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. 2024 Dec 18;24:268. doi: 10.1186/s12902-024-01808-w

Association between night shift work and the risk of type 2 diabetes mellitus: a cohort-based meta-analysis

Fei Xie 1,✉, Kangshuo Hu 2, Rongrong Fu 3, Yueming Zhang 4, Kaiqi Xiao 2, Jieni Tu 2
PMCID: PMC11653577  PMID: 39696306

Abstract

Background

The impact of night shift work on the incidence of type 2 diabetes mellitus (T2DM) is not well understood. This meta-analysis assesses the association between night shift work and the risk of developing T2DM and explores this relationship across various subgroups.

Methods

We systematically searched PubMed, Web of Science, EBSCO, and the Cochrane Library from their inception until February 2024. We employed hazard ratios (HR) and 95% confidence intervals (95%CI) to quantify the association between night shift work and T2DM risk.

Results

Our analysis synthesized data from 9 articles encompassing 10 cohort studies. Overall, night shift workers exhibited a 30% increased incidence of T2DM compared to their daytime counterparts (HR = 1.30, 95% CI: [1.18, 1.43], P < 0.001). Among females, night shift workers had a higher incidence of T2DM (HR = 1.28, 95% CI: [1.16, 1.41]); however, in males, the association was not statistically significant (95% CI: [0.89, 2.63]). For individuals with a body mass index (BMI) > 30 kg/m2, night shift work was associated with an increased T2DM risk (HR = 1.14, P = 0.007), whereas there was no significant association for those with a BMI ≤ 30 kg/m2 (P = 0.255). Further, the risk of T2DM increased with longer durations of night shift work; workers with more than 10 years of night shift work faced a higher T2DM risk than those with 10 years or fewer (HR for > 10 years = 1.17, 95% CI: [1.10, 1.24]; HR for ≤ 10 years = 1.06, 95% CI: [1.03, 1.10]).

Conclusion

Findings suggest potential link between night shift work and T2DM risk. Longer durations of night shift work may increase the risk of T2DM. There may be gender differences (greater harm in women, but the male sample size is small) and obesity differences.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12902-024-01808-w.

Keywords: Night shift work, Type 2 diabetes mellitus, Gender, BMI, Risk, Meta-analysis

Introduction

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder characterized by elevated blood sugar levels, insulin resistance, or deficiency. It is closely linked to various comorbidities including atherosclerosis, cardiovascular disease, myocardial infarction, heart failure, and stroke [1, 2]. As the global population ages and expands, the prevalence of T2DM has dramatically increased, the global age-standardized total diabetes prevalence increased by 90.5% from 1990 to 2021 [3]. The number of affected people rose from 108 million in 1980 to 422 million in 2014 [4]. In 2021, there were approximately 529 million T2DM patients. As early as 2017, diabetes had already ranked as the ninth - leading cause of death. It is even predicted that more than 1.31 billion people will have T2DM in 2050 [3]. The medical expenses of T2DM patients without complications are approximately 3.2 times the average medical expenditure, and those of patients with microvascular and macrovascular complications can be up to 9 times the average [5]. T2DM represents a substantial challenge to public health security. Beyond genetic factors, the potential risk factors for T2DM include obesity, dietary habits, occupation, lifestyle, and psychological stress. Conversely, intake of 66 g of fruits and/or vegetables per day may reduce the risk of T2DM by a quarter over time [6].

Numerous studies have identified night shift work as a contributing factor to adverse health outcomes, such as increased incidences of T2DM, hypertension, and dyslipidemia [7, 8]. Over the past decade, several meta-analyses have examined the link between night shift work and T2DM. A 2015 meta-analysis found that shift work significantly elevates the risk of T2DM, particularly among females compared to males [9]. However, this study may have overestimated the impact of night shift work on T2DM risk, as it included some participants categorized as prediabetic. A more recent study in 2020 confirmed the positive association between shift work and T2DM risk but noted that less than half of the included studies were cross-sectional, offering weaker evidence [10]. In response to these findings, our current study exclusively focuses on published cohort studies to further investigate the association between night shift work and the risk of T2DM.

Methods

Search Strategy

This systematic review and meta-analysis adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [11]. The review was registered with PROSPERO (ID: CRD42024520037). We searched the electronic databases PubMed, Web of Science, EBSCO, and the Cochrane Library from inception through February 2024. Search terms used included MeSH terms “Shift Work Schedule” and “Diabetes Mellitus, Type 2”, supplemented with keywords “Night shift”, “Shift work”, and “T2DM”. We also manually screened references to identify relevant studies. Two researchers independently screened all retrieved literature based on pre-defined criteria, with discrepancies resolved through consensus.

Inclusion and exclusion criteria

Inclusion criteria encompassed studies where: (1) participants did not have T2DM, (2) the exposure factor was night shift work (night shift work and shift work that includes night shift work), (3) the control condition was non-night shift work, and (4) the study was an English-language cohort study examining the association between night shift work and T2DM.

Exclusion criteria included: (1) studies where data could not be statistically analyzed, and (2) studies originating from the same cohort, selecting only the most recent or comprehensive articles for inclusion.

Data extraction

Data were extracted by two independent researchers using a standardized form. Extracted data included authors, publication year, country, sample size, participant age and gender, body mass index (BMI), profession, study design, source of population, follow-up duration, adjustment parameters, duration of night shifts, and assessments of prediabetes and T2DM.

Quality Assessment

The quality of cohort studies was assessed independently by two reviewers using the Newcastle-Ottawa Scale (NOS). Four stars were allocated to cohort selection criteria, three to outcome assessment, and two to comparability between groups. Studies were then categorized as low (0–3), moderate (4–6), or high (7–9) quality. Only high-quality studies were included. Any disagreements were resolved by a third investigator.

Statistical analysis

The association between night shift work and T2DM was analysed using hazard ratios (HR) and 95% confidence intervals (95%CI). Given potential heterogeneity due to factors such as shift intensity, dietary habits, ethnicity, and physical activity, a random effects model was employed to calculate weights. Heterogeneity among studies was assessed using the Chi-square and I2 tests, with p < 0.05 and I2 ≥ 50% indicating significant heterogeneity. Original studies with large sample sizes (the results are more reliable) are often given higher weights. The combined results are represented by forest plots. Publication bias was evaluated using Begg’s test. Sensitivity analyses were conducted using the leave-one-out method. Statistical analyses were performed using Stata 12.0, employing a two-sided hypothesis test with significance set at p < 0.05.

Results

Literature search

The search and selection processes are depicted in Fig. 1. Initially, 4170 records were retrieved from electronic databases. An additional two studies were included through manual searches of reference lists from relevant studies. After duplicates were removed, 3454 articles remained. Based on title and abstract screening, 3390 articles were excluded. Following a full-text review of 64 articles against the selection criteria, 55 were excluded for the following reasons: non-cohort study design (n = 15), failure to meet inclusion criteria (n = 26), lack of available data (n = 11), and overlapping reports on the same participants (n = 3). Ultimately, 9 articles, comprising 10 cohort studies, were included in the meta-analysis [12–20].

Fig. 1.

Fig. 1

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Flow diagram of the selection process

Study characteristics

The 9 included articles, published between 1999 and 2021, consisted of one retrospective and nine prospective cohort studies. Geographically, four studies were conducted in Eastern countries and six in Western countries. The detailed characteristics of the included cohort studies are presented in Table 1.

Table 1.

Characteristics of included observational studies in the meta-analysis

Author Year Country Cohort No. of participant Follow-up time (year) Professions The type of work shift Adjust parameters Study design
Osaki, Y. 2021 Japan J-ECOH 17,628 13 Workers Shift work age, gender, marital status, hypertension, dyslipidemia, family history of diabetes, sedentary work, over time working, job position, alcohol, smoking, sleep duration, physical activity, BMI Prospective
Silva-Costa, A. 2020 Brazill ELSA-Brasil 8656 12 Civil servants Night shifts (≥ 5 consecutive hours of night work [22:00–05:00 h] at least four times per month) age, education, hours of work, BMI, physical activity Prospective
Hanprathet, N. 2019 Thailand NA 5947 7 Workers Current shift workers (did permanent night shifts only for at least three night shifts per month or; who rotated between two or three shifts with at least three night shifts per month until the baseline year) age, marital status, family history of diabetes, BMI, hypertension, DBP, FPG, WBC, TG, HDL-C, WC, education Retrospective
Shan, Z. 2018 United States Nurses’ Health Study 55,324 24 Nurses Rotating night shift work age, calendar year, ethnicity, BMI, marital status, living status, family history of diabetes, menopausal status, oral contraceptive, alcohol, energy intake, smoking, physical activity, AHEI Prospective
Shan, Z. 2018 United States Nurses’ Health Study II 88,086 22 Nurses Rotating night shift work age, marital status, calendar year, BMI, ethnicity, living status, family history of diabetes, menopausal status, oral contraceptive, alcohol, energy intake, smoking, physical activity, AHEI Prospective
Bannai, A. 2016 Japan NA 3195 6 Civil servants Shift work age, marital status, FPG, family history of diabetes, education, job position Prospective
Hansen, Anne B. 2016 Denmark The Danish Nurse Cohort 19,492 19 Nurses Night shifts age, smoking, physical activity, alcohol, fatty meat intake, marital status, job position, acute myocardial infarction, hypertension, fruit and vegetables intake, BMI Prospective
Vimalananda, V. G. 2015 USA BWHS 28,041 8 NA Night shift work age, questionnaire cycle, BMI, family history of diabetes, education, neighborhood socioeconomic status, vigorous activity levels, smoking, alcohol, energy intake, diet, coffee, decaffeinated coffee, soda, diet soda Prospective
Poulsen, K. 2014 Denmark NA 7305 7 Health care workers Evening/night shift work health, work, lifestyle Prospective
Kawakami, N. 1999 Japan NA 2194 8 Industrial workers Rotating shift workers engaged in two or three shift work schedules including night shift, with a weekly clockwise rotation age, BMI, education, alcohol, smoking, physical activity, family history of diabetes Prospective
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J-ECOH: Japan Epidemiology Collaboration on Occupational Health Study; BWHS: Black Women’s Health Study; No.: number; NA: not available; BMI: body mass index; DBP: diastolic blood pressure; WBC: white blood cell; TG: triglyceride; HDL-C: high density lipoprotein cholesterol; WC: waist circumference; AHEI: Alternate Healthy Eating Index score; FPG: fasting plasma glucose

Assessment of T2DM

T2DM was primarily assessed through fasting plasma glucose levels (FPG) ≥ 126 mg/dL, physician diagnoses, or medication usage. Adjusted parameters commonly included age, gender, marital status, BMI, ethnicity, living status (alone or with others), family history of diabetes, alcohol consumption, and smoking habits. These details are further elaborated in Supplementary Table 1.

Bias risk assessment

The Newcastle-Ottawa Scale (NOS) was employed to objectively assess the quality of the included observational cohort studies. The evaluations revealed that four cohort studies scored 9 points, four scored 8 points, and two scored 7 points. Detailed bias risk assessments are documented in Supplementary Table 2.

Association between Night Shift Work and T2DM

The meta-analysis demonstrated that night shift workers exhibit a higher incidence rate of T2DM compared to non-night shift workers (HR = 1.30, 95%CI: [1.18, 1.43], P < 0.001, I2 = 57.6%). Further details are presented in Fig. 2. All p-values in texts, tables, and captions are derived from HR analysis and all p-values in pictures are from heterogeneity analysis.

Fig. 2.

Fig. 2

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Forest plot of a meta-analysis assessing the association between night shift work and the risk of T2DM in all participants (p < 0.001)

Subgroup analysis of the association between night shift work and risk of T2DM

Gender association

In the female subgroup, night shift work was associated with a higher incidence of T2DM than the non-night shift work group (HR = 1.28, 95%CI: [1.16, 1.41], P < 0.001, I2 = 57.8%). In contrast, no significant association was observed in the male subgroup (HR = 1.53, 95%CI: [0.89, 2.63], P = 0.128, I2 = 45.8%). Further details can be found in Fig. 3.

Fig. 3.

Fig. 3

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Forest plots of a meta-analysis assessing the association between night shift work and the risk of T2DM in sex-specific subgroups (a: male, p = 0.128; b: female, p < 0.001)

Occupational association

Both medical and non-medical workers exposed to night shifts exhibited a higher risk of T2DM compared to those who were not exposed to night shifts (medical workers: HR = 1.33, P < 0.001; non-medical workers: HR = 1.27, P = 0.007), as detailed in Table 2.

Table 2.

Subgroup analyses assessing the association between night shift work and the risk of T2DM

Subgroup No. of researches No. of non-night shift work No. of night shift work HR 95%CI p I2 (%)
Gender
Female 5 89,748 104,578 1.28 (1.16,1.41) < 0.001 57.8
Male 4 4340 6806 1.53 (0.89,2.63) 0.128 45.8
BMI
≤ 30 kg/m2 2 22,549 6455 1.34 (0.81, 2.22) 0.255 87.4
> 30 kg/m2 2 7396 4018 1.14 (1.04, 1.25) 0.007 0
Profession
Medical workers 3 70,597 93,617 1.33 (1.22, 1.46) < 0.001 33.3
Non-medical workers 6 47,524 18,147 1.27 (1.07, 1.52) 0.007 55.2
Night shift duration
≤ 5 years 2 70,425 73,519 1.05 (1.01, 1.10) 0.024 0
> 5 years 3 77,454 28,322 1.13 (1.09, 1.18) < 0.001 0
≤ 10 years 3 89,399 77,454 1.06 (1.03, 1.10) < 0.001 0
> 10 years 3 13,264 77,454 1.17 (1.10, 1.24) < 0.001 0
Follow-up time
≤ 10 years 5 30,847 15,822 1.43 (1.09, 1.86) 0.009 64.0
> 10 years 4 87,274 95,942 1.30 (1.18, 1.43) < 0.001 48.2
Age
≤ 60 years old 3 56,798 92,559 1.35 (1.20, 1.52) < 0.001 44.6
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NO: number; HR: hazard ratio; 95%CI: 95% confidence intervals; BMI: body mass index; T2DM: type 2 diabetes mellitus

BMI-based association

For participants with a BMI ≤ 30 kg/m2, no significant association was found between night shift work and T2DM (HR = 1.34, 95%CI: [0.81, 2.22], P = 0.255, I2 = 87.4%). However, for those with a BMI > 30 kg/m2, night shift workers had a higher incidence of T2DM compared to non-night shift workers (HR = 1.14, 95%CI: [1.04, 1.25], P = 0.007, I2 = 0.0%), as shown in Fig. 4.

Fig. 4.

Fig. 4

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Forest plots of a meta-analysis assessing the association between night shift work and the risk of T2DM across BMI subgroups (a: BMI ≤ 30 kg/m2, p = 0.255; b: BMI > 30 kg/m2, p = 0.007)

Duration of night shift work

Participants with ≤ 5 years of night shift work had an increased risk of T2DM compared to those with no night shift work (HR = 1.05, 95%CI: [1.01, 1.10]), which was more pronounced in those with > 5 years of exposure (HR = 1.13, 95%CI: [1.09, 1.18]). The risks associated with ≤ 10 years and > 10 years of night shift work were similarly elevated (≤ 10 years: HR = 1.06, 95%CI: [1.03, 1.10]; >10 years: HR = 1.17, 95%CI: [1.10, 1.24]). These findings are detailed in Table 2; Fig. 5.

Fig. 5.

Fig. 5

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Forest plots of a meta-analysis assessing the association between night shift work and the risk of T2DM across night shift duration subgroups (a: ≤10 years, p < 0.001; b: >10 years, p < 0.001)

Follow-up time

The risk of T2DM was higher in night shift workers compared to non-night shift workers regardless of the follow-up time (≤ 10 years: HR = 1.43, 95%CI: [1.09, 1.86], P = 0.009, I2 = 64.0%; >10 years: HR = 1.30, 95%CI: [1.18, 1.43], P < 0.001, I2 = 48.2%), with details in Table 2.

Age-specific association

For individuals ≤ 60 years old, the incidence of T2DM was significantly higher among night shift workers (HR = 1.35, 95%CI: [1.20, 1.52], P < 0.001, I2 = 44.6%), as reported in Table 2.

Publication bias and sensitivity analysis

The assessment of publication bias and sensitivity regarding the association between night shift work and T2DM is detailed in Supplementary Figs. 1 and 2. The Begg’s test indicated no significant publication bias (P = 0.371). Sensitivity analysis, conducted using the leave-one-out method, confirmed the stability of the statistical results.

Discussion

This meta-analysis sought to investigate the relationship between night shift work and T2DM. The study synthesized data from 9 articles encompassing 10 cohort studies with over 235,800 participants, revealing a significant positive association between night shift work and the risk of developing T2DM. Specifically, the results of this meta-analysis show that night shift work exposed individuals have a 30% increased risk of T2DM compared to non-night shift exposed individuals. This association persisted across subgroup analyses by occupation (including medical and non-medical workers), duration of night shifts, and follow-up duration. Sensitivity analyses confirmed the stability of these results.

The increased risk among night shift workers may stem from disruptions in circadian rhythms. Normally, during the sleep phase under typical circadian conditions, vasopressin neurons in the suprachiasmatic nucleus (SCN) release vasopressin, which promotes the expression of glucose transporter 1 (GLUT1) in the arcuate nucleus (ARC). Night shift work disrupts this mechanism by directly affecting the SCN via the retinohypothalamic tract, leading to subsequent reduction in the activity of vasopressin neurons. This reduction in activity decreases GLUT1 expression in the ARC, thereby impairing glucose uptake, elevating circulating glucose levels, and promoting hyperglycemia [21–26].

Another critical pathway involves the hypothalamic suprachiasmatic nucleus, which releases various hormones that act on the paraventricular nucleus (PVN). The PVN influences the pineal gland to secrete melatonin via the sympathetic nervous system. Melatonin activates M1 and M2 receptors on the α and β cells of pancreatic islets, enhancing insulin secretion, promoting glycogen synthesis and glycolysis, inhibiting liver gluconeogenesis, and stimulating adipogenesis. Night shift work disrupts this pathway by suppressing PVN activation through light stimuli, resulting in reduced melatonin secretion from the pineal gland [27, 28]. This decrease in melatonin leads to lower insulin synthesis, reduced glucose utilization, and elevated circulating glucose levels [29]. Animal studies have demonstrated that melatonin supplementation can improve glucose metabolism in insulin-resistant mice fed high-fat diets [30].

Moreover, meta-analytical evidence from Delpino FM et al. suggests that melatonin may have an inhibitory effect on obesity. Experiments by Aubrecht et al. have shown that male mice exposed to dim light at night (dLAN) in conjunction with a high-fat diet (HFD) experience significant weight gain and impaired glucose tolerance, as well as diminished insulin secretion, indicating a synergistic effect between dLAN and HFD, where dLAN exacerbates the weight gain associated with HFD-induced obesity [31]. In the context of night shift work, many workers tend to consume late-night snacks, often high in fats. Our findings indicate that among those exposed to night shifts, individuals with obesity are at a heightened risk of developing T2DM, likely due to the described mechanisms. Conversely, non-obese individuals do not show an increased risk, possibly owing to their higher insulin sensitivity and more stable glucose levels.

Obese individuals exposed to night shifts experience exacerbated insulin resistance due to the dual impact of obesity and disrupted circadian rhythms. Clinical studies by Al-Sulaiti H et al. have shown that elevated levels of phospholipid metabolites such as choline, glycerophosphoethanolamine, and glycerophosphocholine are positively associated with insulin resistance in obese populations [32]. Obesity, often characterized by an increase in visceral fat, enhances lipid breakdown [33]. Adipose tissue, functioning as an endocrine organ, secretes various adipocyte-derived factors including free fatty acids (FFA), TNF-α, IL-6, leptin, adiponectin, visfatin, and other peptides [34]. FFAs, utilized for energy, reduce glucose uptake, thereby contributing significantly to insulin resistance. Pro-inflammatory cytokines such as TNF-α and IL-6, along with leptin, also promote insulin resistance, with TNF-α specifically inhibiting insulin receptor tyrosine kinase phosphorylation.

Additionally, there is significant evidence of gender disparities in the prevalence of T2DM, with females more frequently affected than males [35]. Our analysis indicates a positive association between night shift work and T2DM prevalence in the female subgroup, while no significant association was found in males. The association between higher BMI and increased T2DM risk is well-established. Systematic reviews have also shown that females are more likely to exhibit higher rates of obesity than males [36], and they have a greater rate of subcutaneous adipose tissue (SAT) formation and a more pronounced increase in waist circumference (WC) [37]. Furthermore, an increased WC is associated with a heightened risk of developing T2DM [38].

Meta-analytical evidence from previous research suggests significant gender association in hormonal profiles related to T2DM. Females generally exhibit higher levels of leptin and adiponectin compared to males of the same age and BMI. Notably, plasma adiponectin levels are inversely correlated with insulin sensitivity, a relationship that is more pronounced in females. Conversely, male testosterone levels, which suppress adiponectin secretion, appear to confer a protective effect against T2DM. Another previous meta-analysis further supports this by showing that men with T2DM have testosterone levels lower by 2.66 nmol/L than those without the disease [39, 40]. In this meta-analysis, it should be emphasized that since most of the cohort studies are nurse cohorts, the proportion of men is small. There are only more than 10,000 men, while there were nearly 200,000 women. The test power of the male subgroup is relatively low, so it is not easy to obtain positive results.

Additionally, women are more vulnerable to the adverse effects of social and occupational stressors, as well as sleep disorders [41]. Research indicates that night shift work exacerbates psychological stress and depression, particularly among women [42]. This stress activates the sympathetic nervous system, which in turn stimulates the hypothalamus to release corticotropin-releasing hormone (CRH), leading to adrenal cortex hormone release. Activating the hypothalamic-pituitary-adrenal axis, this process elevates cortisol levels, which promotes energy storage and mobilizes glucose and lipids into the bloodstream. Such hormonal fluctuations not only increase circulating glucose levels but also diminish insulin sensitivity, ultimately contributing to insulin resistance. Experimental findings by Fransson, L. et al. have shown that removal of the adrenal glands in mice leads to enhanced insulin sensitivity, underscoring the impact of adrenal hormones on glucose metabolism [43].

This study has demonstrated that prolonged exposure to night shifts is associated with an increased risk of developing T2DM, underscoring the detrimental effects linked to extended durations of such work schedules. In addition, the impact of night-shift exposure on the risk of T2DM may also be affected by various factors such as economic status, ethnicity, dietary conditions, and activity intensity. A cohort study has shown that the lower the household income, the higher the risk of diabetes in children or adolescents [44]. This may be related to the consumption of inexpensive and unhealthy food, poor lifestyle habits (smoking, excessive alcohol consumption) and socioeconomic stress among people with lower income. In another study, it has been indicated that a healthy diet and physical activity can reduce the incidence of T2DM [45]. Studies have also demonstrated that individuals of South Asian and African descent seem to be more susceptible to T2DM [46, 47]. This may be associated with genetic factors related to insulin resistance.

Our meta-analysis focused only on cohort studies with high-strength evidence and excluded pre-diabetic individuals. We used HR as the outcome measure for evaluating the risk of T2DM. Therefore, compared with the two previously published meta-analyses [9, 10], we only included 9 cohort studies. For example, the studies by Eriksson, A. K. et al. [48] and Ika, K. et al. [49] used odds ratio (OR) as the evaluation index; the study by Kita, T. et al. [50] was about the association between sleep duration/quality and diabetes risk, and the study by Oberlinner, C. et al. [51] focused on the impact of health examinations on the mortality rate of chronic diseases. None of these studies contained the HR index data of night shift work on the risk of T2DM.

Nevertheless, our study is not without limitations. Since in the included original studies the number of the female population was larger than that of the male, the lack of observed significant impact of night shift work on the prevalence of T2DM in the male subgroup might be related to the small sample size. For the subgroup analysis related to BMI, the ideal approach would be to use a dose-effect model and conduct linear regression analysis to explore the relationship between BMI and night shift work on the incidence of T2DM. Due to a lack of data, we can only perform subgroup analyses for BMI > 30 kg/m2 and BMI ≤ 30 kg/m2. Since there are differences in the adjustment factors of each original study and not all factors can be controlled, these can lead to biases in the results. The absence of detailed original data on variables such as age, intensity of night shift work, start times, and dietary habits restricted our ability to conduct more nuanced and diversified subgroup analyses. It is hoped that there will be more original research data in the future.

Conclusion

In summary, the present study establishes a correlation between night shift work and an elevated risk of T2DM, with the risk increasing as the duration of night shift exposure extends. Notably, this association exhibits gender-specific variations; the data reveal a discernible trend in women, whereas no significant trend is apparent in men. Regarding obesity status, a propensity for a stronger association with increased T2DM risk is observed among obese individuals, in contrast to their non-obese counterparts, where the association is less pronounced. These findings are consistent across various occupations, including medical and non-medical fields, diverse geographical regions, and multiple follow-up periods. While these results align with certain aspects of prior research, they underscore the need for further investigation and validation to elucidate the underlying mechanisms and potential occupational health interventions.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1 (13.8KB, docx)
Supplementary Material 2 (18.7KB, docx)
Supplementary Material 3 (26.4KB, docx)
Supplementary Material 4 (472.1KB, tif)
Supplementary Material 5 (851.4KB, tif)

Acknowledgements

None.

Abbreviations

95%CI

95% Confidence Interval

ARC

Arcuate Nucleus

BMI

Body Mass Index

CRH

Corticotropin-Releasing Hormone

dLAN

Dim Light at Night

FFA

Free Fatty Acids

FPG

fasting plasma glucose levels

GLUT1

Glucose Transporter 1

HR

Hazard Ratio

HFD

High-Fat Diet

NOS

Newcastle-Ottawa Scale

Odds ratio

OR

PVN

Paraventricular Nucleus

SAT

Subcutaneous Adipose Tissue

SCN

Suprachiasmatic Nucleus

SNS

Sympathetic Nervous System

T2DM

Type 2 Diabetes Mellitus

WC

Waist Circumference

Author contributions

FX designed the research process. FX and KSH searched the database for corresponding articles. KSH and RRF extracted useful information from the articles above. YMZ used statistical software for analysis. FX, KSH and KQX drafted the meta-analysis. KSH and JNT polished this article. All authors had read and approved the manuscript and ensured that this was the case.

Funding

No financial support was received for this study.

Data availability

The datasets supporting the conclusions of this article are included within the article. For further details, please contact the corresponding author.

Declaration

Ethics approval and consent to participate

Not applicable, as this paper is based on research from global databases.

Clinical trial number

not applicable.

Consent to Publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1 (13.8KB, docx)
Supplementary Material 2 (18.7KB, docx)
Supplementary Material 3 (26.4KB, docx)
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Supplementary Material 5 (851.4KB, tif)

Data Availability Statement

The datasets supporting the conclusions of this article are included within the article. For further details, please contact the corresponding author.

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