title: Hypertension in employees of a University General Hospital.
abstract: To find out the prevalence of hypertension in employees of the Hospital and relate it to social demographic variables.
  
  
  
  Blood pressure measurement was performed with a mercury sphygmomanometer, using an appropriate cuff size for arm circumference, weight, and height in a population sample of 864 individuals out of the 9,905 employees of a University General Hospital stratified by gender, age, and job position.
  
  
  
  Hypertension prevalence was 26% (62% of these reported being aware of their hypertension and 38% were unaware but had systolic/diastolic blood pressures of >140 and/or >90 mm Hg at the moment of the measurement). Of those who were aware of having hypertension, 51% were found to be hypertensive at the moment of the measurement. The prevalence was found to be 17%, 23%, and 29% (P <.05) in physicians, nursing staff, and "others", respectively. The univariate analysis showed a significant odds ratio for the male gender, age >50 years, work unit being the Institute of Radiology and the Administration Building, educational level <elementary school, length of work >10 years, and body mass index >30 kg/m2. The multivariate logistic regression model revealed a statistically significant association of hypertension with the following variables: gender, age, skin color, family income, and body mass index.
  
  
  
  Hypertension prevalence was high, mainly in those who were not physicians or members of the nursing staff. High-risk groups (obese, non-white, men, low family income) should be better advised of prevention and early diagnosis of hypertension by means of special programs.
authors.affiliation: Hypertension Unit, Hospital das Clínicas, Faculty of Medicine, University of São PauloSão Paulo, SP, Brazil. deciomion@uol.com.br
authors.forename: Decio
authors.initials: D
authors.lastname: Mion
authors.forename: Angela M G
authors.initials: AM
authors.lastname: Pierin
authors.forename: Alberto P
authors.initials: AP
authors.lastname: Bambirra
authors.forename: Jorge H
authors.initials: JH
authors.lastname: Assunção
authors.forename: Juliana M
authors.initials: JM
authors.lastname: Monteiro
authors.forename: Roberta Y
authors.initials: RY
authors.lastname: Chinen
authors.forename: Roger B
authors.initials: RB
authors.lastname: Coser
authors.forename: Vânia N
authors.initials: VN
authors.lastname: Aikawa
authors.forename: Fernanda M
authors.initials: FM
authors.lastname: Cação
authors.forename: Mariana
authors.initials: M
authors.lastname: Hausen
authors.forename: Marcelo F
authors.initials: MF
authors.lastname: Vilibor
authors.forename: Nádia E
authors.initials: NE
authors.lastname: Aikawa
authors.forename: Sérgio N
authors.initials: SN
authors.lastname: Konno
authors.forename: Roger B
authors.initials: RB
authors.lastname: Coser
mesh_terms: D000328:Adult; D015992:Body Mass Index; D001938:Brazil / Q000453:epidemiology; D004812:Epidemiologic Methods; D005260:Female; D006282:Health Personnel; D006769:Hospitals, General / Q000706:statistics & numerical data; D006785:Hospitals, University / Q000706:statistics & numerical data; D006801:Humans; D006973:Hypertension / Q000175:diagnosis / Q000453:epidemiology*; D008297:Male; D008875:Middle Aged; D012959:Socioeconomic Factors