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Abstract
Introduction In Kuwait, a severe diabetes and obesity epidemic coexists with intense dust storms and harsh summer heat. While, theoretically, this interplay between dust, heat, and diabetes presents a serious public health problem, the empirical understanding of the actual risks remains limited. We hypothesized that increased exposure to heat and dust, independently and jointly, exacerbates the risk of hospitalization for diabetes patients.
Research design and methods We placed custom-designed particle samplers in Kuwait to collect daily dust samples for 2 years from 2017 to 2019. Samples were analyzed for elemental concentrations to identify and quantify dust pollution days. Temperature data were collected from meteorological stations. We then collected hospitalization data for unplanned diabetic admissions in all public hospitals in Kuwait. We used a case-crossover study design and conditional quasi-Poisson models to compare hospitalization days to control days within the same subject. Finally, we fitted generalized additive models to explore the smoothed interaction between temperature and dust days on diabetes hospitalization.
Results There were 11 155 unplanned diabetes hospitalizations over the study period. We found that each year, there was an excess of 282 diabetic admissions attributed to hot days (95% CI: −14 to 473). Additionally, for every 10 µg/m3 increase in dust levels, there were about 114 excess diabetic admissions annually (95% CI: 11 to 219). Compared with mild non-dusty days (33°C (0 µg/m3)), hot–dusty days jointly increased the relative risk of diabetic admissions from 1.11 at 42°C (85 µg/m3) to 1.36 at 42°C (150 µg/m3).
Conclusions Both heat and dust seem to contribute to the increased diabetes morbidity, with combined hot–dusty conditions exacerbating these risks even further.
- Environmental Health
- Public Health
- Epidemiology
- Population Health
Data availability statement
Data are available on reasonable request.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
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WHAT IS ALREADY KNOWN ON THIS TOPIC
There is a high prevalence of diabetes and obesity in Kuwait, accompanied by severe environmental conditions such as extreme heat and dust storms, which are theorized to exacerbate health complications in diabetics.
WHAT THIS STUDY ADDS
This study provides empirical evidence that both extreme heat and dust storms independently and jointly increase hospitalization rates for diabetic patients in Kuwait.
HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY
This study points to healthcare systems who should start to integrate environmental risk factors into clinical practices and policies, ensuring preparedness for the compounded health impacts of extreme climate conditions on vulnerable populations, such as diabetics.
Introduction
In the harsh desert environment of Kuwait, there is (1) an alarming diabetes and obesity epidemic, (2) dramatic dust storms and dust haze that frequently blanket the country year-round, and (3) extremely hot summers with record-breaking temperatures. The simultaneous interplay between two major environmental phenomena and a public health epidemic in Kuwait provides a unique window to study the effects of the environment on diabetes.
The Kuwait Diabetes Epidemiology Program reported a diabetes prevalence among adults at 19.1%, significantly higher than the global average of 9%, with a staggering 64.8% prevalence in individuals over 60 years.1 2 Additionally, 74% of the adult population are either overweight or obese.3 4 Diabetes medications alone accounted for 22.8% of the nation’s drug expenditures in 2018, roughly US$218 million.5
Within the same context, the country faces the harshest extreme weather events. Every year, more than 270 tons of dust are deposited in every kilometer square in Kuwait.6 In the southern part of the country, air pollution from fine particulate matter (PM2.5; particulate matter with aerodynamic diameter less than 2.5 microns) exceeded the daily WHO limits in almost 90% of the days.7 Meanwhile, summer temperatures frequently surpass 50°C, with a record high of 54°C in 2016.8 9 These unprecedented hot temperatures are expected to escalate with the progression of climate change.10
Diabetic patients are thought to be vulnerable to air pollution and extreme heat.11–15 The increased heat sensitivity in diabetics can be attributed to impaired sweat production, reduced blood flow to the skin, and diabetic peripheral neuropathy, which together impair heat dissipation and temperature regulation.16 Furthermore, fine dust particles can induce endothelial damage and oxidative stress, exacerbating vascular complications and systemic inflammation, thus worsening diabetic outcomes.17 18 While, theoretically, this interplay between dust, heat, and diabetes presents a serious public health crisis, the empirical understanding of the actual risks remains limited. We leveraged the presence of amplified exposures and the high proportion of diabetics to collect data on temperature, dust, and hospital admissions throughout Kuwait. The aim was to investigate the short-term impact of hot and dusty days on the acute hospitalization admission rates of individuals with diabetes. We hypothesized that increased exposure to heat and dust, independently and jointly, exacerbates the risk of hospitalization for diabetes patients.
Methods
Dust data
For the period from October 2017 to October 2019, we placed particle samplers at two locations in Kuwait to collect daily samples of PM2.5 (in µg/m3). These samplers were custom designed at the Harvard T.H. Chan School of Public Health (known as ‘Harvard Impactor’).19 They were made capable of collecting large quantities of particles during dust storms using a polyurethane foam impaction substrate to efficiently collect particles above specific size thresholds, proving to be very accurate and precise in the challenging desert environment (figure 1).7 20 21 Daily collected samples were then shipped to Boston, Massachusetts, for speciated analysis of elemental concentrations. Trace elements were detected using Energy Dispersive X-Ray Fluorescence. Quality assurance measures and protocols were developed by the Harvard T.H. Chan School of Public Health, ensuring reliable data collection and analysis as outlined in Alahmad et al.7
Dust collection process showing (A) a sampling location in Kuwait, (B) custom-designed Harvard Impactors, and (C) the acceleration jet and polyurethane foam that can enable accurate dust collection (the arrow shows a large amount of accumulated dust in the rectangular yellow surface).
Speciation data (elemental concentrations) for each day during the sampling period were fitted in positive matrix factorization models.22 These models discern ‘source factors’ based on statistical correlations and variations in the data, effectively separating and identifying distinct pollution sources by their unique compositional profiles. To single out the dust pollution (as opposed to traffic or fossil fuel burning pollution), we relied on the presence of high loadings from fingerprint crustal and geological elements (eg, Mg, Al, Si, Ca, Ti, and Fe).23 24 Correlation between measured fingerprint elements and the sourced overall dust concentration is shown in online supplemental figure S1. In this analysis, for each day, we calculate the average from the two locations to get the daily observed dust-sourced PM2.5 (in µg/m3).25 This is referred to as ‘dust’ onwards.
Supplemental material
Temperature data
Daily temperature (in °C) data were obtained from Kuwait International Airport from the Meteorological Department of the Directorate General of Civil Aviation in Kuwait. Airport data is known for its comprehensive record of hourly weather data extending back to the 1960s. Additionally, the Kuwait Environmental Public Authority conducts regular monitoring of meteorological indicators, including 24-hour daily average temperatures and relative humidity, gathered from 15 meteorological stations across urban areas in Kuwait. We selected the Airport data for this analysis due to its completeness and the lack of significant heterogeneity across the small geographic distribution of urban areas.26
Hospitalization data
The Ministry of Health keeps records of discharge forms (that subsequently get digitized) for every hospitalization. We obtained all ‘non-planned’ hospital admissions for diabetes mellitus from 14 public hospitals in Kuwait (7 general hospitals and 7 peripheral/tertiary hospitals). The data was available by the admission date and discharge diagnosis classified by the International Classification of Diseases 10 revision. We analyzed all admitted patients for diabetes mellitus causes (E10–E14), which includes type 1, type 2, and unspecified. The data structure did not enable us to detect multiple hospitalizations by the same individual. The admissions data were available from 1 January 2010 to 31 December 2020. We excluded the year 2020 because of the COVID-19 disruption to healthcare access.
Study design
We used a case-crossover design where each subject serves as their own control. This extension of the conventional case–control studies allows for a comparison within the same subject and, therefore, eliminates confounding at the individual level (eg, by age, sex, body mass index, smoking, etc).27 We compared temperature and dust concentrations during the day of hospitalization (case) to other days of the same day of the week (effectively 1 week apart) within the same month and the same year when the same individual was not hospitalized (self-control).
Statistical analysis
We fitted a conditional quasi-Poisson model with eliminated strata of a three-way interaction between day of the week, month, and year. The conditional Poisson models are efficient alternatives to conditional logistic models.28 Model specification is presented in online supplemental methods.
To estimate the effects of heat, we restricted the analysis to the hottest three summer months (June, July, and August) from 2010 to 2019. Temperature was fitted using distributed lag non-linear models (DLNM) that simultaneously model the temperature and lag dimensions.29 We used a short lag of 7 days with two natural spline knots placed equally on the log scale. Temperature was modeled with two natural spline knots placed at the 50th and 90th percentiles. The relative risk of diabetes hospitalization was calculated by comparing hot summer days to the lowest summer temperature day (33°C, rounded to the whole number). We summed up the contribution of each summer day using Gasparrini and Leone extension to calculate attributable risk.30
When estimating the effects of dusty days, we used all months from 2017 to 2019. Using penalized splines,31 we did not find evidence of non-linearity in the dust and hospitalization dose–response relationship. Dust was then fitted linearly in models adjusted for temperature, relative humidity, and anthropogenic-source pollution (regional PM2.5). We used a 7-day moving average to account for the lag effect. The relative risk of diabetes hospitalization was reported for every 10 µg/m3 increase in dust level. The attributable risk was calculated by multiplying the risk fraction by the total diabetes admissions per year.
We then used a generalized additive model to fit an interaction penalized spline31 for two continuous variables: 7-day moving average of temperature and dust. From the resulting smoothed three-dimensional relationship (dust–temperature–diabetes), we obtained predictions at three dust scenarios: no dust (0 µg/m3), high dust (85 µg/m3), and very high dust day (150 µg/m3), and used them to calculate the relative risk of diabetic hospitalization from summer hot days.
All analyses were done using R software (V.4.2.1) and the DLNM, MGCV, and Plotly packages.
Results
The total number of unplanned hospital admissions for diabetes mellitus was 11 155 all year long from 2017 to 2019 (table 1 and online supplemental table S1). For the summer months (June to August) from 2010 to 2019, there were a total of 8960 hospital admissions. Distribution of admissions across the years is presented in online supplemental figure S2.
Descriptive analysis of the study population and the environmental exposures
During the summer months, the average temperature was at 39.1°C (27.9°C for the year-long period), with a considerably narrower SD in summer, indicating less variation and a hot prolonged period (table 1). The climate was also characterized by dry heat with average relative humidity during summers as low as 16.5% (± 9.5%). Dust concentration averaged at 23.8 µg/m3 during summers. The year-long average of dust concentrations in Kuwait was 17.3 µg/m3 (± 26.7 µg/m3), although with a broader range from no dust days (0 µg/m3) to severe dust storms (290.4 µg/m3).
Figure 2 represents the dose–response relationships for heat and dust (independently) and the relative risk of diabetes hospitalization in Kuwait during the study period. For dust particles, the relationship shows a linear increase in risk as dust concentration rises. For every 10 micrograms per cubic meter increase in dust, the risk of hospitalization for diabetes increased by 3% (relative risk=1.03, 95% CI: 1.00 to 1.06) translating into about 114 excess diabetic admissions annually (95% CI: 11 to 219) (table 2).
Dose–response relationship showing the relative risk of diabetes hospital admissions for (A) summer heat and (B) dust in Kuwait.
Overall and stratified relative risk of diabetes hospitalization for heat and dust exposure in Kuwait
For the heat in summer months, the curve demonstrates a non-linear relationship where the relative risk increases substantially as temperatures rise from the summer minimum of 33°C, reaching a peak at around 38°C, then fluctuates and shows another smaller peak around 43°C (figure 2). Compared with the 33°C as a reference, the relative risk of hospitalization at 34°C was 1.11 (95% CI: 1.01 to 1.23); at 35°C was 1.26 (95% CI: 1.02 to 1.57); and this risk continued to increase, peaking at 38°C with a relative risk of 1.58 (95% CI: 1.03 to 2.42) (table 2). We found that each year, there were an excess of about 282 diabetic admissions attributed to hot days that were above 33°C (95% CI: −14 to 473). We observed almost a similar pattern among subgroups such as males versus females (p value=0.14) (table 2).
In three-dimensional smoothing, the temperature slope at extreme dust is less pronounced compared with the dust slope at extreme temperatures (online supplemental figure S3). In interaction analysis (table 3), compared with mild temperature non-dusty days (33°C (0 µg/m3)), hot–dusty days jointly increased the relative risk of diabetic admissions from 1.11 (95% CI: 0.85 to 1.45) at 42°C (85 µg/m3) to 1.36 (0.70 to 2.62) at 42°C (150 µg/m3). These findings of compounded risk of combined exposures warrant cautious interpretation, given the lack of precision in interaction models.
Interaction of hot–dusty days and the relative risk of diabetes hospitalization in Kuwait
Discussion
Kuwait’s extreme climate, being one of the hottest and dustiest environments globally, offers a unique natural laboratory to study the impacts of hot and dusty days on the incidence and management of an existing epidemic of diabetic patients. Our findings show that, in Kuwait, both heat and dust contribute to increased diabetes hospitalizations, with combined hot–dusty conditions seem to be exacerbating these risks even further.
There are several hypotheses that suggest diabetics may react to heat more intensely than healthy individuals. This increased heat sensitivity could be due to impaired sweat production and reduced blood flow to the skin, which are common in diabetes and can impair heat dissipation.16 Additionally, diabetic peripheral neuropathy and vascular damage may affect the body’s ability to regulate temperature.16 With heightened exposure, the pathophysiology here suggests pathways leading to three adverse outcomes that could lead to unplanned hospitalization for diabetic patients: worsening foot ulcers, hypoglycemia, and hyperglycemia. First, warm temperatures could promote bacterial growth,32 which, when coupled with the compromised healing capabilities inherent in diabetic patients, can significantly exacerbate the severity of diabetic foot ulcers.33 Second, thermal stress is associated with an increase in catabolic hormones such as epinephrine, glucagon, cortisol, and growth hormone, which serve as insulin antagonists.34 This hormonal surge may lead to a counter-regulatory response that precipitates hypoglycemia. Adding complexity to this scenario, heat also seems to enhance the absorption of subcutaneously injectable insulin, further increasing the risk for hypoglycemia.35 Finally, heat-induced fluid loss and subsequent dehydration can disrupt metabolic control, heightening the risk of hyperglycemic crises such as diabetic ketoacidosis in type 1 diabetics.36
When individuals breathe in dust, the fine particles (those lower than 2.5 µm in diameter) travel down to the pulmonary alveoli, where they can cross into the bloodstream. This translocation can lead to endothelial damage, as the particles directly injure the vascular endothelium. The resultant endothelial dysfunction is a recognized factor in the progression of vascular complications in diabetics.17 Concurrently, the presence of these dust particles can induce oxidative stress, overwhelming the body with free radicals leading to potential cellular damage, especially in tissues that are already susceptible due to hyperglycemic conditions.17 18 Additionally, the systemic inflammation triggered by the air pollution particles further exacerbates the chronic inflammatory state inherent to diabetes.37 This could precipitate acute diabetic complications, such as poor wound healing, an increased risk of infections, and cardiovascular events.
Exploring the interactive effects of air pollution and air temperature on health is increasingly gaining momentum, as these two exposures often occur simultaneously. Several studies have investigated this interaction in various geographic locations, focusing on hospital admissions38–40 and mortality, both within specific regions41 and globally across multiple countries and cities.42 43 These previous studies predominantly focused on cardiovascular and respiratory causes. To our knowledge, though, this is the first epidemiological assessment of such combined effects of harsh environmental conditions on diabetes. While earlier research has linked an increased risk of diabetes to carbonaceous particles emitted from man-made pollution sources,11 12 the impact of intensified natural dust storms on diabetes remains poorly understood.44 Dust events in the Middle East are increasing in frequency and severity due to a warming climate, causing more droughts.45 46 To isolate the effects of natural dust from other pollutants, we collected primary dust samples and analyzed their epidemiological impact on a population level. Additionally, prior studies have indicated that elevated temperatures can escalate the risk and complications associated with diabetes.13 However, the extreme heat observed in Kuwait, as reported in our study, is unlike most studied locations. The evidence we provide here is suggestive that the combined hot–dusty conditions may synergistically increase susceptibility among diabetics and increase healthcare costs and burdens.
This study has a number of limitations. Initially, our air pollution sampling campaign was designed to extend over at least 3 years; however, it was prematurely stopped in 2020 due to the COVID-19 lockdowns. The stoppage of funding also prevented us from restarting the air sampling. Despite this, with only 2 years of speciated dust data, we were still able to detect a statistically significant effect. However, expectedly, the interaction analysis was likely underpowered. Nevertheless, we argue that the effect estimates were strongly suggestive of worsening outcomes from combined hot–dusty conditions. Moreover, our approach aggregated data across types of diabetes, which may obscure differences in environmental susceptibility among patients with type 1, type 2, and unspecified diabetes. Surprisingly, the majority of discharge forms, completed by attending physicians, did not specify the type of diabetes. We were logistically unable to find the discharge forms and recode them. This was a lost opportunity to gain a deeper insight into the pathophysiological impacts of environmental factors on diabetes and its complexities. A limitation of this analysis is also the potential misclassification of exposures to heat and air pollution, as it is expected that subjects would spend most of their day indoors, whereas our measurements were taken from outdoor monitors. This discrepancy likely led to inaccuracies in exposure assessment. Additionally, physical activity, which is known to improve blood glucose control in type 2 diabetes, is likely reduced on days with high dust and heat, potentially exacerbating diabetic conditions. Finally, the geographical specificity to Kuwait, although a strength in understanding unique climate impacts, may limit the generalizability of our findings to regions with different climates and healthcare systems.
Conclusion
In today’s climate change, more regions find themselves unprepared to handle healthcare strains posed by intensive heatwaves and the potential transboundary desert dust. This study shows the role of extreme climate conditions on diabetic health in a country with one of the highest rates of obesity and diabetes globally. Environmental exposures do not happen in isolation; whether independently or jointly, they could contribute to increased diabetes hospitalizations. The diabetes healthcare professional community cannot afford to ignore emerging environmental risk factors.
Data availability statement
Data are available on reasonable request.
Ethics statements
Patient consent for publication
Ethics approval
This study was approved by the Dasman Diabetes Institute Ethical Review Committee (reference: RA MoH-2024-003).
References
Footnotes
Contributors BA, HA, and FA-M conceptualized the idea and commissioned the research analysis. BA and YA did the data cleaning and analysis. BA wrote the first draft of the manuscript. All authors significantly contributed to the planning, conduct, and reporting of this manuscript. BA had full access to the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Funding This study was supported by a grant from the Kuwait Foundation for the Advancement of Science grant CN23-13MM-1795 awarded to BA. The sampling work was supported by the Veterans Affairs Cooperative Studies Program #595: Pulmonary Health and Deployment to Southwest Asia and Afghanistan, from the United States (US) Department of Veterans Affairs, Office of Research and Development, Clinical Science Research and Development, Cooperative Studies Program. This publication was also made possible by US Environmental Protection Agency grant RD-835872, and the US National Aeronautics and Space Administration grant 80NSSC19K0225 awarded to PK.
Disclaimer The contents are solely the responsibility of the grantee and do not necessarily represent the official views of KFAS, VA, EPA or NASA. Further, the US Government and its granting entities do not endorse the purchase of any commercial products or services mentioned in the publication.
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.