Prediction of basal metabolic rate in overweight/obese and non-obese subjects and its relation to pulmonary function tests

Predictive Roles of Basal Metabolic Rate and Muscle Mass in Lung Function among Patients with Obese Asthma: A Prospective Cohort Study

BACKGROUND

The metabolic-status-related mechanisms underlying the deterioration of the lung function in obese asthma have not been completely elucidated.

OBJECTIVE

This study aimed to investigate the basal metabolic rate (BMR) in patients with obese asthma, its association with the lung function, and its mediating role in the impact of obesity on the lung function.

METHODS

A 12-month prospective cohort study (n = 598) was conducted in a real-world setting, comparing clinical, body composition, BMR, and lung function data between patients with obese (n = 282) and non-obese (n = 316) asthma. Path model mediation analyses for the BMR and skeletal muscle mass (SMM) were conducted. We also explored the effects of the BMR on the long-term lung function in patients with asthma.

RESULTS

Patients with obese asthma exhibited greater airway obstruction, with lower FEV1 (1.99 vs. 2.29 L), FVC (3.02 vs. 3.33 L), and FEV1/FVC (65.5 vs. 68.2%) values compared to patients with non-obese asthma. The patients with obese asthma also had higher BMRs (1284.27 vs. 1210.08 kcal/d) and SMM (23.53 vs. 22.10 kg). Both the BMR and SMM mediated the relationship between obesity and the lung function spirometers (FEV1, %FEV1, FVC, %FVC, and FEV1/FVC). A higher BMR or SMM was associated with better long-term lung function.

CONCLUSIONS

Our study highlights the significance of the BMR and SMM in mediating the relationship between obesity and spirometry in patients with asthma, and in determining the long-term lung function. Interventions for obese asthma should focus not only on reducing adiposity but also on maintaining a high BMR.

The association of predicted resting energy expenditure with risk of breast cancer among postmenopausal women in the Women's Health Initiative cohort

Obesity and obesity-related metabolic disorders, such as obesity and chronic inflammation, have been positively associated both with postmenopausal breast cancer and with resting energy expenditure (REE). However, there is limited epidemiological evidence on the associations between REE and risk of postmenopausal breast cancer. We used multivariable Cox proportional hazards models to examine the association between predicted REE (calculated using the Ikeda, Livingston and Mifflin equations) and risk of postmenopausal breast cancer overall and by subtypes, and by level of body fat) among 137,305 postmenopausal women in the Women's Health Initiative (WHI). All predicted REEs were positively associated with risk of invasive breast cancer (HRq5 vs q1: 1.69; 95% CI: 1.57-1.81, HR: 1.69; 95% CI: 1.57-1.82 and HR: 1.68; 95% CI: 1.56-1.80 for Ikeda, Livingston and Mifflin, respectively). These positive associations were observed irrespective of the hormone receptor subtype, grade and stage of the tumors, but were most pronounced for estrogen receptor positive/progesterone receptor positive tumors. After additional adjustment for BMI, the associations were mostly attenuated and remained statistically significant for most of the outcomes. We also observed an interaction between the predicted REEs and BMI, with the associations being somewhat stronger among normal weight and overweight women than among obese women (pinteractions <0.05). Our findings indicate that relatively high REE is associated with increased risk of invasive breast cancer among postmenopausal women (particularly for the obesity-related tumor subtypes), irrespective of the equation used. Further studies using more objective measures of REE are, however, needed to confirm our findings.

New Predictive Equations for Resting Energy Expenditure in Normal to Overweight and Obese Population

BACKGROUND AND AIMS

The unique demographic and dietary characteristics of modern Arabic population require development of a new predictive equation for the estimation of resting energy expenditure (REE). This study presented new equations characteristic to Saudi population.

METHODS

A set of predictive equations for REE was derived for 427 healthy male and female subjects (aged 18-57 ± 14 years). REE was measured (REEm) by indirect calorimetry (IC) and predicted (REEp) using nine equations. REEp was compared with REEm to determine the predictive accuracy of these equations. Using IC and anthropometrics for stepwise linear regression analysis, a new set of equations to predict REE of men and women was developed. Accuracy of the new main equations was further tested in an external sample of 48 subjects (men = 50%).

RESULTS

Using a number of parameters (bias, underprediction, overprediction, and % accurate prediction), our results suggested that almost all (9/9 in men and 7/9 in women) equations either underpredicted or overpredicted (2/9) REE. None of the already existing equations showed an acceptable REEp/REEm difference as low as 5% and an accurate prediction (∼55%) at the individual level. Based on these findings, a new prediction equation (hereafter referred to as the Almajwal-Abulmeaty (AA) equation) was developed using this study's data, after a rigorous stepwise regression analysis using the following formula: REE = 3832.955 + AdjWt (kg) × 48.037 - Ht (cm) × 30.642 + gender × 141.268 - age (years) × 4.525 [AdjWt is Adjusted body weight = (Wt - IBW)/4 + IBW. IBW is Ideal body weight; for men IBW = (Ht(cm) - 152.4) × 1.0714) + 45.36 and for women IBW = (Ht(cm)-152.4) × 0.8928) + 45.36]. The regression model accounted for approximately 70% of the variance in REEm (R 2 = 0.702).

CONCLUSION

Previous equations likely over- or underpredicted REE. Therefore, the new predictive AA equations developed in this study are recommended for the estimation of REE in young to middle-aged Saudi men and women with different body mass indexes. Future research is also required for further clinical and cross-validation of these new equations.

Dietary Intake and Associated Body Weight in Canadian Undergraduate Students Enrolled in Nutrition Education

The primary purpose of this study was to describe dietary intakes among Canadian undergraduate students enrolled in an Introductory Nutrition course. A secondary objective was to determine food group servings associated with meeting more Dietary Reference Intakes (DRIs) of select nutrients and with a lower body mass index (BMI). Participants (n = 124, 20.7±3.2yrs) provided output from a 3-day dietary record and completed a physical activity/demographics questionnaire. Linear regression showed that the dietary intake associated with meeting the most DRIs included vegetables, fruits, protein foods, and dairy (p = 0.001). Protein foods were a positive predictor and fruit a negative predictor of BMI (p = 0.001 and p = 0.023 respectively). Males consumed more grains (p = 0.001), dairy (p = 0.04), protein foods (p < 0.001), empty calories (p = 0.007) and total calories than females (p < 0.001). A diet characterized by greater intake of vegetables, fruits, protein foods, and dairy was associated with a Canadian undergraduate population meeting the greatest number of nutrient requirements.