Table 7.
Influence of BMI in samples that condition on days from onset.
| Hotspots | Natural log number of confirmed cases | Case fatality rate | Red zones | |
|---|---|---|---|---|
| (1) | (2) | (3) | (4) | |
| Panel A: Adults (15−49) | ||||
| BMI: Sample in which days from onset=0 | 0.144*** | 0.365** | −0.070 | 0.075** |
| (0.035) | (0.147) | (0.081) | (0.038) | |
| Observations | 391 | 266 | 137 | 389 |
| R-squared | 0.442 | 0.503 | 0.517 | 0.342 |
| Panel B: Adults (15−49) | ||||
| BMI: Sample in which days from onset = 1 | 0.116** | 0.208 | −0.027 | 0.144** |
| (0.058) | (0.178) | (0.103) | (0.061) | |
| Observations | 209 | 172 | 100 | 208 |
| R-squared | 0.521 | 0.583 | 0.642 | 0.446 |
| Panel C: Adults (15−49) | ||||
| BMI: Sample in which days from onset=5 | 0.157 | 0.049 | 0.170 | 0.202* |
| (0.112) | (0.276) | (0.200) | (0.114) | |
| Observations | 131 | 122 | 64 | 131 |
| R-squared | 0.571 | 0.598 | 0.743 | 0.449 |
| Panel D: Adults (15−49) | ||||
| BMI: Sample in which days from onset = 10 | 0.092 | −0.002 | 0.080 | 0.084 |
| (0.082) | (0.255) | (0.177) | (0.090) | |
| Observations | 185 | 151 | 79 | 184 |
| R-squared | 0.521 | 0.608 | 0.714 | 0.429 |
| Includes rainfall and temperature | YES | YES | YES | YES |
| Includes controls | YES | YES | YES | YES |
| Include control for testing rate | YES | YES | YES | YES |
| Include controls for demographic/health infrastructure | YES | YES | YES | YES |
| Includes controls for HBA, BP and glucose levels | YES | YES | YES | YES |
| Includes log number of women elected | YES | YES | YES | YES |
| Includes state fixed-effects | NO | NO | NO | NO |
Notes: OLS regression results of district-level data presented. Models include a constant term which is not reported. Controls include a set of individual (height, age, marital status, educational level, and number of children less than 5 years in the household) and household characteristics (religion and caste identifiers, wealth index, controls for age of the household head, gender of the household head, household size, type of wall material of the house, rural/urban status, presence of electricity, type of toilet facility, primary source of drinking water and years lived in place of residence). Testing rate is measured at the state-level. State-level measures on demographic/health infrastructure include the natural log of population density in 2011, natural log of per capita health expenditure in 2016, natural log number of doctors in 2018, proportion of respiratory cases in 2018, and proportion of the population that is 60 years and above in 2017. State fixed-effects cannot be included in columns (1)-(4) as these variables are at the state-level. Robust White standard errors reported. Table reports weighted estimates. Onset day is defined as the day at which the number of confirmed cases reaches 1 per 100,000 people (Desmet and Wacziarg, 2020). *** Denotes significance at the 1 % level, ** at the 5 % level and * at the 1 % level.