https://imcjms.com Ibrahim Medical College Journal of Medical Science https://imcjms.com/registration/journal_full_text/52 Tue, 02 Aug 2016 11:07:45 +0000 The study was undertaken to estimate the risk factors age, gender, race, obesity (BMI), glycemic status (prediabetes, diabetes), exercise and psychosocial factors (sleep, sadness) related to coronary artery disease (CAD). The data set for this study is the National Health Interview Survey (NHIS), which is a large scale, cross sectional, voluntary, household interview survey maintaining data on health status, health care access and progress towards achieving the national health objectives in the USA. A total of 26,965 (male/female =55.8/ 44.2%) subjects were included in the study. Of them, 79.9% were less than 65 years of age. Regarding obesity, overweight, obese and morbid obese were 34.8, 17.3 and 11.0%, respectively. Sadness of any degree was reported in 28%. Sleep duration was found <5h/d in 8.7% and > 9h/d in 9.7%. Heart disease was reported in 4.9%. About 10% were reported to have diabetes and 4.1% prediabetes. 40% of the respondents’ maintained exercise once per week and only 12.8% maintained 10 or more times per week. Logistic regression estimated that compared with the non-diabetics, the subjects with prediabetes (OR 3.27, 95% CI, 2.32-4.59) and diabetes (OR 6.44 95% CI, 5.21-7.96) had excess risk of CAD, more significant in the younger subjects (<65y) than in the older (>65y). The risk of CAD was found significant in both prediabetes (OR 2.47, 95% CI, 1.44-4.23) and diabetes (OR 3.03, 95% CI, 2.16-4.24) as compared with non-diabetic group who slept >9h a day. The subjects with prediabetes or diabetes had excess risk for CAD compared with the non-diabetic subjects, which was more marked in the younger people. Again, compared with the non-diabetic people, the subjects with prediabetes or diabetes, having less sleep or excess sleep, had excess risk for CAD. Further study may confirm our findings. Introduction An increase in blood glucose may result in prediabetes and diabetes. According to the American Diabetic Association, prediabetes is a stage where the blood glucose level is higher than normal but not high enough to be diagnosed as diabetes and include impaired fasting glucose (IFG) and impaired glucose tolerance (IGT).6 It has been estimated that the global diabetes prevalence among adults over 19 years would be 6.4%, affecting 285 million adults in 2010, and might increase to 7.7% and 439 million adults by 2030. Between 2010 and 2030, there will be a 69% increase in numbers of adults with diabetes in developing countries and a 20% increase in developed countries.7 The increase in the incidence of prediabetes, diabetes and heart disease is increasing in the same fashion and same distribution.8 There are many known modifiable (eg. smoking, obesity, physical inactivity, hypertension, hyperglycemia, dyslipidemia) and non-modifiable (e.g. ageing, heredity / ethnicity) risk factors for developing atherosclerotic heart disease.8,9 Younger aged people with diabetes were found to have enhanced atherogenesis than their non-diabetic younger counterparts.10 Psychosocial stress, sleep disorders, mood disorders have also been found to have detrimental effect on coronary artery disease (CAD).11-14 This study aimed to measure the risk factors for CAD like age, gender, race, obesity (BMI), glycemic status (prediabetes, diabetes), exercise and psychosocial factors (sleep, sadness). Additionally, habit of smoking and excess sugar intake was also investigated as risk factor. Materials and Methods The NHIS data set of 2010 was used in our study.1 The inclusion criteria included all the adults of age 18 or more who were in any of the four racial groups as Hispanics, non-Hispanic White, non-Hispanic Blacks and non-Hispanic Asians. The exclusion criteria included those who could not be classified in either of the four race groups and who were less than 18 years of age. We initially merged the dataset for adult person and family questions from core questionnaire. The merged data set had 27,157 observations from which the non-Hispanic and all other racial groups were excluded (n=192) resulting 26,965 observations. Taking CAD as an outcome variable we included age, race, gender, race, obesity (BMI), exercise, and habit of smoking and added sugar consumption as the other risk variables (covariates). For a crude assessment of psychosocial risks sadness and sleep status were included as other covariates. Education was included as a surrogate social class.   A description of the baseline characteristic of the study population is provided in Table 1. The total sample size for the study was 26,965, of which 79.9% were less than 65 years of age with an average age of 47.8 years, with a slight female predominance (55.8% vs. 44.2% male) and 57.3% were non-Hispanic White. Regarding obesity, overweight, obese and morbid obese were 34.8%, 17.3% and 11.0%, respectively. Sadness of any degree was reported in 28%. Sleep duration was found lower than 5h/d in 8.7% and higher than 9h/d in 9.7%. Heart disease was reported in 4.9%. About 10% were reported to have diabetes and 4.1% prediabetes. 40% of the respondents used to maintain exercise for less than 1 time per week and only 12.8% maintained 10 or more times per week.Table-1. Study characteristics, National Health Interview Survey, 2010(1) (n=26,965) The measurement of association of risk variables with CAD are shown in Table 2. Compared with the younger subjects the elderly people had more risk (OR, 6.4; 95% CI, 5.7-7.2). Compared with the women the men had higher risk (OR, 1.7; 95% CI, 1.5-1.9). For other categorical variables, the risks of CAD were found significantly increasing with increasing obesity (BMI), hyperglycemia and sadness, and with decreasing exercise (Table 2). As regards race, compared with other groups, non-Hispanic whites had excess risk. Taking sleep duration of 6–8 h/d as normal and reference category, both lower (<5h/d) and higher (>9h/d) duration of sleep had more risk. An association was also found with smoking. Education level, marital status and added sugar intake were found to have no significant effect on CAD. Table-2. Study characteristics by Coronary Artery Disease (CAD), National Health Interview Survey, 2010(1) The unadjusted logistic regression model for unweighted data (Table 3) showed a significant positive association of CAD with prediabetes (OR 2.97, 95% CI, 2.39- 3.69) and with diabetes (OR 5.81, 95% CI, 5.13- 6.57). When adjusted for the possible confounders, those with prediabetes were 2 times more likely and those with diabetes were 3.2 times more likely to have coronary artery disease compared to non diabetics. When weighted data was used, although the adjusted association remained significant but there was a slight increase in odds ratio and narrowing of the confidence interval possibly because the data was weighted to a larger population. We need to use special statistical techniques to correct the confidence interval and standard error which is beyond the scope of this study. As the association more or less remained similar, so we would be using unweighted data for further analysis. Table-3. Crude and adjusted Odds Ratios for the Association between Diabetes and Prediabetes with Coronary Artery Disease(1) The risk of CAD related to prediabetes and diabetes according to age-groups and sleep duration was shown in Table 4. The analyses included “no diabetes” as a reference category, and adjusted for gender, race, sadness status, BMI, smoking status, education level, exercise status, added sugar consumption and marital status. Compared with the subjects having no diabetes, the subjects with prediabetes (OR 3.27, 95% CI, 2.32-4.59) and diabetes (OR 6.44, 95% CI, 5.21-7.96) were proved to have excess risk of CAD, which were strongly significant in the relatively younger subjects (<65y); whereas, for the elderly subjects (>65y), the prediabetes group showed no significant risk though it was somehow significant for the diabetes group. The subjects having diabetes and used to sleep <5h a day had significant risk for CAD as compared with the non-diabetic subjects having same duration of sleep. The risk of CAD was found significant in both prediabetes (OR 2.47, 95% CI, 1.44-4.23) and diabetes (OR 3.03, 95% CI, 2.16-4.24) as compared with non-diabetic group having sleep >9h a day.Table-4. Effect of Prediabetes and Diabetes on CAD by Age group and sleep abnormalities(1)   The study investigated some known risk factors (age, sex, race, obesity, diabetes, exercise and smoking) related to coronary artery disease (CAD). Other possible risk factors like mood disorders (sadness), altered sleep habits (lack or excess) and social status (education) were also estimated to relate CAD. As Stern pointed out that diabetes and cardiovascular diseases are very much interrelated,3 it is important to determine the quantity of association between diabetes and CAD. Thus, this study addressed important issues in quantifying some risk factors related to CAD. Altered sleep habits, either less (<5h/d) or excess (>9h/d), were found to have significant risk for developing CAD. This finding is important because either extreme of sleep abnormalities predict CAD. Other investigators also observed similar association of sleep abnormalities with hypertension, diabetes and CAD.12-14 So, our findings also indicate the importance of early detection and intervention of sleep habit changes. Further studies may be undertaken to relate sleep with CAD. The cross sectional nature of the dataset limits the study to measure association only and not temporality and causality. The self reporting of diabetes status and heart disease might provide erroneous information and result in misclassification and recall bias. The sensitivity and specificity of the data could have been increased if we had medical and laboratory report which is one of the many drawbacks of the data set. We could not take into consideration income, occupational status, stress factor, use of diabetic medications, and duration of diabetes either due to unavailability of variable or large number of missing data.   Hyperglycemia of any grade – mild, moderate or severe whether prediabetes or diabetes was proved to have significant risk for CAD. The diabetic subjects aged less than 65 years were more prone to develop CAD than their non-diabetic counterparts. Again, compared with the non-diabetic people, the subjects with prediabetes or diabetes, having less sleep or excess sleep, had excess risk for CAD. Further study may confirm our findings. Acknowledgment    1.   Schiller JS, Lucas JW, Ward BW, Peregoy JA. Summary health statistics for U.S. adults: National Health Interview Survey, 2010. National Center for Health Statistics. Vital Health Stat 2012; 10(252): 1-207. 3.   Stern M. Diabetes and cardiovascular disease. The “common soil” hypothesis. Diabetes1995; 44: 369-74. 5.   CDC. Heart Disease Facts, 2012; Available from: http://www.cdc.gov/heartdisease/facts.htm. 7.   Shaw J, Sicree R, Zimmet P. Global estimates of the prevalence of diabetes for 2010 and 2030. Diabetes research and clinical practice 2010; 87: 4-14. 9.   Haffner SM. Pre-diabetes, insulin resistance, inflammation and CVD risk. Diabetes research and clinical practice 2003; 61: S9-S18. 11.Hancox RJ, Landhuis CE. Association between sleep duration and haemoglobin A1C in young adults.  J Epidemiol Community Health 2011. 13.Chao CY, Wu JS, Yang YC, Shih CC, Wang RH, Lu FH, et al. Sleep duration is a potential risk factor for newly diagnosed type 2 diabetes mellitus. Metabolism; 60: 799-804. 15.Grundy SM, Benjamin IJ, Burke GL, Chait A, Eckel RH, Howard BV, et al. Diabetes and cardiovascular disease: a statement for healthcare professionals from the American Heart Association. Circulation 1999; 100: 1134-46. 17.Deedwania PC, Fonseca VA. Diabetes, prediabetes, and cardiovascular risk: shifting the paradigm. The American journal of medicine 2005; 118: 939-47. 18.  Centers for Disease Control and Prevention. Racial/Ethnic and Socioeconomic Disparities in Multiple Risk Factors for Heart Disease and Stroke—United States, 2003. Morb Mortal Wkly Rep 2005; 54(5): 113–117. 2026 Ibrahim Medical College. All rights reserved.