# Community Profiles

### Examples of the Model Queries

A few examples will help you to understand how you can use the model.

**Example One**

You might be interested in learning how many 85+ persons are projected to live in your area in 2026.

Enter your selection

1. | Enter Year | 2026 |

2. | Enter FSA | B3T |

3. | Enter age cohort | 85+ |

The following result will be shown:

Total Population for **B3T** is 14767 in year
**2026**

FSA | Gender | Age Group | Number of People |

B3T | F | 85+ | 66 |

B3T | M | 85+ | 25 |

**Example One**

You might also ask how many of this population will likely fall into each of the four health states.

Enter your selection

1. | Enter Year | 2026 |

2. | Enter FSA | B3T |

3. | Enter age cohort | 85+ |

4. | Enter Health | All |

The following result will appear:

Total Population for **B3T** is 14767 in year
**2026**

FSA | Gender | Age Group | Health State | Number of People |

B3T | F | 85+ | H1 | 16 |

B3T | F | 85+ | H2 | 13 |

B3T | F | 85+ | H3 | 14 |

B3T | F | 85+ | H4 | 23 |

B3T | M | 85+ | H1 | 10 |

B3T | M | 85+ | H2 | 6 |

B3T | M | 85+ | H3 | * |

B3T | M | 85+ | H4 | 5 |

The use of an * indicates that there are less than 5 persons in this category. Any number less than 5 will not be reported in the tables.

**Example Three**

If you are only interested in the wealth state of the 85+ age group you can:

1. | Enter Year | 2026 |

2. | Enter FSA | B3T |

3. | Enter Age | 85+ |

4. | Enter Wealth | All |

The following result will appear:

Total Population for **B3T** is 14767 in year
**2026**

FSA | Gender | Age Group | Wealth State | Number of People |

B3T | F | 85+ | W1 | 17 |

B3T | F | 85+ | W2 | 28 |

B3T | F | 85+ | W3 | 11 |

B3T | F | 85+ | W4 | 9 |

B3T | M | 85+ | W1 | 6 |

B3T | M | 85+ | W2 | 11 |

B3T | M | 85+ | W3 | * |

B3T | M | 85+ | W4 | * |

The use of an * indicates that there are less than 5 persons in this category. Any number less than 5 will not be reported in the tables.

**Example Four**

The final level of analysis combines health and wealth to produce sixteen possible outcomes ranging from H1W1 to H4W4. In the first case (H1W1) would be people who are dependence free, in good health and well off. At the other end of the continuum would be persons with institutionalized dependence and very limited resources.

1. | Enter Year | 2001 |

2. | Enter FSA | A0A |

3. | Enter Gender | Female |

4. | Enter Age | 75-79 |

5. | Enter Health | All |

6. | Enter Wealth | All |

The result is shown below:

Total Population for **A0A** is 57949 in year
**2001**

FSA | Gender | Age Group | Health State | Wealth State | Number of People |

A0A | F | 75-79 | H1 | W1 | 147 |

A0A | F | 75-79 | H1 | W2 | 165 |

A0A | F | 75-79 | H1 | W3 | 130 |

A0A | F | 75-79 | H1 | W4 | 136 |

A0A | F | 75-79 | H2 | W1 | 31 |

A0A | F | 75-79 | H2 | W2 | 34 |

A0A | F | 75-79 | H2 | W3 | 27 |

A0A | F | 75-79 | H2 | W4 | 28 |

A0A | F | 75-79 | H3 | W1 | 14 |

A0A | F | 75-79 | H3 | W2 | 15 |

A0A | F | 75-79 | H3 | W3 | 12 |

A0A | F | 75-79 | H3 | W4 | 13 |

A0A | F | 75-79 | H4 | W1 | 12 |

A0A | F | 75-79 | H4 | W2 | 13 |

A0A | F | 75-79 | H4 | W3 | 10 |

A0A | F | 75-79 | H4 | W4 | 11 |

To view an illustrative example of applying the model, Click here