Background: Previous trials of binders in chronic kidney disease (CKD) stages 3–5 have shown only modest changes in serum phosphate but evaluated morning phosphate. It is unknown whether a circadian ...pattern of phosphate concentrations exists in CKD and is modifiable by dietary manipulation.Objectives: We determined the circadian pattern of serum phosphate concentrations in CKD and whether it was modifiable by altering absorbable phosphate.Design: This was a crossover feeding study in 11 CKD participants (estimated glomerular filtration rate: 30–45 mL · min−1 · 1.73 m−2) and 4 healthy control subjects. All subjects received high-phosphate (2500 mg/d), normal-phosphate (1500 mg/d), and low-phosphate (1000 mg/d plus 1000 mg lanthanum carbonate 3 times/d) diets for 5 d followed by a 10-d washout. After each 5-d feed, phosphate and other measurements were made every 4 h over 1 day.Results: In CKD participants who consumed the high-phosphate diet, there were circadian changes in phosphate with lowest concentrations (±SDs) at 0800 (4.2 ± 0.5 mg/dL) and 2 peaks at 1600 and 0400 (4.5 ± 0.8 and 4.4 ± 0.6 mg/dL, respectively), which were similar to those in healthy controls. Results with the normal-phosphate diet were similar. The low-phosphate diet altered the circadian rhythm (P = 0.02) such that 0400 and 1600 peaks were absent. Differences in phosphate for lowest- compared with highest-phosphate diets were smallest at 0800 and largest at 1600 (0.5 compared with 1.0 mg/dL) in CKD. Circadian changes in phosphate were not explained by urine phosphate excretion, parathyroid hormone, or fibroblast growth factor-23.Conclusions: A circadian pattern of serum phosphate is observed in CKD with lowest concentrations at 0800 and highest at 1600 and 0400. This circadian pattern is modifiable by phosphate intake and most evident at 1600. Future intervention studies targeting intestinal phosphate absorption should consider afternoon phosphate measurements.
BACKGROUND: Chronic kidney disease is a major worldwide problem. Although epidemiologic and experimental studies suggest that n-3 long-chain polyunsaturated fatty acid (n-3 LCPUFA) supplementation ...may prevent or slow the progression of kidney disease, evidence from clinical trials is inconsistent. OBJECTIVE: The objective was to combine evidence from controlled clinical trials to assess the effect of n-3 LCPUFA supplementation on the change in urine protein excretion (UPE) and on glomerular filtration rate (GFR). DESIGN: We performed a meta-analysis of clinical trials that tested the effect of n-3 LCPUFA supplementation on UPE, a marker of kidney damage, and on GFR, a marker of kidney function. A random-effects model was used to pool SD effect size (Cohen's d) across studies. RESULTS: Seventeen trials with 626 participants were included in the meta-analysis. Most trials focused on patients with a single underlying diagnosis: IgA nephropathy (n = 5), diabetes (n = 7), or lupus nephritis (n = 1). The dose of n-3 LCPUFAs ranged from 0.7 to 5.1 g/d, and the median follow-up was 9 mo. In the pooled analysis, there was a greater reduction in UPE in the n-3 LCPUFA group than in the control group: Cohen's d for all trials was -0.19 (95% CI: -0.34, -0.04; P = 0.01). In a patient with 1 g UPE/d , this corresponds to a reduction of 190 mg/d. Effects on GFR were reported in 12 trials. The decline in GFR was slower in the n-3 LCPUFA group than in the control group, but this effect was not significant (0.11; 95% CI: -0.07, 0.29; P = 0.24). CONCLUSIONS: In our meta-analysis, use of n-3 LCPUFA supplements reduced UPE but not the decline in GFR. However, small numbers of participants in trials, different methods of assessing proteinuria and GFR, and inconsistent data reporting limit the strength of these conclusions. Large, high-quality trials with clinical outcomes are warranted.
The US Centers for Disease Control and Prevention have identified a lack of encouragement, support, or companionship from family and friends as a major barrier to physical activity. To overcome this ...barrier, online social networks are now actively leveraging principles of companion social support in novel ways.
The aim was to evaluate the functionality, features, and usability of existing online social networks which seek to increase physical activity and fitness among users by connecting them to physical activity partners, not just online, but also face-to-face.
In September 2012, we used 3 major databases to identify the website addresses for relevant online social networks. We conducted a Google search using 8 unique keyword combinations: the common keyword "find" coupled with 1 of 4 prefix terms "health," "fitness," "workout," or "physical" coupled with 1 of 2 stem terms "activity partners" or "activity buddies." We also searched 2 prominent technology start-up news sites, TechCrunch and Y Combinator, using 2 unique keyword combinations: the common keyword "find" coupled with 1 of 2 stem terms "activity partners" and "activity buddies." Sites were defined as online social health activity networks if they had the ability to (1) actively find physical activity partners or activities for the user, (2) offer dynamic, real-time tracking or sharing of social activities, and (3) provide virtual profiles to users. We excluded from our analysis sites that were not Web-based, publicly available, in English, or free.
Of the 360 initial search results, we identified 13 websites that met our complete criteria of an online social health activity network. Features such as physical activity creation (13/13, 100%) and private messaging (12/13, 92%) appeared almost universally among these websites. However, integration with Web 2.0 technologies such as Facebook and Twitter (9/13, 69%) and the option of direct event joining (8/13, 62%) were not as universally present. Largely absent were more sophisticated features that would enable greater usability, such as interactive engagement prompts (3/13, 23%) and system-created best fit activities (3/13, 23%).
Several major online social networks that connect users to physical activity partners currently exist and use standardized features to achieve their goals. Future research is needed to better understand how users utilize these features and how helpful they truly are.
Debate over the cardiometabolic risk associated with metabolically healthy obesity (MHO) continues. Many studies have investigated this relationship by examining MHO at baseline with longitudinal ...follow-up, with inconsistent results.
The authors hypothesized that MHO at baseline is transient and that transition to metabolic syndrome (MetS) and duration of MetS explains heterogeneity in incident cardiovascular disease (CVD) and all-cause mortality.
Among 6,809 participants of the MESA (Multi-Ethnic Study of Atherosclerosis) the authors used Cox proportional hazards and logistic regression models to investigate the joint association of obesity (≥30 kg/m2) and MetS (International Diabetes Federation consensus definition) with CVD and mortality across a median of 12.2 years. We tested for interaction and conducted sensitivity analyses for a number of conditions.
Compared with metabolically healthy normal weight, baseline MHO was not significantly associated with incident CVD; however, almost one-half of those participants developed MetS during follow-up (unstable MHO). Those who had unstable MHO had increased odds of CVD (odds ratio OR: 1.60; 95% confidence interval CI: 1.14 to 2.25), compared with those with stable MHO or healthy normal weight. Dose response for duration of MetS was significantly and linearly associated with CVD (1 visit with MetS OR: 1.62; 95% CI: 1.27 to 2.07; 2 visits, OR: 1.92; 95% CI: 1.48 to 2.49; 3+ visits, OR: 2.33; 95% CI: 1.89 to 2.87; p value for trend <0.001) and MetS mediated approximately 62% (44% to 100%) of the relationship between obesity at any point during follow-up and CVD.
Metabolically healthy obesity is not a stable or reliable indicator of future risk for CVD. Weight loss and lifestyle management for CVD risk factors should be recommended to all individuals with obesity.
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Objective
To examine the relationship between local food environments and obesity and assess the quality of studies reviewed.
Methods
Systematic keyword searches identified studies from US and Canada ...that assessed the relationship of obesity to local food environments. We applied a quality metric based on design, exposure and outcome measurement, and analysis.
Results
We identified 71 studies representing 65 cohorts. Overall, study quality was low; 60 studies were cross‐sectional. Associations between food outlet availability and obesity were predominantly null. Among non‐null associations, we saw a trend toward inverse associations between supermarket availability and obesity (22 negative, 4 positive, 67 null) and direct associations between fast food and obesity (29 positive, 6 negative, 71 null) in adults. We saw direct associations between fast food availability and obesity in lower income children (12 positive, 7 null). Indices including multiple food outlets were most consistently associated with obesity in adults (18 expected, 1 not expected, 17 null). Limiting to higher quality studies did not affect results.
Conclusions
Despite the large number of studies, we found limited evidence for associations between local food environments and obesity. The predominantly null associations should be interpreted cautiously due to the low quality of available studies.
Overweight and obesity are epidemic among persons with serious mental illness, yet weight-loss trials systematically exclude this vulnerable population. Lifestyle interventions require adaptation in ...this group because psychiatric symptoms and cognitive impairment are highly prevalent. Our objective was to determine the effectiveness of an 18-month tailored behavioral weight-loss intervention in adults with serious mental illness.
We recruited overweight or obese adults from 10 community psychiatric rehabilitation outpatient programs and randomly assigned them to an intervention or a control group. Participants in the intervention group received tailored group and individual weight-management sessions and group exercise sessions. Weight change was assessed at 6, 12, and 18 months.
Of 291 participants who underwent randomization, 58.1% had schizophrenia or a schizoaffective disorder, 22.0% had bipolar disorder, and 12.0% had major depression. At baseline, the mean body-mass index (the weight in kilograms divided by the square of the height in meters) was 36.3, and the mean weight was 102.7 kg (225.9 lb). Data on weight at 18 months were obtained from 279 participants. Weight loss in the intervention group increased progressively over the 18-month study period and differed significantly from the control group at each follow-up visit. At 18 months, the mean between-group difference in weight (change in intervention group minus change in control group) was -3.2 kg (-7.0 lb, P=0.002); 37.8% of the participants in the intervention group lost 5% or more of their initial weight, as compared with 22.7% of those in the control group (P=0.009). There were no significant between-group differences in adverse events.
A behavioral weight-loss intervention significantly reduced weight over a period of 18 months in overweight and obese adults with serious mental illness. Given the epidemic of obesity and weight-related disease among persons with serious mental illness, our findings support implementation of targeted behavioral weight-loss interventions in this high-risk population. (Funded by the National Institute of Mental Health; ACHIEVE ClinicalTrials.gov number, NCT00902694.).
South Asians are at high risk of metabolic syndrome, and dietary patterns may influence this risk.
We aimed to determine prevalent dietary patterns for South Asians in the United States and their ...associations with risk factors for metabolic syndrome.
South Asians aged 40-84 y without known cardiovascular disease were enrolled in a community-based cohort called Mediators of Atherosclerosis in South Asians Living in America. A validated food frequency questionnaire and serum samples for fasting and 2-h glucose, insulin, glycated hemoglobin, triglycerides, and total and HDL cholesterol were collected cross-sectionally. We used principal component analysis with varimax rotation to determine dietary patterns, and sequential linear and logistic regression models for associations with metabolic factors.
A total of 892 participants were included (47% women). We identified 3 major dietary patterns: animal protein; fried snacks, sweets, and high-fat dairy; and fruits, vegetables, nuts, and legumes. These were analyzed by tertile of factor score. The highest vs. the lowest tertile of the fried snacks, sweets, and high-fat dairy pattern was associated with higher homeostasis model assessment of insulin resistance (HOMA-IR) (β: 1.88 mmol/L ⋅ uIU/L) and lower HDL cholesterol (β: -4.48 mg/dL) in a model adjusted for age, sex, study site, and caloric intake (P < 0.05). The animal protein pattern was associated with higher body mass index (β: 0.73 m/kg(2)), waist circumference (β: 0.84 cm), total cholesterol (β: 8.16 mg/dL), and LDL cholesterol (β: 5.69 mg/dL) (all P < 0.05). The fruits, vegetables, nuts, and legumes pattern was associated with lower odds of hypertension (OR: 0.63) and metabolic syndrome (OR: 0.53), and lower HOMA-IR (β: 1.95 mmol/L ⋅ uIU/L) (P < 0.05).
The animal protein and the fried snacks, sweets, and high-fat dairy patterns were associated with adverse metabolic risk factors in South Asians in the United States, whereas the fruits, vegetables, nuts, and legumes pattern was linked with a decreased prevalence of hypertension and metabolic syndrome.
The Dietary Guidelines for Americans (DGA) is published every 5 y jointly by the Department of Health and Human Services (HHS) and the USDA and provides a framework for US-based food and nutrition ...programs, health promotion and disease prevention initiatives, and research priorities. Summarized in this report are the methods, major conclusions, and recommendations of the Scientific Report of the 2015 US Dietary Guidelines Advisory Committee (DGAC). Early in the process, the DGAC developed a conceptual model and formulated questions to examine nutritional risk and determinants and impact of dietary patterns in relation to numerous health outcomes among individuals aged ≥2 y. As detailed in the report, an expansive, transparent, and comprehensive process was used to address each question, with multiple opportunities for public input included. Consensus was reached on all DGAC’s findings, including each conclusion and recommendation, and the entire report. When research questions were answered by original systematic literature reviews and/or with existing, high-quality expert reports, the quality and strength of the evidence was formally graded. The report was organized around the following 5 themes: 1) food and nutrient intakes and health: current status and trends; 2) dietary patterns, foods and nutrients, and health outcomes; 3) diet and physical activity behavior change; 4) food and physical activity environments; and 5) food sustainability and food safety. The following 3 cross-cutting topics were addressed: 1) sodium, 2) saturated fat, and 3) added sugars. Physical activity recommendations from recent expert reports were endorsed. The overall quality of the American diet was assessed to identify overconsumed and underconsumed nutrients of public health concern. Common food characteristics of healthy dietary patterns were determined. Features of effective interventions to change individual and population diet and physical activity behaviors in clinical, public health, and community settings were identified. The report was used by the HHS and the USDA to develop the 2015 DGA.
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