Dietary Habits and Dietary Antioxidant Intake Are Related to Socioeconomic Status in Polish Adults: A Nationwide Study

Zujko, Małgorzata Elżbieta; Waśkiewicz, Anna; Drygas, Wojciech; Cicha-Mikołajczyk, Alicja; Zujko, Kinga; Szcześniewska, Danuta; Kozakiewicz, Krystyna; Witkowska, Anna

doi:10.3390/nu12020518

Cited by 30 publications

(22 citation statements)

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“…This finding is in line with other authors results suggesting that those with elementary or less than college degrees exhibit unhealthy behaviour profiles [40][41][42]. According to Zujko et al (2020) higher socioeconomic status was significantly associated with a more favourable lifestyle, better objective health outcomes and better dietary habits (including a higher intake of dietary antioxidants) [13]. Also a recent report of Zagozdzon et al (2020) revealed substantial differences regarding socioeconomic characteristics between smokers and non-smokers in Poland [41].…”

Section: Discussionsupporting

confidence: 89%

“…Two editions of the project performed in 2003-2005 and ten years later provide national representative data on changes of several aspects of non-communicable diseases using standardized methods. Several already published papers presenting the results of these projects focused separately on selected risk factors and behaviours [11][12][13][14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

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Ten-year changes in adherence to a healthy lifestyle: the results of the WOBASZ Surveys

Kwaśniewska

Pikala

Aranowska

et al. 2021

Polish Archives of Internal Medicine

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This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0), allowing third parties to copy and redistribute the material in any medium or format and to remix, transform, and build upon the material, provided the original work is properly cited, distributed under the same license, and used for noncommercial purposes only.

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Section: Discussionsupporting

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Ten-year changes in adherence to a healthy lifestyle: the results of the WOBASZ Surveys

Kwaśniewska

Pikala

Aranowska

et al. 2021

Polish Archives of Internal Medicine

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“…SES scores were calculated by multiplying ordinal numerical values assigned to consecutive categories of education level and annual household income. 27 Educational attainment was divided into six groups, and annual household income was divided into seven groups. The SES score ranged from 1 to 42.…”

Section: Sociodemographic Characteristicsmentioning

confidence: 99%

Sociodemographic disparity in health-related behaviours and dietary habits among public workers in China: a cross-sectional study

Ouyang

et al. 2021

BMJ Open

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ObjectiveWe aimed to estimate the distribution of health-related behaviours and dietary habits by sociodemographics among public workers in China.DesignCross-sectional study.SettingA representative sample was obtained from 10 government-run institutions in Hunan province of China.ParticipantsA total of 5029 public workers were included in this study.Primary and secondary outcome measuresPrevalence on their sociodemographic characteristics, health-related behaviours and dietary habits. Socioeconomic status (SES) scores were calculated by multiplying ordinal numerical values assigned to consecutive categories of education level and annual household income. Multivariate logistic regression analysis and categorical principal component analysis were used to estimate differences in health-related behaviours and dietary habits by sociodemographics.ResultsThe distribution of health-related behaviours and dietary habits was varied by sociodemographic groups. Middle-aged groups (41–60 years) were more likely to smoke (for men, 34.5%), use alcohol (for men, 22.5%), and have short sleep duration (for men, 36.3%; for women, 39.6%). Young participants (≤30 years) were more likely to have multiple unhealthy behaviours and dietary habits. Those in low-SES have a significant higher rate of smoking (ORadj=1.46, 95% CI: 1.15 to 1.85) and leisure-time physical inactivity (ORadj=1.18, 95% CI: 1.02 to 1.37), but a lower rate of late sleeping (ORadj=0.69, 95% CI: 0.57 to 0.83) than those in high-SES. Notably, older men (≥51 years) with low-SES preferred the ‘smoked and pickled foods and dessert’ and ‘fish and nut’ pattern. In high-SES groups, 41–50 year old people preferred the ‘traditional foods’ and ‘cereals and dairy product’ pattern. No difference in dietary patterns by sociodemographics was found among women (p<0.05).ConclusionsOur findings of the disparity distribution of health-related behaviours and dietary habits by specific gender, age and SES among Chinese public workers have important policy implications for developing targeted health interventions to facilitate health-related behaviours and dietary habits in this population.

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“…The collected sociodemographic data included information on demographic (age, gender, marital status) and socioeconomic characteristics (education and annual household income). SES scores were calculated by multiplying ordinal numerical values assigned to consecutive categories of education level and annual household income [26]. Educational attainment was divided into six groups, and annual household income was divided into seven groups.…”

Section: Sociodemographic Characteristicsmentioning

confidence: 99%

Sociodemographic disparity in health-related behaviors and dietary habits among governmental employees in Hunan, China

Li¹,

He²,

Ouyang³

et al. 2020

Preprint

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BackgroundHealth-related behaviors and dietary habits have played essential roles in shaping population health and are related to morbidity or mortality. We aimed to estimate the distribution of health-related behaviors and dietary habits by socio-demographics among governmental employees in China.MethodA total of 5029 participants were included in this study. Information on their sociodemographic characteristics, health-related behaviors and dietary habits was collected. Socioeconomic status (SES) scores were calculated by multiplying ordinal numerical values assigned to consecutive categories of education level and annual household income. Adjusted multinomial logistic regression analysis and categorical principal component analysis were used to estimate differences in health-related behaviors and dietary habits by socio-demographics.ResultsThe distribution of health-related behaviors and dietary habits varied by sociodemographic groups. Middle-aged males (41–60 years) were more likely to smoke, use alcohol and have short sleep duration. Young participants (≤ 30 years) were more likely to have multiple unhealthy behaviors and dietary habits. Those in high-SES have a lower level of smoking and leisure-time physical inactivity, but a high level of late sleeping than those in low-SES. Notably, older males (≥ 51 y) with low-SES preferred the ‘smoked and pickled foods, and dessert’ and ‘fish and nut’ pattern. In high-SES groups, 41–50 y people preferred the ‘traditional foods’ and ‘cereals and dairy product’ pattern. No difference in dietary patterns by socio-demographics were found among females.ConclusionsOur findings of the disparity distribution of health-related behaviors and dietary habits by specific-gender, age and SES among Chinses governmental employees have important policy implications for developing targeted health interventions to facilitate health-related behaviors and dietary habits in this population.

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Dietary Habits and Dietary Antioxidant Intake Are Related to Socioeconomic Status in Polish Adults: A Nationwide Study

Cited by 30 publications

References 43 publications

Ten-year changes in adherence to a healthy lifestyle: the results of the WOBASZ Surveys

Ten-year changes in adherence to a healthy lifestyle: the results of the WOBASZ Surveys

Sociodemographic disparity in health-related behaviours and dietary habits among public workers in China: a cross-sectional study

Sociodemographic disparity in health-related behaviors and dietary habits among governmental employees in Hunan, China

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