Xiang Qi

Abstract

Diabetes mellitus (DM) is a recognized risk factor for dementia, and increasing evidence shows that tooth loss is associated with cognitive impairment and dementia. However, the effect of the co-occurrence of DM and edentulism on cognitive decline is understudied. This 12-y cohort study aimed to assess the effect of the co-occurrence of DM and edentulism on cognitive decline and examine whether the effect differs by age group. Data were drawn from the 2006 to 2018 Health and Retirement Study. The study sample included 5,440 older adults aged 65 to 74 y, 3,300 aged 75 to 84 y, and 1,208 aged 85 y or older. Linear mixed-effect regression was employed to model the rates of cognitive decline stratified by age cohorts. Compared with their counterparts with neither DM nor edentulism at baseline, older adults aged 65 to 74 y (β = −1.12; 95% confidence interval [CI], −1.56 to −0.65; P < 0.001) and those aged 75 to 84 y with both conditions (β = −1.35; 95% CI, −2.09 to −0.61; P < 0.001) had a worse cognitive function. For the rate of cognitive decline, compared to those with neither condition from the same age cohort, older adults aged 65 to 74 y with both conditions declined at a higher rate (β = −0.15; 95% CI, −0.20 to −0.10; P < 0.001). Having DM alone led to an accelerated cognitive decline in older adults aged 65 to 74 y (β = −0.09; 95% CI, −0.13 to −0.05; P < 0.001); having edentulism alone led to an accelerated decline in older adults aged 65 to 74 y (β = −0.13; 95% CI, −0.17 to −0.08; P < 0.001) and older adults aged 75 to 84 (β = −0.10; 95% CI, −0.17 to −0.03; P < 0.01). Our study finds the co-occurrence of DM and edentulism led to a worse cognitive function and a faster cognitive decline in older adults aged 65 to 74 y.

Abstract

Objectives: To develop symptom networks and examine the longitudinal relationships of depressive symptoms among middle-aged and older adults in China. Method: This study used three-wave data from the China Health and Retirement Longitudinal Study (2013 (T1), 2015 (T2), and 2018 (T3)). Depressive symptoms were measured by the 10-item Center for Epidemiologic Studies Depression Scale (CES-D). A multilevel vector autoregression model (VAR) was used to identify ten depressive symptoms dynamically interacting with each other over time. Results: A total of 3,558 participants were included in the final analysis. The strongest direct effects were ‘D10: felt fearful’ -> ‘D6: felt everything I did was an effort’ (β = 0.14). ‘D10: felt fearful’ reported the largest value of out-predictability (r = 0.064) and out-strength (r = 0.635). ‘D3: felt depressed’ reported the largest value of in-predictability (r = 0.077) and in-strength (r = 0.545). Substantial heterogeneity in the network may stem from an individual’s sex and place of residence. Conclusions: ‘Felt fearful’ was the strongest predictor compared to the other nine depressive symptoms based on node centrality. Our study suggests that, after understanding the causes of fear, strategies to reduce fear should be incorporated into multimodal interventions for middle-aged and older adults with depressive symptoms.

Abstract

OBJECTIVE: To investigate how cognitive function domains change in phenotypic networks in cognitive deterioration and improvement groups.DESIGN: Secondary data analysis.SETTING AND PARTICIPANTS: Respondents in the Aging, Demographics, and Memory Study (ADAMS) who were 70 years or older at the time of the data collection in 2000 or 2002.METHODS: This study used data from the ADAMS in Wave A and Wave B. We assessed 12 cognitive function domains. Latent profile transition analysis (LPTA) and the cross-lagged panel network model were used to the dynamic interactions of the 12 cognitive function domains over time in both the deterioration and improvement groups.RESULTS: A total of 252 participants were included in the final analysis. LPTA identified 5 subgroups and categorized all samples into 3 main categories: improvement group (n = 61), deterioration group (n = 54), and no change group (n = 137). "D9: psychomotor processing" showed the largest value of out-strength in the deterioration group (r = 0.941) and improvement group (r = 0.969). The strongest direct positive effect in the deterioration group was "C9: psychomotor processing" -> "C8: attention" (β = 0.39 [0.00, 1.13]). In the improvement group, the strongest direct positive effect was "C9 = psychomotor processing" -> "C7 = visual memory" (β = 0.69 [0.07, 1.30]).CONCLUSION AND IMPLICATIONS: Psychomotor processing affected other cognitive domains, and it played a crucial role in changes of cognitive function. The paths of psychomotor processing to attention and visual memory were found to be major factors in cognitive deterioration and improvement. Targeting psychomotor processing may lead to the development of more effective and precise interventions.

Abstract

Background: Internal migrants are exposed to higher risks of depressive symptoms due to migration-related stress. It has been recognized that perceived neighborhood social cohesion has direct and indirect associations with depressive symptoms. However, the pathway from perceived social cohesion to internal migrants' depressive symptoms was less discussed. Objectives: To assess mental health disparities among internal migrants. To investigate the association between social cohesion and depressive symptoms among urban-to-urban and rural-to-urban migrants and to examine the mediating role of social adaptation. Methods: Data from the “2017 Urbanization and New Migrant Survey” was used, including 2,584 internal migrants age 18–65 from 10 cities in China. Social cohesion was measured by a six-item modified Community-level Cohesion Scale. Depressive symptoms was measured using the Center for Epidemiological Studies Depression Scale, and social adaptation was assessed by a single-item question of migrants' adaptation to local life. Multivariate linear regression models were used to examine the association between social cohesion and depressive symptoms. Baron and Kenny's mediation tests were conducted to examine the mediating role of social adaptation on the association. All analyses were adjusted using sampling weights to account for this survey's sampling design. Results: Rural-to-urban migrants were found to have more clinically significant depressive symptoms, lower perceived social cohesion, and fair or low social adaptation than urban-to-urban migrants (all p < 0.001). Being rural-to-urban migrants as compared with urban-to-urban migrants [Odds Ratio (OR) = 1.46, 95% Confidence Interval (CI) = 1.456, 1.461, p < 0.001], had lower perceived social cohesion (OR = 1.46, 95% CI = 1.458, 1.463, p < 0.001), and poorer social adaptation (OR = 1.94, 95% CI = 1.932, 1.941, p < 0.001), are associated with higher odds of having clinically significant depressive symptoms. Social adaptation partially mediated the association between social cohesion and depressive symptoms by explaining 15.39% of its effect for urban-to-urban migrants and 18.97% for rural-to-urban migrants. Conclusions: Findings from this study reveal mental health inequalities among internal migrants and demonstrate the importance of social adaption on the association between social cohesion and depressive symptoms. Social strategies and public policies are needed to build a more cohesive community that serves both local residents and internal migrants, especially rural-to-urban migrants.

Abstract

The SARS-CoV-2 coronavirus pandemic has led to increased food insecurity levels. This cross-sectional study examines the prevalence and determinants of food insecurity during the two-month (1 April to 1 June 2022) city-wide lockdown in Shanghai. The data was collected via an online questionnaire from 3230 adult Shanghai residents during the lockdown. Food insecurity was measured using an adapted version of the Household Food Insecurity Access Scale. Nearly 70% of participants reported being exposed to food insecurity. Using multivariable logistic regressions, we examined the associations between key correlates (i.e. age, income, lockdown-related income loss, migration, employment status, social capital, preparedness, and received social support) and overall food insecurity while adjusting for ethnicity, gender, education, household size, and marital status. Results showed that compared to local Shanghai residents, migrants (i.e, permanent migrants with Hukou (OR = 2.16), permanent migrants without Hukou (OR = 2.06), temporary migrants (OR = 2.74)), and participants with less than or greather than 50% lockdown-related income loss (OR = 2.60, OR = 3.09), were associated with higher odds of overall food insecurity. Participants with greater preparedness (OR = 0.66), greater bonding social capital (OR = 0.93), and greater bridging social capital (OR = 0.94), had lower odds of overall food insecurity. Targeted interventions are needed to enhance food resilience and health equity among vulnerable populations.

Abstract

BACKGROUND: Limited evidence exists about the prevalence and incidence of mild cognitive impairment (MCI) in individuals with diabetes in the U.S. We aimed to address such knowledge gaps using a nationally representative study dataset.METHOD: We conducted a secondary analysis from the Health and Retirement Study (HRS) (1996-2018). The sample for examining the prevalence of MCI was14,988, with 4,192 (28.0%) having diabetes, while the sample for the incidence was 21,824, with 1,534 (28.0%) having diabetes.RESULTS: Participants with diabetes had a higher prevalence of MCI than those without diabetes (19.9% vs. 14.8%; odds ratio [95% confidence interval] (OR[95%CI]): 1.468 [1.337, 1.611], p<.001). The incidence of MCI in participants with/without newly diagnosed diabetes was 42.9% vs. 31.6% after a mean 10-year follow-up, with the incidence rate ratio (IRR) [95%CI] (1.314 [1.213, 1.424], p<.001). Newly diagnosed diabetes was associated with elevated risks of MCI compared with non-diabetes, with the uncontrolled hazard ratio (HR) [95%CI] (1.498 [1.405, 1.597], p<.001).CONCLUSIONS: Using a nationally representative study data in the U.S., participants with diabetes had a higher prevalence and incidence of MCI than those without diabetes. Findings show the importance of developing interventions tailored to the needs of individuals with diabetes and cognitive impairment.

Abstract

Background: Previous research has reported the association between social isolation and cognitive impairment. However, biological mechanisms underlying this association are understudied. It is also unclear whether there are sex differences in these biological mechanisms. Objectives: To examine whether chronic inflammation biomarkers are potential mediators of the association between social isolation and cognitive functioning among older men and women. Methods: Data were the National Health and Nutrition Examination Survey 1999–2002. A total of 2535 older adults aged 60 and older were included. Chronic inflammation was measured by C-reactive protein (CRP), plasma fibrinogen, and serum albumin. Cognitive functioning was assessed by the Digit Symbol Substitution Test (DSST). Social isolation was defined using a 4-point composite index of items pertaining to the strength of social network and support. Linear regression models and formal mediation analysis were applied. Results: Social isolation was associated with lower DSST scores [β (SE) = −2.445 (1.180), p < 0.01 for men; β (SE) = −5.478 (1.167), p < 0.001 for women]. For older men, social isolation was associated with higher levels of CRP (β [SE] = 0.226 (0.110), p < 0.05) and fibrinogen (β [SE] = 0.058 (0.026), p < 0.05). In mediation analyses, among older men, CRP mediated 6.1% and fibrinogen mediated 12.0% of the association of social isolation with DSST. Conclusion: Social isolation was associated with poorer cognitive functioning partially via heightened inflammatory responses in older men. Defining these associations’ mechanisms in sex-specific contexts could inform preventive and therapeutic strategies for cognitive impairment in older adults.

Abstract

Objective: Social isolation and loneliness have been linked to numerous determinants of health and well-being. However, the effects of social isolation and loneliness on oral health remain unclear. The purpose of this study was to examine the effects of social isolation and loneliness on the number of remaining teeth and the rate of tooth loss over time among Chinese older adults. Methods: We used three waves of data (2011/2012, 2014 and 2018) from the Chinese Longitudinal Healthy Longevity Survey with 4268 older adults aged 65 and older who were interviewed in at least two waves. The number of remaining teeth was first evaluated at baseline and then subsequently at follow-up visits. Mixed-effects Poisson regression was used to examine the associations between social isolation, loneliness, and both the number of remaining teeth and the rate of tooth loss. Results: Social isolation was associated with fewer remaining teeth (β = −.06, 95% CI = −0.13 to 0.00, p <.05) and accelerated tooth loss (β = −.02, 95% CI = −0.02 to −0.01, p <.01) after adjusting for sociodemographic covariates, lifestyle and oral hygiene behaviours, physical and cognitive health, and loneliness. Loneliness was neither associated with the number of remaining teeth (β =.15, 95% CI = −0.01 to 0.30, p =.06) nor with the rate of tooth loss (β = −.01, 95% CI = −0.02 to 0.00, p =.16) after adjusting for all other factors. Conclusions: This study provides strong evidence that social isolation was associated with fewer remaining teeth and accelerated tooth loss among Chinese older adults. These findings expand our knowledge about the impact of social disconnection on tooth loss. More future studies are needed to further examine the associations between social connections and oral conditions using longitudinal cohort studies and intervention studies.

Abstract

Background: Social isolation is prevalent and associated with dementia, yet the directionality and mechanisms are less understood. This study examined the association between social isolation and cognitive functioning and explored the mediating role of sleep disturbance on the social isolation–cognition relationship. Methods: Data from 5 753 dementia-free Americans aged ≥50 of 2006 (T1), 2010 (T2), and 2014 (T3) waves of the Health and Retirement Study. Social isolation was measured by the Steptoe Social Isolation Index. Cognitive functioning was measured by the Telephone Interview of Cognitive Status. Sleep disturbance was measured with the modified Jenkins Sleep Scale. We used cross-lagged panel models to determine the associations between social isolation, sleep disturbance, and cognitive functioning. Results: Social isolation is significantly associated with subsequent cognitive functioning (T1 to T2: β = −0.055, standard error [SE] = 0.014, p < .001; T2 to T3: β = −0.044, SE = 0.016, p < .001). Lower cognitive functioning is significantly associated with greater subsequent social isolation (T1 to T2: β = −0.101, SE = 0.020, p < .001; T2 to T3: β = −0.058, SE = .011, p < .001). Sleep disturbance at T2 partially mediated the effect of social isolation (T1) on cognitive functioning (T3), accounting for 6.2% of the total effect (β = −0.003, SE = 0.001, p < .01). Conclusions: Social isolation may deteriorate cognitive functioning and vice versa. The association between social isolation and cognition is partially explained by sleep disturbance.