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Kusuma D, Pradeepa R, Khawaja KI, Hasan M, Siddiqui S, Mahmood S, Ali Shah SM, De Silva CK, de Silva L, Gamage M, Loomba M, Rajakaruna VP, Hanif AAM, Kamalesh RB, Kumarendran B, Loh M, Misra A, Tassawar A, Tyagi A, Waghdhare S, Burney S, Ahmad S, Mohan V, Sarker M, Goon IY, Kasturiratne A, Kooner JS, Katulanda P, Jha S, Anjana RM, Mridha MK, Sassi F, Chambers JC. Low uptake of COVID-19 prevention behaviours and high socioeconomic impact of lockdown measures in South Asia: Evidence from a large-scale multi-country surveillance programme. SSM Popul Health 2021; 13:100751. [PMID: 33665333 PMCID: PMC7902538 DOI: 10.1016/j.ssmph.2021.100751] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Revised: 01/29/2021] [Accepted: 02/01/2021] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND South Asia has become a major epicentre of the COVID-19 pandemic. Understanding South Asians' awareness, attitudes and experiences of early measures for the prevention of COVID-19 is key to improving the effectiveness and mitigating the social and economic impacts of pandemic responses at a critical time for the Region. METHODS We assessed the knowledge, behaviours, health and socio-economic circumstances of 29,809 adult men and women, at 93 locations across four South Asian countries. Data were collected during the national lockdowns implemented from March to July 2020, and compared with data collected prior to the pandemic as part of an ongoing prospective surveillance initiative. RESULTS Participants were 61% female, mean age 45.1 years. Almost half had one or more chronic disease, including diabetes (16%), hypertension (23%) or obesity (16%). Knowledge of the primary COVID-19 symptoms and transmission routes was high, but access to hygiene and personal protection resources was low (running water 63%, hand sanitisers 53%, paper tissues 48%). Key preventive measures were not widely adopted. Knowledge, access to, and uptake of COVID-19 prevention measures were low amongst people from disadvantaged socio-economic groups. Fifteen percent of people receiving treatment for chronic diseases reported loss of access to long-term medications; 40% reported symptoms suggestive of anxiety or depression. The prevalence of unemployment rose from 9.3% to 39.4% (P < 0.001), and household income fell by 52% (P < 0.001) during the lockdown. Younger people and those from less affluent socio-economic groups were most severely impacted. Sedentary time increased by 32% and inadequate fruit and vegetable intake increased by 10% (P < 0.001 for both), while tobacco and alcohol consumption dropped by 41% and 80%, respectively (P < 0.001), during the lockdown. CONCLUSIONS Our results identified important knowledge, access and uptake barriers to the prevention of COVID-19 in South Asia, and demonstrated major adverse impacts of the pandemic on chronic disease treatment, mental health, health-related behaviours, employment and household finances. We found important sociodemographic differences for impact, suggesting a widening of existing inequalities. Our findings underscore the need for immediate large-scale action to close gaps in knowledge and access to essential resources for prevention, along with measures to safeguard economic production and mitigate socio-economic impacts on the young and the poor.
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Affiliation(s)
- Dian Kusuma
- Centre for Health Economics & Policy Innovation, Imperial College Business School, UK
| | | | | | - Mehedi Hasan
- BRAC James P Grant School of Public Health, BRAC University, Dhaka, Bangladesh
| | | | - Sara Mahmood
- Services Institute of Medical Sciences, Lahore, Pakistan
| | | | | | | | - Manoja Gamage
- Faculty of Medicine, University of Colombo, Colombo, Sri Lanka
| | | | | | - Abu AM Hanif
- BRAC James P Grant School of Public Health, BRAC University, Dhaka, Bangladesh
| | | | | | - Marie Loh
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
- School of Public Health, Imperial College London, London, UK
| | | | | | | | | | - Saira Burney
- Services Institute of Medical Sciences, Lahore, Pakistan
| | - Sajjad Ahmad
- Punjab Institute of Cardiology, Lahore, Pakistan
| | | | - Malabika Sarker
- BRAC James P Grant School of Public Health, BRAC University, Dhaka, Bangladesh
| | - Ian Y. Goon
- School of Public Health, Imperial College London, London, UK
| | | | - Jaspal S. Kooner
- National Heart and Lung Institute, Imperial College London, London, UK
| | | | | | | | - Malay K. Mridha
- BRAC James P Grant School of Public Health, BRAC University, Dhaka, Bangladesh
| | - Franco Sassi
- Centre for Health Economics & Policy Innovation, Imperial College Business School, UK
| | - John C. Chambers
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
- School of Public Health, Imperial College London, London, UK
| | - NIHR Global Health Research Unit for Diabetes and Cardiovascular Disease in South Asia
- Centre for Health Economics & Policy Innovation, Imperial College Business School, UK
- Madras Diabetes Research Foundation, Chennai, India
- Services Institute of Medical Sciences, Lahore, Pakistan
- BRAC James P Grant School of Public Health, BRAC University, Dhaka, Bangladesh
- Max Healthcare, New Delhi, India
- Punjab Institute of Cardiology, Lahore, Pakistan
- Faculty of Medicine, University of Kelaniya, Ragama, Sri Lanka
- Faculty of Medicine, University of Colombo, Colombo, Sri Lanka
- Faculty of Medicine, University of Jaffna, Jaffna, Sri Lanka
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
- School of Public Health, Imperial College London, London, UK
- National Heart and Lung Institute, Imperial College London, London, UK
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Joshi A, Malhotra B, Amadi C, Loomba M, Misra A, Sharma S, Arora A, Amatya J. Gender and the Digital Divide Across Urban Slums of New Delhi, India: Cross-Sectional Study. J Med Internet Res 2020; 22:e14714. [PMID: 32343670 PMCID: PMC7338923 DOI: 10.2196/14714] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2019] [Revised: 10/18/2019] [Accepted: 12/16/2019] [Indexed: 01/20/2023] Open
Abstract
Background Disparities in access to specific technologies within gender groups have not been investigated. Slum settings provide an ideal population to investigate the contributing factors to these disparities. Objective This study aimed to examine gender differences in mobile phone ownership, internet access, and knowledge of SMS text messaging among males and females living in urban slum settings. Methods A convenience sampling approach was used in sample selection from 675 unnotified slums. A total of 38 slum sites were then selected across four geographic zones. Of these, 10% of the households in each slum site was selected from each zone. One household member was interviewed based on their availability and fulfillment of the eligibility criteria. Eligible individuals included those aged 18 years and above, residing in these slums, and who provided voluntary consent to participate in the study. Individuals with mental or physical challenges were excluded from the study. Results Our results showed that females were half as likely to own mobile phones compared with males (odds ratio [OR] 0.53, 95% CI 0.37-0.76), less likely to have internet access (OR 0.79, 95% CI 0.56-1.11), or know how to send text messages (OR 0.93, 95% CI 0.66-1.31). The predictors of mobile phone ownership, internet access, and text messaging between males and females included age, individual education, housing type, and the number of earning members in a household in the adjusted analysis. Among males, the number of earning members was a predictor of both mobile phone ownership and text messaging, whereas household education was a predictor of both internet access and text messaging. Age and individual education only predicted internet access, whereas housing type only predicted text messaging. Among females, household education was a predictor of all the technology outcomes. Age and type of toilet facility only predicted mobile phone ownership; housing type only predicted internet access whereas television ownership with satellite service and smoking behavior only predicted text messaging. Conclusions Our study findings showing disparate access to technology within gender groups lend support for further research to examine the causal mechanisms promoting these differences to proffer significant solutions. Specifically, our study findings suggest that improving household education is crucial to address the disparate access and usage of mobile phones, the internet, and text messaging among women in slum settings. This suggestion is due to the consistency in household educational level as a predictor across all these technology indicators. In addition, the mechanisms by which the number of household earning members influences the disparate access to technology among men call for further exploration.
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Affiliation(s)
- Ashish Joshi
- Graduate School of Public Health and Health Policy, City University of New York, New York, NY, United States
| | - Bhavya Malhotra
- Foundation of Health care Technologies Society, Delhi, India
| | - Chioma Amadi
- Graduate School of Public Health and Health Policy, City University of New York, New York, NY, United States
| | - Menka Loomba
- Foundation of Health care Technologies Society, Delhi, India
| | - Archa Misra
- Foundation of Health care Technologies Society, Delhi, India
| | - Shruti Sharma
- Foundation of Health care Technologies Society, Delhi, India
| | - Arushi Arora
- Foundation of Health care Technologies Society, Delhi, India
| | - Jaya Amatya
- Graduate School of Public Health and Health Policy, City University of New York, New York, NY, United States
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Joshi A, Arora A, Amadi-Mgbenka C, Mittal N, Sharma S, Malhotra B, Grover A, Misra A, Loomba M. Burden of household food insecurity in urban slum settings. PLoS One 2019; 14:e0214461. [PMID: 30939157 PMCID: PMC6445475 DOI: 10.1371/journal.pone.0214461] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Accepted: 03/13/2019] [Indexed: 11/19/2022] Open
Abstract
This study examined the burden of food insecurity in India’s un-notified slums, using an SDG framework to identify correlates of food insecurity. A convenience sampling approach was employed in selecting 38 slums from 675 un-notified slums across four geographic zones. Ten percent of the households in each slum site were selected from each zone, and one household member was interviewed, based on their availability and fulfilment of the eligibility criteria. Eligible individuals included those aged 18 years and above, who were resident in the selected slums and provided consent. Individuals with mental or physical challenges were excluded. A total sample of 907 study participants were included. Results showed that 43% (n = 393) of the participants were food insecure. More than half were females (73%, n = 285), who had not completed any schooling (51%, n = 202). One-third (n = 128) resided in the Northern Region of Delhi. SDG-related predictors of food insecurity included: household educational level (SDG 4 Quality education) (p = 0.03), coverage of health service needs (SDG 3 Good health and well-being) (p = 0.0002), electricity needs (SDG 7 affordable and clean energy) (p<0.0001), and employment needs (SDG 8 Decent and economic growth) (p = 0.003). Having healthcare needs that were partially or fully met was equally associated with higher food insecurity: this could be attributed to high healthcare costs and the lack of federal subsidies in un-notified slums, collectively contributing to high out-of-pocket health costs. Failure to fully meet employment needs was also significantly associated with higher food insecurity. However, met needs for electricity, finance, women’s safety and satisfactory family relationships, were associated with lower food insecurity. Household predictors of food insecurity included: number of household members, and the presence of physically disabled household members. Necessary interventions should include connecting food insecure households to existing social services such as India’s Public Distribution System, and multi-sector partnerships to address the existing challenges.
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Affiliation(s)
- Ashish Joshi
- Department of Epidemiology, City University of New York Graduate School of Public Health and Health Policy, New York, New York, United States of America
- * E-mail:
| | - Arushi Arora
- Foundation of Health care Technologies Society, New Delhi, India
- Columbia University Mailman School of Public Health, New York, New York, New York, United States of America
| | - Chioma Amadi-Mgbenka
- Department of Epidemiology, City University of New York Graduate School of Public Health and Health Policy, New York, New York, United States of America
| | - Nidhi Mittal
- Foundation of Health care Technologies Society, New Delhi, India
| | - Shruti Sharma
- Foundation of Health care Technologies Society, New Delhi, India
| | - Bhavya Malhotra
- Foundation of Health care Technologies Society, New Delhi, India
| | - Ashoo Grover
- Indian Council of Medical Research, New Delhi, India
| | - Archa Misra
- Foundation of Health care Technologies Society, New Delhi, India
| | - Menka Loomba
- Foundation of Health care Technologies Society, New Delhi, India
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