Joshua A. Bell

Metabolically healthy obesity and risk of incident type 2 diabetes: a meta-analysis of prospective cohort studies

The risk of type 2 diabetes among obese adults who are metabolically healthy has not been established. We systematically searched Medline (1946–August 2013) and Embase (1947–August 2013) for prospective studies of type 2 diabetes incidence (defined by blood glucose levels or self‐report) among metabolically healthy obese adults (defined by body mass index [BMI] and normal cardiometabolic clustering, insulin profile or risk score) aged ≥18 years at baseline. We supplemented the analysis with an original effect estimate from the English Longitudinal Study of Ageing (ELSA), with metabolically healthy obesity defined as BMI ≥ 30 kg m−2 and <2 of hypertension, impaired glycaemic control, systemic inflammation, adverse high‐density lipoprotein cholesterol and adverse triglycerides. Estimates from seven published studies and ELSA were pooled using random effects meta‐analyses (1,770 healthy obese participants; 98 type 2 diabetes cases). The pooled adjusted relative risk (RR) for incident type 2 diabetes was 4.03 (95% confidence interval = 2.66–6.09) in healthy obese adults and 8.93 (6.86–11.62) in unhealthy obese compared with healthy normal‐weight adults. Although there was between‐study heterogeneity in the size of effects (I2 = 49.8%; P = 0.03), RR for healthy obesity exceeded one in every study, indicating a consistently increased risk across study populations. Metabolically healthy obese adults show a substantially increased risk of developing type 2 diabetes compared with metabolically healthy normal‐weight adults. Prospective evidence does not indicate that healthy obesity is a harmless condition.

Metabolically healthy obesity and risk of incident type 2 diabetes

The risk of type 2 diabetes among obese adults who are metabolically healthy has not been established. We systematically searched Medline (1946–August 2013) and Embase (1947–August 2013) for prospective studies of type 2 diabetes incidence (defined by blood glucose levels or self‐report) among metabolically healthy obese adults (defined by body mass index [BMI] and normal cardiometabolic clustering, insulin profile or risk score) aged ≥18 years at baseline. We supplemented the analysis with an original effect estimate from the English Longitudinal Study of Ageing (ELSA), with metabolically healthy obesity defined as BMI ≥ 30 kg m−2 and <2 of hypertension, impaired glycaemic control, systemic inflammation, adverse high‐density lipoprotein cholesterol and adverse triglycerides. Estimates from seven published studies and ELSA were pooled using random effects meta‐analyses (1,770 healthy obese participants; 98 type 2 diabetes cases). The pooled adjusted relative risk (RR) for incident type 2 diabetes was 4.03 (95% confidence interval = 2.66–6.09) in healthy obese adults and 8.93 (6.86–11.62) in unhealthy obese compared with healthy normal‐weight adults. Although there was between‐study heterogeneity in the size of effects (I2 = 49.8%; P = 0.03), RR for healthy obesity exceeded one in every study, indicating a consistently increased risk across study populations. Metabolically healthy obese adults show a substantially increased risk of developing type 2 diabetes compared with metabolically healthy normal‐weight adults. Prospective evidence does not indicate that healthy obesity is a harmless condition.

The natural course of healthy obesity over 20 years

Intense interest surrounds the “healthy” obese phenotype, which is defined as obesity in the absence of metabolic risk factor clustering [(1)][1]. Efforts to understand the cardiovascular consequences of healthy obesity are ongoing [(2)][2]; however, its conceptual validity and clinical value

Healthy obesity and objective physical activity

Background: Disease risk is lower in metabolically healthy obese adults than in their unhealthy obese counterparts. Studies considering physical activity as a modifiable determinant of healthy obesity have relied on self-reported measures, which are prone to inaccuracies and do not capture all movements that contribute to health. Objective: We aimed to examine differences in total and moderate-to-vigorous physical activity between healthy and unhealthy obese groups by using both self-report and wrist-worn accelerometer assessments. Design: Cross-sectional analyses were based on 3457 adults aged 60–82 y (77% male) participating in the British Whitehall II cohort study in 2012–2013. Normal-weight, overweight, and obese adults were considered “healthy” if they had <2 of the following risk factors: low HDL cholesterol, hypertension, high blood glucose, high triacylglycerol, and insulin resistance. Differences across groups in total physical activity, based on questionnaire and wrist-worn triaxial accelerometer assessments (GENEActiv), were examined by using linear regression. The likelihood of meeting 2010 World Health Organization recommendations for moderate-to-vigorous activity (≥2.5 h/wk) was compared by using prevalence ratios. Results: Of 3457 adults, 616 were obese [body mass index (in kg/m2) ≥30]; 161 (26%) of those were healthy obese. Obese adults were less physically active than were normal-weight adults, regardless of metabolic health status or method of physical activity assessment. Healthy obese adults had higher total physical activity than did unhealthy obese adults only when assessed by accelerometer (P = 0.002). Healthy obese adults were less likely to meet recommendations for moderate-to-vigorous physical activity than were healthy normal-weight adults based on accelerometer assessment (prevalence ratio: 0.59; 95% CI: 0.43, 0.79) but were not more likely to meet these recommendations than were unhealthy obese adults (prevalence ratio: 1.26; 95% CI: 0.89, 1.80). Conclusions: Higher total physical activity in healthy than in unhealthy obese adults is evident only when measured objectively, which suggests that physical activity has a greater role in promoting health among obese populations than previously thought.

Overweight, obesity, and risk of cardiometabolic multimorbidity: pooled analysis of individual-level data for 120 813 adults from 16 cohort studies from the USA and Europe

Summary Background Although overweight and obesity have been studied in relation to individual cardiometabolic diseases, their association with risk of cardiometabolic multimorbidity is poorly understood. Here we aimed to establish the risk of incident cardiometabolic multimorbidity (ie, at least two from: type 2 diabetes, coronary heart disease, and stroke) in adults who are overweight and obese compared with those who are a healthy weight. Methods We pooled individual-participant data for BMI and incident cardiometabolic multimorbidity from 16 prospective cohort studies from the USA and Europe. Participants included in the analyses were 35 years or older and had data available for BMI at baseline and for type 2 diabetes, coronary heart disease, and stroke at baseline and follow-up. We excluded participants with a diagnosis of diabetes, coronary heart disease, or stroke at or before study baseline. According to WHO recommendations, we classified BMI into categories of healthy (20·0–24·9 kg/m2), overweight (25·0–29·9 kg/m2), class I (mild) obesity (30·0–34·9 kg/m2), and class II and III (severe) obesity (≥35·0 kg/m2). We used an inclusive definition of underweight (<20 kg/m2) to achieve sufficient case numbers for analysis. The main outcome was cardiometabolic multimorbidity (ie, developing at least two from: type 2 diabetes, coronary heart disease, and stroke). Incident cardiometabolic multimorbidity was ascertained via resurvey or linkage to electronic medical records (including hospital admissions and death). We analysed data from each cohort separately using logistic regression and then pooled cohort-specific estimates using random-effects meta-analysis. Findings Participants were 120  813 adults (mean age 51·4 years, range 35–103; 71 445 women) who did not have diabetes, coronary heart disease, or stroke at study baseline (1973–2012). During a mean follow-up of 10·7 years (1995–2014), we identified 1627 cases of multimorbidity. After adjustment for sociodemographic and lifestyle factors, compared with individuals with a healthy weight, the risk of developing cardiometabolic multimorbidity in overweight individuals was twice as high (odds ratio [OR] 2·0, 95% CI 1·7–2·4; p<0·0001), almost five times higher for individuals with class I obesity (4·5, 3·5–5·8; p<0·0001), and almost 15 times higher for individuals with classes II and III obesity combined (14·5, 10·1–21·0; p<0·0001). This association was noted in men and women, young and old, and white and non-white participants, and was not dependent on the method of exposure assessment or outcome ascertainment. In analyses of different combinations of cardiometabolic conditions, odds ratios associated with classes II and III obesity were 2·2 (95% CI 1·9–2·6) for vascular disease only (coronary heart disease or stroke), 12·0 (8·1–17·9) for vascular disease followed by diabetes, 18·6 (16·6–20·9) for diabetes only, and 29·8 (21·7–40·8) for diabetes followed by vascular disease. Interpretation The risk of cardiometabolic multimorbidity increases as BMI increases; from double in overweight people to more than ten times in severely obese people compared with individuals with a healthy BMI. Our findings highlight the need for clinicians to actively screen for diabetes in overweight and obese patients with vascular disease, and pay increased attention to prevention of vascular disease in obese individuals with diabetes. Funding NordForsk, Medical Research Council, Cancer Research UK, Finnish Work Environment Fund, and Academy of Finland.

Metabolically healthy obesity: What is the role of sedentary behaviour?☆

Objective The role of sedentary behaviour in metabolically healthy obesity is unknown. We examined cross-sectional differences in television viewing time across metabolic and obesity phenotypes, hypothesizing that healthy obese individuals spend less time viewing television than their unhealthy counterparts. Methods A nationally representative sample of 4931 older adults in England (mean age 65.1; SD = 8.9 years) was drawn from the 2008/9 wave of the English Longitudinal Study of Ageing. Average weekly television viewing time was derived from two questions about weekday and weekend viewing. Obesity was defined as body mass index ≥ 30 kg/m2, and metabolically healthy as having < 2 metabolic abnormalities (low HDL-cholesterol, high triglycerides, high blood pressure, hyperglycaemia, high inflammation). Results After adjusting for covariates including chronic illness, functional limitations and physical activity, mean weekly viewing times were 4.7 (95% confidence interval 2.9, 6.5), 5.8 (2.5, 9.0) and 7.8 (5.7, 9.8) h higher in unhealthy non-obese, healthy obese, and unhealthy obese groups respectively, compared to the healthy non-obese group (p for heterogeneity < 0.001). Conclusions A common type of leisure-time sedentary behaviour varies across metabolic and obesity phenotypes. However, healthy obesity is not explained through differences in leisure-time sedentary behaviour.

Physical activity and adiposity markers at older ages: accelerometer vs questionnaire data.

Objective Physical activity is critically important for successful aging, but its effect on adiposity markers at older ages is unclear as much of the evidence comes from self-reported data on physical activity. We assessed the associations of questionnaire-assessed and accelerometer-assessed physical activity with adiposity markers in older adults. Design/Setting/Participants This was a cross-sectional study on 3940 participants (age range 60-83 years) of the Whitehall II study who completed a 20-item physical activity questionnaire and wore a wrist-mounted accelerometer for 9 days in 2012 and 2013. Measurements Total physical activity was estimated using metabolic equivalent hours/week for the questionnaire and mean acceleration for the accelerometer. Time spent in moderate-and-vigorous physical activity (MVPA) was also assessed by questionnaire and accelerometer. Adiposity assessment included body mass index, waist circumference, and fat mass index. Fat mass index was calculated as fat mass/height² (kg/m²), with fat mass estimated using bioimpedance. Results Greater total physical activity was associated with lower adiposity for all adiposity markers in a dose-response manner. In men, the strength of this association was 2.4 to 2.8 times stronger with the accelerometer than with questionnaire data. In women, it was 1.9 to 2.3 times stronger. For MVPA, questionnaire data in men suggested no further benefit for adiposity markers past 1 hour/week of activity. This was not the case for accelerometer-assessed MVPA where, for example, compared with men undertaking <1 hour/week of accelerometer-assessed MVPA, waist circumference was 3.06 (95% confidence interval 2.06–4.06) cm lower in those performing MVPA 1–2.5 hours/week, 4.69 (3.47–5.91) cm lower in those undertaking 2.5–4 hours/week, and 7.11 (5.93–8.29) cm lower in those performing ≥4 hours/week. Conclusions The association of physical activity with adiposity markers in older adults was stronger when physical activity was assessed by accelerometer compared with questionnaire, suggesting that physical activity might be more important for adiposity than previously estimated.

Incidence of Metabolic Risk Factors Among Healthy Obese Adults: 20-Year Follow-Up

There is growing evidence that obese adults without metabolic risk factor clustering (the so-called “healthy obese”) progress to unhealthy obesity over time [(1)][1]. However, the pathophysiological changes underlying the long-term transition into an unhealthy obese state have not been well

Physical activity patterns over 10 years in relation to body mass index and waist circumference: the Whitehall II cohort study.

Physical activity patterns over 10‐years in relation to changes in body mass index (BMI) and waist circumference (WC) were examined.

Association between inflammatory biomarkers and all-cause, cardiovascular and cancer-related mortality

BACKGROUND: The inflammatory biomarker α1-acid glycoprotein (AGP) was found to have the strongest association with 5-year mortality in a recent study of 106 biomarkers. We examined whether AGP is a better biomarker of mortality risk than the more widely used inflammatory biomarkers interleukin-6 (IL-6) and C-reactive protein (CRP). METHODS: We analyzed data for 6545 men and women aged 45–69 (mean 55.7) years from the Whitehall II cohort study. We assayed AGP, IL-6 and CRP levels from fasting serum samples collected in 1997–1999. Mortality followup was until June 2015. Cox regression analysis was used to model associations of inflammatory biomarkers with all-cause, cardiovascular and cancer-related mortality. RESULTS: Over the mean follow-up of 16.7 years, 736 deaths occurred, of which 181 were from cardiovascular disease and 347 from cancer. In the model adjusted for all covariates (age, sex, socioeconomic status, body mass index, health behaviours and chronic disease), AGP did not predict mortality beyond the first 5 years of follow-up; over this period, IL-6 and CRP had stronger associations with mortality. When we considered all covariates and biomarkers simultaneously, AGP no longer predicted all-cause mortality over the entire follow-up period (adjusted hazard ratio [HR] 0.99, 95% confidence interval [CI] 0.90–1.08). Only IL-6 predicted all-cause mortality (adjusted HR 1.22, 95% CI 1.12–1.33) and cancer-related mortality (adjusted HR 1.13, 95% CI 1.00–1.29) over the entire follow-up period, whereas CRP predicted only cardiovascular mortality (adjusted HR 1.30, 95% CI 1.06–1.61). INTERPRETATION: Our findings suggest that AGP is not a better marker of short-or long-term mortality risk than the more commonly used biomarkers IL-6 and CRP.