Literature DB >> 25249653

BMI and coronary heart disease risk among low-income and underinsured diabetic patients.

Nan Li1, Peter T Katzmarzyk2, Ronald Horswell2, Yonggang Zhang2, Weiqin Li1, Wenhui Zhao2, Yujie Wang2, Jolene Johnson3, Gang Hu4.   

Abstract

OBJECTIVE: The association between obesity and coronary heart disease (CHD) risk remains debatable, and no studies have assessed this association among diabetic patients. The aim of our study was to investigate the association between BMI and CHD risk among patients with type 2 diabetes. RESEARCH DESIGN AND METHODS: The sample included 30,434 diabetic patients (10,955 men and 19,479 women) 30-95 years of age without a history of CHD or stroke in the Louisiana State University Hospital-Based Longitudinal Study.
RESULTS: During a mean follow-up period of 7.3 years, 7,414 subjects developed CHD. The multivariable-adjusted hazard ratios for CHD across levels of BMI at baseline (18.5-24.9, 25-29.9, 30-34.9, 35-39.9, and ≥40 kg/m(2)) were 1.00, 1.14 (95% CI 1.00-1.29), 1.27 (1.12-1.45), 1.54 (1.34-1.78), and 1.42 (1.23-1.64) (Ptrend < 0.001) in men and 1.00, 0.95 (0.85-1.07), 0.95 (0.84-1.06), 1.06 (0.94-1.20), and 1.09 (1.00-1.22) (Ptrend < 0.001) in women, respectively. When we used an updated mean or last visit value of BMI, the positive association between BMI and CHD risk did not change in men. However, the positive association of BMI with CHD changed to a U-shaped association in women when we used the last visit value of BMI.
CONCLUSIONS: Our study suggests that there is a positive association between BMI at baseline and during follow-up with the risk of CHD among patients with type 2 diabetes. We indicate a U-shaped association between BMI at the last visit and the risk of CHD among women with type 2 diabetes.
© 2014 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.

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Mesh:

Year:  2014        PMID: 25249653      PMCID: PMC4237979          DOI: 10.2337/dc14-1091

Source DB:  PubMed          Journal:  Diabetes Care        ISSN: 0149-5992            Impact factor:   19.112


Introduction

Obesity and diabetes are two important public health problems in the U.S. (1). Two in three adults in the U.S. are currently classified as overweight or obese (BMI ≥25 kg/m2), and one-third of them are frankly obese (BMI ≥30 kg/m2) (1). The estimated number of adults with diabetes in the U.S. is 26.1 million in 2005–2010 or ∼12% of the population (2). Among U.S. diabetic patients, the prevalence of overweight or obesity has increased to ≥80% (3). Obesity is associated with increased risks of several cardiometabolic diseases, including hypertension (4), diabetes (5), coronary heart disease (CHD) (6,7), heart failure (8), and stroke (9). Cardiovascular diseases, especially CHD, are the leading causes of death worldwide. In recent years, several prospective studies have assessed the association between obesity and the risks of total and CVD mortality among diabetic patients, and the results are inconsistent. To date, many studies have reported positive associations (10,11), inverse associations (12–14), U-shaped associations (15–17), or no associations (18) between BMI and mortality among patients with diabetes. All of these studies were focused on the association between BMI and CVD mortality; however, no studies assessed the association between BMI and the risk of incident CHD among diabetic patients. In this study, we examined the association between BMI and the risk of CHD among patients with type 2 diabetes in the Louisiana State University Hospital-Based Longitudinal Study (LSUHLS).

Research Design and Methods

Study Population

Between 1997 and 2012, the LSU Health Care Services Division (LSUHCSD) operated seven public hospitals and affiliated clinics in Louisiana providing quality medical care to the residents of Louisiana regardless of their income or insurance coverage (19–26). Overall, LSUHCSD facilities have served ∼1.6 million patients (35% of the Louisiana population) since 1997. Administrative, anthropometric, laboratory, clinical diagnosis, and medication data collected at these facilities are available in electronic form for both inpatients and outpatients from 1997. Using these data, we have established the LSUHLS (19). A cohort of diabetic patients was established by using the ICD-9 (code 250) between 1 January 1999 and 31 December 2009. Both inpatients and outpatients were included, and all patients were under primary care. Confirmation of diabetes diagnoses was made by applying the American Diabetes Association criteria: a fasting plasma glucose level ≥126 mg/dL; 2-h glucose level ≥200 mg/dL after a 75-g 2-h oral glucose tolerance test; and one or more classic symptoms plus a random plasma glucose level ≥200 mg/dL (27,28). The first record of diabetes diagnosis was used to establish the baseline for each patient in the present analyses due to the design of the cohort study. Before diagnosis with diabetes, these patients have used the LSU system for an average 5.0 years. We have validated the diabetes diagnosis in LSUHCSD hospitals. The agreement of diabetes diagnosis was 97%: 20,919 of a sample of 21,566 hospital discharge diagnoses based on ICD codes also had physician-confirmed diabetes by using the American Diabetes Associates diabetes diagnosis criteria (27). The current study included 30,434 newly diagnosed patients (10,955 men and 19,479 women) with type 2 diabetes who were 30–95 years of age without a history of CHD and stroke at the time of diabetes diagnosis and with complete repeated data on all risk factor variables. We only included African Americans and whites because the patient numbers of Hispanics, Asians, and Native Americans are very small in the LSUHCSD hospitals. Patients were excluded if they were underweight (BMI <18.5 kg/m2) because of limited statistical power for this group. Compared with diabetic patients excluded from the present analyses due to missing data, those included in the analyses were younger (51.0 vs. 57.6 years old), had a higher frequency of African Americans (58.6 vs. 45.4%), and less males (37.2 vs. 47.1%). The study and analysis plan was approved by the Pennington Biomedical Research Center and LSU Health Sciences Center Institutional Review Boards, LSU System. We did not obtain informed consent from participants involved in our study because we used anonymized data compiled from electronic medical records.

Baseline Measurements

The patient’s characteristics, including age at diabetes diagnosis, sex, race/ethnicity, family income, smoking status, types of health insurance, BMI, blood pressure, total cholesterol, HDL cholesterol, LDL cholesterol, triglycerides, glycosylated hemoglobin (HbA1c), estimated glomerular filtration rate (eGFR), and medication (antihypertensive drug, cholesterol-lowering drug, and antidiabetes drug) within a half year before the diabetes diagnosis (baseline), during follow-up after the diabetes diagnosis (follow-up), and the last visit were extracted from the computerized hospitalization records. Height and weight were measured without shoes and with light clothing according to a standardized protocol. BMI was calculated by dividing weight in kilograms by the square of height in meters. Values of BMI, blood pressure, HbA1c, LDL cholesterol, and eGFR over time were measured firstly at baseline and secondly as an updated mean of annual measurements, calculated for each participant from baseline to each year of follow-up. For example, at 1 year, the updated mean is the average of the baseline and 1-year values, and at 3 years, it is the average of baseline, 1-year, 2-year, and 3-year values. In the case of an event during follow-up, the period for estimating updated mean values was from baseline to the year before this event occurred (29). The average number of BMI measurements during the follow-up period was 15.0.

Prospective Follow-up

Follow-up information was obtained from the LSUHLS inpatient and outpatient database by using the unique number assigned to every patient who visits the LSUHCSD hospitals. The diagnosis of CHD was the primary end point of interest of the study and defined according to the following ICD-9: CHD (ICD-codes 410–414). Follow-up of each cohort member continued until the date of the diagnosis of CHD, the date of the last visit if the subject stopped use of LSUHCSD hospitals, or the date of death, determined from linking to the Louisiana Office of Public Health Vital Records Registry, or 31 May 2012 (23,26).

Statistical Analyses

The association between BMI and the risk of CHD was analyzed by using Cox proportional hazards models. BMI was evaluated in the following two ways: 1) as five weight categories (18.5–24.9 [reference group], 25–29.9, 30–34.9, 35–39.9, and ≥40 kg/m2) and 2) as a continuous variable. The trend over different categories of BMI was tested in models with the median of each category as a continuous variable. All analyses were adjusted for age (continuous variable) and race (African American and white) (model 1) and further for smoking (never, past, and current), income (continuous variable), and types of insurance (free, self-pay, Medicaid, Medicare, and commercial) (model 2), and additionally for systolic blood pressure (continuous variable), HbA1c (continuous variable), LDL cholesterol (continuous variable), HDL cholesterol (continuous variable), triglycerides (continuous variable), eGFR (≥90, 60–89, 30–59, 15–29, and <15 mL/min/1.73 m2), use of antihypertensive drugs (no use, ACE inhibitor, angiotensin II receptor blockers, β-blockers, calcium channel blocker, diuretics, and other antihypertensive drugs), use of diabetes medications (no use, oral hypoglycemic agents, and insulin), and use of cholesterol-lowering agents (no use, statins, and other cholesterol-lowering agents) (model 3). We stratified the samples by sex because there was a significant interaction between sex and BMI on the risk of CHD. Since the interactions between race and BMI on the risk of CHD were not statistically significant, data for white and African Americans were combined in some analyses. Statistical significance was considered to be P < 0.05. All statistical analyses were performed with PASW for Windows, version 20.0 (IBM SPSS Inc., Chicago, IL).

Results

General characteristics of the study population at baseline are presented in Table 1.
Table 1

Baseline characteristics of patients with type 2 diabetes by the outcome during follow-up

Men
Women
No CHDCHDP valueNo CHDCHDP value
Number of participants8,0292,92614,9914,488
Age, mean (SE) (years)50.2 (0.11)54.1 (0.18)<0.00151.1 (0.08)53.9 (0.15)<0.001
Income, mean (SE) ($/family)18,935 (319)22,207 (521)<0.00118,850 (203)20,273 (371)<0.001
BMI at baseline, mean (SE) (kg/m2)32.5 (0.09)33.3 (0.14)<0.00135.6 (0.07)35.7 (0.12)0.36
BMI during follow-up, mean (SE) (kg/m2)32.3 (0.08)33.2 (0.13)<0.00135.5 (0.07)35.7 (0.12)0.18
BMI at last visit, mean (SE) (kg/m2)32.2 (0.09)33.0 (0.14)<0.00135.3 (0.07)35.4 (0.13)0.42
Race, N (%)<0.001<0.001
 African American4,731 (58.9)1,369 (46.8)9,168 (61.2)2,380 (53.0)
 White3,298 (41.1)1,557 (53.2)5,823 (38.8)2,108 (47.0)
HbA1c, mean [% (mmol/mol)]8.02 (64)7.99 (64)0.597.51 (59)7.71 (61)<0.001
HDL cholesterol, mean (SE) (mg/dL)39.5 (0.1)38.8 (0.2)0.00646.0 (0.1)45.0 (0.2)<0.001
LDL cholesterol, mean (SE) (mg/dL)109 (0.5)105 (0.8)<0.001116 (0.3)113 (0.6)<0.001
Triglycerides, mean (SE) (mg/dL)151 (1.0)160 (1.7)<0.001140 (0.6)149 (1.2)<0.001
GFR, N (%) (mL/min/1.73 m2)<0.001<0.001
 ≥904,261 (53.1)1,215 (41.5)7,256 (48.4)1,824 (40.7)
 60–892,977 (37.1)1,208 (41.3)6,027 (40.2)1,820 (40.5)
 30–59656 (8.2)430 (14.7)1,539 (10.3)752 (16.8)
 15–2984 (1.0)52 (1.8)113 (0.7)73 (1.6)
 <1551 (0.6)21 (0.7)56 (0.4)19 (0.4)
Current smoker, N (%)2,930 (36.5)987 (33.7)0.0143,808 (25.4)1,178 (26.3)0.46
Types of insurance, N (%)<0.001<0.001
 Free5,999 (74.7)1,969 (67.3)12,559 (83.8)3,399 (75.7)
 Self-pay698 (8.7)141 (4.8)601 (4.0)125 (2.8)
 Medicaid368 (4.6)150 (5.1)692 (4.6)325 (7.3)
 Medicare732 (9.1)591 (20.2)844 (5.6)561 (12.5)
 Commercial232 (2.9)75 (2.6)295 (2.0)78 (1.7)
Uses of medications, N %
 Glucose-lowering medication5,196 (64.7)1,989 (68.0)<0.0019,730 (64.9)3,085 (68.7)<0.001
 Lipid-lowering medication3,852 (48.0)1,879 (64.2)<0.0018,188 (54.6)2,994 (66.7)<0.001
 Antihypertensive medication5,495 (68.4)2,183 (74.6)<0.00111,017 (73.5)3,484 (77.6)<0.001

aData represent means or percentages. All data except age are adjusted for age and race.

Baseline characteristics of patients with type 2 diabetes by the outcome during follow-up aData represent means or percentages. All data except age are adjusted for age and race. During a mean follow-up period of 7.3 years, 7,414 subjects (2,926 men and 4,488 women) developed CHD. Patients who developed CHD during follow-up were older and used more glucose-lowering, lipid-lowering, and antihypertensive medication compared with those who did not develop CHD. The multivariable-adjusted (age, race, smoking, income, and types of insurance) (model 2) hazard ratios (HRs) for CHD at different levels of BMI at baseline (18.5–24.9 [reference group], 25–29.9, 30–34.9, 35–39.9, and ≥40 kg/m2) were 1.00, 1.14 (95% CI 1.00–1.29), 1.27 (1.12–1.45), 1.54 (1.34–1.78), and 1.42 (1.23–1.64) (Ptrend < 0.001) in men and 1.00, 0.95 (0.85–1.07), 0.95 (0.84–1.06), 1.06 (0.94–1.20), and 1.09 (1.00–1.22) (Ptrend < 0.001) in women, respectively (Table 2). After further adjustment for other confounding factors (systolic blood pressure, HbA1c, LDL cholesterol, HDL cholesterol, triglycerides, eGFR, use of antihypertensive drugs, use of diabetes medications, and use of cholesterol-lowering agents), this association remained significant among men (Ptrend < 0.001) and women (Ptrend = 0.006).
Table 2

HRs of CHD according to different levels of BMI at baseline, during follow-up, and at last visit among patients with type 2 diabetes

BMI (kg/m2)
P for trendEach 1-kg/m2 increase
<25.025.0–29.930–34.935–39.9≥40
Baseline
 Men1,5613,0082,9481,7891,649
  Number of cases350774811540451
  Person-years11,08521,19219,99011,38210,889
  Adjustment    HR (95% CI)
   Model 1a1.001.12 (0.98–1.27)1.24 (1.09–1.41)1.50 (1.31–1.72)1.39 (1.20–1.61)<0.0011.015 (1.010–1.020)
   Model 2b1.001.14 (1.00–1.29)1.27 (1.12–1.45)1.54 (1.34–1.78)1.42 (1.23–1.64)<0.0011.015 (1.011–1.020)
   Model 3c1.001.16 (1.00–1.33)1.24 (1.07–1.43)1.47 (1.26–1.72)1.45 (1.24–1.70)<0.0011.015 (1.009–1.020)
 Women1,6813,8734,7193,9685,238
  Number of cases4209041,0549381,172
  Person-years12,66430,03236,54830,10239,538
  Adjustment  HR (95% CI)
   Model 1a1.000.93 (0.83–1.05)0.92 (0.82–1.03)1.03 (0.91–1.16)1.05 (0.94–1.18)0.0101.004 (1.000–1.007)
   Model 2b1.000.95 (0.85–1.07)0.95 (0.84–1.06)1.06 (0.94–1.20)1.09 (1.00–1.22)<0.0011.004 (1.001–1.008)
   Model 3c1.000.93 (0.82–1.06)0.92 (0.82–1.05)1.02 (0.90–1.16)1.07 (0.95–1.22)0.0061.005 (1.001–1.009)
Follow-up
 Men1,4943,1083,0281,7971,528
  Number of cases335814813529435
  Person-years10,69121,87620,54211,6299,806
  Adjustment HR (95% CI)
   Model 1a1.001.14 (1.00–1.30)1.22 (1.07–1.39)1.49 (1.30–1.72)1.50 (1.29–1.74)<0.0011.017 (1.012–1.023)
   Model 2b1.001.16 (1.02–1.32)1.26 (1.11–1.44)1.53 (1.33–1.77)1.55 (1.33–1.80)<0.0011.018 (1.013–1.023)
   Model 3c1.001.18 (1.02–1.36)1.24 (1.07–1.44)1.45 (1.24–1.69)1.55 (1.31–1.82)<0.0011.017 (1.011–1.023)
 Women1,5793,8974,8743,9655,164
  Number of cases3889051,0869481,161
  Person-years12,09830,03437,74929,86239,139
  Adjustment HR (95% CI)
   Model 1a1.000.97 (0.86–1.10)0.95 (0.84–1.07)1.10 (0.98–1.25)1.10 (0.98–1.24)<0.0011.004 (1.001–1.008)
   Model 2b1.000.99 (0.88–1.12)0.98 (0.87–1.11)1.14 (1.01–1.29)1.14 (1.01–1.29)<0.0011.006 (1.002–1.009)
   Model 3c1.001.00 (0.88–1.15)1.00 (0.88–1.14)1.12 (0.98–1.28)1.12 (0.99–1.28)0.0031.005 (1.000–1.009)
Last visit
 Men1,7153,0642,8921,7131,571
  Number of cases406794782494450
  Person-years12,24121,43119,68211,10810,076
  Adjustment HR (95% CI)
   Model 1a1.001.12 (0.99–1.27)1.20 (1.06–1.36)1.44 (1.25–1.64)1.48 (1.28–1.70)<0.0011.016 (1.011–1.020)
   Model 2b1.001.15 (1.01–1.30)1.25 (1.10–1.41)1.49 (1.30–1.70)1.53 (1.32–1.76)<0.0011.016 (1.011–1.021)
   Model 3c1.001.11 (0.97–1.26)1.19 (1.04–1.37)1.33 (1.15–1.54)1.46 (1.25–1.70)<0.0011.015 (1.009–1.020)
 Women1,8913,9894,7083,8375,054
  Number of cases5029071,0399131,127
  Person-years14,25930,87436,34628,96238,442
  Adjustment HR (95% CI)
   Model 1a1.000.87 (0.78–0.97)0.87 (0.78–0.97)1.01 (0.90–1.13)1.00 (0.90–1.12)0.0221.004 (1.000–1.007)
   Model 2b1.000.89 (0.80–1.00)0.90 (0.81–1.00)1.05 (0.93–1.17)1.04 (0.93–1.17)0.0031.004 (1.001–1.008)
   Model 3c1.000.90 (0.80–1.02)0.91 (0.81–1.03)1.03 (0.92–1.17)1.00 (0.89–1.13)0.0851.003 (0.999–1.006)

aAdjusted for age and race.

bAdjusted for age, race, types of insurance, income, and smoking.

cAdjusted for age, race, types of insurance, income, smoking, systolic blood pressure, LDL cholesterol, HDL cholesterol, triglycerides, HbA1c, eGFR, use of antihypertensive drugs (none, ACE inhibitor, angiotensin II receptor blockers, β-blockers, calcium channel blocker, diuretics, other antihypertensive drugs, and any two or more of above treatments), glucose-lowering agents (none, oral hypoglycemic agents, and insulin), and cholesterol-lowering agents (none, statins, and other cholesterol-lowering agents).

HRs of CHD according to different levels of BMI at baseline, during follow-up, and at last visit among patients with type 2 diabetes aAdjusted for age and race. bAdjusted for age, race, types of insurance, income, and smoking. cAdjusted for age, race, types of insurance, income, smoking, systolic blood pressure, LDL cholesterol, HDL cholesterol, triglycerides, HbA1c, eGFR, use of antihypertensive drugs (none, ACE inhibitor, angiotensin II receptor blockers, β-blockers, calcium channel blocker, diuretics, other antihypertensive drugs, and any two or more of above treatments), glucose-lowering agents (none, oral hypoglycemic agents, and insulin), and cholesterol-lowering agents (none, statins, and other cholesterol-lowering agents). When BMI was examined as a continuous variable, the multivariable-adjusted (model 2) HRs of CHD for each one-unit increase in BMI at baseline were 1.015 (95% CI 1.011–1.020) in men and 1.004 (95% CI 1.001–1.008) in women (Table 2). There was a significant interaction between sex and BMI on CHD risk (χ2 = 9.86; 1df, P < 0.005), which indicated that this positive association was stronger in men than in women. When we did an additional analysis by using an updated mean value of BMI, we found the same positive association between BMI and CHD risk among both men (Ptrend < 0.001) and women (Ptrend < 0.001) (Table 2). When we did another additional analysis by using the last visit value of BMI, we found a positive association between BMI and CHD risk among men (Ptrend < 0.001) and a U-shaped association between BMI and CHD risk among women (Ptrend = 0.003) (Table 2). Women who were overweight and had class I obesity (BMI 25–34.9 kg/m2) at last visit had a lower risk of CHD compared with normal-weight women (BMI <25 kg/m2). After excluding subjects who were diagnosed with CHD during the first 2 years of follow-up (n = 3,207), the multivariable-adjusted HRs (model 2) of CHD for each one-unit increase in BMI at baseline, during follow-up, and at the last visit were 1.014 (95% CI 1.010–1.019), 1.017 (1.012–1.022), and 1.015 (1.009–1.019) in men and 1.005 (1.001–1.009), 1.006 (1.002–1.010), and 1.005 (1.000–1.008) in women (data not shown), respectively. In stratified analyses, the multivariable-adjusted positive association between BMI and CHD risk was present among men with different smoking status (Tables 3 and 4). When stratified by age, race, and use of antidiabetic drugs, this positive association of BMI at baseline, during follow-up, and at the last visit with CHD risk was still present among men in all subgroups and among women in some of the subgroups (Tables 3 and 4).
Table 3

HRs (95% CIs) of CHD according to different levels of BMI at baseline among various subpopulations

BMI (kg/m2)
P for trendP for interaction
<25.025.0–29.930–34.935–39.9≥40
Men
 Age groups (years)>0.50
  <501.001.07 (0.86–1.33)1.19 (0.96–1.48)1.47 (1.19–1.85)1.44 (1.15–1.80)<0.001
  50–591.001.28 (1.01–1.60)1.48 (1.17–0.85)1.57 (1.23–2.00)1.56 (1.22–2.01)<0.001
  ≥601.001.01 (0.8–1.27)1.07 (0.84–1.35)1.42 (1.10–1.85)0.83 (0.59–1.15)0.38
 Race>0.10
  African American1.001.18 (0.99–1.40)1.26 (1.05–1.51)1.54 (1.26–1.88)1.53 (1.24–1.89)<0.001
  White1.001.08 (0.89–1.32)1.27 (1.05–1.54)1.54 (1.26–1.88)1.35 (1.10–1.66)<0.001
 Smoking status<0.05
  Never1.001.17 (0.95–1.44)1.35 (1.10–1.67)1.68 (1.35–2.09)1.70 (1.36–2.12)<0.001
  Ever or current1.001.33 (1.09–1.62)1.41 (1.15–1.73)1.61 (1.28–2.03)1.38 (1.08–1.76)<0.001
 Glucose-lowering medication>0.25
  No use1.001.56 (1.19–2.06)1.40 (1.05–1.88)1.66 (1.20–2.29)1.85 (1.33–2.56)0.001
  Oral hypoglycemic agents1.001.25 (0.95–1.65)1.46 (1.11–1.92)1.66 (1.23–2.23)1.57 (1.15–2.14)<0.001
   Metformin1.001.08 (0.87–1.34)1.31 (1.06–1.62)1.56 (1.24–1.95)1.47 (1.16–1.85)<0.001
   Sulfonylureas1.001.04 (0.83–1.32)1.24 (0.98–1.56)1.47 (1.15–1.88)1.32 (1.02–1.71)<0.001
   Other oral agents1.001.13 (0.78–1.66)1.35 (0.93–1.95)1.52 (1.03–2.22)1.76 (1.20–2.59)<0.001
  Insulin1.001.09 (0.88–1.34)1.29 (1.05–1.58)1.56 (1.26–1.94)1.49 (1.19–1.86)<0.001
Women
 Age groups (years)>0.05
  <501.001.10 (0.89–1.37)1.04 (0.84–1.29)1.09 (0.88–1.35)1.06 (0.86–1.30)0.70
  50–591.000.89 (0.73–1.08)0.88 (0.73–1.07)1.02 (0.84–1.24)1.06 (0.87–1.28)0.048
  ≥601.000.89 (0.72–1.09)0.89 (0.73–1.09)0.99 (0.79–1.23)1.06 (0.85–1.33)0.46
 Race>0.20
  African American1.000.90 (0.77–1.05)0.85 (0.72–0.99)1.06 (0.90–1.24)1.07 (0.92–1.26)0.005
  White1.001.03 (0.86–1.23)1.09 (0.91–1.30)1.08 (0.90–1.29)1.13 (0.95–1.35)0.17
 Smoking status>0.75
  Never1.000.92 (0.77–1.08)0.96 (0.82–1.13)1.06 (0.90–1.26)1.11 (0.94–1.31)0.005
  Ever or current1.001.05 (0.85–1.29)1.04 (0.85–1.28)1.11 (0.89–1.37)1.10 (0.89–1.37)0.21
 Glucose-lowering medication>0.05
  No use1.001.05 (0.82–1.34)1.08 (0.84–1.38)1.08 (0.83–1.40)1.30 (1.01–1.67)0.029
  Oral hypoglycemic agents1.000.94 (0.75–1.17)0.87 (0.70–1.08)0.93 (0.74–1.16)0.89 (0.71–1.12)0.43
   Metformin1.001.04 (0.86–1.26)1.04 (0.86–1.26)1.16 (0.95–1.40)1.12 (0.93–1.36)0.073
   Sulfonylureas1.000.85 (0.69–1.05)0.92 (0.75–1.12)0.99 (0.80–1.22)0.99 (0.81–1.22)0.17
   Other oral agents1.000.79 (0.60–1.03)0.77 (0.59–0.99)0.83 (0.64–1.09)0.83 (0.64–1.07)0.80
  Insulin1.000.90 (0.74–1.10)0.97 (0.80–1.18)1.12 (0.92–1.36)1.14 (0.94–1.38)0.001

aAdjusted for age, race, types of insurance, income, and smoking, other than the variable for stratification.

Table 4

HRs (95% CIs) of CHD according to different levels of BMI during follow-up and at last visit among various subpopulations

BMI (kg/m2)
P for trendP for interaction
<25.025.0–29.930–34.935–39.9≥40
Follow-up
 Men
  Age groups (years)>0.25
   <501.001.07 (0.86–1.34)1.21 (0.97–1.51)1.43 (1.13–1.81)1.58 (1.25–2.00)<0.001
   50–591.001.21 (0.90–1.52)1.36 (1.08–1.71)1.59 (1.25–2.02)1.52 (1.18–1.95)<0.001
   ≥601.001.12 (0.89–1.41)1.10 (0.86–1.39)1.34 (1.02–1.77)1.07 (0.76–1.49)0.22
  Race>0.10
   African American1.001.08 (0.91–1.29)1.14 (0.95–1.36)1.50 (1.23–1.82)1.62 (1.31–2.01)<0.001
   White1.001.25 (1.03–1.53)1.41 (1.16–1.72)1.62 (1.31–1.99)1.56 (1.26–1.94)<0.001
  Smoking status<0.05
   Never1.001.23 (0.99–1.53)1.40 (1.12–1.73)1.73 (1.38–2.17)1.93 (1.53–2.43)<0.001
   Ever or current1.001.27 (1.04–1.55)1.34 (1.09–1.64)1.61 (1.29–2.03)1.36 (1.05–1.76)<0.001
  Glucose-lowering medication>0.25
   No use1.001.55 (1.18–2.05)1.46 (1.08–1.96)1.71 (1.24–2.37)1.86 (1.32–2.62)0.001
   Oral hypoglycemic agents1.001.11 (0.85–1.45)1.33 (1.02–1.73)1.44 (1.07–1.93)1.60 (1.18–2.18)<0.001
    Metformin1.001.18 (0.95–1.48)1.36 (1.09–1.70)1.62 (1.28–2.05)1.64 (1.29–2.10)<0.001
    Sulfonylureas1.000.98 (0.77–1.24)1.13 (0.90–1.43)1.37 (1.07–1.75)1.35 (1.04–1.76)<0.001
    Other oral agents1.001.18 (0.78–1.78)1.41 (0.94–2.09)1.56 (1.03–2.35)1.79 (1.18–2.71)<0.001
   Insulin1.001.18 (0.95–1.46)1.32 (1.06–1.64)1.64 (1.31–2.05)1.63 (1.29–2.07)<0.001
 Women
  Age groups (years)>0.25
   <501.001.11 (0.87–1.40)1.16 (0.92–1.45)1.21 (0.97–1.52)1.14 (0.92–1.42)0.18
   50–591.001.01 (0.82–1.24)0.93 (0.76–1.14)1.11 (0.90–1.36)1.15 (0.94–1.40)0.030
   ≥601.000.87 (0.71–1.07)0.84 (0.69–1.03)1.04 (0.84–1.29)1.01 (0.81–1.27)0.42
  Race>0.25
   African American1.000.94 (0.80–1.10)0.97 (0.83–1.14)1.11 (0.95–1.31)1.15 (0.98–1.36)<0.001
   White1.001.06 (0.89–1.28)1.01 (0.84–1.20)1.19 (1.00–1.43)1.15 (0.96–1.38)0.044
  Smoking status>0.90
   Never1.000.99 (0.83–1.18)1.01 (0.86–1.20)1.15 (0.96–1.36)1.19 (1.01–1.42)<0.001
   Ever or current1.001.14 (0.92–1.41)1.15 (0.93–1.42)1.31 (1.06–1.64)1.20 (0.96–1.49)0.036
  Glucose-lowering medication>0.10
   No use1.001.08 (0.84–1.40)1.06 (0.82–1.37)1.33 (1.02–1.73)1.38 (1.06–1.79)0.002
   Oral hypoglycemic agents1.000.96 (0.77–1.20)0.94 (0.76–1.17)0.94 (0.75–1.18)0.90 (0.72–1.13)0.35
    Metformin1.001.11 (0.91–1.35)1.13 (0.93–1.37)1.21 (0.99–1.47)1.21 (0.99–1.47)0.035
    Sulfonylureas1.000.99 (0.79–1.24)1.01 (0.82–1.25)1.08 (0.87–1.35)1.08 (0.87–1.35)0.17
    Other oral agents1.000.96 (0.71–1.31)0.82 (0.61–1.11)0.88 (0.64–1.20)0.92 (0.68–1.25)0.76
   Insulin1.001.05 (0.85–1.31)1.10 (0.89–1.35)1.26 (1.02–1.56)1.29 (1.05–1.59)<0.001
Last visit
 Men
  Age groups (years)>0.25
   <501.001.03 (0.83–1.28)1.14 (0.92–1.41)1.45 (1.16–1.81)1.50 (1.20–1.87)<0.001
   50–591.001.25 (1.01–1.55)1.37 (1.10–1.69)1.56 (1.24–1.96)1.50 (1.19–1.91)<0.001
   ≥601.001.10 (0.89–1.36)1.13 (0.90–1.41)1.24 (0.95–1.63)1.17 (0.86–1.60)0.09
  Race>0.10
   African American1.001.06 (0.89–1.25)1.15 (0.97–1.36)1.42 (1.17–1.72)1.61 (1.32–1.97)<0.001
   White1.001.26 (1.04–1.51)1.36 (1.13–1.64)1.58 (1.30–1.93)1.53 (1.25–1.87)<0.001
  Smoking status>0.05
   Never1.001.25 (1.02–1.52)1.44 (1.19–1.76)1.66 (1.35–2.05)1.95 (1.58–2.41)<0.001
   Ever or current1.001.15 (0.95–1.38)1.19 (0.98–1.44)1.50 (1.20–1.88)1.25 (0.98–1.59)0.003
  Glucose-lowering medication>0.10
   No use1.001.54 (1.19–2.00)1.41 (1.06–1.86)1.69 (1.25–2.30)1.65 (1.18–2.32)0.004
   Oral hypoglycemic agents1.001.06 (0.83–1.36)1.32 (1.03–1.69)1.42 (1.08–1.88)1.61 (1.21–2.14)<0.001
    Metformin1.000.99 (0.82–1.21)1.23 (1.01–1.49)1.40 (1.13–1.73)1.48 (1.19–1.83)<0.001
    Sulfonylureas1.000.97 (0.78–1.21)1.19 (0.96–1.47)1.40 (1.11–1.78)1.34 (1.06–1.71)<0.001
    Other oral agents1.000.97 (0.66–1.41)1.26 (0.88–1.81)1.38 (0.94–2.02)1.46 (1.00–2.14)<0.001
   Insulin1.001.04 (0.85–1.26)1.22 (1.00–1.48)1.38 (1.12–1.70)1.47 (1.19–1.82)<0.001
 Women
  Age groups (years)>0.25
   <501.000.93 (0.75–1.14)0.97 (0.79–1.19)1.04 (0.85–1.28)0.96 (0.79–1.16)0.75
   50–591.000.86 (0.72–1.04)0.86 (0.72–1.03)0.99 (0.83–1.20)1.05 (0.87–1.25)0.055
   ≥601.000.87 (0.72–1.05)0.80 (0.66–0.97)0.99 (0.81–1.22)1.02 (0.82–1.27)0.66
  Race>0.25
   African American1.000.83 (0.72–0.97)0.88 (0.76–1.02)1.02 (0.88–1.19)1.04 (0.90–1.21)0.001
   White1.000.97 (0.82–1.15)0.93 (0.79–1.09)1.08 (0.91–1.28)1.06 (0.90–1.25)0.14
  Smoking status>0.90
   Never1.000.88 (0.75–1.03)0.92 (0.79–1.07)1.05 (0.90–1.23)1.07 (0.92–1.25)0.005
   Ever or current1.001.03 (0.84–1.26)1.06 (0.87–1.29)1.18 (0.96–1.45)1.08 (0.88–1.33)0.26
  Glucose-lowering medication0.262
   No use1.000.93 (0.73–1.19)1.15 (0.91–1.45)1.13 (0.88–1.45)1.23 (0.96–1.58)0.016
   Oral hypoglycemic agents1.000.94 (0.77–1.14)0.87 (0.71–1.06)0.95 (0.77–1.17)0.85 (0.69–1.05)0.23
    Metformin1.001.02 (0.86–1.22)0.97 (0.82–1.16)1.14 (0.96–1.36)1.08 (0.91–1.29)0.11
    Sulfonylureas1.000.91 (0.74–1.11)0.88 (0.72–1.07)1.05 (0.86–1.28)0.97 (0.79–1.18)0.39
    Other oral agents1.000.83 (0.63–1.08)0.74 (0.57–0.96)0.81 (0.62–1.06)0.80 (0.62–1.04)0.40
   Insulin1.000.85 (0.70–1.03)0.88 (0.73–1.05)1.07 (0.89–1.30)1.03 (0.86–1.24)0.013

aAdjusted for age, race, types of insurance, income, and smoking, other than the variable for stratification.

HRs (95% CIs) of CHD according to different levels of BMI at baseline among various subpopulations aAdjusted for age, race, types of insurance, income, and smoking, other than the variable for stratification. HRs (95% CIs) of CHD according to different levels of BMI during follow-up and at last visit among various subpopulations aAdjusted for age, race, types of insurance, income, and smoking, other than the variable for stratification.

Conclusions

Our study found a positive association of BMI at baseline and during follow-up with the risk of CHD among both men and women with type 2 diabetes, and this association was stronger among men than among women. In addition, we found that a positive association between BMI and the risk of CHD was present in both African Americans and whites with type 2 diabetes and in nonsmokers and smokers. The positive association did not change among men but changed to a U-shaped association among women with type 2 diabetes when we assessed BMI of the last visit with CHD risk. Only a few prospective studies have evaluated the association between obesity and total and CVD mortality among diabetic patients, and the results are controversial including inverse associations (12–14), positive associations (10,11), U-shaped associations (15–17), or no association (18). The current study was the first, to our knowledge, to assess the association between BMI and the risk of incident CHD among diabetic patients. The results of our study indicated a positive association between BMI and the risk of CHD among patients with type 2 diabetes. We found this positive association of CHD risk by BMI at baseline and during follow-up. In addition, this positive association was present in different race, antidiabetes medication, and smoking groups. It is noteworthy that there was a U-shaped association between BMI at the last visit and the risk of CHD among women with type 2 diabetes in the current study. Our study found that diabetic women who were overweight and had class I obesity (BMI 25–34.9 kg/m2) at the last visit had a lower risk of CHD compared with normal-weight women (BMI <25 kg/m2). It is well known that women with diabetes have a greater or equal relative risk of CHD than men with diabetes (30,31). The current study found a significant positive association of BMI and CHD risk among both men and women with type 2 diabetes, and this association is stronger among men than among women. The finding from our study is noteworthy for us to prevent CHD among patients with type 2 diabetes. In addition, more studies are needed to confirm the different effect size of BMI with CHD risk among men and women with type 2 diabetes. It has been suggested that three potential methodological concerns should be considered when assessing the associations between obesity and health outcomes (32). The most serious concern is reverse causation associated with CHD and death risk. People with a history of CVD and several other chronic diseases frequently lose weight, and thus, people with a lower weight might increase the estimated risk of death. A recent analysis pooling five longitudinal studies has found that patients who have normal weight at the time of diabetes diagnosis have a higher mortality risk than those who are overweight or obese (12). They suggest that diabetic individuals with metabolically obese normal-weight may reflect underlying illness that predisposes to mortality (33). Despite having a normal BMI, these diabetic individuals have hyperinsulinemia, insulin resistance, and dyslipidemia, and all of these factors predispose individuals to death (33). In the current study, we excluded patients with a history of CHD and stroke at time of diabetes diagnosis, which can minimize the influence of reverse causation. Moreover, we performed another sensitivity analysis by excluding the subjects who were diagnosed with CHD during the first 2 years of follow-up (n = 3,207), and the positive association of BMI at baseline and during follow-up with CHD risk was still present. The second major concern is that confounding factors may distort the association between body weight and CHD. Smoking is a particularly important factor because smokers tend to weigh less and have much higher CHD risk than nonsmokers. In the current study, smoking status was considered as a confounding factor in the multivariable model, and the positive association between BMI and the risk of CHD was found in both never-smokers and smokers. The third methodological concern in some analyses between weight and CHD risk is that the physiologic effects of excess fatness, such as hypertension, diabetes, and dyslipidemia, were controlled for statistically, thus artificially removing some of the effects of being overweight. Obesity has been found as a strong risk factor for hypertension (4), high levels of HbA1c (5), and high serum cholesterol among diabetic patients (34) and has also been the key or important component of the metabolic syndrome (35). All of these factors are associated with an increased risk of CHD (35–37) and considered as mediating factors for the physiologic effects of obesity on the CHD risk. In the current study, the adjustment for systolic blood pressure, LDL cholesterol, HDL cholesterol, triglycerides, HbA1c, eGFR, and treatment attenuated the association between BMI and CHD risk, but BMI as a continuous variable remained a statistically significant predictor of CHD in the multivariable model. There are several strengths in our study, including the large sample size, high proportion of African Americans, and the use of administrative databases to avoid differential recall biases. We have used baseline BMI levels, updated mean values of BMI during follow-up, and the last visit value of BMI in the analyses, which can avoid potential bias from a single baseline measurement. In addition, participants in this study used the same public health care system that minimizes the influence of accessibility to health care, particularly in comparing men and women. One limitation of our study is that our analysis was not performed on a representative sample of the population, which limits the generalizability of this study; however, LSUHCSD hospitals are public hospitals and cover >1.6 million patients, most of whom are low-income persons in Louisiana. The results of the current study will have wide applicability for the population with low income and without health insurance in the U.S. Another limitation of our study is that we did not have data on other obesity indicators, such as waist, hip, and thigh circumferences, and did not assess abdominal height, although these adiposity predictors have been shown to be associated with CVD risk (6,38,39). Third, while body weight was measured at each clinic visit, clinically measured BMI might not be as accurate as BMI measured in carefully conducted laboratory studies (40). Fourth, even though our analyses adjusted for an extensive set of confounding factors, residual confounding due to the measurement error in the assessment of confounding factors, unmeasured factors such as heart rates, physical activity, education, and dietary factors, cannot be excluded. In summary, we found a positive association between BMI at baseline and during follow-up with the risk of CHD among men and women with type 2 diabetes, and this association was stronger among men than among women. We also found a positive association between BMI at the last visit and the risk of CHD among men with type 2 diabetes and a U-shaped association between BMI at the last visit and the risk of CHD among women with type 2 diabetes.
  40 in total

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