Systemic inflammation, lifestyle behaviours and dementia: A 10-year follow-up investigation

Objectives

Lifestyle behaviours have been linked to dementia incidence, but their cumulative impact on dementia and the underlying mechanisms remain poorly understood. This study investigated the association of co-occurring lifestyle behaviours with dementia incidence and the mediating role of systemic inflammation in this association.

Methods

The sample comprised 3131 participants (55.2% female) from the English Longitudinal Study of Ageing aged 52-92 years at baseline (2008/09). Self-reported baseline lifestyle behaviours (alcohol intake, fruit and vegetable consumption, smoking, physical activity, sleep duration, social engagement, and cognitive activity) were summed to derive an index of lifestyle behaviours, ranging from 0 to 7, with higher scores denoting a higher number of health-risk behaviours. Incident dementia cases (n = 130, 4.2%) were identified through doctor-diagnosed dementia, informant interviews, and health records between 2014/15 and 2018/19. Systemic inflammation was measured through fasting plasma concentrations of C-reactive protein in 2012/13.

Results

Binary logistic regression models indicated that the odds of subsequent dementia increased by 1.19 for each additional health-risk behaviour (95% confidence intervals: 1.04, 1.37, p = 0.014) after adjusting for age, sex, ethnicity, wealth, education, marital status, body mass index, coronary heart disease, hypertension, stroke, and depression. However, this association was not mediated by C-reactive protein.

Conclusions

Co-occurring health-risk behaviours were associated with higher dementia incidence up to 10 years later, underscoring the importance of modifying health-risk behaviours for the prevention of dementia. Systemic inflammation did not explain the association between behaviours and dementia.

Prospective association of comorbid hypertension and depressive symptoms with C-reactive protein in older adults

BACKGROUND

Hypertension and depressive symptoms often occur together in the older population, and each has been separately linked to elevated C-reactive protein (CRP). This study investigated the prospective association between comorbid hypertension and depressive symptoms and high-sensitivity CRP (hs-CRP) in a Chinese older population.

METHODS

This study used data from 4978 participants aged 50 and above, who took part in two waves (2011 and 2015) of the China Health and Retirement Longitudinal Study (CHARLS). Hypertension, depressive symptoms and hs-CRP were measured. Logistic regressions adjusted for confounding variables were used to examine the association between the baseline comorbidity of hypertension and depressive symptoms and the change in hs-CRP levels.

RESULTS

Hypertension and depressive symptoms did not show independent associations with an elevated level of hs-CRP. Participants with comorbid hypertension and depressive symptoms were more likely to develop a higher level of hs-CRP at follow-up (OR = 1.39, 95 % CI: 1.12-1.74) even after adjusting for covariates. Sex- and age-stratified analyses indicated that the association between the comorbidity and higher levels of hs-CRP were prone to be observed in women (OR = 1.55, 95 % CI: 1.16-2.08) and older adults (OR = 1.74, 95 % CI: 1.20-2.52).

CONCLUSIONS

Comorbid hypertension and depressive symptoms is related to a higher risk of elevated hs-CRP levels. This association appears to be more pronounced among women and older adults compared to their counterparts.

LIMITATION

Depression was self-reported by participants, which might be considered less unreliable than clinical diagnoses.

Monitoring Social Determinants of Health Assessing Patients and Communities

Because of the devastating health effects of social determinants of health (SDoH), it is important for the primary care provider to assess and monitor these types of stressors. This can be done via surveys, geomapping, or various biomarkers. To date, however, each of these methods is fraught with obstacles. There are currently are no validated "best" SDoH screening tools for use in clinical practice. Nor is geomapping, a perfect solution. Although mapping can collect location specific factors, it does not account for the fact that patients may live in one area, work in another and travel frequently to a third.

Characterizing Patterns of Nurses' Daily Sleep Health: a Latent Profile Analysis

BACKGROUND

Nursing is a demanding occupation characterized by dramatic sleep disruptions. Yet most studies on nurses' sleep treat sleep disturbances as a homogenous construct and do not use daily measures to address recall biases. Using person-centered analyses, we examined heterogeneity in nurses' daily sleep patterns in relation to psychological and physical health.

METHODS

Nurses (N = 392; 92% female, mean age = 39.54 years) completed 14 daily sleep diaries to assess sleep duration, efficiency, quality, and nightmare severity, as well as measures of psychological functioning and a blood draw to assess inflammatory markers interleukin-6 (IL-6) and C-reactive protein (CRP). Using recommended fit indices and a 3-step approach, latent profile analysis was used to identify the best-fitting class solution.

RESULTS

The best-fitting solution suggested three classes: (1) "Poor Overall Sleep" (11.2%), (2) "Nightmares Only" (8.4%), (3) "Good Overall Sleep" (80.4%). Compared to nurses in the Good Overall Sleep class, nurses in the Poor Overall Sleep or Nightmares Only classes were more likely to be shift workers and had greater stress, PTSD symptoms, depression, anxiety, and insomnia severity. In multivariate models, every one-unit increase in insomnia severity and IL-6 was associated with a 33% and a 21% increase in the odds of being in the Poor Overall Sleep compared to the Good Overall Sleep class, respectively.

CONCLUSION

Nurses with more severe and diverse sleep disturbances experience worse health and may be in greatest need of sleep-related and other clinical interventions.

Factors related to the accumulation of healthy behavior among older adults attending primary Health Care

The adoption and maintenance of healthy behaviors contribute for its accumulation throughout life, which require more than information disclosure and recommendations. Biopsychosocial factors may work as barriers to adherence to healthier behaviors, and yet have been underexplored. The objective was to investigate the factors related to the accumulation of healthy behavior among older adults attending Primary Health Care. Cross-sectional analysis with 201 older adults from baseline of Longitudinal Investigation of Functioning Epidemiology (LIFE) was performed in a Southeastern Brazilian city. The Healthy Behavior Score (HBS), ranging from 0 to 8, was calculated by the sum of the following habits: Physical activity practice, healthy eating, water consumption, night sleep time, not smoking, not drinking alcohol, frequent social relations, and spirituality. A linear multivariate regression was performed to test the influence of biopsychosocial aspects on HBS, with 95% confidence interval. Higher number of healthy behaviors was related to high social support, better cognitive status, less depressive symptoms and lower functional performance. Additionally, age and resilience score were correlated to healthy behaviors, which were higher among women and those with sufficient income. Multivariate analysis revealed depressive symptoms, functional performance and education as independent predictors of HBS. Depressive symptoms, functional performance and education are predictors of accumulation of health behaviors, independently of health status, contextual and sociodemographic aspects. Higher social support partially contributed to the higher number of healthy behaviors, and should be considered in public health policies for healthy longevity.

A review and novel theoretical model of how negative emotions influence inflammation: The critical role of emotion regulation

Psychological distress is an inevitable part of life. Research drawing on theories from clinical psychology, health psychology, and psychoneuroimmunology (PNI) has identified relationships between negative emotions such as anxiety and sadness with inflammation. When not regulated properly, negative emotions can create biological wear and tear on the body that can increase risk for morbidity and mortality. This review discusses previously available research on relationships between negative emotions and emotion regulation with inflammation among both physically healthy adults and those with chronic illnesses. I then present a novel comprehensive biobehavioral model of negative emotionality. This model emphasizes the influence of negative emotions and their contribution to heightened inflammation. Further, I also discuss how emotion regulation (including perseverative processes such as worry and rumination) mediates this association. The relationships between negative emotionality and emotion regulation may be bidirectional, and empirical investigation of this model should specifically seek to disentangle these relationships. The proposed model offers the opportunity to advance PNI research through understanding how emotional factors alter inflammation and contribute to accelerated biological aging and disease risk.

The negative relationship of dietary inflammatory index and sleeping quality in obese and overweight women

Background and aims: Substantial evidence have linked low grade inflammation with the pathophysiology of chronic diseases and psychological impairment. An integral component underlying the link is pro-inflammatory diet. While sleeping is another significant contributor, few studies have addressed the relationship between the sleep quality and inflammatory cascade with the dietary quality as a moderator. The current study assesses the relation between inflammatory potential of the diet and sleep quality in Iranian obese and overweight women. Method: A total of 219 obese and overweight adult women were enrolled in this cross-sectional study. A standard 147-item food-frequency-questionnaire was used to record the dietary intakes; then, the dietary inflammatosry index (DII) was derived from the result-consolidated questionnaires. Pittsburg Sleep Quality Index (PSQI) was utilized to withdraw the sleep quality and quantity. Results: The mean (±standard deviation) age, body mass index, and PSQI of individuals were 36.49 (8.38) years, 31.04 (4.31) kg/m², and 5.78(3.55), respectively. Patients in the highest DII quartile were the ones with the higher consumption of pro-inflammatory food, and, ~58% of participants who were in the higher quartile had a sleep disturbance status. Results revealed an inverse relationship between sleep quality and DII in the crude model (β=-0.17, p=0.01) as well as full-adjusted model (β=0.24, p<0.001), such that women with higher DII had the poorest sleep quality. Conclusion: Based on the present observational study, obese and overweight females with higher adherence of the anti-inflammatory diet may have better sleeping status.

Healthy Behaviors Associated with Changes in Mental and Physical Strength in Urban African American and White Adults

Over time, adherence to healthy behaviors may improve physical and mental strength which is essential for successful aging. A plausible mechanism is the reduction of inflammation. Research on the association of risky health behaviors on change in strength with age is limited. This study examined changes in the inflammatory potential of the diet, smoking, illicit drug use with changes in strength in a racially and socioeconomically diverse adult sample from the Healthy Aging in Neighborhoods of Diversity Across the Life Span study. The dietary inflammatory index (DII) was calculated from 35 food components derived from multiple 24-h dietary recalls. Strength was evaluated by handgrip strength (HGS), SF-12 PCS and SF-12 MCS (physical and mental component scores). Repeated measures analyses were used to examine associations. At baseline, mean age was 48.4 ± 0.25 years, 56% of the sample were women, and 58% African American. Significant 4-way interactions were found between age, race, socioeconomic status, and DII for women, on change in HGS (p < 0.05) and in SF-12 PCS (p < 0.05) and for men, in change in SF-12 PCS (p < 0.05). Improvements in SF-12 MCS were associated with all three health behaviors as main effects. This study provided evidence that changes towards improving healthy behaviors, diet with anti-inflammatory potential, not smoking cigarettes and not using illicit drugs, were associated with improved strength. Health professionals, especially registered dietitians and health coaches, should create lifestyle interventions to reduce inflammation targeting change in more than one risky health behavior.

Explaining socioeconomic disparities in health behaviours: A review of biopsychological pathways involving stress and inflammation

The purpose of this article was to explore how individuals' position in a socioeconomic hierarchy is related to health behaviours that are related to socioeconomic disparities in health. We identified research which shows that: (a) low socioeconomic status (SES) is associated with living in harsh environments, (b) harsh environments are related to increased levels of stress and inflammation, (c) stress and inflammation impact neural systems involved in self-control by sensitising the impulsive system and desensitising the reflective system, (d) the effects are inflated valuations of small immediate rewards and deflated valuations of larger delayed rewards, (e) these effects are observed as increased delay discounting, and (f) delay discounting is positively associated with practicing more unhealthy behaviours. The results are discussed within an adaptive evolutionary framework which lays out how the stress response system, and its interaction with the immune system and brain systems for decision-making and behaviours, provides the biopsychological mechanisms and regulatory shifts that make widespread conditional adaptability possible. Consequences for policy work, interventions, and future research are discussed.

The association between dietary inflammatory index with sleep quality and obesity amongst iranian female students: A cross-sectional study

BACKGROUND

Overweight, obesity and lack of sleep quality as inflammatory states are the common problems amongst college students and the Association of Dietary Inflammatory Index (DII) with these problems amongst this population is unknown. We aimed to evaluate the relationship of the DII with obesity and sleep quality amongst Iranian female students.

METHODS

The present cross-sectional study was conducted on 249 female college students. The Dietary Inflammatory Index (DII) was calculated using a valid and reliable 147-item food frequency questionnaire (FFQ). To assess sleep quality, Pittsburgh Sleep Quality Index (PSQI) was used. Odds Ratio (OR) and 95% Confidence Intervals (CIs) were estimated for anthropometric indices and sleep quality according to the DII score. Linear regression was used to estimate the relationship between DII score with sleep and anthropometric indices.

RESULTS

There was a significant association evident between DII and sleep quality (>5 is considered as poor quality of sleep); ie, the odds ratios between DII quartile 2 vs 1 (unadjusted model: OR = 0.33 (CI: 0.14-0.74), P for trend = .002; model 1: the fully adjusted OR = 0.31(CI: 0.12-0.78), P for trend = .005; model 2:OR = 0.30 (CI: 0.12-0.78), P for trend = .005) to quartile 4(unadjusted model: OR = 1.13(CI: 0.45-2.80); model 1: OR = 1.11(CI: 0.44-2.79); model 2:OR = 1.13(CI: 0.44-2.87), P for trend = .005). Also, odds ratios increased significantly from quartile 2 to quartile 4 in all models for DII and sleep quality. According to the continuous score of DII, there was a significant positive association between DII and sleep quality in all three models: unadjusted, model 1, and model 2 (OR = 1.21 (CI: 1.05-1.40), OR = 1.21 (CI: 1.03-1.43), and OR = 1.22 (CI: 1.03-1.44), respectively.

CONCLUSIONS

In this study, after removing the effect of confounding factors, participants in the highest quartile of DII score had significantly higher PSQI global score.

Dietary Inflammatory Index and Sleep Quality in Southern Italian Adults

BACKGROUND

Current evidence supports the central role of a subclinical, low-grade inflammation in a number of chronic illnesses and mental disorders; however, studies on sleep quality are scarce. The aim of this study was to test the association between the inflammatory potential of the diet and sleep quality in a cohort of Italian adults.

METHODS

A cross-sectional analysis of baseline data of the Mediterranean healthy Eating, Aging, and Lifestyle (MEAL) study was conducted on 1936 individuals recruited in the urban area of Catania during 2014-2015 through random sampling. A food frequency questionnaire and other validated instruments were used to calculate the dietary inflammatory index (DII®) and assess sleep quality (Pittsburg sleep quality index). Multivariable logistic regression analyses were performed to determine the association between exposure and outcome.

RESULTS

Individuals in the highest quartile of the DII were less likely to have adequate sleep quality (odds ratio (OR) = 0.49, 95% CI: 0.31, 0.78). Among individual domains of sleep quality, an association with the highest exposure category was found only for sleep latency (OR = 0.60, 95% CI: 0.39, 0.93).

CONCLUSIONS

The inflammatory potential of the diet appears to be associated with sleep quality in adults. Interventions to improve diet quality might consider including a dietary component that aims to lower chronic systemic inflammation to prevent cognitive decline and improve sleep quality.

The Prospective Association Between the Five Factor Personality Model With Health Behaviors and Health Behavior Clusters

To examine the prospective association of personality with individual behavior, multibehavior and clustered health behavior profiles. A prospective study design was employed. Two hundred young adults provided baseline data and 126 (mean age: 21.6 yrs) provide complete data for a 5-month follow-up assessment (63% response rate). Personality and health behaviors (and covariates) were assessed via validated questionnaires. A multibehavior index variable was created ranging from 0-5; two separate health behavior cluster indices were created, including high (4-5 behaviors) vs. low (2 or fewer) behavior adoption and an energy balance cluster (MVPA and diet). When examining MVPA as a continuous variable, the personality trait conscientiousness was prospectively associated with MVPA and a healthy diet. Extraversion was prospectively associated with high (vs. low) behavioral clustering (OR = 1.18; 95% CI: 1.00-1.40) and conscientiousness was prospectively associated with energy balance clustering (OR = 1.09; 95% CI: 1.01-1.17). Extraversion, conscientiousness, openness to experience, and agreeableness were associated with select health-related behaviors. Further, extraversion and conscientiousness were associated with health behavior clustering.

Behavioral and mental health risk factor profiles among diverse primary care patients

Behavioral and mental health risk factors are prevalent among primary care patients and contribute substantially to premature morbidity and mortality and increased health care utilization and costs. Although prior studies have found most adults screen positive for multiple risk factors, limited research has attempted to identify factors that most commonly co-occur, which may guide future interventions. The purpose of this study was to identify subgroups of primary care patients with co-occurring risk factors and to examine sociodemographic characteristics associated with these subgroups. We assessed 12 behavioral health risk factors in a sample of adults (n=1628) receiving care from nine primary care practices across six U.S. states in 2013. Using latent class analysis, we identified four distinct patient subgroups: a 'Mental Health Risk' class (prevalence=14%; low physical activity, high stress, depressive symptoms, anxiety, and sleepiness), a 'Substance Use Risk' class (29%; highest tobacco, drug, alcohol use), a 'Dietary Risk' class (29%; high BMI, poor diet), and a 'Lower Risk' class (27%). Compared to the Lower Risk class, patients in the Mental Health Risk class were younger and less likely to be Latino/Hispanic, married, college educated, or employed. Patients in the Substance Use class tended to be younger, male, African American, unmarried, and less educated. African Americans were over 7 times more likely to be in the Dietary Risk versus Lower Risk class (OR 7.7, 95% CI 4.0-14.8). Given the heavy burden of behavioral health issues in primary care, efficiently addressing co-occurring risk factors in this setting is critical.

Sex and age differences in the associations between sleep behaviors and all-cause mortality in older adults: results from the National Health and Nutrition Examination Surveys

OBJECTIVE

Our aim was to examine sex- and age-specific relationships of sleep behaviors with all-cause mortality rates.

METHODS

A retrospective cohort study was conducted among 5288 adults (≥50 years) from the 2005-2008 National Health and Nutrition Examination Surveys who were followed-up for 54.9 ± 1.2 months. Sleep duration was categorized as < 7 h, 7-8 h and >8 h. Two sleep quality indices were generated through factor analyses. 'Help-seeking behavior for sleep problems' and 'diagnosis with sleep disorders' were defined as yes/no questions. Sociodemographic covariates-adjusted Cox regression models were applied to estimate hazard ratios (HRs) and 95% confidence intervals (CIs).

RESULTS

A positive relationship was observed between long sleep and all-cause mortality rate in the overall sample (HR = 1.90, 95% CI: 1.38, 2.60), among males (HR = 1.48, 95% CI: 1.05, 2.09), females (HR = 2.32, 95% CI: 1.48, 3.61) and elderly (≥65 years) people (HR = 1.80, 95% CI: 1.30, 2.50). 'Sleepiness/sleep disturbance' (Factor I) and all-cause mortality rate were positively associated among males (HR = 1.22, 95% CI: 1.03, 1.45), whereas 'poor sleep-related daytime dysfunction' (Factor II) and all-cause mortality (HR = 0.75, 95% CI: 0.62, 0.91) were negatively associated among elderly people.

CONCLUSIONS

Sex- and age-specific relationships were observed between all-cause mortality rate and specific sleep behaviors among older adults.