Contrasting socioeconomic profiles related to healthier lifestyles in China and the United States

Department of Nutrition, University of North Carolina, Chapel Hill, NC 27516, USA.
American Journal of Epidemiology (Impact Factor: 5.23). 02/2004; 159(2):184-91.
Source: PubMed


Health disparity by socioeconomic status has recently become an important public health concern. Socioeconomic status may affect health status through several pathways including lifestyle choices. The authors tested the link between socioeconomic status and lifestyle in China (in 1993) and in the United States (in 1994-1996), countries with high contrasts in development, to understand health discrepancy issues cross-nationally. Healthfulness of lifestyle was measured using the Lifestyle Index, a summary score that integrates four key lifestyle factors: diet, physical activity, smoking, and alcohol consumption. Income and education were used as indicators of socioeconomic status. In China, as socioeconomic status improved, lifestyle was less healthy (relative odds for the highest socioeconomic status group = 0.19, 95% confidence interval: 0.10, 0.35). Conversely, in the United States, higher socioeconomic status was related to a healthier lifestyle (relative odds for the highest socioeconomic status group = 3.81, 95% confidence interval: 2.94, 4.94). The contrasting relation between socioeconomic status and lifestyle depicts different phases of the lifestyle transition (changes in lifestyles accompanying economic development). The differences may in part explain why nutrition-related noncommunicable diseases are more prevalent in the developing world among people with a high socioeconomic status, whereas often the opposite is found in developed societies. Public health programs may benefit by advising each socioeconomic status group separately, while considering the country's level of development.

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Available from: Barry M Popkin, Jan 27, 2015
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    • "The relationship between lifestyle factors, including physical activity, and SES is complex and may differ between LMICs and high income countries (HICs) [18,19]. Our findings indicate that in rural South African adolescents greater SES is associated with more time spent in sedentary behavior’s such as watching television and reading, less time walking as a means of transport, and more time participating in MVPA involved in school and club sports. "
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    ABSTRACT: Physical inactivity is increasing among children and adolescents and may be contributing to the increasing prevalence of overweight and obesity. This study examines physical activity and sedentary behavior patterns, and explores associations with individual, maternal, household, and community factors amongst rural South African adolescents. In 2009, 381 subjects, stratified by ages 11-12-years and 14-15-years, were randomly selected from 3511 children and adolescents who had participated in a growth survey two years previously. Weight and height were measured and self-reported Tanner pubertal stage was collected. A questionnaire quantifying frequency and duration of physical activity (PA) domains and sedentary time for the previous 12 months was administered. Moderate-vigorous physical activity (MVPA mins/wk) was calculated for time spent in school and club sport. Socio-demographic and other related data were included from the Agincourt health and socio-demographic system (HDSS). The Agincourt HDSS was established in 1992 and collects prospective data on the community living in the Agincourt sub-district of Mpumalanga Province in rural north-east South Africa. Puberty, maternal education and socio-economic status (SES) contributed significantly to the mulitiple linear regression model for sedentary behavior (R2 = 0.199; adjusted R2 = 0.139; p < 0.000), and sex, SES and maternal education contributed to the tobit regression model for school and club sport MVPA (p < 0.000). MVPA, calculated from school and club sport, was higher in boys than girls (p < 0.001), and informal activity was lower (boys: p < 0.05 and girls: p < 0.01) while sedentary time was higher (girls: p < 0.01) in the older than the younger groups. Ninety-two percent (92%) of the sample reported walking for transport. In this study of rural South African adolescent boys and girls, SES at the maternal, household and community level independently predicted time spent in sedentary behaviors, and school and club MVPA. This study provides local data that can be used to develop health promotion strategies specific to this community, and other similar communities in developing countries.
    BMC Public Health 01/2014; 14(1):40. DOI:10.1186/1471-2458-14-40 · 2.26 Impact Factor
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    • "These four NCDs share risk factors such as tobacco use, physical inactivity, unhealthy diets and harmful use of alcohol [11]. Health behaviors are affected by socioeconomic status, such as income and education, sociodemographic factors, and cultural values [12]. There are significant differences in socioeconomic and health status among different regions in China. "
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    ABSTRACT: Chronic non-communicable diseases have become the major cause of death in China. This study describes and compares chronic disease mortality between urban and rural residents in Hubei Province, central China. Death records of all individuals aged 15 years and over who died from 2008 through 2010 in Hubei were obtained from the Disease Surveillance Points system maintained by the Hubei Province Centers for Disease Control and Prevention. Average annual mortality, standardized death rates, years of potential life lost (YLL), average years of potential life lost (AYLL) and rates of life lost were calculated for urban and rural residents. Standardized rate ratios (SRR) were calculated to compare the death rates between urban and rural areas. A total of 86.2% of deaths were attributed to chronic non-communicable diseases in Hubei. Cerebrovascular diseases, ischemic heart disease and neoplasms were the main leading causes in both urban and rural areas, and the mortality rates were higher among rural residents. Lung cancer was the principal cause of mortality from cancer among urban and rural residents, and stomach cancer and liver cancer were more common in rural than urban areas. Breast cancer mortality among women in rural areas was lower than in urban areas (SRR=0.73, 95% CI=0.63--0.85). The standardized mortality for chronic lower respiratory disease among men in rural areas was higher than in urban areas (SRR=4.05, 95% CI=3.82--4.29). Among men, total AYLL from liver cancer and other diseases of liver were remarkably higher than other causes in urban and rural areas. Among women the highest AYLL were due to breast cancer in both urban and rural areas. Chronic diseases were the major cause of death in Hubei Province. While circulatory system diseases were the leading causes in both urban and rural areas, our study highlights that attention should also be paid to breast cancer among women and chronic lower respiratory disease among rural residents. It is important that governments focus on this public health issue and develop preventive strategies to reduce morbidity and premature mortality from chronic non-communicable diseases.
    BMC Public Health 08/2013; 13(1):713. DOI:10.1186/1471-2458-13-713 · 2.26 Impact Factor
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    • "Such high risk profiles have been documented to be negatively associated with SES in middle- or high-income countries/regions [35-40], but positively associated with SES in low-income countries [41-44]. SES may affect health status through lifestyle choices [45], and healthy lifestyle was associated with lower risk of stroke [46,47]. SES also related to education and health literacy in populations, which in turn related to a lower risk of stroke [48,49]. "
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    ABSTRACT: Introduction The effect of socioeconomic status (SES) on stroke mortality at population level has been controversial. This study explores the association of SES in childhood and adulthood with stroke mortality, as well as variations in this association among countries/regions. Methods Sex-specific stroke mortality at country level with death registry covering ≥ 70% population was obtained from the World Health Organization. Human Development Index (HDI) developed by the United Nations was chosen as the SES indicator. The associations between the latest available stroke mortality with HDI in 1999 (adulthood SES) and with HDI in 1960 (childhood SES) for the group aged 45–54 years among countries were examined with regression analysis. Age-standardized stroke mortality and HDI during 1974–2001 were used to estimate the association by time point. Results The population data were available mostly for low-middle to high income countries. HDI in 1960 and 1999 were both inversely associated with stroke mortality in the group aged 45–54 years in 39 countries/regions. HDI in 1960 accounted for 37% of variance of stroke mortality among countries/regions; HDI in 1999 for 35% in men and 53% in women (P < 0.001). There was a quadratic relationship between age-standardized stroke mortality and HDI for the countries from 1974 to 2001: the association was positive when HDI < 0.77 but it became negative when HDI > 0.80. Conclusions SES is a strong predictor of stroke mortality at country level. Stroke mortality increased with improvement of SES in less developed countries/region, while it decreased with advancing SES in more developed areas.
    International Journal for Equity in Health 06/2013; 12(1):42. DOI:10.1186/1475-9276-12-42 · 1.71 Impact Factor
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