Spatial Pattern and Determinants of Diagnosed Diabetes in Southern India: Evidence From a Population Based Survey

2018 ◽  
Author(s):  
Somdutta Barua ◽  
Nandita Saikia ◽  
Rayhan Sk
2020 ◽  
pp. 1-16
Author(s):  
Somdutta Barua ◽  
Nandita Saikia ◽  
Rayhan Sk

Abstract The diabetes epidemic is expanding rapidly in India, with 69.2 million people living with diabetes in 2015. This study assessed the spatial pattern and determinants of diagnosed diabetes prevalence in the districts of six states and one union territory (UT) in southern India – a region that has a high prevalence of diabetes. Using cross-sectional population-based survey data from the 2012–13 District Level Household and Facility Survey-4, the prevalence and magnitude of diagnosed diabetes at district level for the population aged 18 years and above were computed. Moran’s I was calculated to explore the spatial clustering of diagnosed diabetes prevalence. Ordinary Least Square (OLS) and Spatial Lag (SL) regression models were carried out to investigate the spatial determinants of diagnosed diabetes prevalence. The prevalence of diagnosed diabetes was found to be substantially higher than that of self-reported diabetes in southern India (7.64% vs 2.38%). Diagnosed diabetes prevalence in the study area varied from 10.52% in Goa to 4.89% in Telangana. The Moran’s I values signified positive moderate autocorrelation. Southern India had 14.15 million individuals with diagnosed diabetes in 2012–13. Bangalore had the highest number of persons with diagnosed diabetes, and Palakkad had the smallest number. In the OLS and SL models, the proportion of people with secondary education and above, wealthy and Christian populations were found to be significant determinants of diagnosed diabetes prevalence. In addition, in the OLS model, the proportion of Scheduled Tribe population showed a negative relationship with diagnosed diabetes prevalence. In order to prevent or postpone the onset age for diabetes, there is a need to raise awareness about diabetes in India.


Author(s):  
Mohamed H Al-Thani ◽  
Elmoubasher Farag ◽  
Roberto Bertollini ◽  
Hamad Eid Al Romaihi ◽  
Sami Abdeen ◽  
...  

Abstract Background Qatar experienced a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic that disproportionately affected the craft and manual worker (CMW) population who comprise 60% of the total population. This study aimed to assess ever and/or current infection prevalence in this population. Methods A cross-sectional population-based survey was conducted during July 26-September 09, 2020 to assess both anti-SARS-CoV-2 positivity through serological testing and current infection positivity through polymerase chain reaction (PCR) testing. Associations with antibody and PCR positivity were identified through regression analyses. Results Study included 2,641 participants, 69.3% of whom were <40 years of age. Anti-SARS-CoV-2 positivity was 55.3% (95% CI: 53.3-57.3%) and was significantly associated with nationality, geographic location, educational attainment, occupation, and previous infection diagnosis. PCR positivity was 11.3% (95% CI: 9.9-12.8%) and was significantly associated with nationality, geographic location, occupation, contact with an infected person, and reporting two or more symptoms. Infection positivity (antibody and/or PCR positive) was 60.6% (95% CI: 58.6-62.5%). The proportion of antibody-positive CMWs that had a prior SARS-CoV-2 diagnosis was 9.3% (95% CI: 7.9-11.0%). Only seven infections were ever severe and one was ever critical—an infection severity rate of 0.5% (95% CI: 0.2-1.0%). Conclusions Six in every 10 CMWs have been infected, suggestive of reaching the herd immunity threshold. Infection severity was low with only one in every 200 infections progressing to be severe or critical. Only one in every 10 infections had been previously diagnosed suggestive of mostly asymptomatic or mild infections.


Author(s):  
Marion Meuwly ◽  
Diane Auderset ◽  
Sophie Stadelmann ◽  
Joan-Carles Suris ◽  
Yara Barrense-Dias

Sign in / Sign up

Export Citation Format

Share Document