Question

What is the dependent, independent, and confounding variables from this abstract?

Background: Little is known about the effects of the amount and type of carbohydrates on risk of coronary heart disease (CHD).

Objective: The objective of this study was to prospectively evaluate the relations of the amount and type of carbohydrates with risk of CHD.

Design: A cohort of 75 521 women aged 38–63 y with no previous diagnosis of diabetes mellitus, myocardial infarction, angina, stroke, or other cardiovascular diseases in 1984 was followed for 10 y. Each participant’s dietary glycemic load was calculated as a function of glycemic index, carbohydrate content, and frequency of intake of individual foods reported on a validated food-frequency questionnaire at baseline. All dietary variables were updated in 1986 and 1990.

Results: During 10 y of follow-up (729 472 person-years), 761 cases of CHD (208 fatal and 553 nonfatal) were documented. Dietary glycemic load was directly associated with risk of CHD after adjustment for age, smoking status, total energy intake, alcohol intake, physical activity, postmenopausal hormone use, multivitamin use, use of vitamin E supplements, parental history of MI before age 60 y, history of hypertension, and history of hypercholesterolemia. The relative risks from the lowest to highest quintiles of glycemic load were 1.00, 1.01, 1.25, 1.51, and 1.98 (95% CI: 1.41, 2.77 for the highest quintile; P for trend < 0.0001). Carbohydrate classified by glycemic index, as opposed to its traditional classification as either simple or complex, was a better predictor of CHD risk. The association between dietary glycemic load and CHD risk was most evident among women with body weights above average [i.e., body mass index (in kg/m²) ≥ 23] (p for interaction < 0.01).

Conclusion: These epidemiologic data suggest that a high dietary glycemic load from refined carbohydrates increases the risk of CHD, independent of known coronary disease risk factors.

Answer 1

1. Dependent Variable- CHD (Coronary Heart Disease). It is dependent on various factors such as the types of Carbohydrate

2. Independant Variable-Types of Carbohydrate which is dietary glycemic load estimates the impact of carbohydrate intake using the glycemic index while taking into account the amount of carbohydrates that are eaten.

3. Confounding Variables - Frequency of intake of individual foods is one confounding Variable as it’s also possible that men eat more than women; this could also make sex a confounding variable. Age is also a confounding variable as the age increase the health factor may go down. Other confounding variables are smoking status,alcohol intake, physical activity, postmenopausal hormone use, multivitamin use, use of vitamin E supplements, parental history of MI before age 60 y, history of hypertension, and history of hypercholesterolemia.