Seasonality in diabetes in Yaounde, Cameroon: a relation with precipitation and temperature

The relationship of short-term exposure to meteorological factors on diabetes mellitus mortality risk in Hefei, China: a time series analysis

OBJECTIVES

The study aims to explore whether short-term exposure to meteorological factors has a potential association with the risk of diabetes mellitus (DM) mortality.

METHODS

During the period 2015-2018, we collected daily data on meteorological factors and deaths of diabetic patients in Hefei. A total of 1101 diabetic deaths were recorded. We used structural equation modeling to initially explore the relationships among air pollutants, meteorological variables, and mortality, and generalized additive modeling (GAM) and distributional lag nonlinear modeling (DLNM) to explore the relationship between meteorological factors and the mortality risk of DM patients. We also stratified by age and gender. The mortality risk in diabetic patients was expressed by relative risks (RR) and 95% confidence intervals (CI) for both single and cumulative days.

RESULTS

Single-day lagged results showed a high relative humidity (RH) (75th percentile, 83.71%), a fairly high average temperature (T mean) (95th percentile, 30.32 °C), and an extremely low diurnal temperature range (DTR) (5th percentile, 3.13 °C) were positively related to the mortality risk of DM. Stratified results showed that high and very high levels of T mean were significantly positively linked to the mortality risk of DM among females and the elderly, while very high levels of DTR were linked to the mortality risk in men and younger populations.

CONCLUSION

In conclusion, this study found that short-duration exposure to quite high T mean, high RH, and very low DTR were significantly positively related to the mortality risk of DM patients. For women and older individuals, exposure to high and very high T mean environments should be minimized. Men and young adults should be aware of daily temperature changes.

Climate change-induced shifts in the food systems and diet-related non-communicable diseases in sub-Saharan Africa: a scoping review and a conceptual framework

OBJECTIVES

To determine the relationship between climate change, food systems and diet-related non-communicable diseases (DR-NCDs) in sub-Saharan Africa (SSA) and propose a conceptual framework for food systems in SSA.

DESIGN

A scoping review.

ELIGIBILITY CRITERIA

Studies included investigated the relationship between climate change and related systemic risks, food systems, DR-NCDs and its risk factors in SSA. Studies focusing on the association between climate change and DR-NCDs unrelated to food systems, such as social inequalities, were excluded.

SOURCES OF EVIDENCE

A comprehensive search was conducted in ProQuest (nine databases), Google Scholar and PubMed in December 2022.

CHARTING METHODS

Data extracted from studies included author, study type, country of study, climate change component, DR-NCD outcomes and risk factors, and impacts of climate change on DR-NCDs. A narrative approach was used to analyse the data. Based on the evidence gathered from SSA, we modified an existing food system conceptual framework.

RESULTS

The search retrieved 19 125 studies, 10 of which were included in the review. Most studies used a cross-sectional design (n=8). Four explored the influence of temperature on liver cancer through food storage while four explored the influence of temperature and rainfall on diabetes and obesity through food production. Cross-sectional evidence suggested that temperature is associated with liver cancer and rainfall with diabetes.

CONCLUSION

The review highlights the vulnerability of SSA's food systems to climate change-induced fluctuations, which in turn affect dietary patterns and DR-NCD outcomes. The evidence is scarce and concentrates mostly on the health effects of temperature through food storage. It proposes a conceptual framework to guide future research addressing climate change and DR-NCDs in SSA.

The impact of environmental conditions on non-communicable diseases in sub-Saharan Africa: A scoping review of epidemiologic evidence

Background

The burden of non-communicable diseases (NCDs) in sub-Saharan Africa (SSA) is increasing. Environmental conditions such as heavy metals and air pollution have been linked with the incidence and mortality of chronic diseases such as cancer, as well as cardiovascular and respiratory diseases. We aimed to scope the current state of evidence on the impact of environmental conditions on NCDs in SSA.

Methods

We conducted a scoping review to identify environmental conditions linked with NCDs in SSA by identifying studies published from January 1986 through February 2023. We searched African Index Medicus, Ovid Medline, Scopus, Web of Science, and Greenfile. Using the PICOS study selection criteria, we identified studies conducted in SSA focussed on physical environmental exposures and incidence, prevalence, and mortality of NCDs. We included only epidemiologic or quantitative studies.

Results

We identified 6754 articles from electronic database searches; only 36 met our inclusion criteria and were qualitatively synthesised. Two studies were conducted in multiple SSA countries, while 34 were conducted across ten countries in SSA. Air pollution (58.3%) was the most common type of environmental exposure reported, followed by exposure to dust (19.4%), meteorological variables (13.8%), heavy metals (2.7%), soil radioactivity (2.7%), and neighbourhood greenness (2.7%). The examined NCDs included respiratory diseases (69.4%), cancer (2.7%), stroke (5.5%), diabetes (2.7%), and two or more chronic diseases (19.4%). The study results suggest an association between environmental exposures and NCDs, particularly for respiratory diseases. Only seven studies found a null association between environmental conditions and chronic diseases.

Conclusions

There is a growing body of research on environmental conditions and chronic diseases in the SSA region. Although some cities in SSA have started implementing environmental monitoring and control measures, there remain high levels of environmental pollution. Investment can focus on improving environmental control measures and disease surveillance.

Predictors of prolonged length of hospital stay and in-hospital mortality in patients aged 1-24 months with acute bronchiolitis in Douala, Cameroon

INTRODUCTION

In Cameroon, acute bronchiolitis has been reported as the third commonest lower respiratory infection and is usually associated with low mortality. Nonetheless, respiratory distress associated with non-adherence to management guidelines can prolong hospital stay. This study aimed to explore predictors of prolonged hospital stay (≥ 5 days) and mortality in patients aged < 2years hospitalised for acute bronchiolitis.

METHODOLOGY

We conducted a retrospective cohort study at three paediatric units in the city of Douala, Cameroon. Factors associated with prolonged hospital stay and mortality were determined using multivariable linear regression model. Threshold for significance was set at p ≤ 0.05.

RESULTS

A total of 215 patients with bronchiolitis were included with mean age of 6.94 ± 5.71 months and M/F sex ratio of 1.39/1. Prolonged hospital stay was reported in 46.98% and mortality in 10.70% of patients hospitalised for bronchiolitis. Factors independently associated with prolonged hospital duration were oxygen administration [b = 0.36, OR = 2.35 (95% CI:1.16-4.74), p = 0.017], abnormal respiratory rate [b = 0.38, OR = 2.13 (1.00-4.55), p = 0.050] and patients presenting with cough [b = 0.33, OR = 2.35 (95% CI: 1.22-4.51), p = 0.011], and diarrhoea [b = 0.71, OR = 6.44 (95% CI: 1.6-25.86), p = 0.009] on admission. On the other hand, factors independently associated with mortality were age of the patient [b= -0.07, OR = 0.84 (95% CI: 0.74-0.97), p = 0.014] and oxygen administration [b = 1.08, OR = 9.64 (95% CI:1.16-79.85), p = 0.036] CONCLUSION: Acute bronchiolitis represented 1.24% of admissions and was common in the rainy season, in males and 3-11-month-old patients. Management guidelines were poorly respected. Prolonged length of stay was reported in half of the patients hospitalized and mortality was high, especially in younger patients and in patients receiving oxygen.

Seasonal changes in proportion of cardiac surgeries associated with diabetes, smoking and elderly age

Background

Seasonal variations in the ambient temperature may affect the exacerbation of cardiovascular diseases. Our primary objective was to evaluate the seasonality of the monthly proportion of cardiac surgeries associated with diabetes, smoking and/or elderly age at a tertiary-care university hospital in East-Central Europe with a temperate climate zone. As a secondary objective, we also assessed whether additional factors affecting small blood vessels (smoking, aging, obesity) modulate the seasonal variability of diabetes.

Methods

Medical records were analyzed for 9838 consecutive adult patients who underwent cardiac surgery in 2007–2018. Individual seasonal variations of diabetes, smoking, and elderly patients were analyzed monthly, along with the potential risk factors for cardiovascular complication. We also characterized whether pairwise coexistence of diabetes, smoking, and elderly age augments or blunts the seasonal variations.

Results

Seasonal variations in the monthly proportion of cardiac surgeries associated with diabetes, smoking and/or elderly age were observed. The proportion of cardiac surgeries of non-elderly and smoking patients with diabetes peaked in winter (amplitude of change as [peak-nadir]/nadir: 19.2%, p<0.02), which was associated with increases in systolic (6.1%, p<0.001) and diastolic blood pressures (4.4%, p<0.05) and serum triglyceride levels (27.1%, p<0.005). However, heart surgery in elderly patients without diabetes and smoking was most frequently required in summer (52.1%, p<0.001). Concomitant occurrence of diabetes and smoking had an additive effect on the requirement for cardiac surgery (107%, p<0.001), while the simultaneous presence of older age and diabetes or smoking eliminated seasonal variations.

Conclusions

Scheduling regular cardiovascular control in accordance with periodicities in diabetes, elderly, and smoking patients more than once a year may improve patient health and social consequences.

Trial registration

NCT03967639.

Non-autoimmune diabetes mellitus and the risk of virus infections: a systematic review and meta-analysis of case-control and cohort studies

A significant number of studies invoked diabetes as a risk factor for virus infections, but the issue remains controversial. We aimed to examine whether non-autoimmune diabetes mellitus enhances the risk of virus infections compared with the risk in healthy individuals without non-autoimmune diabetes mellitus. In this systematic review and meta-analysis, we assessed case-control and cohort studies on the association between non-autoimmune diabetes and viruses. We searched PubMed, Embase, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, and Web of Science with no language restriction, to identify articles published until February 15, 2021. The main outcome assessment was the risk of virus infection in individuals with non-autoimmune diabetes. We used a random-effects model to pool individual studies and assessed heterogeneity (I²) using the χ2 test on Cochrane's Q statistic. This study is registered with PROSPERO, number CRD42019134142. Out of 3136 articles identified, we included 68 articles (90 studies, as the number of virus and or diabetes phenotype varied between included articles). The summary OR between non-autoimmune diabetes and virus infections risk were, 10.8(95% CI: 10.3-11.4; 1-study) for SARS-CoV-2; 3.6(95%CI: 2.7-4.9, I² = 91.7%; 43-studies) for HCV; 2.7(95% CI: 1.3-5.4, I² = 89.9%, 8-studies;) for HHV8; 2.1(95% CI: 1.7-2.5; 1-study) for H1N1 virus; 1.6(95% CI: 1.2-2.13, I² = 98.3%, 27-studies) for HBV; 1.5(95% CI: 1.1-2.0; 1-study) for HSV1; 3.5(95% CI: 0.6-18.3 , I² = 83.9%, 5-studies) for CMV; 2.9(95% CI: 1-8.7, 1-study) for TTV; 2.6(95% CI: 0.7-9.1, 1-study) for Parvovirus B19; 0.7(95% CI: 0.3-1.5 , 1-study) for coxsackie B virus; and 0.2(95% CI: 0-6.2; 1-study) for HGV. Our findings suggest that, non-autoimmune diabetes is associated with increased susceptibility to viruses especially SARS-CoV-2, HCV, HHV8, H1N1 virus, HBV and HSV1. Thus, these viruses deserve more attention from diabetes health-care providers, researchers, policy makers, and stakeholders for improved detection, overall proper management, and efficient control of viruses in people with non-autoimmune diabetes.

Climate factors and gestational diabetes mellitus risk - a systematic review

BACKGROUND

Current and projected increases in global temperatures and extreme climate events have led to heightened interest in the impact of climate factors (i.e. ambient temperature, season/seasonality, and humidity) on human health. There is growing evidence that climate factors may impact metabolic function, including insulin sensitivity. Gestational diabetes mellitus (GDM) is a common pregnancy complication, with an estimated global prevalence of up to 14%. While lifestyle and genetic risk factors for GDM are well established, environmental factors may also contribute to GDM risk. Previous reviews have summarized the growing evidence of environmental risk factors for GDM including endocrine disrupting chemicals and ambient air pollution. However, studies of the effects of climate factors on GDM risk have not been systematically evaluated. Therefore, we conducted a systematic review to summarize and evaluate the current literature on the associations of climate factors with GDM risk.

METHODS

We conducted systematic searches in PubMed and EMBASE databases for original research articles on associations of climate factors (i.e. ambient temperature, season/seasonality, and humidity) with GDM and/or related glycemic outcomes for all publication dates through September 20th, 2020.

RESULTS

Our search identified 16 articles on the associations of ambient temperature and/or season with GDM and maternal glycemic outcomes during pregnancy, which were included in this review. Despite inconsistencies in exposure and outcome assessment, we found consistent evidence of a seasonal effect on GDM risk, with higher prevalence of GDM and higher pregnancy glucose levels in summer months. We found suggestive evidence of an association between higher ambient temperature and elevated glucose levels from GDM screening tests.

CONCLUSION

Climate factors may be associated with GDM risk. However, further research is needed to evaluate these associations and to elucidate the specific mechanisms involved.

Risk Analysis of Air Pollution and Meteorological Factors Affecting the Incidence of Diabetes in the Elderly Population in Northern China

BACKGROUND

Research investigating the effect of air pollution on diabetes incidence is mostly conducted in Europe and the United States and often produces conflicting results. The link between meteorological factors and diabetes incidence remains to be explored. We aimed to explore associations between air pollution and diabetes incidence and to estimate the nonlinear and lag effects of meteorological factors on diabetes incidence.

METHODS

Our study included 19,000 people aged ≥60 years from the Binhai New District without diabetes at baseline. The generalized additive model (GAM) and the distributed lag nonlinear model (DLNM) were used to explore the effect of air pollutants and meteorological factors on the incidence of diabetes. In the model combining the GAM and DLNM, the impact of each factor (delayed by 30 days) was first observed separately to select statistically significant factors, which were then incorporated into the final multivariate model. The association between air pollution and the incidence of diabetes was assessed in subgroups based on age, sex, and body mass index (BMI).

RESULTS

We found that cumulative RRs for diabetes incidence were 1.026 (1.011-1.040), 1.019 (1.012-1.026), and 1.051 (1.019-1.083) per 10 μg/m³ increase in PM_2.5, PM₁₀, and NO₂, respectively, as well as 1.156 (1.058-1.264) per 1 mg/m³ increase in CO in a single-pollutant model. Increased temperature, excessive humidity or dryness, and shortened sunshine duration were positively correlated with the incidence of diabetes in single-factor models. After adjusting for temperature, humidity, and sunshine, the risk of diabetes increased by 9.2% (95% confidence interval (CI):2.1%-16.8%) per 10 μg/m³ increase in PM_2.5. We also found that women, the elderly (≥75 years), and obese subjects were more susceptible to the effect of PM_2.5.

CONCLUSION

Our data suggest that PM_2.5 is positively correlated with the incidence of diabetes in the elderly, and the relationship between various meteorological factors and diabetes in the elderly is nonlinear.

Seasonal and Monthly Patterns, Weekly Variations, and the Holiday Effect of Outpatient Visits for Type 2 Diabetes Mellitus Patients in China

OBJECTIVE

To explore the seasonal and monthly patterns, weekly variations, and the holiday effect of outpatient visits for type 2 diabetes mellitus patients, as well as the influence of gender, age, and insurance type on variations.

METHODS

Data were obtained from the Shandong medical insurance database, including all outpatients in 12 cities of Shandong province in China from 2015 to 2017. The seasonal index (S_t) was calculated in terms of seasons, months, and weeks by the moving average method.

RESULTS

A total of 904,488 patients received outpatient services during the study period. The seasonal indices of outpatient visits by type 2 diabetes patients were higher in autumn (108.36%) and spring (102.67%), while lower in winter (89.92%) and summer (99.04%), exhibiting an obvious seasonality. Gender and age had no effect on seasonal patterns. The month impacted the seasons patterns: January to February were the lowest and December the highest months of outpatient visits, complicating the seasonal patterns. We also identified a weekly pattern of outpatient visits. In addition, the outpatient visits for type 2 diabetes mellitus patients was also strongly affected by the Spring Festival, Lantern Festival, and National Day holiday periods. The type of medical insurance had a significant impact on outpatient visits.

CONCLUSIONS

The outpatient visits for type 2 diabetes mellitus patients displayed seasonal patterns that were contradictory to the variations in blood glucose fluctuations found in previous studies and was also strongly affected by the holiday effect. The type of medical insurance impacted the pattern of outpatient visits.

Chronic lifestyle diseases display seasonal sensitive comorbid trend in human population evidence from Google Trends

Seasonal and human physiological changes are important factors in the development of many diseases. But, the study of genuine seasonal impact on these diseases is difficult to measure due to many other environment and lifestyle factors which directly affect these diseases. However, several clinical studies have been conducted in different parts of the world, and it has clearly indicated that certain groups of population are highly subjected to seasonal changes, and their maladaptation can possibly lead to several disorders/diseases. Thus, it is crucial to study the significant seasonal sensitive diseases spread across the human population. To narrow down these disorders/diseases, the study hypothesized that high altitude (HA) associated diseases and disorders are of the strong variants of seasonal physiologic changes. It is because, HA is the only geographical condition for which humans can develop very efficient physiological adaptation mechanism called acclimatization. To study this hypothesis, PubMed was used to collect the HA associated symptoms and disorders. Disease Ontology based semantic similarity network (DSN) and disease-drug networks were constructed to narrow down the benchmark diseases and disorders of HA. The DSN which was further subjected to different community structure analysis uncovered the highly associated or possible comorbid diseases of HA. The predicted 12 lifestyle diseases were assumed to be “seasonal (sensitive) comorbid lifestyle diseases (SCLD)”. A time series analyses on Google Search data of the world from 2004–2016 was conducted to investigate whether the 12 lifestyle diseases have seasonal patterns. Because, the trends were sensitive to the term used as benchmark; the temporal relationships among the 12 disease search volumes and their temporal sequences similarity by dynamic time warping analyses was used to predict the comorbid diseases. Among the 12 lifestyle diseases, the study provides an indirect evidence in the existence of severe seasonal comorbidity among hypertension, obesity, asthma and fibrosis diseases, which is widespread in the world population. Thus, the present study has successfully addressed this issue by predicting the SCLD, and indirectly verified them among the world population using Google Search Trend. Furthermore, based on the SCLD seasonal trend, the study also classified them as severe, moderate, and mild. Interestingly, seasonal trends of the severe seasonal comorbid diseases displayed an inverse pattern between USA (Northern hemisphere) and New Zealand (Southern hemisphere). Further, knowledge in the so called “seasonal sensitive populations” physiological response to seasonal triggers such as winter, summer, spring, and autumn become crucial to modulate disease incidence, disease course, or clinical prevention.

Human herpesvirus 8 infection DNA positivity is associated with low insulin secretion: A case-control study in a sub-Saharan African population with diabetes

BACKGROUND

Viruses have been considered potential triggers for the development of diabetes. This study assessed insulin secretion and insulin sensitivity in human herpesvirus 8 (HHV8)-infected and uninfected sub-Saharan African people with diabetes.

METHODS

In all, 173 people with non-autoimmune diabetes were enrolled consecutively: 124 with type 2 diabetes mellitus (T2DM) and 49 with ketosis-prone diabetes (KPD) admitted in hyperglycemic crisis. Those with KPD were further subdivided into those with new-onset ketotic-phase KPD (n = 34) or non-ketotic phase KPD (n = 15). All participants were screened for HHV8-specific antibodies and genomic DNA. Blood samples were collected for analysis of fasting glucose, HbA1c, lipid profile, and C-peptide, with insulin resistance and secretion estimated by homeostasis model assessment.

RESULTS

Among the 173 diabetic participants, 88 (50.9%) were positive for HHV8 antibodies (Ac-HHV8+), including 15 (8.7%) positive for HHV8 DNA (DNA-HHV8+). The seroprevalence of HHV8 was similar between T2DM (55.6%) and KPD (61.2%) subjects. Of those with and without ketotic-phase KPD, 35.3% and 46.7% were Ac-HHV8+, respectively. Body mass index was significantly in lower DNA-HHV8+ than DNA-HHV8- subjects. Low-density lipoprotein and total cholesterol were significantly higher, but C-peptide and homeostatic model assessment of β-cell function (HOMA-β) were significantly lower in DNA-HHV8+ than DNA-HHV8- participants. After excluding DNA-HHV8+ participants, triglyceride concentrations were significantly higher in Ac-HHV8+ (n = 73) than Ac-HHV8- (n = 85) subjects. In contrast, HOMA-β was significantly higher among Ac-HHV8+ than Ac-HHV8- participants.

CONCLUSIONS

In the present study, HHV8 DNA positivity was associated with low insulin secretion in this sub-Saharan African diabetes population.