Midlife obesity and dementia: Meta‐analysis and adjusted forecast of dementia prevalence in the united states and china

Objective:

Obesity is a risk factor of dementia. Current forecasts of dementia prevalence fail to take the rising obesity prevalence into account.

Design and Methods:

Embase and Medline were searched for observational studies on the association between overweight (BMI 25‐30 kg/m²) or obesity (BMI > 30 kg/m²) and dementia and pooled the effect sizes by meta‐analysis. The population attributable risk (PAR) was calculated for different time points and adjusted them for confounders. Based on current prevalence rates of dementia and demographic forecasts, patient numbers were calculated and adjusted by the growth rates of PAR.

Results:

Compared to normal weight, midlife obesity increases the risk of dementia later in life (BMI 25‐30: RR = 1.34 [95% CI 1.08, 1.66], BMI > 30: RR = 1.91 [1.4, 2.62]). If obesity is included into forecast models, the prevalence of dementia is estimated to be 7.1 million (6.9, 7.3) and 11.3 million (10.9, 11.7) for the United States in 2030 and 2050, respectively. In China, the estimate is 13.1 million (12.8, 13.3) in 2030 and 26.2 million (25.1, 27.4) in 2050. These figures are 9% and 19% higher for the United States and China, respectively, than forecasts that rely solely on the demographic change.

Conclusion:

The past and ongoing increase in midlife obesity prevalence will contribute significantly to the future prevalence of dementia and public health measures to reduce midlife obesity are simultaneously primary prevention measures to reduce the risk of dementia.     

An Investigation into the Strength of the Association and Agreement Levels between Subjective and Objective Sleep Duration in Adolescents

Study Objectives

The majority of adolescent sleep research has utilized self-reported sleep duration and some have based information on a solitary question. Whilst some have claimed to have validated sleep survey data with objective actigraphy measures in adolescents, the statistical approach applied only demonstrates the strength of the association between subjective and objective sleep duration data and does not reflect if these different methods actually agree.

Methods

Data were collected as part of the Midlands Adolescents Schools Sleep Education Study (MASSES). Adolescents (n=225) aged 11-13 years provided estimates for weekday, weekend and combined sleep duration based on self-reported survey data, a 7-day sleep diary, and wrist-worn actigraphy.

Results

We assessed the strength of the relationship as well as agreement levels between subjective and objectively determined sleep duration (weekday, weekend and combined). Subjective diary sleep duration was significantly correlated with actigraphy estimates for weekday and weekend sleep duration r=0.30, p≤0.001 and r=0.31, p≤0.001 respectively. Pitman’s test demonstrated no significant difference in the variance between weekend sleep duration (r=0.09, p=0.16) and combined sleep duration (r=0.12, p=0.08) indicating acceptable agreement between actigraphy and sleep diary sleep duration only. Self-reported sleep duration estimates (weekday, weekend and combined) did not agree with actigraphy determined sleep duration.

Conclusions

Sleep diaries are a cost-effective alternative to survey/questionnaire data. Self-reported measures of sleep duration in adolescents do not agree with actigraphy measures and should be avoided where possible. Previous adolescent sleep studies that have utilized self-reported survey data may not provide a complete representation of sleep on the outcome measure of interest.     

Moderate‐To‐vigorous physical activity is associated with decreases in body mass index from ages 9 to 15 years

Objective:

The purpose of this study is to determine whether time spent in objectively measured physical activity is associated with change in body mass index (BMI) from ages 9 to 15.

Design and Methods:

The participants were enrolled in the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development (n = 938). At ages 9, 11, 12, and 15 the time spent in moderate‐to‐vigorous physical activity (MVPA) was objectively measured, and BMI was calculated (kg/m²). Longitudinal quantile regression was used to analyze the data. The 10th, 25th, 50th, 75th, and 90th BMI percentiles were modeled as the dependent variables with age and MVPA (h/day) modeled as predictors. Adjustment was also made for gender, race, sleep, healthy eating score, maternal education, and sedentary behavior.

Results:

A negative association between MVPA and change in BMI was observed at the 90th BMI percentile (?3.57, 95% CI ?5.15 to ?1.99 kg/m² per hour of MVPA). The negative association between time spent in MVPA and change in BMI was progressively weaker toward the 10th BMI percentile (?0.27, 95% CI ?0.62 to 0.07 kg/m² per hour of MVPA). The associations remained similar after adjusting for the covariates, and when the analyses were stratified by gender.

Conclusion:

Time spent in MVPA was negatively associated with change in BMI from age 9 to 15. The association was strongest at the upper tail of the BMI distribution, and increasing time spent in MVPA could help reduce the prevalence of childhood obesity.

     

Evening Chronotype Is Associated with Changes in Eating Behavior,More Sleep Apnea,and Increased Stress Hormones in Short Sleeping Obese Individuals

Background

Short sleep duration and decreased sleep quality are emerging risk factors for obesity and its associated morbidities. Chronotype, an attribute that reflects individual preferences in the timing of sleep and other behaviors, is a continuum from morningness to eveningness. The importance of chronotype in relation to obesity is mostly unknown. Evening types tend to have unhealthy eating habits and suffer from psychological problems more frequently than Morning types, thus we hypothesized that eveningness may affect health parameters in a cohort of obese individuals reporting sleeping less than 6.5 hours per night.

Methodology and Principal Findings

Baseline data from obese (BMI: 38.5±6.4 kg/m²) and short sleeping (5.8±0.8 h/night by actigraphy) participants (n = 119) of the Sleep Extension Study were analyzed (www.ClinicalTrials.gov, identifier {"type":"clinical-trial","attrs":{"text":"NCT00261898","term_id":"NCT00261898"}}NCT00261898). Assessments included the Horne and Ostberg Morningness-Eveningness questionnaire, a three-day dietary intake diary, a 14-day sleep diary, 14 days of actigraphy, and measurements of sleep apnea. Twenty-four hour urinary free cortisol, 24 h urinary norepinephrine and epinephrine levels, morning plasma ACTH and serum cortisol, fasting glucose and insulin, and lipid parameters were determined. Eveningness was associated with eating later in the day on both working and non-working days. Progression towards eveningness was associated with an increase in BMI, resting heart rate, food portion size, and a decrease in the number of eating occasions and HDL-cholesterol. Evening types had overtly higher 24 h urinary epinephrine and morning plasma ACTH levels, and higher morning resting heart rate than Morning types. In addition, Evening types more often had sleep apnea, independent of BMI or neck circumference.

Conclusions

Eveningness was associated with eating later and a tendency towards fewer and larger meals and lower HDL-cholesterol levels. In addition, Evening types had more sleep apnea and higher stress hormones. Thus, eveningness in obese, chronically sleep-deprived individuals compounds the cardiovascular risk associated with obesity.     

Greater screen time is associated with adolescent obesity: A longitudinal study of the BMI distribution from Ages 14 to 18

Objective:

Previous research has examined the association between screen time and average changes in adolescent body mass index (BMI). Until now, no study has evaluated the longitudinal relationship between screen time and changes in the BMI distribution across mid to late adolescence.

Design and Methods:

Participants (n = 1,336) were adolescents who were followed from age 14 to age 18 and surveyed every 6 months. Time spent watching television/videos and playing video games was self‐reported (<1 h day^?1, 1 h day^?1, 2 h day^?1, 3 h day^?1, 4 h day^?1, or 5+ h day^?1). BMI (kg m^?2) was calculated from self‐reported height and weight. Longitudinal quantile regression was used to model the 10th, 25th, 50th, 75th, and 90th BMI percentiles as dependent variables. Study wave and screen time were the main predictors, and adjustment was made for gender, race, maternal education, hours of sleep, and physical activity.

Results:

Increases at all the BMI percentiles over time were observed, with the greatest increase observed at the 90th BMI percentile. Screen time was positively associated with changes in BMI at the 50th (0.17, 95% CI: 0.06, 0.27), 75th (0.31, 95% CI: 0.10, 0.52), and 90th BMI percentiles (0.56, 95% CI: 0.27, 0.82). No associations were observed between screen time and changes at the 10th and 25th BMI percentiles.

Conclusions:

Positive associations between screen time and changes in the BMI at the upper tail of the BMI distribution were observed. Therefore, lowering screen time, especially among overweight and obese adolescents, could contribute to reducing the prevalence of adolescent obesity.

     

Prevalence of Sleep Apnea and Electrocardiographic Disturbances in Morbidly Obese Patients

Objective: To determine the prevalence of sleep apnea in morbidly obese patients and its relationship with cardiac arrhythmias. Research Methods and Procedures: Fifty‐two consecutive morbidly obese (body mass index ≥ 40 kg/m²) outpatients from the Obesity Clinic of the National Institute of Nutrition Salvador Zubirán underwent two nights of polysomnography with standard laboratory techniques. Electrocardiographic polysomnography signals (Lead II) were evaluated by two experienced cardiologists, and sleep complaints were measured with a standard sleep questionnaire (Sleep Disorders Questionnaire). In order to make comparisons between groups with different severities of sleep‐disordered breathing, we classified the patients in four groups using the apnea‐hypopnea index (AHI): Group 1, AHI 5 < 15 (n = 10); Group 2, AHI 15 < 30 (n = 10); Group 3, AHI 30 < 65 (n = 14); Group 4, AHI ≥ 65 (n = 17). Results: A wide range of sleep‐disordered breathing, ranging from AHI of 2.5 to 128.9 was found. Ninety‐eight percent of the sample (n = 51) had an AHI ≥ 5 (mean = 51 ± 37), and 33% had severe sleep apnea with AHI ≥ 65 with a mean nocturnal desaturation time of <65% over 135 minutes. Electrocardiographic abnormalities were present in 31% of the patients. Cardiac rhythm alterations showed an association with the level of sleep‐disordered breathing and oxygen desaturation. Discussion: We conclude that there is a high prevalence of sleep apnea in morbidly obese patients and that the risk for cardiac arrhythmias increases in this population in the presence of a severe sleep apnea (AHI ≥ 65) with severe oxygen desaturation (Sao ₂ ≤ 65%).     

Habitual Sleep Measures are Associated with Overall Body Fat,and not Specifically with Visceral Fat,in Men and Women

Objective

This study aimed to investigate the associations of sleep duration and sleep quality with visceral adipose tissue (VAT) in middle‐aged individuals.

Methods

In this cross‐sectional analysis of baseline measurements of the Netherlands Epidemiology of Obesity (NEO) study, participants underwent anthropometry and completed the Pittsburgh Sleep Quality Index (PSQI) for assessing short sleep duration (as sex‐specific age‐adjusted percentiles) and poor quality (PSQI > 5). VAT was assessed by magnetic resonance imaging in a random subgroup. We performed linear regression analyses to examine associations of short sleep and poor sleep with measures of body fat, adjusted for confounding, including total body fat in models with VAT.

Results

A total of 5,094 participants (52% women; mean age of 56 [SD 6] years), 1,947 of whom had VAT measurements, were analyzed. The difference in VAT between poor sleep (PSQI > 5) and good sleep (PSQI ≤ 5) was 7.2cm² (95% CI: 1.2‐13.8) in women and 16.1cm² (95% CI: 6.2‐26.0) in men. These differences attenuated toward the null after the adjustment for total body fat. Similar patterns of associations were observed for short sleep (lowest 10% compared with median 60%).

Conclusions

Our results suggest that measures of sleep are not specifically associated with a higher amount of VAT.     

Body Mass Index,Mortality, and Gender Difference in Advanced Chronic Kidney Disease

Background and Aim

A higher body mass index (BMI) appears to be reversely associated with mortality in dialysis patients. Moreover, although women have better survival in chronic kidney disease (CKD), this survival advantage is cancelled in dialysis. The association between BMI and mortality and the gender difference remain controversial in advanced CKD.

Methods

This study enrolled 3,320 patients (1,938 men and 1,382 women) from southern Taiwan who had CKD stages 3–5 with a BMI of 15.0–35.0 kg/m².

Results

During a median 2.9-year follow-up, there were 328 (16.9%) all-cause mortality and 319 (16.5%) cardiovascular (CV) events and death in male patients, 213 (15.4%) all-cause mortality and 224 (16.2%) CV events and death in female patients. Compared with the reference BMI of 27.6–30.0 kg/m² in an adjusted Cox model, lower-BMI groups in men, BMI 15.0–20.0 kg/m² and 20.1–22.5 kg/m², were associated with higher risks of all-cause mortality: hazard ratios (HRs) 3.19 (95% confidence interval [CI], 1.97–5.18) and 2.01 (95% CI, 1.29–3.14), respectively. Higher-BMI group in men, BMI 30.1–35.0 kg/m², was associated with a higher risk of all-cause mortality: HR 1.72 (95% CI, 1.02–2.96). Likewise, lower- and higher-BMI groups in men were associated with a higher risk of CV events and death. In women, these associations between BMI and poor outcomes were not observed.

Conclusions

In advanced CKD, there was a reverse J-shaped association between BMI and all-cause mortality, and a U-shaped association between BMI and CV outcomes in men. Neutral associations between BMI and poor outcomes were detected in women. Gender could modify the effect of BMI on mortality in patients with CKD.     

Sleep apnea modifies the long‐term impact of surgically induced weight loss on cardiac function and inflammation

Objective:

Obesity is frequently associated with obstructive sleep apnea (OSA). Both conditions are proinflammatory and proposed to deteriorate cardiac function. We used a nested cohort study design to evaluate the long‐term impact of bariatric surgery on OSA and how weight loss and OSA relate to inflammation and cardiac performance.

Design and Methods:

At 10‐year follow‐up in the Swedish Obese Subjects (SOS) study, we identified 19 obese subjects (BMI 31.2 ± 5.3 kg m^?2), who following bariatric surgery at SOS‐baseline had displayed sustained weight losses (surgery group), and 20 obese controls (BMI 42.0 ± 6.2 kg m^?2), who during the same time‐period had maintained stable weight (control group). All study participants underwent overnight polysomnography examination, echocardiography and analysis of inflammatory markers.

Results:

The surgery group displayed a lower apnea hypopnea index (AHI) (19.9 ± 21.5 vs. 37.8 ± 27.7 n/h, P = 0.013), lower inflammatory activity (hsCRP 2.3 ± 3.0 vs. 7.2 ± 5.0 mg L^?1, P < 0.001), reduced left ventricular mass (165 ± 22 vs. 207 ± 22 g, P < 0.001) and superior left ventricular diastolic function (E/A ratio 1.24 ± 1.10 vs. 1.05 ± 0.20, P = 0.006) as compared with weight stable obese controls. In multiple regression analyses including all subjects (n = 39) and controlling for BMI, the AHI remained independently associated with hsCRP (β = 0.09, P < 0.001), TNF‐α (β = 0.03, P = 0.031), IL‐6 (β = 0.01, P = 0.007), IL 10 (β = ?0.06; P = 0.018), left ventricular mass (β = 0.64, P < 0.001), left atrial area (β = 0.08, P = 0.002), pulmonary artery pressure (β = 0.08, P = 0.011) and E/E_a ratio (β = 0.04, P = 0.021).

Conclusions:

Patients with sustained weight loss after bariatric surgery display less severe sleep apnea, reduced inflammatory activity, and enhanced cardiac function. Persisting sleep apnea appears to limit the beneficial effect of weight loss on inflammation and cardiac performance.

     

Aerobic exercise and snoring in overweight children: a randomized controlled trial

Objective: To determine whether regular aerobic exercise improves symptoms of sleep‐disordered breathing in overweight children, as has been shown in adults. Research Methods and Procedures: Healthy but overweight (BMI ≥85th percentile) 7‐ to 11‐year‐old children were recruited from public schools for a randomized controlled trial of exercise effects on diabetes risk. One hundred children (53% black, 41% male) were randomly assigned to a control group (n = 27), a low‐dose exercise group (n = 36), or a high‐dose exercise group (n = 37). Exercise groups underwent a 13 ± 1.5 week after‐school program that provided 20 or 40 minutes per day of aerobic exercise (average heart rate = 164 beats per minute). Group changes were compared on BMI z‐score and four Pediatric Sleep Questionnaire scales: Snoring, Sleepiness, Behavior, and a summary scale, Sleep‐Related Breathing Disorders. Analyses were adjusted for age. Results: Both the high‐dose and low‐dose exercise groups improved more than the control group on the Snoring scale. The high‐dose exercise group improved more than the low‐dose exercise and control groups on the summary scale. No group differences were found for changes on Sleepiness, Behavior, or BMI z‐score. At baseline, 25% screened positive for sleep‐disordered breathing; half improved to a negative screen after intervention. Discussion: Regular vigorous exercise can improve snoring, a symptom of sleep‐disordered breathing, in overweight children. Aerobic exercise programs may be valuable for prevention and treatment of sleep‐disordered breathing in overweight children.     

Prediction of measured weight from self‐reported weight was not improved after stratification by body mass index

Objective:

Self‐reported weight may underestimate measured weight. Researchers have tried to reduce the error using statistical models to predict weight from self‐reported weight. We investigate whether deriving equations within separate BMI categories improves the prediction of weight compared with an equation derived regardless of an individual's BMI.

Design and Methods:

The analysis included self‐reported and measured data from 20,536 individuals participating in the EPIC‐Norfolk study. In a derivation set (n = 15,381) two approaches were used to predict weight from self‐reported weight: (1) using a linear regression model with measured weight as outcome and self‐reported weight and age as predictors, and (2) using the same model fit separately within 3 strata defined by BMI (< 25, 25‐30, ≥30 kg m^?2). The performance of these approaches was assessed in a validation set (n = 5,155). Measured weight was compared to self‐reported weight and predicted weight.

Results:

Self‐reported weight underestimated measured weight (P < 0.0001): mean difference ?1.2 ± 3.1 kg (men), ?1.3 ± 2.5 kg (women). Underestimation was greater in obese participants (P < 0.0001). Predicted weight using approach 1 was not significantly different from measured weight (P < 0.05). However, in individuals with BMI < 25 kg m^?2, weight was overestimated in men (0.90 ± 3.87 kg) and women (0.57 ± 2.06 kg), but underestimated in overweight (?0.29 ± 3.58, ?0.20 ± 2.62 kg) and obese (?1.46 ± 5.05 kg, ?0.73 ± 3.54 kg) men and women.

Conclusions:

Using separate prediction equations in strata of BMI did not further improve prediction of weight. In conclusion, predicted weight was closer to measured weight compared with self‐reported weight, but using equations derived in strata of BMI did not further improve the prediction and are not recommended for prediction of weight.

     

Reduced physical activity in adults at risk for type 2 diabetes who curtail their sleep

Adults with parental history of type 2 diabetes have high metabolic morbidity, which is exacerbated by physical inactivity. Self‐reported sleep <6 h/day is associated with increased incidence of obesity and diabetes, which may be mediated in part by sleep‐loss‐related reduction in physical activity. We examined the relationship between habitual sleep curtailment and physical activity in adults with parental history of type 2 diabetes. Forty‐eight young urban adults with parental history of type 2 diabetes (27 F/21 M; mean (s.d.) age 26 (4) years; BMI 23.8 (2.5) kg/m²) each completed 13 (2) days of sleep and physical activity monitoring by wrist actigraphy and waist accelerometry while following their usual lifestyle at home. Laboratory polysomnography was used to screen for sleep disorders. The primary outcome of the study was the comparison of total daily activity counts between participants with habitual sleep <6 vs. ≥6 h/night. Secondary measures included daily time spent sedentary and in light, moderate, and vigorous physical activity. Short sleepers had no sleep abnormalities and showed signs of increased sleep pressure consistent with a behavioral pattern of habitual sleep curtailment. Compared to participants who slept ≥6 h/night, short sleepers had 27% fewer daily activity counts (P = 0.042), spent less time in moderate‐plus‐vigorous physical activity (?43 min/day; P = 0.010), and remained more sedentary (+69 min/day; P = 0.026). Our results indicate that young urban adults with parental history of type 2 diabetes who habitually curtail their sleep have less daily physical activity and more sedentary living, which may enhance their metabolic risk.     

The Association Between Sleep Duration and General and Abdominal Obesity in Koreans: Data From the Korean National Health and Nutrition Examination Survey, 2001 and 2005

This study aimed to investigate the association between self‐reported sleep duration and general and abdominal obesity in Korean adults. A total of 8,717 adults aged 20–65 years from the Korean National Health and Nutrition Examination Survey (KNHANES) 2001 and 2005 were included. General obesity was defined as BMI ≥25 kg/m² and abdominal obesity as waist circumference ≥90 cm in men and ≥85 cm in women. To control for sociodemographic and lifestyle factors and comorbidities, multivariable logistic regression was used to calculate the adjusted odds ratios (ORs) and 95% confidence intervals (CIs) of general and abdominal obesity across the following sleep duration categories: ≤5, 6, 7, 8, and ≥9 h/day. Mean sleep duration (±s.d.) was 6.9 ± 1.3 h. Those sleeping ≤5 h/day had the highest BMI and waist circumference compared with those sleeping 7, 8, or ≥9 h/day (P < 0.05 for all comparisons). After controlling for sociodemographic and lifestyle factors, the adjusted ORs (95% CIs) associated with sleeping ≤5 h/day (vs. 7 h/day) were 1.25 (1.06–1.48) for general obesity and 1.24 (1.03–1.48) for abdominal obesity. Further adjustment for hypertension and diabetes mellitus did not significantly affect the associations. These data suggest that short sleep duration is significantly associated with a modest increase in general and abdominal obesity in Korean adults.     

Racial/ethnic differences in the prevalence of gestational diabetes mellitus and maternal overweight and obesity,by Nativity,Florida, 2004‐2007

Objective:

We examined the risk of gestational diabetes mellitus (GDM) among foreign‐born and U.S.‐born mothers by race/ethnicity and BMI category.

Design and Method:

We used 2004‐2007 linked birth certificate and maternal hospital discharge data of live, singleton deliveries in Florida to compare GDM risk among foreign‐born and U.S.‐born mothers by race/ethnicity and BMI category. We examined maternal BMI and controlled for maternal age, parity, and height.

Results:

Overall, 22.4% of the women in our study were foreign born. The relative risk (RR) of GDM among women who were overweight or obese (BMI ≥ 25.0 kg m^?2) was higher than among women with normal BMI (18.5‐24.9 kg m^?2) regardless of nativity, ranging from 1.3 (95% confidence interval (CI) = 1.0, 1.9) to 3.8 (95% CI = 2.1, 7.2).Foreign‐born women also had a higher GDM risk than U.S.‐born women, with RR ranging from 1.1 (95% CI = 1.1, 1.2) to 2.1 (95% CI = 1.4, 3.1). This finding was independent of BMI, age, parity, and height for all racial/ethnicity groups.

Conclusions:

Although we found differences in age, parity, and height by nativity, these differences did not substantially reduce the increased risk of GDM among foreign‐born mothers. Health practitioners should be aware of and have a better understanding of how race/ethnicity and nativity can affect women with a high risk of GDM. Although BMI is a major risk factor for GDM, it does not appear to be associated with race/ethnicity or nativity.

     

No association between leptin levels and sleep duration or quality in obese adults

Previous research in lean subjects has found lower leptin levels associated with shorter sleep duration. Since leptin levels are higher and some of the actions of leptin are impaired in obese individuals, one cannot assume that sleep will be similarly associated with leptin in obese individuals. The aim of this paper was to examine the cross-sectional association between habitual sleep duration and quality and plasma leptin levels in a sample of 80 obese men and premenopausal women aged 18-50 years. Leptin levels (ng/ml) were assayed on a fasting blood sample taken in the morning. We calculated a relative leptin level by dividing leptin by body fat percentage. Sleep duration and sleep efficiency were measured by 2 weeks of wrist actigraphy and respiratory disturbance index (RDI), a measure of sleep disordered breathing, was assessed by a portable screening device on a single night. Mean leptin levels and body fat percentage were higher in women than men (P < 0.001), however, mean RDI was higher in men (P = 0.01). There were no significant associations between relative leptin level and any of the sleep measures, including sleep duration, sleep efficiency, and sleep disordered breathing. There was also no difference between men and women in the association between sleep and leptin. In conclusion, contrary to what has been reported in other studies, measures of sleep duration and quality were not associated with leptin levels in our sample of obese adults.     

Body Mass Index and Risk of Parkinson’s Disease: A Dose-Response Meta-Analysis of Prospective Studies

Background

A number of epidemiologic studies examining the relationship between body mass index (BMI) and the future occurrence of Parkinson’s disease (PD) reported largely inconsistent findings. We conducted a dose-response meta-analysis of prospective studies to clarify this association.

Methods

Eligible prospective studies were identified by a search of PubMed and by checking the references of related publications. The generalized least squares trend estimation was employed to compute study-specific relative risks (RR) and 95% confidence intervals (CI) for an increase in BMI of 5 kg/m², and the random-effects model was used to compute summary RR and 95% CI.

Results

A total of 10 prospective studies were included in the final analysis. An increase in BMI of 5 kg/m² was not associated with PD risk, with a summary RR of 1.00 (95% CI = 0.89-1.12). Results of subgroup analysis found similar results except for a week positive association in studies that adjusted for alcohol consumption (RR = 1.13, 95% CI = 0.99-1.29), and a week inverse association in studies that did not (RR = 0.90, 95% CI = 0.78-1.04). In a separate meta-analysis, no significant association between overweight (25 kg/m² ≤ BMI ≤29.9 kg/m²), obesity (BMI≥30 kg/m²) or excess weight (BMI≥25 kg/m²) and PD risk was observed.

Conclusion

This meta-analysis does not support the notion that higher BMI materially increases PD risk. However, a week positive BMI-PD association that may be masked by confounders still cannot be excluded, and future prospective studies with a good control for potential confounding factors are needed.     

The Effect of Elevated Body Mass Index on Ischemic Heart Disease Risk: Causal Estimates from a Mendelian Randomisation Approach

Background

Adiposity, assessed as elevated body mass index (BMI), is associated with increased risk of ischemic heart disease (IHD); however, whether this is causal is unknown. We tested the hypothesis that positive observational associations between BMI and IHD are causal.

Methods and Findings

In 75,627 individuals taken from two population-based and one case-control study in Copenhagen, we measured BMI, ascertained 11,056 IHD events, and genotyped FTO(rs9939609), MC4R(rs17782313), and TMEM18(rs6548238). Using genotypes as a combined allele score in instrumental variable analyses, the causal odds ratio (OR) between BMI and IHD was estimated and compared with observational estimates. The allele score-BMI and the allele score-IHD associations used to estimate the causal OR were also calculated individually. In observational analyses the OR for IHD was 1.26 (95% CI 1.19–1.34) for every 4 kg/m² increase in BMI. A one-unit allele score increase associated with a 0.28 kg/m² (95 CI% 0.20–0.36) increase in BMI and an OR for IHD of 1.03 (95% CI 1.01–1.05) (corresponding to an average 1.68 kg/m² BMI increase and 18% increase in the odds of IHD for those carrying all six BMI increasing alleles). In instrumental variable analysis using the same allele score the causal IHD OR for a 4 kg/m² increase in BMI was 1.52 (95% CI 1.12–2.05).

Conclusions

For every 4 kg/m² increase in BMI, observational estimates suggested a 26% increase in odds for IHD while causal estimates suggested a 52% increase. These data add evidence to support a causal link between increased BMI and IHD risk, though the mechanism may ultimately be through intermediate factors like hypertension, dyslipidemia, and type 2 diabetes. This work has important policy implications for public health, given the continuous nature of the BMI-IHD association and the modifiable nature of BMI. This analysis demonstrates the value of observational studies and their ability to provide unbiased results through inclusion of genetic data avoiding confounding, reverse causation, and bias. Please see later in the article for the Editors'' Summary     

Obesity and Quality of Life: Mediating Effects of Pain and Comorbidities

Objective: To estimate the association between body mass index (BMI) and health‐related quality of life (HRQL) and examine whether joint pain and obesity‐related comorbidities mediate the BMI‐HRQL association. Research Methods and Procedures: Population‐based survey data from the 1999 Behavioral Risk Factor Surveillance Survey. Adults (N = 155, 989) were classified according to BMI as underweight (<18.5 kg/m²), desirable weight (18.5 to 24.9 kg/m²), overweight (25 to 29.9 kg/m²), obese class I (30 to 34.9 kg/m²), obese class II (35 to 39.9 kg/m²), and obese class III (≥40 kg/m²). Data including general health status, unhealthy days in the past 30 caused by physical problems and mental problems, and total unhealthy days in the past 30 were collected. Results: After adjusting for age, sex, race, smoking, education, and income, we observed J‐shaped associations between BMI and HRQL. Compared with desirable weight adults, underweight, overweight, and obesity classes I, II, and III adults [odds ratio (OR) = 1.57, 1.19, 1.95, 2.72, and 4.36, respectively] were significantly (p < 0.001) more likely to report fair/poor general health status. For unhealthy days caused by physical problems, the corresponding ORs were 1.51, 1.15, 1.66, 2.27, and 3.61 (p < 0.001). For unhealthy days caused by mental problems, the ORs were 1.35, 1.14 1.43, 1.57, and 2.25 (p < 0.001). For total unhealthy days, the corresponding ORs were 1.27, 1.09, 1.37, 1.73, and 2.46 (p < 0.01). Adding joint pain and obesity‐related comorbidities into models attenuated BMI‐HRQL associations. Discussion: Associations between BMI and HRQL indices were J‐shaped. Joint pain and comorbidities may mediate BMI‐HRQL associations.     

Eating Frequency is Associated With Energy Intake but Not Obesity in Midlife Women

Midlife women tend to gain weight with age, thus increasing risk of chronic disease. The purpose of this study was to examine associations between overweight/obesity and behavioral factors, including eating frequency, in a cross‐sectional national sample of midlife women (n = 1,099) (mean age = 49.7 years, and BMI = 27.7 kg/m²). Eating behaviors and food and nutrient intakes were based on a mailed 1‐day food record. BMI was calculated from self‐reported height and weight, and level of physical activity was assessed by self‐reported questionnaire. After exclusion of low‐energy reporters (32% of sample), eating frequency was not associated with overweight/obesity (P > 0.05) and was not different between BMI groups (normal, 5.21 ± 1.79; overweight, 5.16 ± 1.74; obese, 5.12 ± 1.68, P = 0.769). Adjusted logistic regression showed that eating frequency, snacking frequency, breakfast consumption, eating after 10 pm and consuming meals with children or other adults were not significantly associated with overweight/obesity. Total energy intake increased as eating frequency increased in all BMI groups, however, obese women had greater energy intake compared to normal weight women who consumed the same number of meals and snacks. Intake of fruit and vegetables, whole grains, dietary fiber, dairy, and added sugars also increased as eating frequency increased. While eating frequency was not associated with overweight/obesity, it was associated with energy intake. Thus, addressing total energy intake rather than eating frequency may be more appropriate to prevent weight gain among midlife women.