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Varghese C, Wu Z, Bissett IP, Connolly MJ, Broad JB. Seasonal variations in acute diverticular disease hospitalisations in New Zealand. Int J Colorectal Dis 2023; 38:46. [PMID: 36795135 PMCID: PMC9935723 DOI: 10.1007/s00384-023-04338-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/07/2023] [Indexed: 02/17/2023]
Abstract
PURPOSE Seasonal variation of acute diverticular disease is variably reported in observational studies. This study aimed to describe seasonal variation of acute diverticular disease hospital admissions in New Zealand. METHODS A time series analysis of national diverticular disease hospitalisations from 2000 to 2015 was conducted among adults aged 30 years or over. Monthly counts of acute hospitalisations' primary diagnosis of diverticular disease were decomposed using Census X-11 times series methods. A combined test for the presence of identifiable seasonality was used to determine if overall seasonality was present; thereafter, annual seasonal amplitude was calculated. The mean seasonal amplitude of demographic groups was compared by analysis of variance. RESULTS Over the 16-year period, 35,582 hospital admissions with acute diverticular disease were included. Seasonality in monthly acute diverticular disease admissions was identified. The mean monthly seasonal component of acute diverticular disease admissions peaked in early-autumn (March) and troughed in early-spring (September). The mean annual seasonal amplitude was 23%, suggesting on average 23% higher acute diverticular disease hospitalisations during early-autumn (March) than in early-spring (September). The results were similar in sensitivity analyses that employed different definitions of diverticular disease. Seasonal variation was less pronounced in patients aged over 80 (p = 0.002). Seasonal variation was significantly greater among Māori than Europeans (p < 0.001) and in more southern regions (p < 0.001). However, seasonal variations were not significantly different by gender. CONCLUSIONS Acute diverticular disease admissions in New Zealand exhibit seasonal variation with a peak in Autumn (March) and a trough in Spring (September). Significant seasonal variations are associated with ethnicity, age, and region, but not with gender.
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Affiliation(s)
- Chris Varghese
- Department of Geriatric Medicine, The University of Auckland, PO Box 93 503, 124 Shakespeare Road, Takapuna, Auckland, New Zealand
- Department of Surgery, The University of Auckland, Auckland, New Zealand
| | - Zhenqiang Wu
- Department of Geriatric Medicine, The University of Auckland, PO Box 93 503, 124 Shakespeare Road, Takapuna, Auckland, New Zealand.
- School of Population Health, The University of Auckland, Auckland, New Zealand.
| | - Ian P Bissett
- Department of Surgery, The University of Auckland, Auckland, New Zealand
| | - Martin J Connolly
- Department of Geriatric Medicine, The University of Auckland, PO Box 93 503, 124 Shakespeare Road, Takapuna, Auckland, New Zealand
- Waitematā District Health Board, Auckland, Auckland, New Zealand
| | - Joanna B Broad
- Department of Geriatric Medicine, The University of Auckland, PO Box 93 503, 124 Shakespeare Road, Takapuna, Auckland, New Zealand
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Li Y, Luo X, Wu Y, Yan S, Liang Y, Jin X, Sun X, Mei L, Tang C, Liu X, He Y, Yi W, Wei Q, Pan R, Cheng J, Su H. Is higher ambient temperature associated with acute appendicitis hospitalizations? A case-crossover study in Tongling, China. INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2022; 66:2083-2090. [PMID: 35913519 DOI: 10.1007/s00484-022-02342-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 04/12/2022] [Accepted: 07/25/2022] [Indexed: 06/15/2023]
Abstract
Existing studies suggested that ambient temperature may affect the attack of acute appendicitis. However, the identification of the quantitative effect and vulnerable populations are still unknown. The purposes of this study were to quantify the impact of daily mean temperature on the hospitalization of acute appendicitis and clarify vulnerable groups, further guide targeted prevention of acute appendicitis in Tongling. Daily data of cases and meteorological factors were collected in Tongling, China, during 2015-2019. Time stratified case-crossover design and conditional logistic regression model were used to evaluate the odds ratio (OR) of ambient temperature on hospitalizations for acute appendicitis. Stratified analyses were performed by sex, age, and marital status. The odds ratio (OR) of hospitalizations for acute appendicitis increased by 1.6% for per 1 ℃ rise in mean temperature at lag3[OR = 1.016, 95% confidence interval (CI): 1.004-1.028]. In addition, our results suggest it is in the women that increased ambient temperature is more likely to contribute to acute appendicitis hospitalizations; we also found that the married are more susceptible to acute appendicitis hospitalizations due to increased ambient temperature than the unmarried; people in the 21-40 years old are more sensitive to ambient temperature than other age groups. The significant results of the differences between the subgroups indicate that the differences between the groups are all statistically significant. The elevated ambient temperatures increased the risk of hospitalizations for acute appendicitis. The females, married people, and patients aged 21-40 years old were more susceptible to ambient temperature. These findings suggest that more attention should be paid to the impact of high ambient temperature on acute appendicitis in the future.
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Affiliation(s)
- Yuxuan Li
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, 230032, Anhui, China
| | - Xuelian Luo
- Department of Medicine, Tongling Vocational and Technical College, Tongling, 244000, China
| | - Yudong Wu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, 230032, Anhui, China
| | - Shuangshuang Yan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, 230032, Anhui, China
| | - Yunfeng Liang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, 230032, Anhui, China
| | - Xiaoyu Jin
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, 230032, Anhui, China
| | - Xiaoni Sun
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, 230032, Anhui, China
| | - Lu Mei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, 230032, Anhui, China
| | - Chao Tang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, 230032, Anhui, China
| | - Xiangguo Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, 230032, Anhui, China
| | - Yangyang He
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, 230032, Anhui, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, 230032, Anhui, China
| | - Qiannan Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, 230032, Anhui, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, 230032, Anhui, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, 230032, Anhui, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China.
- Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, 230032, Anhui, China.
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