# 2. Health status indicators based on vital statistics (Statistics Canada)

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For more information on vital statistics go to the Vital Statistics – Death Database, the Vital Statistics – Birth Database, and the Vital Statistics – Stillbirth Database.

## 2.1 Provincial vital and cancer statistics

Health indicators based on vital and cancer statistics are produced at the Canada, province and territorial level only, with long time series. These indicators may have different methodologies compared to the regional health indicators (refer to section 2.2). Data on provincial health and on regional health may be the same indicator, but the numbers or rates may differ because of their methodologies. One key difference is that, apart from life expectancy, the provincial indicators are based on single years of data, whereas regional level data are based on multiple year averages (refer to section 2.2). For this reason, in addition to certain additional methodological differences, comparisons between these two sources are not recommended.

These provincial health indicators include the Canada/province/territory–only time series data for life expectancy, low birth weight, age–standardized mortality rates, infant mortality, potential years of life lost and cancer incidence.

The figures have been subjected to a confidentiality procedure known as controlled rounding to prevent the possibility of associating statistical data with any identifiable individual. Under this method, all figures, including totals and margins, are rounded either up or down to a multiple of 5. Controlled rounding has the advantage over other types of rounding of producing additive tables as well as offering more protection.

Age–standardized mortality were calculated using the direct method as presented in section 2.2.2.

Life expectancy is calculated using the Greville method, a widely recognized method of constructing a life table^{1}. These provincial/territorial life expectancy data were based on three years of mortality and population. Although their methodologies differ, the Greville, Chiang and Keyfitz methods of calculating life expectancy yield similar results^{2}.

The provincial–level vital statistics indicators for low birth weight and infant mortality were based on a single year of data.

Potential years of life lost (PYLL) was calculated in the same fashion as the regional–level indicators of the same name, as described in section 2.2.9, except that here it is based on a single year of data.

## 2.2 Regional–level vital statistics indicators

Rates are based on place of residence for indicators derived from birth and death events.

Indicators presented in this product (with the exception of province–only indicators, described above) which were derived from vital statistics, are based on three years of data in both numerator and denominator. For most birth related statistics (for example, low birth weight), three years of birth data are used in both the numerator and denominator. For infant and perinatal mortality, three years of death or stillbirth data are divided by the same three years of birth data. For mortality and potential years of life lost (PYLL), three consecutive years of death data (for example, 2005 to 2007) are summed and divided by three consecutive years of population data. For life expectancy, three years of death data (for example, 2005 to 2007) are divided by three years of population estimates (for example, 2005 to 2007). In vital statistics table titles, the start and end year of the three year period is referred to.

### 2.2.1 Regional level data quality measures: Confidence Intervals

All data presented have an associated 95% confidence interval (CI). The confidence interval illustrates the degree of variability associated with a rate. Wide confidence intervals indicate high variability, thus, these rates should be interpreted and compared with due caution. Some age–standardized rates were suppressed due to both a very small underlying count plus extremely high variability. Confidence intervals can also be used to determine whether a rate in one health region is statistically below, above or no different than the rate for the same indicator in another health region.

The confidence intervals for the age–standardized rates were produced using the variance derived using the Spiegelman method^{3 }.

Where,

is the standard population (refer to section 2.2.2),

is the age–specific standard population,

is the age group (using 5-year age groups),

is the population estimate for the corresponding age group,

is the mean age–specific crude mortality rate,

**Note(s):** when using *n* years of data, a different expression is used for

Where is the number of deaths in age group *x* in year *i* .

The confidence intervals for the crude count, crude rate and birth–related data were produced via the Fleiss method^{4} . Take note that the lower limit of the confidence interval (CI) in this formula is constrained by zero, which means the difference between the rate and the lower CI is not always equal to the difference between the rate and the upper CI.

Lower limit

Upper limit

Where,

*n* is the number of events,

*p* is the proportion or rate,

*c* is the standard error (1.96 at 95% confidence)

*q* = (1 - p).

Remember that *n* is comprised of three years' worth of data, and

, where pop is three years' worth of life–years.

### 2.2.2 Age–standardized rates

Mortality rates, with the exception of crude rates, infant and perinatal mortality, as well as cancer incidence and certain CIHI–based data, are age–standardized using the direct method, and the 2011 Canadian Census population structure. The use of a standard population results in more meaningful rate comparisons, as it adjusts for variations in population age distributions over time and across different geographic areas.

Age (in years) |
Standard population |
---|---|

0 to 4 | 1,899,064 |

5 to 9 | 1,810,433 |

10 to 14 | 1,918,164 |

15 to 19 | 2,238,952 |

20 to 24 | 2,354,354 |

25 to 29 | 2,369,841 |

30 to 34 | 2,327,955 |

35 to 39 | 2,273,087 |

40 to 44 | 2,385,918 |

45 to 49 | 2,719,909 |

50 to 54 | 2,691,260 |

55 to 59 | 2,353,090 |

60 to 64 | 2,050,443 |

65 to 69 | 1,532,940 |

70 to 74 | 1,153,822 |

75 to 79 | 919,338 |

80 to 84 | 701,140 |

85 to 89 | 426,739 |

90 and over | 216,331 |

The formula for age–standardized death rate *r* is:

Where for age group

*i,*

is the age–sex specific death count,

is the population size for a given cause of death and geographical area, and

is the weight for that group.

**Note(s):** that the same weight is used for each sex. To yield a rate per 100,000 population, *r* is multiplied by 100,000.

### 2.2.3 Geographic coding (geo–coding) to health regions

Birth and death data have been linked to health regions using postal codes reported with place of residence and converted to census geography using the automated geo–coding system (PCCF+^{5}) developed by the Health Statistics Division of Statistics Canada.

Numbers and rates for tables where this geo–coding is performed may differ to those found in similar tables using Vital Statistics data.

### 2.2.4 Birth statistics

Low birth weight is calculated as the number of live births with a birth weight of less than 2,500 grams. High birth weight is calculated as the number of live births with a birth weight of greater than 4,500 grams. The rates for these indicators are calculated by dividing the count by the number of live births where the birth weight was known.

Small and large for gestational age counts and rates are calculated using the birth weight for gestational age chart found in Kramer et al. “A New and Improved Population–based Canadian Reference for Birth Weight for Gestational age”^{6}. Small for gestational age counts include live births with a birth weight less than the 10th percentile of birth weights of the same sex and gestational age in weeks whereas large for gestational age counts include live births with a birth weight greater than the 90th percentile of birth weights of the same sex and gestational age in weeks. The rates for these indicators are calculated by dividing the count by the number of live singleton births with known birth weight and with gestational ages between 22 and 43 weeks.

Preterm births are calculated as live births with a gestational age of less than 37 weeks. The rate is calculated by dividing the count by the number of live births where the gestational age was known.

Infant mortality is calculated as deaths of those under one year of age. The rate is calculated by dividing the count by the number of live births.

Perinatal mortality is calculated as the total number of stillbirths with a gestational age of 28 weeks or more added to the number of deaths of infants aged less than one week. The rate is calculated by dividing the count by the sum of stillbirths with a gestational age of 28 weeks or more and all live births.

### 2.2.5 Life expectancy

This variable is calculated using the Greville methodology for abridged life tables. The estimates are based on three consecutive years (for example, 2005 to 2007) of mortality data and population estimates. See "Life Tables, Canada, provinces and territories, 2000/2002" (catalogue number 84-537-XIE) for a complete explanation of the methodology used to produce abridged life tables.

Since there is more variability in the number of events by age in smaller geographic areas, abridged life tables are more suitable for the adaptation to a sub–provincial level (health region). Greville’s method in particular was chosen because it was relatively easy to adapt to the health region level data and aligned with the methodology used to calculate provincial level estimates. Confidence intervals for life expectancy data were produced using the Chiang method and included the calculation of standard error (in this case, addressing the variability of deaths from one year to the next).

### 2.2.6 Disability–free life expectancy

Estimates of disability–free life expectancy are calculated using Sullivan’s method^{7}. Essentially, the latter generalizes Chiang’s method^{8}.

Sullivan’s method is based on activity limitation rates within a population, according to sex and age group, in the calculation of life expectancy with disability. In the case of people living in health institutions, it was assumed that everyone had at least one activity limitation. For people living in other types of institutions, the hypothesis established is that the activity limitation rate by age group and sex was identical to the population in private households.

Disability–free life expectancy represents the difference between life expectancy and life expectancy with disability. The standard deviations of disability–free life expectancy estimates (and consequently the upper and lower limits of the confidence intervals associated with these estimates) are based on Colin Mathers’ method^{9}. This method takes into account both the stochastic fluctuations in the observed death rates and the sampling variability of the activity limitation rates.

**Note(s):** The disability data for DFLE came from the 1996 Census of Population. Questions on disability in the Census of Population are generally used to capture the sample of post–censal Health and Activity Limitations Survey. Because of the decision not to conduct this survey in 1996, data on disability from the Census of population of 1996 were neither verified nor imputed. More precisely, no validation was undertaken to check the completeness or consistency of the data, and as a result, no corrections to the data were made. In addition, the data were not adjusted to account for population undercounts.

DFLE estimates will vary according to both the concepts from which they are based and the surveys from which the data are extracted.

DFLE (Volume 2001, No’s. 1 and 2): For these issues, disability was defined as “having any activity limitation or handicap”.

DFLE (Volume 2001, No. 3 and beyond): Disability is defined as “having an activity limitation that affects activities at home, work or at school”. This differs from previous Health Indicators issues by excluding limitations that only affect activities other than home, work or school as well as respondents who stated that they had some form of handicap other than an activity limitation.

### 2.2.7 Disability–adjusted life expectancy (DALE)

Disability–adjusted life expectancy (DALE) is similar to DFLE, in that they are both measures of quality of life lived and both are based on mortality and disability data. However, DALE is an expectation of life weighted to account for four health states defined in terms of disability. These health states are, in order of greatest to least weight:

- (1) having no activity limitations;
- (2) having activity limitations in leisure time activities and/or transportation;
- (3) having activity limitations at work, home and/or school; and
- (4) institutionalization in a health care facility.

Specifically, state #1 has a weight of 1.0; state #2 has a weight of 0.8; state #3 has a weight of 0.65; and state #4 has a weight of 0.5. The sum of life expectancies of persons in a specific age group within a given geography, based on their health states, produces the value of DALEfor that specific age group.

The calculation of the confidence intervals for DALE is based on Colin Mathers’ method. Specifically, for any particular age group,

Where,

is the standard error,

*LE* state *n* denotes life expectancy for a specific health state.

### 2.2.8 Health–adjusted life expectancy (HALE)

Health-adjusted life expectancy is a more comprehensive indicator than that of life expectancy because it introduces the concept of quality of life. Health-adjusted life expectancy is the number of years in full health that an individual can expect to live given the current morbidity and mortality conditions. Health-adjusted life expectancy uses the Health Utility Index (HUI) to weigh years lived in good health higher than years lived in poor health. Thus, health-adjusted life expectancy is not only a measure of quantity of life but also a measure of quality of life.

For more details on concepts and methodological notes for Health–adjusted life expectancy, please contact Client Custom Services at (613) 951-1746, email hd-ds@statcan.gc.ca), Health Statistics Division.

### 2.2.9 Potential years of life lost

In this publication, death was considered premature if the person died before age 75. This is more reflective of life expectancies in recent years and is more reflective of international standards. Many previous Statistics Canada publications provide PYLL data based on death before age 70. Additionally, PYLL can be presented as an age–standardized rate or as a crude rate. As well, the denominator can be based on population aged 0 to 74 or for the total population. In this publication, the denominator is based on the former.

In this publication, a PYLL count was produced. The exact age of each person at time of death was subtracted from 75 to calculate individual years lost. The sum of all these values represents the total PYLL. The PYLL rate is PYLL per 100,000 population aged 0 to 74. The confidence intervals for each PYLL rate were produced by the Spiegelman method (refer to section 2.2.1).

This publication only presents PYLL rates based on the sum of all age groups. Thus, the rate is calculated as follows:

Where,

is the sum of years lost for ages 0 to 74 for the three years of data, and

is the population aged 0–74 for the three years of data.

To calculate the age–specific PYLL rates:

Where is the specific 5–year age group.

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