A cross-sectional, randomized cluster sample survey of household vulnerability to extreme heat among slum dwellers in ahmedabad, india

Abstract

Extreme heat is a significant public health concern in India; extreme heat hazards are projected to increase in frequency and severity with climate change. Few of the factors driving population heat vulnerability are documented, though poverty is a presumed risk factor. To facilitate public health preparedness, an assessment of factors affecting vulnerability among slum dwellers was conducted in summer 2011 in Ahmedabad, Gujarat, India. Indicators of heat exposure, susceptibility to heat illness, and adaptive capacity, all of which feed into heat vulnerability, was assessed through a cross-sectional household survey using randomized multistage cluster sampling. Associations between heat-related morbidity and vulnerability factors were identified using multivariate logistic regression with generalized estimating equations to account for clustering effects. Age, preexisting medical conditions, work location, and access to health information and resources were associated with self-reported heat illness. Several of these variables were unique to this study. As sociodemographics, occupational heat exposure, and access to resources were shown to increase vulnerability, future interventions (e.g., health education) might target specific populations among Ahmedabad urban slum dwellers to reduce vulnerability to extreme heat. Surveillance and evaluations of future interventions may also be worthwhile.

Figure 1

Framework for assessing heat vulnerability: hazard probability, population exposure, susceptibility factors, and adaptive capacity.

Figure 2

Location of 13 randomly selected wards. Markers represent the central location of the sampled wards as a GPS was not accessible. Two wards per zone were sampled in each of five zones (West, New West, South, Central, North); and three wards were sampled in a sixth zone (East). West zone: Sabarmati, Juna Vadaj; New West zone: Thaltej, Johdpur; South zone: Maninagar, Behrampura; Central zone: Madhupura, Dudeshwar; North zone: Saijpur, Asarwa; East zone: Nikol, New Naroda, Ramol.

Figure S1

(A) Sampling design: Among the 6 city zones, two wards were randomly selected per zone (out of 57). The largest slum was selected (12 and one additional in East zone where boundaries were unclear), where 25 households were surveyed for a total of 25 households per slum and 300 total surveys; (B) Household selection method: The neighborhood layout varied among slums. An example of one organized by parallel lanes is shown. Research assistants (5) randomly selected one household to begin at in assigned area. After the initial household, they proceeded to every fourth, right or left of the initial.