Age and sex differences in the relationship between inherited and lifestyle risk factors and subclinical carotid atherosclerosis: the Tromsø study

Objectives: To assess the relationship between modifiable lifestyle factors and risk of overweight/obesity in Chinese students, and to evaluate the predicting prevalence of overweight if the lifestyle risk factors were removed.Methods: A cross-sectional survey was conducted among 40,141 students in grade three and above (8–24yrs) in 2019 in Zhejiang Province, China. Physical examination was performed, and a self-administered questionnaire was used to collect lifestyle information, including dietary behavior, physical activity, TV watching, sleeping, smoking, drinking, and tooth-brushing habits. Logistic regression models were performed to assess the relationship between overweight/obesity and a series of lifestyle factors. Population attributable fractions (PAFs) were used to calculate the predicting prevalence of overweight/obesity if lifestyle risk factors were removed.Results: The prevalence of overweight/obesity of participants was 25.5% (male 32.3%, female 18.1%). Overweight/obesity were associated with adverse lifestyle factors, such as watch TV ≥1 h/day (OR = 1.14, 95% CI: 1.11–1.22), insufficient sleep (OR = 1.14, 95% CI: 1.11–1.22), and irregular toothbrushing habits (OR = 1.19, 95% CI: 1.01–1.39). Based on the calculated PAFs, the predicted prevalence of overweight/obesity would decline moderately if lifestyle factors were modified, with the magnitudes of decrease vary by sex, age and residence. Generally, a larger reduction was estimated if the sleeping time was increased and TV time was reduced, with the prevalence of overweight/obesity decreased by 1.1% (95% CI: 0.7, 1.5%) and 0.9% (95% CI: 0.6, 1.2%), respectively.Conclusions: Predicted prevalence of overweight/ obesity in Chinese students may decrease if modifiable lifestyle risk factors were removed. The attributable risk for obesity of lifestyle behaviors varied in age, sex and residence groups. The findings of this study may provide insights for planning and optimizing future obesity intervention endeavors.

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Diet and Cancer

Psycho-Oncology ◽

10.1093/med/9780190097653.003.0003 ◽

2021 ◽

pp. 13-20

Author(s):

Marian L. Fitzgibbon ◽

Lisa Tussing-Humphreys ◽

Angela Kong ◽

Alexis Bains

Keyword(s):

Risk Factors ◽

Cancer Research ◽

Lifestyle Changes ◽

Lifestyle Modifications ◽

Cancer Society ◽

Lifestyle Risk Factors ◽

Dietary Components ◽

Lifestyle Risk ◽

Obesity And Cancer ◽

The Relationship

Diet contributes to the development of 30% to 35% of cancers. Shifts in the food landscape have contributed to changes in dietary intake, energy balance, and the development of obesity. Obesity, defined as a body mass index (BMI) greater than or equal to 30 kg/m², is associated with several cancers. The World Cancer Research Fund (WCRF), the American Institute for Cancer Research (AICR), the American Cancer Society (ACS), and several large U.S.-based randomized trials are studying the relationship between diet, dietary patterns, lifestyle risk factors, obesity, and cancer. Prior research reported an association between individual nutrients and cancer risk. This research, however, did not fully investigate the complexity of diet and interactions between specific dietary components. Overall, according to data reported by the WCRF and the AICR, primary prevention of many cancers is possible through modifiable lifestyle changes. Identifying and intervening on barriers to lifestyle modifications remains a challenge, but it is increasingly apparent that there is a relationship between diet, lifestyle risk factors, and cancer development and that many cancers can be prevented.

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The Relationship of Lifestyle Risk Factors and Depression in Korean Adults: A Moderating Effect of Overall Nutritional Adequacy

Nutrients ◽

10.3390/nu13082626 ◽

2021 ◽

Vol 13 (8) ◽

pp. 2626

Author(s):

Minjeong Kang ◽

Mingyu Joo ◽

Haeryun Hong ◽

Hyunsik Kang

Keyword(s):

Risk Factors ◽

Moderating Effect ◽

Nutritional Adequacy ◽

Lifestyle Risk Factors ◽

Korean Adults ◽

Lifestyle Risk ◽

Mean Adequacy Ratio ◽

Relationship Of ◽

The Relationship

Background: Little is known regarding the role of nutrition in determining the associations between lifestyle risk factors and depression. Objectives: This study examined whether or not nutritional adequacy modulates the relationship between depression and lifestyle risk factors in Korean adults aged 18-65 years (n = 7446). Methods: Data were obtained from the 2016 and 2018 Korea National Health and Examination Survey. Depression, smoking, at-risk alcohol consumption, physical inactivity, sleep deprivation, and mean adequacy ratio (MAR) were assessed. Results: Individuals with two (OR = 1.960, p < 0.001), three (OR = 4.237, p < 0.001), or four (OR = 5.312, p < 0.001) risk factors had a significantly higher risk of depression compared to individuals with one or zero risk factor. In contrast, individuals with moderate MAR (OR = 0.607, p < 0.001) and high (OR = 0.698, p < 0.001) MAR had a lower depression risk compared to individuals with low MAR. Moderation analysis showed a moderating effect of MAR (coefficient = −0.220, p = 0.007) on the relationship between risk factors and depression. Conclusions: The current findings suggest that overall nutritional adequacy plays a modulating role in determining the relationship between depression and lifestyle risk factors in Korean adults.

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Skeletal Muscle Health and Cognitive Function: A Narrative Review

International Journal of Molecular Sciences ◽

10.3390/ijms22010255 ◽

2020 ◽

Vol 22 (1) ◽

pp. 255

Author(s):

Sophia X. Sui ◽

Lana J. Williams ◽

Kara L. Holloway-Kew ◽

Natalie K. Hyde ◽

Julie A. Pasco

Keyword(s):

Risk Factors ◽

Skeletal Muscle ◽

Cognitive Decline ◽

Targeted Interventions ◽

Lifestyle Risk Factors ◽

Muscle Health ◽

Lifestyle Risk ◽

Underlying Mechanisms ◽

And Function ◽

The Relationship

Sarcopenia is the loss of skeletal muscle mass and function with advancing age. It involves both complex genetic and modifiable risk factors, such as lack of exercise, malnutrition and reduced neurological drive. Cognitive decline refers to diminished or impaired mental and/or intellectual functioning. Contracting skeletal muscle is a major source of neurotrophic factors, including brain-derived neurotrophic factor, which regulate synapses in the brain. Furthermore, skeletal muscle activity has important immune and redox effects that modify brain function and reduce muscle catabolism. The identification of common risk factors and underlying mechanisms for sarcopenia and cognition may allow the development of targeted interventions that slow or reverse sarcopenia and also certain forms of cognitive decline. However, the links between cognition and skeletal muscle have not been elucidated fully. This review provides a critical appraisal of the literature on the relationship between skeletal muscle health and cognition. The literature suggests that sarcopenia and cognitive decline share pathophysiological pathways. Ageing plays a role in both skeletal muscle deterioration and cognitive decline. Furthermore, lifestyle risk factors, such as physical inactivity, poor diet and smoking, are common to both disorders, so their potential role in the muscle–brain relationship warrants investigation.

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Sex Differences in the Relationship of Risk Factors to Subclinical Carotid Atherosclerosis Measured 15 Years Later

Stroke ◽

10.1161/01.str.31.3.574 ◽

2000 ◽

Vol 31 (3) ◽

pp. 574-581 ◽

Cited By ~ 74

Author(s):

Eva Stensland-Bugge ◽

Kaare H. Bønaa ◽

Oddmund Joakimsen ◽

Inger Njølstad

Keyword(s):

Risk Factors ◽

Sex Differences ◽

Carotid Atherosclerosis ◽

Relationship Of ◽

The Relationship

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Lifestyle risk factors for cancer: the relationship with psychosocial work environment

International Journal of Epidemiology ◽

10.1093/ije/29.5.785 ◽

2000 ◽

Vol 29 (5) ◽

pp. 785-792 ◽

Cited By ~ 35

Author(s):

A Jeanne M van Loon ◽

Marja Tijhuis ◽

Paul G Surtees ◽

Johan Ormel

Keyword(s):

Risk Factors ◽

Work Environment ◽

Psychosocial Work Environment ◽

Psychosocial Work ◽

Lifestyle Risk Factors ◽

Lifestyle Risk ◽

The Relationship

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The Relationship between Depressive Symptoms and Modifiable Lifestyle Risk Factors in Office Workers

Journal of Obesity & Metabolic Syndrome ◽

10.7570/jomes.2017.26.1.52 ◽

2017 ◽

Vol 26 (1) ◽

pp. 52-60 ◽

Cited By ~ 1

Author(s):

Youngyun Jin ◽

Changduk Ha ◽

Hyeryun Hong ◽

Hyunsik Kang

Keyword(s):

Risk Factors ◽

Depressive Symptoms ◽

Office Workers ◽

Lifestyle Risk Factors ◽

Lifestyle Risk ◽

The Relationship

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The relationship between lifestyle risk factors and depression in Korean older adults: a moderating effect of gender

BMC Geriatrics ◽

10.1186/s12877-021-02729-2 ◽

2022 ◽

Vol 22 (1) ◽

Author(s):

Shinuk Kim

Keyword(s):

Risk Factors ◽

Older Adults ◽

Moderating Effect ◽

Smoking Habits ◽

Dietary Intakes ◽

Lifestyle Risk Factors ◽

Depression Risk ◽

Patient Health ◽

Lifestyle Risk ◽

The Relationship

Abstract Background Little is known regarding the role of gender as a possible modulator in determining the associations between lifestyle risk factors and depression in older adults. Objectives This study examined whether gender modulates the relationship between depression and lifestyle risk factors in Korean adults aged 65 years and older (n = 3700). Methods Data were obtained from the 2016 and 2018 Korea National Health and Examination Survey. The primary outcome was depression, assessed with the patient health questionnaire-9. As exposures, smoking habits, at-risk alcohol consumption, and physical inactivity were assessed with a standardized questionnaire. In addition, mean adequacy ratio (MAR) as an indicator of overall nutritional inadequacy was assessed with dietary intakes of macro- and micronutrients. Results In men only, either two or three and more risk factors were significantly associated with higher depression risk (OR (95% confidence interval, CI) = 2.886 (1.003–8.299) and OR (95% CI) = 3.109 (1.064–9.097), respectively). In women only, either two or three and more risk factors were also significantly associated with higher depression risk (OR (95% CI) = 1.505 (1.067–2.124) and OR (95% CI) = 2.828 (1.527–5.239), respectively). In particular, the presence of smoking habits and MAR were the major determinants of depression (OR (95% CI) = 1.835 (1.09–3.10) and OR (95% CI) = 1.585 (1.125–2.233), respectively) in women only. Finally, a moderation analysis with the Hayes PROCESS Macro showed a significant moderating effect of gender (β (95% CI) = 0.633 (0.206 ~ 1.060)) on the relationship between risk factors and depression. In addition, the slope of the relationship was much steeper in women than in men. Conclusion Current findings suggest that lifestyle risk factors are more closely associated with depression risk in women than in men.

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Novel Machine-Learned Approach for COVID-19 Resource Allocation: A Tool for Evaluating Community Susceptibility (Preprint)

10.2196/preprints.25132 ◽

2020 ◽

Author(s):

Neil Kale

Keyword(s):

Machine Learning ◽

Risk Factors ◽

Insurance Coverage ◽

Premature Mortality ◽

Health Insurance Coverage ◽

Heart Attacks ◽

Lifestyle Risk Factors ◽

The People ◽

Potential Risk Factors ◽

Lifestyle Risk

BACKGROUND Despite worldwide efforts to develop an effective COVID vaccine, it is quite evident that initial supplies will be limited. Therefore, it is important to develop methods that will ensure that the COVID vaccine is allocated to the people who are at major risk until there is a sufficient global supply. OBJECTIVE The purpose of this study was to develop a machine-learning tool that could be applied to assess the risk in Massachusetts towns based on community-wide social, medical, and lifestyle risk factors. METHODS I compiled Massachusetts town data for 29 potential risk factors, such as the prevalence of preexisting comorbid conditions like COPD and social factors such as racial composition, and implemented logistic regression to predict the amount of COVID cases in each town. RESULTS Of the 29 factors, 14 were found to be significant (p < 0.1) indicators: poverty, food insecurity, lack of high school education, lack of health insurance coverage, premature mortality, population, population density, recent population growth, Asian percentage, high-occupancy housing, and preexisting prevalence of cancer, COPD, overweightness, and heart attacks. The machine-learning approach is 80% accurate in the state of Massachusetts and finds the 9 highest risk communities: Lynn, Brockton, Revere, Randolph, Lowell, New Bedford, Everett, Waltham, and Fitchburg. The 5 most at-risk counties are Suffolk, Middlesex, Bristol, Norfolk, and Plymouth. CONCLUSIONS With appropriate data, the tool could evaluate risk in other communities, or even enumerate individual patient susceptibility. A ranking of communities by risk may help policymakers ensure equitable allocation of limited doses of the COVID vaccine.

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