Turning the analysis of obesity-mortality associations upside down: modeling years of life lost through conditional distributions

Smoking, respiratory symptoms, lung function and life expectancy: A longitudinal study of ageing

BACKGROUND AND OBJECTIVE

Prognostic indices have been developed to predict various outcomes, including mortality. These indices and hazard ratios may be difficult for patients to understand. We investigated the association between smoking, respiratory symptoms and lung function with remaining life expectancy (LE) in older adults.

METHODS

Data were from the 2004/05 English Longitudinal Study of Ageing (ELSA) (n = 8930), participants aged ≥50-years, with mortality data until 2012. Respiratory symptoms included were chronic phlegm and shortness of breath (SOB). The association between smoking, respiratory symptoms and FEV1/FVC, and remaining LE was estimated using a parametric survival function and adjusted for covariates including age at baseline and sex.

RESULTS

The extent to which symptoms and FEV1/FVC predicted differences in remaining LE varied by smoking. Compared to asymptomatic never smokers with normal lung function (the reference group), in never smokers, only those with SOB had a significant reduction in remaining LE. In former and current smokers, those with respiratory symptoms had significantly lower remaining LE compared to the reference group if they had FEV1/FVC <0.70 compared to those with FEV1/FVC ≥0.70. Males aged 50-years, current smokers with SOB and FEV1/FVC <0.70, had a remaining LE of 19.2 (95%CI: 16.5-22.2) years, a decrease of 8.1 (5.3-10.8) years, compared to the reference group.

CONCLUSION

Smoking, respiratory symptoms and FEV1/FVC are strongly associated with remaining LE in older people. The use of remaining LE to communicate mortality risk to patients needs further investigation.

Psychometric evaluation of three-factor eating questionnaire -R18 in aging Finnish men with increased risk for type 2 diabetes

BACKGROUND

Deeper comprehension of eating-related behaviour (how and why people eat) can reveal new aspects to support health and prevent type 2 diabetes (T2D). However, such research is largely missing in aging men.

AIM

The aim was to investigate suitability of the Three-Factor Eating Questionnaire-R18 (TFEQ-R18) in Finnish aging men which is widely used to examine factors: cognitive restraint (CR), uncontrolled eating (UE), and emotional eating (EE).

METHODS

Study population consisted of 420 men aged 50-75, who completed the TFEQ-R18 at the baseline of the T2D-GENE lifestyle intervention study. Inclusion criteria were impaired fasting glucose (IFG) and body mass index ≥25 kg/m2. Confirmatory factor analysis was used to study psychometrics (reliability, validity, and model fit) and factor structure of TFEQ-R18.

RESULTS

The items loaded to the three factors (CR, UE, EE) as in previous studies, except two items at CR factor and one at UE factor, which were therefore omitted. UE was also discovered split into two sub factors (named as 'craving' and 'loss-of-control'), UE being a higher-order (h) factor. The resultant revised version was named as Three-Factor Eating Questionnaire Revised to 15-items with higher-order factor (TFEQ-R15h).

CONCLUSION

The original 18-item version of the TFEQ was not optimal in the population consisting of Finnish aging men with elevated T2D risk. A modified 15-item version of the TFEQ could be used to describe EB in this population instead.

Comparing the Ability of Two Comprehensive Clinical Staging Systems to Predict Mortality: EOSS and CMDS

OBJECTIVE

Differences in discriminative and predictive ability for all-cause mortality of two clinical staging systems, the Edmonton Obesity Staging System (EOSS) and Cardiometabolic Disease Staging (CMDS), were estimated.

METHODS

Data for nonpregnant persons aged 40 to 75 years were extracted from the National Health and Nutrition Examination Survey. Predictive and discriminative ability was assessed using pseudo-R² and C-statistics. Median years of life lost were also computed for each score.

RESULTS

Differences in out-of-sample estimates of pseudo-R² and C-statistics (EOSS model as reference) were 0.02 (95% CI: 0.01-0.04) (Kent pseudo-R² ), 0.03 (0.01-0.04) (Royston pseudo-R² ), and 0.02 (0.01-0.02) (C-statistics). The median years of life lost for EOSS scores 2 and 3 (low to high risk) for a reference person were 1.19 and 6.76 years. Those for CMDS scores 1, 2, 3, and 4 (low to high risk) were 1.53, 2.90, 3.91, and 8.51 years. Consistent results from the in-sample estimates were observed.

CONCLUSIONS

CMDS had statistically significantly greater predictive and discriminative ability than EOSS for persons aged 40 to 75. While the clinical relevance of these differences is unknown, CMDS may have greater clinical utility given that it uses fewer items to risk stratify. The clinical relevance and utility need to be studied further.

All-Cause and Cause-Specific Mortality Associated with Bariatric Surgery: A Review

The question of whether or not nonsurgical intentional or voluntary weight loss results in reduced mortality has been equivocal, with long-term mortality following weight loss being reported as increased, decreased, and not changed. In part, inconsistent results have been attributed to the uncertainty of whether the intentionality of weight loss is accurately reported in large population studies and also that achieving significant and sustained voluntary weight loss in large intervention trials is extremely difficult. Bariatric surgery has generally been free of these conflicts. Patients voluntarily undergo surgery and the resulting weight is typically significant and sustained. These elements, combined with possible non-weight loss-related mechanisms, have resulted in improved comorbidities, which likely contribute to a reduction in long-term mortality. This paper reviews the association between bariatric surgery and long-term mortality. From these studies, the general consensus is that bariatric surgical patients have: 1) significantly reduced long-term all-cause mortality when compared to severely obese non-bariatric surgical control groups; 2) greater mortality when compared to the general population, with the exception of one study; 3) reduced cardiovascular-, stroke-, and cancer-caused mortality when compared to severely obese non-operated controls; and 4) increased risk for externally caused death such as suicide.

Modeling absolute differences in life expectancy with a censored skew-normal regression approach

Parameter estimates from commonly used multivariable parametric survival regression models do not directly quantify differences in years of life expectancy. Gaussian linear regression models give results in terms of absolute mean differences, but are not appropriate in modeling life expectancy, because in many situations time to death has a negative skewed distribution. A regression approach using a skew-normal distribution would be an alternative to parametric survival models in the modeling of life expectancy, because parameter estimates can be interpreted in terms of survival time differences while allowing for skewness of the distribution. In this paper we show how to use the skew-normal regression so that censored and left-truncated observations are accounted for. With this we model differences in life expectancy using data from the Swiss National Cohort Study and from official life expectancy estimates and compare the results with those derived from commonly used survival regression models. We conclude that a censored skew-normal survival regression approach for left-truncated observations can be used to model differences in life expectancy across covariates of interest.

Weight loss interventions for breast cancer survivors: impact of dietary pattern

Body weight management is not emphasized in clinical practice guidelines for breast cancer survivors, reflecting the lack of evidence that weight loss improves prognosis. Even if this situation changes, the optimal design for weight loss interventions is unclear. We conducted a 6-month non-randomized, controlled weight loss intervention in 249 post-menopausal breast cancer survivors. This paper reports effects on two secondary endpoints, change in body weight and composition. Participants were predominantly non-Hispanic whites (89%) with a mean age of 54.9 ± 9.2 years, a mean BMI of 29.0 ± 2.6 kg/m: ² and an average of 43 ± 5% body fat. Two dietary interventions, low fat or low carbohydrate, were investigated and consisted of a 42 day cycle of menus and recipes. Weight loss counseling and anthropometric assessment were provided at monthly clinic visits. One hundred ninety-two women completed the trial (77% retention). In comparison to the nonintervention control, both intervention arms achieved significant decreases in body weight (12.5%), body fat (27.5%), waist circumference (9.5%), and hip circumference (7.8%) (all p < 0.001) with minimal effects on lean mass (1.3% decrease). Median time to 5 and 10% weight loss was 2 (95% confidence interval = 1 to 3) and 4 (95% confidence interval = 3 to 5) months, respectively, and 23% of participants experienced ≥ 15% weight loss. Loss of body weight and fat mass was rapid and substantial irrespective of dietary approach when a structured program was provided with monthly anthropometric assessment and weight loss counseling.

Obesity and mortality: are the risks declining? Evidence from multiple prospective studies in the United States

We evaluated whether the obesity-associated years of life lost (YLL) have decreased over calendar time. We implemented a meta-analysis including only studies with two or more serial body mass index (BMI) assessments at different calendar years. For each BMI category (normal weight: BMI 18.5 to <25 [reference]; overweight: BMI 25 to <30; grade 1 obesity: BMI 30 to <35; and grade 2-3 obesity: BMI ≥ 35), we estimated the YLL change between 1970 and 1990. Because of low sample sizes for African-American, results are reported on Caucasian. Among men aged ≤60 years YLL for grade 1 obesity increased by 0.72 years (P < 0.001) and by 1.02 years (P = 0.01) for grade 2-3 obesity. For men aged >60, YLL for grade 1 obesity decreased by 1.02 years (P < 0.001) and increased by 0.63 years for grade 2-3 obesity (P = 0.63). Among women aged ≤60, YLL for grade 1 obesity decreased by 4.21 years (P < 0.001) and by 4.97 years (P < 0.001) for grade 2-3 obesity. In women aged >60, YLL for grade 1 obesity decreased by 3.98 years (P < 0.001) and by 2.64 years (P = 0.001) for grade 2-3 obesity. Grade 1 obesity's association with decreased longevity has reduced for older Caucasian men. For Caucasian women, there is evidence of a decline in the obesity YLL association across all ages.

How Much Should We Weigh for a Long and Healthy Life Span? The Need to Reconcile Caloric Restriction versus Longevity with Body Mass Index versus Mortality Data

Total caloric restriction (CR) without malnutrition is a well-established experimental approach to extend life span in laboratory animals. Although CR in humans is capable of shifting several endocrinological parameters, it is not clear where the minimum inflection point of the U-shaped curve linking body mass index (BMI) with all-cause mortality lies. The exact trend of this curve, when used for planning preventive strategies for public health is of extreme importance. Normal BMI ranges from 18.5 to 24.9; many epidemiological studies show an inverse relationship between mortality and BMI inside the normal BMI range. Other studies show that the lowest mortality in the entire range of BMI is obtained in the overweight range (25-29.9). Reconciling the extension of life span in laboratory animals by experimental CR with the BMI-mortality curve of human epidemiology is not trivial. In fact, one interpretation is that the CR data are identifying a known: "excess fat is deleterious for health"; although a second interpretation may be that: "additional leanness from a normal body weight may add health and life span delaying the process of aging." This short review hope to start a discussion aimed at finding the widest consensus on which weight range should be considered the "healthiest" for our species, contributing in this way to the picture of what is the correct life style for a long and healthy life span.

Mortality rate and overweight: Overblown or underestimated? A commentary on a recent meta-analysis of the associations of BMI and mortality

In this review, we discuss strengths and limitations of a recent rigorous systematic review and meta-analysis of the literature on associations of all-cause mortality with overweight and obesity. A perspective on its meaning and potential implications are provided. To move this field forward, we suggest modeling BMI as a continuous variable, switching to modeling longevity instead of mortality, and generating large publicly available datasets in broad and diverse populations for discerning the extent to which the BMI-mortality relationship differs between groups and over time. Randomized studies of obesity-related interventions that provide assessments of their actual effects on lifespan or mortality would have great value for helping to establish valid clinical and public health recommendations around weight loss and mortality.