V I T A L S T A T I S T I C S

C O L L E C T I O N

I N

A F G H A N I S T A N

(A PILOT STUDY)

by

Faizullah Kakar, PhD

RESEARCH AND ADVISORY COUNCIL

OF

supported by a grant from W.H.O. VITAL STATISTICS COLLECTION IN AFGHANISTAN

RESEARCH AND ADVISORY COUNCIL

OF AFGHANISTAN

March 17, 1991 INTRODUCTION For planners and workers of public health and community medicine, information on prevailing health conditions in a community is of paramount importance. Without such information health projects cannot be properly planned nor can their effects be evaluated. In addition, vital statistics are valuable as a reflection of a variety of conditions in a community. Infant and child mortality statistics, for example, which are derived from vital statistics, reflect the level of nutrition of a population, its sanitation, and its economic and social development.

In 1989 when I was assigned to head the Afghan Interim Government (AIG) Department of Preventive Medicineand I began planning preventive health services for over six million people residing in the liberated countryside of Afghanistan, the tremendous need for having vital statistics became apparent to me. Motivated by this need,I sought to propose a method of vital statistics collection in Afghanistan that would be culturally acceptable and simple enough to be duplicated everywhere in the country. Involving the mosque and mullah system in the collection of vital statistics seemed very logical and appropriate.

Ninety -nine percent of the families in all parts of Afghanistan have a mullah who leads prayer five times a day and performs services for the family at times of births and deaths. The mullah, in addition to leading prayers, is called to attend funerals, to call adhan in the baby's ear at birth, to preside at weddings, and to perform other services.

The mullah is the most trustworthy individual in the community and is also the most likely to be educated enough to read, write, and count. With these attributes we believed he could be trained and trusted to use simple forms to report vital health statistics. He would also fill the position better than a government official who may be suspected by the people of using the statistics against them. For example, it is well known that previously many families would hide their male children from the government in order to avoid the draft. 2 To pilot test a method of vital statistics collection involving the network of mosques and mullahs,a six month study was conducted under a W.H.O. grant (E17/180/2 AFG) at three sites in different provinces in Afghanistan between May and December 1990. This paper reports our findings.

OBJECTIVES

The specific objectives and their measures were:

1. To assess the feasibility of incorporating the mosque network to obtain vital statistics in Afghanistan.

- -To be measured qualitatively by whether the mullahs showed a cooperative attitude in their ,relationship with the officers of the study, evidenced by taped interviews.

- -To be measured quantitatively by whether the forms were properly filled out and promptly returned, and by whether the statistics appeared reasonably valid in light of statistics obtained in the refugee camps and by survey methods.

2. To obtain vital statistics including number of births and number of deaths as well as size of population base from a village with stable population in three different provinces.

-- Actual birth rate, mortality rate, and cause -specific mortality rate were to be measured at each site and overall.

METHODS

A. Selection of sites

In selecting sites for testing the feasibility of the proposed method of vital statistics collection, we spent a great deal of time searching for the right towns. The stability of the population size and a low emigration and immigration pattern were important considerations at each site.

The towns originally selected in Nangarhar, Kunar, and Paktia Provinces did not pass our specified criteria and thus were disqualified. The main problem was the influx and outflux of Afghan refugees to and from .

The sites finally selected for the study were:

1. Chak in Wardak Province (See Map 1.) 2. Saroza (Sarhawza) in Paktika Province (See Map 2.) 3. GiruDeecy (Giru) in Ghazni Province (See Map 3.). 3

These towns were selected following lengthy interviews with commanders and mujahideen from these areas and after interview information was verified by our visiting team to the actual sites. (Demographic information about each site is given in the section on Results.)

B. Selection of Mullahs

In each town site there are senior mullahs called Moulavis who preach in the larger mosques. Each of these Moulavis have one or more smaller mosques under them which are manned by one of their students or other junior mullahs. We will separate them for discussion in this paper by referring to the senior mullahs as Moulavis and the junior mullahs as Mullahs with a capital letter. After the sites were selected, we negotiated with the local commanders for permission to approach all the mullahs at each site for the purpose of conducting the study. The P.I. explained the objectives of the study to the various commanders or their representatives in . No commander refused permission. After obtaining permission from the commander, the local mujahideen administration helped us perpare a list of all the mullahs at each site and invite them to one of the town mosques where the RACA team explained the studyand its purpose and answered any questions the mullahshad. Again no mullah in any site refused to cooperate.

Since never before in Afghan history had the mullahs been asked to undertake such a job, they consistently askedwhy were they selected for thisjob? Our team answered: "Mullahs were selected because we want the truestatistics about deaths and births. It is only on the basis of sound statistics that a nation can make sound judgements for the health of its people. We need the help of people such as you who are constantly calling people to be truthful."

The number of Moulavis, Mullahs, and mosques ineach site were as follows:

In Chak, Wardak No. Moulavis = 6 No. Mullahs = 16 No. Mosques = 22

In Saroza, Paktika No. Moulavis = 5 No. Mullahs = 6 No. Mosques = 11 4

In GiruDeecy, Ghazni No. Moulavis = 4 No. Mullahs = 9 No. Mosques = 13

For the purpose of this study thevital statistics unit within each site wasa group of mosques under one Moulavi. It was the Moulavi whowas responsible for recording the statistics and forwarding themon to us. Even though we expected cooperation from all theMullahs, too, by making the Moulavi the person responsiblefor the forms, we avoidedsome confusion which might be causedwhen some student Mullahs move from mosque to mosque under thesame Moulavi.

The geographical location of eachstatistical unit within the site was usuallya well- defined area called a Kalay (agroup of related families). In a few locations, the boundaries interdigitated, but each Moulavi hada clear idea of which families were part of hismosque "catchment area" and could list the names of the households heserved.

C. Compensation to the mullahs

Each Moulavi received 500 Pakistanirupees /month and a set of the Holy Quran Tafseer (text, translation,and commentary). The Mullahs also received Tafseer but didnot receive the monthly honorarium.

D. Determination of population size ofa statistical unit

For the purpose of obtaining denominator datawe obtained copies of the household lists of the constituenciesof each of the mosques. These lists contain the name of the head of each family and the number in each household. The lists are kept and updated by the Moulavi for thepurpose of distributing sacrificial meat during Eid (religious holidays) and on other occasions. The lists are also utilized to plan community events such as weddings and estimate theexpenses. To double check these lists we utilized the help of the village dumm. A village dumm performs a variety of jobs such as shaving heads and beards, circumscision, informing people of wedding invitations, and finding cooking utensils for weddings. Most relevant to our study, the social status of the dumm, unlike other unrelated men, allows him toenter a household and the women folk do not cover their faces from him. For these reasons, the dumm has a great deal of information about the members of each household heserves and any vital event that may take place in his locality. 5

Because dumms were available at every site and were easily employable, we asked the dumms to count the number of families in each statistical unit and then specify the number in each household. Independent information from the dumm in three units at the Chak site agreed well with the mosque lists. In some cases the mosque list was found to somewhat underestimate the population, particularly in respect to newborns. For all our denominator data we used a combination of the mosque lists and the information provided by the dumms, sometimes the mullah and the dumm would work together and sometimes independently.

E. Vital Statistics Collection

At each site a local officer was hired to coordinate the local activities, to be responsible for the distribution and collection of vital statistics forms, to transfer payments to each Moulavi, to oversee the dumms' work and to report promptly to the Peshawar -based manager any problem in data collection. Initially the RACA team visiting the various sites provided the forms for the collection of mortality and birth statistics (see appendices) to the Moulavis. Subsequently the job of forms distribution was left to the local officers. Moulavis were requested to provide a form for each month, whether a vital event took place in their unit or not. Each form was signed by the responsible Moulavi and given to the local officer. The local officer would give the forms to the officers visiting from Peshawar, or he himself would bring the forms to Peshawar (where the study base is located). No person other than these officers werreallowed to transfer the forms. Originally we planned to transfer data every month. However because of the selection of sites deep inside Afghanistan, the transfer schedule was modified to be every two months. The variables on which data was gathered are as follows:

Births Name of newborn, Sex, Name of the father, Date of birth, Name of mosque, Moulavi, and site.

Deaths Name of deceased, Name of father of deceased, Ageof deceased, Date of death, Cause of death (classified as disease, injury, stillbirth), Name of mosque, Moulavi, and site. 6

Data collection took place during a six month period. The timeline for each site was as follows:

In Saroza from May 25 to November 25, 1990. In GiruDeecy from June 5 to December 5,1990. In Chak from July 1 to December 30, 1990.

F. Data checking and recording at the study center

Whenever the data arrived they were carefully checked to see if all the forms were complete or if all the names could be read accurately. Any ambiguity found was referred to the corresponding Moulavi for clarification. Each case of birth was assigned a serial number and each case of death was assigned a serial (different and serial) number. Following this the data was coded for computer entry and keyed into an IBM compatible computer using SPSSS /PC + V3.1 program.

As one check of the accuracy of the data, we made a list of all cases of children that died during the study period whose age at death suggested that they should have been born during our study. Using the death data the Moulavis had provided, we searched to see if the case was also listed among the births. After finding the case among the births we would then see if the age at death jived with the birth date of the child. All cases of deaths of infants who were born during the study were in fact also listed in the birth forms filled out weeks or months prior to the date of death. Ages at death also agreed reasonably, although some were a few days off.

G. Data analysis The data was entered into the SPSS -PC +V3.1 program and the data list printout was checked against our hand coded version. The following statistics were generated for each site and overall:

Mortality: a) Crude mortality rate b) Infant mortality rate c) Sex -specific infant mortality rate d) Stillbirth rates e) Perinatal mortality rates f) Cause -specific mortality rates g) Trend in mortality rate over time 7

Births: a) Total birth rates b) Sex -specific birth rates c) Male to female birth ratio d) Percentage of births by sex e) Trend in births over time

In addition to the above statistics, population natural growth rate and doubling time were also calculated. Hypotheses generated by the data were tested by the chi - square statistical method. Mortality and birth rates were calculated per 1000 people per year. Since our data was collected for six months, in calculating rates we multiplied the observed frequencies by a factor of two.

RESULTS

A. Demographics Table 1 demonstrates the number of families, populationand average family size in eachstatistical unit. The overall population base was 12,795 people. The average family size over all sites was 7.31. Of the three study sties, Chak had the largest population size (5945) followed by Saroza(4428) and GiruDeecy (2422).

B. Mortality findings Table 2 shows crude mortality rates for eachsite. Mortality rates of Chak (15.8) and GiruDeecy (14.0) wereclose to each other. Saroza (32.1) however differed from theother two sites for having a mortality rate that was twice theothers. Overall mortality rate of the three sites was21.1 per 1000 population per year. Time trend in mortality rates (Table 3) showsthat the mortality rate gradually decreased during thestudy period indicating that mortality during the summer months washigher than in the Fall (See also Graph 1.).

Table 4 shows the infant mortality dataseparately for each site. The three sites differed considerably intheir infant mortality rates. The overall infant mortality rate was 160.6 per 1000 live births. The data on infant mortality was further analyzed to examine the sex -specificinfant mortality (overall). As Table 5 shows, the mortality rate for male infants was 154.8/1000 live male births and for female infants 169.8/1000 live female births. The difference between the two rates was tested by chi -square test andfound to be non -significant (p >0.9). 8

Stillbirths and perinatal mortality shown in Table 6 suggest an unusually large stillbirth rate in GiruDeecy. Furthermore it appears that there is a cluster of these stillbirth events in one particular statistical unit served by Moulavi #11.

Table 7 presents a summary of Tables 4 and 6. The stillbirth rates of the three sites were further analyzed to test the null hypothesis that there is no difference between the various rates. Using the chi -square statistic, the null hypothesis is rejected with p < 0.025 showing that the GiruDeecy stillbirth rate is significantly greater than the other rates.

C. Birth Rates Findings

Table 8 details the birth rates by varioussites. The overall birth rate was 42.8/1000 pop /year. Examination of birth statistics separated for male and femalebirths showed that in all three sites over 60% of the reportedbirths were male births suggesting some sort ofreporting bias. (This will be further discussed.) This bias appears to be consistant at all sites because the male tofemale birth ratios are appreciably similar throughoutthe three sites (Table 9). Time trend in birth rates is shown in Table10 and Graph 2. No clear trend existed in birth rates. Utilizing birth and mortality rates, thenatural growth rate of population at each site as well astheir population doubling time were calculated. The results are shown in Table 11.

DISCUSSION Feasibility of Collection Method

This method of collection ofvital statistics through the network of mosques and mullahsis upheld as a viable method at three sites inAfghanistan. The overall birth rate (BR) of 43/1000 pop /year, crudemortality rate (MR) of 21/1000 pop /year, andinfant mortality rate (IMR)of 161/1000 live births are in the same range asthose reported for Afghanistan in 1983 (UNICEF, State ofthe World's Children, 1986): BR 50/1000, MR 27/1000,and IMR 195/1000 live births.

In the same line, the IMRcalculated from a survey of refugee camps in Pakistan was156/1000 live births about five years ago, although theinfant mortality rate has improvedgreatly in the camps up until the latestreport of 1989 -90 when it was only 82/1000live births (CDC Survey Afghan Refugee Camps, Pakistan, 1990). On the other hand, theOffice of the United Nations Co- ordinator forHumanitarian and Economic 9 Assistance Programmes Relating to Afghanistan in their September 1988 report predicted an increase in infant mortality from 190 to 220 per 1000 live births in Afghanistan after the war.

As stated in the Methods above, one check of the accuracy of the data was by making a list of all cases of children that died during the study period whose age at death suggested that they should have been born during our study. Using the death data the mullahs had provided, we searched to see if the case was also listed among the births. After finding the case among the births we would then see if the age at death jived with the birth date of the child. The correspondence between infant deaths recorded and their previously recorded births provides evidence that the vital events were recorded properly. Because the previous months' forms had already been sent to Peshawar and no copies were being made, this correspondence seems to represent a real effort by the mullahs to record events accurately.

All interviews in Peshawar with the commanders or their representatives and all taped interviews showed a cooperative and open attitude except perhaps one Moulavi (Moulavi #1 from Chak, Wardak) who could not be dissuaded from his suspicions that this effort had an underlying political aim. The fact that he recorded only one birth and one death for his 553 constituents during the entire six month period also brought his data under suspicion (Tables 2 and 8). However, the local officer found no evidence that he had missed any events so the data was accepted.

The good efforts of the mullahs were also evident when they themselves brought it to our attention, before the data was analyzed, that some of the girl births may be being missed. They pointed out that traditionally when a boy is born a gun is fired in the air, while a girl does not enjoy this reception. The gunfire can be heard quite a distance and the mullah can easily investigate the occasion to discover the boy births, but the mullahs felt that some girl births may be missed. Our initial supposition that the mullah would be called to say the adhan (Islamic call to prayer) in the ear of newborns was only true part of the time because other elders could also perform this ceremony.

The data indeed showed more than 60% of the births reported as male at every site. The consistency of the male to female ratio of 1.58 at all sites could perhaps be explained by the fact that the gunfire to announce a boy's birth is a Pushtun custom and all the sites were predominantly Pushtun. Still it was surprising that even at Chak, the more highly educated site, the bias was consistently observed. It will be interesting to see if the bias is also present in the non- lo Pushtun areas of Afghanistan.

We have no evidence that any families ever reported the birth as male when it was actually female so we could make some estimates of actual birth rates if there were the same number of girl births as boy births reported. Making this adjustment would change the overall birth rate from 43/1000 pop /year to 52/1000 pop /year, much closer to the UNICEF reported BR for 1983 of 50 /1000 pop /year.

In a similar adjustment of raising the birth rate to compensate for unreported girl births, the infant mortality rate would change from 161/1000 live births to 131/1000 live births, assuming that our mortality data is accurate, having no reason to suppose that deaths have gone unreported.

To overcome for the bias of missing girl births in the future, we recommend that the village dumm be employed to notify the mullahs of any births as well as to assist with the population census data.

A traditional attitude toward girl children also was evident when the mullahs informed our team that some of the families were reluctant to provide the girls' names. We instructed the mullahs to record just the sex of the child and the father's name to identify these infants (i.e. Gul Khan's daughter).

We did not expect the mullahs to be able to guess the cause of death except to differentiate disease from injury. However, in Chak the mullahs on their own noted an epidemic of "gozurn" which may be some type of paralysis from meningitis or polio or tetanus causing several deaths. In our future efforts to coordinate our reports with the medical teams in the area, we hope to develop the potential of this project for disease surveillance. We also have added a category for maternal deaths so that future reports will include maternal mortality figures.

Actual Vital Statistics Collected As noted above, the statistics and their trends are consistent with the other reported data for the refugees and for Afghanistan before the war.

The differences between sites are quite interesting and bear some review. Chak is the site closest to , having the most schools, including schools for girls, and having the most access to health care. In Chak there were two boys' schools, two madressas (religious schools) for boys, and three smaller girls' schools, altogether making 1045 11 students. At Saroza there were three boys' schools with 700 pupils altogether, and at GiruDeecy there was only one religious school with 40 students.

As with other developing countries, these factors may be associated with the health of the area and the vital events which occur there. Even for the small sample and short time period of observed events in our study, we can see a general association between education and population growth rate (See Table 12.).

Because GiruDeecy is developmentally quite isolated, its low infant mortality rate was initially a surprise. Its IMR was 34/1000 live births compared to 129 at Chak and 252 at Saroza. When we noted the astounding stillbirth rate (108/1000 births), though, the infant mortality rate was viewed more in perspective.

Analyzing perinatal mortality rates (stillbirths plus deaths of infants under two weeks old) between sites puts GiruDeecy more in line with the other sites. Overall perinatal mortality was 115/1000 births with 123 at GiruDeecy, 144 at Chak, and 85 at Saroza (See Table 7.).

The high stillbirth rate in GiruDeecy on further evaluation showed that the majority of the stillbirths (71 %) had occurred in only one statistical unit (the mosques served by one Moulavi). This geographical clustering suggests a non- random occurrence perhaps caused by a local environmental factor.

We have four possible theories to explain the stillbirth rate in GiruDeecy. One, there may have been an environmental pollution by insecticides or wartime chemical bombs. Two, there may have been narcotics abuse during pregnancy. Three, there may have been inappropriate use during pregnancy of available pharmaceuticals which were commonly being used for pain, fever, or nausea. Four, there may have been an epidemic of malaria among the mothers. We hope to visit GiruDeecy with a medical team to conduct a quick case -control study of the stillbirth events in order to identify the causal factor.

Although perinatal mortality was lowest at Saroza, crude - mortality rate was 32.1/1000 pop /year, more than twice that in either Chak (15.8) or GiruDeecy (14.0). This can be partially attributed to the high number of infant deaths in Saroza. Twenty -nine infant deaths occurred out of 71 total deaths, that is, 41% of the deaths in Saroza were infants, while 28% were infant deaths in Chak and 12% in GiruDeecy.

Providing a category for stillbirths in "cause of death" was 12 generally very useful for the perinatal and infantmortality data and indicates that we may also be ableto collect data on maternal deaths in the future.

From the "cause of death" columnwe also learned that in this six month period therewere few deaths (8/12795 = 0.6/1000 pop) reported due to injury whichwere almost all deaths attributed to gunshots among adultmen. There were no other disasters such as earthquqkesor floods or aerial bombing at these sites during this time although theseevents have occurred more recently at other places.

We are elated to have discovered several tools whichare helpful for statistics collection. The household list in each mosque was not known to us before embarkingon this project. Likewise, utilizing the local knowledge of the village dumm as a resource for statistics collectionwas a serendipitous idea of one officer which proved to be another short cut in the collection of denominator data.

The household list from each mosque has provided a very strong statistical unit for the collection of data. If an unusual event in one unit would skew the data, that unit can be withdrawn from analysis along with its corresponding denominator data.

Analysis of the household lists shows the smallest household size in GiruDeecy where the average size of household was 5.2 persons, while in Chak it was 9.0 persons per household and in Saroza it was 7.1 persons. A survey in the refugee camps in Pakistan in 1982 -83 found 6.2 -6.5 persons per household (Operations Manual for Afghan Refugees Health Program in Pakistan, UNHCR, 1986, p.6). Although it is possible that the families were newer in GiruDeecy, it is more likely that there was a difference in definition of household because we did not define household in advance of the discovery of the lists. The household size was consistent among the Moulavis at each site, however.

CONCLUSION

Having completed the six month pilot study of a method of vital statistics collection in Afghanistan utilizing the network of mosques and mullahs, the results show that the method is scientifically sound and socially acceptable in the sites studied.

The entire network utilized to collect the data included the Maulavis and Mullahs, the village dumms, and the field officers chosen by local commanders. Through these people we 13 tapped two pervasive and age-old elements of Afghansociety, the exceedingly stable mosquenetwork which is presentin serving rich and poor alike,and both urban and rural areas, We the traditional informationsystem of the village dumm. also incorporated the newpolitical structure of the mujahideen who liberated the areasunder study.

The household list fromeach mosque provided a verystrong statistical unit for thecollection of data. The vital events of each unit wereaccompanied by the denominator data of that same unit. The denominator data, orpopulation through census, was furtherverified by the village dumm who his traditional role knowsevents on the inside of the households. All data was certified bythe mujahideen administration who were anxious tobe sure everything was properly recorded in theirdistrict. Ghazni; a At Chak, Wardak; Saroza,Paktika; and GiruDeecy, (junior total of 15 Moulavis(senior mullahs) and 31 Mullahs mullahs) collected the data onvital events over a six month period. The interest and enthusiasmof the mullahs overall was evident in manyaspects of the project andtheir contribution to the success ofthe data collection. cannotbe denied. As with any new method,the pilot study revealedpoints where changes can be made toimprove the method. In the future, we would like to utilize thevillage dumm to help collectbirth Also for data to avoidunderrepresentation of femalebirths. future studies, we arechanging the mortality forms toadd the person the category of maternaldeaths and the gender of written, the sex is deceased. When Pushtu names are automatically specified, butto make the methodgeneralizable this to non -Pushtun groups, wewill need to ask for information. tested in other areas ofAfghanistan, The method needs to be The mosque in other languages and amongother ethnic groups. system is pervasive inAfghanistan, and in most areas a traditional system like thevillage dumm is also present.

Although collecting accuratedata by itself is a very important step in preventivemedicine programs, the data we well, such as received demands certainfollow -up actions as investigating the stillbirthsin GiruDeecy and theepidemic We hope to be able tocoordinate our of "gozurn" in Chak. develop future reports with themedical teams in the area to the potential ofthis project for diseasesurveillance. sites in The actual statistics fromdata collected over three Afghanistan (total 12795 pop)during the last six months of /year and a 1990 showed a crudemortality rate of 21/1000 pop 14 birth rate of 43 /1000 pop /year, adjusted to 52/1000 pop /year to make up for under- reporting of girlbirths.

The overall infant mortality rate of 161/1000 livebirths needs to be considered in light of the high stillbirth rate during this time period (45/1000 births overall) and the problem defining the denominator due to missed girlbirths.

Site -specific data will be useful in planning the level and type of interventions for different sites in post -war Afghanistan. For instance, schools are a priority in GiruDeecy for development and they will also improve the health of the people while preparing the environment for more efficient use of pharmacies or clinics which may be brought later. We strongly recommend that the vitalstatistics collection be continued and expanded because of the importance ofthis data in assessing current needs and in making futureplans as well as in ongoing evaluationof programs as they are put in place. We believe that this method is usefulbecause it uses an already established networkof mosques which is stable and pervasive in the Afghan society. The nature of this network provides an inexpensive and reliable methodof statistics collection which is generalizable to all ofAfghanistan and, once established, couldcontinue to provide data under almost any type of politicalatmosphere. page 15

VITAL STATISTICS PROJECT IN AFGHANISTAN 1990

TABLE 1. DEMOGRAPHIC INFORMATION ** * * * * * * * * * * * * * * * * * * * * * * * ** * * * * **

SITE ID* Number Population Average Moulavi of Families Family Size

CHAK, 1 67 553 8.3 WARDAK 2 131 1283 9.8 3 88 778 8.8 4 95 735 7.7 5 143 1236 8.6 6 137 1360 9.9

Total 661 5945 9.0

SAROZA, 7 157 1126 7.2 PAKTIKA 8 216 1487 6.9 9 80 599 7.5 10 168 1216 7.2

Total 621 4428 7.1

GIRUDEECY, 11 106 600 5.7 GHAZNI 13 158 730 4.6 14 92 420 4.6 15 112 672 6.0

Total 468 2422 5.2

ALL SITES 1750 12795 7.31

2- page 16 VITAL STATISTICS PROJECT IN AFGHANISTAN 1990

TABLE 2. MORTALITY RATES * * * * * * * * * * * * * * * * * * * * * * * **

Site ID $ Deaths in Six Months Mortality Moulavi /1000 pop /year Male Female Total

CHAK, 1 1 0 1 3.6 WARDAK 2 6 3 9 14.0 3 7 3 10 25.7 4 4 4 8 21.8 5 10 2 12 19.4 6 7 0 7 10.3

Total 35 12 47 15.8

SAROZA, 7 5 6 11 19.5 PAKTIKA 8 9 8 17 22.9 9 9 13 22 73.5 10 11 10 21 34.5

Total 34 37 71 32.1

GIRUDEECY, 11 3 4 7 23.3 GHAZNI 13 3 1 4 11.0 14 1 1 2 9.5 15 2 2 4 11.9

Total 9 8 17 14.0

ALL SITES 78 57 135 21.10 page 17

VITAL STATISTICS PROJECT IN AFGHANISTAN 1990

TABLE 3. TIME TREND* IN MORTALITY RATES ** *********** * * * * * * * * * * * * * * * * * * * * * * * ** * * * * **

(All Sites)

June 22 - July 22 - Aug 22 - Sep 22 - Oct 22 - July 21 Aug 21 Sep 21 Oct 21 Nov 21

37.2 20.4 22.8 18.0 16.8

*Since all sites did not start on the same date, statistics only for the five months during which all sites were collecting data are included.

* *Per 1000 pop /year. page 18

VITAL STATISTICS PROJECT IN AFGHANISTAN 1990

TABLE 4. INFANT MORTALITY RATES * * * * * * * * * * * * * * * * * * * * * * * * ** * * * * **

SITE ID Infant Deaths 6 Months Infant Mortality Moulavi /1000 live births Male Female Total

CHAK, 1 0 0 0 0.0 WARDAK 2 4 1 5 250.0 3 3 1 4 121.2 4 3 0 3 428.6 5 1 0 1 52.6 6 0 0 0 0.0

Total 11 2 13 128.7

SAROZA, 7 3 1 4 137.9 PAKTIKA 8 5 1 6 206.9 9 3 8 11 458.3 10 2 6 8 242.4

Total 13 16 29 252.2

GIRUDEECY, 11 1 0 1 76.9 GHAZNI 13 0 0 0 0.0 14 1 0 1 83.3 15 0 0 0 0.0

Total 2 0 2 34.5

ALL SITES 26 18 44 160.6 page 19 VITAL STATISTICS PROJECT IN AFGHANISTAN 1990

TABLE 5. SEX -SPECIFIC INFANT MORTALITY ******** * * * * * * * * * * * * * * * * * * * * * * * ** * * * * **

(All Sites)

MALE FEMALE

LIVE BIRTHS 168 106

INFANT DEATHS 26 18

Infant Mortality /1000 live births 154.8 169.8

Relative Mortality = 169.8/154.8 = 1.09*

*Chi square value for the difference between sex -specific mortality rates = 0.026, p >.90 page 20

VITAL STATISTICS PROJECT INAFGHANISTAN 1990 TABLE 6. PERINATAL MORTALITY RATES **** * * * * * * * * * * * * * * * * * * * * * * ** * * * * * **

SITE ID # Stillbirths/6 Mo Deaths Perinatal deaths /6Mo Moulavi <2wks Male Fem Total Male Fem Total

CHAK, 1 0 0 0 0 0 0 0 WARDAK 2 0 1 1 5 4 2 6 3 1 1 2 4 4 2 6 4 0 0 0 3 3 0 3 5 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0

Total 1 2 3 12 11 4 15

Rates Stillbirths /1000 births Perinatal mortality 28.8 144.2

SAROZA, 7 0 2 2 1 1 2 3 PAKTIKA 8 0 0 0 1 1 0 1 9 0 1 1 2 1 2 3 10 0 0 0 3 1 2 3

Total 0 3 3 7 4 6 10

Rates Stillbirths /1000 births Perinatal mortality 25.4 84.7

GIRUDEECY, 11 3 2 5 0 3 2 5 GHAZNI 13 0 1 1 0 0 1 1 14 0 0 0 1 1 0 1 15 0 1 1 0 0 1 1

Total 3 4 7 1 4 4 8

Rates Stillbirths /1000 births Perinatal mortality 107.7 123.1

ALL SITES 4 9 13 20 19 14 33

Rates Stillbirths /1000 births Perinatal mortality 45.3 115.0

Perinatal deaths = Stillbirths +Infant deaths <2 weeksold Perinatal mortality rate = Perinatal deaths /1000births page 21 VITAL STATISTICS PROJECT IN AFGHANISTAN 1990

TABLE 7. INFANT AND PERINATAL MORTALITY AND STILLBIRTHS BY SITE ******** * * * * * * * * * * * * * * * * * * * * * * * ** * * * * **

Site Infant Perinatal Stillbirths Mortality* Mortality ** **

Chak, Wardak 128.7 144.2 28.8

Saroza, Paktika 252.2 84.7 25.4

GiruDeecy, Ghazni 34.5 123.1 107.7 * **

All sites 160.6 115.0 45.3

* per 1000 live births ** per 1000 births (live + still) * ** chi square of difference with two degrees of freedom = 7.72, p < 0.025. page 22

VITAL STATISTICS PROJECT IN AFGHANISTAN 1990

TABLE 8. BIRTH RATES * * * * * * * * * * * * * * * * * * * **

Site ID * Births in Six Months Percent Births Moulavi /1000 pop/ yr MaleFemale Total Male Female

CHAK, 1 1 0 1 100.0 0.0 3.6 WARDAK 2 11 9 20 55.0 45.0 31.2 3 16 17 33 48.5 51.5 84.8 4 6 1 7 85.7 14.3 19.0 5 12 7 19 63.2 36.8 30.7 6 15 6 21 71.4 28.6 30.9

Total 61 40 101 60.4 39.6 34.0

SAROZA, 7 14 15 29 48.3 51.7 51.5 PAKTIKA 8 21 8 29 72.4 27.6 39.0 9 15 9 24 62.5 37.5 80.1 10 21 12 33 63.6 36.4 54.3

Total 71 44 115 61.7 38.3 51.9

GIRUDEECY, 11 9 4 13 69.2 30.8 43.3 GHAZNI 13 12 5 17 70.6 29.4 46.6 14 6 6 12 50.0 50.0 57.1 15 9 7 16 56.3 43.8 47.6

Total 36 22 58 62.1 37.9 47.9

ALL SITES 168 106 274 61.3 38.7 42.8 page 23

VITAL STATISTICS PROJECT INAFGHANISTAN 1990

TABLE 9. MALE TO FEMALE BIRTH RATIOS BY SITE ****** * * * * * * * * * * * * * * * * * * * * * * * ** * * * * **

Site Male Female Ratio Births Births

Chak 61 40 1.52 Saroza 71 44 1.61 Giru 36 22 1.64

Total 168 106 1.58 page 24

VITAL STATISTICS PROJECT IN AFGHANISTAN 1990

TABLE 10. TIME TREND* IN BIRTH RATES ** ******** * * * * * * * * * * * * * * * * * * * * * * * ** * * * * **

(All Sites)

June 22 - July 22 - Aug 22 - Sep 22 - Oct 22 - July 21 Aug 21 Sep 21 Oct 21 Nov 21

60.0 35.6 30.9 49.7 35.6

*Since all sites did not start on the same date, statistics only for the five months during which all sites were collecting data are included.

* *Per 1000 pop /year. page 25 VITAL STATISTICS PROJECT IN AFGHANISTAN 1990

TABLE 11. BIRTH AND MORTALITY RATES, POPULATION GROWTH RATE AND DOUBLING TIMEBY SITE ***************** * * * * * * * * * ** * * * * * * * * * * * * ** * * * * **

Site Birth Mortality Pop.Growth Pop.Doubling Rate Rate Rate* Time (yrs) **

Chak 34.0 15.8 1.7 41.0

Sarosa 51.9 32.1 2.0 35.0

Giru 47.9 14.0 3.4 20.0

All site 42.8 21.1 2.2 32.0

* per 100 population per year.

** population doubling time (PDI) was calculated using the following equation: PDI = 70 /pop.growth rate % page 26 VITAL STATISTICS PROJECT IN AFGHANISTAN 1990

TABLE 12. ASSOCIATION OF EDUCATION WITH POPULATION GROWTH RATE ********** * * * * * * * * * * * * * * * * * * * * * * * ** * * * * **

Site Students Pop.Growth /1000 pop* Rate **

Chak, Wardak 176 1.7

Saroza, Paktika 158 2.0

GiruDeecy, Ghazni 17 3.4

All Sites 140 2.2

* it students per site population. Note: Only Chak had female students.

** per 100 population per year. Graph 1. Time Trendin MortalityRates

20

17 .

June 22 - July 22 - Aug 22 - Sep 22 - Oct 22 - Month of Deoth