Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText.
Kick-your-searchterm to multiple Engines kick-your-query now !>
A dictionary by aggregated review articles of nephrology, medicine and the life sciences
Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

suck abstract from ncbi


10.1007/s11606-016-3962-1

http://scihub22266oqcxt.onion/10.1007/s11606-016-3962-1
suck pdf from google scholar
C5359156!5359156 !28271422
unlimited free pdf from europmc28271422
    free
PDF from PMC    free
html from PMC    free

Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=28271422 &cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215

suck abstract from ncbi

pmid28271422
      J+Gen+Intern+Med 2017 ; 32 (Suppl 1 ): 11-17
Nephropedia Template TP

gab.com Text

Twit Text FOAVip

Twit Text #

English Wikipedia


  • The Obesity Epidemic in the Veterans Health Administration: Prevalence Among Key Populations of Women and Men Veterans #MMPMID28271422
  • Breland JY ; Phibbs CS ; Hoggatt KJ ; Washington DL ; Lee J ; Haskell S ; Uchendu US ; Saechao FS ; Zephyrin LC ; Frayne SM
  • J Gen Intern Med 2017[Apr]; 32 (Suppl 1 ): 11-17 PMID28271422 show ga
  • BACKGROUND: Most US adults are overweight or obese. Understanding differences in obesity prevalence across subpopulations could facilitate the development and dissemination of weight management services. OBJECTIVES: To inform Veterans Health Administration (VHA) weight management initiatives, we describe obesity prevalence among subpopulations of VHA patients. DESIGN: Cross-sectional descriptive analyses of fiscal year 2014 (FY2014) national VHA administrative and clinical data, stratified by gender. Differences ?5% higher than the population mean were considered clinically significant. PARTICIPANTS: Veteran VHA primary care patients with a valid weight within ±365 days of their first FY2014 primary care visit, and a valid height (98% of primary care patients). MAIN MEASURES: We used VHA vital signs data to ascertain height and weight and calculate body mass index, and VHA outpatient, inpatient, and fee basis data to identify sociodemographic- and comorbidity-based subpopulations. KEY RESULTS: Among nearly five million primary care patients (347,112 women, 4,567,096 men), obesity prevalence was 41% (women 44%, men 41%), and overweight prevalence was 37% (women 31%, men 38%). Across the VHA's 140 facilities, obesity prevalence ranged from 28% to 49%. Among gender-stratified subpopulations, obesity prevalence was high among veterans under age 65 (age 18-44: women 40%, men 46%; age 45-64: women 49%, men 48%). Obesity prevalence varied across racial/ethnic and comorbidity subpopulations, with high obesity prevalence among black women (51%), women with schizophrenia (56%), and women and men with diabetes (68%, 56%). CONCLUSIONS: Overweight and obesity are common among veterans served by the VHA. VHA's weight management initiatives have the potential to avert long-term morbidity arising from obesity-related conditions. High-risk groups-such as black women veterans, women veterans with schizophrenia, younger veterans, and Native Hawaiian/Other Pacific Islander and American Indian/Alaska Native veterans-may require particular attention to ensure that systems improvement efforts at the population level do not inadvertently increase health disparities.
  • |Adult [MESH]
  • |Age Distribution [MESH]
  • |Aged [MESH]
  • |Black or African American/statistics & numerical data [MESH]
  • |Body Mass Index [MESH]
  • |Comorbidity [MESH]
  • |Cross-Sectional Studies [MESH]
  • |Female [MESH]
  • |Humans [MESH]
  • |Male [MESH]
  • |Middle Aged [MESH]
  • |Obesity/*epidemiology/physiopathology [MESH]
  • |Overweight/epidemiology/physiopathology [MESH]
  • |Prevalence [MESH]
  • |Sex Distribution [MESH]
  • |United States/epidemiology [MESH]
  • |Veterans Health/ethnology/*statistics & numerical data [MESH]
  • |Veterans/statistics & numerical data [MESH]


  • DeepDyve
  • Pubget Overpricing
  • suck abstract from ncbi

    Linkout box