Monitoring Gender Equity in Health Using Gender-Sensitive Indicators: A Cross-National Study

Abstract

Background:

As gender is known to be a major determinant of health, monitoring gender equity in health systems remains a vital public health priority. Focusing on a low-income (Peru), middle-income (Colombia), and high-income (Canada) country in the Americas, this study aimed to (1) identify and select gender-sensitive health indicators and (2) assess the feasibility of measuring and comparing gender-sensitive health indicators among countries.

Methods:

Gender-sensitive health indicators were selected by a multidisciplinary group of experts from each country. The most recent gender-sensitive health measures corresponding to selected indicators were identified through electronic databases (CINAHL, PsycINFO, MEDLINE, Embase, LILACS, LIPECS, Latindex, and BIREME) and expert consultation. Data from population-based studies were analyzed when indicator information was unavailable from reports.

Results:

Twelve of the 17 selected gender-sensitive health indicators were feasible to measure in at least two countries, and 9 of these were comparable among all countries. Indicators that were available were not stratified or adjusted by age, education, marital status, or wealth. The largest between-country difference was maternal mortality, and the largest gender inequity was mortality from homicides.

Conclusions:

This study shows that gender inequities in health exist in all countries, regardless of income level. Economic development seemed to confer advantages in the availability of such indicators; however, this finding was not consistent and needs to be further explored. Future initiatives should include identifying health system factors and risk factors associated with disparities as well as assessing the cost-effectiveness of including the routine monitoring of gender inequities in health.

Introduction

It is well established that gender is a major determinant of health. Thus, gender inequities in health are a significant global public health concern in developing and developed countries.^1

–6 Gender equity in health refers to the elimination of avoidable differences between women and men, ensuring equal access to health resources for equal need, and enhancing resources for unequal need.^7,8 In contrast, gender equality refers to the aim of achieving equal health outcomes between women and men, which may not be possible because of inherent biological differences. It is vital to recognize that biological differences between men and women do not account for all gender discrepancies in health. Rather, gender inequalities in social and cultural norms, such as lower wages, reduced healthcare accessibility, and increased caregiving burden, are more likely to disadvantage women and serve to further exacerbate gender disparities in health.^9

–12 The consequences of these gender differences in power, freedom, and opportunities are often manifested as increases in physical and mental illnesses among women and may hinder their availability, acceptability, and accessibility to appropriate health services,^12

–16 Although gender disparities are more damaging to the health of millions of girls and women around the world, they are also harmful to boy's and men's health.⁷ For example, deaths due to violence or accidents are more common among men than women.⁹ The 1994 International Conference on Population and Development in Cairo and the 1995 Beijing Platform for Action of the Fourth World Conference on Women were monumental in advocating for gender mainstreaming in health research, health policies, and health programs cross-nationally to enhance gender equality and equity.^{7,9,17

–20} One method of measuring gender inequities in health is through the use of health indicators. These estimates measure public health performance and can be used within countries to develop policies, allocate resources, and monitor and evaluate inequities in health system performance. For example, the Organization of Economic Cooperation and Development (OECD) routinely measures and compares health system performance across countries using health indicators.^21,22 Incorporating gender into the regular measurement of health indicators can be achieved by using gender-sensitive health indicators.²³ These indicators are measures that capture gender-related changes in health in a population over time and target gender gaps within and between groups of women or men (e.g., by age, ethnicity, urbanicity, education, marital status, and wealth) over time cross-nationally, nationally, regionally, or locally to reduce inequities.^21,23
–25 As gender inequities exist in low-income and middle-income countries as well as in more affluent countries, the use of well-defined, operational, gender-sensitive health indicators measured in the same way across countries would allow for cross-national comparisons. In 2003, the Kobe Centre comprehensively reviewed health reports, identified and selected core gender-sensitive health indicators, and proposed that they should be routinely measured within a Health Information Framework.²⁶ Simultaneously, the Pan-American Health Organization (PAHO) also published operational definitions for >200 gender-sensitive indicators that could be measured and reported for countries in the Americas on a routine basis.^19,27

It is not known if current health reports can be used to measure gender inequities in health across countries. Investigators from a low-income (Peru), middle-income (Colombia), and high-income (Canada) country in the Americas developed a collaborative network to (1) identify and select core gender-sensitive health indicators, (2) assess the feasibility of measuring and comparing them between the countries, and (3) highlight challenges to cross-national comparisons of gender equity in health. These countries were selected for pragmatic reasons, as they represented a high-income, middle-income, and low-income country and the professional connections and resources were readily available to the investigators.

Materials and Methods

Identification and selection of gender-sensitive indicators

An environmental scan of peer-reviewed and nonpeer-reviewed (e.g., technical reports) published literature in Spanish and English was performed to identify reports with gender-sensitive health indicators beyond those identified by Lin et al.'s comprehensive review of gender-sensitive health indicators.^24,28 Electronic databases were searched (CINAHL, PsycINFO, MEDLINE, Embase, LILACS, LIPECS, Latindex, and BIREME) between 2003 and 2008 using combinations of the keywords: gender-sensitive, gender, gender equity, health, monitoring, indicator, performance measurement and quality, and health services. Other peer-reviewed and nonpeer-reviewed articles and reports were identified using Internet search engines, such as Google and Google scholar. The search identified 3168 potential citations and 123 reports on gender and health measures, and 22 of these were included because they reported gender-sensitive health indicators by including sex-specific, sex-disaggregated, or gender-sensitive indicators. Most of the 123 reports were excluded because they were background reports or advocacy pieces.

Conceptual framework

The 38 potential gender-sensitive health indicators were organized into three tiers according to the framework proposed by the WHO Kobe Centre²⁸:(1) health status (e.g., morbidity and mortality outcomes) (n = 10), (2) determinants of health (e.g., gender-related factors that influence health) (n = 20), and (3) health systems (e.g., gender-related accessibility, availability, efficiency, effectiveness, and safety factors) (n = 8). The indicators were then reviewed and independently ranked within each tier by an international expert panel consisting of epidemiologists, government representatives, policy experts, physicians, psychologists, and women's health researchers. The selection criteria included (1) equity, (2) importance, (3) relevance, (4) feasibility, (5) reliability, (6) validity, and (7) actionability. The top 50% of indicators (n = 17) were independently selected and consensually agreed upon by the expert panel, and 12 were feasible to measure in at least two of the three selected countries (Table 1). In addition, panel members were also asked to (1) identify and select new gender-sensitive health indicators that should be considered in future measurements or reports and (2) identify special groups where large gender inequities exist that should be prioritized for measurement.

Table 1.

Feasibility and Comparability of Obtaining Information on Selected Gender-Sensitive General Health Status Indicators for Peru, Colombia, and Canada

Indicator	Peru	Colombia	Canada
Tier I: Health status (n = 5)
Maternal mortality ratio (per 100,000 live births)	FC	FC	FC
Rate of reported domestic (intrafamily) violence, %	FC	FC	F
Rate of reported sexual violence (by relationship), %	F	F	F
Mortality from homicides intentionally inflicted by another person	FC	FC	FC
Infant mortality rate	—	—	—
Tier II: Determinants of health (n = 9)
Population living below poverty line, %	—	—	—
Annual literacy rates, %	FC	FC	FC
Women and men by years of education, %	FC	FC	FC
School dropout rate of adolescent women due to pregnancy, %	—	F	—
Female headed households, %	FC	FC	F
Population with access to adequate sanitation,%	—	—	—
Households with access to potable water in the house, %	—	—	—
Distribution of EAP employed according to employment category, %	FC	FC	FC
Women's participation in the sphere of political decisions by term, %	FC	FC	FC
Tier III: Health systems (n = 3)
Population covered by health insurance plan, %	FC	FC	FC
Births attended by skilled health professional, %	FC	FC	FC
Not seeking or deferring care because of cost	FC	FC	FC

Data were comparable if they came from the same report or, in the case where different reports were used, if they fulfilled the following criteria: the same question/answer was used, the same algorithm to measure the indicator was used, and collection of data occurred during the same time period.

EAP, economically active population; F, feasible but not comparable; FC, feasible and comparable;—, not feasible.

Data sources

Measurement of the selected gender-sensitive health indicators was based on data from reports or national population-based databases, subject to availability. First priority was given to reports that contained data on all or at least two of the included countries. Then, if a selected indicator was not found in any reports, it was measured using the most recent national databases/surveys available.

Data from reports

Data to measure gender-sensitive health indicators were obtained from reports and articles identified from a literature search using the electronic databases mentioned, consulting with investigators in each country, and using Internet search engines. If data on a particular indicator were defined (same numerator and denominator, same time period), analyzed (national databases, same adjustments), and reported (stratified by sex) in a similar way for at least two countries, it was extracted. Feasibility of measuring the indicator nationally and comparability of the indicator among all three countries were determined. Cross-national comparisons of the data were determined to be feasible when the data were harmonious. Criteria for harmony of data across three different reports included use of the same question/answer or indicator, use of the same algorithm to measure the indicator, same time period for data collection, and national representiveness.

Population-based databases

Three indicators that were available for Peru and Colombia were not available in Canada. Therefore, data from two national Canadian surveys were used to measure these three indicators. In Canada, Percent distribution of economically active population (EAP) employed according to employment categories was measured by the variable, worked at job in the past 12 months, from the 2003 Survey of Income and Labor Dynamics (SLID)²⁹; Percent of female headed households was measured by the variable, household type; and Not seeking or deferring care because of healthcare cost was measured by the variable, reason healthcare not received—cost?. The last two indicators used the Canadian Community Health Survey (CCHS), version 2.1, conducted in 2003. The CCHS is a cross-sectional, population-based, multistage survey of Canadian residents (n = 130,700) in private dwellings aged ≥12 years and had similar representativeness and exclusion criteria as the SLID.³⁰ (The definitions of all indicators used in each country were reported in a table that can be obtained from the authors.) All analyses were stratified by sex and conducted using Statistical Analysis Software version 9.1 (SAS, Cary, NC). PROC SURVEYMEANS was used because it takes into account the added variability within subgroups in a complex survey design. The analyses conducted in this study were approved by the University Health Network Research Ethics Board.

Results

Feasibility and comparability of measurement of gender equity

There were nine comparable indicators across all three countries; two were comparable only between Colombia and Peru; Rate of reported sexual violence was not comparable because of variations in definition and timeframe, and School dropout rate due to pregnancy was only measured in Colombia (Table 1) (Appendix: supplemental material available online at www.liebertonline.com). Although there were data on Infant mortality rate, Percentage of population living below poverty line, Percent of population with access to adequate sanitation, and Percent of households with access to potable water in the house, they were not sex disaggregated and were not considered feasible for measurement. Percent of female-headed households was comparable between Peru and Colombia but not with Canada, which measured Percent of female lone parent households.

Tier I: Health status indicators

Two of the three comparable health status indicators (Table 1) followed the economic gradient of the countries, with Peru (lowest-income country) having the highest annual maternal mortality ratio and rate of domestic violence, and Canada (highest-income country) showing the lowest estimates (Table 2). The largest gender inequity for mortality from homicides was reported for Colombia, followed by Peru, and the lowest was Canada (Table 2). Cross-national comparisons show that this indicator was approximately 12 and 15 times higher among Colombian women than Peruvian and Canadian women, respectively. Among Colombian men, it was 23 and 73 times higher than Peruvian and Canadian men, respectively (Table 2).

Table 2.

Selected Gender-Sensitive General Health Indicators in Peru, Colombia, and Canada

	Peru			Colombia			Canada
Indicator	F	M	Sex ratio (F:M)	F	M	Sex ratio (F:M)	F	M	Sex ratio (F:M)
Tier I: Health status
Maternal mortality ratio (per 100,000 live births)	185.0	N/A	N/A	77.8	N/A	N/A	6.9	N/A	N/A
Annual rate of reported domestic violence, %	42.3	—	—	39.0	—	—	7.0	6.0	1.2
Rate of reported sexual violence, %
12 month	3.3^a	—	—	—	—	—	3.5^c	—	—
Lifetime	9.8^a	—	—	11.5^b	—	—	—	—	—
Annual mortality from intentional homicides (per 100,000 population)	1.2	6.7	0.2	13.9	152.6	0.1	0.9	2.1	0.4
Tier II: Determinants of health
Annual literacy rates, %	88.1	95.8	0.9	93.3	93.0	1.0	99.0	99.0	1.0
Annual population by years of education, %
Primary	97.0	97.0	1.0	84.0	83.0	1.0	100.0	99.0	1.0
Secondary	85.8	92.0	0.9	68.5	62.1	1.1	104.9	105.7	1.0
Postsecondary	31.4	32.2	1.0	25.3	23.0	1.0	66.2	49.6	1.3
School dropout rate due to adolescent pregnancy, %	—	N/A	N/A	7.6	N/A	N/A	—	N/A	N/A
Economically active urban population, Total, %	54.9	74.3	0.7	55.2	77.7	0.7	71.4	73.8	1.0
Employers	2.7	7.4	0.4	3.3	7.1	0.5	—	—	—
Salary worker	35.3	54.9	0.6	46.6	51.5	0.9	88.1	81.8	1.1
Self-employed/unpaid family	50.4	36.6	1.4	39.1	41.1	1.0	11.9	18.3	0.7
Domestic service	11.0	0.5	22.0	11.0	0.3	36.7	—	—	—
Female headed households, %	22.0	N/A	N/A	32.0	N/A	N/A	7.3^d	N/A^d	N/A^d
Women's participation in political decisions, % by term
Senate	N/A	N/A	N/A	11.8	N/A	N/A	34.4	N/A	N/A
Congress	29.2	N/A	N/A	8.4	N/A	N/A	21.3	N/A	N/A
Tier III: Health systems
Population with health insurance plan, %	42.5	42.1	1.0	70.0	66.0	0.9	100.0	100.0	1.0
Births attended by skilled professional, %	71.1	N/A	N/A	95.7	N/A	N/A	100.0	N/A	N/A
Population deferring healthcare because of cost, %	53.3	52.7	1.0	34.1	31.1	1.1	1.5	1.1	1.4

Percentage of ever married women physically forced to have sexual relations against her will by her husband.

Percentage of ever married women ever sexually violated by their spouse.

Percentage of women reporting sexual assault by anyone.

Not comparable with other countries.

F, female; M, male; N/A, not applicable;—, missing data.

Tier II: Determinants of health indicators

Gender ratios for literacy rates and primary, secondary, and postsecondary education in all three countries were close to 1, suggesting that gender inequities in receiving basic education were few (Table 2). Lowest rates of literacy were observed among Peruvian girls (88%). In Canada, enrollment in postsecondary education had the largest gender inequity, with a gender ratio of 1.3 indicating that more women (66%) than men (50%) were pursuing higher education. Colombia had the lowest rates of secondary and postsecondary education of the three countries at 62%–69% and 23%–25%, respectively.

For the EAP, gender inequities were highest in Peru and Colombia, whereas no gender inequities were observed among this group in Canada (Table 2). A higher proportion of men (74%–78%) were economically active in Peru and Colombia compared to women (55%), with more women participating in unpaid/self-employment and domestic services in Peru and Colombia compared to Canada. More male than female salaried workers were observed in Peru, whereas salaried men and women had similar distributions in Colombia and Canada. Percentage of female-headed households was greater in Colombia than Peru (32% vs. 22%) and was not comparable with Canada. Finally, the percentage of women's participation in political decisions in Congress was approximately 3.5 and 1.4 times higher in Peru than in Colombia and Canada, respectively (Table 2).

Tier III: Health systems indicators

Almost all gender ratios for the three indicators within this tier were close to 1 for all countries, showing few gender inequities among most of the measured health system indicators (Table 2). However, some discrepancies still exist. Canadian women deferred healthcare due to cost 1.4 times more often than their male counterparts despite a universal healthcare system. Overall, indicator estimates again followed the economic gradient across the countries: Peru reported the lowest estimates for the three indicators for men and women, followed by Colombia, then Canada (Table 2). Less than half the Peruvian population had a health insurance plan compared to 66%–70% of Colombians and 100% of Canadians. Similarly, 71% of births were attended by skilled professionals in Peru compared to 96% and 100% in Colombian and Canada, respectively.

New gender-sensitive health indicator development and special populations

The panel identified and consensually agreed on eight new gender-sensitive health indicators that could be further developed (Table 3). The indicators were chosen and ranked in terms of importance to women's health issues. Most indicators (n = 7) were not sex specific and were meant to be measured as sex-disaggregated indicators. One indicator was sex-specific: Proportion of women with access to prenatal care.

Table 3.

Potential Areas for New Gender-Sensitive Indicator Development

Ranking	Potential new indicator
1	Proportion physically disabled, by sex
2	Proportion of population with anemia, by sex
3	Proportion of women with access to prenatal care
4	Prevalence of sexually transmitted diseases, by sex
5	Percent of population hospitalized in last 12 months, by sex
6	Proportion of workplace sexual harassment/abuse
7	Percent of unemployment, by sex
8	Proportion of children with preschool education, by sex

There were six special populations identified as a priority to measure gender inequities in health. Ranked in order from most important to least important they were (1) immigrants and internally displaced and external refugees, (2) single-parent families, (3) indigenous populations, (4) disabled populations, (5) street children, runaways, and homeless, (6) regular (militia and police) and irregular (insurgents, child soldiers) armed groups. There were no data available by sex across these groups in at least two countries; therefore, no indicators are reported for these special groups

Discussion

Most selected gender-sensitive health indicators were feasible to measure and compare from existing reports for Peru, Colombia, and Canada. Four indicators were not available as sex-disaggregated indicators (infant mortality rate, percentage living below poverty line, accessibility to adequate sanitation, and potable water), and none were reported by age, ethnicity, urbanicity, education, marital status, and wealth. These findings are consistent with reports showing few to no gender analyses for most indicators and a lack of sex disaggregation for health indicators included in international reports.²⁴ The results also identify potential opportunities for nations to collaborate and learn from one another; for example, one indicator, annual school dropout rate due to pregnancy, from Colombia, appears to be a useful indicator to include in future data collection in other countries.

Routine reporting of a complete set of core gender-sensitive health indicators is vital to assessing how gender contributes to poor health outcomes. Priority should be given to providing sex-disaggregated data for the unavailable indicators and measuring available indicators routinely over time. Several of the unavailable indicators, such as Population living below the poverty line and Access to adequate sanitation and potable water, may help reduce avoidable gender disparities in health system processes by highlighting opportunities for improvement, such as improving and monitoring basic needs for women and children in the three countries by creating action programs targeted toward women. As a second priority, future researchers may want to further explore how indicators change over time, as routine assessment of these indicators would enable the identification of trend. For example, a research question that is of interest and could have policy implications could be: Does having a higher proportion of women participating in political decision making influence the health of women in a population as measured by any of the indicators in Tier I? According to our study, such research could be explored further and be of particular interest in Peru.

The selected core gender-sensitive health indicators may be intrinsically linked to one another, and these linkages should be further explored within countries. For example, the largest gender inequity was observed for mortality from homicides, which was higher for men than women in each country, yet the estimates were higher for both sexes in Colombia compared to Peru and Canada, which was consistent with previous reports.³¹ This increase in male mortality may impact families by increasing the number of female-headed households and forcing younger women to work at a younger age or in informal employment to contribute to their household. These impacts may explain other indicators within Colombia, such as lower levels of higher education among men and women, and explain the higher proportion of female-headed households in Colombia compared to Peru, two similar countries from a sociocultural perspective. A strategic action plan targeting the reduction of one gender-sensitive indicator may reduce or increase the gender inequity of another indicator; therefore, these within-country links need to be further explored and identified.

Cross-national comparisons of gender-sensitive indicators may highlight learning opportunities and improvements in health policies across countries. Such between-country comparisons could be useful for health policymakers and public health providers. The largest between-country difference was observed with maternal mortality. Peru has a rate that is 27 times higher than Canada's and twice the rate of Colombia's maternal mortality rate. It may be advantageous for Peruvian policymakers and health providers to examine the Colombian and Canadian maternal health systems with the aim of assessing how their maternal health system can be reformed. Similarly, another between-country difference was the proportion of women participating in political decision making. The lowest-income country, Peru, had the highest estimate relative to the higher-income countries, Colombia and Canada. It may be useful for policymakers in Canada and Colombia to examine what factors or action enabled Peruvians to take these roles and apply such changes to their own countries. Caution must be exercised with such comparisons, however, as considerable between-country variability exists in other factors that were unmeasured and may affect gender equity in health, such as population age distribution, language, culture, religion, ecology, history, economics, or policies. There is potential to make such comparisons, but data need to be measured and collected in the same way to ensure harmonization, indicators must be standardized by age, and data need to be collected and analyzed to account for variability in contextual factors (country and regional level). Future studies should attempt to measure and compare harmonized gender-sensitive health indicators between countries.

This study's limiting factors included data availability and collection methods. Data were not always collected in the same way or within a similar time period. However, efforts were made to compensate for these limitations. The investigators carefully examined indicator definitions, sources of data, and quality of the reports and prioritized reports that used similar data sources, methodology, and analysis and came from sources that extensively documented their methodology, such as the OECD, Demographic and Health Surveys, World Health Organization (WHO), or (PAHO).

To our knowledge, this is the first study to report the feasibility of measuring and comparing gender-sensitive health indicators cross-nationally in the Americas using reports currently generated on a routine basis. Aside from documenting these results, this study highlighted a number of challenges to cross-national comparisons of gender equity. Indicators were not reported for particular subgroups, such as by age and ethnicity or high-risk groups, and data were often not reported according to factors that influence gender and health, such as education and wealth. Future researchers and policymakers should focus on measuring equity in these groups and conducting qualitative studies that may identify particular needs of such high-risk groups as those identified in this study.

Conclusions

Measuring a core set of gender-sensitive indicators could assist policymakers and program planners to identify communities at high risk, assess attribution of gender roles to poor health outcomes, reduce avoidable gender disparities in health system processes, highlight opportunities for improvement, and provide evidence for public health action. Future international studies should attempt to measure and compare harmonized gender-sensitive health indicators between countries by including health-related factors and determinants for the general and special populations. Further, indicators should be linked with public health strategies and action plans, and routine measurement of the indicators should be developed to monitor gender equity in health over time.

Footnotes

Acknowledgments

This study was funded by a Canadian Institute of Health Research grant NIG-79774 and by the Public Health Agency of Canada.

Disclosure Statement

No competing financial interests exist.

Appendix

Data Extraction from Reports Used as Reference for Indicators

Indicator	Country	Numerator	Denominator	Calculation	Database used in each report
Tier I: Health status
Maternal mortality ratio (100,000 live births)	Peru Colombia Canada	Number of reported maternal deaths per year	Number of live births in that same year, expressed by 100,000 live births	(Numerator/denominator) × 100,000	Pan American Health Organization, Basic Indicator Data Base
Rate of reported domestic (intrafamily) violence	Peru Colombia	Number of ever-married women aged 15–49 who have experienced violence by husband/partner ever	Total of ever-married women in that age group	(Numerator/denominator) × 100	Demographic and Health Survey, 2000
	Canada	Number of women or men who have experienced spousal violence in past 5 years	Total women or men in population	(Numerator/denominator) × 100	General Social Survey, Cycle 18: Victimization, 2004. Statistics Canada
Rate of reported sexual violence (by relationship)	Peru	Number of women aged 15–49 reporting different acts of marital sexual violence ever or in past 12 months	Total number of ever-married women aged 15–49	(Numerator/denominator) × 100	Demographic and health Survey, 2000
	Colombia	Number of women by age group reporting sexual violence ever	Total number of ever-married women by age group	(Numerator/denominator) × 100	Encuesta Nacional de Demografia y Salud de 2005
	Canada	Number of women or men who report sexual assault in past 12 months	Total number of women or men in population	(Numerator/denominator) × 100	General Social Survey, Cycle 18: Victimization, 2004. Statistics Canada
Mortality from homicides intentionally inflicted by another person	PeruColombiaCanada	Estimated total number of deaths from homicide and injury inflicted and injury due to legal intervention or war operations in total population	Total number of this population, expressed per 100,000 population	(Numerator/denominator) x 100,000	Pan American Health Organization, Health Statistics from the Americas
Tier II: Determinants of health
Literacy rates (annual)	PeruColombiaCanada	Annual Number of literate persons	Total population of given country	(Numerator/denominator) × 100	United Nations. UNESCO Institute for Statistics. Literacy and Non Formal Education Sector
Percent of women and men by years of education	Peru	1. Number of females enrolled in primary education	1. Total number of males and females enrolled in primary education	1. (Numerator/denominator) × 100	United Nations Educational, Scientific and Cultural Organization. UNESCO 2008 Education Statistical Tables
	Colombia	2. Number of students enrolled in secondary school by sex	2. Population in applicable age group for country (by sex)	2. (Numerator/denominator) × 100
	Canada	3. Number of students enrolled in any type of postsecondary education by sex	3. Population in the applicable age group for country (by sex)	3. Numerator/denominator) × 100
Percent of female-headed households	PeruColombia	Number of households headed by women within each poverty level	Total number of households	(Numerator/denominator) × 100	Economic Commission for Latin America and the Caribbean
	Canada	Number of female lone parent households	Total number of households	(Numerator/denominator) × 100	Statistics Canada. Canadian Community Health Survey Version 2.1, 2003
Percent distribution of economically active population employed according to employment categories	PeruColombia	Number of employed individuals aged 15 and over in each one of the employment categories	Number of females or males aged 15 or over employed in population	(Numerator/denominator) × 100	DANE National Statistics DepartmentINEI National Census 2007
	Canada	Number of employed individuals in each of the employment categories	Total population	(Numerator/denominator) × 100	Statistics Canada. Survey of Labor and Income Dynamics, 2003
Dropout rate of adolescent women due to pregnancy	Peru	Not feasible	Not feasible	Not feasible	Not feasible
	Colombia	Women who dropped out of school due to pregnancy (for each education level)	Total women in school (for each education level)	(Numerator/denominator) × 100	Encuesta Nacional de Demografia y Salud 2005
	Canada	Not feasible	Not feasible	Not feasible	Not feasible
Women's participation in sphere of political decisions, by term	PeruColombiaCanada	Number of women in congress/senate/house of commons	Total number of individuals in congress/senate/house of commons	(Numerator/denominator) × 100	Interparliamentary union PARLINE database, 2007
Tier III: Health systems

Indicator	Country	Numerator	Denominator	Calculation	Database used in each report
Percentage of population covered by health insurance	Peru	Percentage of population covered by health system (public or private)	Total population	(Numerator/denominator) × 100	INEI National Census 2007
	Colombia	Percentage of population affiliated with the Sistema de Seguridad Social en Salud de Colombia, by sex	Total population, by sex	(Numerator/denominator) × 100	Encuesta Nacional de Demografia y Salud, 2005
	Canada	Medicare: universal publicly funded health insurance system			Canada Health Act, 1984
Percentage of births attended by skilled health professional	PeruColombiaCanada	Number of deliveries assisted by trained personnel in specific year	Total number of births in that same year	(Numerator/denominator) × 100	Pan American Health Organization, 2007 Basic Indicator Data Base
Not seeking or deferring care because of healthcare cost	PeruColombiaCanada	Individuals not seeking care due to cost, by sex	Total population	(Numerator/denominator) × 100	Encuesta Nacional de Hogares, 2000Encuesta Nacional de Demografia y Salud, 2005Statistics Canada. Canadian Community Health Survey, Cycle 2.1. 2003

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