Missing millions: undercounting urbanization in India

Onda, Kyle; Sinha, Parmanand; Gaughan, Andrea E.; Stevens, Forrest R.; Kaza, Nikhil

doi:10.1007/s11111-019-00329-2

Cited by 28 publications

(14 citation statements)

References 47 publications

(55 reference statements)

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“…Furthermore, due to the poor public transit infrastructure in India's urban regions, inhabitants opt for private transportation, which has led to massive automobile emissions that contribute to environmental deterioration. Consequently, urbanization in India causes environmental pollution and worsens population health over the long haul (57). As per the IQAir report, India's air quality is unhealthy; the most current statistics show that the country's annual mean concentration exceeds the recommended level of 10 g/m 3 (58).…”

Section: Discussionmentioning

confidence: 99%

Long-Term Air Pollution Exposure and Ischemic Heart Disease Mortality Among Elderly in High Aging Asian Economies

Mumtaz

Rehman

Haider

et al. 2022

Front. Public Health

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In the epidemiological literature, the impact of environmental pollution on cardiac mortality has been well documented. There is, however, a paucity of evidence on the impact of air pollution exposure on ischemic heart disease (IHD) mortality among the Asian aged population. In response, this research seeks to investigate the degree of proximity between exposure to ambient PM2.5, household PM2.5, ground-level ozone (O3), and IHD mortality in the top seven Asian economies with the highest aging rates. This investigation is held in two phases. In the first phase, grey modeling is employed to assess the degree of proximity among the selected variables, and then rank them based on their estimated grey weights. In addition, a grey-based Technique for Order of Preference by Similarity to Ideal Solution (G-TOPSIS) is adopted to identify the key influencing factor that intensifies IHD mortality across the selected Asian economies. According to the estimated results, South Korea was the most afflicted nation in terms of IHD mortality owing to ambient PM2.5 and ground-level O3 exposure, whereas among the studied nations India was the biggest contributor to raising IHD mortality due to household PM2.5 exposure. Further, the outcomes of G-TOPSIS highlighted that exposure to household PM2.5 is a key influencing risk factor for increased IHD mortality in these regions, outweighing all other air pollutants. In conclusion, this grey assessment may enable policymakers to target more vulnerable individuals based on scientific facts and promote regional environmental justice. Stronger emission regulations will also be required to mitigate the adverse health outcomes associated with air pollution exposure, particularly in regions with a higher elderly population.

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Section: Discussionmentioning

confidence: 99%

Long-Term Air Pollution Exposure and Ischemic Heart Disease Mortality Among Elderly in High Aging Asian Economies

Mumtaz

Rehman

Haider

et al. 2022

Front. Public Health

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“…Rapid urbanisation in the near future is estimated to add about 416 million dwellers by 2050. Other studies reported and estimated that the urban population is about 12% more than the official statistics by the Government of India in Census 2011 (Onda et al , 2019; Van Duijne, 2019). While there is no exact data for the number of people engaged in urban agriculture in India, a study by Paschapur and Bhat (2020) revealed that about 65% of produce in urban markets comes from peri-urban production.…”

Section: Methodsmentioning

confidence: 96%

Extent of urban agriculture and food security: evidence from Ghana and India

Bannor

Sharma

Oppong-Kyeremeh

2021

IJSE

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PurposeThe study attempted to assess the food security status of urban agriculture households in Ghana and India. Also, the extent of urban agriculture participation and its effect on food security in Ghana and India were examined.Design/methodology/approachA total of 650 urban agriculture farmers were interviewed for this study in Ghana and India. Food security status of urban households was assessed by the use of the Household Food Insecurity Access Scale, whereas the determinants of the extent of urban agriculture and its effect on food security were analysed by the use of the heteroskedastic linear regression and the Seemingly Unrelated Regression models, respectively.FindingsFrom the study on average, households in Ghana were mildly food insecure, but that of India was moderately food insecure. The results further revealed that various demographic, economic, institutional and health and nutrition factors differently influenced urban food security and urban agriculture. Also, the extent of urban agriculture participation positively influenced food security.Originality/valueSeveral studies in Asia (India) and Africa (Ghana) on urban food security have been geographically limited to New Delhi, Mumbai and Greater Accra, with few studies in the Middle Belt of Ghana, and Bihar in India. Besides, there is a limited, rigorous, empirical study on the effect of the extent of UA on food security in Asia (India) and Africa (Ghana) individually and together. Moreover, we extend the frontiers of the methodological approach by applying the Seemingly Unrelated Regression (SUR) model to understand if the factors that affect food-security accessibility based on two food security accessibility tools are correlated.

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“…The DEGURBA draws on two harmonised EU datasets: the Global Human Settlement Population (GHS-POP) and GHS Settlement Model (SMOD), which are classified based on population size, population counts and built-up area densities. Whilst the classification of urban areas using standardised geographies and urban definitions does facilitate international statistical comparisons, the rigid classification criteria has been controversial [9,10]. More generally and related to the above, smaller urban areas are more difficult to classify than larger urban areas using rigid criteria.…”

Section: Introductionmentioning

confidence: 99%

Identifying urban areas: A new approach and comparison of national urban metrics with gridded population data

Statham¹,

Wolf²,

Fox³

2021

Preprint

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The measurement of urbanization and other key urban indicators depends on how urban areas are defined. The Degree of Urbanization (DEGURBA) has been recently adopted to support international statistical comparability, but its rigid criteria for classify areas as urban/non-urban based upon fixed population size and density criteria is controversial. Here we present an alternative approach to urban classification, using a flexible range of population density \& count thresholds. We then compare how these thresholds affect estimation of urbanization and urban settlement counts across three of the most popular gridded population datasets (GPD). Instead of introducing further uncertainties by matching GPD to built-up area datasets, we classify urban areas in a purely spatial demographic way. By calculating national urban shares and urban area counts, we highlight the often overlooked uncertainties when using GPD. We find that the choice of GPD is generally the dominant factor in altering both of these urban indicators but the choice of urban criteria is also important. Overall, this alternative urban classification method offers a more flexible approach to human settlements classification that can be applied globally for comparative research.

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Missing millions: undercounting urbanization in India

Cited by 28 publications

References 47 publications

Long-Term Air Pollution Exposure and Ischemic Heart Disease Mortality Among Elderly in High Aging Asian Economies

Long-Term Air Pollution Exposure and Ischemic Heart Disease Mortality Among Elderly in High Aging Asian Economies

Extent of urban agriculture and food security: evidence from Ghana and India

Identifying urban areas: A new approach and comparison of national urban metrics with gridded population data

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