Sentences with phrase «adjust for physical activity»

However, once you adjust for physical activity, it's clear that fitness is the major deciding factor of your health.

Not exact matches

Our analyses focused on five conditions that have been consistently associated with breastfeeding in observational studies that adjusted for parity as well as known or suspected confounders such as diet, physical activity, oral contraceptive use (in the case of cancer and hypertension), 6,7,18 and socioeconomic status (Table 1).

Like the previous study, these data were adjusted for factors like the children's physical activity and body composition and parental weight and education.

This finding held true even after the researchers adjusted for country, gender, age, puberty, BMI, birth weight, physical activity level, maternal BMI and maternal education.

The association between the two conditions remained significant even when researchers adjusted for other risk factors, including age, gender, race, body mass index, physical activity, history of alcohol use and smoking, and history of other conditions like myocardial infarction, stroke and diabetes mellitus.

The differences in risk were reduced, but remained statistically significant after adjusting for several factors, including age, race, BMI, birth control use, hormone replacement therapy, number of pregnancies, physical activity and alcohol consumption.

After adjusting for various factors, including age, demographic factors, health behaviors such as smoking and alcohol consumption, physical activity, medical conditions, and socioeconomic status, the researchers found that black workers in general — and black professionals in particular — were more likely to experience short sleep than whites.

These associations persisted even after adjusting for factors such as bone mineral density, physical activity, smoking and alcohol use, calcium and vitamin D intake, falls and all other known fracture risk factors.

To examine food intakes across five intake groups of the different beverages, they used computer modelling adjusted for age, sex, season, method, BMI, leisure time physical activity, total energy intake, smoking, education and alcohol intake.

Those who consistently watched ≥ 14 hours / week of television had lower bone mineral content than those who watched less television, even after adjusting for height, body mass, physical activity, calcium intake, vitamin D levels, alcohol, and smoking (all at age 20).

After adjusting the data for age, sex, race, education, smoking, alcohol use, blood pressure, diabetes, high blood pressure medication, cholesterol levels, statin use and body mass index, the researchers found that those people who met both the recommended activity levels and had vitamin D levels above 20 nanograms per milliliter experienced about a 23 percent less chance of having an adverse cardiovascular event than those people with poor physical activity who were deficient for vitamin D. On the other hand, people who had adequate exercise but were vitamin D deficient didn't have a reduced risk of an adverse event.

They adjusted for a variety of factors, such as age, physical activity, smoking, family history of diabetes, alcohol intake, postmenopausal status, menopausal hormone or oral contraceptive use, total caloric intake, and body mass index.

In the study, the risks were adjusted to account for several known factors that could influence the risk of death, including ethnicity; smoking status; intake of alcohol, fruits and vegetables and total calories; family history of chronic diseases; physical activity; body mass index; and heart disease risk factors when participants enrolled.

The results were adjusted for age at the start of the study, gender, daily calories, body mass index, smoking status, physical activity, education, alcohol intake and study center.

Estimates were derived using Cox regression adjusted for age, sex, smoking status, cumulative tobacco consumption, alcohol consumption, leisure - time physical activity, income, and plasma cholesterol level.

The results for women didn't show an increased risk for vigorous exercisers: All levels of physical activity appeared to lower the risk of infection compared to sedentary behavior, although adjusted results were only significant for the low - activity group.

Multivariate model 1 was adjusted for age (≤ 45, 45.1 — 50, 50.1 — 60, 60.1 — 65, or > 65.1 y), smoking status (never, past, current 1 — 14 cigarettes / d, or current ≥ 15 cigarettes / d), physical activity (< 1.5, 1.5 — 5.9, 6.0 — 11.9, 12.0 — 20.9, or ≥ 21.0 metabolic equivalent h / wk), alcohol intake (none, 0 — 4.9, 5.0 — 10.0, or > 10.0 g / d), total calorie intake (continuous), menopausal status, and postmenopausal hormone use (never, past, or current).

But even after adjusting for BMI, chronic conditions like diabetes and hypertension, and habits like total physical activity, drinking, and smoking, lifting was linked to a 19 percent reduced risk of death.

Cox regression was used to quantify the association between running and mortality after adjusting for baseline age, sex, examination year, body mass index, current smoking, heavy alcohol drinking, hypertension, hypercholesterolemia, parental CVD, and levels of other physical activities.

Over a period of time the body adjusts to higher levels of physical activities and it starts keeping higher reserves of the energy for the vital organs.

First, we adjusted for age (in y), cigarette smoking (yes or no), physical activity (continuous), current estrogen use (yes or no), menopausal status (yes or no), socioeconomic status (categorical), family history of diabetes and stroke (yes or no), and systolic and diastolic blood pressures (continuous).

In the illustrations that accompany this Harvard study it says that the study was «adjusted for age; race; body - mass index; level of physical activity; status with regard to smoking, whether a physical examination was performed for screening purposes, current multivitamin use, and current aspirin use; status with regard to a family history of diabetes mellitus, myocardial infarction, or cancer; status with regard to a history of diabetes mellitus, hypertension, or hypercholesterolemia; intake of total energy, alcohol, RED OR PROCESSED MEAT, fruits, and vegetables; and, for women, menopausal status and hormone use.»

Models in subgroups of women by smoking status and physical activity level did not adjust for the respective stratifying factors.

Model adjusted for age, race, baseline BMI, randomized treatment, nonalcohol energy intake, physical activity level, smoking status, postmenopausal status, postmenopausal hormone use, multivitamin use, history of hypercholesterolemia and hypertension, and intake of fruit and vegetables, whole grains, refined grains, red meats and poultry, low - fat dairy products, high - fat dairy products, energy - adjusted total fat, carbohydrates, and fiber.

In a linear mixed model adjusted for age, sex, education, participation in cognitive activities, physical activities, smoking, and seafood and alcohol consumption, consumption of green leafy vegetables was associated with slower cognitive decline; the decline rate for those in the highest quintile of intake (median 1.3 servings / d) was slower by β = 0.05 standardized units (p = 0.0001) or the equivalent of being 11 years younger in age.

In discussing the limited evidence for the «probable» link between red meat and colorectal cancer, the WHO itself concedes that it is not possible to rule out other explanations (which it helpfully describes as «chance, bias or confounding»).2 Harcombe agrees, arguing that even when studies strive to adjust statistically for baseline differences in relevant factors such as socioeconomic status, body mass index, physical activity, smoking status and diabetes, it is impossible to grapple fully with all the factors that differentiate «the couch potato» from «the paleo buff» (her ideal), or to take into account the «chasm» that separates fresh and traditionally preserved meats from modern manufactured meat products.9

The Curves Diet plan is very likely to produce weight loss success for most women, however this will be largely related to calorie restriction and increased physical activity rather than adjusting the metabolic rate or altering the set - point of the body.

Adjusting for daily alcohol consumption, physical activity, and BMI only slightly attenuated the relationship between TUI and risk of hypertension.

All weight changes were adjusted simultaneously for age, baseline body - mass index, sleep duration, and changes in smoking status, physical activity, television watching, alcohol use, and all of the dietary factors shown.

After adjusting for self - reported changes in other lifestyle factors likely to affect weight, such as smoking status and physical activity, an increased intake of fruits and of several vegetables was inversely associated with 4 - y weight change.

He thought it would be important to promote more active levels and stated that the Physical Activity Coefficients could be used to adjust the recommended food patterns for more active groups.

The model was adjusted for age, sex, race / ethnicity, educational attainment, smoking status, alcohol consumption, physical activity level, family history of cardiovascular disease, antihypertensive medication use, Healthy Eating Index score, body mass index, systolic blood pressure, total serum cholesterol, and total calories.

Although we were able to adjust for changes in physical activity, we can not rule out the possibility of residual confounding due to health consciousness if individuals who are eating healthier also make other healthier lifestyle changes not captured completely by our questionnaires.

In the multivariable analysis, we further adjusted for several potential dietary and lifestyle confounding factors, including multivitamin use, smoking status, pack - years of smoking, body mass index, physical activity, alcohol consumption, history of hypertension diagnosis, glycemic index, and intake of whole grains, total fiber, fruits, and vegetables.

Adjusted for age (continuous); interval; total energy intake (continuous); current menopausal hormones (binary); smoking status (never, past, or current smoker); body mass index (< 25.0, 25.0 - 29.9, or ≥ 30.0)(calculated as weight in kilograms divided by height in meters squared); physical activities (quintiles); marital status (married or partnered; widowed; or separated, divorced, or single); not involved in a church, volunteer, or community group (binary); retired (binary); reported diagnosis of diabetes mellitus (binary); cancer (binary); high blood pressure (binary); or myocardial infarction or angina (binary); and Mental Health Index score (86 - 100, 76 - 85, 53 - 75) in 1996.

Model 1 was energy partition adjusted; model 2 adjusted for variables in model 1 plus age, race - ethnicity, education, income, BMI, diabetes, hypertension, myocardial infarction, stroke, cardiovascular disease, cancer, Alzheimer disease, hormone replacement therapy, physical activity, alcohol, smoking, stressful life events, social support, and energy - adjusted intakes of SFAs, MUFAs, PUFAs, and trans fatty acids; model 3 adjusted for variables in model 2 plus energy - adjusted intakes of fruit, vegetables, legumes, nuts / seeds, and fiber and Healthy Eating Index score.

Adjusted for age, education, family history of breast cancer, history of benign breast disease, parity, age at first birth, age at menarche, age at menopause, oral contraceptive use, postmenopausal hormone use, BMI, physical activity, smoking, calcium supplement use, and alcohol intake.

The study was able to adjust for a large number of potential confounding factors, including education, lifestyle (smoking, alcohol, physical activity), dietary factors, and BMI.

After adjusting for factors such as levels of physical activity, the study findings noted that a higher intake of whole grains was associated with lower amounts of total body fat and abdominal fat.

After adjusting the data to account for known cardiovascular disease risk factors — such as smoking, physical activity, weight, blood pressure and cholesterol levels and diabetes — the researchers found no statistically significant association in the risk for cardiovascular disease between the highest levels of cocoa consumption and the lowest.

In preparing their reports, the researchers adjusted for other colorectal cancer risk factors, such as not getting screened, obesity, physical activity and eating a lot of red or processed meats.

• Exceptional mechanical aptitude aimed at controlling and operating complex machinery • Deep technical knowledge of CAD / CAM technology and how it is used for machine operations • Great physical stamina and dexterity to perform repetitive work activities and movements • Well - versed in reading and interpreting blueprints with a view to understand machine schematics and models • Demonstrated ability to learn new machine operations and adjust machine parts to meet specific instructions • Capable of working in a high noise environment • Able to monitor and assess performance of machinery and make needed adjustments • Proven ability to perform quality control analysis by conducting tests and inspections • Exceptional time management skills aimed at ensuring that machine operations are carried out in a time efficient manner • Excellent judgment and decision making skills; ability to consider costs and benefits of optimal machine operations • Critical thinking abilities aimed at identifying alternative solutions to machine operation problems • Complex problem solving skills targeted at evaluating possible machine operational issues • Able to plan, organize and schedule machine operations in sync with production agendas • Track record of prioritizing work activities in accordance to scheduled operating precedence • Skilled at dismantling, repairing and maintaining equipment • Knowledge of operating hand and power tools used in the production trade

All of the models were first adjusted for race and SES (Model 1), and then adjusted for baseline values of the primary outcome (i.e. adolescent physical activity or TV / video viewing) along with race and SES (Model 2).

Gender stratification was done a priori because of knowledge from other research showing differences in health outcomes for men and women (eg, BMI, fruit and vegetable intake, physical activity).4, 7,26,27 All regression models were adjusted for age, race and ethnicity, and SES.