Overweight and underweight coexist within households in Brazil, China and Russia.
The possibility that underweight and overweight coexist within households and understanding such an occurrence have not been studied sufficiently. In fact, underweight and overweight are thought of as resulting from very different environmental, behavioral and individual risk factors. This study identified households in which overweight and underweight coexist and explored household-level associations such as urban residence and income. Using three large national surveys from Brazil, China and Russia, the prevalence of such households ranged from 8% in China and Russia to 11% in Brazil. Even more important from the public health perspective is the finding that these under/over households accounted for a high proportion of all households with an underweight member in China (23%), Brazil (45%), and Russia (58%). The prevalence of the underweight/overweight household was highest in the urban environment in all three countries. There was no clear pattern in the prevalence of the underweight/overweight household type by income. Multivariable logistic regression was used to test the significance of the association of household type with urban residence and income while controlling for household size and household demographics by gender. Further analysis was done to consider the age relationships within the underweight/overweight pair. The underweight child coexisting with an overweight nonelderly adult was the predominant pair combination in all three countries. These findings illustrate the need for public health programs that are able to address underweight and overweight simultaneously.
Doak
C M
CM
Department of Nutrition, School of Public Health, University of North Carolina, Chapel Hill, NC 27514-7400, USA.
Adair
L S
LS
Monteiro
C
C
Popkin
B M
BM
D000367:Age Factors; D015992:Body Mass Index; D001938:Brazil / Q000453:epidemiology; D002681:China / Q000453:epidemiology; D005190:Family; D005191:Family Characteristics; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D009748:Nutrition Disorders / Q000453:epidemiology*; D009749:Nutrition Surveys; D009765:Obesity / Q000453:epidemiology*; D015995:Prevalence; D012307:Risk Factors; D012426:Russia / Q000453:epidemiology; D012737:Sex Factors; D012959:Socioeconomic Factors; D014504:Urban Health / Q000706:statistics & numerical data*