Self-rated Health Status among Korean Adolescents : Differences in Home Environmental Factors, Health Behaviors, Psychological Factors, and Dietary Habits

2018 ◽  
Vol 19 (1) ◽  
pp. 27-45
Author(s):  
Seonghee Hwang ◽  
◽  
Seunghee Kye
Keyword(s):  
Health Status ◽  
Environmental Factors ◽  
Health Behaviors ◽  
Psychological Factors ◽  
Dietary Habits ◽  
Korean Adolescents ◽  
Self Rated Health

scholarly journals Physical and Psychological Factors Associated with Poor Self-Reported Health Status in Older Adults with Falls

2020 ◽  
Vol 17 (10) ◽  
pp. 3548 ◽  
Author(s):  
Jiyeon Kim ◽  
Mikyong Byun ◽  
Moonho Kim
Keyword(s):  
Older Adults ◽  
Health Status ◽  
Psychological Factors ◽  
Hearing Impairments ◽  
Factors Associated ◽  
Self Rated Health ◽  
Physical Tests ◽  
Reported Health ◽  
Self Reported Health Status ◽  
Poor Nutrition

Background: Previous studies have proposed various physical tests for screening fall risk in older adults. However, older adults may have physical or cognitive impairments that make testing difficult. This study describes the differences in individual, physical, and psychological factors between adults in good and poor self-rated health statuses. Further, we identified the physical or psychological factors associated with self-rated health by controlling for individual variables. Methods: Data from a total of 1577 adults aged 65 years or over with a history of falls were analyzed, using the 2017 National Survey of Older Persons in South Korea. Self-reported health status was dichotomized as good versus poor using the 5-point Likert question: “poor” (very poor and poor) and “good” (fair, good, and very good). Results: Visual/hearing impairments, ADL/IADL restriction, poor nutrition, and depression were more frequently observed in the group with poor self-rated health. Multivariable logistic regression revealed that poor self-reported health was significantly associated with hearing impairments (OR: 1.51, 95% CI 1.12–2.03), ADL limitation (OR: 1.77, 95% CI 1.11–2.81), IADL limitation (OR: 2.27, 95% CI 1.68–3.06), poor nutrition (OR: 1.36, 95% CI 1.05–1.77), and depression (OR 3.77, 95% CI 2.81–5.06). Conclusions: Auditory impairment, ADL/IADL limitations, poor nutrition, and depression were significantly associated with poor self-reported health. A self-rated health assessment could be an alternative tool for older adults who are not able to perform physical tests.

scholarly journals Personality traits predict dietary habits in middle-to-older adults

2019 ◽  
Author(s):  
Sara J Weston ◽  
Grant Edmonds ◽  
Patrick Hill
Keyword(s):  
Older Adults ◽  
Health Behaviors ◽  
Personality Traits ◽  
Healthy Eating ◽  
Dietary Habits ◽  
Eating Habits ◽  
Emotional Stability ◽  
Healthy Foods ◽  
Self Rated Health

Personality traits are consistently associated with health behaviors, but little research has examined the role of personality on eating habits among middle-to-older adults. The current study (n = 665) examined the associations between traits and dietary habits and whether healthy eating predicted health at age 60, with the Hawaii Personality and Health Cohort. Eating healthy foods was associated with higher agreeableness, conscientiousness, emotional stability, and openness, and predicted better self-rated health and lower BMI. Eating unhealthy foods was associated with lower agreeableness, conscientiousness, emotional stability, and openness, and predicted lower self-rated health. Results were not moderated by SES.

scholarly journals Associations of Living Environment and Lifestyle Factors with Sub-Health Status: A Population-Based Cross-Sectional Study in Urban China

2020 ◽  
Author(s):  
Yefang Feng ◽  
Yunlian Xue ◽  
Guihao Liu ◽  
Mengyao Xu ◽  
Lijie Jiang ◽  
...  
Keyword(s):  
Health Status ◽  
Environmental Factors ◽  
Dietary Habits ◽  
Population Based ◽  
Equation Model ◽  
Living Environment ◽  
Urban China ◽  
Lifestyle Behaviors ◽  
Cross Sectional ◽  
Detection Rates

Abstract Background: Sub-health status (SHS) is an increasingly concerned issue with a high prevalence worldwide. Although some factors of lifestyle and environment has been study, few studies have determined comprehensively the associations of lifestyle and living environmental factors with general, physical, mental and social SHS. Methods: A cross-sectional face-to-face survey (Sep 2017 to Sep 2018) was conducted via questionnaire among 6,750 urban residents aged 14 years and above randomly selected from five Chinese cities. There were 5,881 valid questionnaires with a response rate of 87%. General linear model and structure equation model were developed to quantifying the effects of lifestyle behaviors and living environmental factors on SHS. Results: Detection rates of general SHS, physical SHS, mental SHS and social SHS were 66.7%, 67.0%, 65.5% and 70.0%, respectively. Significant association of general SHS, physical SHS, mental SHS and social SHS had been found in smoking, bad dietary habits, breakfast consumption, physical exercise, sleep duration, air, neighbor harmony and living convenience, instead of noiseless. However, associations of general SHS, physical SHS, mental SHS and social SHS were different for second-hand smoking influence, alcohol consumption, sunshine, Bedtime before 11pm, surfing the internet, greenery, air, pleasant housing, spacious rooms and fitness facility. Good lifestyle behaviors and favorable living environment factors positively affected SHS (P<0.001). Lifestyle behaviors had the largest effect on physical SHS (β=-0.418), but the least on social SHS (β=-0.274). Living environmental factors had the largest effect on mental SHS (β=0.286), but the least on physical SHS (β=0.225). Conclusions: Lifestyle behaviors and living environmental factors were important influencing factors of SHS. Physical SHS was more associated with lifestyle. Lifestyle and living environment were similarly associated with mental and social SHS.

scholarly journals Correlates of Commuter Cycling in Three Norwegian Counties

2019 ◽  
Vol 16 (22) ◽  
pp. 4372 ◽  
Author(s):  
Nordengen ◽  
Ruther ◽  
Riiser ◽  
Andersen ◽  
Solbraa
Keyword(s):  
Physical Activity ◽  
Health Status ◽  
Environmental Factors ◽  
Physical Inactivity ◽  
Good Health ◽  
High Population Density ◽  
Physically Active ◽  
Web Based ◽  
Self Rated Health ◽  
Objectively Measured

Globally, there is an increasing challenge of physical inactivity and associated diseases. Commuter cycling is an everyday physical activity with great potential to increase the health status in a population. We aimed to evaluate the association of self-reported factors and objectively measured environmental factors in residence and along commuter routes and assessed the probability of being a commuter cyclist in Norway. Our study included respondents from a web-based survey in three Norwegian counties and we used a Geographic Information Systems (GIS) to evaluate the natural and built environment. Of the 1196 respondents, 488 were classified as commuter cyclists. Self-reported factors as having access to an e-bike (OR 5.99 [CI: 3.71–9.69]), being physically active (OR 2.56 [CI: 1.42–4.60]) and good self-rated health (OR 1.92 [CI: 1.20–3.07]) increased the probability of being a cyclist, while being overweight or obese (OR 0.71 [CI: 0.54–0.94]) reduced the probability. Environmental factors, such as high population density (OR 1.49 [CI: 1.05–2.12]) increased the probability, while higher slope (trend p = 0.020), total elevation along commuter route (trend p = 0.001), and >5 km between home and work (OR 0.17 [CI: 0.13–0.23]) decreased the probability of being a cyclist. In the present study, both self-reported and environmental factors were associated with being a cyclist. With the exception of being in good health, the characteristics of cyclists in Norway, a country with a low share of cyclists, seem to be similar to countries with a higher share of cyclists. With better knowledge about characteristics of cyclists, we may design better interventions and campaigns to increase the share of commuter cyclists.

scholarly journals Associations of living environment and lifestyle factors with sub-health status: A population-based cross-sectional study in urban China

2020 ◽  
Author(s):  
Yunlian xue ◽  
guihao liu ◽  
Yefang Feng ◽  
Mengyao Xu ◽  
Lijie Jiang ◽  
...  
Keyword(s):  
Health Status ◽  
Environmental Factors ◽  
Dietary Habits ◽  
Population Based ◽  
Equation Model ◽  
Living Environment ◽  
Urban China ◽  
Lifestyle Behaviors ◽  
Cross Sectional ◽  
Detection Rates

Abstract Background Sub-health status (SHS) is an increasingly concerned issue with a high prevalence worldwide. Although some factors of lifestyle and environment has been study, few studies have determined comprehensively the associations of lifestyle and living environmental factors with general, physical, mental and social SHS. Methods A cross-sectional face-to-face survey (Sep 2017 to Sep 2018) was conducted via questionnaire among 6,750 urban residents aged 14 years and above randomly selected from five Chinese cities. There were 5,881 valid questionnaires with a response rate of 87%. General linear model and structure equation model were developed to quantifying the effects of lifestyle behaviors and living environmental factors on SHS. Results Detection rates of general SHS, physical SHS, mental SHS and social SHS were 66.7%, 67.0%, 65.5% and 70.0%, respectively. Significant association of general SHS, physical SHS, mental SHS and social SHS had been found in smoking, bad dietary habits, breakfast consumption, physical exercise, sleep duration, air, neighbor harmony and living convenience, instead of noiseless. However, associations of general SHS, physical SHS, mental SHS and social SHS were different for second-hand smoking influence, alcohol consumption, sunshine, Bedtime before 11 pm, surfing the internet, greenery, air, pleasant housing, spacious rooms and fitness facility. Good lifestyle behaviors and favorable living environment factors positively affected SHS (P < 0.001). Lifestyle behaviors had the largest effect on physical SHS (β=-0.418), but the least on social SHS (β=-0.274). Living environmental factors had the largest effect on mental SHS (β = 0.286), but the least on physical SHS (β = 0.225). Conclusions Lifestyle behaviors and living environmental factors were important influencing factors of SHS. Physical SHS was more associated with lifestyle. Lifestyle and living environment were similarly associated with mental and social SHS.

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