higher cardiorespiratory fitness, though our findings did not demonstrate a link between self-reported exercise frequency and fitness, likely reflecting limitations of self-reported physical activity data. Future studies should use objective measures (e.g., accelerometry). Similar to findings in the general population, weight status was associated with cardiorespiratory fitness among adults at risk for T2DM. Overweight and obese individuals were estimated to have lower cardiorespiratory fitness than normal-weight adults, consistent with the established link between obesity and metabolic disease [18] . The mean estimated VO₂max for cases in the present study (34.29 mL/kg/min) falls in the 'below average' fitness category, indicating not only genetic risk from family history but also fitness-related risk for adverse health outcomes. Overall, findings suggest that apparently healthy adults with a family history of T2DM, particularly those who are overweight or obese, may be at increased risk for morbidity and mortality associated with low cardiorespiratory fitness and elevated oxidative stress. Lifestyle modification including regular physical activity is likely to be beneficial in this population [19,20,21] . When promoting physical activity, clinicians may consider tailored counselling approaches such as motivational interviewing and cognitive behavioural therapy, which have shown efficacy in at-risk populations [22] . Addressing physical activity barriers such as depression, weakness, and low outcome expectations may further improve adherence [23] .

Conclusion

This cross-sectional observational study demonstrates that apparently healthy adults with a positive family history of T2DM exhibit significantly higher adiposity, impaired cardiorespiratory fitness, elevated fasting blood glucose, and greater oxidative stress compared to individuals without such family history. These findings indicate that familial genetic predisposition to T2DM may manifest as early physiological and metabolic alterations, including reduced TAOS and elevated MDA, even in the absence of clinical disease. Future longitudinal and interventional studies are warranted to evaluate whether targeted physical activity and lifestyle modification programmes can attenuate these risk markers in this high-risk population.

References

1. Park K. Park's textbook of preventive and social medicine. 22nd ed. Jabalpur: M/S Banarasidas Bhanot Publishers; 2013. p. 362-367.
2. Vlassara H, Uribarri J. Advanced glycation end products (AGE) and diabetes: cause, effect, or both? Curr Diab Rep. 2014;14(1):453.
3. Montezano AC, Touyz RM. Reactive oxygen species and endothelial function: role of nitric oxide synthase uncoupling and Nox family nicotinamide adenine dinucleotide phosphate oxidases. Basic Clin Pharmacol Toxicol. 2012;110(1):87-94.
4. Giorgino F, Leonardini A, Laviola L. Cardiovascular disease and glycemic control in type 2 diabetes: now that the dust is settling from large clinical trials. Ann N Y Acad Sci. 2013;1281(1):36-50.
5. Esser N, Legrand-Poels S, Piette J, Scheen AJ, Paquot N. Inflammation as a link between obesity, metabolic syndrome and type 2 diabetes. Diabetes Res Clin Pract. 2014;105(2):141-150.
6. Alahmadi MA, Hills AP, King NA, Byrne NM. Exercise intensity influences non-exercise activity thermogenesis in overweight and obese adults. Med Sci Sports Exerc. 2011;43(4):624-631.
7. Banerjee S, Bhattacharya S. Oxidative stress parameters and antioxidant status in middle aged and elderly subjects: an age-related comparative study. Int J Bioassays. 2014;3(7):3131-3136.
8. Kunwar A, Priyadarsini KI. Free radicals, oxidative stress and importance of antioxidants in human health. J Med Allied Sci. 2011;1(2):53-60.
9. Giacco F, Brownlee M. Oxidative stress and diabetic complications. Circ Res. 2010;107(9):1058-1070.
10. Ramadan R, Dhawan SS, Syed H, Pohlel FK, Binongo JN, Ghazzal ZB, et al. Effects of clopidogrel therapy on oxidative stress, inflammation, vascular function and progenitor cells in stable coronary artery disease. J Cardiovasc Pharmacol. 2014;63(5):369-374.
11. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2010;33 Suppl 1-S69.
12. Totsikas C, Rohm J, Kantartzis K, Thamer C, Rittig K, Machann J, et al. Cardiorespiratory fitness determines the reduction in blood pressure and insulin resistance during lifestyle intervention. J Hypertens. 2011;29(6):1220-1227.
13. Sieverdes JC, Sui X, Lee DC, Church TS, McClain A, Hand GA, et al. Physical activity, cardiorespiratory fitness and the incidence of type 2 diabetes in a prospective study of men. Br J Sports Med. 2010;44(4):238-244.
14. Sawada SS, Lee IM, Naito H, Tsukamoto K, Muto T, Blair SN. Long-term trends in cardiorespiratory fitness and the incidence of type 2 diabetes. Diabetes Care. 2010;33(6):1353-1357.
15. Jackson AS, Blair SN, Mahar MT, Wier LT, Ross RM, Stuteville JE. Prediction of functional aerobic capacity without exercise testing. Med Sci Sports Exerc. 1990;22(6):863-870.
16. Lau C, Kuk F. Enough is enough: a primer on power analysis in study designs. Hearing J. 2011;64(4):30-39.
17. Jakicic JM, Jaramillo SA, Balasubramanyam A, Bancroft B, Curtis JM, Mathews A, et al. Effect of a lifestyle intervention on change in cardiorespiratory fitness in adults with type 2 diabetes: results from the Look AHEAD Study. Int J Obes (Lond). 2009;33(3):305-316.
18. Durdin R, McAuley E. Construct validation of a nonexercise measure of cardiorespiratory fitness in older adults. BMC Public Health. 2010;10:59. International Journal of Advanced Biochemistry Research http://www.biochemjournal.com
19. Wang CY, Haskell WL, Farrell SW, LaMonte MJ, Blair SN, Curtin LR, et al. Cardiorespiratory fitness levels among US adults 20-49 years of age: findings from the 1999-2004 National Health and Nutrition Examination Survey. Am J Epidemiol. 2010;171(4):426-435.
20. Flegal KM, Carroll MD, Ogden CL, Curtin LR. Prevalence and trends in obesity among US adults, 1999-2008. JAMA. 2010;303(3):235-241.
21. Loprinzi PD, Cardinal BJ. Association between biologic outcomes and objectively measured physical activity accumulated in ≥10-minute bouts and <10minute bouts. Am J Health Promot. 2013;27(3):143151.
22. Zierath JR. Invited review: exercise training-induced changes in insulin signaling in skeletal muscle. J Appl Physiol. 2002;93(2):773-781.
23. Buse JB, Ginsberg HN, Bakris GL, Clark NG, Costa F, Eckel R, et al. Primary prevention of cardiovascular diseases in people with diabetes mellitus: a scientific statement from the American Heart Association and the American Diabetes Association. Diabetes Care. 2007;30(1):162-172.