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Investigating the association between population density and travel patterns in Indian cities-An analysis of 2011 census data.

ABSTRACT: Many transport planners consider urban population density to be a significant determinant of travel behaviour. Much of the evidence for this comes from research in low-density, high-income settings. The 2011 Census of India reported mode of travel to work and distance for the first time. We have used these data to investigate the effect of urban density on commute travel patterns at city-level for Indian cities. In addition, we investigated the relationship between travel behaviour and other city-level variables. Using regression, we found almost no independent effect of density on the mode share of walk, cycle, motorised two-wheelers, cars and public transport, after controlling for population and income levels for the cities. Further, it appears that once density levels are greater than ~80 persons per hectare (pph), other factors become more important in determining travel patterns in cities. This evidence has significant implications for urban planning and transport policy in Indian cities and for many other low- and middle-income cities where average density tends to be higher than ~80 pph. For these cities, growth in the use of sustainable transport may not depend on further densification of already dense cities, but on details of how neighbourhoods and streets are designed.

SUBMITTER: Goel R

PROVIDER: S-EPMC7197754 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Investigating the association between population density and travel patterns in Indian cities-An analysis of 2011 census data.

Goel Rahul R Mohan Dinesh D

Cities (London, England) 20200501

Many transport planners consider urban population density to be a significant determinant of travel behaviour. Much of the evidence for this comes from research in low-density, high-income settings. The 2011 Census of India reported mode of travel to work and distance for the first time. We have used these data to investigate the effect of urban density on commute travel patterns at city-level for Indian cities. In addition, we investigated the relationship between travel behaviour and other cit ...[more]

PMID: 32382207

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Project description:BackgroundProviding infrastructure and land uses to encourage active travel (i.e., bicycling and walking) are promising strategies for designing health-promoting cities. Population-level exposure to air pollution during active travel is understudied.ObjectivesOur goals were a) to investigate population-level patterns in exposure during active travel, based on spatial estimates of bicycle traffic, pedestrian traffic, and particulate concentrations; and b) to assess how those exposure patterns are associated with the built environment.MethodsWe employed facility-demand models (active travel) and land use regression models (particulate concentrations) to estimate block-level (n = 13,604) exposure during rush-hour (1600-1800 hours) in Minneapolis, Minnesota. We used the model-derived estimates to identify land use patterns and characteristics of the street network that are health promoting. We also assessed how exposure is correlated with indicators of health disparities (e.g., household income, proportion of nonwhite residents). Our work uses population-level rates of active travel (i.e., traffic flows) rather than the probability of walking or biking (i.e., "walkability" or "bikeability") to assess exposure.ResultsActive travel often occurs on high-traffic streets or near activity centers where particulate concentrations are highest (i.e., 20-42% of active travel occurs on blocks with high population-level exposure). Only 2-3% of blocks (3-8% of total active travel) are "sweet spots" (i.e., high active travel, low particulate concentrations); sweet spots are located a) near but slightly removed from the city-center or b) on off-street trails. We identified 1,721 blocks (~ 20% of local roads) where shifting active travel from high-traffic roads to adjacent low-traffic roads would reduce exposure by ~ 15%. Active travel is correlated with population density, land use mix, open space, and retail area; particulate concentrations were mostly unchanged with land use.ConclusionsPublic health officials and urban planners may use our findings to promote healthy transportation choices. When designing health-promoting cities, benefits (physical activity) as well as hazards (air pollution) should be evaluated.

Project description:BackgroundDetailed assessments of mortality by occupation are scarce. We aimed to assess mortality by occupation in the UK, differences in rates between England and Wales and Scotland, and changes over time in Scotland.MethodsWe analysed adults of working age (20-59 years) using linked census and death records. Main occupation was coded into more than 60 groups in the 2001 census, with mortality follow-up until Dec 31, 2011. Comparable occupation data were available for Scotland in 1991, allowing assessment of trends over time. We calculated age-standardised all-cause mortality rates (per 100 000 person-years), stratified by sex. We used Monte Carlo simulation to derive p values and 95% CIs for the difference in mortality over time and between England and Wales and Scotland.FindingsDuring 4·51 million person-years of follow-up, mortality rates by occupation differed by more than three times between the lowest and highest observed rates in both men and women. Among men in England and Wales, health professionals had the lowest mortality (225 deaths per 100 000 person-years [95% CI 145-304]), with low rates also shown in managers and teachers. The highest mortality rates were in elementary construction (701 deaths per 100 000 person-years [95% CI 593-809]), and housekeeping and factory workers. Among women, teachers and business professionals had low mortality, and factory workers and garment trade workers had high rates. Mortality rates have generally fallen, but have stagnated or even increased among women in some occupations, such as cleaners (337 deaths per 100 000 person years [95% CI 292-382] in 1991, rising to 426 deaths per 100 000 person years in 2001 [371-481]). Findings from simulation models suggested that if mortality rates by occupation in England and Wales applied to Scotland, 631 fewer men (95% CI 285-979; a 9·7% decrease) and 273 fewer women (26-513; 6·7% decrease) of working age would die in Scotland every year. Excess deaths in Scotland were concentrated among lower skilled occupations (eg, female cleaners).InterpretationMortality rates differ greatly by occupation. The excess mortality in Scotland is concentrated among low-skilled workers and, although mortality has improved in men and women in most occupational groups, some groups have experienced increased rates. Future research investigating the specific causes of death at the detailed occupational level will be valuable, particularly with a view to understanding the health implications of precarious employment and the need to improve working conditions in very specific occupational groups.FundingNone.

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Investigating the association between population density and travel patterns in Indian cities-An analysis of 2011 census data.

Publications

Investigating the association between population density and travel patterns in Indian cities-An analysis of 2011 census data.

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