Exposures to road traffic, noise, and air pollution as risk factors for type 2 diabetes: A feasibility study in Bulgaria

Association between exposure to heavy metals in atmospheric particulate matter and sleep quality: A nationwide data linkage study

BACKGROUND

Recent studies have demonstrated that long-term exposure to particulate matter (PM) is associated with poor sleep quality. However, no studies have linked PM constituents, particularly heavy metals, to sleep quality.

OBJECTIVE

This study investigated the association between exposure to heavy metals in PM and sleep quality.

METHODS

We obtained nationwide data from the Korean Community Health Survey conducted in 2018 among adults aged 19-80 years. Sleep quality was evaluated using Pittsburgh Sleep Quality Index (PSQI). Poor sleep quality was defined as PSQI ≥5. One-year and three-month average concentrations of heavy metals (lead, manganese, cadmium, and aluminum) in PM with diameter ≤10 μm were obtained from nationwide air quality monitoring data and linked to the survey data based on individual district-level residential addresses. Logistic regression analyses were performed after adjusting for age, gender, education level, marital status, smoking status, alcohol consumption, history of hypertension, and history of diabetes mellitus.

RESULTS

Of 32,050 participants, 17,082 (53.3%) reported poor sleep quality. Increases in log-transformed one-year average lead (odds ratio, 1.14; 95% confidence interval, 1.08-1.20), manganese (1.31; 1.25-1.37), cadmium (1.03; 1.00-1.05), and aluminum concentrations (1.17; 1.10-1.25) were associated with poor sleep quality. Increases in log-transformed three-month average manganese (odds ratio, 1.13; 95% confidence interval, 1.09-1.17) and aluminum concentrations (1.28; 1.21-1.35) were associated with poor sleep quality.

CONCLUSION

We showed for the first time that exposure to airborne lead, manganese, cadmium, and aluminum were associated with poor sleep quality. This study may be limited by self-reported sleep quality and district-level exposure data.

Association between occupational noise exposure and diabetes: A systematic review and meta-analysis

BACKGROUND

In addition to the well-known risk factors of diabetes, evidence is accumulating on the negative role of environmental and occupational factors such as noise exposure. We conducted a systematic review and meta-analysis on the association between long-term occupational noise exposure and diabetes.

METHODS

We systematically searched evidence in PubMed, Scopus, and Web of Science (until August 2022) according to the PRISMA protocol. Risk of bias was assessed using the Newcastle-Ottawa scale. Random-effects meta-analysis was applied separately for risk ratio (odds ratio, relative risk) and hazard ratio. We evaluated the heterogeneity and publication bias. We applied meta-regressions to identify sources of heterogeneity. The overall body of evidence was assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) framework.

RESULTS

Of 533 retrieved articles, twelve studies (11 on non-gestational, and one on gestational diabetes) on total 106,045 population (23,996 diabetic cases) met our inclusion criteria; of which eight studies were cross-sectional, three were cohorts, and one was case-control. Only 40% of papers (five out of 12) had fair, good or very good quality, and most of the papers had poor or very poor quality in terms of risk of bias. We observed a non-significant increased risk of diabetes in association with occupational noise exposure (combined risk estimates: 1.16, 95% confidence interval [CI]: 0.97: 1.34; I² = 57.7%). Doing separate meta-analyses on cohort and rest of studies, we found similar findings (cohort studies (n = 3): combined risk estimate: 1.17; 95% CI: 0.84: 1.50; I² = 79%; cross-sectional studies (n = 8): combined risk estimate: 1.26; 95% CI: 0.93: 1.58; I² = 50.4%). We found no indication of publication bias.

CONCLUSIONS

The overall evidence on the association between occupational noise exposure and diabetes is heterogeneous, limited, and mostly with low quality. More robust studies in terms of population selection, exposure and outcome assessment, and adjustment for confounders are necessary.

Occupational and Environmental Noise Exposure and Extra-Auditory Effects on Humans: A Systematic Literature Review

Noise is a common harmful factor in our work and the environment. Most studies have investigated the auditory effects of noise exposure; however, few studies have focused on the extra-auditory effects of exposure to occupational or environmental noise. This study aimed to systematically review published studies on the extra-auditory effects of noise exposure. We reviewed literature from PubMed and Google Scholar databases up to July 2022, using the Patient, Intervention, Comparison, and Outcome criteria and Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to identify studies that reported extra-auditory effects of occupational or environmental noise exposure. Studies were evaluated utilizing validated reporting tools (CONSORT, STROBE) appropriate to study design. A total of 263 articles were identified, of which 36 were finally selected and reviewed. Upon conducting a review of the articles, exposure to noise can elicit a variety of extra-auditory effects on humans. These effects include circulatory effects linked to higher risk of cardiovascular disease and decreased endothelial function, nervous system effects correlated with sleep disturbance, cognitive impairment, and mental health problems, immunological and endocrinal effects connected to increased physiological stress response and metabolic disorders, oncological and respiratory effects associated with an elevated risk of acoustic neuroma and respiratory disorders, gastrointestinal effects linked to an increased risk of gastric or duodenal ulcer, and obstetric effects connected to the risk of preterm birth. Our review suggests that there are numerous extra-auditory effects of noise exposure on human, and further investigations are needed to fully understand these effects.

Long-Term Exposure to Traffic-Related Air Pollution and Diabetes: A Systematic Review and Meta-Analysis

Objectives: We report results of a systematic review on the health effects of long-term traffic-related air pollution (TRAP) and diabetes in the adult population. Methods: An expert Panel appointed by the Health Effects Institute conducted this systematic review. We searched the PubMed and LUDOK databases for epidemiological studies from 1980 to July 2019. TRAP was defined based on a comprehensive protocol. Random-effects meta-analyses were performed. Confidence assessments were based on a modified Office for Health Assessment and Translation (OHAT) approach, complemented with a broader narrative synthesis. We extended our interpretation to include evidence published up to May 2022. Results: We considered 21 studies on diabetes. All meta-analytic estimates indicated higher diabetes risks with higher exposure. Exposure to NO₂ was associated with higher diabetes prevalence (RR 1.09; 95% CI: 1.02; 1.17 per 10 μg/m³), but less pronounced for diabetes incidence (RR 1.04; 95% CI: 0.96; 1.13 per 10 μg/m³). The overall confidence in the evidence was rated moderate, strengthened by the addition of 5 recently published studies. Conclusion: There was moderate evidence for an association of long-term TRAP exposure with diabetes.

Long-term residential exposure to source-specific particulate matter and incidence of diabetes mellitus - A cohort study in northern Sweden

Diabetes mellitus (DM) incidence have been assessed in connection with air pollution exposure in several studies; however, few have investigated associations with source-specific local emissions. This study aims to estimate the risk of DM incidence associated with source-specific air pollution in a Swedish cohort with relatively low exposure. Individuals in the Västerbotten intervention programme cohort were followed until either a DM diagnosis or initiation of treatment with glucose-lowering medication occurred. Dispersion models with high spatial resolution were used to estimate annual mean concentrations of particulate matter (PM) with aerodynamic diameter ≤10 μm (PM₁₀) and ≤2.5 μm (PM_2.5) at individual addresses. Hazard ratios were estimated using Cox regression models in relation to moving averages 1-5 years preceding the outcome. During the study period, 1479 incident cases of DM were observed during 261,703 person-years of follow-up. Increased incidence of DM was observed in association with PM₁₀ (4% [95% CI: -54-137%] per 10 μg/m³), PM₁₀-traffic (2% [95% CI: -6-11%] per 1 μg/m³) and PM_2.5-exhaust (11% [95% CI: -39-103%] per 1 μg/m³). A negative association was found for both PM_2.5 (-18% [95% CI: -99-66%] per 5 μg/m³), but only in the 2nd exposure tertile (-10% [95% CI: -25-9%] compared to the first tertile), and PM_2.5-woodburning (-30% [95% CI: -49-4%] per 1 μg/m³). In two-pollutant models including PM_2.5-woodburning, there was an 11% [95% CI: -11-38%], 6% [95% CI: -16-34%], 13% [95% CI: -7-36%] and 17% [95% CI: 4-41%] higher risk in the 3rd tertile of PM₁₀, PM_2.5, PM₁₀-traffic and PM_2.5-exhaust, respectively, compared to the 1st. Although the results lacked in precision they are generally in line with the current evidence detailing particulate matter air pollution from traffic as an environmental risk factor for DM.

Environmental noise and health in low-middle-income-countries: A systematic review of epidemiological evidence

Evidence of the health impacts from environmental noise has largely been drawn from studies in high-income countries, which has then been used to inform development of noise guidelines. It is unclear whether findings in high-income countries can be readily translated into policy contexts in low-middle-income-countries (LMICs). We conducted this systematic review to summarise noise epidemiological studies in LMICs. We conducted a literature search of studies in Medline and Web of Science published during 2009-2021, supplemented with specialist journal hand searches. Screening, data extraction, assessment of risk of bias as well as overall quality and strength of evidence were conducted following established guidelines (e.g. Navigation Guide). 58 studies were identified, 53% of which were from India, China and Bulgaria. Most (92%) were cross-sectional studies. 53% of studies assessed noise exposure based on fixed-site measurements using sound level meters and 17% from propagation-based noise models. Mean noise exposure among all studies ranged from 48 to 120 dB (L_eq), with over half of the studies (52%) reporting the mean between 60 and 80 dB. The most studied health outcome was noise annoyance (43% of studies), followed by cardiovascular (17%) and mental health outcomes (17%). Studies generally reported a positive (i.e. adverse) relationship between noise exposure and annoyance. Some limited evidence based on only two studies showing that long-term noise exposure may be associated with higher prevalence of cardiovascular outcomes in adults. Findings on mental health outcomes were inconsistent across the studies. Overall, 4 studies (6%) had "probably low", 18 (31%) had "probably high" and 36 (62%) had "high" risk of bias. Quality of evidence was rated as 'low' for mental health outcomes and 'very low' for all other outcomes. Strength of evidence for each outcome was assessed as 'inadequate', highlighting high-quality epidemiological studies are urgently needed in LMICs to strengthen the evidence base.

Traffic noise and adiposity: a systematic review and meta-analysis of epidemiological studies

Traffic noise has attracted much attention as a significant and intractable public health threat. This study was designed as a systematical review to explore the association of traffic noise with different indicators of obesity, thus providing updated quantitative estimates for the pooled effect estimates of the existing literature. We conducted an extensive search for epidemiological studies that investigated the association of traffic noise with obesity in three electronic databases till February 23, 2021. We used random-effects meta-analysis to calculate the summary effect estimates for each 10-dB(A) increase in noise and compared the highest with the lowest category of noise in relation to seven obesity indicators. Meanwhile, we assessed the risk of bias and the overall quality of the evidence of each study as well as the level of evidence for each exposure-outcome pair. The initial search identified 30 studies, 13 of which were ultimately included. The meta-analysis for the highest versus the lowest category of noise exposure was generally associated with higher waist circumfluence (WC) ranging from 0.326 cm (95% confidence interval (CI) = 0.078, 0.574) to 0.705 cm (95% CI = 0.071, 1.340) and higher odds of central obesity ranging from 1.055 (95% CI = 1.000, 1.109) to 1.167 (95% CI = 1.037, 1.298). When the continuous exposure (each 10 dB(A) increase in noise) was introduced, similar results were found. This study indicated positive associations of traffic noise with WC and central obesity. However, in consideration of some limitations, there is an urgent need for future studies to increase the sample size, discriminate the etiological differences in different noise and obesity indicators, and thoroughly consider socioeconomic status.

Occupational Noise Exposure and Diabetes Risk

Introduction

Noise is one of the most common worldwide environmental pollutants, especially in occupational fields. As a stressor, it affects not only the ear but also the entire body. Its physiological and psychological impacts have been well established in many conditions such as cardiovascular diseases. However, there is a dearth of evidence regarding diabetes risk related to noises.

Aim

To evaluate the relationship between occupational exposure to noise and the risk of developing diabetes.

Methods

This is a cross-sectional analytical study enrolling two groups of 151 workers each. The first group (noise exposed group: EG) included the employees of a Tunisian power plant, who worked during the day shift and had a permanent position. The second group (unexposed to noise group: NEG) included workers assigned to two academic institutions, who were randomly selected in the Occupational Medicine Department of the Farhat Hached University Hospital in Sousse, during periodical fitness to work visits. Both populations (exposed and unexposed) were matched by age and gender. Data collection was based on a preestablished questionnaire, a physical examination, a biological assessment, and a sonometric study.

Results

The mean equivalent continuous sound level was 89 dB for the EG and 44.6 dB for the NEG. Diabetes was diagnosed in 24 workers from EG (15.9%) and 14 workers from NEG (9.3%), with no statistically significant difference (p=0.08). After multiple binary logistic regression, including variables of interest, noise did not appear to be associated with diabetes.

Conclusion

Our results did not reveal a higher risk of developing diabetes in workers exposed to noise. Further studies assessing both level and duration of noise exposure are needed before any definitive conclusion.

Quiet, clean, green, and active: A Navigation Guide systematic review of the impacts of spatially correlated urban exposures on a range of physical health outcomes

BACKGROUND

Recent epidemiologic analyses have considered impacts of multiple spatially correlated urban exposures, but this literature has not been systematically evaluated.

OBJECTIVES

To characterize the long-term impacts of four distinct spatially correlated urban environmental exposures - traffic-related air pollution (TRAP), noise, natural spaces, and neighborhood walkability - by evaluating studies including measures of at least two such exposures in relationship to mortality, cardiovascular disease, chronic respiratory disease, allergy, type 2 diabetes, or reproductive outcomes.

METHODS

Following the Navigation Guide framework, the literature was searched for studies published since 2003 and meeting predefined inclusion criteria. Identified studies were scored individually for risk of bias and all studies related to an exposure-group set were appraised for overall quality and strength of evidence.

RESULTS

A total of 51 individual studies (TRAP and noise: n = 29; TRAP and natural spaces: n = 10; noise and natural spaces: n = 2; TRAP, noise, and natural spaces: n = 7; TRAP, noise, natural spaces, and walkability: n = 3) were included. When TRAP and noise were considered jointly, evidence was sufficient for increased cardiovascular morbidity with higher noise exposures; sufficient for no effect of TRAP on CVD morbidity; sufficient for increased mortality with higher TRAP exposures, but limited for noise; and limited for increased adverse reproductive outcomes with higher TRAP exposures and no effect of noise. Looking at natural spaces and TRAP, there was limited evidence for lower risk of chronic respiratory disease and small increases in birthweight with greater natural space; this relationship with birthweight persisted after adjustment for noise as well. Evidence was inadequate for all other exposure groups and outcomes.

DISCUSSION

Studies that properly account for the complexity of relationships between urban form and physical health are limited but suggest that even highly correlated exposures may have distinct effects.

REVIEW REGISTRATION

PROSPERO 2018 CRD42018106050.

The Effects of Social, Personal, and Behavioral Risk Factors and PM2.5 on Cardio-Metabolic Disparities in a Cohort of Community Health Center Patients

(1) Background: Cardio-metabolic diseases (CMD), including cardiovascular disease, stroke, and diabetes, have numerous common individual and environmental risk factors. Yet, few studies to date have considered how these multiple risk factors together affect CMD disparities between Blacks and Whites. (2) Methods: We linked daily fine particulate matter (PM2.5) measures with survey responses of participants in the Southern Community Cohort Study (SCCS). Generalized linear mixed modeling (GLMM) was used to estimate the relationship between CMD risk and social-demographic characteristics, behavioral and personal risk factors, and exposure levels of PM2.5. (3) Results: The study resulted in four key findings: (1) PM2.5 concentration level was significantly associated with reported CMD, with risk rising by 2.6% for each µg/m3 increase in PM2.5; (2) race did not predict CMD risk when clinical, lifestyle, and environmental risk factors were accounted for; (3) a significant variation of CMD risk was found among participants across states; and (4) multiple personal, clinical, and social-demographic and environmental risk factors played a role in predicting CMD occurrence. (4) Conclusions: Disparities in CMD risk among low social status populations reflect the complex interactions of exposures and cumulative risks for CMD contributed by different personal and environmental factors from natural, built, and social environments.

All-source and source-specific air pollution and 10-year diabetes Incidence: Total effect and mediation analyses in the Heinz Nixdorf recall study

BACKGROUND

An increasing number of studies have been published recently on the association between ambient air pollution (AP) and incident diabetes mellitus (DM), but studies investigating source-specific AP toxicity and potential mediating pathways are rare. We investigated the associations of all-source, traffic-specific, and industry-specific outdoor AP exposure with 10-year incidence of DM and potential mediation via inflammation-associated biomarkers.

METHODS

Data from participants of the prospective Heinz Nixdorf Recall cohort study who attended the baseline (t₀; 2000-2003), 5-year follow-up (t₁; 2006-2008), and 10-year follow-up (t₂; 2011-2015) examinations was used. For participants without DM at baseline (determined using information on physician diagnosis and glucose-lowering medication), residential long-term exposure (total, traffic-specific, and industry-specific) to particulate matter (PM_2.5, PM₁₀), nitrogen dioxide (NO₂), and accumulation mode particle number concentration (PN_AM) were estimated using a chemistry transport model. Covariate-adjusted modified Poisson regression models with robust standard errors were applied to estimate relative risks (RR) for the associations between baseline AP and incident DM at t₂. Mediation analyses for adiponectin, high-sensitivity C-reactive protein (hsCRP), and interleukin-1 receptor antagonist (IL-1RA) were conducted to estimate natural direct and indirect effects.

RESULTS

Of the 4,814 participants at t₀, 2,451 participants (mean baseline age: 58.2 years) were included in the main analysis. Interquartile range (IQR) increases in total PM₁₀ and PN_AM were associated with increased risk of DM (e.g., RR: 1.25 [95% Confidence Interval (CI): 1.02, 1.53] per 3.8 µg/m³ PM₁₀). Whereas traffic-specific exposures were associated with DM risk for all air pollutants (e.g., RR: 1.24 [95% CI: 1.06, 1.46] per 0.3 µg/m³ PM₁₀), significant associations for industry exposures were limited to NO₂ and PN_AM (e.g., RR: 1.24 [95% CI: 1.03, 1.49] per 230 particles/mL PN_AM). Potential mediation of the association between AP and DM was observed for adiponectin but not for hsCRP and IL-1RA.

CONCLUSION

Our study shows that long-term exposure to total and source-specific ambient AP may increase DM risk, with consistent results observed across traffic-specific exposures. Decreases in adiponectin may play a potential role along the causal pathway.

Socio-Demographic Determinants of Mortality from Chronic Noncommunicable Diseases in Women of Reproductive Age in the Republic of Georgia: Evidence from the National Reproductive Age Mortality Study (2014)

Purpose

Worldwide, noncommunicable diseases (NCDs) are the leading cause of premature death of women, taking the highest toll in developing countries. This study aimed to identify key socio-demographic determinants of NCD mortality in reproductive-aged women (15-49 years) in Georgia.

Materials and Methods

The study employed the verbal autopsy data from the second National Reproductive Age Mortality Survey 2014. Univariate and multivariate logistic regression models were fitted to explore the association between each risk factor and NCD mortality, measured by crude and adjusted odds ratio (AOR) with respective 95% confidence intervals (95% CI).

Results

In the final sample of 843 women, 586 (69.5%) deaths were attributed to NCDs, the majority of which occurred outside a hospital (72.7%) and among women aged 45-49 years (46.8%), ethnic Georgians (85.2%), urban residents (60.1%), those being married (60.6%), unemployed (75.1%) or having secondary and higher education (69.5%), but with nearly equal distribution across the wealth quintiles. After multivariate adjustment, the odds of dying from NCDs were significantly higher in women aged 45-49 years (AOR=17.69, 95% CI= 9.35 to 33.50), those being least educated (AOR=1.55, 95% CI= 1.01 to 2.37) and unemployed (AOR=1.47, 95% CI= 1.01 to 2.14) compared, respectively, to their youngest (15-24 years), more educated and employed counterparts. Strikingly, the adjusted odds were significantly lower in "other" ethnic minorities (AOR=0.29, 95% CI= 0.14 to 0.61) relative to ethnic Georgians. Contrariwise, there were no significant associations between NCD mortality and women's marital or wealth status, place of residence (rural/urban) or place of death.

Conclusion

Age, ethnicity, education, and employment were found to be strong independent predictors of young women's NCD mortality in Georgia. Further research on root causes of inequalities in mortality across the socioeconomic spectrum is warranted to inform equity- and life course-based multisectoral, integrated policy responses that would be conducive to enhancing women's survival during and beyond reproduction.

Lack of association between particulate air pollution and blood glucose levels and diabetic status in peri-urban India

BACKGROUND

Limited evidence exists on the effect of particulate air pollution on blood glucose levels. We evaluated the associations of residential and personal levels of fine particulate matter (PM_2.5) and black carbon (BC) with blood glucose and diabetic status among residents of 28 peri-urban villages in South India.

METHODS

We used cross-sectional data from 5065 adults (≥18 years, 54% men) included in the Andhra Pradesh Children and Parents Study. Fasting plasma glucose was measured once in 2010-2012 and prevalent prediabetes and diabetes were defined following the American Diabetes Association criteria. We estimated annual ambient PM_2.5 and BC levels at residence using land-use regression models and annual personal exposure to PM_2.5 and BC using prediction models based on direct measurements from a subsample of 402 participants. We used linear and logistic nested mixed-effect models to assess the association between exposure metrics and health outcomes. For personal exposures, we stratified analyses by sex.

RESULTS

Mean (SD) residential PM_2.5 and BC were 32.9 (2.6) μg/m³ and 2.5 (2.6) μg/m³, respectively; personal exposures to PM_2.5 and BC were 54.5 (11.5) μg/m³ and 5.8 (2.5) μg/m³, respectively. Average (SD) fasting blood glucose was 5.3 (1.3) mmol/l, 16% of participants had prediabetes, and 5.5% had diabetes. Residential PM_2.5 and BC were not associated with higher blood glucose levels. Personal PM_2.5 (20 μg/m³ increase) and BC (1 μg/m³ increase) were negatively associated with blood glucose levels in women (PM_2.5: -1.93, 95%CI: -3.12, -0.73; BC: -0.63, 95%CI: -0.90, -0.37). In men, associations were negative for personal PM_2.5 (-1.99, 95%CI: -3.56, -0.39) and positive for personal BC (0.49, 95%CI: -0.44, 1.43). We observed no evidence of associations between any exposure and prevalence of prediabetes/diabetes.

CONCLUSIONS

Our results do not provide evidence that residential exposures to PM_2.5 or BC are associated with blood glucose or prevalence of prediabetes/diabetes in this population. Associations with personal exposure may have been affected by unmeasured confounding, highlighting a challenge in using personal exposure estimates in air pollution epidemiology. These associations should be further examined in longitudinal studies.

Sleep and Environmental Factors Affecting Glycemic Control in People with Type 2 Diabetes Mellitus

PURPOSE OF REVIEW

Sleep and environmental factors both impact glycemic control in persons with type 2 diabetes mellitus (T2DM). This narrative article aims to review research within the past 5 years, focusing on chronotype, light, noise, and neighborhood disparities in relation to sleep in people with T2DM.

RECENT FINDINGS

Sleep quality and duration have been shown to impact glycemic control in patients with T2DM. Later chronotype can lead to poorer glycemic control due to disruption of circadian rhythms. Light exposure also has similar effects, likely due to its inherent influence on sleep quality. Environmental determinants, were associated with lower T2DM incidence, and noise and air pollution were associated with increased risks for T2DM. Findings were mixed; while most studies found that later chronotype, light/noise exposure, and neighborhood disadvantages were associated with poorer glycemic control in patients with T2DM, other environmental factors, such as green space, were not significantly associated with diabetes outcomes.

Exploration of Risk Factors for Type 2 Diabetes among Arabs in Israel

Background:

Type 2 Diabetes Mellitus (T2DM) is becoming increasingly prevalent and is considered to be a major public health threat worldwide. Behavioral and sociodemographic factors associated with T2DM vary within different societies.

Objective:

The aim of this study is to determine the various behavioral and sociodemographic factors associated with T2DM in the Arab society in Israel.

Methods:

A cross-sectional study was conducted based on data from 1,894 residents over the age of 21 belonging to the Arab population in Israel. The data collected from the subjects were subjected to statistical analyses using the SPSS program.

Findings:

Of the total sample population, 13.7% were found to be affected with T2DM. The prevalence of T2DM increased sharply in the successive age groups of both men and women. The prevalence of T2DM was found to increase progressively particularly in women with an increase in BMI (~20%, 37% and 44% respectively), while, in men it increased sharply (from 25% to ~50%) until a BMI of 29.9; it then decreased drastically (to ~24%) for a BMI of ≥30. About 85% of the men affected with T2DM were physically inactive, while 97% of the affected women were physically inactive. Almost half of the participants with diabetes have a family history of the disease in both genders. In the multivariate analysis, it was found that age, obesity, physical inactivity and family history of the disease were the significant factors associated with the prevalence of diabetes.

Conclusions:

It could be concluded that age, obesity, family history and physical inactivity were the significant factors associated with the prevalence of T2DM within the Arab society in Israel.

Traffic noise exposure in relation to adverse birth outcomes and body mass between birth and adolescence

BACKGROUND

There is growing evidence that traffic noise exposure is associated with adiposity among adults but data in children are limited.

OBJECTIVE

This longitudinal study examined whether pre- and postnatal noise exposure is associated with body mass index (BMI) between birth and adolescence or with adverse birth outcomes.

METHODS

The study was conducted using data from the BAMSE birth cohort, which included 4089 children born in Stockholm County, Sweden. Data on BMI from birth to adolescence were collected via questionnaires, clinical examinations and health care records. A national register provided information on birth outcomes. Road traffic noise levels at the most exposed façade were estimated for all residences of the children during follow-up, as well as of their mothers during pregnancy, and time-weighted average exposure was calculated for different time windows. Maternal occupational noise exposure was obtained from a job-exposure-matrix. Logistic- and quantile regression models were used to estimate associations between noise exposure and health outcomes.

RESULTS

We found residential road traffic noise exposure to be associated with increases in BMI from school age to adolescence, but not at earlier ages. In the age groups 8-11 years and 12-16 years the BMI increments were 0.11 kg/m² per 10 dB L_den (95% CI 0.08-0.13) and 0.20 kg/m² per 10 dB L_den (95% CI 0.17-0.22), respectively. Maternal noise exposure during pregnancy was generally unrelated to adverse birth outcomes and BMI from birth to adolescence in the children, however, traffic noise exposure was associated with a decreased risk of preterm birth CONCLUSION: Residential road traffic noise exposure was associated with BMI increases from school age to adolescence, but not at earlier ages. Maternal occupational noise exposure or exposure from road traffic during pregnancy were not consistently related to birth outcomes or BMI from birth to adolescence.

Traffic noise, noise annoyance and psychotropic medication use

BACKGROUND

Road-traffic noise can induce stress, which may contribute to mental health disorders. Mental health problems have not received much attention in noise research. People perceive noise differently, which may affect the extent to which noise contributes to poor mental health at the individual level. This paper aims to assess the relationships between outdoor traffic noise and noise annoyance and the use of psychotropic medication.

METHODS

We conducted a survey to assess noise annoyance and psychotropic medication among residents of the Helsinki Capital Region of Finland. We also assessed the associations of annoyance and road-traffic noise with sleep disorders, anxiety and depression. Respondents were randomly sampled from the Finnish Population registry, and data was collected using a self-administered questionnaire. Outdoor traffic noise was modelled using the Nordic prediction model. Associations between annoyance and modelled façade-noise levels with mental health outcome indicators were assessed using a binary logistic regression while controlling for socioeconomic, lifestyle and exposure-related factors.

RESULTS

A total of 7321 respondents returned completed questionnaires. Among the study respondents, 15%, 7% and 7% used sleep medication, anxiolytic and antidepressant medications, respectively, in the year preceding the study. Noise annoyance was associated with anxiolytic drug use, OR = 1.41 (95% CI: 1.02-1.95), but not with sedative or antidepressant use. There was suggestive association between modelled noise at levels higher than 60 dB and anxiolytic or antidepressant use. In respondents whose bedroom windows faced the street, modelled noise was definitively associated with antidepressant use. Noise sensitivity did not modify the effect of noise but was associated with an increased use of psychotropic medication.

CONCLUSION

We observed suggestive associations between high levels of road-traffic noise and psychotropic medication use. Noise sensitivity was associated with psychotropic medication use.

Association between noise exposure and diabetes: A systematic review and meta-analysis

BACKGROUND

The prevalence of diabetes is on rise worldwide and environmental factors are being increasingly recognized to be involved in this rise. An emerging body of evidence has evaluated the impact of long-term exposure to noise on diabetes mellitus, highlighting the need to synthesize this evidence.

OBJECTIVES

To systematically review and conduct meta-analysis of the available evidence on the association between long-term exposure to transport and occupational noise exposure and diabetes mellitus.

METHODS

Selected databases were searched for available evidence published till September 13th, 2017 following MOOSE guidelines. The quality of articles was assessed using the Newcastle-Ottawa Scale. Random effects meta-analysis was applied to abstract combined estimates for diabetes mellitus per 5 dB increase in noise exposure. We evaluated the heterogeneity applying Cochran's Q test and quantified it using I² statistic. Meta-regressions were conducted to identify sources of heterogeneity. Publication bias was evaluated using funnel plot and Egger's test.

RESULTS

Fifteen studies met our inclusion criteria of which nine including five prospective cohorts, two cross-sectional and two case-control studies with a total number of 444460 adult participants and 17430 diabetes mellitus cases included in meta-analyses. We observed a 6% (95% confidence interval (CI): 3%, 9%) increase in the risk of diabetes mellitus per 5 dB increase in noise exposure regardless of its source. Source-specific analyses were suggestive for stronger associations for air traffic noise (combined odds ratio: 1.17; 95% CI: 1.06, 1.29 per 5 dB increase in exposure) flowed by road traffic noise (combined odds ratio: 1.07; 95% CI: 1.02, 1.12). We observed some indications of publication bias; however the findings were robust after trim and fill test. Meta-regression analyses showed that the adjustment in general, and not specifically related to air pollution, could predict the between-study heterogeneity in reported associations.

CONCLUSIONS

The results indicate an increased risk of diabetes mellitus associated with noise exposure, mainly related to air and road traffic.

Acute effects of air pollution on type II diabetes mellitus hospitalization in Shijiazhuang, China

Air pollution has been considered as an important contributor to diabetes development. However, the evidence is fewer in developing countries where air pollution concentrations were much higher. In this study, we conduct a time-series study to investigate the acute adverse effect of six air pollutants on type II diabetes mellitus (T2DM) hospitalization in Shijiazhuang, China. An over-dispersed passion generalized addictive model adjusted for weather conditions, day of the week, and long-term and seasonal trends was used. Finally, a 10-μg/m³ increase of fine particulate matter (PM_2.5), inhalable particulate matter (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and carbon monoxide (CO) corresponded to 0.53% (95% confidence interval = 0.22-0.83), 0.32% (95% CI = 0.10-0.55), 0.55% (95% CI = 0.04-1.07), 1.27% (95% CI = 0.33-2.22), and 0.04% (95% CI = 0.02-0.06) increment of T2DM hospitalization, respectively. The effects of PM_2.5, PM₁₀, and CO were robust when adjusted for co-pollutants. The associations appeared to be a little stronger in the cool season than in the warm season. And stronger associations were found in male and elderly (≥ 65 years) than in female and younger people (35-65 years). Our results contribute to the limited data in the scientific literature on acute effects of air pollution on type II diabetes mellitus in developing countries.

MAIN FINDINGS

This is the first adverse effect evidence of air pollution on T2DM in Shijiazhuang, a severely polluted city in China. Males were more vulnerable than females in severe pollution.

Road traffic air and noise pollution exposure assessment - A review of tools and techniques

Road traffic induces air and noise pollution in urban environments having negative impacts on human health. Thus, estimating exposure to road traffic air and noise pollution (hereafter, air and noise pollution) is important in order to improve the understanding of human health outcomes in epidemiological studies. The aims of this review are (i) to summarize current practices of modelling and exposure assessment techniques for road traffic air and noise pollution (ii) to highlight the potential of existing tools and techniques for their combined exposure assessment for air and noise together with associated challenges, research gaps and priorities. The study reviews literature about air and noise pollution from urban road traffic, including other relevant characteristics such as the employed dispersion models, Geographic Information System (GIS)-based tool, spatial scale of exposure assessment, study location, sample size, type of traffic data and building geometry information. Deterministic modelling is the most frequently used assessment technique for both air and noise pollution of short-term and long-term exposure. We observed a larger variety among air pollution models as compared to the applied noise models. Correlations between air and noise pollution vary significantly (0.05-0.74) and are affected by several parameters such as traffic attributes, building attributes and meteorology etc. Buildings act as screens for the dispersion of pollution, but the reduction effect is much larger for noise than for air pollution. While, meteorology has a greater influence on air pollution levels as compared to noise, although also important for noise pollution. There is a significant potential for developing a standard tool to assess combined exposure of traffic related air and noise pollution to facilitate health related studies. GIS, due to its geographic nature, is well established and has a significant capability to simultaneously address both exposures.

Ambient and Traffic-Related Air Pollution Exposures as Novel Risk Factors for Metabolic Dysfunction and Type 2 Diabetes

PURPOSE OF REVIEW

Diabetes mellitus is a top contributor to the global burden of mortality and disability in adults. There has also been a slow, but steady rise in prediabetes and type 2 diabetes in youth. The current review summarizes recent findings regarding the impact of increased exposure to air pollutants on the type 2 diabetes epidemic.

RECENT FINDINGS

Human and animal studies provide strong evidence that exposure to ambient and traffic-related air pollutants such as particulate matter (PM), nitrogen dioxide (NO2), and nitrogen oxides (NOx) play an important role in metabolic dysfunction and type 2 diabetes etiology. This work is supported by recent findings that have observed similar effect sizes for increased exposure to air pollutants on clinical measures of risk for type 2 diabetes in children and adults. Further, studies indicate that these effects may be more pronounced among individuals with existing risk factors, including obesity and prediabetes.

SUMMARY

Current epidemiological evidence suggests that increased air pollution exposure contributes to alterations in insulin signaling, glucose metabolism, and beta (β)-cell function. Future work is needed to identify the specific detrimental pollutants that alter glucose metabolism. Additionally, advanced tools and new areas of investigation present unique opportunities to study the underlying mechanisms, including intermediate pathways, that link increased air pollution exposure with type 2 diabetes onset.

The Study on the Correlation Between Six Kinds of Mineral Elements and Diabetes

The study aimed to explore the relationship of six kinds of mineral elements and diabetes among adults in northeast China. A cross-sectional survey was conducted in Jilin Province, northeast China. A total of 366 males and 204 females aged 18 ~ 77 years from Jingyu town, Dongliao town, and Changling town were included using a multistage stratified random cluster sampling design. Data was obtained from face to face interview, physical examination, and laboratory measurement. We defined the normal people (3.9 ~ 6.0 mmol/L), impaired fasting glucose (IFG) individuals (6.1 ~ 6.9 mmol/L), and diabetes mellitus (DM) (> 7.0 mmol/L) according to the WHO diagnostic criteria. Kruskal-Wallis test, Spearman rank correlation, as well as binary logistic regression were used to analyze influencing factors. lg(Cu/Zn)was correlated with DM (OR 8.390; 95% CI of OR 1.272-55.347). The specific mineral elements such as Zn, Ca, as well as Cu/Zn ratio may be the potential risk factors for diabetes. So, the supplement or reduction of these elements is supposed to be told to IFG to prevent or delay the occurrence of diabetes or DM to avoid its complication.

Long-term exposure to transportation noise and air pollution in relation to incident diabetes in the SAPALDIA study

Background

Epidemiological studies have inconsistently linked transportation noise and air pollution (AP) with diabetes risk. Most studies have considered single noise sources and/or AP, but none has investigated their mutually independent contributions to diabetes risk.

Methods

We investigated 2631 participants of the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA), without diabetes in 2002 and without change of residence between 2002 and 2011. Using questionnaire and biomarker data, incident diabetes cases were identified in 2011. Noise and AP exposures in 2001 were assigned to participants’ residences (annual average road, railway or aircraft noise level during day-evening-night (Lden), total night number of noise events, intermittency ratio (temporal variation as proportion of event-based noise level over total noise level) and nitrogen dioxide (NO₂) levels. We applied mixed Poisson regression to estimate the relative risk (RR) of diabetes and their 95% confidence intervals (CI) in mutually-adjusted models.

Results

Diabetes incidence was 4.2%. Median [interquartile range (IQR)] road, railway, aircraft noise and NO₂ were 54 (10) dB, 32 (11) dB, 30 (12) dB and 21 (15) μg/m³, respectively. Lden road and aircraft were associated with incident diabetes (respective RR: 1.35; 95% CI: 1.02–1.78 and 1.86; 95% CI: 0.96–3.59 per IQR) independently of Lden railway and NO₂ (which were not associated with diabetes risk) in mutually adjusted models. We observed stronger effects of Lden road among participants reporting poor sleep quality or sleeping with open windows.

Conclusions

Transportation noise may be more relevant than AP in the development of diabetes, potentially acting through noise-induced sleep disturbances.

The role of pollutants in type 2 diabetes mellitus (T2DM) and their prospective impact on phytomedicinal treatment strategies

Type 2 diabetes mellitus (T2DM) is the most common form of diabetes and it is characterized by high blood sugar and abnormal sera lipid levels. Although the specific reasons for the development of these abnormalities are still not well understood, traditionally, genetic and lifestyle behavior have been reported as the leading causes of this disease. In the last three decades, the number of diabetic patients has drastically increased worldwide, with current statistics suggesting the number is to double in the next two decades. To combat this incurable ailment, orthodox medicines, to which economically disadvantaged patients have minimal access to, have been used. Thus, a considerable amalgamation of medicinal plants has recently been proven to possess therapeutic capabilities to manage T2DM, and this has prompted studies primarily focusing on the healing aspect of these plants, and ultimately, their commercialization. Hence, this review aims to highlight the potential threat of pollutants, i.e., polyfluoroalkyl compounds (PFCs), endocrine disrupting chemicals (EDCs) and heavy metals, to medicinal plants, and their prospective impact on the phytomedicinal therapy strategies for T2DM. It is further suggested that auxiliary research be undertaken to better comprehend the factors that influence the uptake of these compounds by these plants. This should include a comprehensive risk assessment of phytomedicinal products destined for the treatment of T2DM. Regulations that control the use of PFC-precursors in certain developing countries are also long overdue.

Built environmental characteristics and diabetes: a systematic review and meta-analysis

BACKGROUND

The built environment influences behaviour, like physical activity, diet and sleep, which affects the risk of type 2 diabetes mellitus (T2DM). This study systematically reviewed and meta-analysed evidence on the association between built environmental characteristics related to lifestyle behaviour and T2DM risk/prevalence, worldwide.

METHODS

We systematically searched PubMed, EMBASE.com and Web of Science from their inception to 6 June 2017. Studies were included with adult populations (>18 years), T2DM or glycaemic markers as outcomes, and physical activity and/or food environment and/or residential noise as independent variables. We excluded studies of specific subsamples of the population, that focused on built environmental characteristics that directly affect the cardiovascular system, that performed prediction analyses and that do not report original research. Data appraisal and extraction were based on published reports (PROSPERO-ID: CRD42016035663).

RESULTS

From 11,279 studies, 109 were eligible and 40 were meta-analysed. Living in an urban residence was associated with higher T2DM risk/prevalence (n = 19, odds ratio (OR) = 1.40; 95% CI, 1.2-1.6; I² = 83%) compared to living in a rural residence. Higher neighbourhood walkability was associated with lower T2DM risk/prevalence (n = 8, OR = 0.79; 95% CI, 0.7-0.9; I² = 92%) and more green space tended to be associated with lower T2DM risk/prevalence (n = 6, OR = 0.90; 95% CI, 0.8-1.0; I² = 95%). No convincing evidence was found of an association between food environment with T2DM risk/prevalence.

CONCLUSIONS

An important strength of the study was the comprehensive overview of the literature, but our study was limited by the conclusion of mainly cross-sectional studies. In addition to other positive consequences of walkability and access to green space, these environmental characteristics may also contribute to T2DM prevention. These results may be relevant for infrastructure planning.

Environmental Risk Factors for Developing Type 2 Diabetes Mellitus: A Systematic Review

Different elements of the environment have been posited to influence type 2 diabetes mellitus (T2DM). This systematic review summarizes evidence on the environmental determinants of T2DM identified in four databases. It proposes a theoretical framework illustrating the link between environment and T2DM, and briefly discusses some methodological challenges and potential solutions, and opportunities for future research. Walkability, air pollution, food and physical activity environment and roadways proximity were the most common environmental characteristics studied. Of the more than 200 reported and extracted relationships assessed in 60 studies, 82 showed significant association in the expected direction. In general, higher levels of walkability and green space were associated with lower T2DM risk, while increased levels of noise and air pollution were associated with greater risk. Current evidence is limited in terms of volume and study quality prohibiting causal inferences. However, the evidence suggests that environmental characteristics may influence T2DM prevention, and also provides a reasonable basis for further investigation with better quality data and longitudinal studies with policy-relevant environmental measures. This pursuit of better evidence is critical to support health-orientated urban design and city planning.

Urban residential greenspace and mental health in youth: Different approaches to testing multiple pathways yield different conclusions

BACKGROUND

Urban greenspace can benefit mental health through multiple mechanisms. They may work together, but previous studies have treated them as independent.

OBJECTIVES

We aimed to compare single and parallel mediation models, which estimate the independent contributions of different paths, to several models that posit serial mediation components in the pathway from greenspace to mental health.

METHODS

We collected cross-sectional survey data from 399 participants (15-25 years of age) in the city of Plovdiv, Bulgaria. Objective "exposure" to urban residential greenspace was defined by the Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index, tree cover density within the 500-m buffer, and Euclidean distance to the nearest urban greenspace. Self-reported measures of availability, access, quality, and usage of greenspace were also used. Mental health was measured with the General Health Questionnaire. The following potential mediators were considered in single and parallel mediation models: restorative quality of the neighborhood, neighborhood social cohesion, commuting and leisure time physical activity, road traffic noise annoyance, and perceived air pollution. Four models were tested with the following serial mediation components: (1) restorative quality → social cohesion; (2) restorative quality → physical activity; (3) perceived traffic pollution → restorative quality; (4) and noise annoyance → physical activity.

RESULTS

There was no direct association between objectively-measured greenspace and mental health. For the 500-m buffer, the tests of the single mediator models suggested that restorative quality mediated the relationship between NDVI and mental health. Tests of parallel mediation models did not find any significant indirect effects. In line with theory, tests of the serial mediation models showed that higher restorative quality was associated with more physical activity and more social cohesion, and in turn with better mental health. As for self-reported greenspace measures, single mediation through restorative quality was significant only for time in greenspace, and there was no mediation though restorative quality in the parallel mediation models; however, serial mediation through restorative quality and social cohesion/physical activity was indicated for all self-reported measures except for greenspace quality.

CONCLUSIONS

Statistical models should adequately address the theoretically indicated interdependencies between mechanisms underlying association between greenspace and mental health. If such causal relationships hold, testing mediators alone or in parallel may lead to incorrect inferences about the relative contribution of specific paths, and thus to inappropriate intervention strategies.

Residential road traffic noise and general mental health in youth: The role of noise annoyance, neighborhood restorative quality, physical activity, and social cohesion as potential mediators

Given the ubiquitous nature of both noise pollution and mental disorders, their alleged association has not escaped the spotlight of public health research. The effect of traffic noise on mental health is probably mediated by other factors, which have not been elucidated sufficiently. Herein, we aimed to disentangle the pathways linking road traffic noise to general mental health in Bulgarian youth, with a focus on several candidate mediators - noise annoyance, perceived restorative quality of the living environment, physical activity, and neighborhood social cohesion. A cross-sectional sample was collected in October - December 2016 in the city of Plovdiv, Bulgaria. It consisted of 399 students aged 15-25years, recruited from two high schools and three universities. Road traffic noise exposure (L_den) was derived from the strategic noise map of Plovdiv. Mental health was measured with the 12-item form of the General Health Questionnaire (GHQ-12). Noise annoyance, perceived restorative quality of the living environment, commuting and leisure time physical activity, and neighborhood social cohesion were assessed using validated questionnaires. Analyses were based on linear regression mediation models and a structural equation modeling (SEM) to account for the hypothesized interdependencies between candidate mediators. Results showed that higher noise exposure was associated with worse mental health only indirectly. More specifically, tests of the single and parallel mediation models indicated independent indirect paths through noise annoyance, social cohesion, and physical activity. In addition, the SEM revealed that more noise annoyance was associated with less social cohesion, and in turn with worse mental health; noise annoyance was also associated with lower neighborhood restorative quality, thereby with less social cohesion and physical activity, and in turn with worse mental health. However, causality could not be established. Further research is warranted to expand our still limited understanding of these person-environment interactions.

Association between community noise and adiposity in patients with cardiovascular disease

INTRODUCTION

This study aimed to explore the effect of community noise on body mass index (BMI) and waist circumference (WC) in patients with cardiovascular disease (CVD).

MATERIALS AND METHODS

A representative sample of 132 patients from three tertiary hospitals in the city of Plovdiv, Bulgaria was collected. Anthropometric measurements were linked to global noise annoyance (GNA) based on different residential noise annoyances, day-evening-night (Lden), and nighttime (Lnight) road traffic noise exposure. Noise map Lden and Lnight were determined at the living room and bedroom façades, respectively, and further corrected to indoor exposure based on the window-opening frequency and soundproofing insulation.

RESULTS AND DISCUSSION

Results showed that BMI and WC increased (non-significantly) per 5 dB. The effect of indoor noise was stronger in comparison with that of outdoor noise. For indoor Lden, the effect was more pronounced in men, those with diabetes, family history of diabetes, high noise sensitivity, using solid fuel/gas for domestic heating/cooking, and living on the first floor. As regards indoor Lnight, its effect was more pronounced in those with low socioeconomic status, hearing loss, and using solid fuel/gas for domestic heating/cooking. GNA was associated with lower BMI and WC.

CONCLUSION

Road traffic noise was associated with an increase in adiposity in some potentially vulnerable patients with CVD.

Therapeutic Effect of Sodium Glucose Co-Transporter 2 Inhibitor Dapagliflozin on Renal Cell Carcinoma

Background

Patients with type 2 diabetes mellitus (T2DM) have a high incidence of renal cell carcinoma (RCC) and high sodium glucose co-transporters 2 (SGLT2) expressions. The purpose of this study was to evaluate the anticancer activity of dapagliflozin as an SGLT2 inhibitor on RCC cell lines in vitro and in vivo.

Material/Methods

qRT-PCR and Western blot were used to detect SGLT2 expression on different human renal cells. Then, flow cytometry and immunofluorescence were used to investigate the effects of dapagliflozin on cell cycle, apoptosis, and SGLT2 expression of CaKi-1 cells. Finally, a xenograft model and immunohistochemical staining were used to investigate the function of dapagliflozin in nude mice.

Results

We proved that SGLT2 is highly expressed in RCC cell lines. We found that dapagliflozin exerts a higher cytotoxic effect on human RCC than on normal human renal cells, regulates the cell cycle and apoptosis, and reduces the glucose uptake and SGLT2 expression of CaKi-1 cells. Moreover, dapagliflozin inhibits tumor growth and reduces SGLT2 expression in vivo.

Conclusions

Our results indicate that dapagliflozin has high efficiency and low toxicity and could be a new therapeutic target for RCC.

Residential Proximity to Major Roadways and Risk of Type 2 Diabetes Mellitus: A Meta-Analysis

Research indicates that higher levels of traffic-related pollution exposure increase the risk of diabetes, but the association between road proximity and diabetes risk remains unclear. To assess and quantify the association between residential proximity to major roadways and type 2 diabetes, a systematic review and meta-analysis was performed. Embase, Medline, and Web of Science were searched for eligible studies. Using a random-effects meta-analysis, the summary relative risks (RRs) were calculated. Bayesian meta-analysis was also performed. Eight studies (6 cohort and 2 cross-sectional) with 158,576 participants were finally included. The summary unadjusted RR for type 2 diabetes associated with residential proximity to major roadways was 1.24 (95% confidence interval [CI]: 1.07–1.44, p = 0.001, I² = 48.1%). The summary adjusted RR of type 2 diabetes associated with residential proximity to major roadways was 1.12 (95% CI: 1.03–1.22, p = 0.01, I² = 17.9%). After excluding two cross-sectional studies, the summary results suggested that residential proximity to major roadways could increase type 2 diabetes risk (Adjusted RR = 1.13; 95% CI: 1.02–1.27, p = 0.025, I² = 36.6%). Bayesian meta-analysis showed that the unadjusted RR and adjusted RR of type 2 diabetes associated with residential proximity to major roadways were 1.22 (95% credibility interval: 1.06–1.55) and 1.13 (95% credibility interval: 1.01–1.31), respectively. The meta-analysis suggested that residential proximity to major roadways could significantly increase risk of type 2 diabetes, and it is an independent risk factor of type 2 diabetes. More well-designed studies are needed to further strengthen the evidence.