Guide To DHS Statistics 7

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Guide to DHS Statistics
DHS-7
The Demographic and Health Surveys Program
Guide to DHS Statistics ii August 2018
This publication was developed with support provided by the United States Agency for International
Development (USAID) through The Demographic and Health Surveys Program (#AID-OAA-C-13-00095).
The views expressed are those of the authors and do not necessarily reflect the views of USAID or the
United States government.
The DHS Program assists countries worldwide in the collection and use of data to monitor and evaluate
population, health, and nutrition programs. Information on The DHS Program may be obtained from ICF,
530 Gaither Road, Suite 500, Rockville MD, 20850, USA; telephone: 301-407-6500; fax: 301-407-6501; e-
mail: info@DHSprogram.com; website: www.DHSprogram.com.
Recommended citation:
Croft, Trevor N., Aileen M. J. Marshall, Courtney K. Allen, et al. 2018. Guide to DHS Statistics. Rockville,
Maryland, USA: ICF.
Guide to DHS Statistics iii August 2018
Table of Contents
Foreword .........................................................................................................................................xviii
Acknowledgements .......................................................................................................................... xix
Introduction and Description of DHS Datasets ........................................................................... 1.1
Purpose of the Guide
Description of The Demographic and Health Surveys Program
The DHS Program ............................................................................................................................... 1.1
Model Questionnaires ....................................................................................................................... 1.3
Questionnaire Modules ..................................................................................................................... 1.5
Other Basic Documentation ............................................................................................................... 1.6
Reports and Data ............................................................................................................................... 1.7
Data Archiving .................................................................................................................................... 1.8
Model Datasets .................................................................................................................................. 1.9
DHS Website .................................................................................................................................... 1.10
Other Tools and Resources .............................................................................................................. 1.10
Organization of DHS Data
Structure of DHS Data ...................................................................................................................... 1.13
Recode Files ..................................................................................................................................... 1.15
Recode File Naming ......................................................................................................................... 1.18
Recode Variable Naming .................................................................................................................. 1.19
Not Applicable and Missing Values and Other Special Codes ......................................................... 1.21
Construction of Variables ................................................................................................................. 1.23
Analyzing DHS Data
Sample Design, Stratification and Sampling Weights ...................................................................... 1.29
Households ...................................................................................................................................... 1.36
De Facto and De Jure Populations ................................................................................................... 1.36
Age of Children ................................................................................................................................. 1.37
All Women Factors ........................................................................................................................... 1.40
Median Calculations ......................................................................................................................... 1.44
Matching and Merging Datasets ...................................................................................................... 1.48
Background characteristics .............................................................................................................. 1.58
Data Suppression and Parenthesizing .............................................................................................. 1.65
Indicator Guidelines
Indicator Pages ................................................................................................................................. 1.66
Example Indicator Page .................................................................................................................... 1.68
Using Indicator Pages ....................................................................................................................... 1.69
International Indicator Guides and Resources
Population and Housing ............................................................................................................... 2.1
Household Drinking Water
Guide to DHS Statistics iv August 2018
Percent distribution of households and de jure population by source of drinking water ................ 2.2
Percent distribution of households and de jure population by time to obtain drinking water ........ 2.6
Percentage of households and de jure population using methods to treat drinking water and
percentage using an appropriate treatment method........................................................................ 2.8
Percent distribution of households and de jure population using piped water or water from a tube
well or borehole by availability of water ......................................................................................... 2.10
Type of Sanitation Facility
Percent distribution of households and de jure population by type of sanitation facility, by
improved and unimproved sanitation ............................................................................................. 2.12
Percent distribution of households and de jure population with a toilet/latrine facility by location of
facility ............................................................................................................................................... 2.15
Household Characteristics
Percent distribution of households and de jure population by housing characteristics ................. 2.17
Cooking Fuel
Percent distribution of households and de jure population by type of cooking fuel, percentage using
solid fuel for cooking, and percentage using clean fuel for cooking ............................................... 2.19
Smoking in Home
Percent distribution by frequency of smoking in the home ............................................................ 2.21
Household Possessions
Percentage of households possessing various household effects, means of transport, ownership of
agricultural land, and ownership of livestock/farm animals ........................................................... 2.23
Wealth Quintiles
Percent distribution of the de jure population by wealth quintiles and the Gini coefficient .......... 2.25
Handwashing
Percentage of households in which a place used for handwashing was observed, and among those
households, percent distribution by the availability of water, soap, and other cleansing agents .. 2.30
Household Population by Age, Sex, and Residence
Percent distribution of the de facto household population by different age groupings, according to
sex and residence. ............................................................................................................................ 2.32
Household Composition
Percent distribution of households by sex of head of household and by household size, mean size of
households, and percentage of households with orphans and foster children under age 18 ........ 2.34
Children’s Living Arrangements and Orphanhood
Percent distribution of de jure children, children not living with a biological parent, and children
with one or both parents dead ........................................................................................................ 2.37
Birth Registration
Percentage of de jure children whose births are registered with civil authorities ......................... 2.39
Educational Attainment of Household Members
Percent distribution of the de facto female and male household population age 6 and over by
highest level of schooling attended or completed .......................................................................... 2.41
Median years of education completed ............................................................................................ 2.43
Guide to DHS Statistics v August 2018
School Attendance Ratios
Net attendance ratios (NAR) and gross attendance ratios (GAR) for the de facto household
population by sex and level of schooling, and the Gender Parity Index (GPI) ................................. 2.45
Respondents’ Characteristics ...................................................................................................... 3.1
Background Characteristics of Respondents
Percent distribution of women and men by background characteristics .......................................... 3.2
Educational Attainment of Women and Men
Percent distribution of women and men by highest level of schooling attended or completed ...... 3.3
Median years of education completed .............................................................................................. 3.5
Literacy
Percent distribution of women and men by level of schooling attended and level of literacy, and
percentage literate ............................................................................................................................ 3.7
Exposure to Mass Media
Percentage of women and men exposed to specific media on a weekly basis ................................. 3.9
Internet Usage
Percentage of women and men who have ever used the internet, percentage who have used the
internet in the past 12 months, and among women and men who have used the internet in the past
12 months, percent distribution by frequency of internet use in the past month ......................... 3.11
Employment and Occupation
Percent distribution of women and men by employment status .................................................... 3.13
Percent distribution of women and men age 15-49 employed in the 12 months preceding the
survey by occupation ....................................................................................................................... 3.15
Percent distribution of women employed by type of earnings, type of employer, and continuity of
employment, according to type of employment ............................................................................. 3.17
Health Insurance Coverage
Percentage of women and men with specific types of health insurance coverage, and percentage
with any health insurance ................................................................................................................ 3.19
Tobacco Use
Percentage of women and men who smoke various tobacco products ......................................... 3.21
Percent distribution of men by smoking frequency ........................................................................ 3.23
Average number of cigarettes smoked per day ............................................................................... 3.24
Percentage of women and men age who currently use smokeless tobacco, according to type of
tobacco product, and percentage who use any type of tobacco .................................................... 3.26
Marriage and Sexual Activity ....................................................................................................... 4.1
Current Marital Status
Percent distribution by current marital status .................................................................................. 4.2
Number of Co-Wives and Number of Wives
Percent distribution of currently married women by number of co-wives ....................................... 4.4
Percent distribution of currently married men by number of wives ................................................. 4.6
Guide to DHS Statistics vi August 2018
Age at First Marriage
Percentage first married by specific exact ages ................................................................................. 4.8
Median age at first marriage ........................................................................................................... 4.10
Age at First Sexual Intercourse
Percentage who had first sexual intercourse by specific exact ages ............................................... 4.13
Median age at first sexual intercourse ............................................................................................ 4.15
Fertility .......................................................................................................................................... 5.1
Current Fertility
Age-Specific Fertility Rate (ASFR) ....................................................................................................... 5.2
Age-Specific Fertility Rate (ASFR) 10-14 ............................................................................................ 5.7
Trends in Age-Specific Fertility Rates ............................................................................................... 5.12
Total Fertility Rate (TFR) .................................................................................................................. 5.14
General Fertility Rate (GFR) ............................................................................................................. 5.15
Crude Birth Rate (CBR) ..................................................................................................................... 5.17
Percentage currently pregnant ........................................................................................................ 5.19
Completed Fertility
Mean number of children ever born to women age 40-49 ............................................................. 5.20
Children Ever Born and Living
Percent distribution by number of children ever born .................................................................... 5.21
Mean number of children ever born and mean number of living children ..................................... 5.22
Birth Intervals
Percent distribution by months since preceding birth .................................................................... 5.24
Median number of months since preceding birth ........................................................................... 5.26
Postpartum Exposure: Amenorrhea, Abstinence, and Insusceptibility
Percentage of births for which mothers are: a) postpartum amenorrheic, b) abstaining from sexual
intercourse and c) insusceptible to pregnancy, by number of months since birth ......................... 5.28
Median and Mean Durations of Postpartum Amenorrhea, Abstinence, and Insusceptibility ........ 5.30
Menopause
Percentage of women who are menopausal ................................................................................... 5.35
Age at First Birth
Percentage of women who gave birth by specific exact ages ......................................................... 5.37
Median age at first birth .................................................................................................................. 5.39
Teenage Pregnancy and Motherhood
Percentages of teenage girls who are mothers, pregnant with their first child, and have begun
childbearing...................................................................................................................................... 5.41
Fertility Preferences ..................................................................................................................... 6.1
Fertility Preferences
Percent distribution by desire for children ........................................................................................ 6.2
Desire to Limit Childbearing
Guide to DHS Statistics vii August 2018
Percentage who want no more children ........................................................................................... 6.4
Ideal Number of Children
Percent distribution by ideal number of children .............................................................................. 6.6
Mean ideal number of children ......................................................................................................... 6.8
Fertility Planning
Fertility planning status ................................................................................................................... 6.10
Wanted Fertility
Wanted Fertility Rates ..................................................................................................................... 6.12
Family Planning ............................................................................................................................ 7.1
Knowledge of Contraceptive Methods
Percentage who know of any method, any modern method, any traditional method and specific
methods; mean number of methods known ..................................................................................... 7.2
Ever Use of Contraceptive Methods
Percentages who ever used any method, any modern method, any traditional method and specific
methods ............................................................................................................................................. 7.7
Current Use of Contraceptive Methods
Percentage of women who currently use any method, any modern method, any traditional method
and specific methods ....................................................................................................................... 7.11
Knowledge of the Fertile Period
Percent distribution of women, by knowledge of the fertile period during the ovulatory cycle .... 7.16
Percentage of women with correct knowledge of the fertile period during the ovulatory cycle ... 7.18
Age at Sterilization
Percentage distribution of women sterilized in specific age groups ............................................... 7.19
Median Age at Sterilization .............................................................................................................. 7.20
Source of Contraception
Percent distribution of current users of modern methods, by most recent source of method...... 7.22
Use of Social Marketing Brand Pill and Condom
Percentage of women currently using oral contraceptives or condoms who use a specific socially
marketed brand ............................................................................................................................... 7.24
Informed Choice
Percentage of current users of selected contraceptive methods who were informed about side
effects or problems of the method used, what to do if they experienced side effects or problems,
and who were informed of other methods of contraception that could be used .......................... 7.26
Contraceptive Discontinuation
First-year contraceptive discontinuation rates ................................................................................ 7.28
Percent distribution of discontinued episodes of contraceptive use in the 5 years preceding the
survey by reason
for discontinuation ............................................................................................... 7.35
Need and Demand for Family Planning
Guide to DHS Statistics viii August 2018
Percentage of women with a) unmet need for family planning, b) met need for family planning, c)
total demand for family planning by whether for spacing, limiting, and total, and the percentage of
the demand for family planning that is satisfied ............................................................................. 7.38
Decision making about Family Planning
Percent distribution of currently married women who are current users of family planning by who
makes the decision to use family planning, and percent distribution of currently married women
who are not currently using family planning by who makes the decision not to use family planning
......................................................................................................................................................... 7.45
Future Use of Contraception
Percent distribution of currently married women who are not using a contraceptive method, by
intention to use in the future. ......................................................................................................... 7.47
Exposure to Family Planning Messages
Percentages of all women and men who heard or saw a family planning message on the radio,
television, in a newspaper or magazine, or on a mobile phone in the past few months or in none of
the four media sources. ................................................................................................................... 7.49
Contact of Nonusers with Family Planning Providers
Percentages of women who are not using contraception who were visited by a fieldworker who
discussed family planning, who visited a health facility and discussed family planning, who visited a
health facility but did not discuss family planning and who did not discuss family planning with a
fieldworker or at a health facility during the 12 months preceding the survey. ............................. 7.51
Infant and Child Mortality............................................................................................................ 8.1
Early Childhood Mortality
Methodology of DHS Mortality Rates Estimation ............................................................................... 8.2
Neonatal Mortality Rate (NNMR), Post-Neonatal Mortality Rate (PNMR), Infant Mortality Rate (IMR),
Child Mortality Rate (CMR) (Ages 1-4), Under-five Mortality Rate (U5MR) ........................................ 8.5
Perinatal Mortality
Perinatal mortality rate .................................................................................................................... 8.11
High-Risk Fertility Behavior
Risk ratio of children in high-risk fertility behavior categories ......................................................... 8.14
Percentage of births in high-risk fertility behavior categories ......................................................... 8.17
Percentage of currently married women in high-risk fertility behavior categories ......................... 8.19
Reproductive Health .................................................................................................................... 9.1
Antenatal Care
Percent distribution of antenatal care by type of provider, and percentage of antenatal care from a
skilled provider ................................................................................................................................... 9.2
Percent distribution of number of antenatal care visits, and of timing of first antenatal visit ......... 9.5
Median number of months pregnant at time of first antenatal care visit ........................................ 9.8
Percentage of women receiving components of antenatal care ....................................................... 9.9
Tetanus Toxoid Injections
Guide to DHS Statistics ix August 2018
Percentage of women receiving two or more tetanus toxoid injections during pregnancy, and
percentage whose most recent live birth was protected against neonatal tetanus ....................... 9.11
Place of Delivery
Percent distribution of live births by place of delivery, and the percentage of live births delivered in
a health facility ................................................................................................................................. 9.14
Assistance during Delivery
Percent distribution of live births by person providing assistance during delivery, and the
percentage assisted by a skilled provider ........................................................................................ 9.16
Caesarean Section
Percentage of live births delivered by caesarean section, the percentage that was planned before
the onset of labor pains, and that was decided after the onset of labor pains............................... 9.19
Duration of Stay in Health Facility after Birth
Percent distribution by duration of stay in the health facility following the most recent live birth by
type of delivery ................................................................................................................................ 9.21
Postnatal Care
Percent distribution of timing of first postnatal check for the mother, and percentage who received
a postnatal check during the first 2 days ......................................................................................... 9.23
Percent distribution of type of provider for the first postnatal check for the mother.................... 9.26
Percent distribution of timing of first postnatal check for the newborn, and percentage receiving a
postnatal check during the first 2 days ............................................................................................ 9.29
Percent distribution of type of provider for the first postnatal check for the newborn ................. 9.32
Percentage of newborns receiving selected function of postnatal care ......................................... 9.35
Problems in Accessing Health Care
Percentage of women who reported serious problems in accessing health care for themselves, by
type of problem ............................................................................................................................... 9.37
Child Health ............................................................................................................................. 10.1
Child Size and Weight at Birth
Percent distribution of live births by birth size and birth weight .................................................... 10.2
Vaccination
Percentage of children age 12-23 months and children age 24-35 months who received specific
vaccines at any time before the survey according to vaccination card, according to mother’s report,
according to either vaccination card or mother’s report, and percentage who received specific
vaccines by appropriate age ............................................................................................................ 10.4
Percentage of children who ever had a vaccination card and who had a vaccination card seen . 10.11
Prevalence and Treatment of Symptoms of Acute Respiratory Infection (ARI)
Percentage of children under age 5 with symptoms of ARI, and among children under age 5 with
symptoms of ARI, the percentage for whom advice or treatment was sought and for whom advice
or treatment was sought the same or next day. ........................................................................... 10.13
Percentage of children under age 5 with symptoms of ARI for whom advice or treatment was
sought from specific sources, and among those for whom advice or treatment was sought,
percentage for whom advice or treatment was sought from specific sources ............................. 10.16
Guide to DHS Statistics x August 2018
Prevalence and Treatment of Fever
Percentage of children under age 5 with fever, percentage with fever for whom advice or treatment
was sought, for whom advice or treatment was sought the same or next day, and who took
antibiotic drugs .............................................................................................................................. 10.19
Prevalence and Treatment of Diarrhea
Percentage of children under age 5 with diarrhea, and percentage for whom advice or treatment
was sought ..................................................................................................................................... 10.22
Feeding Practices during Diarrhea
Percent distribution of children under age 5 with diarrhea by amount of liquids given, and by
amount of foods given ................................................................................................................... 10.25
Oral Rehydration Therapy, Zinc, and Other Treatments for Diarrhea
Among children under age 5 who had diarrhea in the 2 weeks preceding the survey, percentage
given fluid from an ORS packet or pre-packaged ORS fluid, recommended homemade fluids (RHF),
ORS or RHF, zinc, ORS and zinc, ORS or increased fluids, oral rehydration therapy (ORT), continued
feeding and ORT, and other treatments; and percentage given no treatment ............................ 10.27
Source of Advice or Treatment for Children with Diarrhea
Percentage of children under age 5 with diarrhea for whom advice or treatment was sought from
specific sources, among children with diarrhea for whom advice or treatment was sought,
percentage sought from specific sources, and among children with diarrhea who received ORS, the
percentage for whom advice or treatment was sought from specific sources ............................. 10.30
Knowledge of ORS packets
Percentage of mothers who know about ORS packets or ORS pre-packaged liquids ................... 10.32
Disposal of children’s stool
Percent distribution of youngest children under age 2 living with the mother, by the manner of
disposal of child’s last fecal matter, and the percentage of children whose stools are disposed of
appropriately .................................................................................................................................. 10.33
Nutrition of Children and Adults ............................................................................................ 11.1
Initial Breastfeeding
Percentage of children ever breastfed, who started breastfeeding within one hour of birth, who
started breastfeeding within one day of birth, and who received a prelacteal feed ...................... 11.3
Breastfeeding and Complementary Feeding
Percent distribution of children exclusively breastfeeding, or breastfeeding and consuming plain
water only, non-milk liquids, consuming other milk, and consuming complementary foods ........ 11.5
Percentage of children exclusively breastfed, predominantly breastfed, age-appropriately
breastfed, and introduced to solid, semi-solid, or soft foods ........................................................ 11.10
Percentage of children currently breastfeeding, continuing breastfeeding at 1 year and at 2 years
....................................................................................................................................................... 11.13
Percentage of children using a bottle with a nipple ...................................................................... 11.15
Median and mean durations of breastfeeding among children born in the past three years for any
breastfeeding, exclusive breastfeeding, predominant breastfeeding ........................................... 11.16
Foods and Liquids Consumed by Children
Guide to DHS Statistics xi August 2018
Percentage of breastfeeding and non-breastfeeding children consuming specific foods ............ 11.22
Minimum Dietary Diversity, Minimum Meal Frequency and Minimum Acceptable Diet
Percentage of children fed the minimum dietary diversity, the minimum meal frequency, and the
minimum acceptable diet .............................................................................................................. 11.25
Iodization of Household Salt
Percentage of households with salt tested for iodine content, with salt but salt not tested, with no
salt, and among households tested percentage with iodized salt................................................. 11.29
Micronutrient Intake among Children
Percentage of children who consumed foods rich in vitamin A, who consumed foods rich in iron,
who were given multiple micronutrient powder, who were given iron supplements, who received
vitamin A supplements, who received deworming medication, or who live in household with tested
iodized salt ..................................................................................................................................... 11.31
Therapeutic and Supplemental Foods
Percentage of children who received Plumpy’Nut or who received Plumpy’Doz ......................... 11.35
Micronutrient Intake among Women
Percent distribution of women with a birth in last five years, by number of days they took iron
tablets or syrup during pregnancy of last birth, percentage who took deworming medication, and
percentage who live in a household with tested iodized salt........................................................ 11.37
Anemia Status
Percentage of children with anemia .............................................................................................. 11.39
Percentage of women with anemia ............................................................................................... 11.42
Percentage of men with anemia .................................................................................................... 11.46
Nutritional Status
Percentage of children stunted, wasted, and underweight, and mean z-scores for stunting, wasting
and underweight. ........................................................................................................................... 11.49
Percentage of women by nutritional status .................................................................................. 11.54
Percentage of men by nutritional status ....................................................................................... 11.57
Malaria ..................................................................................................................................... 12.1
Household Possession of Mosquito Nets
Percentage of households with at least one mosquito net, with at least one insecticide-treated net
(ITN), average number of mosquito nets, average number of ITNs, percentage of households with
at least one mosquito net for every two persons who stayed in the household last night, and
percentage of households with at least one ITN for every two persons who stayed in the household
last night ........................................................................................................................................... 12.3
Source of Mosquito Nets
Percent distribution of mosquito nets by source of net .................................................................. 12.6
Access to an Insecticide-Treated Net (ITN)
Percent distribution of the household population by number of ITNs the household owns .......... 12.8
Percentage of the population with access to an ITN ..................................................................... 12.10
Use of Mosquito Nets by Persons in the Household
Guide to DHS Statistics xii August 2018
Percentage of the household population who slept the night before the survey under a mosquito
net, under an insecticide-treated net (ITN), and among the population in households with at least
one ITN, the percentage who slept under an ITN the night before the survey ............................. 12.13
Use of Existing ITNs
Percentage of insecticide-treated nets (ITNs) used the night before the survey .......................... 12.15
Use of Mosquito Nets by Children
Percentage of children under age 5 who slept the night before the survey under a mosquito net,
under an insecticide treated net (ITN), and among children under age 5 in households with at least
one ITN, the percentage who slept under an ITN the night before the survey ............................. 12.17
Use of Mosquito Nets by Pregnant Women
Percentage of pregnant women who slept the night before the survey under a mosquito net, who
slept the night before the survey under an insecticide-treated net (ITN), and among pregnant
women age 15-49 in households with at least one ITN, the percentage who slept under an ITN the
night before the survey .................................................................................................................. 12.19
Use of Intermittent Preventive Treatment (IPTp) by Women during Pregnancy
Percentage of women who, during the pregnancy that resulted in the last live birth, received one or
more doses of SP/Fansidar, received two or more doses of SP/Fansidar, and who received three or
more doses of SP/Fansidar ............................................................................................................ 12.22
Prevalence, Diagnosis, and Prompt Treatment of Children with Fever
Percentage of children with fever in the 2 weeks preceding the survey; and among children with
fever, percentage for whom advice or treatment was sought, percentage for whom advice or
treatment was sought the same or next day following the onset of fever, and percentage who had
blood taken from a finger or heel for testing ................................................................................ 12.24
Percentage of children under age 5 with fever in the 2 weeks preceding the survey for whom advice
or treatment was sought from specific sources; and among children under age 5 with fever in the 2
weeks preceding the survey for whom advice or treatment was sought, the percentage for whom
advice or treatment was sought from specific sources ................................................................. 12.27
Type of Antimalarial Drugs Used
Among children with fever in the 2 weeks preceding the survey who took any antimalarial
medication, percentage who took specific antimalarial drugs ...................................................... 12.30
Coverage of Testing for Anemia and Malaria in Children
Percentage of eligible children who were tested for anemia and for malaria .............................. 12.33
Hemoglobin <8.0 g/dl in Children
Percentage of children with hemoglobin lower than 8.0 g/dl ....................................................... 12.35
Prevalence of Malaria in Children
Percentage of children classified in two tests as having malaria .................................................. 12.38
HIV-AIDS Related Knowledge, Attitudes, and Behaviors ...................................................... 13.1
Knowledge of HIV or AIDS
Percentage of women and men who have heard of HIV or AIDS .................................................... 13.2
Knowledge of HIV Prevention Methods
Guide to DHS Statistics xiii August 2018
Percentage of women and men who know that people can reduce the risk of getting HIV by use of
condoms and having just one uninfected faithful partner .............................................................. 13.4
Comprehensive Knowledge about HIV (Total and Youth)
Percentage of women and men who know that a healthy looking person can have HIV and reject
local misconceptions about transmission or prevention of HIV ...................................................... 13.6
Percentage of women and men with comprehensive knowledge about HIV, percentage of young
women and young men with comprehensive knowledge about HIV .............................................. 13.9
Knowledge of Prevention of Mother-to-Child Transmission
Percentage of women and men who know that HIV can be transmitted from mother to child during
pregnancy, during delivery, by breastfeeding, and in all 3 ways; Percentage of women and men who
know that the risk of mother-to-child transmission can be reduced by the mother taking special
drugs .............................................................................................................................................. 13.12
Discriminatory Attitudes towards People Living with HIV
Percentage who have discriminatory attitudes towards people living with HIV among women and
men who have heard of HIV or AIDS ............................................................................................. 13.14
Multiple Sexual Partners, Higher-Risk Sexual Partners, and Condom Use
Percentage of all women and men and of young women and men who had multiple sexual
partners, higher-risk sexual partners, condom use with multiple partners, and condom use at last
high-risk sex ................................................................................................................................... 13.16
Mean number of sexual partners .................................................................................................. 13.19
Payment for Sexual Intercourse and Condom Use
Percentage of men who ever paid for sexual intercourse, percentage who paid for sexual
intercourse in the past 12 months, and percentage reporting using a condom at last paid sexual
intercourse ..................................................................................................................................... 13.20
Coverage of Prior HIV Testing
Percentage of women and men who know where to get an HIV test, percent distribution by prior
HIV testing status and whether they received the result of their last test, percentage ever tested for
HIV, percentage who have been tested for HIV in the past 12 months and received the results of
the last test .................................................................................................................................... 13.22
Pregnant Women Counseled and Tested for HIV
Percentage of women who received counseling on HIV during antenatal care; percentage tested for
HIV during antenatal care according to whether they received their test results and post-test
counseling; percentage who received counseling on HIV and an HIV test during antenatal care and
received the test result; and percentage who received an HIV test during antenatal care or labor,
according to whether they received the test result ...................................................................... 13.25
Male Circumcision
Percentage of men circumcised, and percent distribution of men according to circumcision status
and circumcision provider .............................................................................................................. 13.27
Prevalence of Sexually Transmitted Infections (STIs) and STI Symptoms
Percentage of women and men who had an STI in the past 12 months, had an abnormal genital
discharge in the past 12 months, had a genital sore or ulcer in the past 12 months, had an STI or
symptoms of an STI in the past 12 months .................................................................................... 13.29
Guide to DHS Statistics xiv August 2018
Care-Seeking Behavior for Sexually Transmitted Infections (STI)
Among women and men who reported an STI or symptoms of an STI in the past 12 months, the
percentage who sought advice or treatment ................................................................................ 13.31
Age at First Sexual Intercourse among Young People
Percentage of young women and men who had sexual intercourse before age 15 or age 18 ..... 13.34
Premarital Sexual Intercourse among Young People
Percentage of never-married young women and men who have never had sexual intercourse . 13.36
Recent HIV Tests among Young People
Among young women and men age 15-24 who have had sexual intercourse in the past 12 months,
percentage who have been tested for HIV in the past 12 months and received the results ........ 13.38
Self-Testing for HIV
Percentage of women and men who have ever heard of HIV self-test kits and percentage who have
ever used a self-test kit .................................................................................................................. 13.40
HIV Prevalence ........................................................................................................................ 14.1
Coverage of HIV Testing
Percent distribution of women and men eligible for HIV testing .................................................... 14.2
HIV Prevalence
Among women and men interviewed and tested, percentage HIV positive ................................... 14.5
Prior HIV Testing
Percent distribution of women and men who tested HIV positive and who tested HIV negative
according to HIV testing status prior to the survey ......................................................................... 14.8
HIV Prevalence by Male Circumcision
Among men who were tested for HIV, percentage HIV positive by circumcision status .............. 14.10
HIV Prevalence among Couples
Percent distribution of couples living in the same household by HIV status ................................ 14.12
Women’s Empowerment ....................................................................................................... 15.1
Employment and Cash Earnings
Percentage of currently married women and men employed in the past 12 months, and percent
distribution of currently married women and men employed in the past 12 months by type of
earnings ............................................................................................................................................ 15.2
Control over Women’s Cash Earnings
Percent distribution of currently married women who received cash earnings for employment in
the 12 months preceding the survey by person who decides how wife’s cash earnings are used, and
percent distribution by whether she earned more or less than her husband ................................ 15.4
Control over Men’s Cash Earnings
Percent distribution of currently married men who receive cash earnings by person who decides
how husband’s cash earnings are used, and percent distribution of currently married women whose
husbands receive cash earnings, by person who decides how husband’s cash earnings are used 15.6
Guide to DHS Statistics xv August 2018
Ownership of Assets
Percent distribution of women and men by ownership of housing and land ................................. 15.8
Ownership of Title or Deed for House or Land
Percent distribution of women (or men) who own a house or own land by whether the house or
land owned has a title or deed, and whether or not the woman/man's name appears on the title or
deed ............................................................................................................................................... 15.10
Ownership and Use of Bank Accounts and Mobile Phones
Percentage of women and men who use an account in a bank or other financial institution and
percentage who own a mobile phone, and among women and men who own a mobile phone,
percentage who use it for financial transactions ........................................................................... 15.12
Participation in Decision Making
Percent distribution of currently married women and men by person who usually makes decisions
about various issues ....................................................................................................................... 15.14
Percentage of currently married women and men who usually make specific decisions either alone
or jointly with their husband/wife ................................................................................................. 15.16
Attitude towards Wife Beating
Percentage of all women and men who agree that a husband is justified in hitting or beating his
wife for specific reasons ................................................................................................................ 15.18
Attitudes towards Negotiating Safer Sexual Relations with Husband
Percentage of women and men who believe that a woman is justified in refusing to have sexual
intercourse with her husband if she knows that he has sexual intercourse with other women, and
percentage who believe that a woman is justified in asking that they use a condom if she knows
that her husband has a sexually transmitted infection (STI) ......................................................... 15.20
Ability to Negotiate Sexual Relations with Husband
Percentage of currently married women who can say no to their husband if they do not want to
have sexual intercourse, and percentage who can ask their husband to use a condom .............. 15.22
Indicators of Women’s Empowerment
Percentage of currently married women who participate in all decision making, and percentage
who disagree with all of the reasons justifying wife-beating ........................................................ 15.24
Adult and Maternal Mortality ................................................................................................ 16.1
Adult Mortality Rates
Age-specific adult mortality rates, and age 15-49 mortality rate .................................................... 16.2
Probability of dying between the ages of 15 and 50 for women and men ..................................... 16.8
Maternal Mortality and Pregnancy-related Mortality
Age-specific pregnancy-related and maternal mortality rates, and total pregnancy-related and
maternal mortality rate ................................................................................................................. 16.14
Percentage of female deaths that are pregnancy-related deaths and maternal deaths .............. 16.21
Pregnancy-related mortality ratio and maternal mortality ratio .................................................. 16.25
Lifetime risk of pregnancy-related death and maternal death ...................................................... 16.31
Completeness of Information on Siblings
Guide to DHS Statistics xvi August 2018
Completeness of data on survival status of sisters and brothers, age of living siblings and age at
death and years since death of dead siblings. ............................................................................... 16.33
Sibship Size and Sex Ratio of Siblings
Mean sibship size and sex ratio of siblings at birth ....................................................................... 16.35
Domestic Violence .................................................................................................................. 17.1
Experience of Physical Violence
Percentage of women who have experienced physical violence, and who have experienced physical
violence in the past 12 months ........................................................................................................ 17.3
Persons Committing Physical Violence
Among women who have experienced physical violence since age 15, percentage who report
specific persons who committed the violence ................................................................................ 17.6
Experience of Sexual Violence
Percentage of women who have ever experienced sexual violence, and who experienced sexual
violence in the 12 months preceding the survey ............................................................................. 17.9
Persons Committing Sexual Violence
Among women who have experienced sexual violence, percentage who report specific persons who
committed the violence ................................................................................................................. 17.12
Age at First Experience of Sexual Violence
Percentage of women who have experienced sexual violence by exact ages .............................. 17.15
Experience of Physical or Sexual Violence by Anyone: Different Combinations
Percentage of women who have experienced physical violence only, sexual violence only, physical
and sexual violence, and experienced physical or sexual violence ............................................... 17.17
Experience of Physical Violence during Pregnancy
Percentage of women who have experienced violence during pregnancy ................................... 17.20
Marital Control
Percentage of ever-married women whose husbands/partners demonstrated types of controlling
behaviors ........................................................................................................................................ 17.22
Spousal Physical Violence
Percentage of ever-married women who have experienced spousal physical violence ever or in the
12 months preceding the survey by their current or most recent husbands/partners................. 17.25
Spousal Sexual Violence
Percentage of ever-married women who have experienced spousal sexual violence ever or in the 12
months preceding the survey ........................................................................................................ 17.27
Spousal Emotional Violence
Percentage of ever-married women who have experienced spousal emotional violence ever or in
the 12 months preceding the survey ............................................................................................. 17.29
Combinations of Types of Spousal Violence: Ever Experienced
Percentage of ever-married women who have ever experienced physical violence and sexual
violence, physical violence and sexual violence and emotional violence, physical violence or sexual
Guide to DHS Statistics xvii August 2018
violence, physical violence or sexual violence or emotional violence by their current or most recent
husbands/partners ......................................................................................................................... 17.31
Combinations of Types of Spousal Violence: 12 months preceding the Survey
Percentage of ever-married women who have experienced physical violence and sexual violence,
physical violence and sexual violence and emotional violence, physical violence or sexual violence,
physical violence or sexual violence or emotional violence by their current or most recent
husbands/partners in the 12 months preceding the survey ......................................................... 17.33
Types of Spousal Violence
Percentage of ever-married women who have experienced emotional violence, physical violence,
sexual violence, physical violence and sexual violence, physical violence and sexual violence and
emotional violence, physical violence or sexual violence, physical violence or sexual violence or
emotional violence by any husband or partner in the 12 months preceding the survey ............. 17.35
Experience of spousal violence by duration of marriage
Among married women married only once, the percentage who first experienced spousal physical
or sexual violence by specific exact years since marriage ............................................................. 17.38
Injuries to Women due to Spousal Violence
Among ever-married women who have experienced violence committed by their current or most
recent husband/partner, the percentage who have been injured as a result of the violence...... 17.40
Initiation of Spousal Violence by Women
Percentage of ever-married women who have committed physical violence against their current or
most recent husband/partner when he was not already beating or physically hurting her, ever and
in the past 12 months .................................................................................................................... 17.42
Help Seeking to Stop the Violence
Percent distribution of women who have experienced physical or sexual violence by help-seeking
behavior ......................................................................................................................................... 17.44
Sources for Help to Stop the Violence
Percentage of women age who have experienced physical or sexual violence and sought help by
sources from which they sought help ............................................................................................ 17.46
Guide to DHS Statistics xviii August 2018
Foreword
DHS surveys collect a wealth of information on a wide range of topics from a representative sample of
the population in the countries that participate in The DHS Program. For each country, the information
collected is processed, tabulated, and presented in a report that describes the living conditions and the
demographic and health situation in the country. Before producing the tables, many steps are necessary
to ensure that the data properly reflect the situation they intend to describe. This involves editing the
data for consistency, imputation of key dates of events, weighting the sample results, considering such
factors as the sample design and response rates, calculating the wealth index, and constructing accurate
summary variables.
Many of the procedures involved are straightforward and are familiar to demographic analysts.
However, other procedures need special attention and have been developed on the basis of experience
accumulated over many years regarding the preferred way of calculating certain indicators, what to
guard against, and what not to forget.
This Guide to DHS Statistics is meant to be a tool for all data users. It can be an aid for those who are just
starting out in data analysis, a tool for checking procedures for those whose skills are more advanced,
and a reference document for all who deal with data generated by The DHS Program surveys. Even
those who do not analyze data using a statistical software package can benefit from a deeper
understanding of the definitions of these indicators and a closer examination of the numerators and
denominators.
I hope that this valuable tool will significantly increase the capacity of many researchers to do their own
tabulations and analyses. I trust that it will help make data users aware of the precautions to take and
the procedures that need to be followed to ensure that indicators are calculated correctly. It should also
ensure that the strengths and limitations of certain data and indicators are clear to all users.
Sunita Kishor
Project Director
Guide to DHS Statistics xix August 2018
Acknowledgements
The original Guide to DHS Statistics was written in 2003 and revised in 2006 by Shea Rutstein and
Guillermo Rojas. This version of the Guide to DHS Statistics written in 2018 is not just an update, but a
complete revision of the guide and focuses on the indicators produced as part of the tabulations for a
standard DHS-7 survey.
This version of the guide was prepared by Trevor Croft with substantial support from Aileen Marshall
and Courtney Allen. Many DHS Program staff contributed to the writing or reviewing of particular
chapters or topics including Fred Arnold, Shireen Assaf, Sarah Balian, Yodit Bekele, Jean de Dieu
Bizimana, Clara Burgert, Debbie Collison, Joy Fishel, Julia Fleuret, Lia Florey, Jose Miguel Guzman, Sara
Head, Richard Joseph, Sunita Kishor, Annē Linn, Joanna Lowell, Lindsay Mallick, Claudia Marchena,
Fidele Mutima, Erica Nybro, Ladys Ortiz Parra, Tom Pullum, Keith Purvis, Christian Reed, Kia Reinis, Luis
Alejandro Rey, Guillermo Rojas, Gulnara Semenov, Amadou Sow, Sarah Staveteig, Cameron Taylor,
Albert Themme, Wenjuan Wang, Ann Way, Rebecca Winter, Mianmian Yu, Sally Zweimueller.
Chapters of the Guide were also reviewed by Patrick Gerland, Philipp Ueffing, Joseph Cummins, Anaka
Aivar, and Nehar Agarwal. Robert Bozsa provided support for the development of the web version.
Many thanks to everyone who contributed to this Guide to DHS Statistics for their valuable input.
Guide to DHS Statistics 1.1 August 2018
Introduction and Description of DHS Datasets
Purpose of the Guide
This guide has two main purposes:
To explain how statistics produced in Demographic and Health Surveys (DHS) reports are
defined and calculated and serve as a reference document for researchers.
To provide an overview of the structure and use of DHS datasets.
The first version of this document (Rutstein and Rojas, 2003 [updated 2006]) had been prepared in
response to feedback received from DHS data users on the need for a detailed guide to assist them in
understanding DHS data sets and reproducing the statistics in DHS reports. This version updates the
earlier versions to capture new variable definitions and the expanding array of data.
The first chapter of the guide deals with general topics including DHS data file structure, recode files and
variable naming, sampling design, sampling weights and sample stratification, century month codes and
other created variables, matching and merging datasets, adjustment factors employed in surveys in
which only ever-married women are interviewed, and background variables used in tabulations.
The remaining chapters deal with the definitions of individual statistics presented in DHS reports by
chapter.
Description of The Demographic and Health Surveys Program
The DHS Program
The DHS Program was established by the United States Agency for International Development (USAID) in
1984. Originally designed as a follow-up to the World Fertility Survey (WFS) and the Contraceptive
Prevalence Survey (CPS) projects, it has provided technical assistance to more than 350 surveys in over
90 countries, advancing global understanding of health and population trends in developing countries.
The DHS Program has been implemented in overlapping five-year phases:
DHS-I 1984 - 1990
DHS-II 1989 - 1993
DHS-III 1992 - 1998
DHS-IV 1997 - 2003 (MEASURE DHS)
DHS-V 2003 - 2008 (MEASURE DHS+)
DHS-VI 2008 - 2013 (MEASURE DHS Phase III)
DHS-7 2013 - 2018
The DHS Program has been implemented by the same team since its inception although the name of the
organization has changed through acquisitions. It was first awarded in 1984 to Westinghouse Health
Systems, which subsequently evolved into part of Macro Systems, ORC Macro, Macro International and
is now part of ICF. The DHS Program is implemented by ICF and its partners Path, Avenir Health, Johns
Hopkins Center for Communication Programs, Vysnova, Blue Raster, Kimetrica, and Encompass.
Guide to DHS Statistics 1.2 August 2018
The main objective of The DHS Program is to improve the collection, analysis, and dissemination of
population, health, and nutrition data and to facilitate use of these data for planning, policy-making and
program management, resulting in:
Improved tools, methods, partnerships, and technical guidance to collect quality population,
health, and nutrition data.
Increased in-country individual and institutional capacity for identification of data needs and for
survey design, management, and data collection to meet those needs.
Improved availability of DHS Program survey data and information.
Advanced availability and synthesis of DHS Program survey data.
Improved facilitation of DHS Program data use among stakeholders worldwide.
Many countries have conducted multiple surveys to establish trend data that enable them to gauge
progress in their programs. Countries that participate in The DHS Program are primarily countries that
receive USAID assistance; however, several non-USAID supported countries have participated with
funding from other donors such as UNICEF, UNFPA, the World Bank, and national governments. The
Demographic and Health Survey was the original survey tool developed by The DHS Program in 1984.
More than 300 DHS surveys in over 90 countries have been conducted since the program’s inception.
The DHS Program has evolved over the years to incorporate several other survey types:
The DHS Program created the AIDS Indicator Survey (AIS) in 2003 to respond to the need for global
monitoring of the HIV/AIDS epidemic. The AIS is a household based survey focusing on HIV and AIDS
knowledge, attitudes, behavior, and prevalence. Demand for the AIS was not as high as had been
anticipated, largely because the DHS was also designed to collect the same HIV data as a subset of the
larger DHS and most countries requested a DHS rather than an AIS. Eleven AIS surveys were conducted
in 2003-2015.
In 2006, The DHS Program began implementing the Malaria Indicator Survey (MIS), also a household
based survey, designed to collect data focused on internationally accepted malaria indicators. More
than 30 MIS have been conducted since 2006. Though a DHS collects the same malaria indicators as an
MIS, differences between the two surveys include the collection of malaria parasitemia and data
collection during malaria high transmission season during an MIS, whereas a DHS typically collects data
during the dry season.
Finally, the Service Provision Assessment (SPA) survey is a health facility assessment that provides a
comprehensive overview of a country’s health service delivery. It meets the need for monitoring health
system strengthening in developing countries.
This Guide will focus on DHS surveys and the statistics produced in the reports; note that most DHS
survey reports include all the statistics that are presented in the more narrowly focused AIS and MIS
reports.
Guide to DHS Statistics 1.3 August 2018
Model Questionnaires
One of the key aims of The DHS Program is to collect data that are comparable across countries. To
achieve this, standard model questionnaires have been developed. These model questionnaires—which
have been reviewed and modified in each of the seven phases of The DHS program—form the basis for
the questionnaires that are implemented in each country. Typically, a country is asked to adopt the
model questionnaire in its entirety, but can add questions of particular interest. However, questions in
the model may be deleted when they are irrelevant in a particular country.
DHS surveys are designed to collect data on marriage, fertility, mortality, family planning, reproductive
health, child health, nutrition, and HIV/AIDS. Due to the subject matter of the survey, women of
reproductive age (15–49) are the focus of the survey. Women eligible for an individual interview are
identified through the households selected in the sample. Consequently, all DHS surveys utilize a
minimum of two questionnaires—a Household Questionnaire and a Woman’s Questionnaire.
The Household Questionnaire is used to list all the usual members and visitors in the selected
households. The respondent for the Household Questionnaire is any knowledgeable person age 15 or
older living in the household. Some basic information is collected on the characteristics of each person
listed, including his/her age, sex, education, and relationship to the head of the household. The main
purpose of the Household Questionnaire is to provide the mechanism for identifying women eligible for
individual interview and children under five who are to be weighed, measured, and tested for anemia. In
addition, information is collected about the dwelling itself, such as the source of water, type of
sanitation facilities, materials used to construct the house, ownership of various consumer goods, and
use of iodized salt.
The Biomarker Questionnaire, introduced as part of DHS-7, collects biomarker data for eligible
household members. These include anthropometric measurements (height and weight), tests for the
hemoglobin level in blood for anemia, samples for HIV testing, malaria testing and other lab based
biomarkers. Previously, in DHS-IV to DHS-VI, the biomarker questionnaire was part of the Household
Questionnaire.
The Woman’s Questionnaire forms the central part of the DHS questionnaires and covers all of the key
topics of the survey. The Woman’s Questionnaire surveys women of reproductive age (15-49). The
Woman’s Questionnaire, along with other questionnaires, has undergone changes in every phase of
DHS. In DHS-I through DHS-IV, questionnaires for women distinguished between countries with high and
low contraceptive prevalence rates. The DHS Model “A” Woman’s Questionnaire was for use in the high
contraceptive prevalence countries, while the DHS Model “B” Woman’s Questionnaire was for use in
countries with relatively low contraceptive use. The main difference between these questionnaires was
that the “A” core collected considerably more information on family planning than the “B” core. In DHS-
V and later, these have been combined into a single Woman’s Questionnaire.
The DHS-7 Woman’s Questionnaire includes the following standard sections:
1) Background characteristics (age, education, religion, etc.)
2) Reproduction
3) Contraception
4) Pregnancy and postnatal care
5) Immunization
Guide to DHS Statistics 1.4 August 2018
6) Child health and nutrition
7) Marriage and sexual activity
8) Fertility preferences
9) Husband’s background and woman’s work
10) HIV/AIDS
11) Other health issues
The Man’s Questionnaire is similar but shorter than the Woman’s Questionnaire and is used to collect
data on background characteristics, reproduction and fertility preferences, contraception, employment
and gender roles, HIV/AIDS, and other health issues. The respondent to the Man’s questionnaire is men
of reproductive age (typically 15 to 49, 54, or 59).
In 2015, The DHS Program introduced the Fieldworker Questionnaire to collect data on the background
characteristics of interviewers, supervisors, field editors and health technicians. Data from the
fieldworker questionnaire permit users to include characteristics of the fieldworkers as well as the
survey respondents in their analysis.
See https://www.dhsprogram.com/What-We-Do/Survey-Types/DHS-Questionnaires.cfm for more
information on the DHS questionnaires.
The model questionnaires for all seven phases of DHS can be found at:
DHS-7 https://www.dhsprogram.com/publications/publication-DHSQ7-DHS-Questionnaires-and-Manuals.cfm
DHS-VI https://www.dhsprogram.com/publications/publication-DHSQ6-DHS-Questionnaires-and-Manuals.cfm
DHS-V https://www.dhsprogram.com/publications/publication-DHSQ5-DHS-Questionnaires-and-Manuals.cfm
DHS-IV https://www.dhsprogram.com/publications/publication-DHSQ4-DHS-Questionnaires-and-Manuals.cfm
DHS-III https://www.dhsprogram.com/publications/publication-DHSQ3-DHS-Questionnaires-and-Manuals.cfm
DHS-II https://www.dhsprogram.com/publications/publication-DHSQ2-DHS-Questionnaires-and-Manuals.cfm
DHS-I https://www.dhsprogram.com/publications/publication-DHSQ1-DHS-Questionnaires-and-Manuals.cfm
Guide to DHS Statistics 1.5 August 2018
Questionnaire Modules
Some countries have a need for special information not contained in the model questionnaires. To
accommodate this need and to achieve some level of comparability across countries that apply them,
optional questionnaire modules have been developed on a series of topics. The modules currently
available in the DHS-7 phase are:
Accident and Injury
Adult and Maternal mortality
Disability
Domestic Violence
Female Genital Cutting
Fistula
Male Child Circumcision
Newborn Care
Non-communicable Diseases
Out-of-pocket Health Expenditures
The modules can be found at https://www.dhsprogram.com/publications/publication-DHSQM-DHS-
Questionnaires-and-Manuals.cfm and are available in English and French.
Various other modules have been used in previous phases of DHS, but are no longer maintained as
supported modules, including:
Children’s education
Consanguinity
HIV/AIDS
Malaria
Pill-taking behavior
Sterilization experience
Verbal autopsy
Women’s status
Some of these modules have been incorporated into the standard DHS questionnaire, including much of
the HIV/AIDS, Malaria, and Women’s Status modules. Earlier versions of some of these modules can be
found at https://www.dhsprogram.com/publications/publication-DHSQMP-DHS-Questionnaires-and-
Manuals.cfm.
DHS surveys are also sometimes requested to include UNICEF Multiple Indicator Cluster Surveys (MICS)
modules, such as:
Child Discipline
Child Labor
Early Childhood Development
These modules can be found as part of the MICS tools at http://mics.unicef.org/tools.
Guide to DHS Statistics 1.6 August 2018
Other Basic Documentation
To achieve comparable information across countries, it is necessary to ensure that the questionnaires
and the survey procedures followed in each country are similar. Therefore, The DHS Program has
developed a set of basic documentation to go with the model questionnaires. The basic documentation
consists of the following manuals, most of which are available in English and French:
The DHS Interviewer’s Manual provides a detailed explanation of the survey questions and tips on
conducting interviews.
The DHS Supervisor’s and Editor’s Manual explains the roles of the supervisor in leading the field teams,
and for editors, how to check completed questionnaires.
Training Field Staff for DHS Surveys is designed for survey managers to provide tips on how to organize
and conduct training for field staff. It describes techniques of mock interviewing, demonstration
interviews in front of the class, field practice, and sample tests for trainees.
The DHS Sampling Manual presents the DHS approach to issues like optimum sampling frames, sample
domains, stages, and sample selection. The Household Listing portion of the sampling manual describes
how to locate selected sample points, how to draw a sketch map, and how to list the households and
structures.
The DHS Tabulation Plan for Key Indicators Report describe the key tabulations in the Key Indicators
Report.
The Tabulation Plan for DHS Final Report details the tabulations that will be produced with the survey
data for each chapter of the report. This manual also aids data processing staff in determining the exact
tabulations that are required for the survey reports. The Guide to DHS Statistics should be used in
conjunction with the Tabulation Plan and describes the statistics presented in each tabulation.
The Biomarker Field Manual is designed to be used, in combination with classroom instruction and
practical experience, to teach fieldworkers how to collect biomarkers for a DHS, MIS or AIS.
The DHS User’s Guide for Questionnaires in Excel is guide to using the Excel versions of the DHS
questionnaires in adapting them to individual surveys.
Incorporating Geographic Information into Demographic and Health Surveys: A Field Guide to GPS Data
Collection is designed to be a start-to-finish guide to Global Positioning System (GPS) data collection in
DHS, MIS, and AIS. This guide provides background information on GPS, how the technology works, how
GPS data are collected, and how they are used in the context of a DHS.
DHS Survey Organization Manual is intended as an aid to host country survey staff, donors, and others,
and explains the standard approach to implementing a DHS.
The basic documentation for The DHS Program can be found at
https://www.dhsprogram.com/publications/Publication-Search.cfm?type=35.
Guide to DHS Statistics 1.7 August 2018
Reports and Data
The survey results for each participating country are published initially in a Key Indicators Report (KIR -
formerly known as a preliminary report), followed by a more detailed Final Report and a summary type
Key Findings report. The latter two reports are widely distributed and constitute primary outputs of the
project. Results are also presented through fact sheets and other dissemination materials.
Further dissemination of survey data is achieved through the publication of analytical and other reports.
Of particular relevance for program and policy purposes are the Comparative Report series. These
descriptive reports provide information across survey countries and can contribute greatly to the policy
debate through the exhaustive view they provide on a particular situation in a large number of
countries. Analytical Studies are also published and provide rigorous analysis of survey data,
emphasizing policy and program-relevant themes and research questions. Further Analysis reports
provide results emanating from research that is typically based in and on a single DHS country.
Methodological reports cover issues relating to the collection and analysis of DHS data, particularly
focusing on new types of data.
DHS data are also shared through a number of tools, including the STATcompiler, Mobile app, API,
Spatial Data Repository (see Other Tools and Resources). However, the major output of the surveys is
the micro-level datasets distributed through the DHS Data Archive.
Guide to DHS Statistics 1.8 August 2018
Data Archiving
The DHS Program believes that widespread access to survey data by responsible researchers has
enormous advantages for the countries concerned and the international community in general.
Therefore, The DHS Program policy is to release survey data to the public when the main survey report
is published, generally within 12 months after the end of fieldwork.
DHS Archive
DHS maintains a data archive of all survey datasets collected over the more than 30 years of The DHS
Program. Datasets are available at https://www.dhsprogram.com/data/available-datasets.cfm. Users log
in or register for access to datasets at https://dhsprogram.com/data/dataset_admin/login_main.cfm.
Once registered and access permission has been provided, users may download the datasets from the
required countries. The DHS Program has developed a set of tutorial videos on YouTube on dataset
registration, modifying dataset requests, dataset names, dataset types, downloading datasets,
downloading multiple datasets, and an introduction to DHS datasets (these are just a few of the DHS
tutorial videos on YouTube).
The reformatting of each dataset into standard recode files facilitates use of DHS data. These files
standardize the variable names and coding categories across countries and construct many of the
commonly used variables such as marital status or age in five-year groups. Because DHS surveys collect
an enormous amount of information on different subjects for the household, household members,
women age 15–49, children under age five, and men age 15–59, these standard recode files are a
particular advantage for cross-country analysis. The DHS recode datasets are described in more detail in
Organization of DHS Data.
IPUMS-DHS
IPUMS-DHS is designed to facilitate further analysis of DHS data. It provides an interface to select and
download a customized set of variables across a number of surveys or countries in a single dataset.
IPUMS-DHS contains thousands of consistently coded variables on the health and well-being of women,
children, and births, and on all household members, for 24 African countries and 4 Asian countries.
IPUMS-DHS datasets do differ from datasets available directly through The DHS Program website. The
IUPMS-DHS datasets are created from the original recode datasets. Either dataset can be used to
reproduce the results published in the DHS survey reports, but the variable names and the coding
schemes within the datasets are different. While the original datasets use a naming system of letters
and digits for the variables (e.g. v705), the IPUMS-DHS datasets use short names for the variables (e.g.
currwork). Additionally, the coding of each variable is different. The IPUMS-DHS datasets have
harmonized coding schemes across the phases of DHS with more detailed coding schemes incorporating
survey-specific codes consistently over time.
The indicator definitions in the Guide to DHS Statistics refer to the variable names and coding from the
DHS standard recode datasets available through https://www.dhsprogram.com/.
Guide to DHS Statistics 1.9 August 2018
Model Datasets
The DHS Program has created model datasets so users can become familiar with datasets without
having to register for access. These datasets have been created strictly for practice and do not represent
any country's actual data. Model datasets are based on the DHS 6 Questionnaire and Recode. They can
be downloaded from the Download Model Datasets page on the website.
Guide to DHS Statistics 1.10 August 2018
DHS Website
The DHS Program website provides access to survey documentation, survey reports, analytical studies,
datasets and much more. Resources include:
Core documentation: questionnaires, manuals, and methodology
Microdata and Indicator data: Datasets, support for dataset use, and links to online data tools
Publications, including survey reports, and dissemination materials
Further analysis reports: analytical reports, comparative reports and methodological reports
Journal articles database: a database of peer-reviewed journal articles that feature DHS data
Indicator information: Topical pages provide an in-depth look at key topics including SDGs
Other Tools and Resources
STATcompiler allows users to make custom tables, charts, and maps with DHS indicator-level data. The
STATcompiler contains over 1,000 indicators for all DHS countries. It is designed to explore trends and
cross-country comparisons. The tool is available in English and French.
API: The DHS Program Application Programming Interface (API) provides software developers access to
aggregated indicator data from The DHS Program. The API can be used to create various applications to
help analyze, visualize, explore and disseminate data on population, health, HIV, and nutrition from
more than 90 countries.
Mobile app: The DHS Program mobile application provides up-to-date indicator data through tables,
charts, and maps, as well as basic survey information and links to publications. It is available for free for
Apple and Android devices. Search “DHS Program” in your app store.
The DHS Program User Forum is an online community designed to foster conversation and data use
support between DHS data users. Users can search the forum for answers to frequently asked questions
on technical or analytical topics, post new questions, or respond to queries from other users. The DHS
Program staff moderate the forum and often provide answers to questions.
Spatial Data Repository: The DHS Program Spatial Data Repository (SDR) provides geographically-linked
health and demographic data from The DHS Program and the U.S. Census Bureau for mapping in a
geographic information system (GIS).
Boundaries: Explore how DHS region boundaries have changed over time and download survey
boundary data.
Modeled surfaces: Modeled surfaces are produced using standardized geostatistical methods,
publically available DHS data, and a standardized set of covariates across countries. Each map
package contains a mean estimate surface, an uncertainty surface, and corresponding
information on the model creation process and validation.
Covariates: Datasets containing key covariate data for DHS Program survey clusters from
external geospatial covariate datasets covering agriculture, climate, environment, health,
infrastructure, and population variables.
Blog: The DHS Program blog highlights new tools, explores complex data topics, and keeps followers
abreast of changes to the questionnaire and other developments
Guide to DHS Statistics 1.11 August 2018
eLearning courses: The DHS Program has partnered with K4Health to develop 3 elearning courses on
the Global Health eLearning Center:
Demographic and Health Surveys: Data Use
Data Visualization: an Introduction
Social Media for Health and Development
YouTube: The DHS Program’s YouTube channel is the home of tutorial videos, Key Findings videos, and
interviews with topical experts. Of particular relevance to dataset users are the following:
Intro to The DHS Program (7 min)
How to Read Tables
o English (7 min)
o French (10 min total)
o Also available in Portuguese, Spanish, Arabic
Sampling and Weighting (Part I and Part II) (30 min total)
De Jure and De Facto (5 min)
Using DHS Datasets for Analysis: 9 videos (32 min total)
Matching DHS Final Report Tables: Parts I-IV (19 min total)
STATcompiler Tutorial
o Parts 1-3 (English) (<15 min)
o Parts 1-3 (French) (<15 min)
DHS Program digital resources (4 min)
GIS Playlist: 4 videos (32 min total)
Top 10 STATcompiler features (3 min)
How to subscribe to forums & topics DHS Program User Forum (6 min)
Topical Videos
Family Planning:
Contraceptive Prevalence Rate: Indicator Snapshot (4 min)
Contraceptive Calendar Tutorial Part I & Part II (15 min total)
Demand satisfied by modern methods: Indicator Snapshot (8 min)
Malaria:
ITN Access: Indicator Snapshot (English or French) (6-9 min)
Maternal Mortality Ratio (MMR) and Pregnancy-related Mortality Ratio (PRMR):
MMR versus PRMR 3 video playlist:
o MMR Indicator Snapshot (8 min) (English)
o Differences between MMR and PRMR (9 min) (English)
o Interpreting trends in PRMR (14 min) (English)
Announcements and updates about new surveys, data, and resources are made on the DHS website,
through email alerts (register on the website), and through social media channels:
Twitter @dhsprogram
Facebook facebook.com/dhsprogram
LinkedIn linkedin.com/company/dhs-program
Guide to DHS Statistics 1.12 August 2018
DHS Newsletter bit.ly/DHSsubscribe
DHS Blog blog.dhsprogram.com
Guide to DHS Statistics 1.13 August 2018
Organization of DHS Data
Structure of DHS Data
DHS surveys collect data through four main questionnaires. The Household Questionnaire collects data
on the characteristics of the household and list all household members. The household roster within this
questionnaire captures key characteristics of each household member and is used to select women and
men eligible for individual interviews. The Biomarker Questionnaire collects information for each eligible
household member on anthropometric measurements and levels of hemoglobin, and records
information about samples for biomarker testing. Eligible household members are typically children
under age 5, and women and men age 15-49.
Women and men age 15-49 (age range varies for men) are interviewed using the Woman’s
Questionnaire and Man’s Questionnaire respectively. The Woman’s Questionnaire, in addition to
questions about the woman, contains a birth history that is used to list all children (alive or dead) that
the respondent has given birth to, with the child’s sex, date of birth, age, and survival status. The birth
history is then the basis for selecting children under certain ages for the maternal health, immunization,
child health, and nutrition sections of the questionnaire.
The data from a DHS survey naturally forms a hierarchy of households within a cluster, household
members within each household, interviewed women and men as a subset of household members, and
children of each interviewed woman, as shown in the example figure below.
Within this hierarchy, data may be collected about the same person in more than one questionnaire. For
example, data about women may be collected in the Household Questionnaire, and also in the Woman’s
Questionnaire. Similarly for men, some basic characteristics are collected in the Household
Questionnaire and in the Man’s Questionnaire. Additionally, data on children may be collected in the
Household Questionnaire and in the birth history within a Woman’s Questionnaire – these data can be
linked in analysis.
The DHS Program uses a software package, CSPro, to process its surveys. CSPro is developed by the US
Bureau of the Census, ICF, and SerPro SA with funding from USAID. CSPro is specifically designed to
Guide to DHS Statistics 1.14 August 2018
meet the data processing needs of complex surveys such as DHS, and one of its key features is its ability
to handle hierarchical files. CSPro is used in The DHS Program in all steps of data processing with no
need for another package or computer language. All steps, from entering/capturing the data to the
production of statistics and tables published in DHS final reports, are performed with CSPro. In addition,
CSPro provides a mechanism to export data to the statistical packages Stata, SPSS, SAS and R.
The example above shows that, while a single questionnaire is always completed for each household in
the DHS sample, the number of Woman’s Questionnaires or Man’s Questionnaires that will be
completed depends on the number of eligible women or men listed in the Household Questionnaire. In
other words, for each Household Questionnaire there may be zero or several Woman’s or Man’s
Questionnaires.
The hierarchical data file produced in CSPro has a two-level structure reflecting the relationship
between the questionnaires; the Household Questionnaire and Biomarker Questionnaire are at level 1
and the Woman’s and Man’s Questionnaires are at level 2. Within each CSPro level, there can be one or
more different types of records each containing many variables. For example, records in the household
level in a typical DHS file can be single (e.g. household characteristics) or multiple (e.g. household
member’s roster). Thus, using the same file, it is possible to work with different units of analysis
(households, household members, women, men and children). This makes the analysis of variables
across different units very convenient.
The hierarchical structure defined by CSPro has several advantages and disadvantages. Among the
advantages, the following can be highlighted:
All the data are stored in just one ASCII file. Virtually all packages can read ASCII files.
Since all the data are stored in the same file, it is easy to maintain the integrity of the data in
terms of data structure related to levels and records.
The data file mirrors the paper questionnaire. Each section in the questionnaire can be defined
as a record in the data file and only the information that is needed is present in the file.
The major disadvantage is that only CSPro easily handles hierarchical data. Most analysis software does
not support hierarchical data, or at least not simply, so The DHS Program produces a set of exported
datasets from the CSPro versions of the DHS recode files with different units of analysis that are
convenient for use in statistical software such as Stata, SPSS, SAS and R.
In the exported files, there is one record for each case. All variables in each case are placed
subsequently on the same record. The multiple or repeating records from the hierarchical file are placed
one after the other on the record, with the maximum number of occurrences of each section
represented in the data file. For example, if a data file collects information on the age of a woman’s
children, up to a maximum of 20 children, then there will be 20 records represented in the data file
whether or not a woman had the maximum number of children. Each variable in a repeating section is
placed immediately after the preceding variable of the same occurrence, such that all variables for
occurrence 1 precede all variables for occurrence 2 of a section.
For more information, see the YouTube tutorial video Introduction to DHS Data Structure.
Guide to DHS Statistics 1.15 August 2018
Recode Files
There are four main questionnaires in DHS surveys: A Household Questionnaire, a Biomarker
Questionnaire, a Woman’s Questionnaire, and a Man’s Questionnaire. There are also several
standardized modules for countries with interest in extra topics. These modules are applied as part of
the Household, Biomarker, Woman’s, or Man’s Questionnaires.
Since the very beginning of DHS, a recode file has been a standard part of the survey process. Primarily
the recode file was developed to define a standardized file that would facilitate cross-country analysis.
Initially it was also to compare data with the World Fertility Surveys (WFS) to study trends. In DHS-I the
recode file was defined only for the Woman’s Questionnaire, as the Household Questionnaire was
originally just used for the selection of women for interview. Additionally, the use of a Man’s
Questionnaire was not part of the original design, and only a few men’s surveys took place in DHS-I. The
recode file proved to be very useful and as a result, since DHS-II, a recode file was introduced for the
Household and Man’s Questionnaires.
DHS questionnaires have changed extensively since the first phase. For this reason, there is a different
recode definition for each DHS phase. However, if a variable is present in one or more phases, that
variable has the same meaning in each phase in which it is present. If a question is dropped from one
phase to another, the name of the variable used for that question is not reusable. The variable will not
be present in the recode of the phase where it was dropped. If a new question is added to the core
questionnaire, a new variable will be added to the recode definition.
See https://www.dhsprogram.com/data/Data-Variables-and-Definitions.cfm for a discussion of the
benefits of the recode files.
Recode files are created using a hierarchical model in CSPro and later exported to files compatible with
Stata, SPSS, SAS and R for use by analysts. The DHS Recode Manual provides a description of the
contents of the recode file, including a brief description of each variable and the applicable base for the
variable. The DHS Recode Map provides a simple codebook for the standard DHS recode. The DHS
Recode Manual and Map for all phases of DHS can be found at
https://www.dhsprogram.com/publications/publication-dhsg4-dhs-questionnaires-and-manuals.cfm.
The DHS Program recode files are exported into several dataset types. Below is a description of the
dataset types referred to in the Guide to DHS Statistics, together with the unit of analysis (or case) for
each dataset:
HR: Household Recode
Unit of analysis: Households
Includes household characteristics, the household roster, and biomarkers rosters as repeating sets of
variables. This dataset is used for calculation of household level indicators such as water and sanitation
(see Chapter2).
PR: Household members (or Persons) Recode
Unit of analysis: Household member
Includes characteristics of household members including age, sex, marital status, education, as well as
biomarker measurement information. The dataset includes both de facto and de jure household
Guide to DHS Statistics 1.16 August 2018
members. It also includes the characteristics of the households where the individual lives or was visiting.
This dataset is used for analysis of education of household members (Chapter 2) and of anthropometry
and anemia in children under age 5 (Chapter 11).
IR: Individual (Women’s) Recode
Unit of analysis: De facto woman interviewed
Contains all the data collected in the Woman’s Questionnaire for de facto women plus some variables
from the Household Questionnaire. Up to 20 births in the birth history (see also BR file), and up to 6
children under age 5 (see also KR file), for whom pregnancy and postnatal care as well as immunization,
health and nutrition data were collected, can be found as repeated variables in this file. This dataset is
used for most woman-level analysis including marriage and sexual activity (Chapter 4), fertility and
fertility preferences (Chapters 5 and 6), family planning (Chapter 7), anthropometry and anemia in
women (Chapter 11), malaria prevention for women (Chapter 12), HIV/AIDS (Chapters 13 and 14),
women’s empowerment (Chapter 15), adult and maternal mortality (Chapter 16), and domestic violence
(Chapter 17).
BR: Births Recode
Unit of analysis: Birth
Contains the full birth history of all women interviewed, including information on pregnancy and
postnatal care as well as immunization, health and nutrition data for children born in the last 5 years.
Data for the mother of each of these children are also included. This dataset is used for fertility (Chapter
5) and mortality (Chapter 8) analysis.
KR: Kids Recode
Unit of analysis: Child under age 5 born to a woman interviewed
Contains the information related to the child's pregnancy and postnatal care and immunization, health
and nutrition data. The data for the mother of each of these children is also included. This dataset is
used to look at child health indicators such as immunization coverage, vitamin A supplementation,
recent occurrences of diarrhea, fever, and cough for young children and treatment of childhood diseases
(Chapter 10), nutrition of young children (Chapter 11), and malaria prevention and treatment (Chapter
12).
MR: Men’s Recode
Unit of analysis: De facto man interviewed
Contains all data collected in the Man’s Questionnaire de facto men plus some variables from the
Household Questionnaire. This dataset is used for most man-level analysis including marriage and sexual
activity (Chapter 4), fertility preferences (Chapters 6), and HIV/AIDS (Chapters 13 and 14).
CR: Couples Recode
Unit of analysis: Married woman and man
Contains data for married or living together women and men who both declared that they are married
(living together) to each other and with completed individual interviews. This dataset is the result of
linking the IR and MR files, based on whom they both declared as partners. In polygynous societies a
man’s data may be linked to more than one woman’s data. This dataset is used for analysis of couples,
principally related to HIV (Chapters 13 and 14).
Guide to DHS Statistics 1.17 August 2018
AR: HIV testing Recode
Unit of analysis: Person tested for HIV
Contains the result of lab testing for HIV from blood samples provided by women and men, together
with a separate weight variable for use when analyzing HIV test results. This dataset is used for analysis
of HIV prevalence (Chapter 14).
The DHS Program has also prepared two geographic datasets that data analysts can use with DHS data:
GE: Geographic Data
Unit of analysis: Cluster
The geographic datasets (also known as GPS data) contain a single record per cluster in which the survey
was conducted and provide the latitude, longitude and elevation for the survey cluster, for use in
Geographic Information Systems (GIS). Questions concerning the geographic data are addressed on the
Geographic Data forum within the DHS User Forum.
GC: Geospatial Covariates
Unit of analysis: Cluster
The geospatial covariate datasets link survey cluster locations to ancillary data, known as covariates,
that contain data on topics including agriculture, environment, health, infrastructure, and population
factors. This allows individuals with limited GIS experience to conduct geospatial statistical analysis
without having to manually source and link these covariates to cluster locations. These covariates are
extracted from freely available global datasets. See the Spatial Data Repository’s Covariates webpage
and Methodology webpage for more information.
In addition to the contextual variables that can be included in analysis from the geospatial covariates,
interviewers can also have an effect on the responses to certain survey questions. To permit analysis of
interviewer effects on survey responses analysts can also use the characteristics of the fieldworkers.
FW: Fieldworker’s Dataset
Unit of analysis: Fieldworker
Contains the basic characteristics of each fieldworker who participated in the survey, including their age,
sex, marital status, level of education, region of residence, languages, and prior experience with DHS or
other surveys. Data from the fieldworker’s dataset may be linked to the survey responses using the
interviewer, supervisor, field editor, or biomarker specialists IDs.
Additional dataset types also exist, and when using older datasets, two of these are of particular
relevance:
WI: Wealth Index
Unit of analysis: Household
Contains the wealth score and quintiles for surveys prior to the late 1990’s. Wealth Index analysis was
introduced to The DHS Program around the end of the 1990's. When the decision was made to include
the wealth index as part of DHS, standard variables were added to the recode definition for both the
household and individual datasets (hv270 and hv271 for households; v190 and v191 for women; and
Guide to DHS Statistics 1.18 August 2018
mv190 and mv191 for men). For surveys conducted prior to the change in the recode file definition a file
was created containing the score and the quintile variables. Wealth index files were created for all DHS
surveys except surveys carried out as part of DHS-I. This dataset can be linked to any of the datasets
described above.
HW: Height and Weight
Unit of analysis: Children under age 5
In 2006 new child growth standards were introduced by WHO. Prior to this time, The DHS Program used
the NCHS/CDC/WHO reference. After the adoption of the new WHO standards, standard recode
variables hv70 to hv73 and hw70 to hw73 were added to the recode definition to store the z-scores
based on the new WHO child growth definition. All files using the DHS-V, DHS-VI or DHS-7 recode
structure have these variables. For surveys prior to DHS-V, a file was created containing the z-scores
based on the new standard. In early DHS phases only children of interviewed women were measured.
Starting with DHS-III onwards all children under five listed in households interviewed have been
measured. This dataset can be linked to the household members (PR), the children under five (KR) or the
births (BR) datasets described above if height and weight was taken for children in the households. The
file can only be linked to the children under five (KR) or birth (BR) dataset when only children of
interviewed women were measured for early DHS phases.
Additional information about datasets can be found in The DHS Program YouTube video on DHS Dataset
Types in 60 Seconds and on The DHS Program at https://www.dhsprogram.com/data/Dataset-
Types.cfm.
Recode File Naming
Survey datasets are distributed as compressed .zip files. Each zip file contains a dataset and related
documentation files. The naming of the zip files and their contents follows the DHS file naming
convention: CCDDVVFF[DS].ZIP
Code Description:
CC: Country Code
DD: Dataset Type. See File types above.
VV: Dataset Version. First character - DHS Phase, second character - Release version.
FF: File Format. DT - Stata, SV - SPSS, SD - SAS, FL - Flat, no file format – Hierarchical.
DS: Data Structure. SPA only: SR - SPA Recode, SP - SPA Raw.
For example, UGIR7ADT.ZIP contains the Stata version of the Individual Women’s Recode dataset for the
Uganda 2016 DHS conducted as part of DHS-7.
The DHS file naming convention is described in detail at https://www.dhsprogram.com/data/File-Types-
and-Names.cfm.
The list of datasets available for each survey can be found on The DHS Program website at
https://www.dhsprogram.com/data/available-datasets.cfm, or through The DHS Program API using the
datasets call, e.g. https://api.dhsprogram.com/rest/dhs/datasets?f=html&perpage=1000. The API call
can be filtered by country, survey, survey type, file format, or dataset type (file type). See
https://api.dhsprogram.com/#/api-datasets.cfm for more information on using the API datasets call.
Guide to DHS Statistics 1.19 August 2018
Recode Variable Naming
Variables in the recode file begin with one or two letters followed by one to four (typically three) digits
and in some cases followed by a letter. Following is a list describing the general variable name
conventions.
Household Recode (HR) and Household Member Recode (PR)
hv0xx Basic characteristics of the household interview (hhid,hv000-hv046)
hv8xx Time of household interview and date of biomarker visit (hv801-hv807a)
hv1xx Characteristics of household members (hvidx,hv101-hv140)
hv2xx Characteristics of the household (hv201-hv271a)
haxx Anthropometry, anemia and biomarkers for women (ha0-ha70)
hbxx Anthropometry, anemia and biomarkers for men (hb0-hb70)
hcxx Anthropometry, anemia and biomarkers for children (hc0-hc73)
hmlxx Mosquito net characteristics and use (hmlidx,hml3-hml11,hml21-hml23,hmla-hmle)
Mosquito net use by household members (hml12-20), and malaria test results (hml30-hml36)
shxxx Survey-specific household or household member characteristics
Women’s Individual Recode (IR), Births Recode (BR), and Children Under age 5 Recode (KR)
v0xx Basic characteristics of the women’s interview (caseid,v000-v046)
v1xx Woman’s characteristics (v101-v191a)
bxx Birth history (bidx,bord,b1-b20)
v2xx Reproduction (v201-v244)
v3xx Contraception (v301-v3a09b)
mxx Maternal health, pregnancy, postnatal care and breastfeeding (midx,m1-m78j)
v4xx Anthropometry and anemia of interviewed women, breastfeeding, and feeding of youngest
child living with mother (v401-v482c)
hxx Immunization and child health (hidx,h0-h80g)
hwxx Anthropometry for children of interviewed women (hwidx,hw1-hw73)
v5xx Marriage and sexual exposure
v6xx Fertility preferences
v7xx Husband’s characteristics, women’s work, women’s empowerment (v701-v746)
HIV/AIDS knowledge, attitudes and practices, and sexually transmitted infections (v750-v791a)
v8xx Interview characteristics (v801-v815c)
HIV related practices, sexual activity (v820-v858)
vcal Reproductive/contraceptive calendar
mmxx Adult and maternal mortality (optional)
mlxx Malaria-related child health (idxml,ml0-ml25a)
dxxx Domestic violence (d005,d101-d130c)
gxxx Female genital cutting (g100-g119,gidx,g121-124)
sxxx Women’s survey-specific
Men’s Recode (MR)
mv0xx Basic characteristics of the men’s interview (mcaseid,mv000-mv046)
mv8xx Interview characteristics (mv801-mv803)
mv1xx Man’s characteristics (mv101-mv191a)
mv2xx Reproduction (mv201-mv252)
Guide to DHS Statistics 1.20 August 2018
mv3xx Contraception (mv301-mv3b25b)
mv4xx Smoking, tuberculosis and other adult health issues (mv463a-mv484l)
mv5xx Marriage and sexual exposure (mv501-mv541)
mv6xx Fertility preferences (mv602-mv634d)
mv7xx Employment (mv714-mv747b)
HIV/AIDS knowledge, attitudes and practices, and sexually transmitted infections (mv750-
mv793b,mv820-mv858)
mgxxx Female genital cutting (mg100-mg119)
smxx Men’s survey-specific
HIV Testing Data (AR)
hivxx HIV test results
Recode variable names are used consistently across DHS, AIS and MIS to facilitate analysis of all surveys
types.
Guide to DHS Statistics 1.21 August 2018
Not Applicable and Missing Values and Other Special Codes
In DHS datasets there are several special values that have particular codes. Two of them are very
important – not applicable and missing. The DHS Program treats these two differently although some
software treat them as the same.
“Not applicable” is defined as when a question is not supposed to be asked due to the flow of
the questionnaire. For example question 227 in the Woman’s Questionnaire “How many
months pregnant are you?” is not applicable if the answer to the preceding question 226 “Are
you pregnant now?” is No or Unsure. Question 227 would be left blank in the questionnaire in
this case.
“Missing” is defined as a variable that should have a response, but because of interview error
the question was not asked. For example, question 227 “How many months pregnant are you?”
should be answered if a woman responded Yes to question 226 “Are you pregnant now?” If the
interviewer incorrectly left the question blank then a code is required to recognize that. The
general rule for DHS data processing is that answers should not be made up, and so a “missing
value” will be assigned. The data will be kept as missing in the data file and no imputation for
this kind of question will be done. Missing values in general are codes 9, 99, 999, 9999, etc.
depending on the number of digits used for the variable.
There are important differences in how “not applicable” and “missing” are handled in each of the
statistical software:
In Stata, in most datasets both not applicable and missing values have been converted to Stata’s
missing value (.). In some datasets though the codes remain as 9, 99, 999 or 9999.
In SPSS, not applicable values are converted to system missing, while the missing values are
converted to user missing.
In SAS, as in Stata, both not applicable and missing values have been converted to SAS’ missing
value (.)
The distinction between “not applicable” and “missing” can be important for matching results from DHS
reports. In general the denominators for most indicators in DHS reports exclude the “not applicable”
cases, but include the “missing” cases. Careful attention to the selection of the denominator and then
ensuring that “missing” values are correctly treated is important for ensuring that results match those
published in DHS survey reports.
There are some important background variables where the “missing” code is not accepted, including:
Geographical variables such as type of place of residence (urban/rural) (hv025, v025, mv025,
v102, mv102), regions (hv024, v024, v101, mv101), and any other variable whose value can be
established by the sample design
Level of education for women and men in the individual questionnaire (v106, mv106)
Current use of contraception for women (v312)
Current marital status of women and men (v501, mv501)
Variables related to the woman’s birth history (v201 to v210, b0, b4, b5, b9).
Note though that in earliest phases of DHS it is possible that some of these variables may have “missing”
values.
Guide to DHS Statistics 1.22 August 2018
In addition to “not applicable” and “missing” values there are often other special values recorded in the
datasets. Codes 8, 98, 998, 9998 are assigned to “don’t know” responses. These codes are normally pre-
coded in the questionnaires, and are consistently used throughout the recode file.
Another special code used for data editing purposes is code “Inconsistent.” This code is generally used in
the secondary editing of data, when a value or code is not plausible, but it is impossible to determine
the correct code. For example, dates for vaccinations recorded as having occurred before the birth of
the child. The value is not missing, but is not possible. The secondary editing team is instructed to first
check for clues that could lead to correcting the problem, but if that is not possible, to establish which
piece of information is wrong (day, month, or year) and assign the code for “Inconsistent” to that item.
Inconsistent codes are 7, 97, 997, 9997 depending on the variable number of digits.
Other special responses may be coded 96 (996, 9996), 95 (995, 9995), 94 (994, 9994), etc. For example,
in variable v226 (Time since last period (comp) (months)) code 996 means “Never menstruated”, code
995 means “Before last birth”, and code 994 means “In menopause”. As another example, variable v525
(age at first sex) has codes 99 “Missing”, 98 “Don’t know”, 97 “Inconsistent”, 96 “At first union”, and 0
“Not had sex”.
All of these special codes should be taken into account when analyzing DHS datasets. For example, if
they are not excluded to calculate the mean age at first sex, eventually the mean will be inflated by ages
96, 97, 98, and 99. Even code 0 would need to be excluded as it would incorrectly deflate the mean age
at first sex.
In general, The DHS Program uses a conservative approach to the calculation of indicators including
missing and special values in denominators of most percentages (but not means and medians) and
excluding them from the numerators or showing them as separate categories in percent distributions.
Guide to DHS Statistics 1.23 August 2018
Construction of Variables
DHS Recode files are created through a complex recoding application, converting the raw data as
collected in the questionnaires into a standardized recode format for use in analysis. In this process
there are a number of different types of variables constructed. For most variables this is a one-to-one
conversion, possibly recoding categories (e.g. converting No = 2 in the questionnaire to No = 0 in the
recode variable), while for others the creation is more complex. The creation of some types of variables
is described below.
Multiple Response Variables
In multiple response questions, the question is asked and the respondent spontaneously begins
providing answers. The answers are not read, but the interviewer has to classify the response according
to the options available for the question. The interviewer keeps probing for other responses until the
respondent says that she has no more answers. Question 409 of the Woman’s Questionnaire is a typical
example of this type of question:
At the time of data capture, all responses are stored in just one field. However, dealing with
combinations of alphabetic codes presents a challenge for analysis purposes, so each response for this
type of question is translated into codes 0 = No, 1 = Yes, 9 = Missing, in separate variables in the recode
files:
m2a Prenatal care: Doctor
m2b Prenatal care: Nurse/Midwife
m2c Prenatal care: Auxiliary Midwife
m2d Prenatal care: CS Health Specialist
m2e Prenatal care: CS Health Specialist
m2f Prenatal care: CS Health Specialist
m2g Prenatal care: Traditional Birth Attendant
m2h Prenatal care: Village Health Worker
m2i Prenatal care: CS Other Person
m2j Prenatal care: CS Other Person
m2k Prenatal care: Other Response (uncoded)
m2l Prenatal care: CS Other
m2m Prenatal care: CS Other
m2n Prenatal care: No One
Guide to DHS Statistics 1.24 August 2018
(variables in italics are used for survey-specific categories)
In creating these variables there are several conditions taken into consideration with this type of
variable:
If the question was missing, all applicable variables will be assigned the code “missing”.
If a response category does not exist for a particular survey, the variable will be left blank “not
applicable”.
There are provisions for survey-specific (CS = country-specific) responses that are not part of the
standard model questionnaires. For example, some countries include additional categories of
health professionals.
Multipart Questions
In multipart questions the response for the separate parts of the question are usually stored in separate
variables in the recode files. For example, question 413 in the Woman’s Questionnaire is as follows:
Each part of the question is treated as a separate variable in the recode file:
m42c During pregnancy: blood pressure taken
m42d During pregnancy: urine sample taken
m42e During pregnancy: blood sample taken
Each variable is coded 0 = No, 1 = Yes, 9 = Missing.
Date Variables
Certain date variables in DHS surveys receive special treatment. As dates are central to the calculation
of fertility and mortality rates and the selection of cases for inclusion in other analyses, there is a need
for fully specified dates (month and year) for key events. These events are:
Date of birth of the respondent
Date of first marriage or union
Dates of birth of each child
Date started using current method of contraception
Date current pregnancy started
Date of interview
Note that date of interview is always fully specified and can have no special values.
However, the respondent may not know the exact date of an event, the date (or part of it) may have
been left blank by the interviewer, or the date may have been inconsistent with other information. For
all of these situations the month and/or year part of the date variables may have either the missing
value code or one of the other special codes. As fully specified dates are required for analysis The DHS
Guide to DHS Statistics 1.25 August 2018
Program uses a process of date editing and imputation to impute exact dates (to the month and year)
for each of these dates.
The DHS Program date editing and imputation uses a multi-step process:
1) Construct logical ranges using the information reported for the date.
2) Apply isolated constraints to narrow the ranges
3) Apply neighboring constraints to further narrow the ranges
4) Ensure sufficient gap between events, further narrowing ranges
5) Random imputation within final ranges.
The result of these steps is the production of imputed dates for the key dates:
Date of birth of the respondent (month: v009, year: v010, CMC: v011, flag: v014)
Date of first marriage or union (month: v507, year: v508, CMC: v509, flag: v510)
Dates of birth of each child (month: b1, year: b2, CMC: b3, flag: b10)
Date started using current method of contraception (month: v315, year: v316, CMC: v317, flag:
v318)
Date current pregnancy started (duration of current pregnancy: v214, flag: v223)
Date of interview (month: v006, year: v007, CMC: v008)
Flag variables indicate the information originally provided as input to the imputation process for the
date. Note that although date of current pregnancy started is imputed, the variable included in the
recode file is just the duration of pregnancy, calculated by subtracting the imputed date current
pregnancy started from date of interview.
Each of these steps is described in more detail in DHS Data Editing and Imputation (Croft, 1991)
https://www.dhsprogram.com/publications/publication-DHSG3-DHS-Questionnaires-and-Manuals.cfm.
For simplicity of calculation dates of key events are presented both as month and year and in terms of
Century Month Codes.
Century Month Code
Century month codes (CMC) are calculated by taking the difference between the year of an event and
1900, multiplying by 12, and adding the month of the event:
CMC = (Year – 1900) * 12 + Month
January 1900 is CMC, February 1900 is CMC 2, January 1901 is CMC 13, and December 1999 is CMC
1200. For example, the CMC for August 2018 is:
CMC = (2018 - 1900) * 12 + 8 = 1424
In other words, 1424 months have elapsed between January 1900 and August 2018, inclusive.
Based on CMC it is possible to calculate the month and year using the following formulas:
Year = int( ( CMC - 1 )/12 ) + 1900 [int(x) is the integer part of x]
Month = CMC - ( ( Year - 1900 ) * 12 )
Guide to DHS Statistics 1.26 August 2018
The year 1900 was chosen as the reference date because all of the DHS relevant events occurred during
the twentieth or twenty-first centuries. Century Month Codes was also used in the World Fertility
Surveys (https://wfs.dhsprogram.com/) that were the precursor to The DHS Program, and all dates in
those surveys (conducted from 1976 to 1984) were in the 20th century, hence the name.
Century month codes are particularly important to check consistency of dates, to calculate intervals
between events, and in the imputation of dates when the information for an event is missing or partially
complete. The main DHS events with their corresponding recode variable names are given above.
Example:
Let us see the events for a married, sterilized respondent with three births and with event dates that
occurred as shown in the following figure. If a horizontal line is drawn from the woman’s date of birth to
the date of interview, all the events can be depicted in the line.
Variables
v011
v509
b3_1
b3_2
b3_3
v317
v008
Dates
04/1992
10/2011
07/2013
10/2014
11/2016
04/2017
08/2018
CMC
1108
1342
1363
1378
1403
1408
1424
Event
Date of birth
Date of
marriage
Date of birth
of first child
Date of birth
of second
child
Date of birth
of third child
Date of
sterilization
Date of
interview
DHS uses century month codes extensively during the process of editing and imputing data. The
advantages of the approach include the following:
When checking for consistency, use of the century month codes makes it easy to check not only
that the events occurred in chronological order, but also that there should be a minimum
interval between them. For example b3_2 - b3_1 should be greater or equal to 9 months (the
expected duration of a pregnancy).
For imputation purposes, if information were missing between two events, the random
imputation would be quite reasonable. For example, if date of birth for the second child is
unknown, that birth should have occurred between the first birth plus nine months, and nine
months before the third birth. The lower and upper limits for a random number generator are
plausible, e.g.:
random (b3_1 + 9, b3_3 - 9) = random (1372, 1394)
The use of CMC in analysis facilitates the calculation of intervals or ages at different events. Throughout
The DHS Program analysis programs, instructions such as those shown below are very common:
Respondent’s age = int( (v008 - v011)/12 ) (1424 - 1108)/12 = 26 years
Age at first birth = int( (b3_1 - v011)/12 ) (1363 - 1108)/12 = 21 years
Age at sterilization = int( (v317 - v011)/12 ) (1408 - 1108)/12 = 25 years
Age of last child in months = v008 - b3_3 1424 - 1403 = 11 months
Interval between birth 1 and 2 = b3_2 - b3_1 1378 - 1363 = 15 months
Months since sterilization = v008 - v317 1424 - 1408 = 16 months
Guide to DHS Statistics 1.27 August 2018
DHS recommends that analysts use the century month code variables when dealing with intervals or
ages at different events.
The Century Month Code works well for most DHS analyses, but there are three countries that use non-
western calendars. To date these countries are:
• Ethiopia: The Ethiopian calendar is 7-8 years behind the Gregorian (Western) calendar, and the
Ethiopian year starts around September 11th or 12th of each year (exact day varies). 1st July
2017 is 24 Sane (the 10th month) 2009 in the Ethiopian calendar. The Ethiopian calendar
consists of 12 months of 30 days, plus one month of 5 days (or 6 days in a leap year). The
century month codes in the dataset are all based on the Ethiopian calendar, but “squeezing” the
13th month into a 12 month calendar. The reference date for surveys in Ethiopia is 1 Mäskäräm
1900 in the Ethiopian Calendar, which is September 12, 1907 in the Gregorian calendar. To
approximately adjust dates to the Gregorian calendar add 92 months to the CMC.
• Nepal: The Nepali calendar is 56-57 years ahead of the Gregorian (Western) calendar, and the
Nepali year starts around mid-April of each year (exact day varies). 1st July 2017 is 17 Ashad (the
3rd month) 2074 in the Nepali calendar. The Nepali calendar is made up of 12 months of
between 28 and 32 days, and the number of days in a month can vary from year to year. The
century month codes in the dataset are all based on the Nepali calendar. The reference date for
surveys in Nepal is 1 Baisakh 1900 in the Nepali Calendar, which is April 16, 1843 in the
Gregorian calendar, for all surveys in Nepal except for the Nepal DHS 1996, in which the
reference date was 1 Baisakh 2000 in the Nepali Calendar, which is April 14, 1943 in the
Gregorian calendar. To approximately adjust dates to the Gregorian calendar subtract 681
months from the CMC, or, in the case of Nepal DHS 1996, add 519 months.
• Afghanistan: The Afghan calendar is 621-622 years behind the Gregorian (Western) calendar,
and the Afghan year starts around March 20th or 21st of each year (exact day varies). 1st July
2017 is 10 Saratan (the 4th month) 1396 in the Afghan calendar. The Afghan calendar is made up
of 12 months, the first 6 of which have 31 days, the next 5 months have 30 days, and the last
month has 29 or 30 days in a leap year. The century month codes in the dataset are all based on
the Afghan calendar with 1300 as the base year, rather than 1900. The reference date of surveys
in Afghanistan is 1 Hamal 1300, which is March 21, 1921 in the Gregorian calendar. To
approximately adjust dates to the Gregorian calendar add 255 months to the CMC.
All calculations with CMCs in these surveys work as they do for any other survey. The exception is any
analysis requiring specific years, in which case adjustments must be made to the calculated CMC as
described above. It should be noted, however, that these are approximate adjustments as the calendars
start in the middle of months and dates of events to the day would be required to calculate exact
adjustments.
Century Day Code
In DHS-7, The DHS Program introduced the collection of day of birth of children in the birth history in
addition to the month and year of birth. Adding day of birth permits calculating the age of children
more accurately. Calculating age in months using just month and year of birth and month and year of
interview meant that age in months could be off by one month in approximately half of all cases. For
many analyses this difference was small and had little effect, but for some analyses this difference could
Guide to DHS Statistics 1.28 August 2018
be more meaningful. With the introduction of day of birth, and the need to calculate age of children
more accurately, The DHS Program introduced the Century Day Code (CDC). The Century Day Code is the
number of days from the beginning of 1900. January 1, 1900 is CDC 1, January 2, 1900 is CDC 2,
December 31, 1999 is CDC 36525, and August 1, 2018 is CDC 43313. The Century Day Code is not simple
to calculate manually, but it is the same system used in Excel for calculations between dates. To find the
CDC for a date using Excel, enter the date into a field (say A1), and then, in another field (say B1) enter
=VALUE(A1). Similarly, to get the date from a CDC value in Excel, use the day(), month() and year()
functions in Excel (or simply convert the Numeric cell to a Date type cell).
The Century Day Codes are used with the date of birth of children and the date of interview and permit
the calculation of age of children accurate to the day (see Age of Children). For some dates of birth of
children, the exact date may not be fully specified at the time of data collection. For these dates an
imputation process is followed, building on the imputation process for date variables described above,
and resulting in the imputation of a century day code for all children in the woman’s birth history.
Guide to DHS Statistics 1.29 August 2018
Analyzing DHS Data
It is important that analysts be familiar with certain key aspects of DHS data to be able to calculate
accurately the indicators described in further chapters. The following sections describe some of the key
elements to pay attention to in analyzing DHS data.
Sample Design, Stratification and Sampling Weights
DHS sample designs are usually two-stage probability samples drawn from an existing sample frame,
generally the most recent census frame. A probability sample is defined as one in which the units are
selected randomly with known and nonzero probabilities. A sampling frame is a complete list of all
sampling units that entirely covers the target population.
Stratification is the process by which the sampling frame is divided into subgroups or strata that are as
homogeneous as possible using certain criteria. Within each stratum, the sample is designed and
selected independently. The principal objective of stratification is to reduce sampling errors. In a
stratified sample, the sampling errors depend on the population variance existing within the strata but
not between the strata. Typically, DHS samples are stratified by geographic region and by urban/rural
areas within each region.
Within each stratum, the sample design specifies an allocation of households to be selected. Most DHS
surveys use a fixed take of households per cluster of about 25-30 households, determining the number
of clusters to be selected. In the first stage of selection, the primary sampling units (PSUs) are selected
with probability proportional to size (PPS) within each stratum. The PSUs are typically census
enumeration areas (EAS). The PSU forms the survey cluster. In the second stage, a complete household
listing is conducted in each of the selected clusters. Following the listing of the households a fixed
number of households is selected by equal probability systematic sampling in the selected cluster.
The overall selection probability for each household in the sample is the probability of selecting the
cluster multiplied by the probability of selecting the household within the cluster. The overall
probability of selection of a household will differ from cluster to cluster. See Appendix A of the DHS
Survey Reports for most surveys for the details specific to that survey.
DHS dataset users should be aware that, in most cases, the data must be weighted. This is because the
overall probability of selection of each household is not a constant. The following describes how DHS
weights are constructed and when they should be used.
Sampling weights
Sampling weights are adjustment factors applied to each case in tabulations to adjust for differences in
probability of selection and interview between cases in a sample, due to either design or happenstance.
In DHS surveys, in most surveys the sample is selected with unequal probability to expand the number
of cases available (and hence reduce sample variability) for certain areas or subgroups for which
statistics are needed. In this case, weights need to be applied when tabulations are made of statistics to
produce the proper representation. When weights are calculated because of sample design, corrections
for differential response rates are also made.
Guide to DHS Statistics 1.30 August 2018
There are four main sampling weights in DHS surveys: household weights, household weights for the
men’s subsample, individual weights for women, and individual weights for men:
The household weight (hv005) for a particular household is the inverse of its household
selection probability multiplied by the inverse of the household response rate in the stratum.
The household weight for the men’s subsample (hv028) for a particular household is the inverse
of its household selection probability for the subsample multiplied by the inverse of the
household response rate for the subsample in the stratum.
The individual weight for women (v005) is the household weight (hv005) multiplied by the
inverse of the individual response rate for women in the stratum.
The individual weight for men (mv005) is the household weight for the men’s subsample
(hv028) multiplied by the inverse of the individual response rate for men in the stratum.
There may be additional sampling weights for sample subsets, such as anthropometry, biomarkers, HIV
testing, etc. There is only a need for the additional sample weights if there is a differential probability in
selecting the subsamples. For example, if one in five households is selected in the whole sample for
doing biomarkers, then an additional sample weight is not necessary. However, if one in five households
in urban areas and one in two households in rural areas are selected, then an additional sample weight
is necessary when estimating national levels or for any group that includes cases from both urban and
rural areas. Notwithstanding the foregoing, the DHS has customarily included both household weights
and individual weights for the subsample for the men’s surveys, normalizing the weights for the number
of households in the subset for the men’s surveys, and to the number of men’s individual interviews
even when no differential sub-selection has been used.
Response rate groups are groups of cases for which response rates are calculated. In DHS surveys,
households and individuals are grouped into sample strata and response rates are calculated for each
stratum.
Household Response Rate
Coverage: All households. Excluded are dwellings without a household (no household lives in the
dwelling, address is not a dwelling, or the dwelling is destroyed).
Numerator: Number of households with a completed household interview (hv015 = 1).
Denominator: Number of households with a completed household interview, households that live in the
dwelling but no competent respondent was at home, households with permanently postponed or
refused interviews, and households for which the dwelling was not found (hv015 in 1, 2, 4, 5, 8).
The household response rate for the men’s subsample is calculated in the same way, but restricting
numerator and denominator to household selected for the men’s subsample.
Women’s Individual Response Rate
Coverage: Women eligible for interview, usually women age 15-49 who stayed in the household the
night before the survey. In ever-married samples, women are eligible for interview only if they have ever
been married or lived in a consensual union. In some surveys, the age range of eligibility has differed,
e.g., ever-married women age 12-49.
Guide to DHS Statistics 1.31 August 2018
Numerator: Number of eligible women with a completed individual interview (v015 = 1).
Denominator: Number of eligible women with a completed individual interview, eligible women not
interviewed because they were not at home, eligible women with permanently postponed or refused
interviews, eligible women with partially completed interviews, eligible women for whom an interview
could not be completed due to incapacitation or other reasons (v015 in 1:9).
Men’s Individual Response Rates
Coverage: Men eligible for interview, usually men age 15-49, 15-54, or 15-59 who stayed in the
household the night before the survey. In ever-married samples, men are eligible for interview only if
they have ever been married or lived in a consensual union. The age range of eligibility varies from
survey to survey.
Numerator: Number of eligible men with a completed individual interview (mv015 = 1).
Denominator: Number of eligible men with a completed individual interview, eligible men not
interviewed because they were not at home, eligible men with permanently postponed or refused
interviews, eligible men with partially completed interviews, eligible men for whom an interview could
not be completed due to incapacitation or other reasons (mv015 in 1:9).
Normalization of weights
Sample design weights are produced by the DHS sampler using the sample selection probabilities of
each household and the response rates for households and for individuals. The initial design weights are
then normalized by dividing each weight by the average of the initial weights (equal to the sum of the
initial weight divided by the sum of the number of cases) so that the sum of the normalized weights
equals the sum of the cases over the entire sample. The normalization is done separately for each
weight.
Application of sampling weights
Sample weights are calculated to six decimals but are presented in the standard recode files without the
decimal point. They need to be divided by 1,000,000 before use to approximate the number of cases.
Sampling weights can be applied in two main ways:
1) A simple application of weights when all that is needed are indicator estimates.
2) As part of complex sample parameters when standard errors, confidence intervals or
significance testing is required for the indicator.
The methods of applying the weights varies across the various statistical software.
Example 1: Simple weighting
The below examples for Stata, SPSS and R produce simple weighted estimates of current use of modern
methods. Note that any standard error or confidence interval given by the below commands assume a
simple random sample and do not take into account the complex sample used in DHS surveys.
Guide to DHS Statistics 1.32 August 2018
Stata
* Open the model dataset
use "ZZIR62FL.DTA", clear
* Percentage currently using a modern method
gen modern_use = (v313 == 3)
* Create weight variable
gen wt = v005/1000000
* Tabulate indicator by region
mean modern_use [iw=wt], over(v024)
Mean estimation Number of obs = 8,348
_subpop_1: v024 = region 1
_subpop_2: v024 = region 2
_subpop_3: v024 = region 3
_subpop_4: v024 = region 4
--------------------------------------------------------------
Over | Mean Std. Err. [95% Conf. Interval]
-------------+------------------------------------------------
modern_use |
_subpop_1 | .1724828 .007062 .1586395 .1863262
_subpop_2 | .2148514 .0102385 .1947815 .2349213
_subpop_3 | .3124085 .0096652 .2934622 .3313547
_subpop_4 | .1928716 .0099471 .1733729 .2123704
--------------------------------------------------------------
SPSS
* Open the model dataset.
get file = "ZZIR62FL.SAV".
* Percentage currently using a modern method.
compute modern_use = (v313 = 3).
* Create weight variable.
compute wt = v005/1000000.
weight by wt.
* Tabulate indicator by region.
means tables=modern_use by v024 /cells mean count.
Report
modern_use
V024 Region
Mean
N
1 Region 1
.1725
2863
2 Region 2
.2149
1610
3 Region 3
.3124
2300
4 Region 4
.1929
1574
Total
.2231
8348
Guide to DHS Statistics 1.33 August 2018
R
# load libraries
library(foreign)
library(plyr)
# Open the model dataset
dta <- read.dta("ZZIR62FL.dta", convert.factors = FALSE)
# Percentage currently using a modern method
dta$modern_use <- ifelse(dta$v313==3,1,0)
# Create weight variable
dta$wt <- dta$v005/1000000
# Tabulate indicator by region
ddply(dta,~v024,summarise,mean=weighted.mean(modern_use, wt))
v024 mean
1 1 0.1724828
2 2 0.2148514
3 3 0.3124085
4 4 0.1928716
Complex sample designs
However when standard errors, confidence intervals or significance testing is required, then it is
important to take into account the complex sample design. For the complex sample design, it is
necessary to know three pieces of information – the primary sampling unit or cluster variable, the
stratification variable, and the weight variable.
The primary sampling unit variable is typically v021 (or hv021 or mv021). If this variable does not
contain the PSU number then, in all but a few surveys, the cluster number (v001 or hv001 or mv001) can
be used. In most surveys there is a one-to-one correspondence between the cluster number and the
PSU number, but in a small number of surveys, for example some of the surveys in Egypt, the PSU and
cluster number do not match one-to-one – see Appendix A in the DHS survey reports for details of the
sampling design.
The stratification variable is typically v023 (or hv023 or mv023), however the stratification variables
have not been consistently defined in many surveys and may need to be created. It is best to check the
sample design in Appendix A of the DHS survey reports to verify the stratification used in the design of
the sample. In many surveys, the stratification is based on urban and rural areas in each region (v024 x
v025).
The weight variable is v005 (or hv005 or mv005) divided by 1,000,000.
To apply the complex sample design parameters in estimating indicators each of the statistical software
use a different set of commands applying the sample design and producing the indicator estimates:
Stata: svyset and svy: commands
SPSS: csplan, csdescriptives and cstabulate commands
R: survey package, including svydesign and other svy functions.
Guide to DHS Statistics 1.34 August 2018
Example 2: Complex sample design weighting
The below examples for Stata, SPSS, and R, continuing on from example 1, demonstrate the use of the
complex sample designs for estimates of current use of modern methods, together with standard errors
and confidence intervals.
Stata
* define strata
gen stratum = v023
* alternative strata based on region and urban/rural
* egen stratum = group(v024 v025)
* complex sample design parameters
svyset v021 [pw=wt], strata(stratum)
svy: mean modern_use, over(v024)
Survey: Mean estimation
Number of strata = 8 Number of obs = 8,348
Number of PSUs = 217 Population size = 8,347.9996
Design df = 209
_subpop_1: v024 = region 1
_subpop_2: v024 = region 2
_subpop_3: v024 = region 3
_subpop_4: v024 = region 4
--------------------------------------------------------------
| Linearized
Over | Mean Std. Err. [95% Conf. Interval]
-------------+------------------------------------------------
modern_use |
_subpop_1 | .1724828 .0154383 .1420481 .2029175
_subpop_2 | .2148514 .0140044 .1872434 .2424594
_subpop_3 | .3124085 .0357686 .2418951 .3829219
_subpop_4 | .1928716 .0139509 .1653691 .2203742
--------------------------------------------------------------
SPSS
* Define strata.
compute stratum = v023.
* alternative strata based on region and urban/rural.
* compute stratum = v024 * 2 + v025.
* Complex sample design parameters.
csplan analysis
/plan file='C:\Temp\DHS_IR.csplan'
/planvars analysisweight=wt
/design strata=stratum CLUSTER=v021
/estimator type=wr.
* Complex Samples Descriptives.
csdescriptives
/plan file='C:\Temp\DHS_IR.csplan'
/summary variables=modern_use
/subpop table=v024 display=layered
/mean
/statistics se cin
/missing scope=analysis classmissing=exclude.
Guide to DHS Statistics 1.35 August 2018
Univariate Statistics
V024 Region
Estimate
Standard Error
95% Confidence Interval
Lower
Upper
1 Region 1
Mean
modern_use
.1725
.01544
.1420
.2029
2 Region 2
Mean
modern_use
.2149
.01400
.1872
.2425
3 Region 3
Mean
modern_use
.3124
.03577
.2419
.3829
4 Region 4
Mean
modern_use
.1929
.01395
.1654
.2204
R
library(survey)
# Complex sample design parameters
DHSdesign<-svydesign(id=dta$v021, strata=dta$v023, weights=dta$wt, data=dta)
# tabulate indicator by region
svyby(~modern_use, ~v024, DHSdesign, svymean, vartype=c("se","ci"))
v024 modern_use se ci_l ci_u
1 1 0.1724828 0.01543828 0.1422244 0.2027413
2 2 0.2148514 0.01400441 0.1874033 0.2422995
3 3 0.3124085 0.03576857 0.2423034 0.3825136
4 4 0.1928716 0.01395092 0.1655283 0.2202149
Notes and Considerations
The sum of the sample weights only equals the number of cases for the entire sample and not for
subgroups such as urban and rural areas.
Sample weights are inversely proportional to the probability of selection and are used to correct for the
under- or over-sampling of different strata during sample selection. If weights are not used, all
calculations will be biased toward the levels and relationships in the over-sampled strata. Comparisons
of regression coefficients, as well as rates, percentage, means, etc. coming from different surveys are
only valid if weights have been used to correct for the sample designs of the different surveys.
An option to use sample weights is included in virtually all procedures in all statistical packages. Weights
tend to increase the size of standard errors and confidence intervals, but not by large amounts.
Recommendations against the use of weights for estimating relationships, such as regression and
correlation coefficients, in prior versions of the Guide to DHS statistics are no longer DHS policy.
For more information on DHS sample design, stratification and sample weights, see the DHS Sampling
and Household Listing Manual (https://www.dhsprogram.com/publications/publication-DHSM4-DHS-
Questionnaires-and-Manuals.cfm). See also the DHS YouTube videos:
Part I: Introduction to DHS Sampling Procedures
Part II: Introduction to Principles of DHS Sampling Weights
Part III: Demonstration of How to Weight DHS Data in Stata
Part IV: Demonstration of How to Weight DHS Data in SPSS and SAS
Guide to DHS Statistics 1.36 August 2018
Households
Households are the primary unit selected for inter