The association between obesity and acute myocardial infarction is age- and gender-dependent in a Japanese population

Abstract

Controversies concerning the association between obesity and acute myocardial infarction (AMI) are still ongoing in Japan. We investigated the association between obesity defined by body mass index of 25 kg/m(2) or higher and AMI by a case-control study using data from 1199 AMI cases and 4056 apparently healthy controls. The analysis was performed in age- and sex-matched samples of 621 case-control pairs younger than 80 years and in crude samples aged 40-79 years divided into 10-year age groups. Prevalence of obesity, diabetes, current smoking, hypertension, and hypercholesterolemia were compared between cases and controls, and a multivariable odds ratio (OR) of AMI was calculated for each risk factor in various age groups. The OR (95 % confidence interval (CI)) of AMI for obesity was 1.63 (1.23-2.17), P = 0.0008 in men younger than 80 years; 2.65 (1.41-5.00), P = 0.0025 in women younger than 80 years; 2.23 (1.46-3.41), P = 0.0002 in men aged 59 years or younger; 1.34 (0.90-2.01), P = 0.1510 in men aged 60-79 years; and 2.98 (1.56-5.71), P = 0.0010 in women aged 60-79 years using paired samples. The OR (95 % CI) of AMI for obesity was 4.92 (2.53-9.58), P < 0.0001 in men aged 40-49 years; 1.54 (1.07-2.21), P = 0.0197 in men aged 50-59 years; 1.07 (0.69-1.66), P = 0.7717 in men aged 60-69 years; 2.24 (1.20-4.20), P = 0.0118 in men aged 70-79 years; 2.48 (1.12-5.48), P = 0.0245 in women aged 60-69 years; and 3.05 (1.46-6.37), P = 0.0029 in women aged 70-79 years using crude samples. The association between obesity and AMI was age- and gender-dependent in a Japanese population.

Diabetes as a risk factor for acute coronary syndrome in women compared with men: a meta‐analysis, including 10 856 279 individuals and 106 703 acute coronary syndrome events

“…After reviewing the full text of the remaining articles, 19 articles were eligible for the final analysis. [17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35] Table 1 shows the baseline characteristics of all selected studies.…”

“…Of the 19 studies, 3 were hospital-based case-control studies, 19,22,24 6 were population-based case-control studies, [25][26][27][28]34,35 and 10 were cohort studies. 17,18,20,21,23,[29][30][31][32][33] Of these studies, 5 studies were conducted in America (2 in the United States 17,18 and 2 in Canada 20,32 ), 17,18,20,27,32 7 in Europe, 19,[21][22][23][24]30,33 and 6 in Asia (4 in Japan 28,29,34,35 ). 26,28,29,31,34,35 Overall, a total of 10 856 279 individuals participated in our analysis.…”

“…17,18,20,21,23,[29][30][31][32][33] Of these studies, 5 studies were conducted in America (2 in the United States 17,18 and 2 in Canada 20,32 ), 17,18,20,27,32 7 in Europe, 19,[21][22][23][24]30,33 and 6 in Asia (4 in Japan 28,29,34,35 ). 26,28,29,31,34,35 Overall, a total of 10 856 279 individuals participated in our analysis. There were at least 106 703 fatal and nonfatal ACS events among these individuals (1 study did not report the actual number of fatal and nonfatal ACS events).…”

Coronary vessels and cardiac myocytes of middle-aged rats demonstrate regional sex-specific adaptation in response to postmyocardial infarction remodeling

“…Therefore, our study is the first to conduct a side-by-side comparison of the global and regional patterns of LV remodeling between post-MI male and female middle-aged rats. We focused specifically on middle-aged animals because this age group, along with older individuals, corresponds to a human population, including both sexes, which are most vulnerable for myocardial ischemia and infarction [17,18,33,34]. We also chose to evaluate the hearts at the end of the first post-MI month because it usually represents a compensated phase of the infarct-induced LV remodeling process.…”

Impact of performance grading on annual numbers of acute myocardial infarction-associated emergency department visits in Taiwan

“…Several covariates related to the outcome variable were considered as potential confounders, including male sex (proportion of men in the mid-year population covered by the National Health Insurance program), age (in 3 groups, 20–39, 40–64, and ≥65 years) and medical co-morbidities (diabetes mellitus [ICD-9-CM code:250], [20,21] hyperlipidemia [ICD-9-CM code:2720 and 2721], [22] and hypertensive disease [ICD-9-CM code:401 to 405]. [22] …”