Background A pandemic is a very stressful event, especially for highly vulnerable people (e.g., older adults). The purpose of the current study was to investigate the main and interactive relationships of social support and resilience on individual mental health during the COVID-19 pandemic across three age groups: emerging adults, adults, and older adults. Methods A survey was conducted with 23,192 participants aged 18–85. Respondents completed a questionnaire, including items on the COVID-19-related support they perceived from different sources, the abbreviated version of the Connor-Davidson Resilience Scale, and the Mental Health Inventory. Results Latent profile analysis identified five profiles of social support, and the patterns of potential profiles were similar in all groups. However, category distribution in the five profiles was significantly different among the age groups. Furthermore, analysis using the BCH command showed significant differences in mental health among these profiles. Lastly, interactive analyses indicated resilience had a positive relationship with mental health, and social support served as a buffer against the negative impact of low resilience on mental health. Conclusions This study provides quantitative evidence for socioemotional selectivity theory (SST) and enables several practical implications for helping different age groups protecting mental health during pandemic.

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Physiological levels of cortisol have been found to blunt neuroendocrine and metabolic responses to subsequent hypoglycemia in humans. The aim of this study was to determine whether cortisol acts directly on the brain to elicit this effect. A total of 41 conscious unrestrained Sprague-Dawley rats were studied during 2-day experiments. Day 1 consisted of two episodes of clamped 2-h hyperinsulinemic (30 pmol ⅐ kg ؊1 ⅐ min ؊1 ) hypoglycemia (2.8 ؎ 0.1 mmol/l; n ‫؍‬ 12; ANTE HYPO), euglycemia (6.2 ؎ 0.1 mmol/l; n ‫؍‬ 12; ANTE EUG), or euglycemia (6.2 ؎ 0.1 mmol/l) plus simultaneous intracerebroventricular (ICV) infusion of cortisol (25 g/h; n ‫؍‬ 9; ANTE EUG؉Cort) or saline (24 l/h; n ‫؍‬ 8; ANTE EUG؉Sal). For all groups, day 2 consisted of a 2-h hyperinsulinemic (30 pmol ⅐ kg ؊1 ⅐ min ؊1 ) hypoglycemic (2.9 ؎ 0.2 mmol/l) clamp. Plasma epinephrine and glucagon incremental area under the curve (⌬AUC) responses were significantly less in ANTE EUG؉Cort and ANTE HYPO versus both ANTE EUG and ANTE EUG؉Sal (P < 0.05). The ⌬AUC responses of plasma norepinephrine were significantly lower in ANTE EUG؉Cort versus both ANTE EUG and ANTE EUG؉Sal (P < 0.05). Endogenous glucose production was significantly less in ANTE HYPO and ANTE EUG؉Cort versus the other groups (P < 0.05). Lastly, the glucose infusion rate to maintain the desired hypoglycemia was significantly greater in ANTE EUG؉Cort and ANTE HYPO versus the other two groups (P < 0.05). In summary, ICV infusion of cortisol significantly blunted norepinephrine, epinephrine, glucagon, and endogenous glucose production responses to next-day hypoglycemia. We conclude that cortisol can act directly on the central nervous system to blunt counterregulatory responses to subsequent hypoglycemia in the conscious rat. Diabetes 52:2198 -2204, 2003 I ntensive glucose control in type 1 diabetic patients can slow the progression or prevent complications of diabetes such as retinopathy, nephropathy, or neuropathy (1). Unfortunately, it is also well established that intensive glucose treatment increases the frequency of severe hypoglycemia (2). The mechanism for the increased frequency of hypoglycemia may not be simply due to insulin excess. It has been clearly established (3-5) that repeated exposure to hypoglycemia can reduce neuroendocrine (catecholamine, glucagon, and growth hormone) and metabolic (endogenous glucose production [EGP], lactate, and glycerol) counterregulatory responses to subsequent hypoglycemia by as much as 50% in healthy humans and type 1 diabetic subjects (6,7). Thus, blunted counterregulatory responses make type 1 diabetic patients susceptible to an increased vicious cycle of hypoglycemia.Cortisol has been proposed to play a role in blunting neuroendocrine and metabolic responses to subsequent hypoglycemia (8,9). Similar to antecedent hypoglycemia, antecedent elevations of cortisol through infusion of cortisol (9) or adrenocorticotropic hormone (ACTH) (10) blunted neuroendocrine and metabolic counterregulatory responses to subsequent day 2 hypoglycemia in nondiabetic...

Aims/Introduction The coronavirus disease 2019 (COVID‐19) pandemic urged authorities to impose rigorous quarantines and brought considerable changes to people’s lifestyles. The impact of these changes on glycemic control has remained unclear, especially the long‐term effect. We aimed to investigate the impact of COVID‐19 lockdown on glycemic control in children and adolescents with type 1 diabetes. Materials and Methods This observational study enrolled children with type 1 diabetes using continuous glucose monitoring. Continuous glucose monitoring data were extracted from the cloud‐based platform before, during and after lockdown. Demographics and lifestyle change‐related information were collected from the database or questionnaires. We compared these data before, during and after lockdown. Results A total of 43 children with type 1 diabetes were recruited (20 girls; mean age 7.45 years; median diabetes duration 1.05 years). We collected 41,784 h of continuous glucose monitoring data. Although time in range (3.9–10.0 mmol/L) was similar before, during and after lockdown, the median time below range <3.9 mmol/L decreased from 3.70% (interquartile range [IQR] 2.25–9.53%) before lockdown to 2.91% (IQR 1.43–5.95%) during lockdown, but reversed to 4.95% (IQR 2.11–9.42%) after lockdown ( P = 0.004). Time below range <3.0 mmol/L was 0.59% (IQR 0.14–2.21%), 0.38% (IQR 0.05–1.35%) and 0.82% (IQR 0.22–1.69%), respectively ( P = 0.008). The amelioration of hypoglycemia during lockdown was more prominent among those who had less time spent <3.9 mmol/L at baseline. During lockdown, individuals reduced their physical activity, received longer sleep duration and spent more time on diabetes management. In addition, they attended outpatient clinics less and turned to telemedicine more frequently. Conclusion Glycemic control did not deteriorate in children and teenagers with type 1 diabetes around the COVID‐19 pandemic. Hypoglycemia declined during lockdown, but reversed after lockdown, and the changes related to lifestyle might not provide a long‐term effect.

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In this population-based study, we identified 307 confirmed COVID-19 cases from massive surveillance, including 129,551 individuals screened at fever clinics or returning from Hubei and 3710 close contacts of confirmed COVID-19 patients. Among them, 17 patients were asymptomatic at initial clinical assessment. These asymptomatic patients on admission accounted for a small proportion of all patients (5.54%) with relatively weak transmissibility, and the detection rate was 0.35 per 100 close contacts. Moreover, the dynamics of symptoms of the 307 patients showed that the interval from symptom remission to the final negativity of viral nucleic acid was 5.0 days (IQR 2.0 to 11.0 days), with 14 patients (4.56%) having re-detectable viral RNA after discharge. Together, our findings suggested asymptomatic carriers and presymptomatic patients only accounted for a small proportion of COVID-19. Also, the asymptomatic phase in during recovery of COVID-19 urged that negativity in viral RNA is necessary as de-isolation criteria and follow-up is recommended.

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Aims Continuous glucose monitoring (CGM) overcomes the limitations of glycated hemoglobin (HbA1c). This study was to investigate the relationship between CGM metrics and laboratory HbA1c in pregnant women with type 1 diabetes. Methods An observational study enrolled pregnant women with type 1 diabetes who wore CGM devices during pregnancy and postpartum from 11 hospitals in China from January 2015 to June 2019. CGM data were collected to calculate time-in-range (TIR), time above range (TAR), time below range (TBR), and glycemic variability parameters. Relationships between the CGM metrics and HbA1c were explored. Linear and curvilinear regressions were conducted to investigate the best-fitting model to clarify the influence of HbA1c on the TIR-HbA1c relationship during pregnancy. Results A total of 272 CGM data and corresponding HbA1c from 98 pregnant women with type 1 diabetes and their clinical characteristics were analyzed in this study. Mean HbA1c and TIR were 6.49±1.29% and 76.16±17.97% during pregnancy, respectively. HbA1c was moderately correlated with TIR 3.5-7.8(R= -0.429, P=0.001), mean glucose (R= 0.405, P=0.001) and TAR 7.8 (R=0.435, P=0.001), but was weakly correlated with TBR 3.5 (R=0.034, P=0.001) during pregnancy. On average, a 1% (11 mmol/mol) decrease in HbA1c corresponded to an 8.5% increase in TIR 3.5-7.8. During pregnancy, HbA1c of 6.0%, 6.5% and 7.0% were equivalent to a TIR 3.5-7.8 of 78%, 74%, and 69%, respectively. Conclusions We found that there was a moderate correlation between HbA1c and TIR 3.5-7.8 during pregnancy. To achieve the HbA1c target &lt;6.0%, pregnant women with type 1 diabetes should strive for TIR 3.5-7.8 &gt;78% (18h 43min) during pregnancy.