Health Outcomes and Impact

 

The health outcomes and impact collection includes results-based financing indicators that monitor change in the health status of an individual, group or population, which is attributable to a planned intervention or series of interventions, regardless of whether such an intervention was intended to change health status. This collection includes measures of morbidity and mortality.  The RBF Indicator Compendium has three other collections: structural, quality of services, and service use and intervention coverage. 

Hospital admission rates

Definition:

Number (and mean) of hospital admissions per person per year.

Numerator:

Number of hospital admissions per year.

Denominator:

Total population (of the same geographical area).

Disaggregation:

Age, place of residence, sex.

Data Requirements:

Requires complete and reliable recording and reporting of the number of hospital admissions visits by public and private facilities. Recall in population surveys can also be used.

Data Sources:

Facility reports

Facility assessment

Record review

Routine facility information systems

Population-based health surveys

Purpose:

This indicator can be used to inform on inpatient care and utilizationHospital records are the basis for statistics on performance related to inpatient activities, including the numbers of beds, admissions, discharges, deaths and the duration of stay. Two related indicators are (1) Average length of stay: an indicator of quality and efficiency of health services; and (2) Bed occupancy rate: an indicator of efficiency of services.

Issue(s):

As with other routine facility reporting, problems arise from incomplete and late reporting as well as from biases resulting from differences in population use of services. Hospital admission rates have the potential to vary considerably, with country practices and changes in admission or intervention policies. Very low rates tend to indicate that services are not available, but otherwise the statistics are difficult to interpret.

References:

World Health Organization (WHO). 2015 Global Reference List of 100 Core Health Indicators.; 2015. http://apps.who.int/iris/bitstream/10665/173589/1/WHO_HIS_HSI_2015.3_eng.pdf

World Health Organization. Monitoring, Evaluation, and Review of National Health Strategies: A Country-Led Platform for Information and Accountability.; 2011. http://www.who.int/healthinfo/country_monitoring_evaluation/1085_IER_131011_web.pdf

World Health Organization (WHO). Monitoring the Building Blocks of Health Systems: A Handbook of Indicators and Their Measurement Strategies.; 2010. http://www.who.int/healthinfo/systems/WHO_MBHSS_2010_full_web.pdf

Cesarean sections as a percent of all births

Definition:

The percent of pregnant women who have a cesarean section (C-section) in a specific geographical area and reference period.

This indicator is calculated as:

# of C-sections performed x 100
____________________________
# of live births

 

Data Requirements:

The number of C-sections performed in a defined population during a reference period; total number of live births in the same reference period.

Data Sources:

Numerator: clinical registries for data in a given geographical area on the number of C-sections performed; estimates of the number of births in that area; and population- based surveys for self-reported C-sections only.

Denominator: all live births during the reference period. Where data on the numbers of live births are absent, evaluators can calculate total estimated live births using census data for the total population and crude birth rates in a specified area. Total expected births = population x crude birth rate.

Household demographic surveys often produce national and disaggregated estimates of the self-reported C-section rate.

Purpose:

This indicator demonstrates the extent to which a particular life-saving obstetric service is being performed in emergency obstetric care facilities. It reflects the accessibility and utilization of services as well as the functioning of the health service system. The appropriate use of a C-section leads to a decrease in maternal mortality and morbidity, as well as a decrease in perinatal morbidity and mortality. While cesarean sections may be performed solely for the health of the fetus or newborn, in developing countries the vast majority relate to maternal indications.

Many of the major pre- and intrapartum causes of maternal mortality and morbidity require the use of this procedure to save the woman's life or to prevent serious morbidity.

Of all the procedures used to treat the major obstetric complications, C-sections may be the easiest to study because record-keeping for C-sections is more reliable than that for other procedures or obstetric complications (MotherCare, 2000b; UNICEF, WHO, UNFPA, 1997). However, it is critical that evaluators include information for all facilities performing C-sections in the area under study in the numerator.

Changes in the ability of the health care system to provide C-sections can have an impact within six to nine months.

UNICEF/WHO/UNFPA recommend a C-section rate between 5 and 15 percent of all births, based on estimates from a variety of sources. Rates less than 5 percent may indicate inadequate availability and/or access to emergency obstetric care. Rates above 15 percent suggest overuse of the procedure for non-emergency reasons. Excessive use unnecessarily exposes women to anesthesia and surgery with their concomitant risks. Moreover, it drains scarce health-care resources. Most of the countries with excessively high C-section rates are also highly litigious societies such as the United States, where nearly one in three babies is delivered by C-section (NY Times, 2010). However, some private clinics in Brazil have a c-section rate of over 90% (Ribeiro et al., 2007).

Disaggregation of the rate allows one to evaluate access to the procedure. Rates are often inconsistent between urban and rural environments, public or private sectors, different payment schemes, or across regions. Thus, sub-national estimates are encouraged (Maine, McCarthy, and Ward, 1992).

Crude birth rates produce estimates of live births only, whereas some C-sections are performed on pregnancies that result in stillbirths. If the number of C-sections performed for stillbirths is low, the use of live births should be acceptable as the denominator.

An alternative indicator, the proportion of facility deliveries that are C-sections, will vary by the case mix of patients and will be biased by referral patterns of women with complications requiring the procedure. Specifying an appropriate range of target percentages within a facility is impractical.

Issue(s):

The procedure of C-section usually occurs at the end of a complex series of events, possibly including pre-existing and pregnancy-specific medical factors, identification of complications, transportation to health care facilities and availability of necessary technology. When using this indicator, managers and evaluators may also want to employ more in-depth techniques, such as case audits, to investigate what clinical indicators are being used for C-section and if the appropriate women are receiving this service. By itself, the indicator reveals nothing about the appropriateness of the procedure.

References:

"Caesarean Births Are at a High in U.S.".  The New York Times.  March 23, 2010.

Ribeiro V., Figueiredo F., Silva A., Bettiol H., Batista R., Coimbra L., Lamy Z., and Barbieri M. Why are the rates of cesarian section in Brazil higher in more developed cities than in less developed ones?  Brazilian Journal of Medical and Biological Research (2007) 40: 1211-1220.

Intrapartum or fresh stillbirth rate

Definition:

Number of stillbirths per 1000 births (live and stillbirths).

Stillbirths can occur antepartum or intrapartum. In many cases, stillbirths reflect inadequacies in antenatal care coverage or in intrapartum care. For purposes of international comparison, stillbirths are defined as third trimester fetal deaths (≥ 1000 g or ≥28 weeks).

Numerator:

Number of stillborn infants.

Denominator:

Number of births (dead or alive).

Disaggregation:

Fresh/macerated.

See also: Intrapartum and very early neonatal death rate and Perinatal mortality rate (PMR)

Data Requirements:

Data from civil registration: the number of stillbirths divided by the number of total births.

Data from surveys: the number of pregnancy losses during or after the seventh month of pregnancy for the 5 years preceding the interview, divided by the sum of live births and late pregnancy losses in the same time period.

Data from administrative reporting systems/registries: the number of stillbirths divided by the number of total births.

Data from health facilities: the number of stillbirths divided by the number of total births documented in the facility.

For data from countries with civil registration and good coverage, data meeting definition criteria of greater than or equal to 1000 g or 28 completed weeks gestation are taken directly from civil registration without adjustment. For other countries, stillbirth rates are estimated with a regression model.

Data Sources:

Civil registration and vital statistics system, population-based surveys.

Administrative reporting systems, health facility assessments, admission and labor ward registry, partographs, and special studies.

Purpose:

Ideally, intrapartum stillbirth serves as an indicator of the quality of intrapartum care and should include all fetuses weighing 1000 g or more or after 28 weeks of gestation. The indicator is based on the WHO recommended birthweight cut-off for international comparison since setting a birthweight cut-off of 1500 or 2000 g would negatively affect recording of data on stillbirths. 

Issue(s):

Few countries have sufficiently developed vital registration systems that can provide valid and reliable information on all births and deaths in the community. Health information systems can only provide information on births and deaths in facilities and, in most settings, are not well developed.Furthermore, decision-making for low birthweight and short gestational age categories depends on the availability of resources: personnel are reluctant to intervene for the sake of the fetus when resources are limited. 

References:

World Health Organization (WHO). 2015 Global Reference List of 100 Core Health Indicators.; 2015. http://apps.who.int/iris/bitstream/10665/173589/1/WHO_HIS_HSI_2015.3_eng.pdf

World Health Organization (WHO). Consultation on Improving Measurement of the Quality of Maternal, Newborn and Child Care in Health Facilities.; 2013. http://apps.who.int/iris/bitstream/10665/128206/1/9789241507417_eng.pdf

 

Further information and related links

Every newborn: an action plan to end preventable deaths. Geneva: World Health Organization; 2014 (Retrieved from http://www.everynewborn.org/Documents/Full-action-plan-EN.pdf).

World health statistics 2014. Geneva: World Health Organization; 2014 (Retrieved from http://apps.who.int/iris/bitstream/10665/112738/1/9789240692671_eng.pdf?ua=1).


Perioperative mortality rate

Definition:

All-cause death rate prior to discharge among patients having one or more procedures in an operating theatre during the relevant admission.

Numerator:

Number of deaths among patients having one or more procedures in an operating theatre during the relevant admission.

Denominator:

Total number of surgical procedures.

Disaggregation:

By region/health facility, age, emergency and elective surgery.

Also: surgical volume per 100 000 population

Data Requirements:

Requires a register of operations (major surgery only) in hospitals and of survival status at discharge after operation. The indicator also generates information on the surgical volume (procedures performed in an operating theatre per 100 000 population per year). This is a rough indicator of access.

Data Sources:

Hospital registers linked to routine facility information systems.

Purpose:

This indicator is an important outcome measure of quality and safety of care.

References:

World Health Organization (WHO). 2015 Global Reference List of 100 Core Health Indicators.; 2015. http://apps.who.int/iris/bitstream/10665/173589/1/WHO_HIS_HSI_2015.3_eng.pdf

 

Further information and related links

Organisation for Economic Co-operation and Development. Health at a Glance 2013: OECD Indicators, Paris: OECD Publishing; 2013 (Retrieved from http://dx.doi.org/10.1787/health_glance-2013-en)


Institutional maternal mortality ratio

Definition:

Number of maternal deaths among 100 000 deliveries in health facilities/institutions.

Numerator:

Number of maternal deaths in institutions.

Denominator:

Total number of deliveries in institutions.

Disaggregation:

Age, cause of death, geographic location, parity.

Data Requirements:

Labour ward registers, emergency admission registers, specialist ward registers.

Regular quality control for completeness, assessment and misclassification.

Number of maternal deaths among 100 000 deliveries in health facilities/institutions.

See also: Maternal mortality ratio (MMR)

Data Sources:

Routine facility information systems, maternal deaths surveillance and response systems.

Purpose:

This indicator is an important outcome measure of quality and safety of care.

References:

World Health Organization (WHO). 2015 Global Reference List of 100 Core Health Indicators.; 2015. http://apps.who.int/iris/bitstream/10665/173589/1/WHO_HIS_HSI_2015.3_eng.pdf

 

Further information and related links

Countdown to 2015 decade report (2000−2010): taking stock of maternal, newborn and child survival. Geneva and New York (NY): World Health Organization/United Nations Children’s Fund; 2010 (Retrieved from http://www.countdown2015mnch.org/reports-and-articles/previous-reports/2010-decadereport).

Indicators for monitoring the Millennium Development Goals: definitions, rationale, concepts and sources. New York (NY): United Nations; 2012 (Retrieved from http://mdgs.un.org/unsd/mi/wiki/MainPage.ashx).

Keeping promises, measuring results. Commission on information and accountability for Women’s and Children’s Health. Geneva: World Health Organization; 2011 (Retrieved from http://www.who.int/topics/millennium_development_goals/accountability_commission/Commission_Report_advance_copy.pdf).

Next generation indicators reference guide: planning and reporting. Version 1.2. Washington (DC): The President’s Emergency Plan for AIDS Relief; 2013 (Retrieved from http://www.pepfar.gov/documents/organization/206097.pdf).

The UNFPA Strategic Plan, 2014−2017. Report of the Executive Director. New York (NY): United Nations Population Fund; 2013.

World Health Assembly governing body documentation: official records. Geneva: World Health Organization (Retrieved from http://apps.who.int/gb/or/).

World health statistics 2014. Geneva: World Health Organization; 2014 (Retrieved from http://apps.who.int/iris/bitstream/10665/112738/1/9789240692671_eng.pdf?ua=1).

Facility neonatal mortality rate

Definition:

The percent of neonates (children within the first 28 completed days of life) who die in the facility, in a specific year or period.

Neonatal deaths (deaths among live births during the first 28 completed days of life) may be subdivided into early neonatal deaths, occurring during the first 7 days of life, and late neonatal deaths, occurring after the 7th day but before the 28th completed day of life.

Numerator:

Number of children who died during the first 28 days of life.

Denominator:

Total number of live births in the health facility.

Disaggregation:

Age in days/weeks, birth weight (i.e. >4000 g, 2500–3999 g, 2000–2499 g, 1500–1999 g, <1500 g), place of residence, sex, socioeconomic status.

Data Requirements:

Data from routine health information systems: Routine health information systems may collect data for this indicator to obtain estimates of the facility neonatal mortality rate. Facility data are not recommended for estimating the neonatal mortality rate for the general population, because in many settings, many neonatal deaths and live
births occur outside the health system, which will cause substantial selection bias.

Data from household surveys: Calculations are based on full birth history, whereby women are asked for the date of birth of each of their children, whether each child is still alive and if not the age at death.

To ensure consistency with mortality rates in children younger than 5 years (under-five mortality rate) produced by the UN-IGME and to account for variation in survey-to-survey measurement errors, country data points for the under-five and neonatal mortality rates were rescaled for all years to match the latest time series estimates of the under-five mortality rate produced by UN-IGME. This rescaling assumes that the proportionate measurement error in neonatal and under-five mortality rates is equal for each data point.

The following multilevel statistical model was then applied to estimate neonatal mortality rates: log (neonatal mortality rate/1000) = α0 + β1*log(under-five mortality rate/1000) + β2*[log(under-five mortality rate/1000)] 2 ) with random effects parameters or both level and trend regression parameters, and random effects parameters influenced by the country itself.

For countries with high-quality civil registration data for neonatal deaths – defined as (i) 100% complete for adults and only civil registration data is used for child mortality, (ii) population greater than 800 000, (iii) and with at least three civil registration data points for the periods 1990−1994, 1995−1999, 2000−2004 and 2005 onwards – we used the same basic equation, but with random effects parameters for both level and trend regression parameters, and random effects parameters influenced by the country itself.

Predominant type of statistics: adjusted and predicted.

These neonatal rates are estimates, derived from the estimated UN-IGME neonatal rate infant population for World population prospects to calculate the live births; hence they are not necessarily the same as the official national statistics.

See also: Neonatal mortality rate (NMR)Perinatal mortality rate (PMR)  and Birth weight specific mortality rate (BWSMR)

Data Sources:

Hospital records and registers, outcome forms and death case reviews.

Household surveys, population census.

Purpose:

This is a key outcome indicator for newborn care and directly reflects prenatal, intrapartum, and neonatal care. When collected at the facility level, the indicator can be used to monitor the outcome of delivery and newborn care in health facilities. Reliable estimates for individual facilities can only be obtained for very large facilities if there are large numbers of deliveries and neonatal admissions.

Issue(s):

Comparisons of facility-based estimates of the neonatal mortality rate should be interpreted carefully because facility neonatal mortality rate is very sensitive to the case mix of deliveries and neonatal admissions. A higher rate in one facility may not suggest poorer quality of neonatal care in that facility because the neonatal mortality rate may rise or fall with changes in the case-mix. Also, improvements in prenatal and intrapartum care and advances in medical technology may increase the NMR because babies who may otherwise have been stillbirths may survive delivery only to die in the neonatal period.

For these reasons, it is reommended that evaluators break down facility-based estimates of the neonatal mortality rate by birth weight and by admission status (direct admission or transfer-in) as a proxy for case mix.

References:

World Health Organization (WHO). 2015 Global Reference List of 100 Core Health Indicators.; 2015. http://apps.who.int/iris/bitstream/10665/173589/1/WHO_HIS_HSI_2015.3_eng.pdf

World Health Organization (WHO). Consultation on Improving Measurement of the Quality of Maternal, Newborn and Child Care in Health Facilities.; 2013. http://apps.who.int/iris/bitstream/10665/128206/1/9789241507417_eng.pdf

Gage AJ, Ali D, Suzuki C. A Guide for Monitoring and Evaluating Child Health Programs. MEASURE Evaluation. Carolina Population Center, University of North Carolina at Chapel Hill.; 2005. http://www.coregroup.org/storage/documents/Workingpapers/ms-05-15.pdf

 

Further information and related links

Every newborn: an action plan to end preventable deaths. Geneva: World Health Organization; 2014 (Retrieved from http://www.everynewborn.org/Documents/Full-action-plan-EN.pdf).

Framework of actions for the follow-up to the Programme of Action of the International Conference on Population and Development beyond 2014. Report of the Secretary-General. New York (NY): United Nations; 2014 (Retrieved from https://www.unfpa.org/webdav/site/global/shared/documents/ICPD/Framework%20of%20action%20for%20the%20follow-up%20to%20the%20PoA%20of%20the%20ICPD.pdf).

World population prospects. New York (NY): United Nations; 2012 (Retrieved from http://esa.un.org/wpp/).

Fatality rate among hospitalized children <5 years of age

Definition:

Death rate of hospitalized children under 5 years.

Numerator:

Total number of deaths of hospitalized children under 5 years of age in a given period.

Denominator:

Total number of hospitalized children under 5 years for the same period.

Disaggregation:

Place of residence, age, sex, socioeconomic status.

Data Requirements:

WHO hospital quality assessment tool and SARA (service availability and readiness assessment)

Data Sources:

Hospital records and registers, outcome forms and death case reviews.

Purpose:

The hospital mortality rate is an indicator of hospital performance and quality of care.

Data to inform this indicator is readily available, as it is usually collected by health management information systems, and simply requires recording the number of deaths that occurred within a given period (the numerator) and the number of admissions or discharges during the same period (the denominator). When possible, it could be stratified by age, 0–1 month, 2–11 months and 12–59 months, with the option of including deaths occurring within 24 h of admission as a measure of how well emergency cases are managed.

References:

World Health Organization (WHO). 2015 Global Reference List of 100 Core Health Indicators.; 2015. http://apps.who.int/iris/bitstream/10665/173589/1/WHO_HIS_HSI_2015.3_eng.pdf

World Health Organization (WHO). Consultation on Improving Measurement of the Quality of Maternal, Newborn and Child Care in Health Facilities.; 2013. http://apps.who.int/iris/bitstream/10665/128206/1/9789241507417_eng.pdf

Case fatality rate for pneumonia

Definition:

Percent of child deaths in the facility due to pneumonia. 

Numerator:

The number of deaths of children aged 0-59 months due to pneumonia, in past 3 months.

Denominator:

Total number of children aged 0-59 months admitted for pneumonia in past 3 months.

Disaggregation:

Place of residence, age, sex, socioeconomic status.

Data Requirements:

The data for calculating this indicator can be derived from a review of clinic registers or patient charts or through periodic reporting of data on suspected cases of pneumonia (i.e. cases that meet the clinical case definition) from health facilities to districts, or from districts to the provincial/regional level.

The indicator divides the total number of all deaths from pneumonia during a specific period by the total number of cases of the disease in the same period, and multiplying the answer by 100.

Data Sources:

Facility records

Clinic registers

Patient charts

Surveillance reporting forms

Purpose:

Pneumonia is a major cause of child mortality.

The case fatality rate is a measure of severity of illness. The indicator aims at measuring progress towards the reduction of mortality from pneumonia at the health facility level. It expresses the likelihood that a child with pneumonia will live after entering the health facility. A case fatality rate helps to indicate whether a case is identified promptly, and any problems with case management once the disease has been diagnosed. It also helps to identify a more virulent, new, or drug-resistant pathogen and indicate poor quality of care or no medical care.

Once data on cases are being collected, this indicator is relatively easy to calculate. It can also respond to changes over a relatively short period, for example, 6-12 months. This indicator mostly helps service management at the level of each facility. 

Issue(s):

When interpreting this indicator, one should consider that it is sometimes difficult to distinguish deaths from a particular disease from deaths from other causes. Thus, the numerator can be as affected by errors in diagnosis, as by changes in classification.

The case fatality rate is also affected by the quality and promptness of medical care provided in the facility, the condition of the child upon arrival, and distance from the health facility. Case-fatality rates may be underestimates because of incomplete reporting of deaths. For example, a CFR under 5% for pneumonia may suggest an epidemic is just beginning, or “over-diagnosis,” or the fact that severely ill cases may not be reaching health facilities.

One way to disentangle the components of the CFR is to gather information on other indicators of the quality of care, such as the admission-to-treatment time interval. Another approach would be to gather information about the condition of the child at the time of admission. This could help disentangle the effect of patients’ condition from that of quality of care.

It may not be valid to compare case fatality rates between facilities, especially between health centers and hospitals, since children with serious illness could be referred to the hospital at the last moment, where they may die. This would lower the CFR at the health center and raise it at the hospital. Thus, interpretation requires comparing the CFR for a particular facility over time and not comparison between facilities. When using this indicator to monitor trends over time in the quality of care, one caveat worth mentioning is that data from a recent year may be incomplete if there is a significant lag time in reporting.

References:

World Health Organization (WHO). Consultation on Improving Measurement of the Quality of Maternal, Newborn and Child Care in Health Facilities.; 2013. http://apps.who.int/iris/bitstream/10665/128206/1/9789241507417_eng.pdf

World Health Organization. Nutrition Landscape Information System (NLIS). Country Profile Indicators: Interpretation Guide. Geneva, Switzerland; 2010.  http://apps.who.int/iris/bitstream/10665/44397/1/9789241599955_eng.pdf

Gage AJ, Ali D, Suzuki C. A Guide for Monitoring and Evaluating Child Health Programs. MEASURE Evaluation. Carolina Population Center, University of North Carolina at Chapel Hill.; 2005. http://www.coregroup.org/storage/documents/Workingpapers/ms-05-15.pdf

Case fatality rate for diarrhoea

Definition:

Percent of child deaths in the facility due to diarrhoea.

Numerator:

The number of deaths of children aged 0-59 months due to diarrhoea, in past 3 months.

Denominator:

Total number of children aged 0-59 months admitted for diarrhoea in past 3 months.

Disaggregation:

Place of residence, age, sex, socioeconomic status.

Data Requirements:

The data for calculating this indicator can be derived from a review of clinic registers or patient charts or through periodic reporting of data on suspected cases of diarrhoea (i.e. cases that meet the clinical case definition) from health facilities to districts, or from districts to the provincial/regional level.

The indicator divides the total number of all deaths from diarrhoea during a specific period by the total number of cases of the disease in the same period, and multiplying the answer by 100.

Data Sources:

Facility records

Clinic registers

Patient charts

Surveillance reporting forms

Purpose:

Diarrhoeal diseases remain one of the major causes of mortality among children under 5. The case fatality rate is a measure of severity of illness. The indicator aims at measuring progress towards the reduction of mortality from diarrhoeal diseases at the health facility level. It expresses the likelihood that a child with diarrhoea will live after entering the health facility. A case fatality rate helps to indicate whether a case is identified promptly, and any problems with case management once the disease has been diagnosed. It also helps to identify a more virulent, new, or drug-resistant pathogen and indicate poor quality of care or no medical care.

Once data on cases are being collected, this indicator is relatively easy to calculate. It can also respond to changes over a relatively short period, for example, 6-12 months. This indicator mostly helps service management at the level of each facility. 

Issue(s):

When interpreting this indicator, one should consider that it is sometimes difficult to distinguish deaths from a particular disease from deaths from other causes. Thus, the numerator can be as affected by errors in diagnosis, as by changes in classification.

The case fatality rate is also affected by the quality and promptness of medical care provided in the facility, the condition of the child upon arrival, and distance from the health facility. Case-fatality rates may be underestimates because of incomplete reporting of deaths. For example, a CFR under 5% for diarrhoea may suggest an epidemic is just beginning, or “over-diagnosis,” or the fact that severely ill cases may not be reaching health facilities.

One way to disentangle the components of the CFR is to gather information on other indicators of the quality of care, such as the admission-to-treatment time interval. Another approach would be to gather information about the condition of the child at the time of admission. This could help disentangle the effect of patients’ condition from that of quality of care.

It may not be valid to compare case fatality rates between facilities, especially between health centers and hospitals, since children with serious illness could be referred to the hospital at the last moment, where they may die. This would lower the CFR at the health center and raise it at the hospital. Thus, interpretation requires comparing the CFR for a particular facility over time and not comparison between facilities. When using this indicator to monitor trends over time in the quality of care, one caveat worth mentioning is that data from a recent year may be incomplete if there is a significant lag time in reporting.

References:

World Health Organization (WHO). Consultation on Improving Measurement of the Quality of Maternal, Newborn and Child Care in Health Facilities.; 2013. http://apps.who.int/iris/bitstream/10665/128206/1/9789241507417_eng.pdf

World Health Organization. Nutrition Landscape Information System (NLIS). Country Profile Indicators: Interpretation Guide. Geneva, Switzerland; 2010.  http://apps.who.int/iris/bitstream/10665/44397/1/9789241599955_eng.pdf

Gage AJ, Ali D, Suzuki C. A Guide for Monitoring and Evaluating Child Health Programs. MEASURE Evaluation. Carolina Population Center, University of North Carolina at Chapel Hill.; 2005. http://www.coregroup.org/storage/documents/Workingpapers/ms-05-15.pdf

Percent of infants born to HIV-infected mothers who are infected

Definition:

The estimated percentage of infants born to HIV-infected mothers who are also infected with HIV.  For further background and details on this indicator, see Gage et al. (2005); PEPFAR (2009) and UNAIDS (2009).

This indicator is calculated as:

(Number of infants born to HIV-infected mothers who are HIV-infected / Total estimated number of HIV-infected pregnant women) x 100

Data Requirements:

The indicator is calculated by taking the weighted average of the probabilities of mother-to-child transmission (MTCT) for pregnant women receiving and not receiving the various combination antiretroviral (ARV) prophylactic and treatment regimens, as well as the distribution of infant-feeding practices. Data for the numerator is drawn from national program records. Data required for the modeling can be collected through indicators for the number of women who received ARV prophylaxis to reduce MTCT (PEPFAR #P1.2.D) and for the percent of infants born to HIV-infected mothers who were tested within 12 months of birth (PEPFAR #C4.1.D). The data can be put into a computer-modeling program, such as Spectrum, commonly used for HIV projections. This will assess the impact of the programs to reduce MTCT by estimating the proportion of infants born to HIV-infected women. Other Excel-based spreadsheets, such as the “MTCT rate calculator“, (developed by the U.S. Centers for Disease Control and Prevention), also facilitate this estimation (PEPFAR, 2009). The indicator can be calculated annually, or more frequently, depending on a country’s monitoring needs.

Data Sources:

Spectrum, or other statistical modeling based on program coverage and efficacy studies and data.

Purpose:

This indicator is used to assess progress toward eliminating MTCT of HIV primarily through increased provision of ARV medicines and is included as a core indicator in the WHO/UNAIDS/UNICEF/The Global Fund “Three Interlinked Patient Monitoring Systems” (WHO et al., 2010). Programs to prevent mother-to-child transmission (PMTCT) are consistent with achieving Millennium Development Goals #6. to combat HIV/AIDS and #4. to reduce infant and child mortality. In the absence of preventative interventions, infants born to and breastfed by HIV-infected women have about a one-in-three chance of acquiring infection, which can happen during pregnancy, during labor and delivery, or after delivery through breastfeeding. The risk of MTCT can be reduced through the complementary approaches of ARV prophylaxis for the mother, with or without prophylaxis to the infant, implementation of safe delivery practices, and use of safe alternatives to breastfeeding. ARV prophylaxis followed by exclusive breastfeeding may also reduce the risk of vertical transmission when breastfeeding is limited to the first six months. In low-income countries, significant difficulties exist in implementing these strategies due to constraints in accessing, affording and using voluntary counseling and testing services, reproductive health, and maternal and child health services with integrated PMTCT interventions (UNAIDS, 2009). However, substantial reductions in mother-to-child transmission can be achieved through approaches such as short-course ARV prophylaxis.

This indicator allows assessment of the impact of PMTCT programs by estimating the percentage of infants who are HIV-infected out of those born to HIV-infected pregnant women. Where possible, countries should try to monitor PMTCT using actual data on the HIV status and survival of infants born to HIV-infected women during follow-up health care visits with these infants. For further technical guidance on interventions and indicators for PMTCT, see UNAIDS (2010).

Issue(s):

If an infant becomes positive, the indicator cannot distinguish between different pathways of infection (i.e., ARV treatment failure or infection during breastfeeding). Therefore, the indicator may underestimate the rates of MTCT in countries where long periods of breastfeeding are common (Gage et al., 2005). In countries where other forms of PMTCT (e.g. caesarean section) are widely practiced, the indicator will typically overestimate MTCT (PEPFAR, 2009). Consequently, trends in this indicator may not reflect overall trends in MTCT of HIV.  It is difficult to follow-up on mother-infant pairs, particularly at the national level, due to the time lag in reporting and the number and range of health facility sites.  In countries where data are available and confirmatory tests are being conducted, an effort should be made to monitor the percentage of HIV-infected infants born to HIV-infected mothers using actual data for the numerator and denominator.

References:

Gage A, Ali D, Suzuki C, 2005, A Guide for Measuring and Evaluating Child Health Programs, Chapel Hill, NC: MEASURE Evaluation. https://www.cpc.unc.edu/measure/publications/ms-05-15  

PEPFAR, 2009, The President’s Emergency Plan for AIDS Relief: Next Generation Indicators Reference Guide, Washington, DC: USAID/PEPFAR. http://www.pepfar.gov/documents/organization/81097.pdf

UNAIDS, 2009, Monitoring the Declaration of Commitment on HIV/AIDS: Guidelines on Construction of Core Indicators, Geneva: UNAIDS. http://data.unaids.org/pub/Manual/2009/JC1676_Core_Indicators_2009_en.pdf

UNAIDS, 2010, Prevention of Mother-To-Child Transmission of HIV (PMTCT): Technical Guidance Note for Global Fund HIV Proposals, Geneva: UNAIDS. http://www.who.int/hiv/pub/toolkits/PMTCT_Technical_guidance_GlobalFundR10_May2010.pdf

WHO, UNAIDS, UNICEF, The Global Fund, 2010, Three Interlinked Patient Monitoring Systems for HIV Care/ART, MCH/PMTCT and TB/HIV: Standardized Minimum Data Set and Illustrative Tools, Geneva: WHO. http://www.who.int/hiv/pub/imai/forms_booklet.pdf  

Incidence of low birth weight among newborns

Definition:

Percent of live births that weigh less than 2500 g out of the total of live births during the same period.

Numerator:

Number of live-born neonates with weight less than 2500 g at birth.

Denominator:

Number of live births.

Disaggregation:

Place of residence, preterm status, socioeconomic status.

Data Requirements:

Delivery registers (hospital management and information systems – HMIS). This method provides data on the incidence of low birth weight among newborns delivered in health institutions.

Household surveys which collect data on birth weight (recalled by mother) and relative size of the newborn at birth allow for an adjusted value even where many infants are not weighed at birth.

The relative size at birth and recalled birth-weight data are used to estimate incidence. UNICEF maintains a global database in which adjustments are made using survey data (mainly DHS and MICS) and administrative estimates are used where the percentage of weighed newborns is high.

See also: Percent of low birth-weight singleton live births, by parity

Data Sources:

Population-based health surveys and data from administrative/information systems.

Routine facility information systems

Purpose:

Low birth weight is the single most important predictor of new­born well-being and survival. 

At population level, the proportion of infants with a low birth weight is an indicator of a multifaceted public health problem that includes long-term maternal malnutrition, ill health, hard work and poor health care in pregnancy. Low birth weight is more common in developing than developed countries.

Low birth weight is caused by intrauterine growth restriction, prematurity or both. It contributes to a range of poor health outcomes: it is closely associated with fetal and neonatal mortality and morbidity, inhibited growth and cognitive development and chronic diseases later in life. Low-birth-weight infants are approximately 20 times more likely to die than heavier infants.

Issue(s):

Obtaining reliable estimates of low birth weight in the general population is difficult, particularly in many developing coun­tries, where the majority of births occur at home and babies are not weighed. The women surveyed may not know or recall the birth weights of all their children, or they may report them incorrectly.  Promoting childbirth in health facilities where infants are weighed at birth is likely to improve the quality of data on birth weight. 

Many household surveys collect data on birth weight, but since the weights reported are mainly from facility births, these data are also subject to selection bias. Some household surveys (such as the DHS) ask mothers to state whether their baby was smaller than average or very small; and at an aggregate level these data may be used to estimate incidence of LBW at a na­tional level.  

References:

World Health Organization (WHO). 2015 Global Reference List of 100 Core Health Indicators.; 2015. http://apps.who.int/iris/bitstream/10665/173589/1/WHO_HIS_HSI_2015.3_eng.pdf

World Health Organization. Monitoring, Evaluation, and Review of National Health Strategies: A Country-Led Platform for Information and Accountability.; 2011. http://www.who.int/healthinfo/country_monitoring_evaluation/1085_IER_131011_web.pdf

MEASURE Evaluation. FP and Reproductive Health Indicators Database — MEASURE Evaluation. http://www.cpc.unc.edu/measure/prh/rh_indicators/

World Health Organization. Nutrition Landscape Information System (NLIS). Country Profile Indicators: Interpretation Guide. Geneva, Switzerland; 2010. http://apps.who.int/iris/bitstream/10665/44397/1/9789241599955_eng.pdf

Gage AJ, Ali D, Suzuki C. A Guide for Monitoring and Evaluating Child Health Programs. MEASURE Evaluation. Carolina Population Center, University of North Carolina at Chapel Hill.; 2005. http://www.coregroup.org/storage/documents/Workingpapers/ms-05-15.pdf

 

Further information and related links

A draft framework for the global monitoring of the Comprehensive Implementation Plan on Maternal, Infant and Young Child Nutrition. Informal Consultation with Member States and UN Agencies on a Proposed Set of Indicators for the Global Monitoring Framework for Maternal, Infant and Young Child Nutrition, 30 September to 1 October 2013. Geneva: World Health Organization; 2013 (Retrieved from http://www.who.int/nutrition/events/2013_consultation_indicators_globalmonitoringframework_WHO_MIYCN.pdf).

Countdown to 2015 decade report (2000−2010): taking stock of maternal, newborn and child survival. Geneva and New York (NY): World Health Organization/United Nations Children’s Fund; 2010 (Retrieved from http://www.countdown2015mnch.org/reports-and-articles/previous-reports/2010-decadereport).

Organisation for Economic Co-operation and Development. Health at a Glance 2013: OECD Indicators, Paris: OECD Publishing; 2013 (Retrieved from http://dx.doi.org/10.1787/health_glance-2013-en).

Children under 5 years who are stunted

Definition:

Percent of stunted (moderate and severe) children aged 0–59 months (moderate = height-for-age below -2 standard deviations from the WHO Child Growth Standards median; severe = height-for-age below -3 standard deviations from the WHO Child Growth Standards median).

Numerator:

Number of children aged 0–59 months who are stunted.

Denominator:

Total number of children aged 0–59 months who were measured.

Disaggregation:

Age, place of residence, sex, socioeconomic status.

Data Requirements:

Percentage of children aged < 5 years stunted for age = (number of children aged 0–59 months whose z-score falls below -2 standard deviations from the median height-for-age of the WHO Child Growth Standards/total number of children aged 0–59 months who were measured) x 100.

Children’s weight and height are measured using standard equipment and methods (e.g. children younger than 24 months are measured lying down, while standing height is measured in children aged 24 months and older).

WHO maintains the Global Database on Child Growth and Malnutrition, which includes population-based surveys that fulfil a set of criteria. Data are checked for validity and consistency and raw data-sets are analysed according to a standard procedure to obtain comparable results. Prevalence below and above defined cut-off points for weight-for-age, height-for-age, weight-for-height and body mass index (BMI)-for-age in pre-school children are presented using z-scores based on the WHO Child Growth Standards.

Predominant type of statistics: adjusted.

Data Sources:

Population-based household surveys.

Population-based health surveys with nutrition modules, national surveillance systems.

Purpose:

This indicator is used to measure nutritional imbalance resulting in undernutrition (i.e. stunting). Child growth is internationally recognized as an important indicator of nutritional status and health in populations.

The percentage of children with a low height for age (stunting) reflects the cumulative effects of undernutrition and infections since and even before birth. This measure can therefore be interpreted as an indication of poor environmental conditions or long-term restriction of a child's growth potential.

Children who suffer from growth retardation as a result of poor diets or recurrent infections tend to be at greater risk for illness and death. Stunting is the result of long-term nutritional deprivation and often results in delayed mental development, poor school performance and reduced intellectual capacity. This in turn affects economic productivity at the national level. Women of short stature are at greater risk for obstetric complications because of a smaller pelvis. Small women are at greater risk of delivering an infant with low birth weight, contributing to the inter-generational cycle of malnutrition, as infants of low birth weight or retarded intrauterine growth tend be smaller as adults.

Stunting is unaffected by seasonal variation and thus provides a better indication of trends than the wasting indicator (low weight-for-height), since it reflects long-term outcomes, such as frequent and high disease burden, limited access to food supply, poor feeding practices, and/or low household socioeconomic status, in the target population. Because stunting in children reflects socioeconomic conditions that are not conducive to good health and nutrition, this indicator is often used to target development programs. A decrease in the prevalence of stunting at the population level is a long-term indicator that social development is benefiting the poor as well as the relatively wealthy. Information on stunting for individual children is also useful clinically as an aid to diagnosis. Stunting based on height-for-age can be used for evaluation purposes but it is not recommended for monitoring as it does not change in the short term, such as 6-12 months.

Issue(s):

The main limitation of this indicator is that length or height can be a difficult to obtain, thus leading to problems of validity. The most frequent problems in height measurement are inadequate
positioning of the child’s head and feet, a reading done in an oblique position, and not facing the reading point of the measuring board or height-measuring apparatus. If repeated measurements are different from each other, the measurements should be disregarded and the measuring should start again. Accuracy of measurement is achieved through good training and supervision.

References:

World Health Organization (WHO). 2015 Global Reference List of 100 Core Health Indicators.; 2015. http://apps.who.int/iris/bitstream/10665/173589/1/WHO_HIS_HSI_2015.3_eng.pdf

World Health Organization. Nutrition Landscape Information System (NLIS). Country Profile Indicators: Interpretation Guide. Geneva, Switzerland; 2010. http://apps.who.int/iris/bitstream/10665/44397/1/9789241599955_eng.pdf

WHO. WHO Global Database on Child Growth and Malnutrition. Department of Nutrition for Health and Development (NHD), Geneva, Switzerland. http://www.who.int/nutgrowthdb/en/

 Gage AJ, Ali D, Suzuki C. A Guide for Monitoring and Evaluating Child Health Programs. MEASURE Evaluation. Carolina Population Center, University of North Carolina at Chapel Hill.; 2005. http://www.coregroup.org/storage/documents/Workingpapers/ms-05-15.pdf


Further information and related links

A draft framework for the global monitoring of the Comprehensive Implementation Plan on Maternal, Infant and Young Child Nutrition. Informal Consultation with Member States and UN Agencies on a Proposed Set of Indicators for the Global Monitoring Framework for Maternal, Infant and Young Child Nutrition, 30 September to 1 October 2013. Geneva: World Health Organization; 2013 (Retrieved from http://www.who.int/nutrition/events/2013_consultation_indicators_globalmonitoringframework_WHO_MIYCN.pdf).

Countdown to 2015 decade report (2000−2010): taking stock of maternal, newborn and child survival. Geneva and New York (NY): World Health Organization/United Nations Children’s Fund; 2010 (Retrieved from http://www.countdown2015mnch.org/reports-and-articles/previous-reports/2010-decadereport).

Countdown to 2015. Monitoring maternal, newborn and child health: understanding key progress indicators. Geneva: World Health Organization; 2011 (Retrieved from http://apps.who.int/iris/bitstream/10665/44770/1/9789241502818_eng.pdf).

Decision WHA67(9). Maternal, infant and young child nutrition. In: Sixty-seventh World Health Assembly, Geneva, 19-24 May 2014. Resolutions and decisions, annexes. Geneva: World Health Organization; 2014 (Retrieved from http://apps.who.int/gb/ebwha/pdf_files/WHA67-REC1/A67_2014_REC1-en.pdf).

Document A67/15. Maternal, infant and young child nutrition. The Global Strategy and the Comprehensive Implementation Plan. Report by the Secretariat. Sixty-seventh World Health Assembly, Geneva, 19–24 May 2014. Geneva: World Health Organization; 2014 (Retrieved from http://apps.who.int/gb/ebwha/pdf_files/WHA67/A67_15-en.pdf).

Keeping promises, measuring results. Commission on information and accountability for Women’s and Children’s Health. Geneva: World Health Organization; 2011 (Retrieved from http://www.who.int/topics/millennium_development_goals/accountability_commission/Commission_Report_advance_copy.pdf).

Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. Geneva: World Health Organization; 1995 (WHO Technical Report Series, No. 854).

WHO child growth standards: Length/height-for-age, weight-for-age, weight-for-length, weight-for-height and body mass index-for-age: Methods and development. Geneva: World Health Organization; 2006 (Retrieved from http://www.who.int/childgrowth/standards/technical_report/en/).

World health statistics 2014. Geneva: World Health Organization; 2014 (Retrieved from http://apps.who.int/iris/bitstream/10665/112738/1/9789240692671_eng.pdf?ua=1).

Children under 5 years who are wasted

Definition:

Percent of wasted (moderate and severe) children aged 0–59 months (moderate = weight-for-height below -2 standard deviations of the WHO Child Growth Standards median; severe = weight-for-height below -3 standard deviations of the WHO Child Growth Standards median).

Numerator:

Number of children aged 0–59 months who are wasted.

Denominator:

Total number of children aged 0–59 months.

Disaggregation:

Age, place of residence, sex, socioeconomic status.

Data Requirements:

Percentage of children aged < 5 years wasted = (number of children aged 0–59 months whose z-score falls below -2 standard deviations from the median weight-for-height of the WHO Child Growth Standards/total number of children aged 0–59 months who were measured) x 100.

Children’s weight and height are measured using standard equipment and methods (e.g. children under 24 months are measured lying down, while standing height is measured in children aged 24 months and older.

WHO maintains the Global Database on Child Growth and Malnutrition, which includes population-based surveys that fulfil a set of criteria. Data are checked for validity and consistency and raw data sets are analysed according to a standard procedure to obtain comparable results. Prevalence below and above defined cut-off points for weight-for-age, height-for-age, weight-for-height and BMI-for-age, in pre-school children are presented using z-scores based on the WHO Child Growth Standards.

A detailed description of the methodology and procedures of the database – including data sources, criteria for inclusion, data quality control and database workflow – are described in a paper published in 2003 in the International Journal of Epidemiology (de Onis M, Blössner M).

Data Sources:

National nutrition surveys.

Population-based health surveys with nutrition modules, national surveillance systems.

Purpose:

This indicator is used to measure nutritional imbalance resulting in undernutrition (i.e. wasting). Child growth is internationally recognized as an important indicator of nutritional status and health in populations.

Weight-for-height is an index that reflects body weight relative to height. Low weight-for-height helps to identify children suffering from current or acute undernutrition or wasting. Wasting is the result of a weight falling significantly below the weight expected of a child of the same length or height. Wasting in children is a symptom of acute undernutrition, usually as a consequence of insufficient food intake or a high incidence of infectious diseases, especially diarrhoea. Wasting in turn impairs the functioning of the immune system and can lead to increased severity and duration of and susceptibility to infectious diseases and an increased risk for death.

In general, weight-for-length (in children under two years of age) or weight-for-height (in children over two years of age) is appropriate for examining short-term changes, such as seasonal changes in food supply or short-term nutritional stress brought about by illness.

This indicator is simple to calculate and is useful when exact ages are difficult to determine. Low weight-for-height can be used as a screening or targeting indicator, for example to identify infants/children who need supplementary or therapeutic food and/or treatment for diseases, particularly diarrhea. In emergency settings, weight-for-height is a useful indicator for screening and surveillance. In humanitarian assistance activities, wasting or thinness in children aged 6-59 months, combined with nutritional edema, is an indicator of acute malnutrition and should be used to reflect the overall severity of a crisis. Percentage of the reference median should be reported as well, as it is used as an entry criterion for feeding programs. 

Issue(s):

The main limitation of this indicator is that weight and height can be difficult to obtain, leading to problems of validity of measurement. The most frequent problems in height measurement are inadequate positioning of the child’s head and feet, a reading done in an oblique position, and not facing the reading point of the measuring board or height-measuring apparatus. If repeated measurements are different from each other, the measurements should be disregarded and the measuring should start again. Enumerator variability in weight measurement can be reduced through good training and supervision.

Because wasting in individual children and population groups can change rapidly, the indicator is responsive to short-term program influences. However, the indicator is also highly susceptible to seasonal variations in food availability so that weight-for-height is not recommended for evaluating change in anthropometric status in non-emergency situations.

References:

World Health Organization (WHO). 2015 Global Reference List of 100 Core Health Indicators.; 2015. http://apps.who.int/iris/bitstream/10665/173589/1/WHO_HIS_HSI_2015.3_eng.pdf

World Health Organization. Nutrition Landscape Information System (NLIS). Country Profile Indicators: Interpretation Guide. Geneva, Switzerland; 2010. http://apps.who.int/iris/bitstream/10665/44397/1/9789241599955_eng.pdf

WHO. WHO Global Database on Child Growth and Malnutrition. Department of Nutrition for Health and Development (NHD), Geneva, Switzerland. http://www.who.int/nutgrowthdb/en/

Gage AJ, Ali D, Suzuki C. A Guide for Monitoring and Evaluating Child Health Programs. MEASURE Evaluation. Carolina Population Center, University of North Carolina at Chapel Hill.; 2005. http://www.coregroup.org/storage/documents/Workingpapers/ms-05-15.pdf

 

Further information and related links

A draft framework for the global monitoring of the Comprehensive Implementation Plan on Maternal, Infant and Young Child Nutrition. Informal Consultation with Member States and UN Agencies on a Proposed Set of Indicators for the Global Monitoring Framework for Maternal, Infant and Young Child Nutrition, 30 September to 1 October 2013. Geneva: World Health Organization; 2013 (Retrieved from http://www.who.int/nutrition/events/2013_consultation_indicators_globalmonitoringframework_WHO_MIYCN.pdf).

Countdown to 2015 decade report (2000−2010): taking stock of maternal, newborn and child survival. Geneva and New York (NY): World Health Organization/United Nations Children’s Fund; 2010 (Retrieved from http://www.countdown2015mnch.org/reports-and-articles/previous-reports/2010-decadereport).

de Onis M, Blössner M. The World Health Organization Global Database on Child Growth and Malnutrition: methodology and applications. Int J Epidemiol 2003;32(4):518-26.

Decision WHA67(9). Maternal, infant and young child nutrition. In: Sixty-seventh World Health Assembly, Geneva, 19-24 May 2014. Resolutions and decisions, annexes. Geneva: World Health Organization; 2014 (Retrieved from http://apps.who.int/gb/ebwha/pdf_files/WHA67-REC1/A67_2014_REC1-en.pdf, page 62).

Document A67/15. Maternal, infant and young child nutrition. The Global Strategy and the Comprehensive Implementation Plan. Report by the Secretariat. Sixty-seventh World Health Assembly, Geneva, 19–24 May 2014. Geneva: World Health Organization; 2014 (Retrieved from http://apps.who.int/gb/ebwha/pdf_files/WHA67/A67_15-en.pdf).

Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. Geneva: World Health Organization; 1995 (WHO Technical Report Series, No. 854).

WHO child growth standards: Length/height-for-age, weight-for-age, weight-for-length, weight-for-height and body mass index-for-age: Methods and development. Geneva: World Health Organization; 2006 (Retrieved from http://www.who.int/childgrowth/standards/technical_report/en/).

World health statistics 2014. Geneva: World Health Organization; 2014 (Retrieved from http://apps.who.int/iris/bitstream/10665/112738/1/9789240692671_eng.pdf?ua=1).

Children aged under 5 years who are underweight

Definition:

Percent of children aged under 5 years whose weight-for-age is below -2 standard deviations of the WHO Child Growth Standards median.

Numerator:

Number of children aged 0–59 months who are underweight.

Denominator:

Total number of children aged 0–59 months who were measured.

Disaggregation:

Place of residence, age, sex, socioeconomic status.

Data Requirements:

WHO maintains the Global Database on Child Growth and Malnutrition, which includes population-based surveys that fulfil a set of criteria. Data are checked for validity and consistency and raw data-sets are analysed according to a standard procedure to obtain comparable results. Prevalence below and above defined cut-off points for weight-for-age, height-for-age, weight-for-height and body mass index (BMI)-for-age in pre-school children are presented using z-scores based on the WHO Child Growth Standards. Predominant type of statistics: adjusted.

Data Sources:

Population-based household surveys.

Population-based health surveys with nutrition modules, national surveillance systems.

Purpose:

Child growth is internationally recognized as an important indicator of nutritional status and health in populations. As weight is easy to measure, this is the indicator for which most data have been collected in the past. Evidence has shown that the mortality risk of children who are even mildly underweight is increased, and severely underweight children are at even greater risk. Thus, monitoring weight-for-age can help assess the contribution of growth promotion programs to mortality reduction. 

Weight-for-age reflects body mass relative to chronological age. Low weight-for-age identifies the condition of being light or underweight for a specific age and reflects the process of gaining insufficient weight relative to age or losing weight. Since weight-for-age is influenced by both the height of the child and by its weight, the indicator reflects both past (chronic) and/or present (acute) undernutrition. This indicator is also a measure of health and nutritional risk in a population.

Underweight, based on weight-for-age, is recommended as the indicator to assess changes in the magnitude of malnutrition over time.

Issue(s):

The percentage of children who have low weight for age (underweight) can reflect ‘wasting’ (i.e. low weight for height), indicating acute weight loss, ‘stunting’, or both. Thus, 'underweight' is a composite indicator and may therefore be difficult to interpret.

One of the major limitations of the indicator is the issue of the reliability of weight measurements. There may be some degree of variability between interviewers in performing the task of weighing. For weight, the largest acceptable difference between repeated measurements is 0.5 kg (Cogill, 2003). Enumerator variability in weight measurement can be reduced through extensive training. The validity of this indicator also depends on the accuracy of the weighing instruments and the caretaker’s ability to report the correct age of the child.

References:

World Health Organization (WHO). 2015 Global Reference List of 100 Core Health Indicators.; 2015. http://apps.who.int/iris/bitstream/10665/173589/1/WHO_HIS_HSI_2015.3_eng.pdf

World Health Organization. Nutrition Landscape Information System (NLIS). Country Profile Indicators: Interpretation Guide. Geneva, Switzerland; 2010. http://apps.who.int/iris/bitstream/10665/44397/1/9789241599955_eng.pdf

WHO. WHO Global Database on Child Growth and Malnutrition. Department of Nutrition for Health and Development (NHD), Geneva, Switzerland. http://www.who.int/nutgrowthdb/en/

Gage AJ, Ali D, Suzuki C. A Guide for Monitoring and Evaluating Child Health Programs. MEASURE Evaluation. Carolina Population Center, University of North Carolina at Chapel Hill.; 2005. http://www.coregroup.org/storage/documents/Workingpapers/ms-05-15.pdf

Children aged under 5 years who are overweight

Definition:

Prevalence of weight-for-height in children aged 0–59 months defined as above +2 standard deviations of the WHO Child Growth Standards median

Numerator:

Number of children aged 0–59 months who are overweight.

Denominator:

Total number of children aged 0–59 months who were measured.

Disaggregation:

Age, place of residence, sex, socioeconomic status.

Data Requirements:

Percentage of children aged < 5 years who are overweight for age = (number of children aged 0–59 months whose z-score is over two standard deviations above the median weight-for-height of the WHO Child Growth Standards/total number of children aged 0–59 months who were measured) x 100.

Children’s weight and height are measured using standard technology (e.g. children under 24 months are measured lying down, while standing height is measured in children 24 months and older.

The data sources include national nutrition surveys, any other nationally representative population-based surveys with nutrition modules, and national surveillance systems.

WHO maintains the Global Database on Child Growth and Malnutrition, which includes population-based surveys that fulfil a set of criteria. Data are checked for validity and consistency and raw data-sets are analysed according to a standard procedure to obtain comparable results. Prevalence below and above defined cut-off points for weight-for-age, height-for-age, weight-for-height and BMI-for-age in pre-school children are presented using
z-scores based on the WHO Child Growth Standards.

A detailed description of the methodology and procedures of the database – including data sources, criteria for inclusion, data quality control and database workflow – are described in a paper published in 2003 in the International Journal of Epidemiology (de Onis M, Blössner M).

Predominant type of statistics: adjusted.

Data Sources:

National nutrition surveys.

Population-based health surveys with nutrition modules, national surveillance systems.

Purpose:

This indicator is used to measure nutritional imbalance resulting in overnutrition (i.e. overweight). Child growth is internationally recognized as an important indicator of nutritional status and health in populations.

Childhood obesity is associated with a higher probability of obesity in adulthood, which can lead to a variety of disabilities and diseases, such as diabetes and cardiovascular diseases. The risks for most noncommunicable diseases resulting from obesity depend partly on the age at onset and the duration of obesity. Obese children and adolescents are likely to suffer from both short-term and long-term health consequences, the most significant being:

References:

World Health Organization (WHO). 2015 Global Reference List of 100 Core Health Indicators.; 2015. http://apps.who.int/iris/bitstream/10665/173589/1/WHO_HIS_HSI_2015.3_eng.pdf

World Health Organization. Nutrition Landscape Information System (NLIS). Country Profile Indicators: Interpretation Guide. Geneva, Switzerland; 2010. http://apps.who.int/iris/bitstream/10665/44397/1/9789241599955_eng.pdf

WHO. WHO Global Database on Child Growth and Malnutrition. Department of Nutrition for Health and Development (NHD), Geneva, Switzerland. http://www.who.int/nutgrowthdb/en/

 

Further information and related links

A draft framework for the global monitoring of the Comprehensive Implementation Plan on Maternal, Infant and Young Child Nutrition. Informal Consultation with Member States and UN Agencies on a Proposed Set of Indicators for the Global Monitoring Framework for Maternal, Infant and Young Child Nutrition, 30 September to 1 October 2013. Geneva: World Health Organization; 2013 (Retrieved from http://www.who.int/nutrition/events/2013_consultation_indicators_globalmonitoringframework_WHO_MIYCN.pdf).

de Onis M, Blössner M. The World Health Organization Global Database on Child Growth and Malnutrition: methodology and applications. Int J Epidemiol 2003;32(4):518-26.

Decision WHA67(9). Maternal, infant and young child nutrition. In: Sixty-seventh World Health Assembly, Geneva, 19-24 May 2014. Resolutions and decisions, annexes. Geneva: World Health Organization; 2014 (Retrieved from http://apps.who.int/gb/ebwha/pdf_files/WHA67-REC1/A67_2014_REC1-en.pdf, page 62).

Document A67/15. Maternal, infant and young child nutrition. The Global Strategy and the Comprehensive Implementation Plan. Report by the Secretariat. Sixty-seventh World Health Assembly, Geneva, 19–24 May 2014. Geneva: World Health Organization; 2014 (Retrieved from http://apps.who.int/gb/ebwha/pdf_files/WHA67/A67_15-en.pdf).

Draft comprehensive global monitoring framework and targets for the prevention and control of noncommunicable diseases, including a set of indicators. Agenda item A66/8, Sixty-sixth World Health Assembly, 20–28 May 2013. Geneva: World Health Organization; 2013 (Retrieved from http://apps.who.int/gb/ebwha/pdf_files/WHA66/A66_8-en.pdf?ua=1).

Organisation for Economic Co-operation and Development. Health at a Glance 2013: OECD Indicators, Paris: OECD Publishing; 2013 (Retrieved from http://dx.doi.org/10.1787/health_glance-2013-en).

WHO child growth standards: Length/height-for-age, weight-for-age, weight-for-length, weight-for-height and body mass index-for-age: Methods and development. Geneva: World Health Organization; 2006 (Retrieved from http://www.who.int/childgrowth/standards/technical_report/en/).

World health statistics 2014. Geneva: World Health Organization; 2014 (Retrieved from http://apps.who.int/iris/bitstream/10665/112738/1/9789240692671_eng.pdf?ua=1).

Adolescent fertility rate

Definition:

The number of births to women ages 15–19 per 1,000 women in that age group per year (WHO 2010). This is a subset of Age Specific Fertility Rates (ASFR).

Data Requirements:

The number of births in a given year or reference period classified by mothers 15-19 and the number of women in the same age range.

Data Sources:

Vital statistics (numerator only); population censuses or population-based surveys such as DHS

Purpose:

Adolescent birth rate is a progress indicator for the Millennium Development Goal target 5.B for achieving universal access to reproductive health (UNFPA, 2010). Adolescent fertility is high in many targeted countries, which means that many young women face an elevated risk of maternal death and disability. Newborns and infants of adolescent mothers are also at higher risk of low birth weight and mortality. This indicator is of particular interest in countries, cities, or districts with adolescent reproductive health interventions designed to reduce unintended pregnancy. Although the adolescent birth rate is rarely used as an outcome measure in evaluating such programs (due to the human, financial, and logistic resources needed to collect the data), it is a variable that program administrators and policy makers track over time as a macro-level indicator of program effectiveness combined with non-program influences.

Issue(s):

The adolescent birth rate is affected by differences or changes in the number or percent of adolescents exposed to the risk of pregnancy. Thus, changes in the rate may provide misleading information regarding the impact of family planning programs on fertility when other factors affecting risk of pregnancy are changing (for example, when age at marriage is rising quickly for the 15-19 age group).

Gender Implications:

About 14 million women and girls between ages 15 and 19 (both married and unmarried) give birth each year and complications of pregnancy and childbirth for this age group are a leading cause of death, with unsafe abortion being a major factor (UNFPA, 2005). Adolescent mothers are more likely to have children with low birth weight, inadequate nutrition and anemia, and these young women are more likely to develop cervical cancer later in life. Moreover, early childbearing is linked to obstetric fistula, a devastating and socially isolating condition that can leave women incontinent, disabled, and in chronic pain.  Globally, early childbearing often results for women in higher total fertility, lost development opportunities, limited life options, and poorer health.

 

References:

WHO, 2008 Adolescent Pregnancy Fact Sheet. http://www.who.int/making_pregnancy_safer/events/2008/mdg5/adolescent_preg.pdf

UNFPA, 2010 How Universal is Access to Reproductive Health? A review of the evidence. http://www.unfpa.org/public/home/publications/pid/6526

UNFPA, 2005, ‘The Promise of Gender Equality: Gender Equity, Reproductive Health and the MDGs’, State of the World Population 2005, New York; UNFPA. http://www.unfpa.org/swp/2005/english/indicators/index.htm