Prevalence, clustering and combined effects of lifestyle behaviours and their association with health after retirement age in a prospective cohort study, the Nord-Trøndelag Health Study, Norway

Storeng, Siri Høivik; Sund, Erik R.; Krokstad, Steinar

doi:10.1186/s12889-020-08993-y

Cited by 16 publications

(17 citation statements)

References 74 publications

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“…However, no such increase was found in an Australian population-based study [17]. The increased alcohol consumption could be due to poor self-rated health, low life satisfaction and anxiety after retirement, as suggested in a study from Norway [37].…”

Section: Changes In Dietary Intake After Retirementmentioning

confidence: 84%

“…Living in couple is associated with higher affordability of a nutritious diet [40], while being unmarried or living alone increases the odds of being malnourished [9] or having an unhealthier diet [3]. Poor self-rated health, poor life satisfaction and anxiety after retirement increase the risk of excessive alcohol consumption [37]; in turn, an unhealthy diet could decrease subjective well-being [10].…”

Section: Changes In Dietary Intake After Retirementmentioning

confidence: 99%

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Retirement is associated with a decrease in dietary quality

Patriota

Marques‐Vidal

2021

Clinical Nutrition ESPEN

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Background and aim: Retirement has been associated with changes in dietary intake. We evaluated dietary intake and compliance to dietary guidelines after retirement in a population-based survey. Methods: Data from a prospective study conducted in Lausanne, Switzerland. Dietary intake was assessed using a validated food frequency questionnaire in 2009e2012 (first survey) and 2014e2017 (second survey). Total energy intake (TEI), macro and micronutrients, foods, dietary scores and compliance to dietary guidelines were assessed. Three approaches were used comparing changes in dietary intake: 1) before and after retiring (paired analysis); 2) in participants who retired with genderand age-matched participants who did not retire (two-group comparison), and 3) in participants who retired, who did not retire or who were retired at both surveys (analysis of variance). Results: Using the first approach, newly retired participants (n ¼ 215) increased their intake of total (median and [interquartile range]: 15.2 [13.7e17.5] vs. 14.9 [13.3e17.1] % of TEI) and animal (11.1 [9.1 e13.0] vs. 10.0 [8.5e12.6] %TEI) protein; total (35.8 [32.1e40.7] vs. 34.6 [30.0e39.1] %TEI), saturated and monounsaturated fat; alcohol; cholesterol; vitamin D and fish, and decreased their intake of vegetable protein; total carbohydrates and monosaccharides, and of the Mediterranean diet score. Those findings were confirmed for total and saturated fat, alcohol, total carbohydrates and monosaccharides; vitamin D and fish intake, and of the Mediterranean diet score in the other two approaches. Conclusion: Retirement was associated with an unhealthier dietary intake.

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Section: Changes In Dietary Intake After Retirementmentioning

confidence: 84%

Section: Changes In Dietary Intake After Retirementmentioning

confidence: 99%

Retirement is associated with a decrease in dietary quality

Patriota

Marques‐Vidal

2021

Clinical Nutrition ESPEN

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“…Researchers investigating the association between health and lifestyle behaviors in older adults in their first decade after retirement found risky alcohol consumption and disturbed sleep duration to be associated with impaired self-rated health and life satisfaction (Storeng et al, 2020). In our study, alcohol consumption and sleep did not significantly differ between lifestyle profiles.…”

Section: Discussionmentioning

confidence: 99%

Health-related lifestyle and dropout from a web-based physical activity intervention trial in older adults: A latent profile analysis.

Ratz¹,

Voelcker‐Rehage²,

Pischke³

et al. 2021

Health Psychology

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Objective: Selective study dropout limits manifestation and detection of intervention effects and is a major challenge in behavioral intervention studies. Engaging in health-risk behaviors might make individuals especially dropout-vulnerable. Thus, this theory-based study's aim was to identify health-related lifestyle profiles affecting dropout in a web-based physical activity intervention trial targeting older adults. Method: The 12week intervention trial was conducted between 2016 and 2018 in Germany. Baseline lifestyle profiles consisting of self-reported physical activity, sedentary behavior, alcohol consumption, fruit and vegetable intake, nocturnal sleep, and social activity were assessed with questionnaires and investigated in 589 individuals. The risk of study dropout related to health-related lifestyle profile was tested with Poisson regression in 571 individuals (96.9%). Results: Latent profile analysis identified four latent health-related lifestyle profiles: socially inactive (n = 23, 3.9%), slightly unhealthy (n = 449, 75.2%), health-promoting (n = 81, 13.8%), and highly physically active lifestyle (n = 36, 6.1%). Profiles differed significantly by sex, stage of behavior change, and subjective health. Compared with the average of all profiles, statistically significant study dropout adjusted risk ratios (aRR) were 1.91 for the socially inactive lifestyle, and aRR = 0.73 for the slightly unhealthy lifestyle. There were no statistically significant effects for the highly physically active lifestyle (aRR = 0.94) and the healthpromoting lifestyle (aRR = 0.76) on study dropout. Conclusions: This study highlights the relevance of accounting for the correlation between health-related lifestyle profiles and study participation of older adults in physical activity interventions.

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“…Although health risk behaviors most often do not occur in isolation, the majority of previous studies have examined the prevalence of single or pairs of health risk behaviors and their association with health outcomes [9][10][11][12][13], and only a modest body of evidence exists on the prevalence of multiple health risk behaviors, how they cluster and how this clustering is associated with health [14][15][16][17]. To our knowledge, there are a scarcity of recent data on the clustering of multiple health risk behaviors in the Norwegian population [18,19]. Such knowledge is important because previous research indicates that multiple health risk behaviors may have synergistic effects on disease risk, meaning combinations of health risk behaviors are more harmful to an individual's health than can be expected from the added individual effect alone [18, [20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Association between sociodemographic determinants and health behaviors, and clustering of health risk behaviors among 28,047 adults: A cross-sectional study among adults from the general Norwegian population

Korslund

Hansen

Bjørkkjær

2022

Preprint

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Background Understanding the associations between health behaviors and which subgroups are at risk of developing health risk behaviors is vital knowledge to develop effective public health interventions to reduce the high prevalence of non-communicable diseases (NCDs). The objective of the study was to assess the association between physical activity, diet, tobacco use, and alcohol consumption and sociodemographic determinants (sex and education), and to examine clustering patterns of these health behaviors. Method Data was collected from an online self-reported questionnaire from the Norwegian public health survey conducted in 2019. The study sample consisted of 28,047 adults (≥ 18 years old) from Agder county in Southern Norway. Chi-square tests and logistic regression analysis were used to determine the association between sex and education according to physical activity, diet, tobacco use and alcohol consumption. Linear regression was used to examine the association between educational level and number of health risk behaviors, and cluster analysis were performed to determine cluster patterns. Results Females were more likely than men to meet the national public health recommendations for diet (p < 0.001), tobacco use (p < 0.01), and alcohol consumption (p < 0.001). High education was associated with meeting the recommendations for each of the four health behaviors and with a lower risk of having three or four health risk behaviors simultaneously. Furthermore, clustering of health risk behaviors was observed in five of the sixteen health behavior patterns. Conclusion Our findings show a higher risk of having multiple health risk behaviors for males and individuals with low education. These subgroups should be targeted in future public health interventions. Clustering patterns were observed in over 30% of the health behavior patterns. More research is needed on the causal relationship between health behaviors and socioeconomic factors, and the association between clustering and health outcomes to design effective interventions in the future.

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Prevalence, clustering and combined effects of lifestyle behaviours and their association with health after retirement age in a prospective cohort study, the Nord-Trøndelag Health Study, Norway

Cited by 16 publications

References 74 publications

Retirement is associated with a decrease in dietary quality

Retirement is associated with a decrease in dietary quality

Health-related lifestyle and dropout from a web-based physical activity intervention trial in older adults: A latent profile analysis.

Association between sociodemographic determinants and health behaviors, and clustering of health risk behaviors among 28,047 adults: A cross-sectional study among adults from the general Norwegian population

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