Yaguang Zheng

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This secondary analysis of the National Youth Risk Behavior Survey (years 2015-2019) examines associations between school-based protective factors (i.e., safe school environments and academic achievement) and HIV risk behaviors among sexually experienced adolescent gay and bisexual men ( n = 644), a population with the highest prevalence of undiagnosed HIV infections. Demographics included Hispanics/Latinos (25%, n = 158), Other race/ethnicity (14%, n = 88), and non-Hispanic Blacks/African Americans (13%, n = 81). Adjusted models showed that protective factors reduced odds for early sexual debut, multiple sexual partners, sex under the influence of drugs/alcohol, and condomless sex, with an additive effect demonstrated when two protective factors were present. Hispanics/Latinos had greater odds of reporting multiple sexual partners and HIV testing, indicating opportunities for school-based HIV prevention and further research. Our findings provide support for school-based programs that aim to improve social and structural determinants of health and ultimately reduce adolescent HIV burdens.

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OBJECTIVE: To explore the age differences in the effects of multi-component periodontal treatments on oral and metabolic indicators among individuals with periodontitis and diabetes.DATA: Trials reporting the effects of multi-component periodontal treatments on oral and metabolic indicators among participants aged 18 and above with periodontitis and diabetes were included.SOURCES: Six databases (PubMed/Medline, Embase, CINHAL, Web of Science, Cochrane Library, and ProQuest) were searched from database inception to August 2022.STUDY SELECTION: Two reviewers selected the included studies independently. We used bivariate and multivariate meta-regression models to examine the association between age and treatment effect size. The primary outcomes were changes in probing depth (PD), clinical attachment level (CAL), and hemoglobin A1c (HbA1c).RESULTS: A total of 18,067 articles were identified in the database search. Of these, 115 trials (119 articles) met inclusion criteria. The mean age of participants was 58 years old, ranging from 35 to 73 years. The pooled evidence demonstrated that multi-component periodontal treatment significantly reduced PD (g=0.929 [0.689-1.169], I2=94.1%), CAL (g=0.879 [0.669-1.089], I2=92.1%), and HbA1c (g=0.603 [0.443-0.763], I2=87.5%). A significant decreasing trend was observed in the effect size for PD (P for trend = 0.020) and CAL (P for trend = 0.028) as age increases. Results from multivariate meta-regression showed that mean age was associated with a smaller effect size for PD (β=-0.123 [0.041], P = 0.004) and CAL (β=-0.159 [0.055], P = 0.006). Compared to their younger counterparts, the effect size for HbA1c was smaller among participants aged 55 and older (β=-0.792 [0.322], P = 0.017).CONCLUSIONS: Multi-component periodontal treatments may be more effective in younger populations in terms of effects on PD, CAL, and HbA1c.CLINICAL SIGNIFICANCE: Our study highlights the importance of early intervention and tailored treatment approaches. Clinicians should take into account the patient's age when developing periodontal treatment plans and may need to employ more aggressive or personalized strategies for older adults to achieve optimal outcomes.

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BACKGROUND: Family support is important in assisting with diabetes self-management for individuals with cognitive impairment, but what types of family support are most effective remain unknown.OBJECTIVES: We aimed to examine the association between the types of family support in diabetes self-management with glycemic control in middle-aged and older adults with cognitive impairment.METHODS: A total of 267 individuals were included with diabetes and cognitive impairment (27-point Telephone Interview for Cognitive Status score

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Objective: Dietary self-management is one key component to achieve optimal glycemic control. Advances in mobile health (mHealth) technology have reduced the burden of diabetes self-management; however, limited evidence has been known regarding the status of the current body of research using mHealth technology for dietary management for adults with type 2 diabetes. Methods: Literature searches were conducted electronically using PubMed, CINAHL (EBSCO), Web of Science Core Collection, PsycINFO (Ovid), EMBASE (Ovid), and Scopus. Keywords and subject headings covered dietary management, type 2 diabetes, and mHealth. Inclusion criteria included studies that applied mHealth for dietary self-management for adults with type 2 diabetes and were published in English as full articles. Results: This review (N = 15 studies) revealed heterogeneity of the mHealth-based dietary self-management or interventions and reported results related to physiological, dietary behavioral, and psychosocial outcomes. Twelve studies applied smartphone apps with varied functions for dietary management or intervention, while three studies applied continuous glucose monitoring (CGM) to guide dietary changes. Among 15 reviewed studies, only three of them were two-arm randomized clinical trial (RCT) with larger sample and 12-month study duration and 12 of them were pilot testing. Nine of 12 pilot studies showed improved HbA1c; most of them resulted in varied dietary changes; and few of them showed improved diabetes distress and depression. Conclusion: Our review provided evidence that the application of mHealth technology for dietary intervention for adults with type 2 diabetes is still in pilot testing. The preliminary effects are inconclusive on physiological, dietary behavioral, and psychosocial outcomes.

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PurposeTo examine the association between intensive, longitudinal ecological momentary assessment (EMA) and self-reported eating behaviors.MethodsSecondary analysis of the EMPOWER study—a 12-month observational study that examined the microprocesses of relapse following intentional weight loss using smartphone-administered EMA—was conducted. Participants were asked to complete four types of EMA surveys using a mobile app. For this analysis, only the number of completed random EMA surveys was used. Using linear mixed-effects modeling, we analyzed whether the number of completed random EMA surveys was associated with changes in self-reported dietary restraint, dietary disinhibition, and susceptibility to hunger measured using the Three-Factor Eating Questionnaire (TFEQ).ResultsDuring the 12-month study, 132 participants completed a mean of 1062 random EMA surveys (range: 673–1362). The median time it took for participants to complete random EMA surveys was 20 s and 90% of random EMA surveys were completed within 46 s. The number of completed random EMA surveys was not significantly associated with the TFEQ scores.ConclusionsIntensive longitudinal EMA did not influence self-reported eating behaviors. The findings suggest that EMA can be used to frequently assess real-world eating behaviors with minimal concern about assessment reactivity. Nonetheless, care must be taken when designing EMA surveys—particularly when using self-reported outcome measures.

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This analysis of the Youth Risk Behavior Survey examined HIV syndemic factor associations (substance use, violence, mental health, and HIV risk behaviors) among adolescent gay, bisexual, and other men who have sex with men-a population with the highest prevalence of undiagnosed HIV infections. The representative sample ( n = 644) exhibited low condom use (52%) and HIV testing (21%). Adjusted multivariate logistic regression models showed that Blacks were less likely to report HIV testing (adjusted odds ratio [aOR] = 0.06, 95% confidence interval [CI] [0.01-0.44], p < .01), whereas Hispanics were more likely to report four or more lifetime sexual partners (aOR = 3.75, 95% CI [1.49-9.44], p < .01), compared with Whites. A syndemic of substance use and intimate partner violence (sexual, sexual dating, and/or physical dating violence) was associated with early intercourse, multiple sexual partners, and drugs/alcohol before intercourse. Multiple syndemic factor exposures were associated with additive risk, suggesting multilevel approaches for HIV prevention.

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BACKGROUND: Engagement with self-monitoring of blood pressure (BP) declines, on average, over time but may vary substantially by individual.OBJECTIVES: We aimed to describe different 1-year patterns (groups) of self-monitoring of BP behaviors, identify predictors of those groups, and examine the association of self-monitoring of BP groups with BP levels over time.METHODS: We analyzed device-recorded BP measurements collected by the Health eHeart Study-an ongoing prospective eCohort study-from participants with a wireless consumer-purchased device that transmitted date- and time-stamped BP data to the study through a full 12 months of observation starting from the first day they used the device. Participants received no instruction on device use. We applied clustering analysis to identify 1-year self-monitoring, of BP patterns.RESULTS: Participants had a mean age of 52 years and were male and White. Using clustering algorithms, we found that a model with three groups fit the data well: persistent daily use (9.1% of participants), persistent weekly use (21.2%), and sporadic use only (69.7%). Persistent daily use was more common among older participants who had higher Week 1 self-monitoring of BP frequency and was associated with lower BP levels than the persistent weekly use or sporadic use groups throughout the year.CONCLUSION: We identified three distinct self-monitoring of BP groups, with nearly 10% sustaining a daily use pattern associated with lower BP levels.