Miamitown, OH Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| | Miamitown, OH | Ohio | U.S. |
| Total Housing Units | 469, 100% | 4,570,015 | 116,211,092 |
| Utility Gas | 47, 10.02%, see rank | 66.89% | 48.85% |
| Bottled, Tank, or LP Gas | 9, 1.92%, see rank | 5.26% | 4.86% |
| Electricity | 382, 81.45%, see rank | 22.05% | 36.68% |
| Fuel Oil, Kerosene, etc. | 31, 6.61%, see rank | 2.60% | 5.86% |
| Coal or Coke | 0, 0.00%, see rank | 0.07% | 0.12% |
| Wood | 0, 0.00%, see rank | 2.02% | 2.12% |
| Solar Energy | 0, 0.00%, see rank | 0.02% | 0.05% |
| Other Fuel | 0, 0.00%, see rank | 0.72% | 0.47% |
| No Fuel Used | 0, 0.00%, see rank | 0.37% | 1.00% |
ACS 2008-2012 data
| | Miamitown, OH | Ohio | U.S. |
| Total Housing Units | 484, 100% | 4,555,709 | 115,226,802 |
| Utility Gas | 14, 2.89%, see rank | 67.58% | 49.42% |
| Bottled, Tank, or LP Gas | 0, 0.00%, see rank | 5.46% | 5.03% |
| Electricity | 448, 92.56%, see rank | 21.02% | 35.51% |
| Fuel Oil, Kerosene, etc. | 22, 4.55%, see rank | 2.90% | 6.46% |
| Coal or Coke | 0, 0.00%, see rank | 0.08% | 0.12% |
| Wood | 0, 0.00%, see rank | 1.98% | 2.08% |
| Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
| Other Fuel | 0, 0.00%, see rank | 0.67% | 0.43% |
| No Fuel Used | 0, 0.00%, see rank | 0.30% | 0.90% |
ACS 2006-2010 data
| | Miamitown, OH | Ohio | U.S. |
| Total Housing Units | 501, 100% | 4,552,270 | 114,235,996 |
| Utility Gas | 15, 2.99%, see rank | 68.10% | 49.91% |
| Bottled, Tank, or LP Gas | 13, 2.59%, see rank | 5.71% | 5.38% |
| Electricity | 457, 91.22%, see rank | 20.05% | 34.20% |
| Fuel Oil, Kerosene, etc. | 16, 3.19%, see rank | 3.29% | 7.07% |
| Coal or Coke | 0, 0.00%, see rank | 0.09% | 0.12% |
| Wood | 0, 0.00%, see rank | 1.82% | 1.97% |
| Solar Energy | 0, 0.00%, see rank | 0.02% | 0.03% |
| Other Fuel | 0, 0.00%, see rank | 0.67% | 0.42% |
| No Fuel Used | 0, 0.00%, see rank | 0.27% | 0.90% |
* ACS stands for U.S. Census American Community Survey. According to the U.S. Census, if the date is a range, you can interpret the data as an average of the period of time.
